Open Access

ARTICLE

Oakyoung Han¹, Jaehyoun Kim^{2, *}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 553-566, 2020, DOI:10.32604/cmc.2020.09362
Abstract The processing of sound signals is significantly improved recently. Technique for sound signal processing focusing on music beyond speech area is getting attention due to the development of deep learning techniques. This study is for analysis and process of music signals to generate tow-dimensional tabular data and a new music. For analysis and process part, we represented normalized waveforms for each of input data via frequency domain signals. Then we looked into shorted segment to see the difference wave pattern for different singers. Fourier transform is applied to get spectrogram of the music signals. Filterbank is applied to represent the… More >

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Hossein Bisheh^{1, 2}, Yunhua Luo^{1, 3}, Timon Rabczuk^{4, *}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 567-591, 2020, DOI:10.32604/cmc.2020.09393
Abstract Precise evaluation of hip fracture risk leads to reduce hip fracture occurrence in individuals and assist to check the effect of a treatment. A subject-specific QCT-based finite element model is introduced to evaluate hip fracture risk using the strain energy, von-Mises stress, and von-Mises strain criteria during the single-leg stance and the sideways fall configurations. Choosing a proper failure criterion in hip fracture risk assessment is very important. The aim of this study is to define hip fracture risk index using the strain energy, von Mises stress, and von Mises strain criteria and compare the calculated fracture risk indices using… More >

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1235

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Ibrahim Mufrah Almanjahie^{1, 2}, Zouaoui Chikr Elmezouar^{1, 2, 3, *}, Ali Laksaci^{1, 2}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 593-604, 2020, DOI:10.32604/cmc.2020.08901
Abstract This paper examines the causal relationship between oil prices and the Gross Domestic Product (GDP) in the Kingdom of Saudi Arabia. The study is carried out by a data set collected quarterly, by Saudi Arabian Monetary Authority, over a period from 1974 to 2016. We seek how a change in real crude oil price affects the GDP of KSA. Based on a new technique, we treat this data in its continuous path. Precisely, we analyze the causality between these two variables, i.e., oil prices and GDP, by using their yearly curves observed in the four quarters of each year. We… More >

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1709

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1172

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ARTICLE

Junhua Xi^{1, *}, Kouquan Zheng¹, Jianfeng Ma¹, Jungang Yang¹, Zhiyao Liang²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 605-619, 2020, DOI:10.32604/cmc.2020.06343
Abstract Intuitionistic fuzzy Petri net is an important class of Petri nets, which can be used to model the knowledge base system based on intuitionistic fuzzy production rules. In order to solve the problem of poor self-learning ability of intuitionistic fuzzy systems, a new Petri net modeling method is proposed by introducing BP (Error Back Propagation) algorithm in neural networks. By judging whether the transition is ignited by continuous function, the intuitionistic fuzziness of classical BP algorithm is extended to the parameter learning and training, which makes Petri network have stronger generalization ability and adaptive function, and the reasoning result is… More >

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1085

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ARTICLE

Tao Li¹, Xiang Li^{1, *}, Yongjun Ren², Jinyue Xia³
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 621-631, 2020, DOI:10.32604/cmc.2020.06463
Abstract In view of the low accuracy of traditional ground nephogram recognition model, the authors put forward a k-means algorithm-acquired neural network ensemble method, which takes BP neural network ensemble model as the basis, uses k-means algorithm to choose the individual neural networks with partial diversities for integration, and builds the cloud form classification model. Through simulation experiments on ground nephogram samples, the results show that the algorithm proposed in the article can effectively improve the Classification accuracy of ground nephogram recognition in comparison with applying single BP neural network and traditional BP AdaBoost ensemble algorithm on classification of ground nephogram. More >

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1138

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ARTICLE

Chunpeng Ge^{1, *}, Jinyue Xia², Liming Fang¹
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 633-647, 2020, DOI:10.32604/cmc.2020.06217
Abstract An identity-based proxy re-encryption scheme (IB-PRE) allows a semi-trusted proxy to convert an encryption under one identity to another without revealing the underlying message. Due to the fact that the proxy was semi-trusted, it should place as little trust as necessary to allow it to perform the translations. In some applications such as distributed file system, it demands the adversary cannot identify the sender and recipient’s identities. However, none of the exiting IB-PRE schemes satisfy this requirement. In this work, we first define the security model of key-private IB-PRE. Finally, we propose the first key-private IB-PRE scheme. Our scheme is… More >

