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Computers, Materials & Continua

ISSN: 1546-2218 (Print)

ISSN: 1546-2226 (Online)

2018

Vol. 55, No. 1

Ruohan Meng, Steven G. Rice, Jin Wang and Xingming Sun: A Fusion Steganographic Algorithm Based on Faster R-CNN, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 001-016 , 2018

Keywords

Faster R-CNN, fusion steganography, object detection, CNNs, information hiding.

Abstract

The aim of information hiding is to embed the secret message in a normal cover media such as image, video, voice or text, and then the secret message is transmitted through the transmission of the cover media. The secret message should not be damaged on the process of the cover media. In order to ensure the invisibility of secret message, complex texture objects should be chosen for embedding information. In this paper, an approach which corresponds multiple steganographic algorithms to complex texture objects was presented for hiding secret message. Firstly, complex texture regions are selected based on a kind of objects detection algorithm. Secondly, three different steganographic methods were used to hide secret message into the selected block region. Experimental results show that the approach enhances the security and robustness.

Jinhua Cui, Yuanyuan Zhang, Zhiping Cai, Anfeng Liu and Yangyang Li: Securing Display Path for Security-Sensitive Applications on Mobile Devices, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 017-035 , 2018

Keywords

Mobile device, secure display, virtualization, trusted computing base, display path, trust anchor.

Abstract

While smart devices based on ARM processor bring us a lot of convenience, they also become an attractive target of cyber-attacks. The threat is exaggerated as commodity OSes usually have a large code base and suffer from various software vulnerabilities. Nowadays, adversaries prefer to steal sensitive data by leaking the content of display output by a security-sensitive application. A promising solution is to exploit the hardware visualization extensions provided by modern ARM processors to construct a secure display path between the applications and the display device. In this work, we present a scheme named SecDisplay for trusted display service, it protects sensitive data displayed from being stolen or tampered surreptitiously by a compromised OS. The TCB of SecDisplay mainly consists of a tiny hypervisor and a super light-weight rendering painter, and has only ~1400 lines of code. We implemented a prototype of SecDisplay and evaluated its performance overhead. The results show that SecDisplay only incurs an average drop of 3.4%.

Yuling Liu, Hua Peng and Jie Wang: Verifiable Diversity Ranking Search Over Encrypted Outsourced Data, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 037-057 , 2018

Keywords

Cloud security, diversity ranking, relevance, searchable encryption, verifiable search.

Abstract

Data outsourcing has become an important application of cloud computing. Driven by the growing security demands of data outsourcing applications, sensitive data have to be encrypted before outsourcing. Therefore, how to properly encrypt data in a way that the encrypted and remotely stored data can still be queried has become a challenging issue. Searchable encryption scheme is proposed to allow users to search over encrypted data. However, most searchable encryption schemes do not consider search result diversification, resulting in information redundancy. In this paper, a verifiable diversity ranking search scheme over encrypted outsourced data is proposed while preserving privacy in cloud computing, which also supports search results verification. The goal is that the ranked documents concerning diversification instead of reading relevant documents that only deliver redundant information. Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is effective for the diversification of documents and verification.

Qiankai Nie, Xuba Xu, Bingwen Feng and Leo Yu Zhang: Defining Embedding Distortion for Intra Prediction Mode-Based Video Steganography, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp.059-070 , 2018

Keywords

Steganography, intra prediction mode, embedding distortion, video.

Abstract

In this paper, an effective intra prediction mode-based video strganography is proposed. Secret messages are embedded during the intra prediction of the video encoding without causing large embedding impact. The influence on the sum of absolute difference (SAD) in intra prediction modes (IPMs) reversion phenomenon is sharp when modifying IPMs. It inspires us to take the SAD prediction deviation (SPD) to define the distortion function. What is more, the mapping rule between IPMs and the codewords is introduced to further reduce the SPD values of each intra block. Syndrome-trellis code (STC) is used as the practical embedding implementation. Experimental results demonstrate that our proposed steganographic scheme presents high undetectability compared with existing IPMs-based steganographic approaches. It also outperforms these schemes on stego video quality.

Wenyan Liu, Xiangyang Luo, Yimin Liu, Jianqiang Liu, Minghao Liu and Yun Q. Shi: Localization Algorithm of Indoor Wi-Fi Access Points Based on Signal Strength Relative Relationship and Region Division, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 071-093 , 2018

Keywords

Wi-Fi access points, indoor localization, RSS, signal strength relative relationship, region division.

Abstract

Precise localization techniques for indoor Wi-Fi access points (APs) have important application in the security inspection. However, due to the interference of environment factors such as multipath propagation and NLOS (Non-Line-of-Sight), the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS (Received Signal Strength) is difficult to accurately measure. Therefore, the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper. The algorithm hierarchically divide the room where the target Wi-Fi AP is located, on the region division line, a modified signal collection device is used to measure RSS in two directions of each reference point. All RSS values are compared and the region where the RSS value has the relative largest signal strength is located as next candidate region. The location coordinate of the target Wi-Fi AP is obtained when the localization region of the target Wi-Fi AP is successively approximated until the candidate region is smaller than the accuracy threshold. There are 360 experiments carried out in this paper with 8 types of Wi-Fi APs including fixed APs and portable APs. The experimental results show that the average localization error of the proposed localization algorithm is 0.30 meters, and the minimum localization error is 0.16 meters, which is significantly higher than the localization accuracy of the existing typical indoor Wi-Fi access point localization methods.

Jieren Cheng, Ruomeng Xu, Xiangyan Tang, Victor S. Sheng and Canting Cai: An Abnormal Network Flow Feature Sequence Prediction Approach for DDoS Attacks Detection in Big Data Environment, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 095-119 , 2018

Keywords

DDoS attack, time series prediction, ARIMA, big data.

Abstract

Distributed denial-of-service (DDoS) is a rapidly growing problem with the fast development of the Internet. There are multitude DDoS detection approaches, however, three major problems about DDoS attack detection appear in the big data environment. Firstly, to shorten the respond time of the DDoS attack detector; secondly, to reduce the required compute resources; lastly, to achieve a high detection rate with low false alarm rate. In the paper, we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and solve aforementioned problems. We define a network flow abnormal index as PDRA with the percentage of old IP addresses, the increment of the new IP addresses, the ratio of new IP addresses to the old IP addresses and average accessing rate of each new IP address. We design an IP address database using sequential storage model which has a constant time complexity. The autoregressive integrated moving average (ARIMA) trending prediction module will be started if and only if the number of continuous PDRA sequence value, which all exceed an PDRA abnormal threshold (PAT), reaches a certain preset threshold. And then calculate the probability that is the percentage of forecasting PDRA sequence value which exceed the PAT. Finally we identify the DDoS attack based on the abnormal probability of the forecasting PDRA sequence. Both theorem and experiment show that the method we proposed can effectively reduce the compute resources consumption, identify DDoS attack at its initial stage with higher detection rate and lower false alarm rate.

Daojian Zeng, Yuan Dai, Feng Li, R. Simon Sherratt and Jin Wang: Adversarial Learning for Distant Supervised Relation Extraction, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 121-136 , 2018

Keywords

Relation extraction, generative adversarial networks, distant supervision, piecewise convolutional neural networks, pair-wise ranking loss.

Abstract

Recently, many researchers have concentrated on using neural networks to learn features for Distant Supervised Relation Extraction (DSRE). These approaches generally use a softmax classifier with cross-entropy loss, which inevitably brings the noise of artificial class NA into classification process. To address the shortcoming, the classifier with ranking loss is employed to DSRE. Uniformly randomly selecting a relation or heuristically selecting the highest score among all incorrect relations are two common methods for generating a negative class in the ranking loss function. However, the majority of the generated negative class can be easily discriminated from positive class and will contribute little towards the training. Inspired by Generative Adversarial Networks (GANs), we use a neural network as the negative class generator to assist the training of our desired model, which acts as the discriminator in GANs. Through the alternating optimization of generator and discriminator, the generator is learning to produce more and more discriminable negative classes and the discriminator has to become better as well. This framework is independent of the concrete form of generator and discriminator. In this paper, we use a two layers fully-connected neural network as the generator and the Piecewise Convolutional Neural Networks (PCNNs) as the discriminator. Experiment results show that our proposed GAN-based method is effective and performs better than state-of-the-art methods.

Donghui Li, Guozheng Zhang, Zeng Xu, Yong Lan, Yongdong Shi, Zhiyao Liang and Haiwen Chen: Modelling the Roles of Cewebrity Trust and Platform Trust in Consumers’Propensity of Live-Streaming: An Extended TAM Method, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp.137-150 , 2018

Keywords

Live streaming, extended TAM approach, consumers’ propensity, cewebrity trust, platform trust.

Abstract

Live streaming is a booming industry in China, involving an increasing number of Internet users. Previous studies show that trust is a cornerstone to develop e-commerce. Trust in the streaming industry is different from that of other e-commerce areas. There are two major dimensions of trust in the live streaming context: platform trust and cewebrity trust, which are both important for customers to adopt and reuse a specific live streaming service. We collected questionnaire data from 520 participates who have used live streaming services in China. We model the collected data and identified factors that can influence users’ propensity by an extended technology acceptance model (TAM) method. According to our analysis, both cewebrity trust and platform trust will greatly influence users’ intention to reuse a certain platform. Moreover, results also indicate that cewebrity trust is far more important than platform trust. These findings can lead to several management strategies to improve the adherence of users to streaming platforms.

Qili Zhou, Yongbin Qiu, Li Li, Jianfeng Lu, Wenqiang Yuan, Xiaoqing Feng and Xiaoyang Mao: Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 151-163 , 2018

Keywords

Steganography, texture synthesis, LSB, seeded region growing algorithm, information segmentation.

Abstract

Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture. We use seeded region growing algorithm to ensure texture’s similar local appearance. Secondly, the size and capacity of image can be decreased by introducing the information segmentation, because the capacity of the secret information is proportional to the size of the synthetic texture. Thirdly, enhanced security is also a contribution in this research, because our method does not need to transmit parameters for secret information extraction. LSB is used to embed these parameters in the synthetic texture.

Wenyi Yin, Xiangyun Zhang, Bumaliya Abulimiti, Yuzhu Liu, Yihui Yan, Fengbin Zhou and Feng Jin: Electronic Structure and Physical Characteristics of Dioxin Under External Electric Field, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp. 165-176 , 2018

Keywords

Dioxin, IR spectrum, UV-vis spectrum, electric field, density functional theory, excited states.

Abstract

Dioxin is a highly toxic and caustic substance, which widely existed in the atmosphere, soil and water with tiny particles. Dioxin pollution has become a major problem that concerns the survival of mankind, which must be strictly controlled. The bond length, bond angle, energy, dipole moment, orbital energy level distribution of dioxin under the external field are investigated using DFT (density functional theory) on basis set level of B3LYP/6-31G (d, p). The results indicate that with the increase of the electric field, the length of one Carbon-Oxygen bond increases while another Carbon-Oxygen bond decreases. The energy gradually decreases with the electric field, while the change of the dipole moment has an opposite trend. In the infrared spectra, the vibration frequency decreases with the electric field increasing and shows an obvious red shift. Moreover, the ultraviolet-visible absorption spectra under different electric fields are analyzed with TD-DFT (time-dependent density functional theory) method. The wavelength of the strongest absorption peak increases and occurs red shift with the increase of the electric field. All the above results can provide reference for further research on the properties of dioxin under different external electric field.

Kemei Pei, Yueben Dong and Lei Chen: Investigation of the Short-Time Photodissociation Dynamics of Furfural in S2 State by Resonance Raman and Quantum Chemistry Calculations, CMC: Computers, Materials & Continua, Vol. 55, No. 1, pp.189-200 , 2018

Keywords

Furfural, resonance Raman, quantum chemistry calculation, excited state structural dynamics.

Abstract

Raman (resonance Raman, FT-Raman), IR and UV-visible spectroscopy and quantum chemistry calculations were used to investigate the photodissociation dynamics of furfural in S2 state. The resonance Raman(RR) spectra indicate that the photorelaxation dynamics for the S0→S2 excited state is predominantly along nine motions: C=O stretch ν5 (1667 cm-1), ring C=C antisymmetric stretch ν6 (1570 cm-1), ring C=C symmetric stretch ν7 (1472 cm-1), C2-O6-C5 symmetric stretch/C1-H8 rock in plane ν8 (1389 cm-1), C3-C4 stretch/ C1-H8 rock in plane ν9 (1370 cm-1), C5-O6 stretch in plane ν12 (1154 cm-1), ring breath ν13 (1077 cm-1), C3-C4 stretch ν14 (1020 cm-1), C3-C2-O6 symmetric stretch ν16 (928 cm-1 ). Stable structures of S0, S1, S2, T1 and T2 states with Cs point group were optimized at CASSCF method in Franck-Condon region there are S2/S1 conical intersection was found by state average method and RR spectra.

Vol. 55, No. 2

Junjia Chen, Wei Lu, Yuileong Yeung, Yingjie Xue, Xianjin Liu, Cong Lin and Yue Zhang: Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix, CMC: Computers, Materials & Continua, Vol.055,No.2,pp.201-211,2018

Keywords

Binary image steganalysis, informational security, embedding distortion, distortion level map, co-occurrence matrix, support vector machine.

Abstract

In recent years, binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security. In most state-of-the-art binary image steganographic schemes, they always find out the flippable pixels to minimize the embedding distortions. For this reason, the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain. However, the distortion maps can be calculated for cover and stego images and the difference between them is significant. In this paper, a novel binary image steganalytic scheme is proposed, which is based on distortion level co-occurrence matrix. The proposed scheme first generates the corresponding distortion maps for cover and stego images. Then the co-occurrence matrix is constructed on the distortion level maps to represent the features of cover and stego images. Finally, support vector machine, based on the gaussian kernel, is used to classify the features. Compared with the prior steganalytic methods, experimental results demonstrate that the proposed scheme can effectively detect stego images.

Zeyu Xiong, Qiangqiang Shen, Yijie Wang and Chenyang Zhu: Paragraph Vector Representation Based on Word to Vector and CNN Learning, CMC: Computers, Materials & Continua, Vol.055, No.2, pp. 213-227, 2018

Keywords

Distributed word vector, distributed paragraph vector, CNNs, CBOW, deep learning.

Abstract

Document processing in natural language includes retrieval, sentiment analysis, theme extraction, etc. Classical methods for handling these tasks are based on models of probability, semantics and networks for machine learning. The probability model is loss of semantic information in essential, and it influences the processing accuracy. Machine learning approaches include supervised, unsupervised, and semi-supervised approaches, labeled corpora is necessary for semantics model and supervised learning. The method for achieving a reliably labeled corpus is done manually, it is costly and time-consuming because people have to read each document and annotate the label of each document. Recently, the continuous CBOW model is efficient for learning high-quality distributed vector representations, and it can capture a large number of precise syntactic and semantic word relationships, this model can be easily extended to learn paragraph vector, but it is not precise. Towards these problems, this paper is devoted to developing a new model for learning paragraph vector, we combine the CBOW model and CNNs to establish a new deep learning model. Experimental results show that paragraph vector generated by the new model is better than the paragraph vector generated by CBOW model in semantic relativeness and accuracy.

Qi Cui, Suzanne McIntosh and Huiyu Sun: Identifying Materials of Photographic Images and Photorealistic Computer Generated Graphics Based on Deep CNNs, CMC: Computers, Materials & Continua, Vol.055,No.2,pp.229-241,2018

Keywords

Image identification, CNN, DNN, DCNNs, computer generated graphics.

Abstract

Currently, some photorealistic computer graphics are very similar to photographic images. Photorealistic computer generated graphics can be forged as photographic images, causing serious security problems. The aim of this work is to use a deep neural network to detect photographic images (PI) versus computer generated graphics (CG). In existing approaches, image feature classification is computationally intensive and fails to achieve real-time analysis. This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks (DCNNs). Compared with some existing methods, the proposed method achieves real-time forensic tasks by deepening the network structure. Experimental results show that this approach can effectively identify PI and CG with average detection accuracy of 98%.

Ya Tu, Yun Lin, Jin Wang and Jeong-Uk Kim: Semi-Supervised Learning with Generative Adversarial Networks on Digital Signal Modulation Classification, CMC: Computers, Materials & Continua, Vol.55,No.2,pp.243-254,2018

Keywords

Deep Learning, automated modulation classification, semi-supervised learning, gen-erative adversarial networks.

Abstract

Deep Learning (DL) is such a powerful tool that we have seen tremendous success in areas such as Computer Vision, Speech Recognition, and Natural Language Pro-cessing. Since Automated Modulation Classification (AMC) is an important part in Cognitive Radio Networks, we try to explore its potential in solving signal modula-tion recognition problem. It cannot be overlooked that DL model is a complex mod-el, thus making them prone to over-fitting. DL model requires many training data to combat with over-fitting, but adding high quality labels to training data manually is not always cheap and accessible, especially in real-time system, which may counter unprecedented data in dataset. Semi-supervised Learning is a way to exploit unla-beled data effectively to reduce over-fitting in DL. In this paper, we extend Genera-tive Adversarial Networks (GANs) to the semi-supervised learning will show it is a method can be used to create a more data-efficient classifier.

Yangyang Wang, Rongrong Ni, Yao Zhao and Min Xian: Watermark Embedding for Direct Binary Searched Halftone Images by Adopting Visual Cryptography, CMC: Computers, Materials & Continua, Vol.55,No.2,pp.255-265,2018

Keywords

Data hiding, halftone, direct binary search, visual watermark.

Abstract

In this paper, two methods are proposed to embed visual watermark into direct binary search (DBS) halftone images, which are called Adjusted Direct Binary Search (ADBS) and Dual Adjusted Direct Binary Search (DADBS). DADBS is an improved version of ADBS. By using the proposed methods, the visual watermark will be embedded into two halftone images separately, thus, the watermark can be revealed when these two halftone images are overlaid. Experimental results show that both methods can achieve excellent image visual quality and decoded visual patterns.

Xian Tang, Ziyang Chen, Haiyan Zhang, Xiang Liu, Yunyu Shi and Asad Shahzadi: An Optimized Labeling Scheme for Reachability Queries, CMC: Computers, Materials & Continua, Vol.055,No.2,pp.267-283,2018

Keywords

DAG, computing, detection, reachability queries processing.

Abstract

Answering reachability queries is one of the fundamental graph operations. Existing approaches either accelerate index construction by constructing an index that covers only partial reachability relationship, which may result in performing cost traversing operation when answering a query; or accelerate query answering by constructing an index covering the complete reachability relationship, which may be inefficient due to comparing the complete node labels. We propose a novel labeling scheme, which covers the complete reachability relationship, to accelerate reachability queries processing. The idea is to decompose the given directed acyclic graph (DAG) G into two subgraphs, G1 and G2. For G1, we propose to use topological labels consisting of two integers to answer all reachability queries. For G2, we construct 2-hop labels as existing methods do to answer queries that cannot be answered by topological labels. The benefits of our method lie in two aspects. On one hand, our method does not need to perform the cost traversing operation when answering queries. On the other hand, our method can quickly answer most queries in constant time without comparing the whole node labels. We confirm the efficiency of our approaches by extensive experimental studies using 20 real datasets.

Wenjia Xu, Shijun Xiang and Vasily Sachnev: A Cryptograph Domain Image Retrieval Method Based on Paillier Homomorphic Block Encryption, CMC: Computers, Materials & Continua, Vol.055,No.2,pp.285-295,2018

Keywords

Paillier cryptosystem, homomorphic encryption, image retrieval, feature extraction, difference histogram.

Abstract

With the rapid development of information network, the computing resources and storage capacity of ordinary users cannot meet their needs of data processing. The emergence of cloud computing solves this problem but brings data security problems. How to manage and retrieve ciphertext data effectively becomes a challenging problem. To these problems, a new image retrieval method in ciphertext domain by block image encrypting based on Paillier homomophic cryptosystem is proposed in this paper. This can be described as follows: According to the Paillier encryption technology, the image owner encrypts the original image in blocks, obtains the image in ciphertext domain, then passes it to the third party server. The server calculates the difference histogram of the image in ciphertext domain according to the public key and establishes the index database. The user passes the retrieved image to the server. The server computes the differential histogram of the retrieved image by public key. Then, compares the similarity of it with the histogram in index database and selects larger similarity images in ciphertext and send them to the user. The user obtains the target image with the private key. The experimental results show that the method is feasible and simple.

Xiaorui Zhang, Pengpai Wang, Wei Sun and Norman I. Badler: A Novel Twist Deformation Model of Soft Tissue in Surgery Simulation, CMC: Computers, Materials & Continua, Vol.55,No.2,pp.297-319,2018

Keywords

Kriging interpolation method, membrane analogy, twist deformation, virtual soft tissue, surgery simulation.

Abstract

Real-time performance and accuracy are two most challenging requirements in virtual surgery training. These difficulties limit the promotion of advanced models in virtual surgery, including many geometric and physical models. This paper proposes a physical model of virtual soft tissue, which is a twist model based on the Kriging interpolation and membrane analogy. The proposed model can quickly locate spatial position through Kriging interpolation method and accurately compute the force change on the soft tissue through membrane analogy method. The virtual surgery simulation system is built with a PHANTOM OMNI haptic interaction device to simulate the torsion of virtual stomach and arm, and further verifies the real-time performance and simulation accuracy of the proposed model. The experimental results show that the proposed soft tissue model has high speed and accuracy, realistic deformation, and reliable haptic feedback.

