Journals / CMC / Vol.65, No.2
Table of Content


  • ARTICLE

    Complementary Kalman Filter as a Baseline Vector Estimator for GPS-Based Attitude Determination

    Dah-Jing Jwo1, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 993-1014, 2020, DOI:10.32604/cmc.2020.011592
    Abstract The Global Positioning System (GPS) offers the interferometer for attitude determination by processing the carrier phase observables. By using carrier phase observables, the relative positioning is obtained in centimeter level. GPS interferometry has been firstly used in precise static relative positioning, and thereafter in kinematic positioning. The carrier phase differential GPS based on interferometer principles can solve for the antenna baseline vector, defined as the vector between the antenna designated master and one of the slave antennas, connected to a rigid body. Determining the unknown baseline vectors between the antennas sits at the heart of GPS-based attitude determination. The conventional… More >

  • ARTICLE

    Second Law Analysis and Optimization of Elliptical Pin Fin Heat Sinks Using Firefly Algorithm

    Nawaf N. Hamadneh1, Waqar A. Khan2, Ilyas Khan3, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1015-1032, 2020, DOI:10.32604/cmc.2020.011476
    Abstract One of the most significant considerations in the design of a heat sink is thermal management due to increasing thermal flux and miniature in size. These heat sinks utilize plate or pin fins depending upon the required heat dissipation rate. They are designed to optimize overall performance. Elliptical pin fin heat sinks enhance heat transfer rates and reduce the pumping power. In this study, the Firefly Algorithm is implemented to optimize heat sinks with elliptical pin-fins. The pin-fins are arranged in an inline fashion. The natureinspired metaheuristic algorithm performs powerfully and efficiently in solving numerical global optimization problems. Based on… More >

  • ARTICLE

    DL-HAR: Deep Learning-Based Human Activity Recognition Framework for Edge Computing

    Abdu Gumaei1, 2, *, Mabrook Al-Rakhami1, 2, Hussain AlSalman2, Sk. Md. Mizanur Rahman3, Atif Alamri1, 2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1033-1057, 2020, DOI:10.32604/cmc.2020.011740
    Abstract Human activity recognition is commonly used in several Internet of Things applications to recognize different contexts and respond to them. Deep learning has gained momentum for identifying activities through sensors, smartphones or even surveillance cameras. However, it is often difficult to train deep learning models on constrained IoT devices. The focus of this paper is to propose an alternative model by constructing a Deep Learning-based Human Activity Recognition framework for edge computing, which we call DL-HAR. The goal of this framework is to exploit the capabilities of cloud computing to train a deep learning model and deploy it on lesspowerful… More >

  • ARTICLE

    Mitigating and Monitoring Smart City Using Internet of Things

    Sudan Jha1, Lewis Nkenyereye2, *, Gyanendra Prasad Joshi3, Eunmok Yang4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1059-1079, 2020, DOI:10.32604/cmc.2020.011754
    Abstract The present trends in smart world reflects the extensive use of limited resources through information and communication technology. The limited resources like space, mobility, energy, etc., have been consumed rigorously towards creating optimized but smart instances. Thus, a new concept of IoT integrated smart city vision is yet to be proposed which includes a combination of systems like noise and air loss monitoring, web monitoring and fire detection systems, smart waste bin systems, etc., that have not been clearly addressed in the previous researches. This paper focuses on developing an effective system for possible monitoring of losses, traffic management, thus… More >

  • ARTICLE

    Discrete Wavelet Transmission and Modified PSO with ACO Based Feed Forward Neural Network Model for Brain Tumour Detection

    Machiraju Jayalakshmi1, *, S. Nagaraja Rao2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710
    Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and a feed-forward neural network (FNN)… More >

  • ARTICLE

    Towards Improving the Intrusion Detection through ELM (Extreme Learning Machine)

    Iftikhar Ahmad1, *, Rayan Atteah Alsemmeari1
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1097-1111, 2020, DOI:10.32604/cmc.2020.011732
    (This article belongs to this Special Issue: Management of Security, Privacy and Trust of Multimedia Data in Mobile devices communication)
    Abstract An IDS (intrusion detection system) provides a foremost front line mechanism to guard networks, systems, data, and information. That’s why intrusion detection has grown as an active study area and provides significant contribution to cyber-security techniques. Multiple techniques have been in use but major concern in their implementation is variation in their detection performance. The performance of IDS lies in the accurate detection of attacks, and this accuracy can be raised by improving the recognition rate and significant reduction in the false alarms rate. To overcome this problem many researchers have used different machine learning techniques. These techniques have limitations… More >

  • ARTICLE

    Context Based Adoption of Ranking and Indexing Measures for Cricket Team Ranks

    Raja Sher Afgun Usmani1, Syed Muhammad Saqlain Shah1, *, Muhammad Sher Ramzan2, Abdullah Saad AL-Malaise AL-Ghamdi2, Anwar Ghani1, Imran Khan1, Farrukh Saleem2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1113-1136, 2020, DOI:10.32604/cmc.2020.010789
    Abstract There is an international cricket governing body that ranks the expertise of all the cricket playing nations, known as the International Cricket Council (ICC). The ranking system followed by the ICC relies on the winnings and defeats of the teams. The model used by the ICC to implement rankings is deficient in certain key respects. It ignores key factors like winning margin and strength of the opposition. Various measures of the ranking concept are presented in this research. The proposed methods adopt the concepts of h-Index and PageRank for presenting more comprehensive ranking metrics. The proposed approaches not only rank… More >