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1037

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ARTICLE

Likun Liu¹, Jiantao Shi^{1, *}, Xiangzhan Yu¹, Hongli Zhang¹, Dongyang Zhan²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 649-661, 2020, DOI:10.32604/cmc.2020.07736
Abstract Deep Packet Inspection (DPI) at the core of many monitoring appliances, such as NIDS, NIPS, plays a major role. DPI is beneficial to content providers and censorship to monitor network traffic. However, the surge of network traffic has put tremendous pressure on the performance of DPI. In fact, the sensitive content being monitored is only a minority of network traffic, that is to say, most is undesired. A close look at the network traffic, we found that it contains many undesired high frequency content (UHC) that are not monitored. As everyone knows, the key to improve DPI performance is to… More >

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1105

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ARTICLE

Zengpeng Li¹, Jiuru Wang^{2, *}, Chang Choi³, Wenyin Zhang²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 663-674, 2020, DOI:10.32604/cmc.2020.06565
Abstract Multi-factor authentication (MFA) was proposed by Pointcheval et al. [Pointcheval and Zimmer (2008)] to improve the security of single-factor (and two-factor) authentication. As the backbone of multi-factor authentication, biometric data are widely observed. Especially, how to keep the privacy of biometric at the password database without impairing efficiency is still an open question. Using the vulnerability of encryption (or hash) algorithms, the attacker can still launch offline brute-force attacks on encrypted (or hashed) biometric data. To address the potential risk of biometric disclosure at the password database, in this paper, we propose a novel efficient and secure MFA key exchange… More >

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1145

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ARTICLE

Junshan Tan¹, Rong Duan¹, Jiaohua Qin^{1, *}, Xuyu Xiang¹, Yun Tan¹
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 675-689, 2020, DOI:10.32604/cmc.2020.07730
Abstract Hashing technology has the advantages of reducing data storage and improving the efficiency of the learning system, making it more and more widely used in image retrieval. Multi-view data describes image information more comprehensively than traditional methods using a single-view. How to use hashing to combine multi-view data for image retrieval is still a challenge. In this paper, a multi-view fusion hashing method based on RKCCA (Random Kernel Canonical Correlation Analysis) is proposed. In order to describe image content more accurately, we use deep learning dense convolutional network feature DenseNet to construct multi-view by combining GIST feature or BoW_SIFT (Bag-of-Words… More >

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1190

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ARTICLE

Xiangmao Chang^{1, 2, *}, Yuan Qiu¹, Shangting Su¹, Deliang Yang³
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 691-703, 2020, DOI:10.32604/cmc.2020.07923
Abstract Wireless sensor networks are increasingly used in sensitive event monitoring. However, various abnormal data generated by sensors greatly decrease the accuracy of the event detection. Although many methods have been proposed to deal with the abnormal data, they generally detect and/or repair all abnormal data without further differentiate. Actually, besides the abnormal data caused by events, it is well known that sensor nodes prone to generate abnormal data due to factors such as sensor hardware drawbacks and random effects of external sources. Dealing with all abnormal data without differentiate will result in false detection or missed detection of the events.… More >

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1162

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ARTICLE

Qiang Wei^{1, 2, *}, Guangmin Hu¹, Chao Shen³, Yunfei Yin^{4, 5}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 705-724, 2020, DOI:10.32604/cmc.2020.07467
Abstract Fast identifying the amount of information that can be gained by measuring a network via shortest-paths is one of the fundamental problem for networks exploration and monitoring. However, the existing methods are time-consuming for even moderate-scale networks. In this paper, we present a method for fast shortest-path cover identification in both exact and approximate scenarios based on the relationship between the identification and the shortest distance queries. The effectiveness of the proposed method is validated through synthetic and real-world networks. The experimental results show that our method is 10⁵ times faster than the existing methods and can solve the shortest-path… More >