Mingming Wang, Chen Yang and Reza Mousoli: Controlled Cyclic Remote State Preparation of Arbitrary Qubit States, CMC: Computers, Materials & Continua, Vol.55,No.2,pp.321-329,2018

Keywords

Quantum secure communications, remote state preparation, cyclic communications, asymmetric communications, bidirectional communications, quantum control.

Abstract

Quantum secure communications could securely transmit quantum information by using quantum resource. Recently, novel applications such as bidirectional and asymmetric quantum protocols have been developed. In this paper, we propose a new method for generating entanglement which is highly useful for multiparty quantum communications such as teleportation and Remote State Preparation (RSP). As one of its applications, we propose a new type of quantum secure communications, i.e. cyclic RSP protocols. Starting from a four-party controlled cyclic RSP protocol of one-qubit states, we show that this cyclic protocol can be generalized to a multiparty controlled cyclic RSP protocol for preparation of arbitrary qubit states. We point out that previous bidirectional and asymmetric protocols can be regarded as a simpler form of our cyclic RSP protocols.

Zhenjun Tang, Man Ling, Heng Yao, Zhenxing Qian, Xianquan Zhang, Jilian Zhang and Shijie Xu: Robust Image Hashing via Random Gabor Filtering and DWT, CMC: Computers, Materials & Continua, Vol.55,No.2,pp.331-344,2018

Keywords

Image hashing, Gabor filtering, chaotic map, skew tent map, discrete wavelet transform.

Abstract

Image hashing is a useful multimedia technology for many applications, such as image authentication, image retrieval, image copy detection and image forensics. In this paper, we propose a robust image hashing based on random Gabor filtering and discrete wavelet transform (DWT). Specifically, robust and secure image features are first extracted from the normalized image by Gabor filtering and a chaotic map called Skew tent map, and then are compressed via a single-level 2-D DWT. Image hash is finally obtained by concatenating DWT coefficients in the LL sub-band. Many experiments with open image datasets are carried out and the results illustrate that our hashing is robust, discriminative and secure. Receiver operating characteristic (ROC) curve comparisons show that our hashing is better than some popular image hashing algorithms in classification performance between robustness and discrimination.

Ran Wang, Xuegang Yuan, Hongwu Zhang, Jing Zhang and Na Lv: Symmetry Transformations and Exact Solutions of a Generalized Hyperelastic Rod Equation, CMC: Computers, Materials & Continua, Vol.055,No.2,pp.345-357,2018

Keywords

Generalized hyperelastic rod equation, symmetry transformation, Lou’s direct method, exact solution.

Abstract

In this paper, a nonlinear wave equation with variable coefficients is studied, interestingly, this equation can be used to describe the travelling waves propagating along the circular rod composed of a general compressible hyperelastic material with variable cross-sections and variable material densities. With the aid of Lou’s direct method1, the nonlinear wave equation with variable coefficients is reduced and two sets of symmetry transformations and exact solutions of the nonlinear wave equation are obtained. The corresponding numerical examples of exact solutions are presented by using different coefficients. Particularly, while the variable coefficients are taken as some special constants, the nonlinear wave equation with variable coefficients reduces to the one with constant coefficients, which can be used to describe the propagation of the travelling waves in general cylindrical rods composed of generally hyperelastic materials. Using the same method to solve the nonlinear wave equation, the validity and rationality of this method are verified.

Surkay D. Akbarov, Hatam H. Guliyev, Yusif M. Sevdimaliyev and Nazmiye Yahnioglu: The Discrete-Analytical Solution Method for Investigation Dynamics of the Sphere with Inhomogeneous Initial Stresses, CMC: Computers, Materials & Continua, Vol. 55, No. 2, pp. 359-380, 2018

Keywords

Discrete-analytical solution method, initial stress, hollow sphere, natural frequency, dynamical problem.

Abstract

The paper deals with a development of the discrete-analytical method for the solution of the dynamical problems of a hollow sphere with inhomogeneous initial stresses. The examinations are made with respect to the problem on the natural vibration of the hollow sphere the initial stresses in which is caused by internal and external uniformly distributed pressure. The initial stresses in the sphere are determined within the scope of the exact equations of elastostatics. It is assumed that after appearing this static initial stresses the sphere gets a dynamical excitation and mechanical behavior of the sphere caused by this excitation is described with the so-called three-dimensional linearized equations of elastic wave propagation in initially stressed bodies. For the solution of these equations, which have variable coefficients, the discrete analytical solution method is developed and applied. In particular, it is established that the convergence of the numerical results with respect to the number of discretization is very acceptable and applicable for the considered type dynamical problems. Numerical results on the influence of the initial stresses on the values of the natural frequencies of the hollow sphere are also presented and these results are discussed.

Vol. 55, No. 3

Kabir Fardad, Bahman Najafi, Sina Faizollahzadeh Ardabili, Amir Mosavi, Shahaboddin Shamshirband and Timon Rabczuk: Biodegradation of Medicinal Plants Waste in an Anaerobic Digestion Reactor for Biogas Production, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.381-392,2018

Keywords

Biogas, environmental threat, lignocellulose substances, medicinal plants, residual wastes.

Abstract

Glycyrrhiza glabra, Mint, Cuminum cyminum, Lavender and Arctium medicinal are considered as edible plants with therapeutic properties and as medicinal plants in Iran. After extraction process of medicinal plants, residual wastes are not suitable for animal feed and are considered as waste and as an environmental threat. At present there is no proper management of waste of these plants and they are burned or buried. The present study discusses the possibility of biogas production from Glycyrrhiza Glabra Waste (GGW), Mentha Waste (MW), Cuminum Cyminum Waste (CCW), Lavender Waste (LW) and Arctium Waste (AW). 250 g of these plants with TS of 10% were digested in the batch type reactors at the temperature of 35°C. The highest biogas production rate were observed to be 13611 mL and 13471 mL for CCW and GGW (10% TS), respectively. While the maximum methane was related to GGW with a value of 9041 mL (10% TS). The highest specific biogas and methane production were related to CCW with value of 247.4 mL.(g.VS)-1 and 65.1 mL.(g.VS)-1, respectively. As an important result, it was obvious that in lignocellulose materials, it cannot be concluded that the materials with similar ratio of C/N has the similar digestion and biogas production ability.

Qijun Wu, Limin Han, Lingxuan Wang and Xun Gong: Molecular Structure and Electronic Spectra of CoS under the Radiation Fields, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.393-403,2018

Keywords

CoS, density functional theory, molecular structure, radiation field, spectra.

Abstract

We optimized the ground-state stable configuration of CoS molecule in different external radiation fields (0-0.04 atomic units (a.u.)) at the basis set level of 6-311G++ (d, p) using the B3LYP density functional theory. On this basis, the molecular structure, total energy, energy gap, and the intensities of infrared ray (IR) spectra, Raman spectra, and ultraviolet-visible (UV-Vis) absorption spectra of CoS molecule were computed using the same method. The results showed that the molecular structure changed greatly under the effect of the external radiation fields and had significant dependency on the radiation fields. The total energy of CoS molecule grew slightly at first and then significantly decreased in a monotonous manner. The bond length, dipole moment, and energy gap of the molecule all reduced at first and then increased, with the turning point all at F=0.025 a.u. of the radiation field. The absorption peak of IR spectra and Raman optical activity both had maximums at F=0.03 a.u. with significant red shift. In the external radiation field of F=0.030 a.u., the absorption wavelength of the UV-Vis absorption spectra showed large blue shift, and a strong absorption peak was observed.

Xuewen Zhang, Zhonghao Li, Gongshen Liu, Jiajun Xu, Tiankai Xie and Jan Pan Nees: A Spark Scheduling Strategy for Heterogeneous Cluster, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.405-417,2018

Keywords

Spark, optimize scheduling, stratifying algorithm, performance optimization.

Abstract

As a main distributed computing system, Spark has been used to solve problems with more and more complex tasks. However, the native scheduling strategy of Spark assumes it works on a homogenized cluster, which is not so effective when it comes to heterogeneous cluster. The aim of this study is looking for a more effective strategy to schedule tasks and adding it to the source code of Spark. After investigating Spark scheduling principles and mechanisms, we developed a stratifying algorithm and a node scheduling algorithm is proposed in this paper to optimize the native scheduling strategy of Spark. In this new strategy, the static level of nodes is calculated, the dynamic factors such as the length of running tasks, and CPU usage of work nodes are considered comprehensively. And through a series of comparative experiments in alienation cluster, the new strategy costs less running time and lower CPU usage rate than the original Spark strategy, which verifies that the new schedule strategy is more effective one.

Shengqun Fang, Zhiping Cai, Wencheng Sun, Anfeng Liu, Fang Liu, Zhiyao Liang and Guoyan Wang: Feature Selection Method Based on Class Discriminative Degree for Intelligent Medical Diagnosis, CMC: Computers, Materials & Continua, Vol. 55, No. 3, pp. 419-433, 2018

Keywords

Medical expert system, EMR, multi-label classification, feature selection, class discriminative degree.

Abstract

By using efficient and timely medical diagnostic decision making, clinicians can positively impact the quality and cost of medical care. However, the high similarity of clinical manifestations between diseases and the limitation of clinicians’ knowledge both bring much difficulty to decision making in diagnosis. Therefore, building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain. In this paper, we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease categories, and compare this method with the traditional medical expert system to verify the performance. To select the best subset of patient features, we propose a feature selection method based on the composition and distribution of symptoms in electronic medical records and compare it with the traditional feature selection methods such as chi-square test. We evaluate the feature selection methods and diagnostic models from two aspects, false negative rate (FNR) and accuracy. Extensive experiments have conducted on a real-world Chinese electronic medical record database. The evaluation results demonstrate that our proposed feature selection method can improve the accuracy and reduce the FNR compare to the traditional feature selection methods, and the multi-label classification framework have better accuracy and lower FNR than the traditional expert system.

Jixin Liu, Ning Sun, Xiaofei Li, Guang Han, Haigen Yang and Quansen Sun: Rare Bird Sparse Recognition via Part-Based Gist Feature Fusion and Regularized Intraclass Dictionary Learning, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.435-446,2018

Keywords

Rare bird, sparse recognition, part detection, gist feature fusion, regularized intraclass dictionary learning.

Abstract

Rare bird has long been considered an important in the field of airport security, biological conservation, environmental monitoring, and so on. With the development and popularization of IOT-based video surveillance, all day and weather unattended bird monitoring becomes possible. However, the current mainstream bird recognition methods are mostly based on deep learning. These will be appropriate for big data applications, but the training sample size for rare bird is usually very short. Therefore, this paper presents a new sparse recognition model via improved part detection and our previous dictionary learning. There are two achievements in our work: (1) after the part localization with selective search, the gist feature of all bird image parts will be fused as data description; (2) the fused gist feature needs to be learned through our proposed intraclass dictionary learning with regularized K-singular value decomposition. According to above two innovations, the rare bird sparse recognition will be implemented by solving one l1-norm optimization. In the experiment with Caltech-UCSD Birds-200-2011 dataset, results show the proposed method can have better recognition performance than other SR methods for rare bird task with small sample size.

Ming Wan, Jiangyuan Yao, Yuan Jing and Xi Jin: Event-Based Anomaly Detection for Non-Public Industrial Communication Protocols in SDN-Based Control Systems, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.447-463,2018

Keywords

Event sequence, anomaly detection, non-public industrial communication protocols, SDN.

Abstract

As the main communication mediums in industrial control networks, industrial communication protocols are always vulnerable to extreme exploitations, and it is very difficult to take protective measures due to their serious privacy. Based on the SDN (Software Defined Network) technology, this paper proposes a novel event-based anomaly detection approach to identify misbehaviors using non-public industrial communication protocols, and this approach can be installed in SDN switches as a security software appliance in SDN-based control systems. Furthermore, aiming at the unknown protocol specification and message format, this approach first restructures the industrial communication sessions and merges the payloads from industrial communication packets. After that, the feature selection and event sequence extraction can be carried out by using the N-gram model and K-means algorithm. Based on the obtained event sequences, this approach finally trains an event-based HMM (Hidden Markov Model) to identify aberrant industrial communication behaviors. Experimental results clearly show that the proposed approach has obvious advantages of classification accuracy and detection efficiency.

Meijuan Wang, Jian Wang, Lihong Guo and Lein Harn: Inverted XML Access Control Model Based on Ontology Semantic Dependency, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.465-482,2018

Keywords

Privacy protection, access control, semantic dependence, inverted XML global view.

Abstract

In the era of big data, the conflict between data mining and data privacy protection is increasing day by day. Traditional information security focuses on protecting the security of attribute values without semantic association. The data privacy of big data is mainly reflected in the effective use of data without exposing the user’s sensitive information. Considering the semantic association, reasonable security access for privacy protect is required. Semi-structured and self-descriptive XML (eXtensible Markup Language) has become a common form of data organization for database management in big data environments. Based on the semantic integration nature of XML data, this paper proposes a data access control model for individual users. Through the semantic dependency between data and the integration process from bottom to top, the global visual range of inverted XML structure is realized. Experimental results show that the model effectively protects the privacy and has high access efficiency.

Xintao Duan, Haoxian Song, Chuan Qin and Muhammad Khurram Khan: Coverless Steganography for Digital Images Based on a Generative Model, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.483-493,2018

Keywords

Generative model, coverless image steganography, steganalysis, steganographic capacity, security.

Abstract

In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the transmission of the secret image. This is the first time to propose the coverless image information steganographic scheme based on generative model, compared with the traditional image steganography. The transmitted image is not embedded with any information of the secret image in this method, therefore, can effectively resist steganalysis tools. Experimental results show that our scheme has high capacity, security and reliability.

Yang Du, Zhaoxia Yin and Xinpeng Zhang: Improved Lossless Data Hiding for JPEG Images Based on Histogram Modification, CMC: Computers, Materials & Continua, Vol. 55, No. 3, pp. 495-507, 2018

Keywords

Lossless, data hiding, histogram, VLC, JPEG.

Abstract

This paper proposes a lossless and high payload data hiding scheme for JPEG images by histogram modification. The most in JPEG bitstream consists of a sequence of VLCs (variable length codes) and the appended bits. Each VLC has a corresponding RLV (run/length value) to record the AC/DC coefficients. To achieve lossless data hiding with high payload, we shift the histogram of VLCs and modify the DHT segment to embed data. Since we sort the histogram of VLCs in descending order, the filesize expansion is limited. The paper’s key contribution includes: Lossless data hiding, less filesize expansion in identical pay-load and higher embedding efficiency.

Zhenguo Gao, Shixiong Xia, Yikun Zhang, Rui Yao, Jiaqi Zhao, Qiang Niu and Haifeng Jiang: Real-Time Visual Tracking with Compact Shape and Color Feature, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.509-521,2018

Keywords

Visual tracking, compact feature, colour feature, structural learning.

Abstract

The colour feature is often used in the object tracking. The tracking methods extract the colour features of the object and the background, and distinguish them by a classifier. However, these existing methods simply use the colour information of the target pixels and do not consider the shape feature of the target, so that the description capability of the feature is weak. Moreover, incorporating shape information often leads to large feature dimension, which is not conducive to real-time object tracking. Recently, the emergence of visual tracking methods based on deep learning has also greatly increased the demand for computing resources of the algorithm. In this paper, we propose a real-time visual tracking method with compact shape and colour feature, which forms low dimensional compact shape and colour feature by fusing the shape and colour characteristics of the candidate object region, and reduces the dimensionality of the combined feature through the Hash function. The structural classification function is trained and updated online with dynamic data flow for adapting to the new frames. Further, the classification and prediction of the object are carried out with structured classification function. The experimental results demonstrate that the proposed tracker performs superiorly against several state-of-the-art algorithms on the challenging benchmark dataset OTB-100 and OTB-13.

Lizhi Xiong and Yunqing Shi: On the Privacy-Preserving Outsourcing Scheme of Reversible Data Hiding over Encrypted Image Data in Cloud Computing, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.523-539,2018

Keywords

Cloud data security, re-encryption, reversible data hiding, cloud computing, privacy-preserving.

Abstract

Advanced cloud computing technology provides cost saving and flexibility of services for users. With the explosion of multimedia data, more and more data owners would outsource their personal multimedia data on the cloud. In the meantime, some computationally expensive tasks are also undertaken by cloud servers. However, the outsourced multimedia data and its applications may reveal the data owner’s private information because the data owners lose the control of their data. Recently, this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data. In this paper, two reversible data hiding schemes are proposed for encrypted image data in cloud computing: reversible data hiding by homomorphic encryption and reversible data hiding in encrypted domain. The former is that additional bits are extracted after decryption and the latter is that extracted before decryption. Meanwhile, a combined scheme is also designed. This paper proposes the privacy-preserving outsourcing scheme of reversible data hiding over encrypted image data in cloud computing, which not only ensures multimedia data security without relying on the trustworthiness of cloud servers, but also guarantees that reversible data hiding can be operated over encrypted images at the different stages. Theoretical analysis confirms the correctness of the proposed encryption model and justifies the security of the proposed scheme. The computation cost of the proposed scheme is acceptable and adjusts to different security levels.

Lingyun Xiang, Yan Li, Wei Hao, Peng Yang and Xiaobo Shen: Reversible Natural Language Watermarking Using Synonym Substitution and Arithmetic Coding, CMC: Computers, Materials & Continua, Vol.55,No.3,pp.541-559,2018

Keywords

Arithmetic coding, synonym substitution, lossless compression, reversible watermarking

Abstract

For protecting the copyright of a text and recovering its original content harmlessly, this paper proposes a novel reversible natural language watermarking method that combines arithmetic coding and synonym substitution operations. By analyzing relative frequencies of synonymous words, synonyms employed for carrying payload are quantized into an unbalanced and redundant binary sequence. The quantized binary sequence is compressed by adaptive binary arithmetic coding losslessly to provide a spare for accommodating additional data. Then, the compressed data appended with the watermark are embedded into the cover text via synonym substitutions in an invertible manner. On the receiver side, the watermark and compressed data can be extracted by decoding the values of synonyms in the watermarked text, as a result of which the original context can be perfectly recovered by decompressing the extracted compressed data and substituting the replaced synonyms with their original synonyms. Experimental results demonstrate that the proposed method can extract the watermark successfully and achieve a lossless recovery of the original text. Additionally, it achieves a high embedding capacity.

Vol. 56, No. 1

Zhen Yang, Yongfeng Huang, Xing Li and Wenyu Wang: Efficient Secure Data Provenance Scheme in Multimedia Outsourcing and Sharing, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.1-17,2018

Keywords

Data provenance, asymmetric fingerprint protocol, digital watermarking, multimedia outsourcing.

Abstract

To cope with privacy leakage caused by multimedia outsourcing and sharing, data provenance is used to analyze leaked multimedia and provide reactive accountability. Existing schemes of multimedia provenance are based on watermarking protocols. In an outsourcing scenario, existing schemes face two severe challenges: 1) when data leakage occurs, there exists a probability that data provenance results can be repudiated, in which case data provenance tracking fails; and 2) when outsourced data are shared, data encryption transfer causes key management burden outside the schemes, and privacy leakage threatens users. In this paper, we propose a novel data provenance scheme with an improved LUT-based fingerprinting protocol, which integrates an asymmetric watermarking protocol, robust watermark algorithm and homomorphic encryption and digital signatures to achieve full non-repudiation provenance. We build an in-scheme stream cipher to protect outsourced multimedia data from privacy leakage and complicated key management. Our scheme is also lightweight and easy to deploy. Extensive security and performance analysis compares our scheme with the state of the art. The results show that our scheme has not only better provenance security and data confidentiality but also higher efficiency for multimedia outsourcing, sharing and provenance.

Faguo Wu, Xiao Zhang, Wang Yao, Zhiming Zheng, Lipeng Xiang and Wanpeng Li: An Advanced Quantum-Resistant Signature Scheme for Cloud Based on Eisenstein Ring, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.19-34,2018

Keywords

Signature, quantum-resistant, Eisenstein Ring, ETRUS.

Abstract

Signature, widely used in cloud environment, describes the work as readily identifying its creator. The existing signature schemes in the literature mostly rely on the Hardness assumption which can be easily solved by quantum algorithm. In this paper, we proposed an advanced quantum-resistant signature scheme for Cloud based on Eisenstein Ring (ETRUS) which ensures our signature scheme proceed in a lattice with higher density. We proved that ETRUS highly improve the performance of traditional lattice signature schemes. Moreover, the Norm of polynomials decreases significantly in ETRUS which can effectively reduce the amount of polynomials convolution calculation. Furthermore, storage complexity of ETRUS is smaller than classical ones. Finally, according to all convolution of ETRUS enjoy lower degree polynomials, our scheme appropriately accelerate 56.37% speed without reducing its security level.