  • ARTICLE

    A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model

    Fahd N. Al-Wesabi1, 2, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1137-1156, 2020, DOI:10.32604/cmc.2020.011151
    Abstract Text information is principally dependent on the natural languages. Therefore, improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers encounter. Content authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the Internet. In this paper, an intelligent text Zero-Watermarking approach SETZWMWMM (Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model) has been proposed for the content authentication and tampering detection of English text contents. The SETZWMWMM approach embeds and detects the watermark… More >

  • ARTICLE

    Three-Dimensional Isogeometric Analysis of Flexoelectricity with MATLAB Implementation

    Hamid Ghasemi1, Harold S. Park2, Xiaoying Zhuang3, 4, *, Timon Rabczuk5, 6
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1157-1179, 2020, DOI:10.32604/cmc.2020.08358
    Abstract Flexoelectricity is a general electromechanical phenomenon where the electric polarization exhibits a linear dependency to the gradient of mechanical strain and vice versa. The truncated pyramid compression test is among the most common setups to estimate the flexoelectric effect. We present a three-dimensional isogeometric formulation of flexoelectricity with its MATLAB implementation for a truncated pyramid setup. Besides educational purposes, this paper presents a precise computational model to illustrate how the localization of strain gradients around pyramidal boundary shapes contributes in generation of electrical energy. The MATLAB code is supposed to help learners in the Isogeometric Analysis and Finite Elements Methods… More >

  • ARTICLE

    Success Rate Queue-Based Relocation Algorithm of Sensory Network to Overcome Non-Uniformly Distributed Obstacles

    Sooyeon Park1, Moonseong Kim2, Woochan Lee1, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1181-1201, 2020, DOI:10.32604/cmc.2020.011245
    Abstract With the recent development of big data technology that collects and analyzes various data, the technology that continuously collects and analyzes the observed data is also drawing attention. Moreover, its importance is growing in data collection in areas where people cannot access. In general, it is not easy to properly deploy IoT wireless devices for data collection in these areas, and it is also inappropriate to use general wheelbased mobile devices for relocation. Recently, researches have been actively carried out on hopping moving models in place of wheel-based movement for the inaccessible regions. The majority of studies, however, so far… More >

  • ARTICLE

    A Direct Data-Cluster Analysis Method Based on Neutrosophic Set Implication

    Sudan Jha1, Gyanendra Prasad Joshi2, Lewis Nkenyereya3, Dae Wan Kim4, *, Florentin Smarandache5
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1203-1220, 2020, DOI:10.32604/cmc.2020.011618
    Abstract Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine… More >

  • ARTICLE

    Roman Urdu News Headline Classification Empowered with Machine Learning

    Rizwan Ali Naqvi1, Muhammad Adnan Khan2, *, Nauman Malik2, Shazia Saqib2, Tahir Alyas2, Dildar Hussain3
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1221-1236, 2020, DOI:10.32604/cmc.2020.011686
    Abstract Roman Urdu has been used for text messaging over the Internet for years especially in Indo-Pak Subcontinent. Persons from the subcontinent may speak the same Urdu language but they might be using different scripts for writing. The communication using the Roman characters, which are used in the script of Urdu language on social media, is now considered the most typical standard of communication in an Indian landmass that makes it an expensive information supply. English Text classification is a solved problem but there have been only a few efforts to examine the rich information supply of Roman Urdu in the… More >

  • ARTICLE

    A New Idea of Fractal-Fractional Derivative with Power Law Kernel for Free Convection Heat Transfer in a Channel Flow between Two Static Upright Parallel Plates

    Dolat Khan1, Gohar Ali1, Arshad Khan2, Ilyas Khan3, *, Yu-Ming Chu4, 5, Kottakkaran Sooppy Nisar6
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1237-1251, 2020, DOI:10.32604/cmc.2020.011492
    Abstract Nowadays some new ideas of fractional derivatives have been used successfully in the present research community to study different types of mathematical models. Amongst them, the significant models of fluids and heat or mass transfer are on priority. Most recently a new idea of fractal-fractional derivative is introduced; however, it is not used for heat transfer in channel flow. In this article, we have studied this new idea of fractal fractional operators with power-law kernel for heat transfer in a fluid flow problem. More exactly, we have considered the free convection heat transfer for a Newtonian fluid. The flow is… More >

  • ARTICLE

    Statistical Inference of User Experience of Multichannel Audio on Mobile Phones

    Fesal Toosy1, *, Muhammad Sarwar Ehsan1
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1253-1270, 2020, DOI:10.32604/cmc.2020.011667
    Abstract Mobile phones and other handheld electronic devices are now ubiquitous and play an important role in our everyday lives. Over the last decade, we have seen a sharp rise in the sophistication of both hardware and software for these devices, thus significantly increasing their utility and use. Electronic devices are now commonly used for the streaming of audio and video and for the regular playback of music. Multichannel audio has now become a popular format and with recent updates in software, the latest audio codecs that support this format can effectively be played back on most electronic devices. As a… More >

