Open Access

ARTICLE

Paolina Centonze^1,*
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 361-374, 2019, DOI:10.32604/cmc.2019.06223
Abstract In the security and privacy fields, Access Control (AC) systems are viewed as the fundamental aspects of networking security mechanisms. Enforcing AC becomes even more challenging when researchers and data analysts have to analyze complex and distributed Big Data (BD) processing cluster frameworks, which are adopted to manage yottabyte of unstructured sensitive data. For instance, Big Data systems’ privacy and security restrictions are most likely to failure due to the malformed AC policy configurations. Furthermore, BD systems were initially developed toped to take care of some of the DB issues to address BD challenges and… More >

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ARTICLE

Dae-Young Kim¹, Seokhoon Kim^2,*
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 375-387, 2019, DOI:10.32604/cmc.2019.06077
Abstract Communication is important for providing intelligent services in connected vehicles. Vehicles must be able to communicate with different places and exchange information while driving. For service operation, connected vehicles frequently attempt to download large amounts of data. They can request data downloading to a road side unit (RSU), which provides infrastructure for connected vehicles. The RSU is a data bottleneck in a transportation system because data traffic is concentrated on the RSU. Therefore, it is not appropriate for a connected vehicle to always attempt a high speed download from the RSU. If the mobile network… More >

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ARTICLE

Daniel Rivera Ruiz^1,*, Alisha Sawant¹
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 389-396, 2019, DOI:10.32604/cmc.2019.06433
Abstract In this paper we aim to identify certain social factors that influence, and thus can be used to predict, the occurrence of crimes. The factors under consideration for this analytic are social demographics such as age, sex, poverty, etc., train ridership, traffic density and the number of business licenses per community area in Chicago, IL. A factor will be considered pertinent if there is high correlation between it and the number of crimes of a particular type in that community area. More >

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ARTICLE

Nehal Al-Otaiby¹, Heba Kurdi^1,*, Shiroq Al-Megren¹
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 397-404, 2019, DOI:10.32604/cmc.2019.06236
Abstract Trust has become an increasingly important issue given society’s growing reliance on electronic transactions. Peer-to-peer (P2P) networks are among the main electronic transaction environments affected by trust issues due to the freedom and anonymity of peers (users) and the inherent openness of these networks. A malicious peer can easily join a P2P network and abuse its peers and resources, resulting in a large-scale failure that might shut down the entire network. Therefore, a plethora of researchers have proposed trust management systems to mitigate the impact of the problem. However, due to the problem’s scale and More >

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REVIEW

Tongyan Yue^1,2, Magd Abdel Wahab^3,4,*
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 405-432, 2019, DOI:10.32604/cmc.2019.04253
Abstract Fretting wear is a material damage in contact surfaces due to micro relative displacement between them. It causes some general problems in industrial applications, such as loosening of fasteners or sticking in components supposed to move relative to each other. Fretting wear is a complicated problem involving material properties of tribo-system and working conditions of them. Due to these various factors, researchers have studied the process of fretting wear by experiments and numerical modelling methods. This paper reviews recent literature on the numerical modelling method of fretting wear. After a briefly introduction on the mechanism More >

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3748

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ARTICLE

Hongwei Guo³, Xiaoying Zhuang^3,4,5, Timon Rabczuk^1,2,*
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 433-456, 2019, DOI:10.32604/cmc.2019.06660
Abstract In this paper, a deep collocation method (DCM) for thin plate bending problems is proposed. This method takes advantage of computational graphs and backpropagation algorithms involved in deep learning. Besides, the proposed DCM is based on a feedforward deep neural network (DNN) and differs from most previous applications of deep learning for mechanical problems. First, batches of randomly distributed collocation points are initially generated inside the domain and along the boundaries. A loss function is built with the aim that the governing partial differential equations (PDEs) of Kirchhoff plate bending problems, and the boundary/initial conditions More >

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192

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ARTICLE

Qiaoyang Zhang¹, Zhiyao Liang^1,*, Zhiping Cai²
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 457-471, 2019, DOI:10.32604/cmc.2019.03758
Abstract Wearable devices are becoming more popular in our daily life. They are usually used to monitor health status, track fitness data, or even do medical tests, etc. Since the wearable devices can obtain a lot of personal data, their security issues are very important. Motivated by the consideration that the current pairing mechanisms of Bluetooth Low Energy (BLE) are commonly impractical or insecure for many BLE based wearable devices nowadays, we design and implement a security framework in order to protect the communication between these devices. The security framework is a supplement to the Bluetooth… More >

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ARTICLE

Zhangjie Fu^1,*, Lili Xia¹, Yuling Liu², Zuwei Tian³
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 473-491, 2019, DOI:10.32604/cmc.2019.03785
Abstract Nowadays, cloud computing is used more and more widely, more and more people prefer to using cloud server to store data. So, how to encrypt the data efficiently is an important problem. The search efficiency of existed search schemes decreases as the index increases. For solving this problem, we build the two-level index. Simultaneously, for improving the semantic information, the central word expansion is combined. The purpose of privacy-preserving content-aware search by using the two-level index (CKESS) is that the first matching is performed by using the extended central words, then calculate the similarity between More >