Yueyue Li, Zhong Huang, Yugang Ma and Guangjun Wen: acSB: Anti-Collision Selective-Based Broadcast Protocol in CR-AdHocs, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.35-46,2018

Keywords

Broadcast protocol, selective protocol, collision avoidance, distributed data dissemination, cognitive radio ad hoc network.

Abstract

As a fundamental operation in ad hoc networks, broadcast could achieve efficient message propagations. Particularl y in the cognitive radio ad hoc network where unlicensed users have different sets of available channels, broadcasts are carried out on multiple channels. Accordingly, channel selection and collision avoidance are challenging issues to balance the efficiency against the reliability of broadcasting. In this paper, an anti-collision selective broadcast protocol, called acSB, is proposed. A channel selection algorithm based on limited neighbor information is considered to maximize success rates of transmissions once the sender and receiver have the same channel. Moreover, an anti-collision scheme is adopted to avoid simultaneous rebroadcasts. Consequently, the proposed broadcast acSB outperforms other approaches in terms of smaller transmission delay, higher message reach rate and fewer broadcast collisions evaluated by simulations under different scenarios.

Zhiguo Qu, Tiancheng Zhu, Jinwei Wang and Xiaojun Wang: A Novel Quantum Stegonagraphy Based on Brown States, CMC: Computers, Materials & Continua, Vol.56,No.1, pp.47-59,2018

Keywords

Quantum steganography, quantum secure direct communication, entanglement, anti-noise robustness.

Abstract

In this paper, a novel quantum steganography protocol based on Brown entangled states is proposed. The new protocol adopts the CNOT operation to achieve the transmission of secret information by the best use of the characteristics of entangled states. Comparing with the previous quantum steganography algorithms, the new protocol focuses on its anti-noise capability for the phase-flip noise, which proved its good security resisting on quantum noise. Furthermore, the covert communication of secret information in the quantum secure direct communication channel would not affect the normal information transmission process due to the new protocol’s good imperceptibility. If the number of Brown states transmitted in carrier protocol is many enough, the imperceptibility of the secret channel can be further enhanced. In aspect of capacity, the new protocol can further expand its capacity by combining with other quantum steganography protocols. Due to that the proposed protocol does not require the participation of the classic channel when it implements the transmission of secret information, any additional information leakage will not be caused for the new algorithm with good security. The detailed theoretical analysis proves that the new protocol can own good performance on imperceptibility, capacity and security.

Xiaonian Wu, Chuyun Zhang, Runlian Zhang, Yujue Wang and Jinhua Cui: A Distributed Intrusion Detection Model via Nondestructive Partitioning and Balanced Allocation for Big Data, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.61-72,2018

Keywords

Distributed intrusion detection, data allocation, load balancing, data integrity, big data.

Abstract

There are two key issues in distributed intrusion detection system, that is, maintaining load balance of system and protecting data integrity. To address these issues, this paper proposes a new distributed intrusion detection model for big data based on nondestructive partitioning and balanced allocation. A data allocation strategy based on capacity and workload is introduced to achieve local load balance, and a dynamic load adjustment strategy is adopted to maintain global load balance of cluster. Moreover, data integrity is protected by using session reassemble and session partitioning. The simulation results show that the new model enjoys favorable advantages such as good load balance, higher detection rate and detection efficiency.

Hangjun Zhou, Guang Sun, Sha Fu, Wangdong Jiang, Tingting Xie and Danqing Duan: A Distributed LRTCO Algorithm in Large-Scale DVE Multimedia Systems, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.73-89,2018

Keywords

Distributed computing, distributed virtual environment, multimedia system, causality violation, causal order delivery, real time.

Abstract

In the large-scale Distributed Virtual Environment (DVE) multimedia systems, one of key challenges is to distributedly preserve causal order delivery of messages in real time. Most of the existing causal order control approaches with real-time constraints use vector time as causal control information which is closely coupled with system scales. As the scale expands, each message is attached a large amount of control information that introduces too much network transmission overhead to maintain the real-time causal order delivery. In this article, a novel Lightweight Real-Time Causal Order (LRTCO) algorithm is proposed for large-scale DVE multimedia systems. LRTCO predicts and compares the network transmission times of messages so as to select the proper causal control information of which the amount is dynamically adapted to the network latency variations and unconcerned with system scales. The control information in LRTCO is effective to preserve causal order delivery of messages and lightweight to maintain the real-time property of DVE systems. Experimental results demonstrate that LRTCO costs low transmission overhead and communication bandwidth, reduces causal order violations efficiently, and improves the scalability of DVE systems.

Qidi Wu, Yibing Li, Yun Lin and Ruolin Zhou: Weighted Sparse Image Classification Based on Low Rank Representation, CMC: Computers, Materials & Continua, Vol. 56, No. 1, pp. 91-105, 2018

Keywords

Image classification, sparse representation, low-rank representation, numerical optimization.

Abstract

The conventional sparse representation-based image classification usually codes the samples independently, which will ignore the correlation information existed in the data. Hence, if we can explore the correlation information hidden in the data, the classification result will be improved significantly. To this end, in this paper, a novel weighted supervised spare coding method is proposed to address the image classification problem. The proposed method firstly explores the structural information sufficiently hidden in the data based on the low rank representation. And then, it introduced the extracted structural information to a novel weighted sparse representation model to code the samples in a supervised way. Experimental results show that the proposed method is superiority to many conventional image classification methods.

Chuntao Wang, Yang Feng, Tianzheng Li, Hao Xie and Goo-Rak Kwon: A New Encryption-then-Compression Scheme on Gray Images Using the Markov Random Field, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.107-121,2018

Keywords

Encryption-then-compression, compressing encrypted image, Markov random field, compression efficiency, factor graph.

Abstract

Compressing encrypted images remains a challenge. As illustrated in our previous work on compression of encrypted binary images, it is preferable to exploit statistical characteristics at the receiver. Through this line, we characterize statistical correlations between adjacent bitplanes of a gray image with the Markov random field (MRF), represent it with a factor graph, and integrate the constructed MRF factor graph in that for binary image reconstruction, which gives rise to a joint factor graph for gray images reconstruction (JFGIR). By exploiting the JFGIR at the receiver to facilitate the reconstruction of the original bitplanes and deriving theoretically the sum-product algorithm (SPA) adapted to the JFGIR, a novel MRF-based encryption-then-compression (ETC) scheme is thus proposed. After preferable universal parameters of the MRF between adjacent bitplanes are sought via a numerical manner, extensive experimental simulations are then carried out to show that the proposed scheme successfully compresses the first 3 and 4 most significant bitplanes (MSBs) for most test gray images and the others with a large portion of smooth area, respectively. Thus, the proposed scheme achieves significant improvement against the state-of-the-art leveraging the 2-D Markov source model at the receiver and is comparable or somewhat inferior to that using the resolution-progressive strategy in recovery.

Jixian Zhang, Ning Xie, Xuejie Zhang, Kun Yue, Weidong Li and Deepesh Kumar: Machine Learning Based Resource Allocation of Cloud Computing in Auction, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.123-135,2018

Keywords

Cloud computing, resource allocation, machine learning, linear regression, logistic regression.

Abstract

Resource allocation in auctions is a challenging problem for cloud computing. However, the resource allocation problem is NP-hard and cannot be solved in polynomial time. The existing studies mainly use approximate algorithms such as PTAS or heuristic algorithms to determine a feasible solution; however, these algorithms have the disadvantages of low computational efficiency or low allocate accuracy. In this paper, we use the classification of machine learning to model and analyze the multi-dimensional cloud resource allocation problem and propose two resource allocation prediction algorithms based on linear and logistic regressions. By learning a small-scale training set, the prediction model can guarantee that the social welfare, allocation accuracy, and resource utilization in the feasible solution are very close to those of the optimal allocation solution. The experimental results show that the proposed scheme has good effect on resource allocation in cloud computing.

Mengwei Hou, Rong Wei, Tiangang Wang, Yu Cheng and Buyue Qian: Reliable Medical Recommendation Based on Privacy-Preserving Collaborative Filtering, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.137-149,2018

Keywords

Medical recommendation, privacy preserving, neighborhood-based collaborative filtering, differential privacy.

Abstract

Collaborative filtering (CF) methods are widely adopted by existing medical recommendation systems, which can help clinicians perform their work by seeking and recommending appropriate medical advice. However, privacy issue arises in this process as sensitive patient private data are collected by the recommendation server. Recently proposed privacy-preserving collaborative filtering methods, using computation-intensive cryptography techniques or data perturbation techniques are not appropriate in medical online service. The aim of this study is to address the privacy issues in the context of neighborhood-based CF methods by proposing a Privacy Preserving Medical Recommendation (PPMR) algorithm, which can protect patients’ treatment information and demographic information during online recommendation process without compromising recommendation accuracy and efficiency. The proposed algorithm includes two privacy preserving operations: Private Neighbor Selection and Neighborhood-based Differential Privacy Recommendation. Private Neighbor Selection is conducted on the basis of the notion of k-anonymity method, meaning that neighbors are privately selected for the target user according to his/her similarities with others. Neighborhood-based Differential Privacy Recommendation and a differential privacy mechanism are introduced in this operation to enhance the performance of recommendation. Our algorithm is evaluated using the real-world hospital EMRs dataset. Experimental results demonstrate that the proposed method achieves stable recommendation accuracy while providing comprehensive privacy for individual patients.

Yue Zhang, Dengpan Ye, Junjun Gan, Zhenyu Li and Qingfeng Cheng: An Image Steganography Algorithm Based on Quantization Index Modulation Resisting Scaling Attacks and Statistical Detection, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.151-167,2018

Keywords

Image steganography, anti-scaling attack, anti-statistical detection, quantization index modulation.

Abstract

In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method, this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection. For the spatial image, this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain. Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography, and use the minimum distortion coding to realize the embedding of the secret messages. Finally, according to the embedding modification amplitude of secret messages in the new embedded domain, the quantization index modulation algorithm is applied to realize the final embedding of secret messages in the original embedded domain. The experimental results show that the algorithm proposed is robust to the three common interpolation attacks including the nearest neighbor interpolation, the bilinear interpolation and the bicubic interpolation. And the average correct extraction rate of embedded messages increases from 50% to over 93% after 0.5 times-fold scaling attack using the bicubic interpolation method, compared with the classical steganography algorithm S-UNIWARD. Also the algorithm proposed has higher detection resistance than the original watermarking algorithm based on quantization index modulation.

Libardo V. Vanegas-Useche, Magd M. Abdel-Wahab and Graham A. Parker: Determination of the Normal Contact Stiffness and Integration Time Step for the Finite Element Modeling of Bristle-Surface Interaction, CMC: Computers, Materials & Continua, Vol.56,No.1,pp.169-184,2018

Keywords

Brush, street sweeping, finite element modeling, contact mechanics.

Abstract

In finite element modeling of impact, it is necessary to define appropriate values of the normal contact stiffness, Kn, and the Integration Time Step (ITS). Because impacts are usually of very short duration, very small ITSs are required. Moreover, the selection of a suitable value of Kn is a critical issue, as the impact behavior depends dramatically on this parameter. In this work, a number of experimental tests and finite element analyses have been performed in order to obtain an appropriate value of Kn for the interaction between a bristle of a gutter brush for road sweeping and a concrete surface. Furthermore, a suitable ITS is determined. The experiments consist of releasing a steel bristle that is placed vertically at a certain distance from a concrete surface and tracking the impact. Similarly, in the finite element analyses, a beam is modeled in free fall and impacting a surface; contact and target elements are attached to the beam and the surface, respectively. The results of the experiments and the modeling are integrated through the principle of conservation of energy, the principle of linear impulse and momentum, and Newton’s second law. The results demonstrate that, for the case studied, Kn and the impact time tend to be independent of the velocity just before impact and that Kn has a very large variation, as concrete is a composite material with a rough surface. Also, the ratio between the largest height of the bristle after impact and the initial height tends to be constant.

Vol. 56, No. 2

Xuefeng Xi, Victor S. Sheng, Binqi Sun, Lei Wang and Fuyuan Hu: An Empirical Comparison on Multi-Target Regression Learning, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.185-198,2018

Keywords

Multi-target regression, multi-label classification, multi-target stacking.

Abstract

Multi-target regression is concerned with the simultaneous prediction of multiple continuous target variables based on the same set of input variables. It has received relatively small attention from the Machine Learning community. However, multi-target regression exists in many real-world applications. In this paper we conduct extensive experiments to investigate the performance of three representative multi-target regression learning algorithms (i.e. Multi-Target Stacking (MTS), Random Linear Target Combination (RLTC), and Multi-Objective Random Forest (MORF)), comparing the baseline single-target learning. Our experimental results show that all three multi-target regression learning algorithms do improve the performance of the single-target learning. Among them, MTS performs the best, followed by RLTC, followed by MORF. However, the single-target learning sometimes still performs very well, even the best. This analysis sheds the light on multi-target regression learning and indicates that the single-target learning is a competitive baseline for multi-target regression learning on multi-target domains.

Lin Chen, Chunfang Yang, Fenlin Liu, Daofu Gong and Shichang Ding: Automatic Mining of Security-Sensitive Functions from Source Code, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.199-210,2018

Keywords

Code mining, vulnerabilities, static analysis, security-sensitive function, source code.

Abstract

When dealing with the large-scale program, many automatic vulnerability mining techniques encounter such problems as path explosion, state explosion, and low efficiency. Decomposition of large-scale programs based on safety-sensitive functions helps solve the above problems. And manual identification of security-sensitive functions is a tedious task, especially for the large-scale program. This study proposes a method to mine security-sensitive functions the arguments of which need to be checked before they are called. Two argument-checking identification algorithms are proposed based on the analysis of two implementations of argument checking. Based on these algorithms, security-sensitive functions are detected based on the ratio of invocation instances the arguments of which have been protected to the total number of instances. The results of experiments on three well-known open-source projects show that the proposed method can outperform competing methods in the literature.

Wenjie Liu, Zhenyu Chen, Jinsuo Liu, Zhaofeng Su and Lianhua Chi: Full-Blind Delegating Private Quantum Computation, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.211-223,2018

Keywords

Delegating private quantum computation, universal quantum gate set, full-blind, Toffoli gate, circuit optimization.

Abstract

The delegating private quantum computation (DQC) protocol with the universal quantum gate set {X,Z,H,P,R,CNOT}was firstly proposed by Broadbent et al. [Broadbent (2015)], and then Tan et al. [Tan and Zhou (2017)] tried to put forward a half-blind DQC protocol (HDQC) with another universal set {H,P,CNOT,T}. However, the decryption circuit of Toffoli gate (i.e. T) is a little redundant, and Tan et al.’s protocol [Tan and Zhou (2017)] exists the information leak. In addition, both of these two protocols just focus on the blindness of data (i.e. the client’s input and output), but do not consider the blindness of computation (i.e. the delegated quantum operation). For solving these problems, we propose a full-blind DQC protocol (FDQC) with quantum gate set {H,P,CNOT,T}, where the desirable delegated quantum operation, one of {H,P,CNOT,T}, is replaced by a fixed sequence {H,P,CZ,CNOT,T} to make the computation blind, and the decryption circuit of Toffoli gate is also optimized. Analysis shows that our protocol can not only correctly perform any delegated quantum computation, but also holds the characteristics of data blindness and computation blindness.

Taoyun Zhou, Baowang Lian, Siqing Yang, Yi Zhang and Yangyang Liu: Improved GNSS Cooperation Positioning Algorithm for Indoor Localization, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.225-245,2018

Keywords

Indoor localization, GNSS cooperative positioning, extended kalman filtering (EKF), unscented kalman filtering (UKF), particle filtering (PF).

Abstract

For situations such as indoor and underground parking lots in which satellite signals are obstructed, GNSS cooperative positioning can be used to achieve high-precision positioning with the assistance of cooperative nodes. Here we study the cooperative positioning of two static nodes, node 1 is placed on the roof of the building and the satellite observation is ideal, node 2 is placed on the indoor windowsill where the occlusion situation is more serious, we mainly study how to locate node 2 with the assistance of node 1. Firstly, the two cooperative nodes are located with pseudo-range single point positioning, and the positioning performance of cooperative node is analyzed, therefore the information of pseudo-range and position of node 1 is obtained. Secondly, the distance between cooperative nodes is obtained by using the baseline method with double-difference carrier phase. Finally, the cooperative location algorithms are studied. The Extended Kalman Filtering (EKF), Unscented Kalman Filtering (UKF) and Particle Filtering (PF) are used to fuse the pseudo-range, ranging information and location information respectively. Due to the mutual influences among the cooperative nodes in cooperative positioning, the EKF, UKF and PF algorithms are improved by resetting the error covariance matrix of the cooperative nodes at each update time. Experimental results show that after being improved, the influence between the cooperative nodes becomes smaller, and the positioning performance of the nodes is better than before.

Zhifeng Wang, Diqun Yan, Rangding Wang, Li Xiang and Tingting Wu: Speech Resampling Detection Based on Inconsistency of Band Energy, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.247-259,2018

Keywords

Resampling detection, logarithmic ratio, band energy, robustness.

Abstract

Speech resampling is a typical tempering behavior, which is often integrated into various speech forgeries, such as splicing, electronic disguising, quality faking and so on. By analyzing the principle of resampling, we found that, compared with natural speech, the inconsistency between the bandwidth of the resampled speech and its sampling ratio will be caused because the interpolation process in resampling is imperfect. Based on our observation, a new resampling detection algorithm based on the inconsistency of band energy is proposed. First, according to the sampling ratio of the suspected speech, a band-pass Butterworth filter is designed to filter out the residual signal. Then, the logarithmic ratio of band energy is calculated by the suspected speech and the filtered speech. Finally, with the logarithmic ratio, the resampled and original speech can be discriminated. The experimental results show that the proposed algorithm can effectively detect the resampling behavior under various conditions and is robust to MP3 compression.

Yu Yang, Yuwei Chen, Yuling Chen and Wei Bi: A Novel Universal Steganalysis Algorithm Based on the IQM and the SRM, CMC: Computers, Materials & Continua, Vol. 56, No. 2, pp. 261-272, 2018

Keywords

Image steganalysis, IQM, SRM, total variation, universal image steganalysis

Abstract

The state-of-the-art universal steganalysis method, spatial rich model (SRM), and the steganalysis method using image quality metrics (IQM) are both based on image residuals, while they use 34671 and 10 features respectively. This paper proposes a novel steganalysis scheme that combines their advantages in two ways. First, filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods. In addition, a total variant (TV) filter is also used due to its good performance of preserving image edge properties during filtering. Second, due to each type of these filters having own advantages, the multiple filters are used simultaneously and the features extracted from their outputs are combined together. The whole steganalysis procedure is removing steganographic noise using those filters, then measuring the distances between images and their filtered version with the image quality metrics, and last feeding these metrics as features to build a steganalyzer using either an ensemble classifier or a support vector machine. The scheme can work in two modes, the single filter mode using 9 features, and the multi-filter mode using 639 features. We compared the performance of the proposed method, the SRM and the maxSRMd2. The maxSRMd2 is the improved version of the SRM. The simulated results show that the proposed method that worked in the multi-filter mode was about 10% more accurate than the SRM and maxSRMd2 when the data were globally normalized, and had similar performance with the SRM and maxSRMd2 when the data were locally normalized.

Xiaolan Xie, Tianwei Yuan, Xiao Zhou and Xiaochun Cheng: Research on Trust Model in Container-Based Cloud Service, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.273-283,2018

Keywords

Security, cloud service, trust model, container, cooperation.

Abstract

Container virtual technology aims to provide program independence and resource sharing. The container enables flexible cloud service. Compared with traditional virtualization, traditional virtual machines have difficulty in resource and expense requirements. The container technology has the advantages of smaller size, faster migration, lower resource overhead, and higher utilization. Within container-based cloud environment, services can adopt multi-target nodes. This paper reports research results to improve the traditional trust model with consideration of cooperation effects. Cooperation trust means that in a container-based cloud environment, services can be divided into multiple containers for different container nodes. When multiple target nodes work for one service at the same time, these nodes are in a cooperation state. When multi-target nodes cooperate to complete the service, the target nodes evaluate each other. The calculation of cooperation trust evaluation is used to update the degree of comprehensive trust. Experimental simulation results show that the cooperation trust evaluation can help solving the trust problem in the container-based cloud environment and can improve the success rate of following cooperation.

Yuhong Zhang, Qinqin Wang, Yuling Li and Xindong Wu: Sentiment Classification Based on Piecewise Pooling Convolutional Neural Network, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.285-297,2018

Keywords

Sentiment classification, convolutional neural network, piecewise pooling, feature extract.

Abstract

Recently, the effectiveness of neural networks, especially convolutional neural networks, has been validated in the field of natural language processing, in which, sentiment classification for online reviews is an important and challenging task. Existing convolutional neural networks extract important features of sentences without local features or the feature sequence. Thus, these models do not perform well, especially for transition sentences. To this end, we propose a Piecewise Pooling Convolutional Neural Network (PPCNN) for sentiment classification. Firstly, with a sentence presented by word vectors, convolution operation is introduced to obtain the convolution feature map vectors. Secondly, these vectors are segmented according to the positions of transition words in sentences. Thirdly, the most significant feature of each local segment is extracted using max pooling mechanism, and then the different aspects of features can be extracted. Specifically, the relative sequence of these features is preserved. Finally, after processed by the dropout algorithm, the softmax classifier is trained for sentiment classification. Experimental results show that the proposed method PPCNN is effective and superior to other baseline methods, especially for datasets with transition sentences.

