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B. V. Santhosh Krishna^{1, *}, T. Gnanasekaran²
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 855-869, 2019, DOI:10.32604/cmc.2019.07585
Abstract An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages,… More >

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Libardo V. Vanegas-Useche^1,4, Magd M. Abdel-Wahab^2,3,*, Graham A. Parker⁵
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 871-893, 2019, DOI:10.32604/cmc.2019.06480
Abstract Street sweeping is an important public service, as it has an impact on aesthetics and public health. Typically, sweeping vehicles have a gutter brush that sweeps the debris that lies in the road gutter. As most of the debris is located in the gutter, the effective operation of the gutter brush is important. The aim of this work is to study the performance of a type of gutter brush, the cutting brush, through a 3D dynamic (transient), large deflection finite element model developed by the authors. In this brush model, the brush mounting board is… More >

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Ashwinth Janarthanan^1,*, Dhananjay Kumar¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 895-912, 2019, DOI:10.32604/cmc.2019.06805
Abstract Efficient aggregation in wireless sensor nodes helps reduce network traffic and reduce energy consumption. The objective of this work Localization Based Evolutionary Routing (LOBER) is to achieve global optimization for aggregation and WMSN lifetime. Improved localization is achieved by a novel Centroid Based Octant Localization (CBOL) technique considering an arbitrary hexagonal region. Geometric principles of hexagon are used to locate the unknown nodes in the centroid positions of partitioned regions. Flower pollination algorithm, a meta heuristic evolutionary algorithm that is extensively applied in solving real life, complex and nonlinear optimization problems in engineering and industry More >

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Kamaljit Kaur^{1, *}, Kuljit Kaur²
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 913-946, 2019, DOI:10.32604/cmc.2019.07675
Abstract Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the More >

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V. Gowrishankar^1,*, K. Venkatachalam¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 947-957, 2019, DOI:10.32604/cmc.2019.07749
Abstract A high precision 10-bit successive approximation register analog to digital converter (ADC) designed and implemented in 32nm CNTFET process technology at the supply of 0.6V, with 73.24 dB SNDR at a sampling rate of 640 MS/s with the average power consumption of 120.2 μW for the Internet of things node. The key components in CNTFET SAR ADCs are binary scaled charge redistribution digital to analog converter using MOS capacitors, CNTFET based dynamic latch comparator and simple SAR digital code error correction logic. These techniques are used to increase the sampling rate and precision while ensuring More >

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2133

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Belghachi Mohammed^1,*, Debab Naouel¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 959-972, 2019, DOI:10.32604/cmc.2019.07580
Abstract A new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all… More >

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1758

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Rui Song¹, Yubo Song^1,*, Ziming Liu², Min Tang², Kan Zhou³
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 973-987, 2019, DOI:10.32604/cmc.2019.06035
Abstract The birth of blockchain has promoted the development of electronic currencies such as Bitcoin and Ethereum. Blockchain builds a financial system based on cryptology instead of credit, which allows parties to complete the transaction on their own without the need for credible third-party intermediaries. So far, the application scenario of blockchain is mainly confined to the peer-to-peer electronic financial system, which obviously does not fully utilize the potential of blockchain.
In this paper, we introduce GaiaWorld, a new system for decentralized application. To solve the problem of resource waste and mismatch between nodes and computing More >

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Chaofan Duan¹, Jing Feng^1,*, Haotian Chang¹, Jianping Pan², Liming Duan¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 989-1002, 2019, DOI:10.32604/cmc.2019.06033
Abstract Coverage is an important issue for resources rational allocation, cognitive tasks completion in sensor networks. The mobility, communicability and learning ability of smart sensors have received much attention in the past decade. Based on the deep study of game theory, a mobile sensor non-cooperative game model is established for the sensor network deployment and a local information-based topology control (LITC) algorithm for coverage enhancement is proposed. We both consider revenue of the monitoring events and neighboring sensors to avoid nodes aggregation when formulating the utility function. We then prove that the non-cooperative game is an More >

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ARTICLE

Aziguli Wulam^1,2, Yingshuai Wang^1,2, Dezheng Zhang^1,2,*, Jingyue Sang³, Alan Yang⁴
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1003-1013, 2019, DOI:10.32604/cmc.2019.07704
Abstract In recent years, the models combining traditional machine learning with the deep learning are applied in many commodity recommendation practices. It has been proved better performance by the means of the neural network. Feature engineering has been the key to the success of many click rate estimation model. As we know, neural networks are able to extract high-order features automatically, and traditional linear models are able to extract low-order features. However, they are not necessarily efficient in learning all types of features. In traditional machine learning, gradient boosting decision tree is a typical representative of More >