  • ARTICLE

    Polynomials of Degree-Based Indices for Three-Dimensional Mesh Network

    Ali N. A. Koam1, Ali Ahmad2, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1271-1282, 2020, DOI:10.32604/cmc.2020.011736
    Abstract In order to study the behavior and interconnection of network devices, graphs structures are used to formulate the properties in terms of mathematical models. Mesh network (meshnet) is a LAN topology in which devices are connected either directly or through some intermediate devices. These terminating and intermediate devices are considered as vertices of graph whereas wired or wireless connections among these devices are shown as edges of graph. Topological indices are used to reflect structural property of graphs in form of one real number. This structural invariant has revolutionized the field of chemistry to identify molecular descriptors of chemical compounds.… More >

  • ARTICLE

    Secret Image Communication Scheme Based on Visual Cryptography and Tetrolet Tiling Patterns

    N. RajeshKumar1, D. Yuvaraj2, G. Manikandan3, *, R. BalaKrishnan1, B. Karthikeyan3, D. Narasimhan1, N. R. Raajan4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1283-1301, 2020, DOI:10.32604/cmc.2020.011226
    Abstract Visual cryptographic scheme is specially designed for secret image sharing in the form of shadow images. The basic idea of visual cryptography is to construct two or more secret shares from the original image in the form of chaotic image. In this paper, a novel secret image communication scheme based on visual cryptography and Tetrolet tiling patterns is proposed. The proposed image communication scheme will break the secret image into more shadow images based on the Tetrolet tiling patterns. The secret image is divided into 4×4 blocks of tetrominoes and employs the concept of visual cryptography to hide the secret… More >

  • ARTICLE

    Case Study: Spark GPU-Enabled Framework to Control COVID-19 Spread Using Cell-Phone Spatio-Temporal Data

    Hussein Shahata Abdallah1, *, Mohamed H. Khafagy1, Fatma A. Omara2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1303-1320, 2020, DOI:10.32604/cmc.2020.011313
    (This article belongs to this Special Issue: Artificial Intelligence and Information Technologies for COVID-19)
    Abstract Nowadays, the world is fighting a dangerous form of Coronavirus that represents an emerging pandemic. Since its early appearance in China Wuhan city, many countries undertook several strict regulations including lockdowns and social distancing measures. Unfortunately, these procedures have badly impacted the world economy. Detecting and isolating positive/probable virus infected cases using a tree tracking mechanism constitutes a backbone for containing and resisting such fast spreading disease. For helping this hard effort, this research presents an innovative case study based on big data processing techniques to build a complete tracking system able to identify the central areas of infected/suspected people,… More >

  • ARTICLE

    Ensemble Strategy for Insider Threat Detection from User Activity Logs

    Shihong Zou1, Huizhong Sun1, *, Guosheng Xu1, Ruijie Quan2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1321-1334, 2020, DOI:10.32604/cmc.2020.09649
    Abstract In the information era, the core business and confidential information of enterprises/organizations is stored in information systems. However, certain malicious inside network users exist hidden inside the organization; these users intentionally or unintentionally misuse the privileges of the organization to obtain sensitive information from the company. The existing approaches on insider threat detection mostly focus on monitoring, detecting, and preventing any malicious behavior generated by users within an organization’s system while ignoring the imbalanced ground-truth insider threat data impact on security. To this end, to be able to detect insider threats more effectively, a data processing tool was developed to… More >

  • ARTICLE

    End-to-End Latency Evaluation of the Sat5G Network Based on Stochastic Network Calculus

    Huaifeng Shi1, Chengsheng Pan1, *, Li Yang2, Debin Wei2, Yunqing Shi3
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1335-1348, 2020, DOI:10.32604/cmc.2020.011005
    Abstract Simultaneous use of heterogeneous radio access technologies to increase the performance of real-time, reliability and capacity is an inherent feature of satellite-5G integrated network (Sat5G). However, there is still a lack of theoretical characterization of whether the network can satisfy the end-to-end transmission performance for latencysensitive service. To this end, we build a tandem model considering the connection relationship between the various components in Sat5G network architecture, and give an end-to-end latency calculation function based on this model. By introducing stochastic network calculus, we derive the relationship between the end-to-end latency bound and the violation probability considering the traffic characteristics… More >

  • ARTICLE

    Fast Compass Alignment for Strapdown Inertial Navigation System

    Jin Sun1, Dengyin Zhang1, *, Xiaoye Shi1, Fei Ding1, 2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1349-1360, 2020, DOI:10.32604/cmc.2020.011459
    Abstract Initial alignment is the precondition for strapdown inertial navigation system (SINS) to navigate. Its two important indexes are accuracy and rapidity, the accuracy of the initial alignment is directly related to the working accuracy of SINS, but in selfalignment, the two indexes are often contradictory. In view of the limitations of conventional data processing algorithms, a novel method of compass alignment based on stored data and repeated navigation calculation for SINS is proposed. By means of data storage, the same data is used in different stages of the initial alignment, which is beneficial to shorten the initial alignment time and… More >