Yuyu Chen, Bangxu Yin, Hongjie He, Shu Yan, Fan Chen and Hengming Tai: Reversible Data Hiding in Classification-Scrambling Encrypted-Image Based on Iterative Recovery, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.299-312,2018

Keywords

Reversible data hiding, image encryption, scrambling encryption, iterative recovery.

Abstract

To improve the security and quality of decrypted images, this work proposes a reversible data hiding in encrypted image based on iterative recovery. The encrypted image is firstly generated by the pixel classification scrambling and bit-wise exclusive-OR (XOR), which improves the security of encrypted images. And then, a pixel-type-mark generation method based on block-compression is designed to reduce the extra burden of key management and transfer. At last, an iterative recovery strategy is proposed to optimize the marked decrypted image, which allows the original image to be obtained only using the encryption key. The proposed reversible data hiding scheme in encrypted image is not vulnerable to the ciphertext-only attack due to the fact that the XOR-encrypted pixels are scrambled in the corresponding encrypted image. Experimental results demonstrate that the decrypted images obtained by the proposed method are the same as the original ones, and the maximum embedding rate of proposed method is higher than the previously reported reversible data hiding methods in encrypted image.

Chuanlong Li, Yumeng Jiang and Marta Cheslyar: Embedding Image Through Generated Intermediate Medium Using Deep Convolutional Generative Adversarial Network, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.313-324,2018

Keywords

GAN, CNN, texture synthesis, steganography, watermark, image concealing, information hiding.

Abstract

Deep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which requires the embedded image looks like not being tampered to human vision system and also undetectable to most analyzers. Texture synthesizing has drawn lots of attention in computer vision field and is used for image concealing in steganography and watermark. The traditional methods which use synthesized textures for information hiding mainly select features and mathematic functions by human metrics and usually have a low embedding rate. This paper takes advantage of the generative network and proposes an approach for synthesizing complex texture-like image of arbitrary size using a modified deep convolutional generative adversarial network (DCGAN), and then demonstrates the feasibility of embedding another image inside the generated texture while the difference between the two images is nearly invisible to the human eyes.

A Highly Effective DPA Attack Method Based on Genetic Algorithm

Shuaiwei Zhang, Xiaoyuan Yang, Weidong Zhong and Yujuan Sun:

CMC: Computers, Materials & Continua, Vol.56,No.2,pp.325-338,2018

Keywords

DPA, efficiency, noise, genetic algorithm, fitness function, novel model.

Abstract

As one of the typical method for side channel attack, DPA has become a serious trouble for the security of encryption algorithm implementation. The potential capability of DPA attack induces researchers making a lot of efforts in this area, which significantly improved the attack efficiency of DPA. However, most of these efforts were made based on the hypothesis that the gathered power consumption data from the target device were stable and low noise. If large deviation happens in part of the power consumption data sample, the efficiency of DPA attack will be reduced rapidly. In this work, a highly efficient method for DPA attack is proposed with the inspiration of genetic algorithm. Based on the designed fitness function, power consumption data that is stable and less noisy will be selected and the noisy ones will be eliminated. In this way, not only improves the robustness and efficiency of DPA attack, but also reduces the number of samples needed. With experiments on block cipher algorithms of DES and SM4, 10% and 12.5% of the number of power consumption curves have been reduced in average with the proposed DPAG algorithm compared to original DPA attack respectively. The high efficiency and correctness of the proposed algorithm and novel model are proved by experiments.

Yongli Tang, Huanhuan Lian, Zemao Zhao and Xixi Yan: A Proxy Re-Encryption with Keyword Search Scheme in Cloud Computing, CMC: Computers, Materials & Continua, Vol.56,No.2,pp.339-352,2018

Keywords

Cloud computing, keyword search, proxy re-encryption, provable security.

Abstract

With the widespread use of cloud computing technology, more and more users and enterprises decide to store their data in a cloud server by outsourcing. However, these huge amounts of data may contain personal privacy, business secrets and other sensitive information of the users and enterprises. Thus, at present, how to protect, retrieve, and legally use the sensitive information while preventing illegal accesses are security challenges of data storage in the cloud environment. A new proxy re-encryption with keyword search scheme is proposed in this paper in order to solve the problem of the low retrieval efficiency of the encrypted data in the cloud server. In this scheme, the user data are divided into files, file indexes and the keyword corresponding to the files, which are respectively encrypted to store. The improved scheme does not need to re-encrypt partial file cipher-text as in traditional schemes, but re-encrypt the cipher-text of Keywords corresponding to the files. Therefore the scheme can improve the computational efficiency as well as resist chosen keyword attack. And the scheme is proven to be indistinguishable under Hash Diffie-Hellman assumption. Furthermore, the scheme does not need to use any secure channels, making it more effective in the cloud environment.

Vol. 56, No. 3

Yanzhong Wang and Xiangyu Wu: Investigation in the Effects of Configuration Parameters on the Thermal Behavior of Novel Conical Friction Plate in Continuously Sliding Condition, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.353-363,2018

Keywords

Transmission, wet clutch, conical configuration, surface configuration, thermal behavior.

Abstract

To investigate the effects of configuration parameters and operation condition on the thermal behavior of novel conical friction plate, a three-dimensional finite element model of conical friction plate is established for numerical simulation. The conical surface configuration and friction heat generation of novel conical friction surfaces are discussed. The results indicate that the thermal behavior of the conical friction plate during continuously sliding period is influenced by the conical surface configuration. Maximum temperature occurs in the conical friction plate with cone angle of 24°. The maximum temperature value of friction plate is increased 7.4°C, when cone depth increases from 3 mm to 4 mm. Thermal behavior investigation should be carried out when optimize conical surface configuration

Bo Xiao, Zhen Wang, Qi Liu,and Xiaodong Liu: SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.365-379,2018

Keywords

Big data, outlier detection, SMK-means, Mini Batch K-means, simulated annealing

Abstract

In recent years, the rapid development of big data technology has also been favored by more and more scholars. Massive data storage and calculation problems have also been solved. At the same time, outlier detection problems in mass data have also come along with it. Therefore, more research work has been devoted to the problem of outlier detection in big data. However, the existing available methods have high computation time, the improved algorithm of outlier detection is presented, which has higher performance to detect outlier. In this paper, an improved algorithm is proposed. The SMK-means is a fusion algorithm which is achieved by Mini Batch K-means based on simulated annealing algorithm for anomalous detection of massive household electricity data, which can give the number of clusters and reduce the number of iterations and improve the accuracy of clustering. In this paper, several experiments are performed to compare and analyze multiple performances of the algorithm. Through analysis, we know that the proposed algorithm is superior to the existing algorithms

Hongbin Zhang, Yuzi Yi, Junshe Wang, Ning Cao and Qiang Duan: Network Security Situation Awareness Framework based on Threat Intelligence, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.381-399,2018

Keywords

Situation awareness, stochastic game, cloud computing, virtual machine

Abstract

Network security situation awareness is an important foundation for network security management, which presents the target system security status by analyzing existing or potential cyber threats in the target system. In network offense and defense, the network security state of the target system will be affected by both offensive and defensive strategies. According to this feature, this paper proposes a network security situation awareness method using stochastic game in cloud computing environment, uses the utility of both sides of the game to quantify the network security situation value. This method analyzes the nodes based on the network security state of the target virtual machine and uses the virtual machine introspection mechanism to obtain the impact of network attacks on the target virtual machine, then dynamically evaluates the network security situation of the cloud environment based on the game process of both attack and defense. In attack prediction, cyber threat intelligence is used as an important basis for potential threat analysis. Cyber threat intelligence that is applicable to the current security state is screened through the system hierarchy fuzzy optimization method, and the potential threat of the target system is analyzed using the cyber threat intelligence obtained through screening. If there is no applicable cyber threat intelligence, using the Nash equilibrium to make predictions for the attack behavior. The experimental results show that the network security situation awareness method proposed in this paper can accurately reflect the changes in the network security situation and make predictions on the attack behavior.

En Zhang, Xintao Duan, Siuming Yiu, Junbin Fang, Zoe L. Jiang, Tsz HonYuen and Jie Peng: Server-Aided Multi-Secret Sharing Scheme for Weak Computational Devices, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.401-414,2018

Keywords

Secret sharing, server-aided, non-interactive, fairness

Abstract

In the setting of (t, n) threshold secret sharing, at least t parties can reconstruct the secret, and fewer than t parties learn nothing about the secret. However, to achieve fairness, the existing secret sharing schemes either assume a trusted party exists or require running multi-round, which is not practical in a real application. In addition, the cost of verification grows dramatically with the number of participants and the communication complexity is O(t), if there is not a trusted combiner in the reconstruction phase. In this work, we propose a fair server-aided multi-secret sharing scheme for weak computational devices. The malicious behavior of clients or server providers in the scheme can be verified, and the server provider learns nothing about the secret shadows and the secrets. Unlike other secret sharing schemes, our scheme does not require interaction among users and can work in asynchronous mode, which is suitable for mobile networks or cloud computing environments since weak computational mobile devices are not always online. Moreover, in the scheme, the secret shadow is reusable, and expensive computation such as reconstruction computation and homomorphic verification computation can be outsourced to the server provider, and the users only require a small amount of computation

Suzhen Wang, Yanpiao Zhang, Lu Zhang, Ning Cao,and Chaoyi Pang: An Improved Memory Cache Management Study Based on Spark, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.415-431,2018

Keywords

Resilient distribution datasets, update mechanism, weight mode

Abstract

Spark is a fast unified analysis engine for big data and machine learning, in which the memory is a crucial resource. Resilient Distribution Datasets (RDDs) are parallel data structures that allow users explicitly persist intermediate results in memory or on disk, and each one can be divided into several partitions. During task execution, Spark automatically monitors cache usage on each node. And when there is a RDD that needs to be stored in the cache where the space is insufficient, the system would drop out old data partitions in a least recently used (LRU) fashion to release more space. However, there is no mechanism specifically for caching RDD in Spark, and the dependency of RDDs and the need for future stages are not been taken into consideration with LRU. In this paper, we propose the optimization approach for RDDs cache and LRU based on the features of partitions, which includes three parts: the prediction mechanism for persistence, the weight model by using the entropy method, and the update mechanism of weight and memory based on RDDs partition feature. Finally, through the verification on the spark platform, the experiment results show that our strategy can effectively reduce the time in performing and improve the memory usage.

Jin Wang, Chunwei Ju, Yu Gao, Arun Kumar Sangaiah and Gwang-jun Kim: A PSO based Energy Efficient Coverage Control Algorithm for Wireless Sensor Networks, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.433-446,2018

Keywords

Particle swarm optimization, Coverage control, Energy efficiency, Wireless sensor networks

Abstract

Wireless Sensor Networks (WSNs) are large-scale and high-density networks that typically have coverage area overlap. In addition, a random deployment of sensor nodes cannot fully guarantee coverage of the sensing area, which leads to coverage holes in WSNs. Thus, coverage control plays an important role in WSNs. To alleviate unnecessary energy wastage and improve network performance, we consider both energy efficiency and coverage rate for WSNs. In this paper, we present a novel coverage control algorithm based on Particle Swarm Optimization (PSO). Firstly, the sensor nodes are randomly deployed in a target area and remain static after deployment. Then, the whole network is partitioned into grids, and we calculate each grid’s coverage rate and energy consumption. Finally, each sensor nodes’ sensing radius is adjusted according to the coverage rate and energy consumption of each grid. Simulation results show that our algorithm can effectively improve coverage rate and reduce energy consumption

Daofeng Li, Mingxing Luo, Bowen Zhao and Xiangdong Che: Provably Secure APK Redevelopment Authorization Scheme in the Standard Model, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.447-465,2018

Keywords

Sanitizable signature, APK signature mechanism, redevelopment, ID-based signature scheme

Abstract

The secure issues of APK are very important in Android applications. In order to solve potential secure problems and copyrights issues in redevelopment of APK files, in this paper we propose a new APK redevelopment mechanism (APK-SAN). By exploring sanitizable signature technology, APK-SAN allows the original developer to authorize specified modifier who can redevelop the designated source code of APK files. Our scheme does not require interactions between the developer and modifiers. It can reduce the communication overhead and computational overhead for developers. Especially, the signature of redeveloped APK files is valid and maintains the copyrights. The proposed APK-SAN signature can effectively protect the security of the redeveloped APK files and copyrights of the developer and modifier

Qing Tian, Meng Cao and Tinghuai Ma: Feature Relationships Learning Incorporated Age Estimation Assisted by Cumulative Attribute Encoding, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.467-482,2018

Keywords

Age estimation, cumulative attribute, gender-aware age estimation, corre-lation relationship learning

Abstract

The research of human facial age estimation (AE) has attracted increasing attention for its wide applications. Up to date, a number of models have been constructed or employed to perform AE. Although the goal of AE can be achieved by either classification or regression, the latter based methods generally yield more promising results because the continuity and gradualness of human aging can naturally be preserved in age regression. However, the neighbor-similarity and ordinality of age labels are not taken into account yet. To overcome this issue, the cumulative attribute (CA) coding was introduced. Although such age label relationships can be parameterized via CA coding, the potential relationships behind age features are not incorporated to estimate age. To this end, in this paper we propose to perform AE by encoding the potential age feature relationships with CA coding via an implicit modeling strategy. Besides that, we further extend our model to gender-aware AE by taking into account gender variance in aging process. Finally, we experimentally validate the superiority of the proposed methodology

Manyu Jin, Tao Wang, Zexuan Ji and Xiaobo Shen: Perceptual Gradient Similarity Deviation for Full Reference Image Quality Assessment, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.501-515,2018

Keywords

Image quality assessment, full reference, perceptual gradient similarity, multi-scale, standard deviation pooling

Abstract

Perceptual image quality assessment (IQA) is one of the most indispensable yet challenging problems in image processing and computer vision. It is quite necessary to develop automatic and efficient approaches that can accurately predict perceptual image quality consistently with human subjective evaluation. To further improve the prediction accuracy for the distortion of color images, in this paper, we propose a novel effective and efficient IQA model, called perceptual gradient similarity deviation (PGSD). Based on the gradient magnitude similarity, we proposed a gradient direction selection method to automatically determine the pixel-wise perceptual gradient. The luminance and chrominance channels are both took into account to characterize the quality degradation caused by intensity and color distortions. Finally, a multi-scale strategy is utilized and pooled with different weights to incorporate image details at different resolutions. Experimental results on LIVE, CSIQ and TID2013 databases demonstrate the superior performances of the proposed algorithm

Ying Hu, Qinfei Ke, Zhe Li, Wanli Han and Zhiyong Yan: In Situ Synthesis of Cuprous Oxide/Cellulose Nanofibers Gel and Antibacterial Properties, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.517-527,2018

Keywords

Cellulose nanofiber, cuprous oxide, in situ synthesis, antibacterial

Abstract

Cellulose nanofibers were synthesized by acetobacter xylinum (xylinum 1.1812). The cellulose nanofibers with 30-90 nm width constructed three-dimension network gel, which could be used as a wound dressing since it can provide moist environment to a wound. However, cellulose nanofibers have no antimicrobial activity to prevent wound infection. To achieve antimicrobial activity, the cellulose nanofibers can load cuprous oxide (Cu2O) particles on the surface. The cuprous oxide is a kind of safe antibacterial material. The copper ions can be reduced into cuprous oxides by reducing agents such as glucose, N2H4 and sodium hypophosphite. The cellulose nanofibers network gel was soaked in CuSO4 solution and filled with copper ions. The cuprous oxide nanoparticles were in situ synthesized by glucose and embedded in cellulose nanofibers network. The morphologies and structure of the composite gel were analyzed by FESEM, FTIR, WAXRD and inductively coupled plasma (ICP). The sizes of Cu2O embedded in cellulose nanofibers network are 200-500 nm wide. The peak at 605 cm−1 attributed to Cu(I)-O vibration of Cu2O shits to 611 cm−1 in the Cu2O/ cellulose composite. The Cu2O/ cellulose nanofibers composite reveals the obvious characteristic XRD pattern of Cu2O and the results of ICP show that the content of Cu2O in the composite is 13.1%. The antibacterial tests prove that the Cu2O/ cellulose nanofibers composite has the high antibacterial activities which is higher against S. aureus than against E. coli.

Ligang Zheng and Chao Song: Fast Near-duplicate Image Detection in Riemannian Space by A Novel Hashing Scheme, CMC: Computers, Materials & Continua, Vol.56,No.3,pp.529-539, 2018

Keywords

Riemannian manifold, congruent transformation, Hashing, kernel trick

Abstract

There is a steep increase in data encoded as symmetric positive definite (SPD) matrix in the past decade. The set of SPD matrices forms a Riemannian manifold that constitutes a half convex cone in the vector space of matrices, which we sometimes call SPD manifold. One of the fundamental problems in the application of SPD manifold is to find the nearest neighbor of a queried SPD matrix. Hashing is a popular method that can be used for the nearest neighbor search. However, hashing cannot be directly applied to SPD manifold due to its non-Euclidean intrinsic geometry. Inspired by the idea of kernel trick, a new hashing scheme for SPD manifold by random projection and quantization in expanded data space is proposed in this paper. Experimental results in large scale near-duplicate image detection show the effectiveness and efficiency of the proposed method

Vol. 57, No. 1

Huiyu Sun and Suzanne McIntosh: Analyzing Cross-domain Transportation Big Data of New York City with Semi-supervised and Active Learning, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.1-9, 2018

Keywords

Big data, taxi and uber, domain adaptation, active learning, semi-supervised learning.

Abstract

The majority of big data analytics applied to transportation datasets suffer from being too domain-specific, that is, they draw conclusions for a dataset based on analytics on the same dataset. This makes models trained from one domain (e.g. taxi data) applies badly to a different domain (e.g. Uber data). To achieve accurate analyses on a new domain, substantial amounts of data must be available, which limits practical applications. To remedy this, we propose to use semi-supervised and active learning of big data to accomplish the domain adaptation task: Selectively choosing a small amount of datapoints from a new domain while achieving comparable performances to using all the datapoints. We choose the New York City (NYC) transportation data of taxi and Uber as our dataset, simulating different domains with 90% as the source data domain for training and the remaining 10% as the target data domain for evaluation. We propose semi-supervised and active learning strategies and apply it to the source domain for selecting datapoints. Experimental results show that our adaptation achieves a comparable performance of using all datapoints while using only a fraction of them, substantially reducing the amount of data required. Our approach has two major advantages: It can make accurate analytics and predictions when big datasets are not available, and even if big datasets are available, our approach chooses the most informative datapoints out of the dataset, making the process much more efficient without having to process huge amounts of data.

Shuren Zhou, Wenlong Liang, Junguo Li and Jeong-Uk Kim: Improved VGG Model for Road Traffic Sign Recognition, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.11-24, 2018

Keywords

Intelligent transportation, traffic sign, deep learning, GTSRB, data augmentation.

Abstract

Road traffic sign recognition is an important task in intelligent transportation system. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, it presents a road traffic sign recognition algorithm based on a convolutional neural network. In natural scenes, traffic signs are disturbed by factors such as illumination, occlusion, missing and deformation, and the accuracy of recognition decreases, this paper proposes a model called Improved VGG (IVGG) inspired by VGG model. The IVGG model includes 9 layers, compared with the original VGG model, it is added max-pooling operation and dropout operation after multiple convolutional layers, to catch the main features and save the training time. The paper proposes the method which adds dropout and Batch Normalization (BN) operations after each fully-connected layer, to further accelerate the model convergence, and then it can get better classification effect. It uses the German Traffic Sign Recognition Benchmark (GTSRB) dataset in the experiment. The IVGG model enhances the recognition rate of traffic signs and robustness by using the data augmentation and transfer learning, and the spent time is also reduced greatly.

Rui Wang, Miaomiao Shen, Yanping Li and Samuel GOMES: Multi-task Joint Sparse Representation Classification Based on Fisher Discrimination Dictionary Learning, CMC: Computers, Materials & Continua, vol.57 no.1, pp.25-48, 2018

Keywords

Multi-sensor fusion, fisher discrimination dictionary learning (FDDL), vehicle classification, sensor networks, sparse representation classification (SRC).

Abstract

Recently, sparse representation classification (SRC) and fisher discrimination dictionary learning (FDDL) methods have emerged as important methods for vehicle classification. In this paper, inspired by recent breakthroughs of discrimination dictionary learning approach and multi-task joint covariate selection, we focus on the problem of vehicle classification in real-world applications by formulating it as a multi-task joint sparse representation model based on fisher discrimination dictionary learning to merge the strength of multiple features among multiple sensors. To improve the classification accuracy in complex scenes, we develop a new method, called multi-task joint sparse representation classification based on fisher discrimination dictionary learning, for vehicle classification. In our proposed method, the acoustic and seismic sensor data sets are captured to measure the same physical event simultaneously by multiple heterogeneous sensors and the multi-dimensional frequency spectrum features of sensors data are extracted using Mel frequency cepstral coefficients (MFCC). Moreover, we extend our model to handle sparse environmental noise. We experimentally demonstrate the benefits of joint information fusion based on fisher discrimination dictionary learning from different sensors in vehicle classification tasks.

