Journals / CMC / Vol.64, No.2
Table of Content


  • ARTICLE

    Image Segmentation of Brain MR Images Using Otsu’s Based Hybrid WCMFO Algorithm

    A. Renugambal1, *, K. Selva Bhuvaneswari2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 681-700, 2020, DOI:10.32604/cmc.2020.09519
    Abstract In this study, a novel hybrid Water Cycle Moth-Flame Optimization (WCMFO) algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance (MR) image slices. WCMFO constitutes a hybrid between the two techniques, comprising the water cycle and moth-flame optimization algorithms. The optimal thresholds are obtained by maximizing the between class variance (Otsu’s function) of the image. To test the performance of threshold searching process, the proposed algorithm has been evaluated on standard benchmark of ten axial T2-weighted brain MR images for image segmentation. The experimental outcomes infer that it produces better optimal threshold values at a greater and… More >

  • ARTICLE

    Efficient 2D Analysis of Interfacial Thermoelastic Stresses in Multiply Bonded Anisotropic Composites with Thin Adhesives

    Yui-Chuin Shiah1, *, Sheng-Chi Huang1, M. R. Hematiyan2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 701-727, 2020, DOI:10.32604/cmc.2020.010417
    Abstract In engineering practice, analysis of interfacial thermal stresses in composites is a crucial task for assuring structural integrity when sever environmental temperature changes under operations. In this article, the directly transformed boundary integrals presented previously for treating generally anisotropic thermoelasticity in two-dimension are fully regularized by a semi-analytical approach for modeling thin multi-layers of anisotropic/isotropic composites, subjected to general thermal loads with boundary conditions prescribed. In this process, an additional difficulty, not reported in the literature, arises due to rapid fluctuation of an integrand in the directly transformed boundary integral equation. In conventional analysis, thin adhesives are usually neglected due… More >

  • ARTICLE

    Performance Anomaly Detection in Web Services: An RNN- Based Approach Using Dynamic Quality of Service Features

    Muhammad Hasnain1, Seung Ryul Jeong2, *, Muhammad Fermi Pasha3, Imran Ghani4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 729-752, 2020, DOI:10.32604/cmc.2020.010394
    Abstract Performance anomaly detection is the process of identifying occurrences that do not conform to expected behavior or correlate with other incidents or events in time series data. Anomaly detection has been applied to areas such as fraud detection, intrusion detection systems, and network systems. In this paper, we propose an anomaly detection framework that uses dynamic features of quality of service that are collected in a simulated setup. Three variants of recurrent neural networks-SimpleRNN, long short term memory, and gated recurrent unit are evaluated. The results reveal that the proposed method effectively detects anomalies in web services with high accuracy.… More >

  • ARTICLE

    Nature Inspired Improved Firefly Algorithm for Node Clustering in WSNs

    V. Manikandan1, *, M. Sivaram1, Amin Salih Mohammed2, V. Porkodi3
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 753-776, 2020, DOI:10.32604/cmc.2020.010267
    Abstract Wireless Sensor Networks (WSNs) comprises low power devices that are randomly distributed in a geographically isolated region. The energy consumption of nodes is an essential factor to be considered. Therefore, an improved energy management technique is designed in this investigation to reduce its consumption and to enhance the network’s lifetime. This can be attained by balancing energy clusters using a meta-heuristic Firefly algorithm model for network communication. This improved technique is based on the cluster head selection technique with measurement of the tour length of fireflies. Time Division Multiple Access (TDMA) scheduler is also improved with the characteristics/behavior of fireflies… More >

  • ARTICLE

    A Comparative Analysis of RAD and Agile Technique for Management of Computing Graduation Projects