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ARTICLE

Yangyang Li¹, Xue Wang², Weiwei Fang^2,*, Feng Xue², Hao Jin¹, Yi Zhang¹, Xianwei Li³
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 493-508, 2019, DOI:10.32604/cmc.2019.05178
Abstract With the recent proliferation of Internet-of-Things (IoT), enormous amount of data are produced by wireless sensors and connected devices at the edge of network. Conventional cloud computing raises serious concerns on communication latency, bandwidth cost, and data privacy. To address these issues, edge computing has been introduced as a new paradigm that allows computation and analysis to be performed in close proximity with data sources. In this paper, we study how to conduct regression analysis when the training samples are kept private at source devices. Specifically, we consider the lasso regression model that has been More >

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ARTICLE

Peng Fu^1,2, Qianqian Xu¹, Jieyu Zhang³, Leilei Geng^4,*
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 509-515, 2019, DOI:10.32604/cmc.2019.05250
Abstract The superpixel segmentation has been widely applied in many computer vision and image process applications. In recent years, amount of superpixel segmentation algorithms have been proposed. However, most of the current algorithms are designed for natural images with little noise corrupted. In order to apply the superpixel algorithms to hyperspectral images which are always seriously polluted by noise, we propose a noise-resistant superpixel segmentation (NRSS) algorithm in this paper. In the proposed NRSS, the spectral signatures are first transformed into frequency domain to enhance the noise robustness; then the two widely spectral similarity measures-spectral angle More >

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1408

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ARTICLE

Yong Hua¹, Bolun Chen^1,2,*, Yan Yuan¹, Guochang Zhu¹, Jialin Ma¹
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 517-531, 2019, DOI:10.32604/cmc.2019.05278
Abstract The influence maximization is the problem of finding k seed nodes that maximize the scope of influence in a social network. Therefore, the comprehensive influence of node needs to be considered, when we choose the most influential node set consisted of k seed nodes. On account of the traditional methods used to measure the influence of nodes, such as degree centrality, betweenness centrality and closeness centrality, consider only a single aspect of the influence of node, so the influence measured by traditional methods mentioned above of node is not accurate. In this paper, we obtain the More >

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1143

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ARTICLE

Pingshui Wang^1,*, Zecheng Wang¹, Tao Chen^1,2, Qinjuan Ma¹
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 533-546, 2019, DOI:10.32604/cmc.2019.05570
Abstract With the rapid development of the new generation of information technology, the analysis of mobile social network big data is getting deeper and deeper. At the same time, the risk of privacy disclosure in social network is also very obvious. In this paper, we summarize the main access control model in mobile social network, analyze their contribution and point out their disadvantages. On this basis, a practical privacy policy is defined through authorization model supporting personalized privacy preferences. Experiments have been conducted on synthetic data sets. The result shows that the proposed privacy protecting model More >

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1282

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ARTICLE

Jing Qiu¹, Yan Liu², Yuhan Chai², Yaqi Si², Shen Su^{1, ∗}, Le Wang^{1, ∗}, Yue Wu³
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 547-562, 2019, DOI:10.32604/cmc.2019.05892
Abstract Recently dependency information has been used in different ways to improve neural machine translation. For example, add dependency labels to the hidden states of source words. Or the contiguous information of a source word would be found according to the dependency tree and then be learned independently and be added into Neural Machine Translation (NMT) model as a unit in various ways. However, these works are all limited to the use of dependency information to enrich the hidden states of source words. Since many works in Statistical Machine Translation (SMT) and NMT have proven the… More >

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ARTICLE

Zhonghao Li¹, Laijin Meng¹, Shutong Xu¹, Zhaohong Li^1,2,*, Yunqing Shi³, Yuanchang Liang¹
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 563-574, 2019, DOI:10.32604/cmc.2019.05565
Abstract Steganalysis is a technique used for detecting the existence of secret information embedded into cover media such as images and videos. Currently, with the higher speed of the Internet, videos have become a kind of main methods for transferring information. The latest video coding standard High Efficiency Video Coding (HEVC) shows better coding performance compared with the H.264/AVC standard published in the previous time. Therefore, since the HEVC was published, HEVC videos have been widely used as carriers of hidden information.
In this paper, a steganalysis algorithm is proposed to detect the latest HEVC video steganography… More >

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ARTICLE

Zhaowei Qu^1,*, Bingyu Cao¹, Xiaoru Wang¹, Fu Li², Peirong Xu¹, Luhan Zhang¹
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 575-589, 2019, DOI:10.32604/cmc.2019.05569
Abstract Images are complex multimedia data which contain rich semantic information. Most of current image description generator algorithms only generate plain description, with the lack of distinction between primary and secondary object, leading to insufficient high-level semantic and accuracy under public evaluation criteria. The major issue is the lack of effective network on high-level semantic sentences generation, which contains detailed description for motion and state of the principal object. To address the issue, this paper proposes the Attention-based Feedback Long Short-Term Memory Network (AFLN). Based on existing codec framework, there are two independent sub tasks in… More >