Xi Kan, Yonghong Zhang, Linglong Zhu, Liming Xiao, Jiangeng Wang, Wei Tian and Haowen Tan: Snow Cover Mapping for Mountainous Areas by Fusion of MODIS L1B and Geographic Data Based on Stacked Denoising Auto-Encoders, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.49-68, 2018

Keywords

Snow cover, remote sensing, deep learning, Qinghai-Tibetan Plateau, MODIS L1B.

Abstract

Snow cover plays an important role in meteorological and hydrological researches. However, the accuracies of currently available snow cover products are significantly lower in mountainous areas than in plains, due to the serious snow/cloud confusion problem caused by high altitude and complex topography. Aiming at this problem, an improved snow cover mapping approach for mountainous areas was proposed and applied in Qinghai-Tibetan Plateau. In this work, a deep learning framework named Stacked Denoising Auto-Encoders (SDAE) was employed to fuse the MODIS multispectral images and various geographic datasets, which are then classified into three categories: Snow, cloud and snow-free land. Moreover, two independent SDAE models were trained for snow mapping in snow and snow-free seasons respectively in response to the seasonal variations of meteorological conditions. The proposed approach was verified using in-situ snow depth records, and compared to the most widely used snow products MOD10A1 and MYD10A1. The comparison results show that our method got the best performance: Overall accuracy of 98.95% and F-measure of 73.84%. The results indicated that our method can effectively improve the snow recognition accuracy, and it can be further extended to other multi-source remote sensing image classification issues.

Jun Shi, Zhujun Zhang, Yangyang Li, Rui Wang, Hao Shi and Xile Li: New Method for Computer Identification Through Electromagnetic Radiation, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.69-80, 2018

Keywords

Computer security, information security, compromising emanations, electromagnetic interference, signals sources identification, SVM.

Abstract

The electromagnetic waves emitted from devices can be a source of information leakage and can cause electromagnetic compatibility (EMC) problems. Electromagnetic radiation signals from computer displays can be a security risk if they are intercepted and reconstructed. In addition, the leaks may reveal the hardware information of the computer, which is more important for some attackers, protectors and security inspection workers. In this paper, we propose a statistical distribution based algorithm (SD algorithm) to extracted eigenvalues from electromagnetic radiate video signals, and then classified computers by using classifier based on Bayesian and SVM. We can identify computers automatically and accurately through electromagnetic radiation by using the algorithm in our experiment environment.

Tiejun Wang, Tao Wu, Amir Homayoon Ashrafzadeh and Jia He: Crowdsourcing-Based Framework for Teaching Quality Evaluation and Feedback Using Linguistic 2-Tuple, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.81-96, 2018

Keywords

Teaching quality evaluation, crowdsourcing, linguistic 2-tuple, group decision making.

Abstract

Crowdsourcing is widely used in various fields to collect goods and services from large participants. Evaluating teaching quality by collecting feedback from experts or students after class is not only delayed but also not accurate. In this paper, we present a crowdsourcing-based framework to evaluate teaching quality in the classroom using a weighted average operator to aggregate information from students’ questionnaires described by linguistic 2-tuple terms. Then we define crowd grade based on similarity degree to distinguish contribution from different students and minimize the abnormal students’ impact on the evaluation. The crowd grade would be updated at the end of each feedback so it can guarantee the evaluation accurately. Moreover, a simulated case is shown to illustrate how to apply this framework to assess teaching quality in the classroom. Finally, we developed a prototype and carried out some experiments on a series of real questionnaires and two sets of modified data. The results show that teachers can locate the weak points of teaching and furthermore to identify the abnormal students to improve the teaching quality. Meanwhile, our approach provides a strong tolerance for the abnormal student to make the evaluation more accurate.

Lianggui Liu, Wei Li and Huiling Jia: Method of Time Series Similarity Measurement Based on Dynamic Time Warping, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.97-106, 2018

Keywords

Time series, PCA dimensionality reduction, dynamic time warping, hierarchical clustering, cophenetic correlation.

Abstract

With the rapid development of mobile communication all over the world, the similarity of mobile phone communication data has received widely attention due to its advantage for the construction of smart cities. Mobile phone communication data can be regarded as a type of time series and dynamic time warping (DTW) and derivative dynamic time warping (DDTW) are usually used to analyze the similarity of these data. However, many traditional methods only calculate the distance between time series while neglecting the shape characteristics of time series. In this paper, a novel hybrid method based on the combination of dynamic time warping and derivative dynamic time warping is proposed. The new method considers not only the distance between time series, but also the shape characteristics of time series. We demonstrated that our method can outperform DTW and DDTW through extensive experiments with respect to cophenetic correlation.

Xiang Wang, Chen Xiong, Qingqi Pei and Youyang Qu: Expression Preserved Face Privacy Protection Based on Multi-mode Discriminant Analysis, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.107-121, 2018

Keywords

Privacy protection, multi-mode, discrimination, expression-preserving.

Abstract

Most visual privacy protection methods only hide the identity information of the face images, but the expression, behavior and some other information, which are of great significant in the live broadcast and other scenarios, are also destroyed by the privacy protection process. To this end, this paper introduces a method to remove the identity information while preserving the expression information by performing multi-mode discriminant analysis on the images normalized with AAM algorithm. The face images are decomposed into mutually orthogonal subspaces corresponding to face attributes such as gender, race and expression, each of which owns related characteristic parameters. Then, the expression parameter is preserves to keep the facial expression information while others parameters, including gender and race, are modified to protect face privacy. The experiments show that this method yields well performance on both data utility and privacy protection.

Lingling Xia, Bo Song, Zhengjun Jing, Yurong Song and Liang Zhang: Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.123-144, 2018

Keywords

Complex networks, Markov chains theory, interaction process, spreading dynamics, double-layer network.

Abstract

Considering dynamical disease spreading network consisting of moving individuals, a new double-layer network is constructed, one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves. On the basis of Markov chains theory, a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment. Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence spreading dynamics. Simulation results show that the increasing of information transmission rate can reduce the scale of disease spreading in some degree. Shortening infection period and strengthening consciousness for self-protection by decreasing individual’s scope of activity both can effectively reduce the final refractory density for the disease but have less effect on the information dissemination. In addition, the increasing of vaccination rate or decreasing of long-range travel can also reduce the scale of disease spreading.

Guorui Huang, Zhongkai Cui, Pengfei Zhu and Xiaoyun Liu: Modification of Nano Tourmaline Surface Treatment Agent and Its Performance on Negative Ion Release, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.145-150, 2018

Keywords

Tourmaline, dispersant, negative ion, storage stability, wall fabrics.

Abstract

In this paper, a kind of wall fabric’s surface treatment agent modified with nonionic surfactant was reported. This surface treatment agent was prepared by using nano tourmaline powder dispersion in water with surfactant as dispersants by sand milling. Under the influence of different dispersants, the negative ions releasing amount of functional wall fabrics, the milling process and the storage stability of nano tourmaline powder dispersion were discussed. The results showed that nano tourmaline powder dispersion achieved the smallest average diameter of 44 nm and had best storage stability that the average diameter maintained below 200 nm in 17 days when the addition amount of dispersant was 20 percent of the tourmaline powders’ weight. What is more, the quantity of negative ion releasing achieved 6500 ion/cm3 when addition amount of dispersant was 30 percent. This technique could be used to strengthen productivity of nano tourmaline powder dispersion.

Zhaoyue Zhang, Jing Zhang, Peng Wang and Lei Chen: Research on Operation of UAVs in Non-isolated Airspace, CMC: Computers, Materials & Continua, vol.57 no.1,pp.151-166, 2018

Keywords

Unmanned aircraft vehicles, non-isolated airspace, safe operation, risk assessment.

Abstract

In order to explore the safe operation of UAVs in non-segregated airspace, a collision risk model for cylindrical UAVs based on conflict areas was constructed and the risk of conflict between manned and unmanned aerial vehicles was researched. According to the results of risk analysis, a strategy for solving the conflict of aircraft is proposed, and the risk assessment experiment of unmanned aerial vehicle (UAV) in non-isolated airspace conflict is carried out. The results show that under the experimental conditions, large unmanned aerial vehicles equipped with ADS-B, TCAS and other airborne sensing systems will indeed interfere with other aircraft in airspace when they enter non-isolated airspace. Especially when the number of aircraft in airspace is large, the automatic avoidance system of UAV will increase the avoidance time and trigger the safety alarm, but the safety level is still acceptable. This indicates that it is relatively safe for UAVs to enter non-isolated airspace under limited conditions. The results can be used as a reference for the safe operation of unmanned aerial vehicle (UAV) in non-isolated airspace.

Wei Fang, Feihong Zhang, Victor S. Sheng and Yewen Ding: A Method for Improving CNN-Based Image Recognition Using DCGAN, CMC: Computers, Materials & Continua, vol.57 no.1 ,pp.167-178, 2018

Keywords

DCGAN, image recognition, CNN, samples.

Abstract

Image recognition has always been a hot research topic in the scientific community and industry. The emergence of convolutional neural networks(CNN) has made this technology turned into research focus on the field of computer vision, especially in image recognition. But it makes the recognition result largely dependent on the number and quality of training samples. Recently, DCGAN has become a frontier method for generating images, sounds, and videos. In this paper, DCGAN is used to generate sample that is difficult to collect and proposed an efficient design method of generating model. We combine DCGAN with CNN for the second time. Use DCGAN to generate samples and training in image recognition model, which based by CNN. This method can enhance the classification model and effectively improve the accuracy of image recognition. In the experiment, we used the radar profile as dataset for 4 categories and achieved satisfactory classification performance. This paper applies image recognition technology to the meteorological field.

Vol. 57, No. 2

Xiaodong Liu and Qi Liu: A Dual-spline Approach to Load Error Repair in a HEMS Sensor Network, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.179-194, 2018

Keywords

Electric load data analysis, home energy management, quality assurance and control.

Abstract

In a home energy management system (HEMS), appliances are becoming diversified and intelligent, so that certain simple maintenance work can be completed by appliances themselves. During the measurement, collection and transmission of electricity load data in a HEMS sensor network, however, problems can be caused on the data due to faulty sensing processes and/or lost links, etc. In order to ensure the quality of retrieved load data, different solutions have been presented, but suffered from low recognition rates and high complexity. In this paper, a validation and repair method is presented to detect potential failures and errors in a domestic energy management system, which can then recover determined load errors and losses. A Kernel Extreme Learning Machine (K-ELM) based model has been employed with a Radial Basis Function (RBF) and optimised parameters for verification and recognition; whilst a Dual-spline method is presented to repair missing load data. According to the experiment results, the method outperforms the traditional B-spline and Cubic-spline methods and can effectively deal with unexpected data losses and errors under variant loss rates in a practical home environment.

Haipeng Chen, Kexiong Liu, Chunyang Ma, Yu Han and Jian Su: A Novel Time-aware Frame Adjustment Strategy for RFID Anti-collision, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.195-204, 2018

Keywords

Radio frequency identification, anti-collision, alpha, time efficiency.

Abstract

Recently, object identification with radio frequency identification (RFID) technology is becoming increasingly popular. Identification time is a key performance metric to evaluate the RFID system. The present paper analyzes the deficiencies of the state-of-the-arts algorithms and proposes a novel sub-frame-based algorithm with adaptive frame breaking policy to lower the tag identification time for EPC global C1 Gen2 UHF RFID standard. Through the observation of slot statistics in a sub-frame, the reader estimates the tag quantity and efficiently calculates an optimal frame size to fit the unread tags. Only when the expected average identification time in the calculated frame size is less than that in the previous frame size, the reader starts the new frame. Moreover, the estimation of the proposed algorithm is implemented by the look-up tables, which allows dramatically reduction in the computational complexity. Simulation results show noticeable throughput and time efficiency improvements of the proposed solution over the existing approaches.

Wenjun Yang, Pingping Dong, Wensheng Tang, Xiaoping Lou, Hangjun Zhou, Kai Gao and Haodong Wang: A MPTCP Scheduler for Web Transfer, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.205-222, 2018

Keywords

MPTCP, short flow, web transfer, timeout, path heterogeneity.

Abstract

Multipath TCP (MPTCP) is the most significant extension of TCP that enables transmission via multiple paths concurrently to improve the resource usage and throughput of long flows. However, due to the concurrent multiple transfer (CMT) in short flow trans-mission, the congestion window (cwnd) of each MPTCP subflow is too small and it may lead to timeout when a single lost packet cannot be recovered through fast retransmission. As a result, MPTCP has even worse performance for short flows compared to regular TCP. In this paper, we take the first step to analyze the main reason why MPTCP has the diminished performance for short flows, and then we propose MPTCP-SF, which dynamically adjusts the number of subflows for each flow . In particular, MPTCP-SF firstly analyzes the distribution characteristics of the web objects to extract two thresholds to be used for classifying each flow. After eceiving each new ACK, MPTCP-SF periodically counts the data being sent based on per-flow and uses the threshold to classify the we blows. Finally, MPTCP-SF dynamically switches path scheduling model for different classification flows. We conduct extensive experiments in NS3 to evaluate its e fficiency. Our evaluation proves that MPTCP-SF decreases the completion time of short flows by over 42.64% com-pared to MPTCP, and the throughput achieved by MPTCP-SF in transmitting long flows is about 11.11% higher than that of MPTCP in a WLAN/LTE wireless network. The results successfully validate the improved performance of MPTCP-SF.

Xiaoping Zhao, Jiaxin Wu, Yonghong Zhang, Yunqing Shi and Lihua Wang: Fault Diagnosis of Motor in Frequency Domain Signal by Stacked De-noising Auto-encoder, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.223-242, 2018

Keywords

Big data, deep learning, stacked de-noising auto-encoder, fourier transform.

Abstract

With the rapid development of mechanical equipment, mechanical health monitoring field has entered the era of big data. Deep learning has made a great achievement in the processing of large data of image and speech due to the powerful modeling capabilities, this also brings influence to the mechanical fault diagnosis field. Therefore, according to the characteristics of motor vibration signals (nonstationary and difficult to deal with) and mechanical ‘big data’, combined with deep learning, a motor fault diagnosis method based on stacked de-noising auto-encoder is proposed. The frequency domain signals obtained by the Fourier transform are used as input to the network. This method can extract features adaptively and unsupervised, and get rid of the dependence of traditional machine learning methods on human extraction features. A supervised fine tuning of the model is then carried out by backpropagation. The Asynchronous motor in Drivetrain Dynamics Simulator system was taken as the research object, the effectiveness of the proposed method was verified by a large number of data, and research on visualization of network output, the results shown that the SDAE method is more efficient and more intelligent.

Daofu Gong, Yan Chen, Haoyu Lu, Zhenyu Li and Yibing Han: Self-embedding Image Watermarking based on Combined Decision Using Pre-offset and Post-offset Blocks, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.243-260, 2018

Keywords

Fragile watermarking, self-embedding, offset block, tamper recovery, random tampering.

Abstract

To detect and recover random tampering areas, a combined-decision-based self-embedding watermarking scheme is proposed herein. In this scheme, the image is first partitioned into 2×2 size blocks. Next, the high 5 bits of a block’s average value is embedded into its offset block. The tampering type of block is detected by comparing the watermarks of its pre-offset and post-offset blocks. The theoretical analysis and experiments demonstrate that the proposed scheme not only has a lower ratio of false detection but also better performance with regard to avoiding random tampering.

Jun Xie, Chong Wang, Jiaxiang Cai and Fuhong Cai: Band Selection Method of Absorption Peak Perturbance for the FTIR/ATR Spectrum Analysis, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.261-268, 2018

Keywords

Band selection, FTIR, ATR, serum glucose.

Abstract

The rapid quantification method of human serum glucose was established by using the Fourier transform infrared spectroscopy (FTIR) and attenuated total reflection (ATR). By the subtracted spectra between glucose aqueous solution and de-ionized water, absorption peaks are calculated in fingerprint area. Based on these absorption peaks and multiple linear regression (MLR) model, discrete band selection method of absorption peaks disturbance model (APDM) was developed. 5 absorption peaks 1150 cm-1, 1103 cm-1, 1078 cm-1, 1034 cm-1, 991 cm-1 were found in fingerprint area. Used these absorption peaks to establish absorption peaks disturbance model, the optimal wavelength combinations are 1140 cm-1, 1096 cm-1, 1084 cm-1, 1030 cm-1, 993 cm-1, the corresponding C-RMSEP and C-RP are 1.164 mmol/L and 0.828 respectively. The results show that the optimal prediction effect of APDM was obviously better than the one of the Partial least squares (PLS) model, and the complexity of the optimal model is reduced greatly also. The results also provide a theoretical basis for design of small and portable human serum glucose spectrometer.

Kehua Yang, Tian Tan and Wei Zhang: An Evidence Combination Method based on DBSCAN Clustering, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.269-281, 2018

Keywords

D-S evidence theory, information fusion, DBSCAN, combination rules.

Abstract

Dempster-Shafer (D-S) evidence theory is a key technology for integrating uncertain information from multiple sources. However, the combination rules can be paradoxical when the evidence seriously conflict with each other. In the paper, we propose a novel combination algorithm based on unsupervised Density-Based Spatial Clustering of Applications with Noise (DBSCAN) density clustering. In the proposed mechanism, firstly, the original evidence sets are preprocessed by DBSCAN density clustering, and a successfully focal element similarity criteria is used to mine the potential information between the evidence, and make a correct measure of the conflict evidence. Then, two different discount factors are adopted to revise the original evidence sets, based on the result of DBSCAN density clustering. Finally, we conduct the information fusion for the revised evidence sets by D-S combination rules. Simulation results show that the proposed method can effectively solve the synthesis problem of high-conflict evidence, with better accuracy, stability and convergence speed.

Baojia Wang, Pingzeng Liu, Zhang Chao, Wang Junmei, Weijie Chen, Ning Cao, Gregory M.P. O’Hare and Fujiang Wen: Research on Hybrid Model of Garlic Short-term Price Forecasting based on Big Data, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.283-296, 2018

Keywords

Price forecast, machine learning, hybrid model, garlic.

Abstract

Garlic prices fluctuate dramatically in recent years and it is very difficult to predict garlic prices. The autoregressive integrated moving average (ARIMA) model is currently the most important method for predicting garlic prices. However, the ARIMA model can only predict the linear part of the garlic prices, and cannot predict its nonlinear part. Therefore, it is urgent to adopt a method to analyze the nonlinear characteristics of garlic prices. After comparing the advantages and disadvantages of several major prediction models which used to forecast nonlinear time series, using support vector machine (SVM) model to predict the nonlinear part of garlic prices and establish ARIMA-SVM hybrid forecast model to predict garlic prices. The monthly average price data of garlic in 2010-2017 was used to test the effect of ARIMA model, SVM model and ARIMA-SVM model. The experimental results show that: (1) Garlic price is affected by many factors but the most is the supply and demand relationship; (2) The SVM model has a good effect in dealing with the nonlinear relationship of garlic prices; (3) The ARIMA-SVM hybrid model is better than the single ARIMA model and SVM model on the accuracy of garlic price prediction, it can be used as an effective method to predict the short-term price of garlic.

Chak Fong Cheang, Yiqin Wang, Zhiping Cai and Gen Xu: Multi-VMs Intrusion Detection for Cloud Security Using Dempster-shafer Theory, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.297-306, 2018

Keywords

Intrusion detection, cloud computing, Dempster-Shafer theory, evidence fusion.

Abstract

Cloud computing provides easy and on-demand access to computing resources in a configurable pool. The flexibility of the cloud environment attracts more and more network services to be deployed on the cloud using groups of virtual machines (VMs), instead of being restricted on a single physical server. When more and more network services are deployed on the cloud, the detection of the intrusion likes Distributed Denial-of-Service (DDoS) attack becomes much more challenging than that on the traditional servers because even a single network service now is possibly provided by groups of VMs across the cloud system. In this paper, we propose a cloud-based intrusion detection system (IDS) which inspects the features of data flow between neighboring VMs, analyzes the probability of being attacked on each pair of VMs and then regards it as independent evidence using Dempster-Shafer theory, and eventually combines the evidence among all pairs of VMs using the method of evidence fusion. Unlike the traditional IDS that focus on analyzing the entire network service externally, our proposed algorithm makes full use of the internal interactions between VMs, and the experiment proved that it can provide more accurate results than the traditional algorithm.

Xuwei Tang, Juan Xu and Bojia Duan: A Memory-efficient Simulation Method of Grover's Search Algorithm, CMC: Computers, Materials & Continua, Vol.57 No.2 ,pp.307-319, 2018

Keywords

Grover's search algorithm, probability amplitude, quantum simulation, memory compression.

