Open Access
ARTICLE
Seokhoon Kim1, Dae-Young Kim2, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 1-15, 2020, DOI:10.32604/cmc.2020.09545
Abstract The Internet of Things (IoT) has enabled various intelligent services, and IoT
service range has been steadily extended through long range wide area communication
technologies, which enable very long distance wireless data transmission. End-nodes are
connected to a gateway with a single hop. They consume very low-power, using very low
data rate to deliver data. Since long transmission time is consequently needed for each
data packet transmission in long range wide area networks, data transmission should be
efficiently performed. Therefore, this paper proposes a multicast uplink data transmission
mechanism particularly for bad network conditions. Transmission delay will be increased
if… More >
Open Access
ARTICLE
Majed AbuSafiya1, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 17-30, 2020, DOI:10.32604/cmc.2020.09282
Abstract Huffman [Huffman (1952)] encoding is one of the most known compression
algorithms. In its basic use, only one encoding is given for the same letter in text to
compress. In this paper, a text compression algorithm that is based on Huffman encoding
is proposed. Huffman encoding is used to give different encodings for the same letter
depending on the prefix preceding it in the word. A deterministic finite automaton (DFA)
that recognizes the words of the text is constructed. This DFA records the frequencies for
letters that label the transitions. Every state will correspond to one of the prefixes of… More >
Open Access
ARTICLE
Shahid Rahman1, Fahad Masood2, Wajid Ullah Khan2, Niamat Ullah1, Fazal Qudus Khan3, Georgios Tsaramirsis3, Sadeeq Jan4, *, Majid Ashraf5
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 31-61, 2020, DOI:10.32604/cmc.2020.09186
Abstract Steganography aims to hide the messages from unauthorized persons for various
purposes, e.g., military correspondence, financial transaction data. Securing the data during
transmission is of utmost importance these days. The confidentiality, integrity, and
availability of the data are at risk because of the emerging technologies and complexity in
software applications, and therefore, there is a need to secure such systems and data. There
are various methodologies to deal with security issues when utilizing an open system like
the Internet. This research proposes a new technique in steganography within RGB shading
space to achieve enhanced security compared with existing systems. We… More >
Open Access
ARTICLE
M. H. T. Alshbool1, W. Shatanawi2, 3, 4, *, I. Hashim5, M. Sarr1
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 63-80, 2020, DOI:10.32604/cmc.2020.09431
Abstract One of the most attractive subjects in applied sciences is to obtain exact or
approximate solutions for different types of linear and nonlinear systems. Systems of
ordinary differential equations like systems of second-order boundary value problems
(BVPs), Brusselator system and stiff system are significant in science and engineering.
One of the most challenge problems in applied science is to construct methods to
approximate solutions of such systems of differential equations which pose great
challenges for numerical simulations. Bernstein polynomials method with residual
correction procedure is used to treat those challenges. The aim of this paper is to present
a technique… More >
Open Access
ARTICLE
Nithya Rekha Sivakumar1, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 81-96, 2020, DOI:10.32604/cmc.2020.08851
Abstract In the past few decades, Energy Efficiency (EE) has been a significant challenge
in Wireless Sensor Networks (WSNs). WSN requires reduced transmission delay and
higher throughput with high quality services, it further pays much attention in increased
energy consumption to improve the network lifetime. To collect and transmit data
Clustering based routing algorithm is considered as an effective way. Cluster Head (CH)
acts as an essential role in network connectivity and perform data transmission and data
aggregation, where the energy consumption is superior to non-CH nodes. Conventional
clustering approaches attempts to cluster nodes of same size. Moreover, owing to randomly… More >
Open Access
ARTICLE
Kyvia Pereira1, Libardo V. Vanegas-Useche2, Magd Abdel Wahab3, 4, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 97-144, 2020, DOI:10.32604/cmc.2020.09862
Abstract Fretting fatigue is a type of failure that may affect various mechanical
components, such as bolted or dovetail joints, press-fitted shafts, couplings, and ropes.