  • ARTICLE

    Ensemble Learning Based on GBDT and CNN for Adoptability Prediction

    Yunfan Ye1, Fang Liu1, *, Shan Zhao2, Wanting Hu3, Zhiyao Liang4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1361-1372, 2020, DOI:10.32604/cmc.2020.011632
    Abstract By efficiently and accurately predicting the adoptability of pets, shelters and rescuers can be positively guided on improving attraction of pet profiles, reducing animal suffering and euthanization. Previous prediction methods usually only used a single type of content for training. However, many pets contain not only textual content, but also images. To make full use of textual and visual information, this paper proposed a novel method to process pets that contain multimodal information. We employed several CNN (Convolutional Neural Network) based models and other methods to extract features from images and texts to obtain the initial multimodal representation, then reduce… More >

  • ARTICLE

    Rate-Energy Tradeoff for Wireless Simultaneous Information and Power Transfer in Full-Duplex and Half-Duplex Systems

    Xiaoye Shi1, *, Jin Sun1, Dongming Li1, Fei Ding2, Zhaowei Zhang1
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1373-1384, 2020, DOI:10.32604/cmc.2020.011018
    Abstract In this paper, we study the rate-energy tradeoff for wireless simultaneous information and power transfer in full-duplex and half-duplex scenarios. To this end, the weighting function of energy efficiency and transmission rate, as rate-energy tradeoff metric is first introduced and the metric optimization problem is formulated. Applying Karush-Kuhn-Tucker (KKT) conditions for Lagrangian optimality and a series of mathematical approximations, the metric optimization problem can be simplified. The closed-form solution of the power ratio is obtained, building direct relationship between power ratio and the rate-energy tradeoff metric. By choosing power ratio, one can make the tradeoff between information rate and harvested… More >

  • ARTICLE

    Remote Sensing Image Classification Algorithm Based on Texture Feature and Extreme Learning Machine

    Xiangchun Liu1, Jing Yu2,Wei Song1, 3, *, Xinping Zhang1, Lizhi Zhao1, Antai Wang4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1385-1395, 2020, DOI:10.32604/cmc.2020.011308
    Abstract With the development of satellite technology, the satellite imagery of the earth’s surface and the whole surface makes it possible to survey surface resources and master the dynamic changes of the earth with high efficiency and low consumption. As an important tool for satellite remote sensing image processing, remote sensing image classification has become a hot topic. According to the natural texture characteristics of remote sensing images, this paper combines different texture features with the Extreme Learning Machine, and proposes a new remote sensing image classification algorithm. The experimental tests are carried out through the standard test dataset SAT-4 and… More >

  • ARTICLE

    Quantum Hierarchical Agglomerative Clustering Based on One Dimension Discrete Quantum Walk with Single-Point Phase Defects

    Gongde Guo1, Kai Yu1, Hui Wang2, Song Lin1, *, Yongzhen Xu1, Xiaofeng Chen3
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1397-1409, 2020, DOI:10.32604/cmc.2020.011399
    Abstract As an important branch of machine learning, clustering analysis is widely used in some fields, e.g., image pattern recognition, social network analysis, information security, and so on. In this paper, we consider the designing of clustering algorithm in quantum scenario, and propose a quantum hierarchical agglomerative clustering algorithm, which is based on one dimension discrete quantum walk with single-point phase defects. In the proposed algorithm, two nonclassical characters of this kind of quantum walk, localization and ballistic effects, are exploited. At first, each data point is viewed as a particle and performed this kind of quantum walk with a parameter,… More >

  • ARTICLE

    Empirical Analysis of Agricultural Cultural Resources Value Evaluation under DEA Model

    Wei Liang1, 2, Yang Ni3, Tingyi Li1, Xuejiao Lin1, Soo-Jin Chung1, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1411-1424, 2020, DOI:10.32604/cmc.2020.011166
    Abstract Agricultural culture is a productive activity about education and management. It aims at high efficiency and high quality, uses technology as its means, and takes nature as its carrier. Agricultural cultural resources are the product of the rapid development of modern economy. It promotes the development of the national economy and profoundly affects people's production and life. DEA model, also known as data envelope analysis method, is an algorithm that uses multiple data decision units for input and output training to obtain the final model. This article explains the concept and basic characteristics of agricultural culture. Through questionnaire surveys and… More >

  • ARTICLE

    An Improved Differential Fault Analysis on Block Cipher KLEIN-64

    Min Long1, *, Man Kong1, Sai Long1, Xiang Zhang2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1425-1436, 2020, DOI:10.32604/cmc.2020.011116
    Abstract KLEIN-64 is a lightweight block cipher designed for resource-constrained environment, and it has advantages in software performance and hardware implementation. Recent investigation shows that KLEIN-64 is vulnerable to differential fault attack (DFA). In this paper, an improved DFA is performed to KLEIN-64. It is found that the differential propagation path and the distribution of the S-box can be fully utilized to distinguish the correct and wrong keys when a half-byte fault is injected in the 10th round. By analyzing the difference matrix before the last round of S-box, the location of fault injection can be limited to a small range.… More >

