Open Access
ARTICLE
Rashid Amin1, *, Mudassar Hussain2, Mohammed Alhameed3, Syed Mohsan Raza4, Fathe Jeribi3, Ali Tahir3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1869-1890, 2020, DOI:10.32604/cmc.2020.011758
Abstract Software Defined Networking (SDN) being an emerging network control model
is widely recognized as a control and management platform. This model provides efficient
techniques to control and manage the enterprise network. Another emerging paradigm is
edge computing in which data processing is performed at the edges of the network instead
of a central controller. This data processing at the edge nodes reduces the latency and
bandwidth requirements. In SDN, the controller is a single point of failure. Several security
issues related to the traditional network can be solved by using SDN central management
and control. Address Spoofing and Network Intrusion… More >
Open Access
ARTICLE
Dong-Wook Kim1, Gun-Yoon Shin1, Myung-Mook Han2, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1891-1904, 2020, DOI:10.32604/cmc.2020.010933
Abstract This study was conducted to enable prompt classification of malware, which
was becoming increasingly sophisticated. To do this, we analyzed the important features
of malware and the relative importance of selected features according to a learning model
to assess how those important features were identified. Initially, the analysis features
were extracted using Cuckoo Sandbox, an open-source malware analysis tool, then the
features were divided into five categories using the extracted information. The 804
extracted features were reduced by 70% after selecting only the most suitable ones for
malware classification using a learning model-based feature selection method called the
recursive feature… More >
Open Access
ARTICLE
Berat Karaagac1, 2, Kolade Matthew Owolabi1, 3, *, Kottakkaran Sooppy Nisar4
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1905-1924, 2020, DOI:10.32604/cmc.2020.011623
（This article belongs to this Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
Abstract Illicit drug use is a significant problem that causes great material and moral
losses and threatens the future of the society. For this reason, illicit drug use and related
crimes are the most significant criminal cases examined by scientists. This paper aims at
modeling the illegal drug use using the Atangana-Baleanu fractional derivative with
Mittag-Leffler kernel. Also, in this work, the existence and uniqueness of solutions of the
fractional-order Illicit drug use model are discussed via Picard-Lindelöf theorem which
provides successive approximations using a convergent sequence. Then the stability
analysis for both disease-free and endemic equilibrium states is conducted. A… More >
Open Access
ARTICLE
Nithya Rekha Sivakumar1, *, Sara Ghorashi1, Mona Jamjoom1, Mai Alduailij1
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1925-1943, 2020, DOI:10.32604/cmc.2020.011505
Abstract In today’s world, smart phones offer various applications namely face detection,
augmented-reality, image and video processing, video gaming and speech recognition.
With the increasing demand for computing resources, these applications become more
complicated. Cloud Computing (CC) environment provides access to unlimited resource
pool with several features, including on demand self-service, elasticity, wide network
access, resource pooling, low cost, and ease of use. Mobile Cloud Computing (MCC)
aimed at overcoming drawbacks of smart phone devices. The task remains in combining
CC technology to the mobile devices with improved battery life and therefore resulting in
significant performance. For remote execution, recent studies… More >
Open Access
ARTICLE
Isa Abdullahi Baba1, *, Dumitru Baleanu2, 3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1945-1957, 2020, DOI:10.32604/cmc.2020.011508
（This article belongs to this Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
Abstract A mathematical model consisting of a system of four nonlinear ordinary
differential equations is constructed. Our aim is to study the dynamics of the spread of
COVID-19 in Nigeria and to show the effectiveness of awareness and the need for relevant
authorities to engage themselves more in enlightening people on the significance of the
available control measures in mitigating the spread of the disease. Two equilibrium
solutions; Disease free equilibrium and Endemic equilibrium solutions were calculated and
their global stability analysis was carried out. Basic reproduction ratio ( More >
Open Access
ARTICLE
Muhammad Saqib1, Hanifa Hanif1, 2, T. Abdeljawad3, 4, 5, Ilyas Khan6, *, Sharidan Shafie1, Kottakkaran Sooppy Nisar7
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1959-1973, 2020, DOI:10.32604/cmc.2020.011339
Abstract The idea of fractional derivatives is applied to several problems of viscoelastic
fluid. However, most of these problems (fluid problems), were studied analytically using
different integral transform techniques, as most of these problems are linear. The idea of