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ARTICLE

Gengxin Sun^1,*, Sheng Bin¹, Meng Jiang², Ning Cao³, Zhiyong Zheng⁴, Hongyan Zhao⁵, Dongbo Wang⁶, Lina Xu⁷
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1015-1027, 2019, DOI:10.32604/cmc.2019.05644
Abstract With the emergence and development of blockchain technology, a new type of social networks based on blockchain had emerged. In these social networks high quality content creators, filters and propagators can all be reasonably motivated. Due to the transparency and traceability brought by blockchain technology, the public opinion propagation in such social networks presents new characteristics and laws. Based on the theory of network propagation and blockchain, a new public opinion propagation model for this kind of social network based on blockchain technology is proposed in this paper. The model considers the effect of incentive More >

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1804

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Jiancheng Zou^1,*, Tianshu Chen¹, Xin Yang²
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1029-1040, 2019, DOI:10.32604/cmc.2019.05793
Abstract Heart rate is an important physiological parameter for clinical diagnosis, it can infer the health of the human body. Thus, efficient and accurate heart rate measurement is important for disease diagnosis and health monitoring. There are two ways to measure heart rate. One is contact type and the other is non-contact. Contact measurement methods include pulse cutting, electrocardiogram, etc. Because of the inconvenience of this method, a non-contact heart rate method has been proposed. Traditional non-contact measurement method based on image is collecting RGB three-channel signals in continuous video and selecting the average value of… More >

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1800

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ARTICLE

Hefei Ling¹, Jia Wu¹, Ping Li^1,*, Jialie Shen²
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1041-1054, 2019, DOI:10.32604/cmc.2019.05605
Abstract Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes More >

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1473

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ARTICLE

Xiaorui Zhang^1,2,3,*, Jiali Duan¹, Jia Liu², Norman I. Badler³
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1055-1071, 2019, DOI:10.32604/cmc.2019.03915
Abstract Current research on suture simulation mainly focus on the construction of suture line, and existing suture simulation systems still need to be improved in terms of diversity, soft tissue effects, and stability. This paper presents an integrated liver suture surgery system composed of three consecutive suture circumstances, which is conducive to liver suture surgery training. The physically-based models used in this simulation are based on different mass-spring models regulated by a special constrained algorithm, which can improve the model accuracy, and stability by appropriately restraining the activity sphere of the surrounding mass nodes around the… More >

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1528

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Xin Li^1,2, Yanchun Liang^1,2, Minghao Zhao^1,2, Chong Wang^1,2,3, Yu Jiang^1,2,*
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1073-1085, 2019, DOI:10.32604/cmc.2019.05929
Abstract In recent years, extreme weather events accompanying the global warming have occurred frequently, which brought significant impact on national economic and social development. The ocean is an important member of the climate system and plays an important role in the occurrence of climate anomalies. With continuous improvement of sensor technology, we use sensors to acquire the ocean data for the study on resource detection and disaster prevention, etc. However, the data acquired by the sensor is not enough to be used directly by researchers, so we use the Generative Adversarial Network (GAN) to enhance the… More >

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2360

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ARTICLE

Xiaoyu Li¹, Qinsheng Zhu^2,*, Qingyu Meng², Caishu You¹, Mingzheng Zhu¹, Yong Hu², Yiming Huang^1,3, Hao Wu², Desheng Zheng⁴
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1087-1095, 2019, DOI:10.32604/cmc.2019.06060
Abstract Quantum correlation which is different to the entanglement and classical correlation plays important role in quantum information field. In our setup, neural network method is adopted to simulate the link between the Rènyi discord (α = 2) and the geometric discord (Bures distance) for special canonical initial states in order to show the consistency of physical results for different quantification methods. Our results are useful for studying the differences and commonalities of different quantizing methods of quantum correlation. More >