  • ARTICLE

    Adversarial Attacks on License Plate Recognition Systems

    Zhaoquan Gu1, Yu Su1, Chenwei Liu1, Yinyu Lyu1, Yunxiang Jian1, Hao Li2, Zhen Cao3, Le Wang1, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1437-1452, 2020, DOI:10.32604/cmc.2020.011834
    Abstract The license plate recognition system (LPRS) has been widely adopted in daily life due to its efficiency and high accuracy. Deep neural networks are commonly used in the LPRS to improve the recognition accuracy. However, researchers have found that deep neural networks have their own security problems that may lead to unexpected results. Specifically, they can be easily attacked by the adversarial examples that are generated by adding small perturbations to the original images, resulting in incorrect license plate recognition. There are some classic methods to generate adversarial examples, but they cannot be adopted on LPRS directly. In this paper,… More >

  • ARTICLE

    Picture-Induced EEG Signal Classification Based on CVC Emotion Recognition System

    Huiping Jiang1, *, Zequn Wang1, Rui Jiao1, Shan Jiang2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1453-1465, 2020, DOI:10.32604/cmc.2020.011793
    Abstract Emotion recognition systems are helpful in human–machine interactions and Intelligence Medical applications. Electroencephalogram (EEG) is closely related to the central nervous system activity of the brain. Compared with other signals, EEG is more closely associated with the emotional activity. It is essential to study emotion recognition based on EEG information. In the research of emotion recognition based on EEG, it is a common problem that the results of individual emotion classification vary greatly under the same scheme of emotion recognition, which affects the engineering application of emotion recognition. In order to improve the overall emotion recognition rate of the emotion… More >

  • ARTICLE

    Software Defect Prediction Based on Non-Linear Manifold Learning and Hybrid Deep Learning Techniques

    Kun Zhu1, Nana Zhang1, Qing Zhang2, Shi Ying1, *, Xu Wang3
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1467-1486, 2020, DOI:10.32604/cmc.2020.011415
    Abstract Software defect prediction plays a very important role in software quality assurance, which aims to inspect as many potentially defect-prone software modules as possible. However, the performance of the prediction model is susceptible to high dimensionality of the dataset that contains irrelevant and redundant features. In addition, software metrics for software defect prediction are almost entirely traditional features compared to the deep semantic feature representation from deep learning techniques. To address these two issues, we propose the following two solutions in this paper: (1) We leverage a novel non-linear manifold learning method - SOINN Landmark Isomap (SLIsomap) to extract the… More >

  • ARTICLE

    A Robust Resource Allocation Scheme for Device-to-Device Communications Based on Q-Learning

    Azka Amin1, Xihua Liu2, Imran Khan3, Peerapong Uthansakul4, *, Masoud Forsat5, Seyed Sajad Mirjavadi5
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1487-1505, 2020, DOI:10.32604/cmc.2020.011749
    Abstract One of the most effective technology for the 5G mobile communications is Device-to-device (D2D) communication which is also called terminal pass-through technology. It can directly communicate between devices under the control of a base station and does not require a base station to forward it. The advantages of applying D2D communication technology to cellular networks are: It can increase the communication system capacity, improve the system spectrum efficiency, increase the data transmission rate, and reduce the base station load. Aiming at the problem of co-channel interference between the D2D and cellular users, this paper proposes an efficient algorithm for resource… More >

  • ARTICLE

    Quantum Electronic Contract Scheme Based on Single Photon

    Tian Cao1, Yan Chang1, *, Lili Yan1, Shibin Zhang1, Qirun Wang2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1507-1517, 2020, DOI:10.32604/cmc.2020.010213
    Abstract An electronic contract is a contract signed by electronic means, which is widely used in electronic commerce activities. In recent years, with the rapid development of quantum cryptography technology, the quantum electronic contract has been widely studied by researchers. Supported by the basic principles of quantum mechanics, a quantum electronic contract scheme based on the single photon is proposed in this paper. In this scheme, two copies of the same contract are signed by both parties involved, and then a copy of each contract is sent to a trusted third party. The trusted third party verifies the signatures of both… More >

  • ARTICLE

    A Two-Dimension Time-Domain Comparator for Low Power SAR ADCs

    Liangbo Xie1, *, Sheng Li1, Yan Ren1, Zhengwen Huang2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1519-1529, 2020, DOI:10.32604/cmc.2020.011701
    Abstract This paper presents a two-dimension time-domain comparator suitable for low power successive-approximation register (SAR) analog-to-digital converters (ADCs). The proposed two-dimension time-domain comparator consists of a ring oscillator collapsebased comparator and a counter. The propagation delay of a voltage controlled ring oscillator depends on the input. Thus, the comparator can automatically change the comparison time according to its input difference, which can adjust the power consumption of the comparator dynamically without any control logic. And a counter is utilized to count the cycle needed to finish a comparison when the input difference is small. Thus, the proposed comparator can not only… More >

  • ARTICLE

    Blockzone: A Decentralized and Trustworthy Data Plane for DNS

    Ning Hu1, Shi Yin1, Shen Su1, *, Xudong Jia1, Qiao Xiang2, Hao Liu3
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1531-1557, 2020, DOI:10.32604/cmc.2020.010949
    Abstract The domain name system (DNS) provides a mapping service between memorable names and numerical internet protocol addresses, and it is a critical infrastructure of the Internet. The authenticity of DNS resolution results is crucial for ensuring the accessibility of Internet services. Hundreds of supplementary specifications of protocols have been proposed to compensate for the security flaws of DNS. However, DNS security incidents still occur frequently. Although DNS is a distributed system, for a specified domain name, only authorized authoritative servers can resolve it. Other servers must obtain the resolution result through a recursive or iterative resolving procedure, which renders DNS… More >