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1204

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ARTICLE

Cui Li^{1, *}, Gang Wu¹, Lipeng Xing¹, Feng Zhu¹, Liang Zhao²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 725-742, 2020, DOI:10.32604/cmc.2020.07188
Abstract The Vehicular Ad-hoc Network (VANET) is the fundamental of smart transportation system in the future, but the security of the communication between vehicles and vehicles, between vehicles and roadside infrastructures have become increasingly prominent. Certificateless aggregate signature protocol is used to address this security issue, but the existing schemes still have many drawbacks in terms of security and efficiency: First, many schemes are not secure, and signatures can be forged by the attacker; Second, even if some scheme are secure, many schemes use a large number of bilinear pairing operation, and the computation overhead is large. At the same time,… More >

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1514

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1138

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ARTICLE

Guang Sun^{1, 2, *}, Xiaoping Fan¹, Wangdong Jiang¹, Hangjun Zhou¹, Fenghua Li¹, Rong Yang¹
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 743-753, 2020, DOI:10.32604/cmc.2020.05564
Abstract Graph analysis can be done at scale by using Spark GraphX which loading data into memory and running graph analysis in parallel. In this way, we should take data out of graph databases and put it into memory. Considering the limitation of memory size, the premise of accelerating graph analytical process reduces the graph data to a suitable size without too much loss of similarity to the original graph. This paper presents our method of data cleaning on the software graph. We use SEQUITUR data compression algorithm to find out hot code path and store it as a whole paths… More >

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1035

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ARTICLE

Wenzheng Li¹, Yijun Gu^{1, *}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 755-768, 2020, DOI:10.32604/cmc.2020.07984
Abstract As an unsupervised learning method, stochastic competitive learning is commonly used for community detection in social network analysis. Compared with the traditional community detection algorithms, it has the advantage of realizing the timeseries community detection by simulating the community formation process. In order to improve the accuracy and solve the problem that several parameters in stochastic competitive learning need to be pre-set, the author improves the algorithms and realizes improved stochastic competitive learning by particle position initialization, parameter optimization and particle domination ability self-adaptive. The experiment result shows that each improved method improves the accuracy of the algorithm, and the… More >

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1095

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ARTICLE

Guangyong Yang¹, Jianqiu Zeng¹, Mengke Yang^{2, *}, Yifei Wei³, Xiangqing Wang³, Zulfiqar Hussain Pathan⁴
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 769-785, 2020, DOI:10.32604/cmc.2020.07528
Abstract A vast amount of information has been produced in recent years, which brings a huge challenge to information management. The better usage of big data is of important theoretical and practical significance for effectively addressing and managing messages. In this paper, we propose a nine-rectangle-grid information model according to the information value and privacy, and then present information use policies based on the rough set theory. Recurrent neural networks were employed to classify OTT messages. The content of user interest is effectively incorporated into the classification process during the annotation of OTT messages, ending with a reliable trained classification model.… More >

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1191

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ARTICLE

Wuxiong Zhang^{1, 2}, Weidong Fang^{1, 2, *}, Qianqian Zhao^{1, 2}, Xiaohong Ji³, Guoqing Jia³
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 787-811, 2020, DOI:10.32604/cmc.2020.07620
Abstract Energy efficiency is very important for the Internet of Things (IoT), especially for front-end sensed terminal or node. It not only embodies the node’s life, but also reflects the lifetime of the network. Meanwhile, it is also a key indicator of green communications. Unfortunately, there is no article on systematic analysis and review for energy efficiency evaluation in IoT. In this paper, we systemically analyze the architecture of IoT, and point out its energy distribution, Furthermore, we summarized the energy consumption model in IoT, analyzed the pros and cons of improving energy efficiency, presented a state of the art the… More >

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1750

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1284

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ARTICLE

Yue Jia¹, Chun Li^{1, *}, Jinwu Jiang², Ning Wei³, Yang Chen⁴, Yongjie Jessica Zhang⁵
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 813-823, 2020, DOI:10.32604/cmc.2020.07801
Abstract The present work carries out molecular dynamics simulations to compute the thermal conductivity of the borophene nanoribbon and the borophene nanotube using the Muller-Plathe approach. We investigate the thermal conductivity of the armchair and zigzag borophenes, and show the strong anisotropic thermal conductivity property of borophene. We compare results of the borophene nanoribbon and the borophene nanotube, and find the thermal conductivity of the borophene is orientation dependent. The thermal conductivity of the borophene does not vary as changing the width of the borophene nanoribbon and the perimeter of the borophene nanotube. In addition, the thermal conductivity of the borophene… More >