Due to its importance, many researchers have carried out experimental tests and
analytical and numerical modelling, so that the phenomena that govern the failure process
can be understood or appropriately modelled. Consequently, the performance of systems
subjected to fretting fatigue can be predicted and improved. This paper discusses
different aspects related to the finite element modelling of fretting fatigue. It presents
common experimental configurations and the analytical solutions for cylindrical contact.
Then, it discusses aspects of… More >
Open Access
ARTICLE
Kue-Hong Chen1, *, Cheng-Tsung Chen2, 3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 145-160, 2020, DOI:10.32604/cmc.2020.08864
Abstract In this study, we applied a defined auxiliary problem in a novel error
estimation technique to estimate the numerical error in the method of fundamental
solutions (MFS) for solving the Helmholtz equation. The defined auxiliary problem is
substituted for the real problem, and its analytical solution is generated using the
complementary solution set of the governing equation. By solving the auxiliary problem
and comparing the solution with the quasianalytical solution, an error curve of the MFS
versus the source location parameters can be obtained. Thus, the optimal location
parameter can be identified. The convergent numerical solution can be obtained and… More >
Open Access
ARTICLE
Kalaphath Kounlaxay1, Soo Kyun Kim2, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 161-180, 2020, DOI:10.32604/cmc.2020.09930
Abstract To improve and develop education systems, the communication between
instructors and learners in a class during the learning process is of utmost importance.
Currently the presentations of 3D models using mixed reality (MR) technology can be used
to avoid misinterpretations of oral and 2D model presentations. As an independent concept
and MR applications, MR combines the excellent of each virtual reality (VR) and
augmented reality (AR). This work aims to present the descriptions of MR systems, which
include its devices, applications, and literature reviews and proposes computer vision
tracking using the AR Toolkit Tracking Library. The focus of this work… More >
Open Access
ARTICLE
Jae-Hyun Ro1, Won-Seok Lee1, Min-Goo Kang2, Dae-Ki Hong3, Hyoung-Kyu Song1, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 181-191, 2020, DOI:10.32604/cmc.2020.09998
Abstract In this paper, the supervised Deep Neural Network (DNN) based signal detection
is analyzed for combating with nonlinear distortions efficiently and improving error
performances in clipping based Orthogonal Frequency Division Multiplexing (OFDM)
ssystem. One of the main disadvantages for the OFDM is the high Peak to Average Power
Ratio (PAPR). The clipping is a simple method for the PAPR reduction. However, an effect
of the clipping is nonlinear distortion, and estimations for transmitting symbols are difficult
despite a Maximum Likelihood (ML) detection at the receiver. The DNN based online
signal detection uses the offline learning model where all weights and… More >
Open Access
ARTICLE
Xiangmao Chang1, 2, *, Xiaoxiang Xu1, Deliang Yang3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 193-206, 2020, DOI:10.32604/cmc.2020.08183
Abstract Strip Wireless Sensor Networks (SWSNs) have drawn much attention in many
applications such as monitoring rivers, highways and coal mines. Packet delivery in
SWSN usually requires a large number of multi-hop transmissions which leads to long
transmission latency in low-duty-cycle SWSNs. Several pipeline scheduling schemes
have been proposed to reduce latency. However, when communication links are
unreliable, pipeline scheduling is prone to failure. In this paper, we propose a pipeline
scheduling transmission protocol based on constructive interference. The protocol first
divides the whole network into multiple partitions and uses a pipelined mechanism to
allocate active time slots for each partition.… More >
Open Access
ARTICLE
Yu Jiang1, 2, Dengwen Yu1, Mingzhao Zhao1, 2, Hongtao Bai1, 2, Chong Wang1, 2, 3, Lili He1, 2, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 207-216, 2020, DOI:10.32604/cmc.2020.09861
Abstract Semi-supervised clustering improves learning performance as long as it uses a
small number of labeled samples to assist un-tagged samples for learning. This paper
implements and compares unsupervised and semi-supervised clustering analysis of BOAArgo ocean text data. Unsupervised K-Means and Affinity Propagation (AP) are two
classical clustering algorithms. The Election-AP algorithm is proposed to handle the final
cluster number in AP clustering as it has proved to be difficult to control in a suitable
range. Semi-supervised samples thermocline data in the BOA-Argo dataset according to
the thermocline standard definition, and use this data for semi-supervised cluster analysis.