  • ARTICLE

    A Trust Value Sharing Scheme in Heterogeneous Identity Federation Topologies

    Ning Liu1, Fan Yang1, *, Xi Xiong1, 2, Yan Chang1, Shibin Zhang1
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1559-1570, 2020, DOI:10.32604/cmc.2020.010562
    Abstract Recent developments in heterogeneous identity federation systems have heightened the need for the related trust management system. The trust management system evaluates, manages, and shares users’ trust values. The service provider (SP) members of the federation system rely on users’ trust values to determine which type and quality of service will be provided to the users. While identity federation systems have the potential to help federated users save time and energy and improve service experience, the benefits also come with significant privacy risks. So far, there has been little discussion about the privacy protection of users in heterogeneous identity federation… More >

  • ARTICLE

    Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks

    Jianzhong Li1, DexiangMei1, Dong Deng1, Imran Khan2, Peerapong Uthansakul3, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1571-1590, 2020, DOI:10.32604/cmc.2020.011822
    Abstract Non-orthogonal multiple access (NOMA) is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner. NOMA allows multiple terminals to share the same resource unit at the same time. The receiver usually needs to configure successive interference cancellation (SIC). The receiver eliminates co-channel interference (CCI) between users and it can significantly improve the system throughput. In order to meet the demands of users and improve fairness among them, this paper proposes a new power allocation scheme. The objective is to maximize user fairness by… More >

  • ARTICLE

    Recommendation Algorithm Based on Probabilistic Matrix Factorization with Adaboost

    Hongtao Bai1, 2, Xuan Li1, 2, Lili He1, 2, Longhai Jin1, 2, Chong Wang1, 2, 3, Yu Jiang1, 2, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1591-1603, 2020, DOI:10.32604/cmc.2020.09981
    Abstract A current problem in diet recommendation systems is the matching of food preferences with nutritional requirements, taking into account individual characteristics, such as body weight with individual health conditions, such as diabetes. Current dietary recommendations employ association rules, content-based collaborative filtering, and constraint-based methods, which have several limitations. These limitations are due to the existence of a special user group and an imbalance of non-simple attributes. Making use of traditional dietary recommendation algorithm researches, we combine the Adaboost classifier with probabilistic matrix factorization. We present a personalized diet recommendation algorithm by taking advantage of probabilistic matrix factorization via Adaboost. A… More >

  • ARTICLE

    An Adjust Duty Cycle Method for Optimized Congestion Avoidance and Reducing Delay for WSNs

    Ting Xu1, Ming Zhao1, Xin Yao1, *, Kun He2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1605-1624, 2020, DOI:10.32604/cmc.2020.011458
    Abstract With the expansion of the application range and network scale of wireless sensor networks in recent years, WSNs often generate data surges and delay queues during the transmission process, causing network paralysis, even resulting in local or global congestion. In this paper, a dynamically Adjusted Duty Cycle for Optimized Congestion based on a real-time Queue Length (ADCOC) scheme is proposed. In order to improve the resource utilization rate of network nodes, we carried out optimization analysis based on the theory and applied it to the adjustment of the node’s duty cycle strategy. Using this strategy to ensure that the network… More >

  • ARTICLE

    A Middleware for Polyglot Persistence and Data Portability of Big Data PaaS Cloud Applications

    Kiranbir Kaur1, *, Sandeep Sharma1, Karanjeet Singh Kahlon2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1625-1647, 2020, DOI:10.32604/cmc.2020.011535
    Abstract Vendor lock-in can occur at any layer of the cloud stack-Infrastructure, Platform, and Software-as-a-service. This paper covers the vendor lock-in issue at Platform as a Service (PaaS) level where applications can be created, deployed, and managed without worrying about the underlying infrastructure. These applications and their persisted data on one PaaS provider are not easy to port to another provider. To overcome this issue, we propose a middleware to abstract and make the database services as cloud-agnostic. The middleware supports several SQL and NoSQL data stores that can be hosted and ported among disparate PaaS providers. It facilitates the developers… More >

  • ARTICLE

    A Novel Method for Node Connectivity with Adaptive Dragonfly Algorithm and Graph-Based m-Connection Establishment in MANET

    S. B. Manoojkumaar1, *, C. Poongodi2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1649-1670, 2020, DOI:10.32604/cmc.2020.010781
    Abstract Maximizing network lifetime is measured as the primary issue in Mobile Adhoc Networks (MANETs). In geographically routing based models, packet transmission seems to be more appropriate in dense circumstances. The involvement of the Heuristic model directly is not appropriate to offer an effectual solution as it becomes NP-hard issues; therefore investigators concentrate on using Meta-heuristic approaches. Dragonfly Optimization (DFO) is an effective meta-heuristic approach to resolve these problems by providing optimal solutions. Moreover, Meta-heuristic approaches (DFO) turn to be slower in convergence problems and need proper computational time while expanding network size. Thus, DFO is adaptively improved as Adaptive Dragonfly… More >