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1404

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ARTICLE

Abierdi¹, Yuzhou Xiang², Haiyi Zhong², Xin Gu², Hanlong Liu^{2, 3}, Wengang Zhang^{2, 3, *}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 825-844, 2020, DOI:10.32604/cmc.2020.07946
Abstract Tunnel excavation is a complicated loading-unloading-reloading process characterized by decreased radial stresses and increased axial stresses. An approach that considers only loading, is generally used in tunnel model testing. However, this approach is incapable of characterizing the unloading effects induced by excavation on surrounding rocks and hence presents radial and tangential stress paths during the failure process that are different from the actual stress state of tunnels. This paper carried out a comparative analysis using laboratory model testing and particle flow code (PFC^2D)-based numerical simulation, and shed light upon the crack propagation process and, microscopic stress and force chain variations… More >

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1611

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1052

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ARTICLE

Xiao Zhang^{1, 2, 3}, Faguo Wu^{1, 2, 3}, Wang Yao^{1, 2, 3, *}, Wenhua Wang⁴, Zhiming Zheng^{1, 2, 3}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 845-859, 2020, DOI:10.32604/cmc.2020.08008
Abstract Blockchain is an emerging decentralized architecture and distributed computing paradigm underlying Bitcoin and other cryptocurrencies, and has recently attracted intensive attention from governments, financial institutions, high-tech enterprises, and the capital markets. Its cryptographic security relies on asymmetric cryptography, such as ECC, RSA. However, with the surprising development of quantum technology, asymmetric cryptography schemes mentioned above would become vulnerable. Recently, lattice-based cryptography scheme was proposed to be secure against attacks in the quantum era. In 2018, with the aid of Bonsai Trees technology, Yin et al. [Yin, Wen, Li et al. (2018)] proposed a lattice-based authentication method which can extend a… More >

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1338

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ARTICLE

Zhengtao Liu^{1, *}, Yi Ying¹, Yaqin Peng¹, Jinyue Xia²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 861-871, 2020, DOI:10.32604/cmc.2020.07142
Abstract Multi-tenant collaboration brings the challenge to access control in cloud computing environment. Based on the multi-tenant role-based access control (MTRBAC) model, a Temporal MT-RBAC (TMT-RBAC) model for collaborative cloud services is proposed. It adds the time constraint between trusted tenants, including usable role time constraint based on both calendar and interval time. Analysis shows that the new model strengthens the presentation ability of MT-RBAC model, achieves the finergrained access control, reduces the management costs and enhances the security of multitenant collaboration in cloud computing environment. More >

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1097

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ARTICLE

Tao Wu¹, Lei Xie¹, Xi Chen², Amir Homayoon Ashrafzadeh³, Shu Zhang^{4, *}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 873-890, 2020, DOI:10.32604/cmc.2020.07478
Abstract The efficient management of ambulance routing for emergency requests is vital to save lives when a disaster occurs. Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is a kind of metaheuristic algorithms applied to deal with the problem of scheduling. This paper analyzed the motion pattern of particles in a square potential well, given the position equation of the particles by solving the Schrödinger equation and proposed the Binary Correlation QPSO Algorithm Based on Square Potential Well (BCQSPSO). In this novel algorithm, the intrinsic cognitive link between particles’ experience information and group sharing information was created by using normal Copula function. After… More >

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1800

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1220

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ARTICLE

Kun Zhu¹, Nana Zhang¹, Shi Ying^{1, *}, Xu Wang²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 891-910, 2020, DOI:10.32604/cmc.2020.08096
Abstract With the continuous expansion of software scale, software update and maintenance have become more and more important. However, frequent software code updates will make the software more likely to introduce new defects. So how to predict the defects quickly and accurately on the software change has become an important problem for software developers. Current defect prediction methods often cannot reflect the feature information of the defect comprehensively, and the detection effect is not ideal enough. Therefore, we propose a novel defect prediction model named ITNB (Improved Transfer Naive Bayes) based on improved transfer Naive Bayesian algorithm in this paper, which… More >