    Fazal Qudus Khan1, Saim Rasheed1, Maged Alsheshtawi1, Tarig Mohamed Ahmed1, 2, Sadeeq Jan3, *
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 777-796, 2020, DOI:10.32604/cmc.2020.010959
    Abstract Computing students face the problem with time and quality of the work while managing their graduation/senior projects. Rapid Application Development (RAD) model is based on continual user involvement for the process of requirement gathering via prototyping. After each iteration, the developers can validate the requirements that are completed in the iteration. Managing a project with RAD is easier but not flexible. On the other hand, Agile project management techniques focus on flexibility, agility, teamwork and quality based on user stories. Continual user involvement is avoided, which requires extensive maintenance time for fixing iteration and release of the story points. This… More >

  • ARTICLE

    Structure-Preserving Dynamics of Stochastic Epidemic Model with the Saturated Incidence Rate

    Wasfi Shatanawi1, 2, 3, Muhammad Shoaib Arif4, *, Ali Raza4, Muhammad Rafiq5, Mairaj Bibi6, Javeria Nawaz Abbasi6
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 797-811, 2020, DOI:10.32604/cmc.2020.010759
    Abstract The structure-preserving features of the nonlinear stochastic models are positivity, dynamical consistency and boundedness. These features have a significant role in different fields of computational biology and many more. Unfortunately, the existing stochastic approaches in literature do not restore aforesaid structure-preserving features, particularly for the stochastic models. Therefore, these gaps should be occupied up in literature, by constructing the structure-preserving features preserving numerical approach. This writing aims to describe the structure-preserving dynamics of the stochastic model. We have analysed the effect of reproduction number in stochastic modelling the same as described in the literature for deterministic modelling. The usual explicit… More >

  • ARTICLE

    QoS-Aware Energy-Efficient Task Scheduling on HPC Cloud Infrastructures Using Swarm-Intelligence Meta-Heuristics

    Amit Chhabra1, *, Gurvinder Singh2, Karanjeet Singh Kahlon2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 813-834, 2020, DOI:10.32604/cmc.2020.010934
    Abstract Cloud computing infrastructure has been evolving as a cost-effective platform for providing computational resources in the form of high-performance computing as a service (HPCaaS) to users for executing HPC applications. However, the broader use of the Cloud services, the rapid increase in the size, and the capacity of Cloud data centers bring a remarkable rise in energy consumption leading to a significant rise in the system provider expenses and carbon emissions in the environment. Besides this, users have become more demanding in terms of Quality-of-service (QoS) expectations in terms of execution time, budget cost, utilization, and makespan. This situation calls… More >

  • ARTICLE

    Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

    Amer Ibrahim Al-Omari1, *, Ibrahim M. Almanjahie2, Amal S. Hassan3, Heba F. Nagy4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 835-857, 2020, DOI:10.32604/cmc.2020.10944
    Abstract In reliability analysis, the stress-strength model is often used to describe the life of a component which has a random strength (X) and is subjected to a random stress (Y). In this paper, we considered the problem of estimating the reliability R=P [Y<X] when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution. The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample, ranked set sampling and median ranked set sampling methods. Four different reliability estimators under median ranked set sampling are derived. Two estimators are obtained when both strength… More >

  • ARTICLE

    Fractional Optimal Control of Navier-Stokes Equations

    Abd-Allah Hyder1, 2, *, M. El-Badawy3
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 859-870, 2020, DOI:10.32604/cmc.2020.09897
    Abstract In this paper, the non-stationary incompressible fluid flows governed by the Navier-Stokes equations are studied in a bounded domain. This study focuses on the timefractional Navier-Stokes equations in the optimal control subject, where the control is distributed within the domain and the time-fractional derivative is proposed as RiemannLiouville sort. In addition, the control object is to minimize the quadratic cost functional. By using the Lax-Milgram lemma with the assistance of the fixed-point theorem, we demonstrate the existence and uniqueness of the weak solution to this system. Moreover, for a quadratic cost functional subject to the time-fractional Navier-Stokes equations, we prove… More >

  • ARTICLE

    Vibration Performance, Stability and Energy Transfer of Wind Turbine Tower via Pd Controller