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Jingjing Liu^1,2, Bin Zhang³, Xu Cheng⁴, Ying Chen⁵, Li Zhao^1,*
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1097-1108, 2019, DOI:10.32604/cmc.2019.05968
Abstract Visual tracking is a challenging issue in the field of computer vision due to the objects’ intricate appearance variation. To adapt the change of the appearance, multiple channel features which could provide more information are used. However, the low level feature could not represent the structure of the object. In this paper, a superpixel-based adaptive tracking algorithm by using color histogram and haar-like feature is proposed, whose feature is classified into the middle level. Based on the superpixel representation of video frames, the haar-like feature is extracted at the superpixel level as the local feature,… More >

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1419

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Jiao Yao¹, Yiling Ni¹, Jing Zhao², Huiwei Niu¹, Shanyong Liu¹, Yuhui Zheng³, Jin Wang^4,5,*
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1109-1122, 2019, DOI:10.32604/cmc.2019.06252
Abstract Violation probability of taxi drivers in metropolis is far more than that of normal drivers because they are labor-intensive, overconfident of self-driving skill, and always searching potential customers, sometimes even picking up or dropping off passengers randomly. In this paper, four types of violated behavior of taxi drivers in metropolis were first summarized, based on which corresponding scale table was initial designed with social statistical method. Furthermore, with certain samples, relative item analysis, exploratory factor analysis, validity analysis and reliability analysis were conducted to verify validity of the initial scale table, based on which some… More >

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ARTICLE

Yan Liu^1,*, Lian Liu¹, Yu Yan², Hao Feng¹, Shichang Ding³
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1123-1139, 2019, DOI:10.32604/cmc.2019.05619
Abstract Social organizations can be represented by social network because it can mathematically quantify and represent complex interrelated organizational behavior. Exploring the change in dynamic social network is essential for the situation awareness of the corresponding social organization. Social network usually evolves gradually and slightly, which is hard to be noticed. The statistical process control techniques in industry field have been used to distinguish the statistically significant change of social network. But the original method is narrowed due to some limitation on measures. This paper presents a generic framework to address the change detection problem in More >

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1383

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ARTICLE

Zhenqiu Xiao^1,*, Bin Yang², Desy Tjahjadi³
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638
Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting… More >

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2398

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Yanpeng Wu¹, Xiaoqi Peng^1,*, Mohammad Nur², Hengfu Yang¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1155-1170, 2019, DOI:10.32604/cmc.2019.06123
Abstract Foam image segmentation, represented by watershed algorithm, is wildly used in the extraction of bubble morphology features. H-minima transformation was proved to be effective in locating the catchment basins in the traditional watershed segmentation method. To further improve the accuracy of watershed segmentation, method of top-bottom-cap filters and method of morphological reconstruction were implied to marking the catchment basins. In this paper, instead of H-minima transformation, a method of contour lines is specially proposed to obtain the catchment basins for foam image segmentation by using top-bottom-cap filters and less morphological reconstruction. Experimental results in foam More >

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1582

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Yu Wang^1,2,*, Yan Cao², Liancheng Zhang², Hongtao Zhang³, Roxana Ohriniuc⁴, Guodong Wang⁵, Ruosi Cheng⁶
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1171-1187, 2019, DOI:10.32604/cmc.2019.05575
Abstract Network traffic anomaly detection has gained considerable attention over the years in many areas of great importance. Traditional methods used for detecting anomalies produce quantitative results derived from multi-source information. This makes it difficult for administrators to comprehend and deal with the underlying situations. This study proposes another method to yet determine traffic anomaly (YATA), based on the cloud model. YATA adopts forward and backward cloud transformation algorithms to fuse the quantitative value of acquisitions into the qualitative concept of anomaly degree. This method achieves rapid and direct perspective of network traffic. Experimental results with More >

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Zhiliang Wang^1,*, Youpeng Huang¹, Feng Xiong¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1189-1206, 2019, DOI:10.32604/cmc.2019.04972
Abstract This article reports numerical results investigating the damage evolution and spatial distribution characteristics of intact and jointed rockmass subjected to blast loading. The behaviors of rock material are described by the Holmquist- Johnson-Cook (HJC) constitutive model incorporated in the finite element software LS-DYNA. Results indicate that the damage distribution shows a reverse S-shape attenuation with the increase of the distance from borehole, and a better goodness of fit with the Logistic function is observed. In the single-hole blasting of jointed rockmass, there are two types of regions around the intersection of borehole and joint in More >