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2994

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1420

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ARTICLE

Yi Chen¹, Hongxia Wang^{2, *}, Xuyun Zhang³
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 911-922, 2020, DOI:10.32604/cmc.2020.08027
Abstract This paper presents a reversible data hiding (RDH) method, which is designed by combining histogram modification (HM) with run-level coding in H.264/advanced video coding (AVC). In this scheme, the run-level is changed for embedding data into H.264/AVC video sequences. In order to guarantee the reversibility of the proposed scheme, the last nonzero quantized discrete cosine transform (DCT) coefficients in embeddable 4×4 blocks are shifted by the technology of histogram modification. The proposed scheme is realized after quantization and before entropy coding of H.264/AVC compression standard. Therefore, the embedded information can be correctly extracted at the decoding side. Peak-signal-noise-to-ratio (PSNR) and… More >

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1050

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ARTICLE

Xiaolei Ma^{1, 2}, Yang Lu^{1, 2}, Yinan Lu^{1, *}, Zhili Pei², Jichao Liu³
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 923-941, 2020, DOI:10.32604/cmc.2020.07711
Abstract Supervised machine learning approaches are effective in text mining, but their success relies heavily on manually annotated corpora. However, there are limited numbers of annotated biomedical event corpora, and the available datasets contain insufficient examples for training classifiers; the common cure is to seek large amounts of training samples from unlabeled data, but such data sets often contain many mislabeled samples, which will degrade the performance of classifiers. Therefore, this study proposes a novel error data detection approach suitable for reducing noise in unlabeled biomedical event data. First, we construct the mislabeled dataset through error data analysis with the development… More >

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1248

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ARTICLE

Shiru Zhang¹, Zhiyao Liang^{1, *}, Jian Lin²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 943-957, 2020, DOI:10.32604/cmc.2020.08800
Abstract Calculating the semantic similarity of two sentences is an extremely challenging problem. We propose a solution based on convolutional neural networks (CNN) using semantic and syntactic features of sentences. The similarity score between two sentences is computed as follows. First, given a sentence, two matrices are constructed accordingly, which are called the syntax model input matrix and the semantic model input matrix; one records some syntax features, and the other records some semantic features. By experimenting with different arrangements of representing the syntactic and semantic features of the sentences in the matrices, we adopt the most effective way of constructing… More >

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1338

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ARTICLE

Guang Sun¹, Hongzhang Lv^{1, *}, Dianyu Wang², Xiaoping Fan^{1, 3}, Yi Zuo¹, Yanfei Xiao⁴, Xu Liu¹, Wenqian Xiang¹, Ziyi Guo¹
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 959-977, 2020, DOI:10.32604/cmc.2020.08619
Abstract When conducting company performance evaluations, the traditional method cannot reflect the distribution characteristics of the company’s operating conditions in the entire securities market. Gephi is an efficient tool for data analysis and visualization in the era of big data. It can convert the evaluation results of all listed companies into nodes and edges, and directly display them in the form of graphs, thus making up for the defects of traditional methods. This paper will take all the listed companies in the Shanghai and Shenzhen Stock Exchange as the analysis object. First uses tushare and web crawlers to collect the financial… More >

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1473

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ARTICLE

Dongjie Zhu¹, Haiwen Du⁶, Yundong Sun¹, Xiaofang Li², Rongning Qu², Hao Hu¹, Shuangshuang Dong¹, Helen Min Zhou³, Ning Cao^{4, 5, *},
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 979-993, 2020, DOI:10.32604/cmc.2020.06478
Abstract In distributed storage systems, file access efficiency has an important impact on the real-time nature of information forensics. As a popular approach to improve file accessing efficiency, prefetching model can fetches data before it is needed according to the file access pattern, which can reduce the I/O waiting time and increase the system concurrency. However, prefetching model needs to mine the degree of association between files to ensure the accuracy of prefetching. In the massive small file situation, the sheer volume of files poses a challenge to the efficiency and accuracy of relevance mining. In this paper, we propose a… More >