    Y. S. Hamed1, 2, *, Ayman A. Al3, 4, B. Sale3, 4, Ageel F. Alogla3, Awad M. Aljuaid3, Mosleh M. Alharthi0F5
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 871-886, 2020, DOI:10.32604/cmc.2020.08120
    Abstract In this paper, we studied the vibration performance, energy transfer and stability of the offshore wind turbine tower system under mixed excitations. The method of multiple scales is utilized to calculate the approximate solutions of wind turbine system. The proportional-derivative controller was applied for reducing the oscillations of the controlled system. Adding the controller to single degree of freedom system equation is responsible for energy transfers in offshore wind turbine tower system. The steady state solution of stability at worst resonance cases is studied and examined. The offshore wind turbine system behavior was studied numerically at its different parameters values.… More >

  • ARTICLE

    An Efficient Detection Approach of Content Aware Image Resizing

    Ming Lu1, 2, *, Shaozhang Niu1, Zhenguang Gao3
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 887-907, 2020, DOI:10.32604/cmc.2020.09770
    Abstract Content aware image resizing (CAIR) is an excellent technology used widely for image retarget. It can also be used to tamper with images and bring the trust crisis of image content to the public. Once an image is processed by CAIR, the correlation of local neighborhood pixels will be destructive. Although local binary patterns (LBP) can effectively describe the local texture, it however cannot describe the magnitude information of local neighborhood pixels and is also vulnerable to noise. Therefore, to deal with the detection of CAIR, a novel forensic method based on improved local ternary patterns (ILTP) feature and gradient… More >

  • ARTICLE

    Modeling Multi-Targets Sentiment Classification via Graph Convolutional Networks and Auxiliary Relation

    Ao Feng1, Zhengjie Gao1, *, Xinyu Song1, Ke Ke2, Tianhao Xu1, Xuelei Zhang1
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 909-923, 2020, DOI:10.32604/cmc.2020.09913
    Abstract Existing solutions do not work well when multi-targets coexist in a sentence. The reason is that the existing solution is usually to separate multiple targets and process them separately. If the original sentence has N target, the original sentence will be repeated for N times, and only one target will be processed each time. To some extent, this approach degenerates the fine-grained sentiment classification task into the sentencelevel sentiment classification task, and the research method of processing the target separately ignores the internal relation and interaction between the targets. Based on the above considerations, we proposes to use Graph Convolutional… More >

  • ARTICLE

    GACNet: A Generative Adversarial Capsule Network for Regional Epitaxial Traffic Flow Prediction

    Jinyuan Li1, Hao Li1, Guorong Cui1, Yan Kang1, *, Yang Hu1, Yingnan Zhou2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 925-940, 2020, DOI:10.32604/cmc.2020.09903
    Abstract With continuous urbanization, cities are undergoing a sharp expansion within the regional space. Due to the high cost, the prediction of regional traffic flow is more difficult to extend to entire urban areas. To address this challenging problem, we present a new deep learning architecture for regional epitaxial traffic flow prediction called GACNet, which predicts traffic flow of surrounding areas based on inflow and outflow information in central area. The method is data-driven, and the spatial relationship of traffic flow is characterized by dynamically transforming traffic information into images through a two-dimensional matrix. We introduce adversarial training to improve performance… More >

  • ARTICLE

    A Network Traffic Classification Model Based on Metric Learning

    Mo Chen1, Xiaojuan Wang1, *, Mingshu He1, Lei Jin1, Khalid Javeed2, Xiaojun Wang3
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 941-959, 2020, DOI:10.32604/cmc.2020.09802
    Abstract Attacks on websites and network servers are among the most critical threats in network security. Network behavior identification is one of the most effective ways to identify malicious network intrusions. Analyzing abnormal network traffic patterns and traffic classification based on labeled network traffic data are among the most effective approaches for network behavior identification. Traditional methods for network traffic classification utilize algorithms such as Naive Bayes, Decision Tree and XGBoost. However, network traffic classification, which is required for network behavior identification, generally suffers from the problem of low accuracy even with the recently proposed deep learning models. To improve network… More >