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1769

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Shengting Wu¹, Yuling Liu^1,*, Jingwen Wang², Qi Li¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1207-1222, 2019, DOI:10.32604/cmc.2019.05835
Abstract Sentiment analysis is a research hot spot in the field of natural language processing and content security. Traditional methods are often difficult to handle the problems of large difference in sample distribution and the data in the target domain is transmitted in a streaming fashion. This paper proposes a sentiment analysis method based on Kmeans and online transfer learning in the view of fact that most existing sentiment analysis methods are based on transfer learning and offline transfer learning. We first use the Kmeans clustering algorithm to process data from one or multiple source domains More >

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Yue Zhao¹, Jianjian Yue¹, Wei Song^1,*, Xiaona Xu¹, Xiali Li¹, Licheng Wu¹, Qiang Ji²
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1223-1235, 2019, DOI:10.32604/cmc.2019.05636
Abstract Tibetan language has very limited resource for conventional automatic speech recognition so far. It lacks of enough data, sub-word unit, lexicons and word inventories for some dialects. And speech content recognition and dialect classification have been treated as two independent tasks and modeled respectively in most prior works. But the two tasks are highly correlated. In this paper, we present a multi-task WaveNet model to perform simultaneous Tibetan multi-dialect speech recognition and dialect identification. It avoids processing the pronunciation dictionary and word segmentation for new dialects, while, in the meantime, allows training speech recognition and More >

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1707

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ARTICLE

Wenjie Liu^1,2,*, Yong Xu², James C. N. Yang³, Wenbin Yu^1,2, Lianhua Chi⁴
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1237-1250, 2019, DOI:10.32604/cmc.2019.03551
Abstract Privacy-preserving computational geometry is the research area on the intersection of the domains of secure multi-party computation (SMC) and computational geometry. As an important field, the privacy-preserving geometric intersection (PGI) problem is when each of the multiple parties has a private geometric graph and seeks to determine whether their graphs intersect or not without revealing their private information. In this study, through representing Alice’s (Bob’s) private geometric graph G_A (G_B) as the set of numbered grids S_A (S_B), an efficient privacy-preserving quantum two-party geometric intersection (PQGI) protocol is proposed. In the protocol, the oracle operation O_A (O_B) is More >

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1534

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Daojian Zeng^1,2, Yao Xiao^1,2, Jin Wang^2,*, Yuan Dai^1,2, Arun Kumar Sangaiah³
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1251-1261, 2019, DOI:10.32604/cmc.2019.06100
Abstract Recently, many researchers have concentrated on distant supervision relation extraction (DSRE). DSRE has solved the problem of the lack of data for supervised learning, however, the data automatically labeled by DSRE has a serious problem, which is class imbalance. The data from the majority class obviously dominates the dataset, in this case, most neural network classifiers will have a strong bias towards the majority class, so they cannot correctly classify the minority class. Studies have shown that the degree of separability between classes greatly determines the performance of imbalanced data. Therefore, in this paper we More >

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ARTICLE

Xiangyan Tang¹, Qidong Zheng^1,*, Jieren Cheng^1,2, Victor S. Sheng³, Rui Cao¹, Meizhu Chen¹
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1263-1281, 2019, DOI:10.32604/cmc.2019.06173
Abstract The existing network security situation assessment methods cannot effectively assess the Distributed denial-of-service (DDoS) attack situation. In order to solve these problems, we propose a DDoS attack situation assessment method via optimized cloud model based on influence function. Firstly, according to the state change characteristics of the IP addresses which are accessed by new and old user respectively, this paper defines a fusion feature value. Then, based on this value, we establish a V-Support Vector Machines (V-SVM) classification model to analyze network flow for identifying DDoS attacks. Secondly, according to the change of new and… More >

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2298

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ARTICLE

Aziguli Wulamu^1,2, Zhenqi Sun^1,2, Yonghong Xie^1,2,*, Cong Xu^1,2, Alan Yang³
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1283-1295, 2019, DOI:10.32604/cmc.2019.07722
Abstract At present, End-to-End trainable Memory Networks (MemN2N) has proven to be promising in many deep learning fields, especially on simple natural language-based reasoning question and answer (QA) tasks. However, when solving some subtasks such as basic induction, path finding or time reasoning tasks, it remains challenging because of limited ability to learn useful information between memory and query. In this paper, we propose a novel gated linear units (GLU) and local-attention based end-to-end memory networks (MemN2N-GL) motivated by the success of attention mechanism theory in the field of neural machine translation, it shows an improved More >

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