Sheng Liu^{1, *}, Hailin Cao², Decheng Wu², Xiyuan Chen³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 589-605, 2020, DOI:10.32604/cmc.2020.09964

Abstract Arranging multiple identical sub-arrays in a special way can enhance degrees of freedom (DOFs) and obtain a hole-free difference co-array (DCA). In this paper, by adjusting the interval of adjacent sub-arrays, a kind of generalized array architecture with larger aperture is proposed. Although some holes may exist in the DCA of the proposed array, they are distributed uniformly. Utilizing the partial continuity of the DCA, an extended covariance matrix can be constructed. Singular value decomposition (SVD) is used to obtain an extended signal sub-space, by which the direction-of-arrival (DOA) estimation algorithm for quasi-stationary signals is given. In order to eliminating… More >

Xiaoping Zhao^{1, 4}, Yifei Wang^{2, *}, Yonghong Zhang², Jiaxin Wu¹, Yunqing Shi³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 571-587, 2020, DOI:10.32604/cmc.2020.06363

Abstract Stochastic resonance can use noise to enhance weak signals, effectively reducing the effect of noise signals on feature extraction. In order to improve the early fault recognition rate of rolling bearings, and to overcome the shortcomings of lack of interaction in the selection of SR (Stochastic Resonance) method parameters and the lack of validation of the extracted features, an adaptive genetic random resonance early fault diagnosis method for rolling bearings was proposed. compared with the existing methods, the AGSR (Adaptive Genetic Stochastic Resonance) method uses genetic algorithms to optimize the system parameters, and further optimizes the parameters while considering the… More >

Kehua Yang^{1, *}, Shaosong Long¹, Wei Zhang¹, Jiqing Yao², Jing Liu¹

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 557-570, 2020, DOI:10.32604/cmc.2020.09907

Abstract The personalized news recommendation has been very popular in the news recommendation field. In most research, the picture information in the news is ignored, but the information conveyed to the users through pictures is more intuitive and more likely to affect the users’ reading interests than the one in the textual form. Therefore, in this paper, a model that combines images and texts in the news is proposed. In this model, the new tags are extracted from the images and texts in the news, and based on these new tags, an adaptive tag (AT) algorithm is proposed. The AT algorithm… More >

Shu Fang¹, Lei Huang¹, Yi Wan², Weize Sun^{1, *}, Jingxin Xu³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 541-555, 2020, DOI:10.32604/cmc.2020.010066

Abstract With the development of science and technology, the status of the water environment has received more and more attention. In this paper, we propose a deep learning model, named a Joint Auto-Encoder network, to solve the problem of outlier detection in water supply data. The Joint Auto-Encoder network first expands the size of training data and extracts the useful features from the input data, and then reconstructs the input data effectively into an output. The outliers are detected based on the network’s reconstruction errors, with a larger reconstruction error indicating a higher rate to be an outlier. For water supply… More >

Chao Guo¹, Cheng Gong², Juan Guo³, Zhanzhen Wei^{1, *}, Yanyan Han¹, Sher Zaman Khan⁴

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 527-540, 2020, DOI:10.32604/cmc.2020.09788

Abstract Under the background of the rapid development of ground mobile communication, the advantages of high coverage, survivability, and flexibility of satellite communication provide air support to the construction of space information network. According to the requirements of the future space information communication, a software-defined Space-Air-Ground Integrated network architecture was proposed. It consisted of layered structure satellite backbone network, deep space communication network, the stratosphere communication network and the ground network. The SpaceAir-Ground Integrated network was supported by the satellite backbone network. It provided data relay for the missions such as deep space exploration and controlled the deep-space spacecraft when needed.… More >

Weibo Yang¹, Weidong Liu^{2, *}, Jinming Liu³, Mingyang Zhang⁴

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 515-525, 2020, DOI:10.32604/cmc.2020.09801

Abstract The Convolutional Neural Network (CNN) is a widely used deep neural network. Compared with the shallow neural network, the CNN network has better performance and faster computing in some image recognition tasks. It can effectively avoid the problem that network training falls into local extremes. At present, CNN has been applied in many different fields, including fault diagnosis, and it has improved the level and efficiency of fault diagnosis. In this paper, a two-streams convolutional neural network (TCNN) model is proposed. Based on the short-time Fourier transform (STFT) spectral and Mel Frequency Cepstrum Coefficient (MFCC) input characteristics of two-streams acoustic… More >

Yifei Wei^{1, *}, Yu Gong¹, Qiao Li¹, Mei Song^{1, *}, Xiaojun Wang²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 501-514, 2020, DOI:10.32604/cmc.2020.010048

Abstract In this paper, maximizing energy efficiency (EE) through radio resource allocation for renewable energy powered heterogeneous cellular networks (HetNet) with energy sharing, is investigated. Our goal is to maximize the network EE, conquer the instability of renewable energy sources and guarantee the fairness of users during allocating resources. We define the objective function as a sum weighted EE of all links in the HetNet. We formulate the resource allocation problem in terms of subcarrier assignment, power allocation and energy sharing, as a mixed combinatorial and non-convex optimization problem. We propose an energy efficient resource allocation scheme, including a centralized resource… More >

Nana Zhang¹, Kun Zhu¹, Shi Ying^{1, *}, Xu Wang²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 471-499, 2020, DOI:10.32604/cmc.2020.010117

Abstract Software defect prediction is a research hotspot in the field of software engineering. However, due to the limitations of current machine learning algorithms, we can’t achieve good effect for defect prediction by only using machine learning algorithms. In previous studies, some researchers used extreme learning machine (ELM) to conduct defect prediction. However, the initial weights and biases of the ELM are determined randomly, which reduces the prediction performance of ELM. Motivated by the idea of search based software engineering, we propose a novel software defect prediction model named KAEA based on kernel principal component analysis (KPCA), adaptive genetic algorithm, extreme… More >

Jialin Ma^{1, *}, Jieyi Cheng¹, Lin Zhang¹, Lei Zhou¹, Bolun Chen^{1, 2}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 455-469, 2020, DOI:10.32604/cmc.2020.09780

Abstract Traditional topic models have been widely used for analyzing semantic topics from electronic documents. However, the obvious defects of topic words acquired by them are poor in readability and consistency. Only the domain experts are possible to guess their meaning. In fact, phrases are the main unit for people to express semantics. This paper presents a Distributed Representation-Phrase Latent Dirichlet Allocation (DRPhrase LDA) which is a phrase topic model. Specifically, we reasonably enhance the semantic information of phrases via distributed representation in this model. The experimental results show the topics quality acquired by our model is more readable and consistent… More >

Chao Guo^{1, *}, Juan Guo², Chanjuan Yu¹, Zhaobin Li¹, Cheng Gong³, Abdul Waheed⁴

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 439-454, 2020, DOI:10.32604/cmc.2020.09792

Abstract Satellite networks have high requirements for security and data processing speed. In order to improve the reliability of the network, software-defined network (SDN) technology is introduced and a central controller is set in the network. Due to the characteristics of global perspective, control data separation, and centralized control of SDN, the idea of SDN is introduced to the design of the satellite network model. As a result, satellite nodes are only responsible for data transmission, while the maintenance of the links and the calculation of routes are implemented by the controller. For the massive LEO satellite network based on SDN,… More >