  • ARTICLE

    Resource Allocation in Edge-Computing Based Wireless Networks Based on Differential Game and Feedback Control

    Ruijie Lin1, Haitao Xu2, *, Meng Li3, Zhen Zhang4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 961-972, 2020, DOI:10.32604/cmc.2020.09686
    Abstract In this paper, we have proposed a differential game model to optimally solve the resource allocation problems in the edge-computing based wireless networks. In the proposed model, a wireless network with one cloud-computing center (CC) and lots of edge services providers (ESPs) is investigated. In order to provide users with higher services quality, the ESPs in the proposed wireless network should lease the computing resources from the CC and the CC can allocate its idle cloud computing resource to the ESPs. We will try to optimally allocate the edge computing resources between the ESPs and CC using the differential game… More >

  • ARTICLE

    Non-Exchangeable Error Compensation for Strapdown Inertial Navigation System in High Dynamic Environment

    Qi Wang1, 2, *, Changsong Yang2, 3, Shao’en Wu4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 973-986, 2020, DOI:10.32604/cmc.2020.07575
    Abstract Strapdown non-exchangeable error compensation technology in high dynamic environment is one of the key technologies of strapdown inertial navigation system. Mathematical platform is used in strapdown inertial navigation system instead of physical platform in traditional platform inertial navigation system, which improves reliability and reduces cost and volume of system. The maximum error source of attitude matrix solution is the non-exchangeable error of rotation due to the non-exchangeable of finite rotation of rigid bodies. The rotation non-exchangeable error reaches the maximum in coning motion, although it can be reduced by shortening the correction period and increasing the real-time calculation. The equivalent… More >

  • ARTICLE

    Three-Phase Unbalance Prediction of Electric Power Based on Hierarchical Temporal Memory

    Hui Li1, Cailin Shi2, 3, Xin Liu2, 3, Aziguli Wulamu2, 3, *, Alan Yang4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 987-1004, 2020, DOI:10.32604/cmc.2020.09812
    Abstract The difference in electricity and power usage time leads to an unbalanced current among the three phases in the power grid. The three-phase unbalanced is closely related to power planning and load distribution. When the unbalance occurs, the safe operation of the electrical equipment will be seriously jeopardized. This paper proposes a Hierarchical Temporal Memory (HTM)-based three-phase unbalance prediction model consisted by the encoder for binary coding, the spatial pooler for frequency pattern learning, the temporal pooler for pattern sequence learning, and the sparse distributed representations classifier for unbalance prediction. Following the feasibility of spatialtemporal streaming data analysis, we adopted… More >

  • ARTICLE

    New Three-Dimensional Assessment Model and Optimization of Acoustic Positioning System

    Lin Zhao1, Xiaobo Chen1, 2, *, Jianhua Cheng1, Lianhua Yu3, Chengcai Lv4, Jiuru Wang5
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1005-1023, 2020, DOI:10.32604/cmc.2020.010290
    Abstract This paper addresses the problem of assessing and optimizing the acoustic positioning system for underwater target localization with range measurement. We present a new three-dimensional assessment model to evaluate the optimal geometric beacon formation whether meets user requirements. For mathematical tractability, it is assumed that the measurements of the range between the target and beacons are corrupted with white Gaussian noise with variance, which is distance-dependent. Then, the relationship between DOP parameters and positioning accuracy can be derived by adopting dilution of precision (DOP) parameters in the assessment model. In addition, the optimal geometric beacon formation yielding the best performance… More >

  • ARTICLE

    Privacy Protection Algorithm for the Internet of Vehicles Based on Local Differential Privacy and Game Model

    Wenxi Han1, 2, Mingzhi Cheng3, *, Min Lei1, 2, Hanwen Xu2, Yu Yang1, 2, Lei Qian4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1025-1038, 2020, DOI:10.32604/cmc.2020.09815
    Abstract In recent years, with the continuous advancement of the intelligent process of the Internet of Vehicles (IoV), the problem of privacy leakage in IoV has become increasingly prominent. The research on the privacy protection of the IoV has become the focus of the society. This paper analyzes the advantages and disadvantages of the existing location privacy protection system structure and algorithms, proposes a privacy protection system structure based on untrusted data collection server, and designs a vehicle location acquisition algorithm based on a local differential privacy and game model. The algorithm first meshes the road network space. Then, the dynamic… More >