the above fractional derivatives is rarely applied to fluid problems governed by nonlinear
partial differential equations. Most importantly, in the nonlinear problems, either the
fractional models are developed by artificial replacement of the classical derivatives with
fractional derivatives or simple classical problems (without developing the fractional
model even using artificial replacement) are solved. These problems were mostly solved
for steady-state fluid problems.… More >
Open Access
ARTICLE
Baili Zhang1, 2, 3, *, Shan Zhou1, Le Yang1, Jianhua Lv1, 2, Mingjun Zhong4
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1975-1986, 2020, DOI:10.32604/cmc.2020.010914
Abstract The Internet of Medical Things (IoMT) will come to be of great importance in
the mediation of medical disputes, as it is emerging as the core of intelligent medical
treatment. First, IoMT can track the entire medical treatment process in order to provide
detailed trace data in medical dispute resolution. Second, IoMT can infiltrate the ongoing
treatment and provide timely intelligent decision support to medical staff. This
information includes recommendation of similar historical cases, guidance for medical
treatment, alerting of hired dispute profiteers etc. The multi-label classification of
medical dispute documents (MDDs) plays an important role as a front-end process… More >
Open Access
ARTICLE
Ehab Mahmoud Mohamed1, 2, *, Sherief Hashima3, 4, Kohei Hatano3, 5, Hani Kasban4, Mohamed Rihan6
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1987-2007, 2020, DOI:10.32604/cmc.2020.011816
Abstract The communication in the Millimeter-wave (mmWave) band, i.e., 30~300
GHz, is characterized by short-range transmissions and the use of antenna beamforming
(BF). Thus, multiple mmWave access points (APs) should be installed to fully cover a
target environment with gigabits per second (Gbps) connectivity. However, inter-beam
interference prevents maximizing the sum rates of the established concurrent links. In this
paper, a reinforcement learning (RL) approach is proposed for enabling mmWave
concurrent transmissions by finding out beam directions that maximize the long-term
average sum rates of the concurrent links. Specifically, the problem is formulated as a
multiplayer multiarmed bandit (MAB), where mmWave… More >
Open Access
ARTICLE
Hamidreza Noori1, Bohayra Mortazavi2, 3, Alessandro Di Pierro4, Emad Jomehzadeh5, Xiaoying Zhuang2, 3, Zi Goangseup6, Kim Sang-Hyun7, Timon Rabczuk8, 9, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2009-2032, 2020, DOI:10.32604/cmc.2020.011256
Abstract In modern physics and fabrication technology, simulation of projectile and
target collision is vital to improve design in some critical applications, like;
bulletproofing and medical applications. Graphene, the most prominent member of two
dimensional materials presents ultrahigh tensile strength and stiffness. Moreover,
polydimethylsiloxane (PDMS) is one of the most important elastomeric materials with a
high extensive application area, ranging from medical, fabric, and interface material. In
this work we considered graphene/PDMS structures to explore the bullet resistance of
resulting nanocomposites. To this aim, extensive molecular dynamic simulations were
carried out to identify the penetration of bullet through the graphene and… More >
Open Access
ARTICLE
Saqib Murtaza1, Farhad Ali1, Aamina2, 3, *, Nadeem Ahmad Sheikh1, Ilyas Khan4, Kottakkaran Sooppy Nisar5
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2033-2047, 2020, DOI:10.32604/cmc.2020.011817
Abstract It is a very difficult task for the researchers to find the exact solutions to
mathematical problems that contain non-linear terms in the equation. Therefore, this article
aims to investigate the viscous dissipation (VD) effect on the fractional model of Jeffrey
fluid over a heated vertical flat plate that suddenly moves in its own plane. Based on the
Atangana-Baleanu operator, the fractional model is developed from the fractional
constitutive equations. VD is responsible for the non-linear behavior in the problem. Upon
taking the Laplace and Fourier sine transforms, exact expressions have been obtained for
momentum and energy equations. The influence… More >
Open Access
ARTICLE
Ahmed Bachir1, *, Ibrahim Mufrah Almanjahie1, 2, Mohammed Kadi Attouch3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2049-2064, 2020, DOI:10.32604/cmc.2020.011491
Abstract It is well known that the nonparametric estimation of the regression function is
highly sensitive to the presence of even a small proportion of outliers in the data. To solve
the problem of typical observations when the covariates of the nonparametric component
are functional, the robust estimates for the regression parameter and regression operator
are introduced. The main propose of the paper is to consider data-driven methods of
selecting the number of neighbors in order to make the proposed processes fully automatic.
