Open Access
ARTICLE
Oakyoung Han1, Jaehyoun Kim2, *
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 >
Open Access
ARTICLE
Hossein Bisheh1, 2, Yunhua Luo1, 3, Timon Rabczuk4, *
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 >
Open Access
ARTICLE
Ibrahim Mufrah Almanjahie1, 2, Zouaoui Chikr Elmezouar1, 2, 3, *, Ali Laksaci1, 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 >
Open Access
ARTICLE
Junhua Xi1, *, 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 >
Open Access
ARTICLE
Tao Li1, Xiang Li1, *, 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 >
Open Access
ARTICLE
Chunpeng Ge1, *, 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 >
Open Access
ARTICLE
Likun Liu1, Jiantao Shi1, *, 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 >
Open Access
ARTICLE
Zengpeng Li1, Jiuru Wang2, *, 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 >
Open Access
ARTICLE
Junshan Tan1, Rong Duan1, Jiaohua Qin1, *, 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 >
Open Access
ARTICLE
Xiangmao Chang1, 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 >
Open Access
ARTICLE
Qiang Wei1, 2, *, Guangmin Hu1, Chao Shen3, Yunfei Yin4, 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 >
Open Access
ARTICLE
Cui Li1, *, 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 >
Open Access
ARTICLE
Guang Sun1, 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 >
Open Access
ARTICLE
Wenzheng Li1, Yijun Gu1, *
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 >
Open Access
ARTICLE
Guangyong Yang1, Jianqiu Zeng1, Mengke Yang2, *, 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 >
Open Access
ARTICLE
Wuxiong Zhang1, 2, Weidong Fang1, 2, *, Qianqian Zhao1, 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 >
Open Access
ARTICLE
Yue Jia1, Chun Li1, *, 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 >
Open Access
ARTICLE
Abierdi1, Yuzhou Xiang2, Haiyi Zhong2, Xin Gu2, Hanlong Liu2, 3, Wengang Zhang2, 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 (PFC2D)-based numerical simulation, and shed
light upon the crack propagation process and, microscopic stress and force chain variations… More >
Open Access
ARTICLE
Xiao Zhang1, 2, 3, Faguo Wu1, 2, 3, Wang Yao1, 2, 3, *, Wenhua Wang4, Zhiming Zheng1, 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 >
Open Access
ARTICLE
Zhengtao Liu1, *, 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 >
Open Access
ARTICLE
Tao Wu1, Lei Xie1, Xi Chen2, Amir Homayoon Ashrafzadeh3, Shu Zhang4, *
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 >
Open Access
ARTICLE
Kun Zhu1, Nana Zhang1, Shi Ying1, *, 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 >
Open Access
ARTICLE
Yi Chen1, Hongxia Wang2, *, 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 >
Open Access
ARTICLE
Xiaolei Ma1, 2, Yang Lu1, 2, Yinan Lu1, *, 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 >
Open Access
ARTICLE
Shiru Zhang1, Zhiyao Liang1, *, 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 >
Open Access
ARTICLE
Guang Sun1, Hongzhang Lv1, *, Dianyu Wang2, Xiaoping Fan1, 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 >
Open Access
ARTICLE
Dongjie Zhu1, Haiwen Du6, Yundong Sun1, Xiaofang Li2, Rongning Qu2, Hao Hu1, Shuangshuang Dong1, Helen Min Zhou3, Ning Cao4, 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 >
Open Access
ARTICLE
Chao Luo1, Canghong Shi1, Xiaojie Li1, *, 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 >
Open Access
ARTICLE
Zhongxu Yin1, *, 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 >
Open Access
ARTICLE
Changji Wang1, *, 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 >
Open Access
ARTICLE
Manimekalai Thirunavukkarasu1, Romera Joan Sparjan1, *, 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 >
Open Access
ARTICLE
Waqar Ali1, 2, Salah Ud Din1, Abdullah Aman Khan1, Saifullah Tumrani1, Xiaochen Wang1, Jie Shao1, 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 >
Open Access
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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