  • ARTICLE

    Quantum Algorithms and Experiment Implementations Based on IBM Q

    Wenjie Liu1, 2, *, Junxiu Chen2, Yinsong Xu2, Jiahao Tang2, Lian Tong3, Xiaoyu Song4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1671-1689, 2020, DOI:10.32604/cmc.2020.07564
    Abstract With the rapid development of quantum theory and technology in recent years, especially the emergence of some quantum cloud computing platforms, more and more researchers are not satisfied with the theoretical derivation and simulation verification of quantum computation (especially quantum algorithms), experimental verification on real quantum devices has become a new trend. In this paper, three representative quantum algorithms, namely Deutsch-Jozsa, Grover, and Shor algorithms, are briefly depicted, and then their implementation circuits are presented, respectively. We program these circuits on python with QISKit to connect the remote real quantum devices (i.e., ibmqx4, ibmqx5) on IBM Q to verify these… More >

  • ARTICLE

    An Improved Deep Fusion CNN for Image Recognition

    Rongyu Chen1, Lili Pan1, *, Cong Li1, Yan Zhou1, Aibin Chen1, Eric Beckman2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1691-1706, 2020, DOI:10.32604/cmc.2020.011706
    Abstract With the development of Deep Convolutional Neural Networks (DCNNs), the extracted features for image recognition tasks have shifted from low-level features to the high-level semantic features of DCNNs. Previous studies have shown that the deeper the network is, the more abstract the features are. However, the recognition ability of deep features would be limited by insufficient training samples. To address this problem, this paper derives an improved Deep Fusion Convolutional Neural Network (DF-Net) which can make full use of the differences and complementarities during network learning and enhance feature expression under the condition of limited datasets. Specifically, DF-Net organizes two… More >

  • ARTICLE

    Paillier-Based Fuzzy Multi-Keyword Searchable Encryption Scheme with Order-Preserving

    Xiehua Li1,*, Fang Li1, Jie Jiang1, Xiaoyu Mei2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1707-1721, 2020, DOI:10.32604/cmc.2020.011227
    Abstract Efficient multi-keyword fuzzy search over encrypted data is a desirable technology for data outsourcing in cloud storage. However, the current searchable encryption solutions still have deficiencies in search efficiency, accuracy and multiple data owner support. In this paper, we propose an encrypted data searching scheme that can support multiple keywords fuzzy search with order preserving (PMS). First, a new spelling correction algorithm-(Possibility-Levenshtein based Spelling Correction) is proposed to correct user input errors, so that fuzzy keywords input can be supported. Second, Paillier encryption is introduced to calculate encrypted relevance score of multiple keywords for order preserving. Then, a queue-based query… More >

  • ARTICLE

    Identifying Honeypots from ICS Devices Using Lightweight Fuzzy Testing

    Yanbin Sun1, Xiaojun Pan1, Chao Xu2, Penggang Sun2, Quanlong Guan3, Mohan Li1, *, Men Han4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1723-1737, 2020, DOI:10.32604/cmc.2020.010593
    Abstract The security issues of industrial control systems (ICSs) have become increasingly prevalent. As an important part of ICS security, honeypots and antihoneypots have become the focus of offensive and defensive confrontation. However, research on ICS honeypots still lacks breakthroughs, and it is difficult to simulate real ICS devices perfectly. In this paper, we studied ICS honeypots to identify and address their weaknesses. First, an intelligent honeypot identification framework is proposed, based on which feature data type requirements and feature data acquisition for honeypot identification is studied. Inspired by vulnerability mining, we propose a feature acquisition approach based on lightweight fuzz… More >

  • ARTICLE

    Research on Real-Time High Reliable Network File Distribution Technology

    Chenglong Li1, Peipeng Liu1, Hewei Yu1, *, Mengmeng Ge2, Xiangzhan Yu2, Yi Xin2, Yuhang Wang3, Dongyu Zhang4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1739-1752, 2020, DOI:10.32604/cmc.2020.09019
    Abstract The rapid development of Internet of Things (IoT) technology has made previously unavailable data available, and applications can take advantage of device data for people to visualize, explore, and build complex analyses. As the size of the network and the number of network users continue to increase, network requests tend to aggregate on a small number of network resources, which results in uneven load on network requests. Real-time, highly reliable network file distribution technology is of great importance in the Internet of Things. This paper studies real-time and highly reliable file distribution technology for large-scale networks. In response to this… More >

  • ARTICLE

    Secure Provenance of Electronic Records Based on Blockchain

    Qirun Wang1, Fujian Zhu2, Sai Ji2, Yongjun Ren2, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1753-1769, 2020, DOI:10.32604/cmc.2020.07366
    Abstract At present, the provenance of electronic records is stored centrally. The centralized way of information storage has huge risks. Whether the database itself is destroyed or the communication between the central database and the external interruption occurs, the provenance information of the stored electronic records will not play its role. At the same time, uncertainties such as fires and earthquakes will also pose a potential threat to centralized databases. Moreover, the existing security provenance model is not specifically designed for electronic records. In this paper, a security provenance model of electronic records is constructed based on PREMIS and METS. Firstly,… More >

