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  • Open Access

    ARTICLE

    Secrecy Outage Probability Analysis Based on Cognitive Decodeand-Forward Relaying

    Ruoyu Su1, 4, Xiaojun Sun1, 3, Fei Ding1, 2, *, Dengyin Zhang1, 2, Hongbo Zhu1, 2, M. I. M. Wahab5

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1387-1395, 2020, DOI:10.32604/cmc.2020.06864

    Abstract Wireless communications have to face to several different security issues in practice due to the nature of broadcast. The information theory is well known to provide efficient approaches to address security issues in wireless communications, which attracts much attention in both industry and academia in recent years. In this paper, inspired by information theory, we study the outage probability of the opportunistic relay selection based on cognitive decode-and-forward relaying with the secrecy consideration. Specifically, the closed-form expression of the outage probability is proposed. Moreover, the asymptotic performance evaluation on the basis of the analytical results More >

  • Open Access

    ARTICLE

    A Novel Bidirectional LSTM and Attention Mechanism Based Neural Network for Answer Selection in Community Question Answering

    Bo Zhang1, Haowen Wang1, #, Longquan Jiang1, Shuhan Yuan2, Meizi Li1, *

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1273-1288, 2020, DOI:10.32604/cmc.2020.07269

    Abstract Deep learning models have been shown to have great advantages in answer selection tasks. The existing models, which employ encoder-decoder recurrent neural network (RNN), have been demonstrated to be effective. However, the traditional RNN-based models still suffer from limitations such as 1) high-dimensional data representation in natural language processing and 2) biased attentive weights for subsequent words in traditional time series models. In this study, a new answer selection model is proposed based on the Bidirectional Long Short-Term Memory (Bi-LSTM) and attention mechanism. The proposed model is able to generate the more effective question-answer pair More >

  • Open Access

    ARTICLE

    Strategy Selection for Moving Target Defense in Incomplete Information Game

    Huan Zhang1, Kangfeng Zheng1, *, Xiujuan Wang2, Shoushan Luo1, Bin Wu1

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 763-786, 2020, DOI:10.32604/cmc.2020.06553

    Abstract As a core component of the network, web applications have become one of the preferred targets for attackers because the static configuration of web applications simplifies the exploitation of vulnerabilities by attackers. Although the moving target defense (MTD) has been proposed to increase the attack difficulty for the attackers, there is no solo approach can cope with different attacks; in addition, it is impossible to implement all these approaches simultaneously due to the resource limitation. Thus, the selection of an optimal defense strategy based on MTD has become the focus of research. In general, the… More >

  • Open Access

    ARTICLE

    The Frequency Selection of SH0 Waves for Total Transmission and Its Application in the Damage Detection of Aircrafts

    Yanchao Yue1, *, Tangbing Chen1, Lingling Zhang1, Moustafa Abdelsalam1, Josephine Musanyufu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 259-272, 2020, DOI:10.32604/cmes.2020.07218 - 01 January 2020

    Abstract Based on wave interference, a methodology to realize the total transmission phenomenon of SH0 waves is proposed in this paper. After a systematical theoretical investigation, an exact frequency of a flat plate consisting of another medium with finite length, is obtained, which is furthermore exemplified by the finite element method. This frequency is the same as the classical Fabry-Perot condition and dependent on the thickness of the material. It has been revealed that an SH0 wave, with its wavelength equal to twice of the length of another medium, can totally transmit across the medium without… More >

  • Open Access

    ARTICLE

    An Improved Whale Optimization Algorithm for Feature Selection

    Wenyan Guo1, *, Ting Liu1, Fang Dai1, Peng Xu1

    CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 337-354, 2020, DOI:10.32604/cmc.2020.06411

    Abstract Whale optimization algorithm (WOA) is a new population-based metaheuristic algorithm. WOA uses shrinking encircling mechanism, spiral rise, and random learning strategies to update whale’s positions. WOA has merit in terms of simple calculation and high computational accuracy, but its convergence speed is slow and it is easy to fall into the local optimal solution. In order to overcome the shortcomings, this paper integrates adaptive neighborhood and hybrid mutation strategies into whale optimization algorithms, designs the average distance from itself to other whales as an adaptive neighborhood radius, and chooses to learn from the optimal solution… More >