We use the More >
Open Access
ARTICLE
Shuai Wang1, Xianyi Chen2, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2065-2077, 2020, DOI:10.32604/cmc.2020.09857
Abstract With the rapid development of computer technology, millions of images are
produced everyday by different sources. How to efficiently process these images and
accurately discern the scene in them becomes an important but tough task. In this paper,
we propose a novel supervised learning framework based on proposed adaptive binary
coding for scene classification. Specifically, we first extract some high-level features of
images under consideration based on available models trained on public datasets. Then,
we further design a binary encoding method called one-hot encoding to make the feature
representation more efficient. Benefiting from the proposed adaptive binary coding, our
method… More >
Open Access
ARTICLE
Pang Li1, *, Lifeng Zhu2, Brij B. Gupta3, 4, Sunil Kumar Jha5
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2079-2090, 2020, DOI:10.32604/cmc.2020.013696
Abstract In sensor networks, it is a challenge to ensure the security of data exchange
between packet switching nodes holding different private keys. In order to solve this
problem, the present study proposes a scheme called multi-conditional proxy broadcast reencryption (MC-PBRE). The scheme consists of the following roles: the source node,
proxy server, and the target node. If the condition is met, the proxy can convert the
encrypted data of the source node into data that the target node can directly decrypt. It
allows the proxy server to convert the ciphertext of the source node to a new ciphertext of
the… More >
Open Access
ARTICLE
Phyu Hnin Thike1, 2, Zhaoyang Zhao1, Peng Liu1, Feihu Bao1, Ying Jin1, Peng Shi1, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2091-2109, 2020, DOI:10.32604/cmc.2020.011608
Abstract The optimization of network topologies to retain the generalization ability by
deciding when to stop overtraining an artificial neural network (ANN) is an existing vital
challenge in ANN prediction works. The larger the dataset the ANN is trained with, the
better generalization the prediction can give. In this paper, a large dataset of atmospheric
corrosion data of carbon steel compiled from several resources is used to train and test a
multilayer backpropagation ANN model as well as two conventional corrosion prediction
models (linear and Klinesmith models). Unlike previous related works, a grid searchbased hyperparameter tuning is performed to develop multiple… More >
Open Access
ARTICLE
Yudong Wang1, 2, Jie Tan1, *, Zhenjie Liu1, Allah Ditta3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2111-2122, 2020, DOI:10.32604/cmc.2020.011098
Abstract Batteries are often packed together to meet voltage and capability needs.
However, due to variations in raw materials, different ages of equipment, and manual
operation, there is inconsistency between batteries, which leads to reduced available
capacity, variability of resistance, and premature failure. Therefore, it is crucial to pack
similar batteries together. The conventional approach to screening batteries is based on
their capacity, voltage and internal resistance, which disregards how batteries perform
during manufacturing. In the battery discharge process, real time discharge voltage
curves (DVCs) are collected as a set of unlabeled time series, which reflect how the
battery voltage changes.… More >
Open Access
ARTICLE
Dan Ma1, 2, Hongyu Duan2, Qi Zhang3, *, Jixiong Zhang1, Wenxuan Li2, Zilong Zhou2, Weitao Liu4
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2123-2141, 2020, DOI:10.32604/cmc.2020.011430
Abstract Gas fracturing, which overcomes the limitation of hydraulic fracturing, is a
potential alternative technology for the development of unconventional gas and oil
resources. However, the mechanical principle of gas fracturing has not been learned
comprehensively when the fluid is injected into the borehole. In this paper, a damagebased model of coupled thermal-flowing-mechanical effects was adopted to illustrate the
mechanical principle of gas fracturing. Numerical simulation tools Comsol Multiphysics
and Matlab were integrated to simulate the coupled process during the gas fracturing.
Besides, the damage evolution of drilling areas under several conditions was fully
analyzed. Simulation results indicate that the maximum… More >
Open Access
ARTICLE
Xiaoyu Li1, Qinsheng Zhu2, *, Yiming Huang1, Yong Hu2, Qingyu Meng2, Chenjing Su1, Qing Yang2, Shaoyi Wu2, Xusheng Liu3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2143-2151, 2020, DOI:10.32604/cmc.2020.010865
Abstract Quantum correlation shows a fascinating nature of quantum mechanics and
plays an important role in some physics topics, especially in the field of quantum
information. Quantum correlations of the composite system can be quantified by
resorting to geometric or entropy methods, and all these quantification methods exhibit
the peculiar freezing phenomenon. The challenge is to find the characteristics of the
quantum states that generate the freezing phenomenon, rather than only study the
conditions which generate this phenomenon under a certain quantum system. In essence,
this is a classification problem. Machine learning has become an effective method for
researchers to study… More >
Open Access
ARTICLE
Huifang Qian1, Xuan Zhou1, *, Mengmeng Zheng1
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2153-2167, 2020, DOI:10.32604/cmc.2020.011843
Abstract The core technology in an intelligent video surveillance system is that
detecting and recognizing abnormal behaviors timely and accurately. The key
breakthrough point in recognizing abnormal behaviors is how to obtain the effective
features of the picture, so as to solve the problem of recognizing them. In response to this
difficulty, this paper introduces an adjustable jump link coefficients model based on the