  • ARTICLE

    Air Quality Prediction Based on Kohonen Clustering and ReliefF Feature Selection

    Bolun Chen1, 2, Guochang Zhu1, *, Min Ji1, Yongtao Yu1, Jianyang Zhao1, Wei Liu3
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1039-1049, 2020, DOI:10.32604/cmc.2020.010583
    Abstract Air quality prediction is an important part of environmental governance. The accuracy of the air quality prediction also affects the planning of people’s outdoor activities. How to mine effective information from historical data of air pollution and reduce unimportant factors to predict the law of pollution change is of great significance for pollution prevention, pollution control and pollution early warning. In this paper, we take into account that there are different trends in air pollutants and that different climatic factors have different effects on air pollutants. Firstly, the data of air pollutants in different cities are collected by a sliding… More >

  • ARTICLE

    An Immunization Scheme for Ransomware

    Jingping Song1, Qingyu Meng1, Chenke Luo2, Nitin Naik3, Jian Xu1, *
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1051-1061, 2020, DOI:10.32604/cmc.2020.010592
    Abstract In recent years, as the popularity of anonymous currencies such as Bitcoin has made the tracking of ransomware attackers more difficult, the amount of ransomware attacks against personal computers and enterprise production servers is increasing rapidly. The ransomware has a wide range of influence and spreads all over the world. It is affecting many industries including internet, education, medical care, traditional industry, etc. This paper uses the idea of virus immunity to design an immunization solution for ransomware viruses to solve the problems of traditional ransomware defense methods (such as anti-virus software, firewalls, etc.), which cannot meet the requirements of… More >

  • ARTICLE

    Anomaly IoT Node Detection Based on Local Outlier Factor and Time Series

    Fang Wang1, *, Zhe Wei1, Xu Zuo2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1063-1073, 2020, DOI:10.32604/cmc.2020.09774
    Abstract The heterogeneous nodes in the Internet of Things (IoT) are relatively weak in the computing power and storage capacity. Therefore, traditional algorithms of network security are not suitable for the IoT. Once these nodes alternate between normal behavior and anomaly behavior, it is difficult to identify and isolate them by the network system in a short time, thus the data transmission accuracy and the integrity of the network function will be affected negatively. Based on the characteristics of IoT, a lightweight local outlier factor detection method is used for node detection. In order to further determine whether the nodes are… More >

  • ARTICLE

    Research on Detection Method of Interest Flooding Attack on Content Centric Network

    Yabin Xu1, 2, 3, *, Ting Xu3, Xiaowei Xu4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1075-1089, 2020, DOI:10.32604/cmc.2020.09849
    Abstract To improve the attack detection capability of content centric network (CCN), we propose a detection method of interest flooding attack (IFA) making use of the feature of self-similarity of traffic and the information entropy of content name of interest packet. On the one hand, taking advantage of the characteristics of self-similarity is very sensitive to traffic changes, calculating the Hurst index of the traffic, to identify initial IFA attacks. On the other hand, according to the randomness of user requests, calculating the information entropy of content name of the interest packets, to detect the severity of the IFA attack, is.… More >

  • ARTICLE

    A Distributed Approach of Big Data Mining for Financial Fraud Detection in a Supply Chain

    Hangjun Zhou1, *, Guang Sun1, 2, Sha Fu1, Xiaoping Fan1, Wangdong Jiang1, Shuting Hu1, Lingjiao Li1
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1091-1105, 2020, DOI:10.32604/cmc.2020.09834
    Abstract Supply Chain Finance (SCF) is important for improving the effectiveness of supply chain capital operations and reducing the overall management cost of a supply chain. In recent years, with the deep integration of supply chain and Internet, Big Data, Artificial Intelligence, Internet of Things, Blockchain, etc., the efficiency of supply chain financial services can be greatly promoted through building more customized risk pricing models and conducting more rigorous investment decision-making processes. However, with the rapid development of new technologies, the SCF data has been massively increased and new financial fraud behaviors or patterns are becoming more covertly scattered among normal… More >