Abstract

Grover's search algorithm is one of the most significant quantum algorithms, which can obtain quadratic speedup of the extensive search problems. Since Grover's search algorithm cannot be implemented on a real quantum computer at present, its quantum simulation is regarded as an effective method to study the search performance. When simulating the Grover's algorithm, the storage space required is exponential, which makes it difficult to simulate the high-qubit Grover's algorithm. To this end, we deeply study the storage problem of probability amplitude, which is the core of the Grover simulation algorithm. We propose a novel memory-efficient method via amplitudes compression, and validate the effectiveness of the method by theoretical analysis and simulation experimentation. The results demonstrate that our compressed simulation search algorithm can help to save nearly 87.5% of the storage space than the uncompressed one. Thus under the same hardware conditions, our method can dramatically reduce the required computing nodes, and at the same time, it can simulate at least 3 qubits more than the uncompressed one. Particularly, our memory-efficient simulation method can also be used to simulate other quantum algorithms to effectively reduce the storage costs required in simulation.

Yong Jiang, Xiaolin Zhong, Yong Guo and Meixia Duan: Communication Mechanism and Algorithm of Composite Location Analysis of Emergency Communication based on Rail, CMC: Computers, Materials & Continua, Vol. 57, No. 2, pp. 321-340, 2018

Keywords

Emergency communication, elastic wave, attenuation, composite locating algorithm, rfc2544.

Abstract

The emergency communication system based on rail is an unconventional emergency communication mode, it is a complement equipment for that conventional communication system can’t work while tunnel mine accident occurs. Medium of transmission channel is the widely existing rail in the tunnel. In this paper we analyzed the characteristics of the rail transmission channel, verified the feasibility that information is transmitted by vibration signal in rail, we proposed the realization plan of the system. Communication protocol and processing mechanism suitable for rail transmission are designed according to the characteristics of channel bandwidth and low data transmission. Information communication with low bit rate and low bit error is realized in the communication simulation model. In the simplified model, we realized to transmit recognition speech information, and the error rate of the key text information is low to accept. The most concerned problem of personnel location in the mine disaster rescue is proposed, the composite algorithm is based on the model of signal amplitude attenuation, key node information and data frame transmission delay. Location information of hitting point can be achieved within the simplified model of the experiment. Furthermore, we discuss the characteristics of vibration signals passing through different channels.

V. Gopinath and R. S. Bhuvaneswaran: Design of ECC based Secured Cloud Storage Mechanism for Transaction Rich Applications, CMC: Computers, Materials & Continua, Vol.57, No. 2, pp. 341-352, 2018

Keywords

ECC, SSL VPN, cloud computing, banking, security, transaction rich applications.

Abstract

Cloud computing is the highly demanded technology nowadays. Due to the service oriented architecture, seamless accessibility and other advantages of this advent technology, many transaction rich applications are making use of it. At the same time, it is vulnerable to hacks and threats. Hence securing this environment is of at most important and many research works are being reported focusing on it. This paper proposes a safe storage mechanism using Elliptic curve cryptography (ECC) for the Transaction Rich Applications (TRA). With ECC based security scheme, the security level of the protected system will be increased and it is more suitable to secure the delivered data in the portable devices. The proposed scheme shields the aligning of different kind of data elements to each provider using an ECC algorithm. Analysis, comparison and simulation prove that the proposed system is more effective and secure for the Transaction rich applications in Cloud.

Vol. 57, No. 3, 2018

Pengcheng Liu, Xiaojun Wang, S. R. Chaudhry, Khalid Javeed, Yue Ma and Martin Collier (2018): Secure Video Streaming with Lightweight Cipher PRESENT in an SDN Testbed, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.353-363

Keywords

Lightweight cipher, netFPGA, openFlow, RESENT encryption.

Abstract

The combination of traditional processors and Field Programmable Gate Arrays (FPGA) is shaping the future networking platform for intensive computation in resource-constrained networks and devices. These networks present two key challenges of security and resource limitations. Lightweight ciphers are suitable to provide data security in such constrained environments. Implementing the lightweight PRESENT encryption algorithm in a reconfigurable platform (FPGAs) can offer secure communication service and flexibility. This paper presents hardware acceleration of security primitives in SDN using NETFPGA-10G. We implement an efficient design of the PRESENT algorithm for faster, smaller and lower power consumption hardware circuit using Verilog. We evaluate the performance of the hardware and software implementations of PRESENT. Experimental results prove that the proposed hardware design is a viable option for use in resource constrained devices in future networks and their applications.

Rooh ul Amin, Irum Inayat, Li Aijun, Shahaboddin Shamshirband and Timon Rabczuk (2018): A Bio-Inspired Global Finite Time Tracking Control of Four-Rotor Test Bench System, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.365-388

Keywords

Bio-inspired global fast terminal sliding mode controller, attitude tracking, radial basis function network, four-rotor hover system.

Abstract

A bio-inspired global finite time control using global fast-terminal sliding mode controller and radial basis function network is presented in this article, to address the attitude tracking control problem of the three degree-of-freedom four-rotor hover system. The proposed controller provides convergence of system states in a pre-determined finite time and estimates the unmodeled dynamics of the four-rotor system. Dynamic model of the four-rotor system is derived with Newton’s force equations. The unknown dynamics of four-rotor systems are estimated using Radial basis function. The bio-inspired global fast terminal sliding mode controller is proposed to provide chattering free finite time error convergence and to provide optimal tracking of the attitude angles while being subjected to unknown dynamics. The global stability proof of the designed controller is provided on the basis of Lyapunov stability theorem. The proposed controller is validated by (i) conducting an experiment through implementing it on the laboratory-based hover system, and (ii) through simulations. Performance of the proposed control scheme is also compared with classical and intelligent controllers. The performance comparison exhibits that the designed controller has quick transient response and improved chattering free steady state performance. The proposed bio-inspired global fast terminal sliding mode controller offers improved estimation and better tracking performance than the traditional controllers. In addition, the proposed controller is computationally cost effective and can be implanted on multirotor unmanned air vehicles with limited computational processing capabilities.

H. S. Abdel-Aziz, M. Khalifa Saad and A. A. Abdel-Salam (2018): Some Geometric Invariants of Pseudo-Spherical Evolutes in the Hyperbolic 3-Space, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.389-415

Keywords

Pseudo-spherical evolutes, evolute curves, hyperbolic 3-space.

Abstract

In this paper, we study the pseudo-spherical evolutes of curves in three dimensional hyperbolic space. We use techniques from singularity theory to investigate the singularities of pseudo-spherical evolutes and establish some relationships between singularities of these curves and geometric invariants of curves under the action of the Lorentz group. Besides, we defray with illustration some computational examples in support our main results.

Shuai Zhou and Xiaoying Zhuang (2018): Characterization of Loading Rate Effects on the Interactions between Crack Growth and Inclusions in Cementitious Material, CMC: Computers, Materials & Continua, Vol.57 No.3 , pp.417-446

Keywords

Microcapsule, loading rate, cracking processes, DEM, compressive loading.

Abstract

The microcapsule-enabled cementitious material is an appealing building material and it has been attracting increasing research interest. By considering microcapsules as dissimilar inclusions in the material, this paper employs the discrete element method (DEM) to study the effects of loading rates on the fracturing behavior of cementitious specimens containing the inclusion and the crack. The numerical model was first developed and validated based on experimental results. It is then used to systematically study the initiation, the propagation and the coalescence of cracks in inclusion-enabled cementitious materials. The study reveals that the crack propagation speed, the first crack initiation stress, the coalescence stress, the compressive strength and the ultimate strain increase with the loading rate. The initiation position, the propagation direction, the cracking length and the type of the initiated cracks are influenced by the loading rates. Two new crack coalescence patterns are observed. It is easier to cause the coalescence between the circular void and a propagating crack at a slow loading rate than at a fast loading rate.

T. D. Tran, Chien H. Thai and H. Nguyen-Xuan (2018): A Size-Dependent Functionally Graded Higher Order Plate Analysis Based on Modified Couple Stress Theory and Moving Kriging Meshfree Method, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.447-483

Keywords

Modified couple stress theory, isotropic and sandwich FGM plates, moving Kriging meshfree method.

Abstract

A size-dependent computational approach for bending, free vibration and buckling analyses of isotropic and sandwich functionally graded (FG) microplates is in this study presented. We consider both shear deformation and small scale effects through the generalized higher order shear deformation theory and modified couple stress theory (MCST). The present model only retains a single material length scale parameter for capturing properly size effects. A rule of mixture is used to model material properties varying through the thickness of plates. The principle of virtual work is used to derive the discrete system equations which are approximated by moving Kriging interpolation (MKI) meshfree method. Numerical examples consider the inclusions of geometrical parameters, volume fraction, boundary conditions and material length scale parameter. Reliability and effectiveness of the present method are confirmed through numerical results.

Yugai Huang (2018): The Stability of Anionic States of Thymine-Glycine Dimers with Excess Electron, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.485-494

Keywords

Low energy electrons (LEEs), DNA damage, thymine-glycine dimers, stability.

Abstract

It has been demonstrated that low energy electrons (LEEs) can induce serious DNA damages including bases loss and even single and double strand breaks. Experiments also showed that LEE induced DNA damages will be reduced with the presence of amino acids. For understanding of the protection of amino acids to DNA, the stability of 6 kinds of thymine and glycine (T-g) dimers with planar configurations with an excess electron were studied with density functional theory (DFT) method. The results show that, when the excess electron is vertically attached, all the dimers become more active with higher energy. After re-optimization, 4 kinds (66.7%) of T-g dimers become more stable than the corresponding neutral states. For the most stable anionic dimer noted as [34-A]-, the excess electron is localized on the thymine, while one proton transfers from glycine to thymine. The proton transformation decreases the activities and prevents further reactions of the excess electron. For other three dimers, there is no chemical topology change. The glycine attracts the excess electron with hydrogen-bonding to the thymine.

Xiaoqing Tan, Xiaochun Li and Pei Yang (2018): Perfect Quantum Teleportation via Bell States, CMC: Computers, Materials & Continua, Vol.57 No.3 ,495-503

Keywords

Quantum teleportation, Bell states, product state, pure entangled state.

Abstract

Quantum mechanics shows superiority than classical mechanics in many aspects and quantum entanglement plays an essential role in information processing and some computational tasks such as quantum teleportation (QT). QT was proposed to transmit the unknown states, in which EPR pairs, the entangled states, can be used as quantum channels. In this paper, we present two simple schemes for teleporting a product state of two arbitrary single-particle and an arbitrary two-particle pure entangled state respectively. Alice and Bob have shared an entangle state. Two Bell states are used as quantum channels. Then after Alice measuring her qubits and informing Bob her measurement results, Bob can perfectly reconstruct the original state by performing corresponding unitary operators on his qubits. It shown that a product state of two arbitrary single-particle and an arbitrary two-particle pure entangled state can be teleported perfectly, i.e. the success probabilities of our schemes are both 1.

Xiaorui Zhang, Jiali Duan, Lifeng Zhu and Ladislav Kavan (2018): A Virtual Puncture Surgery System Based on Multi-Layer Soft Tissue and Force Mesh, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.505-519

Keywords

Puncture simulation, spherical harmonic function, mass spring model, tissue surface resumption, weighted grading evaluation.

Abstract

Puncture is a common operation in surgery, which involves all kinds of tissue materials with different geometry and mechanical properties. As a new cross-disciplinary research area, Virtual Surgery (VS) makes simulation of soft tissue in puncture operation possible in virtual environment. In this paper, we introduce a VS-based puncture system composed by three-layer soft tissue, simulated with spherical harmonic function (SHF), which is covered with a force mesh, constructed by mass spring model (MSM). The two models are combined together with a parameter of SHF named surface radius, which provides MSM with real-time deformation data needed in force calculation. Meanwhile, force calculation, divided into the surface spring force and the puncture damping force, makes the force presentation better accord to the corresponding tissue characteristics. Moreover, a deformation resumption algorithm is leveraged to simulate the resumption phenomenon of the broken tissue surface. In evaluation experiment, several residents are invited to grades our model along with other four mainstream soft tissue models in terms of 7 different indicators. After the evaluation, the scores are analyzed by a comprehensive weighted grading method. Experiment results show that the proposed model has better performance during puncture operation than other models, and can well simulate surface resumption phenomenon when tissue surface is broken.

Ming He, Hongbin Wang, Lianke Zhou, Pengming Wang and Andrew Ju (2018): Symmetric Learning Data Augmentation Model for Underwater Target Noise Data Expansion, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.521-532

Keywords

Data augmentation, symmetric learning, data expansion, underwater target noise data.

Abstract

An important issue for deep learning models is the acquisition of training of data. Without abundant data from a real production environment for training, deep learning models would not be as widely used as they are today. However, the cost of obtaining abundant real-world environment is high, especially for underwater environments. It is more straightforward to simulate data that is closed to that from real environment. In this paper, a simple and easy symmetric learning data augmentation model (SLDAM) is proposed for underwater target radiate-noise data expansion and generation. The SLDAM, taking the optimal classifier of an initial dataset as the discriminator, makes use of the structure of the classifier to construct a symmetric generator based on antagonistic generation. It generates data similar to the initial dataset that can be used to supplement training data sets. This model has taken into consideration feature loss and sample loss function in model training, and is able to reduce the dependence of the generation and expansion on the feature set. We verified that the SLDAM is able to data expansion with low calculation complexity. Our results showed that the SLDAM is able to generate new data without compromising data recognition accuracy, for practical application in a production environment.

Guoyuan Lin, Bowen Liu, Pengcheng Xiao, Min Lei and Wei Bi (2018): Phishing Detection with Image Retrieval Based on Improved Texton Correlation Descriptor, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.533-547

Keywords

Anti-phishing, blockchain, texton correlation descriptor, weighted euclidean distance, image retrieval.

Abstract

Anti-detection is becoming as an emerging challenge for anti-phishing. This paper solves the threats of anti-detection from the threshold setting condition. Enough webpages are considered to complicate threshold setting condition when the threshold is settled. According to the common visual behavior which is easily attracted by the salient region of webpages, image retrieval methods based on texton correlation descriptor (TCD) are improved to obtain enough webpages which have similarity in the salient region for the images of webpages. There are two steps for improving TCD which has advantage of recognizing the salient region of images: (1) This paper proposed Weighted Euclidean Distance based on neighborhood location (NLW-Euclidean distance) and double cross windows, and combine them to solve the problems in TCD; (2) Space structure is introduced to map the image set to Euclid space so that similarity relation among images can be used to complicate threshold setting conditions. Experimental results show that the proposed method can improve the effectiveness of anti-phishing and make the system more stable, and significantly reduce the possibilities of being hacked to be used as mining systems for blockchain.

Lili He, Dantong Ouyang, Meng Wang, Hongtao Bai, Qianlong Yang, Yaqing Liu and Yu Jiang (2018): A Method of Identifying Thunderstorm Clouds in Satellite Cloud Image Based on Clustering, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.549-570

Keywords

Cloud computing, cluster analysis, FCM, DBSCAN, thunderstorm clouds, satellite cloud image.

Abstract

In this paper, the clustering analysis is applied to the satellite image segmentation, and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power. The method firstly adopts the fuzzy C-means clustering (FCM) to obtain the satellite cloud image segmentation. Secondly, in the cloud image, we dispose the ‘high-density connected’ pixels in the same cloud clusters and the ‘low-density connected’ pixels in different cloud clusters. Therefore, we apply the DBSCAN algorithm to the cloud image obtained in the first step to realize cloud cluster knowledge. Finally, using the method of spectral threshold recognition and texture feature recognition in the steps of cloud clusters, thunderstorm cloud clusters are quickly and accurately identified. The experimental results show that cluster analysis has high research and application value in the segmentation processing of meteorological satellite cloud images.

Ying Li, Jianbo Li, Jianwei Chen, Minchao Lu and Caoyuan Li (2018): Seed Selection for Data Offloading Based on Social and Interest Graphs, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.571-587

Keywords

Mobile social network, social data offloading, extreme value model, Gaussian graphical model.

Abstract

The explosive growth of mobile data demand is becoming an increasing burden on current cellular network. To address this issue, we propose a solution of opportunistic data offloading for alleviating overloaded cellular traffic. The principle behind it is to select a few important users as seeds for data sharing. The three critical steps are detailed as follows. We first explore individual interests of users by the construction of user profiles, on which an interest graph is built by Gaussian graphical modeling. We then apply the extreme value theory to threshold the encounter duration of user pairs. So, a contact graph is generated to indicate the social relationships of users. Moreover, a contact-interest graph is developed on the basis of the social ties and individual interests of users. Corresponding on different graphs, three strategies are finally proposed for seed selection in an aim to maximize overloaded cellular data. We evaluate the performance of our algorithms by the trace data of real-word mobility. It demonstrates the effectiveness of the strategy of taking social relationships and individual interests into account.

Jian Xu, Zhihao Jiang, Andi Wang, Chen Wang and Fucai Zhou (2018): Dynamic Proofs of Retrievability Based on Partitioning-Based Square Root Oblivious RAM, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.589-602

Keywords

Cloud storage, proofs of retrievability, partitioning framework, oblivious RAM.

Abstract

With the development of cloud storage, the problem of efficiently checking and proving data integrity needs more consideration. Therefore, much of growing interest has been pursed in the context of the integrity verification of cloud storage. Provable data possession (PDP) and Proofs of retrievablity (POR) are two kinds of important scheme which can guarantee the data integrity in the cloud storage environments. The main difference between them is that POR schemes store a redundant encoding of the client data on the server so as to she has the ability of retrievablity while PDP does not have. Unfortunately, most of POR schemes support only static data. Stefanov et al. proposed a dynamic POR, but their scheme need a large of amount of client storage and has a large audit cost. Cash et al. use Oblivious RAM (ORAM) to construct a fully dynamic POR scheme, but the cost of their scheme is also very heavy. Based on the idea which proposed by Cash, we propose dynamic proofs of retrievability via Partitioning-Based Square Root Oblivious RAM (DPoR-PSR-ORAM). Firstly, the notions used in our scheme are defined. The Partitioning-Based Square Root Oblivious RAM (PSR-ORAM) protocol is also proposed. The DPOR-PSR-ORAM Model which includes the formal definitions, security definitions and model construction methods are described in the paper. Finally, we give the security analysis and efficiency analysis. The analysis results show that our scheme not only has the property of correctness, authenticity, next-read pattern hiding and retrievabiltiy, but also has the high efficiency.

Suzhen Wang, Lu Zhang, Yanpiao Zhang, Jieli Sun, Chaoyi Pang, Gang Tian and Ning Cao (2018): Natural Language Semantic Construction Based on Cloud Database, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.603-619

Keywords

Natural language, cloud database, semantic construction.

Abstract

Natural language semantic construction improves natural language comprehension ability and analytical skills of the machine. It is the basis for realizing the information exchange in the intelligent cloud-computing environment. This paper proposes a natural language semantic construction method based on cloud database, mainly including two parts: natural language cloud database construction and natural language semantic construction. Natural Language cloud database is established on the CloudStack cloud-computing environment, which is composed by corpus, thesaurus, word vector library and ontology knowledge base. In this section, we concentrate on the pretreatment of corpus and the presentation of background knowledge ontology, and then put forward a TF-IDF and word vector distance based algorithm for duplicated webpages (TWDW). It raises the recognition efficiency of repeated web pages. The part of natural language semantic construction mainly introduces the dynamic process of semantic construction and proposes a mapping algorithm based on semantic similarity (MBSS), which is a bridge between Predicate-Argument (PA) structure and background knowledge ontology. Experiments show that compared with the relevant algorithms, the precision and recall of both algorithms we propose have been significantly improved. The work in this paper improves the understanding of natural language semantics, and provides effective data support for the natural language interaction function of the cloud service.

Jifeng Zhong, Zhihao Liu and Juan Xu (2018): Analysis and Improvement of an Efficient Controlled Quantum Secure Direct Communication and Authentication Protocol, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.621-633

Keywords

Quantum cryptography, controlled quantum secure direct communication, selective-CNOT-operation attack.

Abstract

The controlled quantum secure direct communication (CQSDC) with authentication protocol based on four particle cluster states via quantum one-time pad and local unitary operations is cryptanalyzed. It is found that there are some serious security issues in this protocol. An eavesdropper (Eve) can eavesdrop on some information of the identity strings of the receiver and the controller without being detected by the selective-CNOT-operation (SCNO) attack. By the same attack, Eve can also steal some information of the secret message that the sender transmits. In addition, the receiver can take the same kind of attack to eavesdrop on some information of the secret message out of the control of the controller. This means that the requirements of CQSDC are not satisfied. At last, we improve the original CQSDC protocol to a secure one.

Changting Shi (2018): A Novel Ensemble Learning Algorithm Based on D-S Evidence Theory for IoT Security, CMC: Computers, Materials & Continua, Vol.57 No.3 ,pp.635-652

Keywords

IoT security, physical-layer security, radio frequency fingerprinting, random Forest, evidence theory.