Several semi-supervised clustering… More >
Open Access
ARTICLE
Wei Fang1, 2, Feihong Zhang1, *, Yewen Ding1, Jack Sheng3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 217-231, 2020, DOI:10.32604/cmc.2020.06395
Abstract Image recognition technology is an important field of artificial intelligence.
Combined with the development of machine learning technology in recent years, it has
great researches value and commercial value. As a matter of fact, a single recognition
function can no longer meet people’s needs, and accurate image prediction is the trend
that people pursue. This paper is based on Long Short-Term Memory (LSTM) and Deep
Convolution Generative Adversarial Networks (DCGAN), studies and implements a
prediction model by using radar image data. We adopt a stack cascading strategy in
designing network connection which can control of parameter convergence better. This
new… More >
Open Access
ARTICLE
Shuqiang Guo1, *, Baohai Yue1, Manyang Gao2, Xinxin Zhou1, Bo Wang3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 233-251, 2020, DOI:10.32604/cmc.2020.010039
Abstract The recycling of glass bottles can reduce the consumption of resources and
contribute to environmental protection. At present, the classification of recycled glass
bottles is difficult due to the many differences in specifications and models. This paper
proposes a classification algorithm for glass bottles that is divided into two stages,
namely the extraction of candidate regions and the classification of classifiers. In the
candidate region extraction stage, aiming at the problem of the large time overhead
caused by the use of the SIFT (scale-invariant feature transform) descriptor in SS
(selective search), an improved feature of HLSN (Haar-like based on SPP-Net)… More >
Open Access
ARTICLE
Xiaoyan Zhao1, *, Shuwen Chen2, Lin Zhou3, Ying Chen3, 4
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 253-271, 2020, DOI:10.32604/cmc.2020.09848
Abstract Microphone array-based sound source localization (SSL) is a challenging task
in adverse acoustic scenarios. To address this, a novel SSL algorithm based on deep
neural network (DNN) using steered response power-phase transform (SRP-PHAT)
spatial spectrum as input feature is presented in this paper. Since the SRP-PHAT spatial
power spectrum contains spatial location information, it is adopted as the input feature for
sound source localization. DNN is exploited to extract the efficient location information
from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level
features. SRP-PHAT at each steering position within a frame is arranged into a vector,
which… More >
Open Access
ARTICLE
Yan Liu1, Wenyuan Fang1, Qiang Wei1, *, Yuan Zhao1, Liang Wang2
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 273-295, 2020, DOI:10.32604/cmc.2020.09659
Abstract Code defects can lead to software vulnerability and even produce vulnerability
risks. Existing research shows that the code detection technology with text analysis can
judge whether object-oriented code files are defective to some extent. However, these
detection techniques are mainly based on text features and have weak detection
capabilities across programs. Compared with the uncertainty of the code and text caused
by the developer’s personalization, the programming language has a stricter logical
specification, which reflects the rules and requirements of the language itself and the
developer’s potential way of thinking. This article replaces text analysis with
programming logic modeling, breaks… More >
Open Access
ARTICLE
Jiangheng Kou1, Mingxing He1, *, Ling Xiong1, Zihang Ge2, Guangmin Xie1
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 297-312, 2020, DOI:10.32604/cmc.2020.09758
Abstract With the development of communication technologies, various mobile devices
and different types of mobile services became available. The emergence of these services
has brought great convenience to our lives. The multi-server architecture authentication
protocols for mobile cloud computing were proposed to ensure the security and
availability between mobile devices and mobile services. However, most of the protocols
did not consider the case of hierarchical authentication. In the existing protocol, when a
mobile user once registered at the registration center, he/she can successfully authenticate
with all mobile service providers that are registered at the registration center, but real
application scenarios are… More >
Open Access
ARTICLE
Liang Yang1, *, Daojian Zeng2, Jianhua Yan3, Yaozhang Sai1
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 313-323, 2020, DOI:10.32604/cmc.2020.09809
Abstract The Synthetic Aperture Radar (SAR) raw data generator is required to the
evaluation of focusing algorithms, moving target analysis, and hardware design. The
time-domain SAR simulator can generate the accurate raw data but it needs much time.