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1393

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ARTICLE

Ruixiang Li^1,2, Yingying Liu³, Yaqiong Qiao^1,2, Te Ma^1,2, Bo Wang⁴, Xiangyang Luo^1,2,*
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 591-606, 2019, DOI:10.32604/cmc.2019.05208
Abstract High-density street-level reliable landmarks are one of the important foundations for street-level geolocation. However, the existing methods cannot obtain enough street-level landmarks in a short period of time. In this paper, a street-level landmarks acquisition method based on SVM (Support Vector Machine) classifiers is proposed. Firstly, the port detection results of IPs with known services are vectorized, and the vectorization results are used as an input of the SVM training. Then, the kernel function and penalty factor are adjusted for SVM classifiers training, and the optimal SVM classifiers are obtained. After that, the classifier sequence More >

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ARTICLE

Zhiguo Qu^1,*, Shengyao Wu², Wenjie Liu¹, Xiaojun Wang³
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 607-624, 2019, DOI:10.32604/cmc.2019.02656
Abstract In the field of quantum communication, quantum steganography is an important branch of quantum information hiding. In a realistic quantum communication system, quantum noises are unavoidable and will seriously impact the safety and reliability of the quantum steganographic system. Therefore, it is very important to analyze the influence of noise on the quantum steganography protocol and how to reduce the effect of noise. This paper takes the quantum steganography protocol proposed in 2010 as an example to analyze the effects of noises on information qubits and secret message qubits in the four primary quantum noise More >

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1223

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ARTICLE

Yuqing Yang^1,2, Dequn Zhou^1,*, Xiaojiang Yang^1,3,4
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 625-633, 2019, DOI:10.32604/cmc.2019.05246
Abstract Massive open online courses (MOOC) have recently gained worldwide attention in the field of education. The manner of MOOC provides a new option for learning various kinds of knowledge. A mass of data miming algorithms have been proposed to analyze the learner’s characteristics and classify the learners into different groups. However, most current algorithms mainly focus on the final grade of the learners, which may result in an improper classification. To overcome the shortages of the existing algorithms, a novel multi-feature weighting based K-means (MFWK-means) algorithm is proposed in this paper. Correlations between the widely More >

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1336

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ARTICLE

Yalan Wang^1,2, Yuling Chen^1,*, Haseeb Ahmad³, Zhanhong Wei⁴
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 635-648, 2019, DOI:10.32604/cmc.2019.05251
Abstract To ensure the security during the communication, we often adopt different ways to encrypt the messages to resist various attacks. However, with the computing power improving, the existing encryption and authentication schemes are being faced with big challenges. We take the message authentication as an example into a careful consideration. Then, we proposed a new message authentication scheme with the Advanced Encryption Standard as the encryption function and the new quantum Hash function as the authentication function. Firstly, the Advanced Encryption Standard algorithm is used to encrypt the result of the initial message cascading the… More >

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1255

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ARTICLE

Demin Gao^{1, 2, *}, Shuo Zhang¹, Fuquan Zhang¹, Xijian Fan¹, Jinchi Zhang^1,∗
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 649-667, 2019, DOI:10.32604/cmc.2019.05195
Abstract For rechargeable wireless sensor networks, limited energy storage capacity, dynamic energy supply, low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario. Therefore, before data delivery, a sensor has to update its waking schedule continuously and share them to its neighbors, which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets. In this work, we propose the maximum data generation rate routing protocol based on data More >

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1165

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22

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ARTICLE

Zhe Liu¹, Charlie Maere^1,*, Yuqing Song¹
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 669-686, 2019, DOI:10.32604/cmc.2019.04590
Abstract Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing. We propose a novel approach of automatically identifying region of interest in Computed Tomography Image (CT) images based on temporal and spatial data . Our method is a 3 stages approach, 1) We extract organ features from the CT images by adopting the Hounsfield filter. 2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’ area and automatically detect a seed point. 3) We use a novel approach to More >

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ARTICLE

Jun Xie¹, Dapeng Sun¹, Jiaxiang Cai², Fuhong Cai^1,*
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 687-695, 2019, DOI:10.32604/cmc.2019.03658
Abstract The level of chemical oxygen demand (COD) is an important index to evaluate whether sewage meets the discharge requirements, so corresponding tests should be carried out before discharge. Fourier transform infrared spectroscopy (FTIR) and attenuated total reflectance (ATR) can detect COD in sewage effectively, which has advantages over conventional chemical analysis methods. And the selection of characteristic bands was one of the key links in the application of FTIR/ATR spectroscopy. In this work, based on the moving window partial least-squares (MWPLS) regression to select a characteristic wavelength, a method of equivalent wavelength selection was proposed More >

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