  • ARTICLE

    Lattice-Based Searchable Encryption Scheme against Inside Keywords Guessing Attack

    Xiaoling Yu1, Chungen Xu1, *, Lei Xu1, Yuntao Wang2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1107-1125, 2020, DOI:10.32604/cmc.2020.09680
    Abstract To save the local storage, users store the data on the cloud server who offers convenient internet services. To guarantee the data privacy, users encrypt the data before uploading them into the cloud server. Since encryption can reduce the data availability, public-key encryption with keyword search (PEKS) is developed to achieve the retrieval of the encrypted data without decrypting them. However, most PEKS schemes cannot resist quantum computing attack, because the corresponding hardness assumptions are some number theory problems that can be solved efficiently under quantum computers. Besides, the traditional PEKS schemes have an inherent security issue that they cannot… More >

  • ARTICLE

    Behavioral Feature and Correlative Detection of Multiple Types of Node in the Internet of Vehicles

    Pengshou Xie1, Guoqiang Ma1, *, Tao Feng1, Yan Yan1, 2, Xueming Han1
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1127-1137, 2020, DOI:10.32604/cmc.2020.09695
    Abstract Undoubtedly, uncooperative or malicious nodes threaten the safety of Internet of Vehicles (IoV) by destroying routing or data. To this end, some researchers have designed some node detection mechanisms and trust calculating algorithms based on some different feature parameters of IoV such as communication, data, energy, etc., to detect and evaluate vehicle nodes. However, it is difficult to effectively assess the trust level of a vehicle node only by message forwarding, data consistency, and energy sufficiency. In order to resolve these problems, a novel mechanism and a new trust calculating model is proposed in this paper. First, the four tuple… More >

  • ARTICLE

    A High Gain, Noise Cancelling 2515-4900 MHz CMOS LNA for China Mobile 5G Communication Application

    Xiaorong Zhao1, Weili Cheng2, Hongjin Zhu1, Chunpeng Ge3, Gengyuan Zhou1, *, Zhongjun Fu1
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1139-1151, 2020, DOI:10.32604/cmc.2020.010220
    Abstract With the development of the times, people’s requirements for communication technology are becoming higher and higher. 4G communication technology has been unable to meet development needs, and 5G communication technology has emerged as the times require. This article proposes the design of a low-noise amplifier (LNA) that will be used in the 5G band of China Mobile Communications. A low noise amplifier for mobile 5G communication is designed based on Taiwan Semiconductor Manufacturing Company (TSMC) 0.13 μm Radio Frequency (RF) Complementary Metal Oxide Semiconductor (CMOS) process. The LNA employs self-cascode devices in currentreuse configuration to enable lower supply voltage operation… More >

  • ARTICLE

    Simulation of Coupling Process of Flexible Needle Insertion into Soft Tissue Based on ABAQUS

    Linze Wang1, Dedong Gao1, *, Jiajie Fu1, Yuzhou Luo2, Shijian Zhao1
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1153-1169, 2020, DOI:10.32604/cmc.2020.010073
    Abstract In order to get to the desired target inside the body, it is essential to investigate the needle-tissue coupling process and calculate the tissue deformation. A cantilever beam model is presented to predicting the deflection and bending angle of flexible needle by analyzing the distribution of the force on needle shaft during the procedure of needle insertion into soft tissue. Furthermore, a finite element (FE) coupling model is proposed to simulate the needle-tissue interactive process. The plane and spatial models are created to relate the needle and tissue nodes. Combined with the cantilever beam model and the finite element needle-tissue… More >

  • ARTICLE

    A Method for Assessing the Fairness of Health Resource Allocation Based on Geographical Grid