The frequency-domain simulator not only increases the efficiency but also considers the
trajectory deviations of the radar. In addition, the raw signal of the extended scene
included static and moving targets can be generated by some frequency-domain
simulators. However, the existing simulators concentrate on the raw signal simulation of
the static extended scene and moving targets at uniform speed mostly. As for the… More >
Open Access
ARTICLE
Junxiang Wang1, *, Lin Huang1, Ying Zhang1, Yonghong Zhu1, Jiangqun Ni2, Yunqing Shi3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 325-344, 2020, DOI:10.32604/cmc.2020.09784
Abstract To measure the security for hot searched reversible data hiding (RDH)
technique, especially for the common-used histogram-shifting based RDH (denoted as
HS-RDH), several steganalysis schemes are designed to detect whether some secret data
has been hidden in a normal-looking image. However, conventional steganalysis schemes
focused on the previous RDH algorithms, i.e., some early spatial/pixel domain-based
histogram-shifting (HS) schemes, which might cause great changes in statistical
characteristics and thus be easy to be detected. For recent improved methods, such as
some adaptive prediction error (PE) based embedding schemes, those conventional
schemes might be invalid, since those adaptive embedding mechanism would effectively… More >
Open Access
ARTICLE
Senbo Chen1, 3, *, Wenan Tan1, 2
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 345-358, 2020, DOI:10.32604/cmc.2020.09807
Abstract The problem of influence maximizing in social networks refers to obtaining a
set of nodes of a specified size under a specific propagation model so that the aggregation
of the node-set in the network has the greatest influence. Up to now, most of the research
has tended to focus on monolayer network rather than on multiplex networks. But in the
real world, most individuals usually exist in multiplex networks. Multiplex networks are
substantially different as compared with those of a monolayer network. In this paper, we
integrate the multi-relationship of agents in multiplex networks by considering the
existing and relevant… More >
Open Access
ARTICLE
Muhammad Waqas1, 2, Shanshan Tu1, 3, *, Sadaqat Ur Rehman1, Zahid Halim2, Sajid
Anwar2, Ghulam Abbas2, Ziaul Haq Abbas4, Obaid Ur Rehman5
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 359-371, 2020, DOI:10.32604/cmc.2020.09821
Abstract Security threats to smart and autonomous vehicles cause potential
consequences such as traffic accidents, economically damaging traffic jams, hijacking,
motivating to wrong routes, and financial losses for businesses and governments. Smart
and autonomous vehicles are connected wirelessly, which are more attracted for attackers
due to the open nature of wireless communication. One of the problems is the rogue
attack, in which the attacker pretends to be a legitimate user or access point by utilizing
fake identity. To figure out the problem of a rogue attack, we propose a reinforcement
learning algorithm to identify rogue nodes by exploiting the channel state… More >
Open Access
ARTICLE
Lili He1, 2, Zhiwei Cai1, 2, Dantong Ouyang1, 2, Changshuai Wang1, 2, Yu Jiang1, 2, Chong Wang1, 2, 3, Hongtao Bai1, 2, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 373-388, 2020, DOI:10.32604/cmc.2020.09860
Abstract In view of the satellite cloud-derived wind inversion has the characteristics of
large scale, intensive computing and time-consuming serial inversion algorithm is very
difficult to break through the bottleneck of efficiency. We proposed a parallel acceleration
scheme of cloud-derived wind inversion algorithm based on MPI cluster parallel technique
in this paper. The divide-and-conquer idea, assigning winds vector inversion tasks to each
computing unit, is identified according to a certain strategy. Each computing unit executes
the assigned tasks in parallel, namely divide-and-rule the inversion task, so as to reduce the
efficiency bottleneck of long inversion time caused by serial time accumulation.… More >
Open Access
ARTICLE
Bo Xiao1, Yinghang Jiang2, Qi Liu2, 5, *, Xiaodong Liu3, Mingxu Sun4, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 389-399, 2020, DOI:10.32604/cmc.2020.06092
Abstract MEMS accelerometers are widely used in various fields due to their small size and
low cost, and have good application prospects. However, the low accuracy limits its range of
applications. To ensure data accuracy and safety we need to calibrate MEMS accelerometers.