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1543

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ARTICLE

Chao Luo¹, Canghong Shi¹, Xiaojie Li^{1, *}, Xin Wang⁴, Yucheng Chen³, Dongrui Gao¹, Youbing Yin⁴, Qi Song⁴, Xi Wu¹, Jiliu Zhou¹
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 995-1012, 2020, DOI:10.32604/cmc.2020.07968
Abstract Myocardial segmentation and classification play a major role in the diagnosis of cardiovascular disease. Dilated Cardiomyopathy (DCM) is a kind of common chronic and life-threatening cardiopathy. Early diagnostics significantly increases the chances of correct treatment and survival. However, accurate and rapid diagnosis of DCM is still challenge due to high variability of cardiac structure, low contrast cardiac magnetic resonance (CMR) images, and intrinsic noise in synthetic CMR images caused by motion artifact and cardiac dynamics. Moreover, visual assessment and empirical evaluation are widely used in routine clinical diagnosis, but they are subject to high inter-observer variability and are both subjective… More >

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1725

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ARTICLE

Zhongxu Yin^{1, *}, Yiran Song², Huiqin Chen³, Yan Cao⁴
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 1013-1029, 2020, DOI:10.32604/cmc.2020.09345
Abstract Security-sensitive functions are the basis for building a taint-style vulnerability model. Current approaches for extracting security-sensitive functions either don’t analyze data flow accurately, or not conducting pattern analyzing of conditions, resulting in higher false positive rate or false negative rate, which increased manual confirmation workload. In this paper, we propose a security sensitive function mining approach based on preconditon pattern analyzing. Firstly, we propose an enhanced system dependency graph analysis algorithm for precisely extracting the conditional statements which check the function parameters and conducting statistical analysis of the conditional statements for selecting candidate security sensitive functions of the target program.… More >

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1119

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ARTICLE

Changji Wang^{1, *}, Yuan Yuan²
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 1031-1041, 2020, DOI:10.32604/cmc.2020.06278
Abstract Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptographic solution to the problem for enforcing fine-grained access control over encrypted data in the cloud. However, when applying CP-ABE to data outsourcing scenarios, we have to address the challenging issue of policy updates because access control elements, such as users, attributes, and access rules may change frequently. In this paper, we propose a notion of access policy updatable ciphertext-policy attribute-based encryption (APU-CP-ABE) by combining the idea of ciphertext-policy attribute-based key encapsulation and symmetric proxy re-encryption. When an access policy update occurs, data owner is no longer required to download any data for… More >

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1517

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ARTICLE

Manimekalai Thirunavukkarasu¹, Romera Joan Sparjan^{1, *}, Laxmikandan Thangavelu¹
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 1043-1064, 2020, DOI:10.32604/cmc.2020.09819
Abstract Future wireless networks demand high spectral efficiency, energy efficiency and reliability. Cooperative non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) is considered as one of the novel techniques to meet this demand. In this work, an adaptive power allocation scheme called SWIPT based adaptive power allocation (SWIPT-APA-NOMA) is proposed for a power domain NOMA network. The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use… More >

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1614

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ARTICLE

Waqar Ali^{1, 2}, Salah Ud Din¹, Abdullah Aman Khan¹, Saifullah Tumrani¹, Xiaochen Wang¹, Jie Shao^{1, 3, *}
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 1065-1078, 2020, DOI:10.32604/cmc.2020.010017
Abstract Recommender systems are rapidly transforming the digital world into intelligent information hubs. The valuable context information associated with the users’ prior transactions has played a vital role in determining the user preferences for items or rating prediction. It has been a hot research topic in collaborative filtering-based recommender systems for the last two decades. This paper presents a novel Context Based Rating Prediction (CBRP) model with a unique similarity scoring estimation method. The proposed algorithm computes a context score for each candidate user to construct a similarity pool for the given subject user-item pair and intuitively choose the highly influential… More >

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1389

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RETRACTION

Zhong Liu, Xin’an Wang, Kuntao Lu, David Su
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 1079-1079, 2020, DOI:10.32604/cmc.2020.04882
Abstract This article has no abstract. More >

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