residual network. The effective coefficients for each layer of the network can be set after
using this model to further improving the recognition accuracy of abnormal behavior. A
convolution kernel of 1×1 size is added to reduce… More >
Open Access
ARTICLE
Rashad Bantan1, Amal S. Hassan2, Mahmoud Elsehetry3, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2169-2187, 2020, DOI:10.32604/cmc.2020.011497
Abstract In this article, we offer a new adapted model with three parameters, called
Zubair Lomax distribution. The new model can be very useful in analyzing and modeling
real data and provides better fits than some others new models. Primary properties of the
Zubair Lomax model are determined by moments, probability weighted moments, Renyi
entropy, quantile function and stochastic ordering, among others. Maximum likelihood
method is used to estimate the population parameters, owing to simple random sample
and ranked set sampling schemes. The behavior of the maximum likelihood estimates for
the model parameters is studied using Monte Carlo simulation. Criteria measures… More >
Open Access
ARTICLE
Fengchang Xue1, *, Juan Tian1, Wei Wang2, Yanran Zhang1, Gohar Ali3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2189-2199, 2020, DOI:10.32604/cmc.2020.06513
Abstract For the challenge of parameter calibration in the process of SWMM (storm
water management model) model application, we use particle Swarm Optimization (PSO)
and Sequence Quadratic Programming (SQP) in combination to calibrate the parameters
and get the optimal parameter combination in this research. Then, we compare and
analyze the simulation result with the other two respectively using initial parameters and
parameters obtained by PSO algorithm calibration alone. The result shows that the
calibration result of PSO-SQP combined algorithm has the highest accuracy and shows
highly consistent with the actual situation, which provides a scientific and effective new
idea for parameter… More >
Open Access
ARTICLE
Qiqiang Chen1, *, Xinxin Gan2, Wei Huang1, Jingjing Feng1, H. Shim3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2201-2215, 2020, DOI:10.32604/cmc.2020.011191
Abstract Automatic road damage detection using image processing is an important aspect
of road maintenance. It is also a challenging problem due to the inhomogeneity of road
damage and complicated background in the road images. In recent years, deep
convolutional neural network based methods have been used to address the challenges of
road damage detection and classification. In this paper, we propose a new approach to
address those challenges. This approach uses densely connected convolution networks as
the backbone of the Mask R-CNN to effectively extract image feature, a feature pyramid
network for combining multiple scales features, a region proposal network… More >
Open Access
ARTICLE
Anjie Peng1, Kang Deng1, Shenghai Luo1, Hui Zeng1, 2, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2217-2231, 2020, DOI:10.32604/cmc.2020.011006
Abstract The multi-purpose forensics is an important tool for forge image detection. In
this paper, we propose a universal feature set for the multi-purpose forensics which is
capable of simultaneously identifying several typical image manipulations, including
spatial low-pass Gaussian blurring, median filtering, re-sampling, and JPEG
compression. To eliminate the influences caused by diverse image contents on the
effectiveness and robustness of the feature, a residual group which contains several highpass filtered residuals is introduced. The partial correlation coefficient is exploited from
the residual group to purely measure neighborhood correlations in a linear way. Besides
that, we also combine autoregressive coefficient and… More >
Open Access
ARTICLE
Shaozhang Niu1, *, Xiangxiang Li1, Maosen Wang1, Yueying Li2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2233-2245, 2020, DOI:10.32604/cmc.2020.09471
Abstract In recent years, images have played a more and more important role in our
daily life and social communication. To some extent, the textual information contained in
the pictures is an important factor in understanding the content of the scenes themselves. The more accurate the text detection of the natural scenes is, the more accurate our
semantic understanding of the images will be. Thus, scene text detection has also become
the hot spot in the domain of computer vision. In this paper, we have presented a
modified text detection network which is based on further research and improvement of
Connectionist… More >
Open Access
ARTICLE
Jieren Cheng1, Jun Li2, *, Naixue Xiong3, Meizhu Chen2, Hao Guo2, Xinzhi Yao2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2247-2262, 2020, DOI:10.32604/cmc.2020.011668
Abstract Nowadays, as lightweight mobile clients become more powerful and widely
used, more and more information is stored on lightweight mobile clients, user sensitive data
privacy protection has become an urgent concern and problem to be solved. There has been
a corresponding rise of security solutions proposed by researchers, however, the current
security mechanisms on lightweight mobile clients are proven to be fragile. Due to the fact
that this research field is immature and still unexplored in-depth, with this paper, we aim to
provide a structured and comprehensive study on privacy protection using trusted execution
environment (TEE) for lightweight mobile clients.… More >
Open Access
ARTICLE
Weijin Jiang1, 2, 3, 4, Fang Ye1, 2, *, Wei Liu2, 3, Xiaoliang Liu1, 2, Guo Liang5, Yuhui Xu2, 3, Lina Tan1, 2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2263-2275, 2020, DOI:10.32604/cmc.2020.010082
Abstract With the rapid development of information technology, the explosive growth
of data information has become a common challenge and opportunity. Social network
services represented by WeChat, Weibo and Twitter, drive a large amount of information
due to the continuous spread, evolution and emergence of users through these platforms.