Many authors have improved accelerometer accuracy by calculating calibration parameters,
and a large number of published calibration methods have been confusing. In this context, this
paper introduces these techniques and methods, analyzes and summarizes the main error
models and calibration procedures, and provides useful suggestions. Finally, the content of
the accelerometer calibration method needs to be overcome. More >
Open Access
ARTICLE
Tong Li1, Shibin Zhang1, *, Jinyue Xia2
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 401-438, 2020, DOI:10.32604/cmc.2020.010551
Abstract Generative adversarial network (GAN) is one of the most promising methods for
unsupervised learning in recent years. GAN works via adversarial training concept and has
shown excellent performance in the fields image synthesis, image super-resolution, video
generation, image translation, etc. Compared with classical algorithms, quantum algorithms
have their unique advantages in dealing with complex tasks, quantum machine learning
(QML) is one of the most promising quantum algorithms with the rapid development of
quantum technology. Specifically, Quantum generative adversarial network (QGAN) has
shown the potential exponential quantum speedups in terms of performance. Meanwhile,
QGAN also exhibits some problems, such as barren… More >
Open Access
ARTICLE
Chao Guo1, *, Juan Guo2, Chanjuan Yu1, Zhaobin Li1, Cheng Gong3, Abdul Waheed4
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 439-454, 2020, DOI:10.32604/cmc.2020.09792
Abstract Satellite networks have high requirements for security and data processing
speed. In order to improve the reliability of the network, software-defined network (SDN)
technology is introduced and a central controller is set in the network. Due to the
characteristics of global perspective, control data separation, and centralized control of
SDN, the idea of SDN is introduced to the design of the satellite network model. As a
result, satellite nodes are only responsible for data transmission, while the maintenance of
the links and the calculation of routes are implemented by the controller. For the massive
LEO satellite network based on SDN,… More >
Open Access
ARTICLE
Jialin Ma1, *, Jieyi Cheng1, Lin Zhang1, Lei Zhou1, Bolun Chen1, 2
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 455-469, 2020, DOI:10.32604/cmc.2020.09780
Abstract Traditional topic models have been widely used for analyzing semantic topics
from electronic documents. However, the obvious defects of topic words acquired by
them are poor in readability and consistency. Only the domain experts are possible to
guess their meaning. In fact, phrases are the main unit for people to express semantics.
This paper presents a Distributed Representation-Phrase Latent Dirichlet Allocation (DRPhrase LDA) which is a phrase topic model. Specifically, we reasonably enhance the
semantic information of phrases via distributed representation in this model. The
experimental results show the topics quality acquired by our model is more readable and
consistent… More >
Open Access
ARTICLE
Nana Zhang1, Kun Zhu1, Shi Ying1, *, Xu Wang2
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 471-499, 2020, DOI:10.32604/cmc.2020.010117
Abstract Software defect prediction is a research hotspot in the field of software
engineering. However, due to the limitations of current machine learning algorithms, we
can’t achieve good effect for defect prediction by only using machine learning algorithms.