    Jin Han1, Wenhao Jiang1, Jin Shi2, *, Sun Xin2, Jin Peng2, Haibo Liu3
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1171-1184, 2020, DOI:10.32604/cmc.2019.07447
    Abstract The assessment of the fairness of health resource allocation is an important part of the study for the fairness of social development. The data used in most of the existing assessment methods comes from statistical yearbooks or field survey sampling. These statistics are generally based on administrative areas and are difficult to support a fine-grained evaluation model. In response to these problems, the evaluation method proposed in this paper is based on the query statistics of the geographic grid of the target area, which are more accurate and efficient. Based on the query statistics of hot words in the geographic… More >

  • ARTICLE

    Research on the Pedestrian Re-Identification Method Based on Local Features and Gait Energy Images

    Xinliang Tang1, Xing Sun1, Zhenzhou Wang1, Pingping Yu1, Ning Cao2, *, Yunfeng Xu3
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1185-1198, 2020, DOI:10.32604/cmc.2020.010283
    Abstract The appearance of pedestrians can vary greatly from image to image, and different pedestrians may look similar in a given image. Such similarities and variabilities in the appearance and clothing of individuals make the task of pedestrian re-identification very challenging. Here, a pedestrian re-identification method based on the fusion of local features and gait energy image (GEI) features is proposed. In this method, the human body is divided into four regions according to joint points. The color and texture of each region of the human body are extracted as local features, and GEI features of the pedestrian gait are also… More >

  • ARTICLE

    A Pupil-Positioning Method Based on the Starburst Model

    Pingping Yu1, Wenjie Duan1, Yi Sun2, Ning Cao3, *, Zhenzhou Wang1, Guojun Lu4
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1199-1217, 2020, DOI:10.32604/cmc.2020.010384
    Abstract Human eye detection has become an area of interest in the field of computer vision with an extensive range of applications in human-computer interaction, disease diagnosis, and psychological and physiological studies. Gaze-tracking systems are an important research topic in the human-computer interaction field. As one of the core modules of the head-mounted gaze-tracking system, pupil positioning affects the accuracy and stability of the system. By tracking eye movements to better locate the center of the pupil, this paper proposes a method for pupil positioning based on the starburst model. The method uses vertical and horizontal coordinate integral projections in the… More >

  • ARTICLE

    Image Denoising with Adaptive Weighted Graph Filtering

    Ying Chen1, 2, Yibin Tang3, Lin Zhou1, Yan Zhou3, 4, Jinxiu Zhu3, Li Zhao1, *
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1219-1232, 2020, DOI:10.32604/cmc.2020.010638
    Abstract Graph filtering, which is founded on the theory of graph signal processing, is proved as a useful tool for image denoising. Most graph filtering methods focus on learning an ideal lowpass filter to remove noise, where clean images are restored from noisy ones by retaining the image components in low graph frequency bands. However, this lowpass filter has limited ability to separate the low-frequency noise from clean images such that it makes the denoising procedure less effective. To address this issue, we propose an adaptive weighted graph filtering (AWGF) method to replace the design of traditional ideal lowpass filter. In… More >

  • ARTICLE

    A Multi-Tenant Usage Access Model for Cloud Computing

    Zhengtao Liu1, *, Yun Yang1, Wen Gu1, Jinyue Xia2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1233-1245, 2020, DOI:10.32604/cmc.2020.010846
    Abstract Most cloud services are built with multi-tenancy which enables data and configuration segregation upon shared infrastructures. It offers tremendous advantages for enterprises and service providers. It is anticipated that this situation will evolve to foster cross-tenant collaboration supported by Authorization as a service. To realize access control in a multi-tenant cloud computing environment, this study proposes a multi-tenant cloud computing access control model based on the traditional usage access control model by building trust relations among tenants. The model consists of three submodels, which achieve trust relationships between tenants with different granularities and satisfy the requirements of different application scenarios.… More >