The dynamic modeling, analysis, and network information prediction, has very important
research and application value, and plays a very important role in the discovery of
popular events, personalized information recommendation, and early warning of bad
information. For these reasons, this paper proposes an adaptive prediction algorithm for
network information transmission. A popularity… More >
Open Access
ARTICLE
Yong Wu1, Binjun Wang1, *, Wei Li2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2277-2294, 2020, DOI:10.32604/cmc.2020.011609
Abstract Graph convolutional networks (GCNs) have been developed as a general and
powerful tool to handle various tasks related to graph data. However, current methods
mainly consider homogeneous networks and ignore the rich semantics and multiple types
of objects that are common in heterogeneous information networks (HINs). In this paper,
we present a Heterogeneous Hyperedge Convolutional Network (HHCN), a novel graph
convolutional network architecture that operates on HINs. Specifically, we extract the
rich semantics by different metastructures and adopt hyperedge to model the interactions
among metastructure-based neighbors. Due to the powerful information extraction
capabilities of metastructure and hyperedge, HHCN has the… More >
Open Access
ARTICLE
Huaixi Xing1, Yu Zhao1, Yuhui Zhang1, You Chen1, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2295-2308, 2020, DOI:10.32604/cmc.2020.011858
Abstract Aiming at the yaw problem caused by inertial navigation system errors
accumulation during the navigation of an intelligent aircraft, a three-dimensional trajectory
planning method based on the particle swarm optimization-A star (PSO-A*) algorithm is
designed. Firstly, an environment model for aircraft error correction is established, and the
trajectory is discretized to calculate the positioning error. Next, the positioning error is
corrected at many preset trajectory points. The shortest trajectory and the fewest correction
times are regarded as optimization goals to improve the heuristic function of A star (A*)
algorithm. Finally, the index weights are continuously optimized by the particle swarm… More >
Open Access
ARTICLE
Cong Wang1, Mingming Zhao2, Qinyue Wang2, 3, Min Li2, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2309-2319, 2020, DOI:10.32604/cmc.2020.09958
Abstract This paper introduces a novel mechanism to improve the performance of peer
assessment for collaborative learning. Firstly, a small set of assignments which have being
pre-scored by the teacher impartially, are introduced as “sentinels”. The reliability of a
reviewer can be estimated by the deviation between the sentinels’ scores judged by the
reviewers and the impartial scores. Through filtering the inferior reviewers by the reliability,
each score can then be subjected into mean value correction and standard deviation correction
processes sequentially. Then the optimized mutual score which mitigated the influence of the
subjective differences of the reviewers are obtained. We… More >
Open Access
ARTICLE
Panyu Liu1, Huilin Ren2, Xiaojun Shi3, Yangyang Li4, *, Zhiping Cai1, Fang Liu5, Huacheng Zeng6
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2321-2334, 2020, DOI:10.32604/cmc.2020.010522
Abstract Deep learning technology has been widely used in computer vision, speech
recognition, natural language processing, and other related fields. The deep learning
algorithm has high precision and high reliability. However, the lack of resources in the edge
terminal equipment makes it difficult to run deep learning algorithms that require more
memory and computing power. In this paper, we propose MoTransFrame, a general model
processing framework for deep learning models. Instead of designing a model compression
algorithm with a high compression ratio, MoTransFrame can transplant popular convolutional
neural networks models to resources-starved edge devices promptly and accurately. By the
integration method,… More >
Open Access
ARTICLE
Rong Duan1, Junshan Tan1, *, Jiaohua Qin1, Xuyu Xiang1, Yun Tan1, Neal N. Xiong2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2335-2350, 2020, DOI:10.32604/cmc.2020.012161
Abstract In recent years, with the massive growth of image data, how to match the
image required by users quickly and efficiently becomes a challenge. Compared with
single-view feature, multi-view feature is more accurate to describe image information.
The advantages of hash method in reducing data storage and improving efficiency also
make us study how to effectively apply to large-scale image retrieval. In this paper, a
hash algorithm of multi-index image retrieval based on multi-view feature coding is
proposed. By learning the data correlation between different views, this algorithm uses
multi-view data with deeper level image semantics to achieve better retrieval… More >
Open Access
ARTICLE
Zhenli Wang1, *, Qun Wang1, Jiayin Liu1, Zheng Liang1, Jingsong Xu2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2351-2363, 2020, DOI:10.32604/cmc.2020.011909
Abstract To address the low-resolution imaging problem in relation to traditional Range
Doppler (RD) algorithm, this paper intends to propose a new algorithm based on
Fractional Fourier Transform (FrFT), which proves highly advantageous in the
acquisition of high-resolution Synthetic Aperture Radar (SAR) images. The expression of
the optimal order of SAR range signals using FrFT is deduced in detail, and the
corresponding expression of the azimuth signal is also given. Theoretical analysis shows
that, the optimal order in range (azimuth) direction, which turns out to be very unique,
depends on the known imaging parameters of SAR, therefore the engineering
practicability of… More >
Open Access
ARTICLE
Jin Wang1, 2, Wencheng Chen1, Lei Wang3, *, R. Simon Sherratt4, Osama Alfarraj5, Amr Tolba5, 6
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2365-2384, 2020, DOI:10.32604/cmc.2020.011567
Abstract As the number of sensor network application scenarios continues to grow, the
security problems inherent in this approach have become obstacles that hinder its wide
application. However, it has attracted increasing attention from industry and academia.