In previous studies, some researchers used extreme learning machine (ELM) to conduct
defect prediction. However, the initial weights and biases of the ELM are determined
randomly, which reduces the prediction performance of ELM. Motivated by the idea of
search based software engineering, we propose a novel software defect prediction model
named KAEA based on kernel principal component analysis (KPCA), adaptive genetic
algorithm, extreme… More >
Open Access
ARTICLE
Yifei Wei1, *, Yu Gong1, Qiao Li1, Mei Song1, *, Xiaojun Wang2
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 501-514, 2020, DOI:10.32604/cmc.2020.010048
Abstract In this paper, maximizing energy efficiency (EE) through radio resource
allocation for renewable energy powered heterogeneous cellular networks (HetNet) with
energy sharing, is investigated. Our goal is to maximize the network EE, conquer the
instability of renewable energy sources and guarantee the fairness of users during
allocating resources. We define the objective function as a sum weighted EE of all links
in the HetNet. We formulate the resource allocation problem in terms of subcarrier
assignment, power allocation and energy sharing, as a mixed combinatorial and
non-convex optimization problem. We propose an energy efficient resource allocation
scheme, including a centralized resource… More >
Open Access
ARTICLE
Weibo Yang1, Weidong Liu2, *, Jinming Liu3, Mingyang Zhang4
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 515-525, 2020, DOI:10.32604/cmc.2020.09801
Abstract The Convolutional Neural Network (CNN) is a widely used deep neural network.
Compared with the shallow neural network, the CNN network has better performance and
faster computing in some image recognition tasks. It can effectively avoid the problem that
network training falls into local extremes. At present, CNN has been applied in many
different fields, including fault diagnosis, and it has improved the level and efficiency of
fault diagnosis. In this paper, a two-streams convolutional neural network (TCNN) model is
proposed. Based on the short-time Fourier transform (STFT) spectral and Mel Frequency
Cepstrum Coefficient (MFCC) input characteristics of two-streams acoustic… More >
Open Access
ARTICLE
Chao Guo1, Cheng Gong2, Juan Guo3, Zhanzhen Wei1, *, Yanyan Han1, Sher Zaman Khan4
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 527-540, 2020, DOI:10.32604/cmc.2020.09788
Abstract Under the background of the rapid development of ground mobile
communication, the advantages of high coverage, survivability, and flexibility of satellite
communication provide air support to the construction of space information network.
According to the requirements of the future space information communication, a
software-defined Space-Air-Ground Integrated network architecture was proposed. It
consisted of layered structure satellite backbone network, deep space communication
network, the stratosphere communication network and the ground network. The SpaceAir-Ground Integrated network was supported by the satellite backbone network. It
provided data relay for the missions such as deep space exploration and controlled the
deep-space spacecraft when needed.… More >
Open Access
ARTICLE
Shu Fang1, Lei Huang1, Yi Wan2, Weize Sun1, *, Jingxin Xu3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 541-555, 2020, DOI:10.32604/cmc.2020.010066
Abstract With the development of science and technology, the status of the water
environment has received more and more attention. In this paper, we propose a deep
learning model, named a Joint Auto-Encoder network, to solve the problem of outlier
detection in water supply data. The Joint Auto-Encoder network first expands the size of
training data and extracts the useful features from the input data, and then reconstructs
the input data effectively into an output. The outliers are detected based on the network’s
reconstruction errors, with a larger reconstruction error indicating a higher rate to be an
outlier. For water supply… More >
Open Access
ARTICLE
Kehua Yang1, *, Shaosong Long1, Wei Zhang1, Jiqing Yao2, Jing Liu1
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 557-570, 2020, DOI:10.32604/cmc.2020.09907
Abstract The personalized news recommendation has been very popular in the news
recommendation field. In most research, the picture information in the news is ignored, but
the information conveyed to the users through pictures is more intuitive and more likely to