  • Open Access

    ARTICLE

    Application of Radial Basis Function Networks with Feature Selection for GDP Per Capita Estimation Based on Academic Parameters

    Abdullah Erdal Tümer1,∗, Aytekin Akku¸s2

    Computer Systems Science and Engineering, Vol.34, No.3, pp. 145-150, 2019, DOI:10.32604/csse.2019.34.145

    Abstract In this work, a system based on Radial Basis Function Network was developed to estimate Gross Domestic Product per capita. The data set based on 180 academic parameters of 13 Organisation for Economic Co-operation and Development countries was used to verify the effectiveness and accuracy of the proposed method. Gross Domestic Product per capita was studied to be estimated for the first time with academic parameters in this study. The system has been optimized using feature selection method to eliminate unimportant features. Radial Basis Function network results and Radial Basis Function network with feature selection More >

  • Open Access

    ARTICLE

    Feature Selection and Representation of Evolutionary Algorithm on Keystroke Dynamics

    Purvashi Baynath, Sunjiv Soyjaudah, Maleika Heenaye-Mamode Khan

    Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 651-661, 2019, DOI:10.31209/2018.100000060

    Abstract The goal of this paper is (i) adopt fusion of features (ii) determine the best method of feature selection technique among ant Colony optimisation, artificial bee colony optimisation and genetic algorithm. The experimental results reported that ant colony Optimisation is a promising techniques as feature selection on Keystroke Dynamics as it outperforms in terms of recognition rate for our inbuilt database where the distance between the keys has been considered for the password derivation with recognition rate 97.85%. Finally the results have shown that a small improvement is obtained by fused features, which suggest that More >

  • Open Access

    ARTICLE

    Novel Android Malware Detection Method Based on Multi-dimensional Hybrid Features Extraction and Analysis

    Yue Li1, Guangquan Xu2,3, Hequn Xian1,*, Longlong Rao3, Jiangang Shi4,*

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 637-647, 2019, DOI:10.31209/2019.100000118

    Abstract In order to prevent the spread of Android malware and protect privacy information from being compromised, this study proposes a novel multidimensional hybrid features extraction and analysis method for Android malware detection. This method is based primarily on a multidimensional hybrid features vector by extracting the information of permission requests, API calls, and runtime behaviors. The innovation of this study is to extract greater amounts of static and dynamic features information and combine them, that renders the features vector for training completer and more comprehensive. In addition, the feature selection algorithm is used to further More >

  • Open Access

    ARTICLE

    Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm

    Tinghuai Ma1,*, Honghao Zhou1, Dongdong Jia1, Abdullah Al-Dhelaan2, Mohammed Al-Dhelaan2, Yuan Tian3

    CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 569-592, 2019, DOI:10.32604/cmes.2019.07758

    Abstract Feature selection has been widely used in data mining and machine learning. Its objective is to select a minimal subset of features according to some reasonable criteria so as to solve the original task more quickly. In this article, a feature selection algorithm with local search strategy based on the forest optimization algorithm, namely FSLSFOA, is proposed. The novel local search strategy in local seeding process guarantees the quality of the feature subset in the forest. Next, the fitness function is improved, which not only considers the classification accuracy, but also considers the size of More >

  • Open Access

    ARTICLE

    Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

    Xuting Duan1,2,3, Jingyi Wei1,2,3, Daxin Tian1,2,3,*, Jianshan Zhou1,2,3,4, Haiying Xia5, Xin Li6, Kunxian Zheng1,2,3

    CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1117-1128, 2019, DOI:10.32604/cmc.2019.05578

    Abstract In vehicle ad-hoc networks (VANETs), the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes significant. Motivated by the self-adaptive paradigm of cellular attractors, this paper regards an individual communication as a cell, so that we can apply the revised attractor selection model to induce each connected vehicle. Aiming at improving the Quality of Service (QoS), we presented the bio-inspired handover decision-making mechanism. In addition, we employ the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) for any vehicle to choose an access network. This More >

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