  • ARTICLE

    A Controlled Quantum Dialogue Protocol Based on Quantum Walks

    Jinqiao Dai1, Shibin Zhang1, *, Yan Chang1, Xueyang Li1, Tao Zheng1, Jinyue Xia2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1247-1260, 2020, DOI:10.32604/cmc.2020.010550
    Abstract In order to enable two parties to exchange their secret information equally, we propose a controlled quantum dialogue protocol based on quantum walks, which implements the equal exchange of secret information between the two parties with the help of the controller TP. The secret information is transmitted via quantum walks, by using this method, the previously required entangled particles do not need to be prepared in the initial phase, and the entangled particles can be produced spontaneously via quantum walks. Furthermore, to resist TP’s dishonest behavior, we use a hash function to verify the correctness of the secret information. The… More >

  • ARTICLE

    PUF-Based Key Distribution in Wireless Sensor Networks

    Zheng Zhang1, Yanan Liu1, *, Qinyuan Zuo1, Lein Harn2, Shuo Qiu1, Yuan Cheng1
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1261-1280, 2020, DOI:10.32604/cmc.2020.010034
    Abstract Physical Unclonable Functions (PUFs) can be seen as kind of hardware oneway functions, who are easily fabricated but difficult to clone, duplicate or predict. Therefore, PUFs with unclonable and unpredictable properties are welcome to be applied in designing lightweight cryptography protocols. In this paper, a Basic Key Distribution Scheme (Basic-KDS) based on PUFs is firstly proposed. Then, by employing different deployment modes, a Random Deployment Key Distribution Scheme (RD-KDS) and a Grouping Deployment Key Distribution Scheme (GD-KDS) are further proposed based on the Basic-KDS for large scale wireless sensor networks. In our proposals, a sensor is not pre-distributed with any… More >

  • ARTICLE

    Coverless Image Steganography Based on Image Segmentation

    Yuanjing Luo1, Jiaohua Qin1, *, Xuyu Xiang1, Yun Tan1, Zhibin He1, Neal N. Xiong2
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1281-1295, 2020, DOI:10.32604/cmc.2020.010867
    Abstract To resist the risk of the stego-image being maliciously altered during transmission, we propose a coverless image steganography method based on image segmentation. Most existing coverless steganography methods are based on whole feature mapping, which has poor robustness when facing geometric attacks, because the contents in the image are easy to lost. To solve this problem, we use ResNet to extract semantic features, and segment the object areas from the image through Mask RCNN for information hiding. These selected object areas have ethical structural integrity and are not located in the visual center of the image, reducing the information loss… More >

  • ARTICLE

    A Hybrid Method of Coreference Resolution in Information Security

    Yongjin Hu1, Yuanbo Guo1, Junxiu Liu2, Han Zhang3, *
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1297-1315, 2020, DOI:10.32604/cmc.2020.010855
    Abstract In the field of information security, a gap exists in the study of coreference resolution of entities. A hybrid method is proposed to solve the problem of coreference resolution in information security. The work consists of two parts: the first extracts all candidates (including noun phrases, pronouns, entities, and nested phrases) from a given document and classifies them; the second is coreference resolution of the selected candidates. In the first part, a method combining rules with a deep learning model (Dictionary BiLSTM-Attention-CRF, or DBAC) is proposed to extract all candidates in the text and classify them. In the DBAC model,… More >

  • ARTICLE

    Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space

    Yuheng Sun1, Ye Mu1, 2, 3, 4, *, Qin Feng5, Tianli Hu1, 2, 3, 4, He Gong1, 2, 3, 4, Shijun Li1, 2, 3, 4, Jing Zhou6
    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1317-1328, 2020, DOI:10.32604/cmc.2020.010510
    Abstract In large-scale deer farming image analysis, K-means or maximum betweenclass variance (Otsu) algorithms can be used to distinguish the deer from the background. However, in an actual breeding environment, the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer. Also, when the target and background grey values are similar, the multiple background targets cannot be completely separated. To better identify the posture and behaviour of deer in a deer shed, we used digital image processing to separate the deer from the background. To address the problems… More >

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