Abstract

In the last decade, IoT has been widely used in smart cities, autonomous driving and Industry 4.0, which lead to improve efficiency, reliability, security and economic benefits. However, with the rapid development of new technologies, such as cognitive communication, cloud computing, quantum computing and big data, the IoT security is being confronted with a series of new threats and challenges. IoT device identification via Radio Frequency Fingerprinting (RFF) extracting from radio signals is a physical-layer method for IoT security. In physical-layer, RFF is a unique characteristic of IoT device themselves, which can difficultly be tampered. Just as people’s unique fingerprinting, different IoT devices exhibit different RFF which can be used for identification and authentication. In this paper, the structure of IoT device identification is proposed, the key technologies such as signal detection, RFF extraction, and classification model is discussed. Especially, based on the random forest and Dempster-Shafer evidence algorithm, a novel ensemble learning algorithm is proposed. Through theoretical modeling and experimental verification, the reliability and differentiability of RFF are extracted and verified, the classification result is shown under the real IoT device environments.

Vol. 54, No. 1, 2018

Puneet Kumar and J. Srinivas: Three Phase Composite Cylinder Assemblage Model for Analyzing the Elastic Behavior of MWCNT-Reinforced Polymers, CMC: Computers, Materials & Continua, Vol. 54, No. 1, pp.001-020, 2018

Keywords

Multi-walled carbon nanotube, composite cylinder assemblage, continuum, representative volume element, variable interphase.

Abstract

Evolution of computational modeling and simulation has given more emphasis on the research activities related to carbon nanotube (CNT) reinforced polymer composites recently. This paper presents the composite cylinder assemblage (CCA) approach based on continuum mechanics for investigating the elastic properties of a polymer resin reinforced by multi-walled carbon nanotubes (MWCNTs). A three-phase cylindrical representative volume element (RVE) model is employed based on CCA technique to elucidate the effects of inter layers, chirality, interspacing, volume fraction of MWCNT, interphase properties and temperature conditions on the elastic modulus of the composite. The interface region between CNT and polymer matrix is modeled as the third phase with varying material properties. The constitutive relations for each material system have been derived based on solid mechanics and proper interfacial traction continuity conditions are imposed. The predicted results from the CCA approach are in well agreement with RVE-based finite element model. The outcomes reveal that temperature softening effect becomes more pronounced at higher volume fractions of CNTs.

Chunguang Li, Cuihua Li, Cong Sun and Hong Zheng: Lower Bound Limit Analysis of Anisotropic Soils, CMC: Computers, Materials & Continua, Vol. 54, No. 1, pp.021-041 , 2018

Keywords

Limit analysis, lower bound, finite element, anisotropy.

Abstract

Previous approaches can only tackle anisotropic problems with cohesion varying with direction. A novel linearization of the Mohr-Coulomb yield criterion associated with plane strain problem has been achieved by simulating the Mohr’s circle with orientation lines in σ-τ space, which allows for lower bound solution of soils with cohesion and friction coefficient varying with direction. The finite element lower limit analysis formulation using the modified anisotropic yield criterion is then developed. Several examples are given to illustrate the capability and effectiveness of the proposed numerical procedure for computing rigorous lower bounds for anisotropic soils.

Yi Xue, Faning Dang, Rongjian Li, Liuming Fan, Qin Hao, Lin Mu and Yuanyuan Xia: Seepage-Stress-Damage Coupled Model of Coal Under Geo-Stress Influence, CMC: Computers, Materials & Continua, Vol. 54, No. 1, pp.043-059 , 2018

Keywords

Permeability, porosity, gas pressure, damage, coupled model.

Abstract

In the seepage-stress-damage coupled process, the mechanical properties and seepage characteristics of coal are distinctly different between pre-peak stage and post-peak stage. This difference is mainly caused by damage of coal. Therefore, in the process of seepage and stress analysis of coal under the influence of excavation or mining, we need to consider the weakening of mechanical properties and the development of fractures of damaged coal. Based on this understanding, this paper analyzes the influence of damage on mechanics and seepage behavior of coal. A coupled model is established to analyze the seepage-stress-damage coupled process of coal. This model implemented into COMSOL and MATLAB software to realize the numerical solving. Two examples are adopted to verify the correctness of the model and some useful conclusions are obtained. The numerical model establishes the relationship between microcosmic damage evolution and macroscopical fracture and simulates the whole process of coal from microcosmic damage to macroscopical fracture, and the dynamic simulation of fluid flow in this process. It provides a numerical tool for further research on the seepage-stress-damage analysis.

Surkay D. Akbarov and Mahir A. Mehdiyev: The Interface Stress Field in the Elastic System Consisting of the Hollow Cylinder and Surrounding Elastic Medium Under 3D Non-axisymmetric Forced Vibration, CMC: Computers, Materials & Continua, Vol. 54, No. 1, pp.061-081 , 2018

Keywords

Interface stress field, frequency response, hollow cylinder, elastic medium, forced vibration.

Abstract

The paper develops and employs analytical-numerical solution method for the study of the time-harmonic dynamic stress field in the system consisting of the hollow cylinder and surrounding elastic medium under the non-axisymmetric forced vibration of this system. It is assumed that in the interior of the hollow cylinder the point-located with respect to the cylinder axis, non-axisymmetric with respect to the circumferential direction and uniformly distributed time-harmonic forces act. Corresponding boundary value problem is solved by employing of the exponential Fourier transformation with respect to the axial coordinate and by employing of the Fourier series expansion of these transformations. Numerical results on the frequency response of the interface normal stresses are presented and discussed.

G. Jayaprakash M. P. Muthuraj: Prediction of Compressive Strength of Various SCC Mixes Using Relevance Vector Machine, CMC: Computers, Materials & Continua, Vol. 54, No. 1, pp. 083-102, 2018

Keywords

Relevance Vector Machine, Self-compacting concrete, Compressive strength, Variance.

Abstract

This paper discusses the applicability of relevance vector machine (RVM) based regression to predict the compressive strength of various self compacting concrete (SCC) mixes. Compressive strength data various SCC mixes has been consolidated by considering the effect of water cement ratio, water binder ratio and steel fibres. Relevance vector machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM has an identical functional form to the support vector machine, but provides probabilistic classification and regression. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 75% of the data has been used for development of model and 30% of the data is used for validation. The predicted compressive strength for SCC mixes is found to be in very good agreement with those of the corresponding experimental observations available in the literature.

Vol. 54, No. 2

M. Ozisik, M. A. Mehdiyev and S. D. Akbarov: The Influence of the Imperfectness of Contact Conditions on the Critical Velocity of the Moving Load Acting in the Interior of the Cylinder Surrounded with Elastic Medium, CMC: Computers, Materials & Continua, Vol. 54, No. 2, pp.103-136 , 2018

Keywords

Moving internal pressure, critical velocity, circular hollow cylinder surrounded by elastic medium, shear-spring type imperfection, interface stresses.

Abstract

The dynamics of the moving-with-constant-velocity internal pressure acting on the inner surface of the hollow circular cylinder surrounded by an infinite elastic medium is studied within the scope of the piecewise homogeneous body model by employing the exact field equations of the linear theory of elastodynamics. It is assumed that the internal pressure is point-located with respect to the cylinder axis and is axisymmetric in the circumferential direction. Moreover, it is assumed that shear-spring type imperfect contact conditions on the interface between the cylinder and surrounding elastic medium are satisfied. The focus is on the influence of the mentioned imperfectness on the critical velocity of the moving load and this is the main contribution and difference of the present paper the related other ones. The other difference of the present work from the related other ones is the study of the response of the interface stresses to the load moving velocity, distribution of these stresses with respect to the axial coordinates and to the time. At the same time, the present work contains detail analyses of the influence of problem parameters such as the ratio of modulus of elasticity, the ratio of the cylinder thickness to the cylinder radius, and the shear-spring type parameter which characterizes the degree of the contact imperfection on the values of the critical velocity and stress distribution. Corresponding numerical results are presented and discussed. In particular, it is established that the values of the critical velocity of the moving pressure decrease with the external radius of the cylinder under constant thickness of that.

Zhengzheng Cao, Ping Xu, Zhenhua Li, Minxia Zhang, Yu Zhao and Wenlong Shen: Joint Bearing Mechanism of Coal Pillar and Backfilling Body in Roadway Backfilling Mining Technology, CMC: Computers, Materials & Continua, Vol. 54, No. 2, pp. 137-159 , 2018

Keywords

Roadway backfilling mining technology, coal pillar, backfilling body, joint bearing mechanism, energy variation principle.

Abstract

In the traditional mining technology, the coal resources trapped beneath surface buildings, railways, and water bodies cannot be mined massively, thereby causing the lower coal recovery and dynamic disasters. In order to solve the aforementioned problems, the roadway backfilling mining technology is developed and the joint bearing mechanism of coal pillar and backfilling body is presented in this paper. The mechanical model of bearing system of coal pillar and backfilling body is established, by analyzing the basic characteristics of overlying strata deformation in roadway backfilling mining technology. According to the Ritz method in energy variation principle, the elastic solution expression of coal pillar deformation is deduced in roadway backfilling mining technology. Based on elastic-viscoelastic correspondence principle, combining with the burgers rheological constitutive model and Laplace transform theory, the viscoelastic solution expression of coal pillar deformation is obtained in roadway backfilling mining technology. By analyzing the compressive mechanical property of backfilling body, the time formula required for coal pillar and backfilling body to play the joint bearing function in roadway backfilling mining technology is obtained. The example analysis indicates that the time is 140 days. The results can be treated as an important basis for theoretical research and process design in roadway backfilling mining technology.

Y. A. Amer, A. M. S. Mahdy and E. S. M. Youssef: Solving Fractional Integro-Differential Equations by Using Sumudu Transform Method and Hermite Spectral Collocation Method, CMC: Computers, Materials & Continua, Vol. 54, No. 2, pp. 161-180 , 2018

Keywords

Caputo derivative, integro-differential equations, hermite polynomials, sumudu transform.

Abstract

In this paper we are looking forward to finding the approximate analytical solutions for fractional integro-differential equations by using Sumudu transform method and Hermite spectral collocation method. The fractional derivatives are described in the Caputo sense. The applications related to Sumudu transform method and Hermite spectral collocation method have been developed for differential equations to the extent of access to approximate analytical solutions of fractional integro-differential equations.

Muhammad Shoaib Arif, Mairaj Bibi and Adnan Jhangir: Solution of Algebraic Lyapunov Equation on Positive-Definite Hermitian Matrices by Using Extended Hamiltonian Algorithm, CMC: Computers, Materials & Continua, Vol. 54, No. 2, pp.181-195 , 2018

Keywords

Information geometry, algebraic lyapunov equation, positive-definite Hermitian matrix manifold, natural gradient algorithm, extended hamiltonian algorithm.

Abstract

This communique is opted to study the approximate solution of the Algebraic Lyapunov equation on the manifold of positive-definite Hermitian matrices. We choose the geodesic distance between -AHX - XA and P as the cost function, and put forward the Extended Hamiltonian algorithm (EHA) and Natural gradient algorithm (NGA) for the solution. Finally, several numerical experiments give you an idea about the effectiveness of the proposed algorithms. We also show the comparison between these two algorithms EHA and NGA. Obtained results are provided and analyzed graphically. We also conclude that the extended Hamiltonian algorithm has better convergence speed than the natural gradient algorithm, whereas the trajectory of the solution matrix is optimal in case of Natural gradient algorithm (NGA) as compared to Extended Hamiltonian Algorithm (EHA). The aim of this paper is to show that the Extended Hamiltonian algorithm (EHA) has superior convergence properties as compared to Natural gradient algorithm (NGA). Upto the best of author’s knowledge, no approximate solution of the Algebraic Lyapunov equation on the manifold of positive-definite Hermitian matrices is found so far in the literature.

Yi Cao, Zhili Zhou, Xingming Sun and Chongzhi Gao: Coverless Information Hiding Based on the Molecular Structure Images of Material, CMC: Computers, Materials & Continua, Vol. 54, No. 2, pp.197-207 , 2018

Keywords

Coverless information hiding, molecular structure images of material, pixel value, inverted index, image retrieval, bag of words model.

Abstract

The traditional information hiding methods embed the secret information by modifying the carrier, which will inevitably leave traces of modification on the carrier. In this way, it is hard to resist the detection of steganalysis algorithm. To address this problem, the concept of coverless information hiding was proposed. Coverless information hiding can effectively resist steganalysis algorithm, since it uses unmodified natural stego-carriers to represent and convey confidential information. However, the state-of-the-arts method has a low hidden capacity, which makes it less appealing. Because the pixel values of different regions of the molecular structure images of material (MSIM) are usually different, this paper proposes a novel coverless information hiding method based on MSIM, which utilizes the average value of sub-image’s pixels to represent the secret information, according to the mapping between pixel value intervals and secret information. In addition, we employ a pseudo-random label sequence that is used to determine the position of sub-images to improve the security of the method. And the histogram of the Bag of words model (BOW) is used to determine the number of sub-images in the image that convey secret information. Moreover, to improve the retrieval efficiency, we built a multi-level inverted index structure. Furthermore, the proposed method can also be used for other natural images. Compared with the state-of-the-arts, experimental results and analysis manifest that our method has better performance in anti-steganalysis, security and capacity.

Vol. 54, No. 3

Ying Xiao, Haomiao Zhou and Xiaofan Gou: A Nonlinear Magneto-Mechanical Coupled Constitutive Model for the Magnetostrictive Material Galfenol, CMC: Computers, Materials & Continua, Vol. 54, No. 3, pp.209-228 , 2018

Keywords

Magnetostrictive materials, one-dimensional constitutive relations, galfenol rods, nonlinear magneto-mechanical coupling.

Abstract

In order to predict the performance of magnetostrictive smart material and push its applications in engineering, it is necessary to build the constitutive relations for the magnetostrictive material Galfenol. For Galfenol rods under the action of the pre-stress and magnetic field along the axial direction, the one-dimensional nonlinear magneto-mechanical coupling constitutive model is proposed based on the elastic Gibbs free energy, where the Taylor expansion of the elastic Gibbs free energy is made to obtain the polynomial forms. And then the constitutive relations are derived by replacing the polynomial forms with the proper transcendental functions based on the microscopic magneto-mechanical coupling mechanism. From the perspective of microscopic mechanism, the nonlinear strain related to magnetic domain rotation results in magnetostrictive strain changing with the pre-stress among the elastic strains induced by the pre-stress. By comparison, the predicted stress-strain, magnetostrictive strain, magnetic induction and magnetization curves agreed well with experimental results under the different pre-stresses. The proposed model can describe not only the influences of pre-stress on magnetostrictive strain and magnetization curves, but also nonlinear magneto-mechanical coupling effect of magnetostrictive material systematically, such as the Young’s modulus varying with stress and magnetic field. In the proposed constitutive model, the key material constants are not chosen to obtain a good fit with the experimental data, but are measured directly by experiments, such as the saturation magnetization, saturation magnetostrictive coefficient, saturation Young’s modulus, linear magnetic susceptibility and so on. In addition, the forms of the new constitutive relations are simpler than the existing constitutive models. Therefore, this model could be applied conveniently in the engineering applications.

H. S. Abdel-Aziz and M. Khalifa Saad: On Special Curves According to Darboux Frame in the Three Dimensional Lorentz Space, CMC: Computers, Materials & Continua, Vol. 54, No. 3, pp. 229-249 , 2018

Keywords

Smarandache curves, spacelike curve, timelike surface, Darboux frame.

Abstract

In the light of great importance of curves and their frames in many different branches of science, especially differential geometry as well as geometric properties and the uses in various fields, we are interested here to study a special kind of curves called Smarandache curves in Lorentz 3-space. Then, we present some characterizations for these curves and calculate their Darboux invariants. Moreover, we classify TP, TU, PU and TPU-Smarandache curves of a spacelike curve according to the causal character of the vector, curve and surface used in the study. Besides, we give some of differential geometric properties and important relations between that curves. Finally, to demonstrate our theoretical results a computational example is given with graph.

P. PattunnaRajam, Reeba korah and G. Maria Kalavathy: Test Vector Optimization Using Pocofan-Poframe Partitioning, CMC: Computers, Materials & Continua, Vol. 54, No. 3, pp.251-268 , 2018

Keywords

Pseudo exhaustive testing, POCOFAN (Primary Output Cone Fanout Partitioning), POFRAME partitioning, combinational digital VLSI circuit testing, critical path delay, testing time, design for testability.

Abstract

This paper presents an automated POCOFAN-POFRAME algorithm that partitions large combinational digital VLSI circuits for pseudo exhaustive testing. In this paper, a simulation framework and partitioning technique are presented to guide VLSI circuits to work under with fewer test vectors in order to reduce testing time and to develop VLSI circuit designs. This framework utilizes two methods of partitioning Primary Output Cone Fanout Partitioning (POCOFAN) and POFRAME partitioning to determine number of test vectors in the circuit. The key role of partitioning is to identify reconvergent fanout branch pairs and the optimal value of primary input node N and fanout F partitioning using I-PIFAN algorithm. The number of reconvergent fanout and its locations are critical for testing of VLSI circuits and design for testability. Hence, their selection is crucial in order to optimize system performance and reliability. In the present work, the design constraints of the partitioned circuit considered for optimization includes critical path delay and test time. POCOFAN-POFRAME algorithm uses the parameters with optimal values of circuits maximum primary input cone size (N) and minimum fan-out value (F) to determine the number of test vectors, number of partitions and its locations. The ISCAS’85 benchmark circuits have been successfully partitioned, the test results of C499 shows 45% reduction in the test vectors and the experimental results are compared with other partitioning methods, our algorithm makes fewer test vectors.

Chuanrong Wu, Evgeniya Zapevalova, Yingwu Chen and Feng Li: Time Optimization of Multiple Knowledge Transfers in the Big Data Environment, CMC: Computers, Materials & Continua, Vol. 54, No. 3, pp.269-285 , 2018

Keywords

Big data, knowledge transfer, time optimization, DEP, simulation experiment.

Abstract

In the big data environment, enterprises must constantly assimilate big data knowledge and private knowledge by multiple knowledge transfers to maintain their competitive advantage. The optimal time of knowledge transfer is one of the most important aspects to improve knowledge transfer efficiency. Based on the analysis of the complex characteristics of knowledge transfer in the big data environment, multiple knowledge transfers can be divided into two categories. One is the simultaneous transfer of various types of knowledge, and the other one is multiple knowledge transfers at different time points. Taking into consideration the influential factors, such as the knowledge type, knowledge structure, knowledge absorptive capacity, knowledge update rate, discount rate, market share, profit contributions of each type of knowledge, transfer costs, product life cycle and so on, time optimization models of multiple knowledge transfers in the big data environment are presented by maximizing the total discounted expected profits (DEPs) of an enterprise. Some simulation experiments have been performed to verify the validity of the models, and the models can help enterprises determine the optimal time of multiple knowledge transfer in the big data environment.

Mahesh S. Shinde and Kishor M. Ashtankar: Effect of Different Shapes of Conformal Cooling Channel on the Parameters of Injection Molding, CMC: Computers, Materials & Continua, Vol. 54, No. 3, pp.287-306 , 2018

Keywords

Injection mold, conformal cooling channels, cooling simulation, rapid tooling.

Abstract

Cooling system improvement is important in injection molding to get better quality and productivity. The aim of this paper was to compare the different shapes of the conformal cooling channels (CCC) with constant surface area and CCC with constant volume in injection molding using Mold-flow Insight 2016 software. Also the CCC results were compared with conventional cooling channels. Four different shapes of the CCC such as circular, elliptical, rectangular and semi-circular were proposed. The locations of the cooling channels were also kept constant. The results in terms of cooling time, cycle time reduction and improvement in quality of the product shows that no significant effect of CCC’s shapes when surface area of CCC kept constant. On the other hand the rectangular CCC shows better result as compared to other shapes of CCC when volume of CCC were kept constant.

Papers of 2017

1. U. Babuscu Yesil: Forced and Natural Vibrations of an Orthotropic Pre-Stressed Rectangular Plate with Neighboring Two Cylindrical Cavities. CMC: Computers, Materials & Continua, Vol. 53, No. 1, pp. 1-22, 2017

Keywords: Initial stresses, vibration, cylindrical cavities, 3D FEM, orthotropic material.

Abstract: Forced and natural vibrations of a rectangular pre-stressed orthotropic composite plate containing two neighboring cylindrical cavities whose cross sections are rectangular with rounded-off corners are investigated numerically. It is assumed that all the end surfaces of the rectangular pre-stressed composite plate are simply supported and subjected to a uniformly distributed normal time-harmonic force on the upper face plane. The considered problem is formulated within the Three-Dimensional Linearized Theory of Elastic Waves in Initially Stressed Bodies (TDLTEWISB). The influence of mechanical and geometrical parameters as well as the initial stresses and the effect of cylindrical cavities on the dynamical characteristics of the rectangular orthotropic composite plate are analyzed and discussed.

2. Jaideep Kaur and Kamaljit Kaur: A Fuzzy Approach for an IoT-based Automated Employee Performance Appraisal. CMC: Computers, Materials & Continua, Vol. 53, No. 1, pp. 23-36, 2017

Keywords: Employee Performance appraisal, fuzzy logic, internet of things (IoT), cognitive decision making.