The blockchain is based on a distributed network and has the characteristics of nontampering and traceability of block data. It is thus naturally able to solve the security
problems of the sensor networks. Accordingly, this paper first analyzes the security risks
associated with data storage in the sensor networks, then proposes using blockchain
technology to ensure that data storage in the sensor networks is… More >
Open Access
ARTICLE
Jianzhong Qi1, 2, *, Qingping Song3, Jim Feng4
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2385-2396, 2020, DOI:10.32604/cmc.2020.011651
Abstract The area navigation system, discussed in this paper, is composed of ground
responders and a navigation terminal and can position a high-velocity aircraft and measure
its velocity. This navigation system is silent at ordinary times. It sends out a request signal
when positioning is required for an aircraft, and then the ground responders send a signal
for resolving the aircraft. Combining the direct sequence spread spectrum and frequency
hopping, the concealed communication mode is used in the whole communication process,
with short communication pulses as much as possible, so the system has strong
concealment and anti-interference characteristics. As the transmission… More >
Open Access
ARTICLE
Ying Tian1, *, Libing Wang1, Hexin Gu2, Lin Fan3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2397-2412, 2020, DOI:10.32604/cmc.2020.011386
Abstract The application of deep learning in the field of object detection has
experienced much progress. However, due to the domain shift problem, applying an
off-the-shelf detector to another domain leads to a significant performance drop. A
large number of ground truth labels are required when using another domain to train
models, demanding a large amount of human and financial resources. In order to avoid
excessive resource requirements and performance drop caused by domain shift, this
paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our
approach improves the cross-domain vehicle detection model from image space and
feature space.… More >
Open Access
ARTICLE
Yuqing Yang1, 3, Peng Fu2, *, Xiaojiang Yang1, 4, Hong Hong5, Dequn Zhou1
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2413-2423, 2020, DOI:10.32604/cmc.2020.011881
Abstract Massive Open Online Course (MOOC) has become a popular way of online
learning used across the world by millions of people. Meanwhile, a vast amount of
information has been collected from the MOOC learners and institutions. Based on the
educational data, a lot of researches have been investigated for the prediction of the
MOOC learner’s final grade. However, there are still two problems in this research field.
The first problem is how to select the most proper features to improve the prediction
accuracy, and the second problem is how to use or modify the data mining algorithms for
a better… More >
Open Access
ARTICLE
Hongjin Zhu1, Honghui Fan1, *, Zhenqiu Shu1, Congzhe You1, Xiangjun Chen1, Qian Yu1, Pengzhen Gan2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2425-2439, 2020, DOI:10.32604/cmc.2020.011841
Abstract Studies show that encoding technologies in H.264/AVC, including prediction
and conversion, are essential technologies. However, these technologies are more
complicated than the MPEG-4, which is a standard method and widely adopted worldwide.
Therefore, the amount of calculation in H.264/AVC is significantly up-regulated compared
to that of the MPEG-4. In the present study, it is intended to simplify the computational
expenses in the international standard compression coding system H.264/AVC for moving
images. Inter prediction refers to the most feasible compression technology, taking up to
60% of the entire encoding. In this regard, prediction error and motion vector information
are proposed to… More >
Open Access
ARTICLE
Hao Chen1, Wunan Wan1, *, Jinyue Xia2, *, Shibin Zhang1, Jinquan Zhang1, Xizi Peng1, Xingjie Fan1
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2441-2453, 2020, DOI:10.32604/cmc.2020.011824
Abstract As a new form of network, the Internet of things (IoT) is becoming more
widely used in people’s lives. In this paper, related theoretical research and practical
applications of the IoT are explored. The security of the IoT has become a hot research
topic. Access controls are methods that control reasonable allocations of data and
resources and ensure the security of the IoT. However, most access control systems do
not dynamically assign users’ rights. Additionally, with some access control systems,
there is a risk of overstepping other user’s authority, and there may exist a central
authority that is a single… More >
Open Access
ARTICLE
Runzhe Tao1, *, Yonghong Zhang1, Lihua Wang1, Pengyan Cai1, Haowen Tan2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2455-2474, 2020, DOI:10.32604/cmc.2020.011526
Abstract Aiming at the problem of radar base and ground observation stations on the
Tibet is sparsely distributed and cannot achieve large-scale precipitation monitoring. UNet, an advanced machine learning (ML) method, is used to develop a robust and rapid
algorithm for precipitating cloud detection based on the new-generation geostationary
satellite of FengYun-4A (FY-4A). First, in this algorithm, the real-time multi-band
infrared brightness temperature from FY-4A combined with the data of Digital Elevation
Model (DEM) has been used as predictor variables for our model. Second, the efficiency
of the feature was improved by changing the traditional convolution layer serial
connection method of… More >
Open Access
ARTICLE
Chongchao Cai1, 2, Huahu Xu1, *, Jie Wan2, Baiqing Zhou2, Xiongwei Xie3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2475-2488, 2020, DOI:10.32604/cmc.2020.011693
Abstract In social networks, user attention affects the user’s decision-making, resulting
in a performance alteration of the recommendation systems. Existing systems make
recommendations mainly according to users’ preferences with a particular focus on items.