  • ARTICLE

    Tissue Segmentation in Nasopharyngeal CT Images Using TwoStage Learning

    Yong Luo1, Xiaojie Li2, Chao Luo2, Feng Wang1, Xi Wu2, Imran Mumtaz3, Cheng Yi1, *
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1771-1780, 2020, DOI:10.32604/cmc.2020.010069
    Abstract Tissue segmentation is a fundamental and important task in nasopharyngeal images analysis. However, it is a challenging task to accurately and quickly segment various tissues in the nasopharynx region due to the small difference in gray value between tissues in the nasopharyngeal image and the complexity of the tissue structure. In this paper, we propose a novel tissue segmentation approach based on a two-stage learning framework and U-Net. In the proposed methodology, the network consists of two segmentation modules. The first module performs rough segmentation and the second module performs accurate segmentation. Considering the training time and the limitation of… More >

  • ARTICLE

    A Hybrid Path Planning Method Based on Articulated Vehicle Model

    Zhongping Chen1, Dong Wang1, *, Gang Chen2, Yanxi Ren3, Danjie Du4
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1781-1793, 2020, DOI:10.32604/cmc.2020.010902
    Abstract Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature… More >

  • ARTICLE

    APU-D* Lite: Attack Planning under Uncertainty Based on D* Lite

    Tairan Hu1, Tianyang Zhou1, Yichao Zang1, *, Qingxian Wang1, Hang Li2
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1795-1807, 2020, DOI:10.32604/cmc.2020.011071
    Abstract With serious cybersecurity situations and frequent network attacks, the demands for automated pentests continue to increase, and the key issue lies in attack planning. Considering the limited viewpoint of the attacker, attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach, but it also poses some challenges. To address the efficiency problem in uncertainty planning, we propose the APU-D* Lite algorithm in this paper. First, the pentest framework is mapped to the planning problem with the Planning Domain Definition Language (PDDL). Next, we develop the pentest information graph to organize network information and… More >

  • ARTICLE

    Computational Analysis of the Effect of Nano Particle Material Motion on Mixed Convection Flow in the Presence of Heat Generation and Absorption

    Muhammad Ashraf1, Amir Abbas1, Saqib Zia2, Yu-Ming Chu3, 4, Ilyas Khan5, *, Kottakkaran Sooppy Nisar6
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1809-1823, 2020, DOI:10.32604/cmc.2020.011404
    Abstract The present study is concerned with the physical behavior of the combined effect of nano particle material motion and heat generation/absorption due to the effect of different parameters involved in prescribed flow model. The formulation of the flow model is based on basic universal equations of conservation of momentum, energy and mass. The prescribed flow model is converted to non-dimensional form by using suitable scaling. The obtained transformed equations are solved numerically by using finite difference scheme. For the analysis of above said behavior the computed numerical data for fluid velocity, temperature profile, and mass concentration for several constraints that… More >

  • ARTICLE

    Who Will Come: Predicting Freshman Registration Based on Decision Tree

    Lei Yang1, Li Feng1, *, Liwei Tian1, Hongning Dai1
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1825-1836, 2020, DOI:10.32604/cmc.2020.010011
    Abstract The registration rate of freshmen has been a great concern at many colleges and universities, particularly private institutions. Traditionally, there are two inquiry methods: telephone and tuition-payment-status. Unfortunately, the former is not only time-consuming but also suffers from the fact that many students tend to keep their choices secret. On the other hand, the latter is not always feasible because only few students are willing to pay their university tuition fees in advance. It is often believed that it is impossible to predict incoming freshmen’s choice of university due to the large amount of subjectivity. However, if we look at… More >

  • ARTICLE

    Research on Data Extraction and Analysis of Software Defect in IoT Communication Software

    Wenbin Bi1, Fang Yu2, Ning Cao3, Wei Huo3, Guangsheng Cao4, *, Xiuli Han5, Lili Sun6, Russell Higgs7
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1837-1854, 2020, DOI:10.32604/cmc.2020.010420
    Abstract Software defect feature selection has problems of feature space dimensionality reduction and large search space. This research proposes a defect prediction feature selection framework based on improved shuffled frog leaping algorithm (ISFLA).Using the two-level structure of the framework and the improved hybrid leapfrog algorithm's own advantages, the feature values are sorted, and some features with high correlation are selected to avoid other heuristic algorithms in the defect prediction that are easy to produce local The case where the convergence rate of the optimal or parameter optimization process is relatively slow. The framework improves generalization of predictions of unknown data samples… More >

  • ARTICLE

    An Improved Binary Search Anti-Collision Protocol for RFID Tag Identification

    Guozhong Dong1, Weizhe Zhang1, 2, *, Sichang Xuan3, Feng Qin4, Haowen Tan5
    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1855-1868, 2020, DOI:10.32604/cmc.2020.09919
    Abstract Radio frequency identification (RFID) has been widespread used in massive items tagged domains. However, tag collision increases both time and energy consumption of RFID network. Tag collision can seriously affect the success of tag identification. An efficient anti-collision protocol is very crucially in RFID system. In this paper, an improved binary search anti-collision protocol namely BRTP is proposed to cope with the tag collision concern, which introduces a Bi-response mechanism. In Biresponse mechanism, two groups of tags allowed to reply to the reader in the same slot. According to Bi-response mechanism, the BRTP strengthens the tag identification of RFID network… More >

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