Abstract: The ubiquitous Internet of Things (IoT) through RFIDs, GPS, NFC and other wireless devices is capable of sensing the activities being carried around Industrial environment so as to automate industrial processes. In almost every industry, employee performance appraisal is done manually which may lead to favoritisms. This paper proposes a framework to perform automatic employee performance appraisal based on data sensed from IoT. The framework classifies raw IoT data into three activities (Positive, Negative, Neutral), co-locates employee and activity in order to calculate employee implication and then performs cognitive decision making using fuzzy logic. From the experiments carried out it is observed that automatic system has improved performance of employees. Also the impact of the proposed system leads to motivation among employees. The simulation results show how fuzzy approach can be exploited to reward or penalize employees based on their performance.

3. R. Praveena and S. Nirmala: Bus Encoded LUT Multiplier for Portable Biomedical Therapeutic Devices. CMC: Computers, Materials & Continua,Vol. 53, No. 1, pp. 37-47, 2017

Keywords: Constant coefficient multipliers, Reduced coefficient multipliers, Bus encoding, DSP SoC, Look up table, Barrel shifter, Pre processing.

Abstract: DSP operation in a Biomedical related therapeutic hardware need to be performed with high accuracy and with high speed. Portable DSP hardware’s like pulse/heart beat detectors must perform with reduced operational power due to lack of conventional power sources. This work proposes a hybrid biomedical hardware chip in which the speed and power utilization factors are greatly improved. Multipliers are the core operational unit of any DSP SoC. This work proposes a LUT based unsigned multiplication which is proven to be efficient in terms of high operating speed. For n bit input multiplication n*n memory array of 2n bit size is required to memorize all the possible input and output combination. Various literature works claims to be achieve high speed multiplication with reduced LUT size by integrating a barrel shifter mechanism. This paper work address this problem, by reworking the multiplier architecture with a parallel operating pre-processing unit which used to change the multiplier and multiplicand order with respect to the number of computational addition and subtraction stages required. Along with LUT multiplier a low power bus encoding scheme is integrated to limit the power constraint of the on chip DSP unit. This paper address both the speed and power optimization techniques and tested with various FPGA device families.

4. A. M. Abd-Alla, Aftab Khan and S. M. Abo-Dahab: Rotational Effect on thermoelastic Stoneley, Love and Rayleigh waves in Fibre-reinforced Anisotropic General Viscoelastic Media of Higher Order. CMC: Computers, Materials & Continua, Vol. 53, No. 1, pp. 49-72, 2017

Keywords: Fibre-reinforced, viscoelastic, surface waves, rotation, anisotropic, thermoelastic.

Abstract: In this paper, we investigated the propagation of the rmo elastic surface waves in fibre-reinforced anisotropic general viscoelastic media of higher order ofnth order, including time rate of strain under the influence of rotation.The general surface wave speed is derived to study the effects of rotation and thermal on surface waves. Particular cases for Stoneley, Love and Rayleigh waves are discussed. The results obtained in this investigation are more general in the sense that some earlier published results are obtained from our result as special cases. Our results for viscoelastic of order zero are well agreed to fibre-reinforced materials. Comparison was made with the results obtained in the presence and absence of rotation and parameters for fibre-reinforced of the material medium. It is also observed that, surface waves cannot propagate in a fast rotating medium. Numerical results for particular materials are given and illustrated graphically. The results indicate that the effect of rotation on fibre-reinforced anisotropic general viscoelastic media are very pronounced.

5. Junhui Meng and Mingyun Lv: The Constitutive Relation of a Fabric Membrane Composite for a Stratospheric Airship Envelope Based on Invariant Theory. CMC: Computers, Materials & Continua, Vol. 53, No. 2, pp. 73-89, 2017

Keywords: Stratospheric airship; Fabric membrane composite; Constitutive relation; Invariant theory; Viscoelasticity

Abstract: The study of stratospheric airships has become the focus in many countries in recent years, because of its potential applications in many fields. Lightweight and high strength envelopes are the keys to the design of stratospheric airships, as it directly determines the endurance flight performance and loading deformation characteristics of the airship. A typical envelope of any stratospheric airship is a coated-fabric material which is composed of a fiber layer and several functional membrane layers. According to composite structure, nonlinearity and viscoelasticity are the two main characteristics of such envelope. Based on the analysis on the interaction between the different components in the micro-mechanical model of the coated-fabric, several invariant values reflecting the characteristics of the envelope material are obtained according to invariant theory. Furthermore, the constitutive equation that describes the viscoelasticity of the envelope material is derived. The constitutive equation can represent both the individual roles of the warp and weft fibers, and their further coupled interactions. The theoretical computation results were verified by off-axial tension tests. The results can help gain a deeper understanding of the mechanical mechanism and provide a reference for structural design of envelope material.

6. Ravikumar Gurusamy and Dr Vijayan Subramaniam: A Machine Learning Approach for MRI Brain Tumor Classification. CMC: Computers, Materials & Continua, Vol. 53, No. 2, pp. 91-108, 2017

Keywords: MRI image, brain pathology, K-Means algorithm, Feature extraction, Wavelet transform, SVM, Neural network, K nearest algorithm.

Abstract: A new method for the denoising, extraction and tumor detection on MRI images is presented in this paper. MRI images help physicians study and diagnose diseases or tumors present in the brain. This work is focused towards helping the radiologist and physician to have a second opinion on the diagnosis. The ambiguity of Magnetic Resonance (MR) image features is solved in a simpler manner. The MRI image acquired from the machine is subjected to analysis in the work. The real-time data is used for the analysis. Basic preprocessing is performed using various filters for noise removal. The de-noised image is segmented, and the feature extractions are performed. Features are extracted using the wavelet transform. When compared to other methods, the wavelet transform is more suitable for MRI image feature extraction. The features are given to the classifier which uses binary tree support vectors for classification. The classification process is compared with conventional methods.

7. L.S. Melro and L.R. Jensen: Influence of functionalization on the structural and mechanical properties of grapheme. CMC: Computers, Materials & Continua,Vol. 53, No. 2, pp. 109-127, 2017

Keywords: Functionalization, graphene, molecular dynamics, Young’s modulus, structural properties

Abstract: Molecular dynamics simulations were applied in order to calculate the Young’s modulus of graphene functionalized with carboxyl, hydroxyl, carbonyl, hydrogen, methyl, and ethyl groups. The influence of the grafting density with percentages of 3, 5, 7, and 10% and the type of distribution as a single cluster or several small clusters were also studied. The results show that the elastic modulus is dependent on the type of functional groups. The increasing coverage density also evidenced a decrease of the Young’s modulus, and the organization of functional groups as single cluster showed a lesser impact than for several small clusters. Furthermore, the bond length and angle distribution probability analyses reveal that lengths and angles are affected with increasing functionalization suggesting more out-of-plane displacements of the carbon atoms within the graphene structure.

8. A.M. Farhan: Effect of Rotation on the Propagation of Waves in Hollow Poroelastic Circular Cylinder with Magnetic Field. CMC: Computers, Materials & Continua, Vol. 53, No. 2, pp. 129-156, 2017

Keywords: Wave propagation, Rotation, Magnetic field, Poroelastic medium, Natural frequency.

Abstract: Employing Biot’s theory of wave propagation in liquid saturated porous media, the effect of rotation and magnetic field on wave propagation in a hollow poroelastic circular of infinite extent are investigated. An exact closed form solution is presented. General frequency equations for propagation of poroelastic cylinder are obtained when the boundaries are stress free. The frequencies are calculated for poroelastic cylinder for different values of magnetic field and rotation. Numerical results are given and illustrated graphically. The results indicate that the effect of rotation, and magnetic field are very pronounced. Such a model would be useful in large-scale parametric studies of mechanical response.

9. Susom Dutta, A. Ramachandra Murthy, Dookie Kim and Pijush Samui: Prediction of Compressive Strength of Self-Compacting Concrete Using Intelligent Computational Modeling. CMC: Computers, Materials & Continua, Vol. 53, No. 2, pp. 157-174, 2017

Keywords: Self Compacting Concrete (SCC), Compressive Strength, Extreme Learning Machine (ELM), Adaptive Neuro Fuzzy Inference System (ANFIS), Multi Adaptive Regression Spline (MARS).

Abstract: In the present scenario, computational modeling has gained much importance for the prediction of the properties of concrete. This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete (SCC). Three models, namely, Extreme Learning Machine (ELM), Adaptive Neuro Fuzzy Inference System (ANFIS) and Multi Adaptive Regression Spline (MARS) have been employed in the present study for the prediction of compressive strength of self compacting concrete. The contents of cement (c), sand (s), coarse aggregate (a), fly ash (f), water/powder (w/p) ratio and superplasticizer (sp) dosage have been taken as inputs and 28 days compressive strength (fck) as output for ELM, ANFIS and MARS models. A relatively large set of data including 80 normalized data available in the literature has been taken for the study. A comparison is made between the results obtained from all the above-mentioned models and the model which provides best fit is established. The experimental results demonstrate that proposed models are robust for determination of compressive strength of self-compacting concrete.

10. Zhengzheng Cao, Feng Du, Ping Xu, Haixiao Lin, Yi Xue, Yuejin Zhou: Control Mechanism of Surface Subsidence and Overburden Movement in Backfilling Mining based on Laminated Plate Theory. CMC: Computers, Materials & Continua, Vol. 53, No. 3, pp.175-186 , 2017

Keywords: symmetrical laminated plate theory, surface subsidence, overburden movement, backfilling mining.

Abstract: The backfilling mining technology is a type of high-efficiency coal mining technology that is used to address the environmental issues caused by the caving mining technology. In this paper, the mechanical model of symmetrical laminated plate representing the overburden movement caused by the backfilling mining technology is established, and the governing differential equation of the motion of the overburden is derived. The boundary conditions of the mechanical model are put forward, and the analytical solution of the overburden movement and surface subsidence is obtained. The numerical model of the overburden movement and surface subsidence, under mining with backfilling, is established by means of the FLAC3D numerical software, which aims to systematically study the influence of backfilling compactness, mining thickness, and mining depth on the overburden movement and surface subsidence in backfilling mining. When the compactness η is less than 70%, the overburden movement and surface subsidence is greater, while when η is greater than 70%, the overburden movement and surface subsidence is reduced significantly. On this basis, the control mechanism of surface subsidence and overburden movement in backfilling mining is obtained. The suitable backfilling compactness is the key to controlling surface subsidence and overburden movement in backfilling mining.

11. Xue-cong Liu, Qing Zhang, Xiao-zhou Xia: The Stable Explicit Time Stepping Analysis with a New Enrichment Scheme by XFEM. CMC: Computers, Materials & Continua, Vol. 53, No. 3, pp.187-206,2017

Keywords: XFEM, DSIF, Newmark scheme, Time stepping, Stability.

Abstract: This paper focuses on the study of the stability of explicit time integration algorithm for dynamic problem by the Extended Finite Element Method (XFEM). A new enrichment scheme of crack tip is proposed within the framework of XFEM. Then the governing equations are derived and evolved into the discretized form. For dynamic problem, the lumped mass and the explicit time algorithm are applied. With different grid densities and different forms of Newmark scheme, the Dynamic Stress Intensity Factor (DSIF) is computed by using interaction integral approach to reflect the dynamic response. The effectiveness of the proposed scheme is demonstrated through the numerical examples, and the critical time stepping in different situations are listed and analyzed to illustrate the factors that affect the numerical stability.

12. Mahesh S. Shinde, and Kishor M. Ashtankar: Cycle Time Reduction in Injection Molding by Using Milled Groove Conformal Cooling. CMC: Computers, Materials & Continua, Vol. 53, No. 3, pp. 207-217 , 2017

Keywords: Injection mold, conformal cooling channels, cooling simulation, rapid tooling

Abstract: This paper presents simulation study on Milled Grooved conformal cooling channels (MGCCC) in injection molding. MGCCC has a more effective cooling surface area which helps to provide efficient cooling as compared to conventional cooling. A case study of Encloser part is investigated for cycle time reduction and quality improvement. The performance designs of straight drilled are compared with MGCCC by using Autodesk Moldflow Insight (AMI) 2016. The results show total 32.1% reduction of cooling time and 9.86% reduction of warpage in case of MGCCC as compared to conventional cooling.

13. Zihao Yang, Liang Ma, Qiang Ma, Junzhi Cui1, Yufeng Nie, Hao Dong, Xiaohong An: Multiscale Nonlinear Thermo-Mechanical Coupling Analysis of Composite Structures with Quasi-Periodic Properties. CMC: Computers, Materials & Continua, Vol. 53, No. 3, pp. 219-248 , 2017

Keywords: Thermo-mechanical coupling problem, quasi-periodic properties, multiscale asymptotic analysis, multiscale finite element-difference algorithm.

Abstract: This paper reports a multiscale analysis method to predict the thermo-mechanical coupling performance of composite structures with quasi-periodic properties. In these material structures, the configurations are periodic and the material coefficients are quasi-periodic, i.e., they depend not only on the microscale information but also on the macro location. Also, a mutual interaction between displacement and temperature fields is considered in the problem, which is our particular interest in this study. The multiscale asymptotic expansions of the temperature and displacement fields are constructed and associated error estimation in nearly pointwise sense is presented. Then, a finite element-difference algorithm based on the multiscale analysis method is brought forward in detail. Finally, some numerical examples are given. And the numerical results show that the multiscale method presented in this paper is effective and reliable to study the nonlinear thermo-mechanical coupling problem of composite structures with quasi-periodic properties.

14. Arzu Turan Dincel and Surkay D. Akbarov: Mathematical Modelling and 3D FEM Analysis of the Influence of Initial Stresses on the ERR in a Band Crack’s Front in the Rectangular Orthotropic Thick Plate. CMC: Computers, Materials & Continua, Vol. 53, No. 3, pp.249-270, 2017

Keywords: Band crack, energy release rate, stress intensity factor, initial stress, orthotropic material, rectangular plate, 3D FEM.

Abstract: This paper deals with the mathematical modelling and 3D FEM study of the energy release rate (ERR) in the band crack’s front contained in the orthotropic thick rectangular plate which is stretched or compressed initially before the loading of the crack's edge planes. The initial stretching or compressing of the plate causes uniformly distributed normal stress to appear acting in the direction which is parallel to the plane on which the band crack is located. After the appearance of the initial stress in the plate it is assumed that the crack's edge planes are loaded with additional uniformly distributed normal forces and the ERR caused with this additional loading is studied. The corresponding boundary value problem is formulated within the scope of the so-called 3D linearized theory of elasticity which allows the initial stress on the values of the ERR to be taken into consideration. Numerical results on the influence of the initial stress, anisotropy properties of the plate material, the crack’s length and its distance from the face planes of the plate on the values of the ERR, are presented and discussed. In particular, it is established that for the relatively greater length of the crack’s band, the initial stretching of the plate causes a decrease, but the initial compression causes an increase in the values of the ERR.

15. Haolong Chen, Bo Yu, Huanlin Zhou, Zeng Meng: Comparison of CS, CGM and CS-CGM for Prediction of Pipe’s Inner Surface in FGMs. CMC: Computers, Materials & Continua, Vol. 53, No. 4, pp.271-290 , 2017

Keywords: Inverse geometry problems; Transient heat conduction; Functionally graded materials;Cuckoo search algorithm; Conjugate gradient method.

Abstract: The cuckoo search algorithm (CS) is improved by using the conjugate gradient method(CGM), and the CS-CGM is proposed. The unknown inner boundary shapes are generated randomly and evolved by Lévy flights and elimination mechanism in the CS and CS-CGM. The CS, CGM and CS-CGM are examined for the prediction of a pipe’s inner surface. The direct problem is two-dimensional transient heat conduction in functionally graded materials (FGMs). Firstly, the radial integration boundary element method (RIBEM) is applied to solve the direct problem. Then the three methods are compared to identify the pipe’s inner surfacewith the information of measured temperatures. Finally, the influences of timepoints, measurement point number and random noise on the inverse results are investigated. It is found that the three algorithms are promising and can be used to identify the pipe’s inner surface. The CS-CGM has higher accuracy and faster convergencespeed than the CS and CGM. The CS and CS-CGMare insensitive to the initial values. The CGM and CS-CGM are more insensitive to the measurement noises compared with the CS. With the increase of timepointsand measurement points, and with the decrease of measurement noises, the inverse results are more accurate.

16. Subashini I, Smitha Gopinath and Aahrthy R: Low Velocity Impact Response and Failure Assessment of Textile Reinforced Concrete Slabs. CMC: Computers, Materials & Continua, Vol. 53, No. 4, pp.291-306 , 2017

Keywords: Textile reinforced concrete (TRC), FEM, low velocity impact, smoothed particle hydrodynamics (SPH), weibull distribution.

Abstract: Present paper proposes a methodology by combining finite element method with smoothed particle hydrodynamics to simulate the response of textile reinforced concrete (TRC) slabs under low velocity impact loading. For the constitutive modelling in the finite element method, the concrete damaged plasticity model was employed to the cementitious binder of TRC and Von-Mises criterion was used for the textile reinforcement. Strain dependent smoothed particle hydrodynamics (SPH) was used to assess the damage and failure pattern of TRC slabs. Numerical simulation was carried out on TRC slabs with two different volume fraction of glass textile reinforcement to predict the energy absorption and damage by coupling finite element method with SPH. Parametric studies were also conducted for simulating the effect of number of textile layers in TRC under impact. It is concluded that the proposed methodology well predicts the damage in TRC slabs at various locations. The results were also analysed using two parameter Weibull distribution and the impact failure strength is presented in terms of reliability function. The results indicated that the Weibull distribution allows describing the failure in terms of reliability and safety limits.

17. S.D. Akbarov and M. Negin: Generalized Rayleigh Wave Dispersion in a Covered Half-space Made of Viscoelastic Materials. CMC: Computers, Materials & Continua, Vol. 53, No. 4, pp.307-341 , 2017

Keywords: Generalized Rayleigh wave, viscoelastic material, rheological parameters, dispersion, fractional-exponential operator.

Abstract: Dispersion of the generalized Rayleigh waves propagating in a covered half-space made of viscoelastic materials is investigated by utilizing the exact equations of the theory of linear viscoelasticity. The dispersion equation is obtained for an arbitrary type of hereditary operator of the materials of the constituents and a solution algorithm is developed for obtaining numerical results on the dispersion of the waves under consideration. Dispersion curves are presented for certain attenuation cases and the influence of the viscosity of the materials is studied through three rheological parameters of the viscoelastic materials which characterize the characteristic creep time, long-term values and the mechanical behaviour of the viscoelastic material around the initial state of the deformation. Numerical results are presented and discussed for the case where the viscoelasticity of the materials is described through fractional-exponential operators by Rabotnov. As the result of this discussion, in particular, how the rheological parameters influence the dispersion of the generalized Rayleigh waves propagating in the covered half-space under consideration is established.

18. Guo Zhao, Jiang Guo and Hao Qiang: Research on SFLA-Based Bidirectional Coordinated Control Strategy for EV Battery Swapping Station. CMC: Computers, Materials & Continua, Vol. 53, No. 4, pp.343-356 , 2017

Keywords: SFLA, bidirectional coordinated control, battery swapping station, optimization.

Abstract: As a good measure to tackle the challenges from energy shortages and environmental pollution, Electric Vehicles (EVs) have entered a period of rapid growth. Battery swapping station is a very important way of energy supply to EVs, and it is urgently needed to explore a coordinated control strategy to effectively smooth the load fluctuation in order to adopt the large-scale EVs. Considering bidirectional power flow between the station and power grid, this paper proposed a SFLA-based control strategy to smooth the load profile. Finally, compared simulations were performed according to the related data. Compared to particle swarm optimization (PSO) method, the presented SFLA-based strategy can effectively lower the peak-valley difference with the faster convergence rate and higher convergence precision. It is important for the swapping station that energy exchanging mode can supply energy for large-scale EVs with a smoother load profile than one-way charging mode.

19. Chengsheng Yuan, Xinting Li, Q. M. Jonathan Wu, Jin Li and Xingming Sun: Fingerprint Liveness Detection from Different Fingerprint Materials Using Convolutional Neural Network and Principal Component Analysis. CMC: Computers, Materials & Continua, Vol. 53, No. 3, pp.357-371 , 2017

Keywords: Fingerprint liveness detection, CNNs, PCA, SVM, ROI, LivDet 2013, LivDet 2011.

Abstract: Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints, which are made of common fingerprint materials, such as silicon, latex, etc. Thus, to protect our privacy, many fingerprint liveness detection methods are put forward to discriminate fake or true fingerprint. Current work on liveness detection for fingerprint images is focused on the construction of complex handcrafted features, but these methods normally destroy or lose spatial information between pixels. Different from existing methods, convolutional neural network (CNN) can generate high-level semantic representations by learning and concatenating low-level edge and shape features from a large amount of labeled data. Thus, CNN is explored to solve the above problem and discriminate true fingerprints from fake ones in this paper. To reduce the redundant information and extract the most distinct features, ROI and PCA operations are performed for learned features of convolutional layer or pooling layer. After that, the extracted features are fed into SVM classifier. Experimental results based on the LivDet 2013 and the LivDet 2011 datasets, which are captured by using different fingerprint materials, indicate that the classification performance of our proposed method is both efficient and convenient compared with the other previous methods.

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