However, the significance of users’ attention and the difference in the influence of
different users and items are often ignored. Thus, this paper proposes an attention-based
multi-layer friend recommendation model to mitigate information overload in social
networks. We first constructed the basic user and item matrix via convolutional neural
networks (CNN). Then, we obtained user preferences by using the relationships between
users and items, which were later… More >
Open Access
ARTICLE
Wei Sun1, 2, *, Xiaorui Zhang2, 3, Xiaozheng He4, Yan Jin1, Xu Zhang3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2489-2510, 2020, DOI:10.32604/cmc.2020.012343
Abstract Vehicle type recognition (VTR) is an important research topic due to its
significance in intelligent transportation systems. However, recognizing vehicle type on
the real-world images is challenging due to the illumination change, partial occlusion
under real traffic environment. These difficulties limit the performance of current stateof-art methods, which are typically based on single-stage classification without
considering feature availability. To address such difficulties, this paper proposes a twostage vehicle type recognition method combining the most effective Gabor features. The
first stage leverages edge features to classify vehicles by size into big or small via a
similarity k-nearest neighbor classifier (SKNNC). Further… More >
Open Access
ARTICLE
Weiwei Liu1, Yang Tang2, Fei Yang2, Chennan Zhang1, Dun Cao3, Gwang-jun Kim4, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2511-2527, 2020, DOI:10.32604/cmc.2020.09113
Abstract Intelligent Transportation System (ITS) is essential for effective identification
of vulnerable units in the transport network and its stable operation. Also, it is necessary
to establish an urban transport network vulnerability assessment model with solutions
based on Internet of Things (IoT). Previous research on vulnerability has no congestion
effect on the peak time of urban road network. The cascading failure of links or nodes is
presented by IoT monitoring system, which can collect data from a wireless sensor
network in the transport environment. The IoT monitoring system collects wireless data
via Vehicle-to-Infrastructure (V2I) channels to simulate key segments and their… More >
Open Access
ARTICLE
Yugang Li1, *, Haibo Sun1, Zhe Chen1, Yudan Ding1, Siqi Zhou2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2529-2541, 2020, DOI:10.32604/cmc.2020.011886
Abstract Referring expressions comprehension is the task of locating the image region
described by a natural language expression, which refer to the properties of the region or
the relationships with other regions. Most previous work handles this problem by
selecting the most relevant regions from a set of candidate regions, when there are many
candidate regions in the set these methods are inefficient. Inspired by recent success of
image captioning by using deep learning methods, in this paper we proposed a framework
to understand the referring expressions by multiple steps of reasoning. We present a
model for referring expressions comprehension by… More >
Open Access
ARTICLE
Weijin Jiang1, 2, 3, Wei Liu2, *, Haolong Xia1, Yuhui Xu2, Dongbo Cao1, Guo Liang4
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2543-2555, 2020, DOI:10.32604/cmc.2020.011454
Abstract In networked mobile commerce network transactions, trust is the prerequisite
and key to a smooth transaction. The measurement of trust between entities involves
factors such as transaction amount, transaction time, personal income of consumer
entities and their risk attitude towards trust, etc., so it is difficult to accurately calculate
quantitatively. In order to find out the essential characteristics of this trust relationship,
based on the research background of mobile commerce in the mobile network
environment, a dynamic trust mechanism is proposed through the research of trust in the
mobile network environment, trust influencing factors and trust mechanism. The
calculation model… More >
Open Access
ARTICLE
Yongqiang Bao1, *, Qi Shao1, Xuxu Zhang1, Jiahui Jiang1, Yue Xie1, Tingting Liu1, Weiye Xu2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2557-2570, 2020, DOI:10.32604/cmc.2020.011241
Abstract The field of digital audio forensics aims to detect threats and fraud in audio
signals. Contemporary audio forensic techniques use digital signal processing to detect
the authenticity of recorded speech, recognize speakers, and recognize recording devices.
User-generated audio recordings from mobile phones are very helpful in a number of
forensic applications. This article proposed a novel method for recognizing recording
devices based on recorded audio signals. First, a database of the features of various
recording devices was constructed using 32 recording devices (20 mobile phones of
different brands and 12 kinds of recording pens) in various environments. Second, the
audio… More >
Open Access
ARTICLE
Minjae Seo1, Jong-Ho Paik2, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2571-2589, 2020, DOI:10.32604/cmc.2020.011347
Abstract The trend in video viewing has been evolving beyond simply providing a multiview option. Recently, a function that allows selection and viewing of a clip from a multiview service that captures a specific range or object has been added. In particular, the freeview service is an extended concept of multi-view and provides a freer viewpoint.
However, since numerous videos and additional data are required for its construction, all of
the clips constituting the content cannot be simultaneously provided. Only certain clips are
selected and provided to the user. If the video is not the preferred video, change request is
made,… More >
Open Access
ARTICLE
Tahir Abbas Khan1, Sagheer Abbas1, Allah Ditta2, Muhammad Adnan Khan3, *, Hani Alquhayz4, Areej Fatima3, Muhammad Farhan Khan5
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2591-2605, 2020, DOI:10.32604/cmc.2020.011892
（This article belongs to this Special Issue: Machine Learning and Computational Methods for COVID-19 Disease Detection and Prediction)
Abstract The prediction of human diseases, particularly COVID-19, is an extremely
challenging task not only for medical experts but also for the technologists supporting
them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19,
we propose an Internet of Medical Things-based Smart Monitoring Hierarchical
Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines
the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest,
Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody
detection (lgG) that are directly involved in COVID-19. The expert system has two input
variables in layer 1, and seven input variables… More >
Open Access
ARTICLE
Chunguang Li1, *, Cuihua Li2, Cong Sun3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2607-2621, 2020, DOI:10.32604/cmc.2020.04662
Abstract In this paper, a novel discretization method in σ-τ space is developed to calculate
the upper bound limit loads and failure modes of anisotropic Mohr-Coulomb materials. To
achieve this objective, the Mohr-Coulomb yield criterion is linearized in σ-τ space, which
allows for upper bound solution of soils whose cohesion and friction coefficient varying
with direction. The finite element upper limit analysis formulation using the modified
anisotropic yield criterion is then developed. Several examples are given to illustrate the
capability and effectiveness of the proposed numerical procedure for computing rigorous
upper bounds for anisotropic soils. More >
Open Access
ARTICLE
Lingfeng Qu1, Hongjie He1, Shanjun Zhang2, Fan Chen1, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2623-2638, 2020, DOI:10.32604/cmc.2020.09723
Abstract Reversible data hiding in encrypted images (RDH-EI) technology is widely
used in cloud storage for image privacy protection. In order to improve the embedding
capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed
a reversible data hiding algorithm for encrypted images based on prediction and adaptive
classification scrambling. First, the prediction error image is obtained by a novel
prediction method before encryption. Then, the image pixel values are divided into two
categories by the threshold range, which is selected adaptively according to the image
content. Multiple high-significant bits of pixels within the threshold range are… More >
Open Access
ARTICLE
Malik Javed Akhtar1, Zahur Ahmad1, Rashid Amin1, *, Sultan H. Almotiri2, Mohammed A. Al Ghamdi2, Hamza Aldabbas3
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2639-2663, 2020, DOI:10.32604/cmc.2020.011485
Abstract A large amount of data is present on the web which can be used for useful
purposes like a product recommendation, price comparison and demand forecasting for a
particular product. Websites are designed for human understanding and not for machines.
Therefore, to make data machine-readable, it requires techniques to grab data from web
pages. Researchers have addressed the problem using two approaches, i.e., knowledge
engineering and machine learning. State of the art knowledge engineering approaches use
the structure of documents, visual cues, clustering of attributes of data records and text
processing techniques to identify data records on a web page.… More >
Open Access
ARTICLE
Hongyu Chen1, Shuyu Li1, *, Zhaosheng Zhang1
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2665-2685, 2020, DOI:10.32604/cmc.2020.010965
Abstract In recent years, mobile Internet technology and location based services have
wide application. Application providers and users have accumulated huge amount of
trajectory data. While publishing and analyzing user trajectory data have brought great
convenience for people, the disclosure risks of user privacy caused by the trajectory data
publishing are also becoming more and more prominent. Traditional k-anonymous
trajectory data publishing technologies cannot effectively protect user privacy against
attackers with strong background knowledge. For privacy preserving trajectory data
publishing, we propose a differential privacy based (k-Ψ)-anonymity method to defend
against re-identification and probabilistic inference attack. The proposed method is
divided… More >
Open Access
ARTICLE
Congdong Lv1, *, Ji Zhang2, Zhoubao Sun1, Gang Qian1
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2687-2705, 2020, DOI:10.32604/cmc.2020.011232
Abstract Cloud computing provides services to users through Internet. This open mode
not only facilitates the access by users, but also brings potential security risks. In cloud
computing, the risk of data leakage exists between users and virtual machines. Whether
direct or indirect data leakage, it can be regarded as illegal information flow. Methods,
such as access control models can control the information flow, but not the covert
information flow. Therefore, it needs to use the noninterference models to detect the
existence of illegal information flow in cloud computing architecture. Typical
noninterference models are not suitable to certificate information flow in… More >
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