affect the users’ reading interests than the one in the textual form. Therefore, in this paper, a
model that combines images and texts in the news is proposed. In this model, the new tags
are extracted from the images and texts in the news, and based on these new tags, an adaptive
tag (AT) algorithm is proposed. The AT algorithm… More >
Open Access
ARTICLE
Xiaoping Zhao1, 4, Yifei Wang2, *, Yonghong Zhang2, Jiaxin Wu1, Yunqing Shi3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 571-587, 2020, DOI:10.32604/cmc.2020.06363
Abstract Stochastic resonance can use noise to enhance weak signals, effectively
reducing the effect of noise signals on feature extraction. In order to improve the early fault
recognition rate of rolling bearings, and to overcome the shortcomings of lack of
interaction in the selection of SR (Stochastic Resonance) method parameters and the lack
of validation of the extracted features, an adaptive genetic random resonance early fault
diagnosis method for rolling bearings was proposed. compared with the existing methods,
the AGSR (Adaptive Genetic Stochastic Resonance) method uses genetic algorithms to
optimize the system parameters, and further optimizes the parameters while considering
the… More >
Open Access
ARTICLE
Sheng Liu1, *, Hailin Cao2, Decheng Wu2, Xiyuan Chen3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 589-605, 2020, DOI:10.32604/cmc.2020.09964
Abstract Arranging multiple identical sub-arrays in a special way can enhance degrees
of freedom (DOFs) and obtain a hole-free difference co-array (DCA). In this paper, by
adjusting the interval of adjacent sub-arrays, a kind of generalized array architecture with
larger aperture is proposed. Although some holes may exist in the DCA of the proposed
array, they are distributed uniformly. Utilizing the partial continuity of the DCA, an
extended covariance matrix can be constructed. Singular value decomposition (SVD) is
used to obtain an extended signal sub-space, by which the direction-of-arrival (DOA)
estimation algorithm for quasi-stationary signals is given. In order to eliminating… More >
Open Access
ARTICLE
Jiaye Pan1, Yi Zhuang1, *, Xinwen Hu1, 2, Wenbing Zhao3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 607-622, 2020, DOI:10.32604/cmc.2020.09853
Abstract Nowadays cloud architecture is widely applied on the internet. New malware
aiming at the privacy data stealing or crypto currency mining is threatening the security of
cloud platforms. In view of the problems with existing application behavior monitoring
methods such as coarse-grained analysis, high performance overhead and lack of
applicability, this paper proposes a new fine-grained binary program monitoring and
analysis method based on multiple system level components, which is used to detect the
possible privacy leakage of applications installed on cloud platforms. It can be used online
in cloud platform environments for fine-grained automated analysis of target programs,
ensuring… More >
Open Access
ARTICLE
Deyin Li1, 2, Mingzhi Cheng3, Yu Yang1, 2, *, Min Lei1, 2, Linfeng Shen4
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 623-635, 2020, DOI:10.32604/cmc.2020.09800
Abstract Deep learning networks are widely used in various systems that require
classification. However, deep learning networks are vulnerable to adversarial attacks. The
study on adversarial attacks plays an important role in defense. Black-box attacks require
less knowledge about target models than white-box attacks do, which means black-box
attacks are easier to launch and more valuable. However, the state-of-arts black-box
attacks still suffer in low success rates and large visual distances between generative
adversarial images and original images. This paper proposes a kind of fast black-box
attack based on the cross-correlation (FBACC) method. The attack is carried out in two
stages.… More >
Open Access
ARTICLE
Zijian Li1, Chengying Chi1, *, Yunyun Zhan2, *
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 637-650, 2020, DOI:10.32604/cmc.2020.010265
Abstract The translation quality of neural machine translation (NMT) systems depends
largely on the quality of large-scale bilingual parallel corpora available. Research shows
that under the condition of limited resources, the performance of NMT is greatly reduced,
and a large amount of high-quality bilingual parallel data is needed to train a competitive
translation model. However, not all languages have large-scale and high-quality bilingual
corpus resources available. In these cases, improving the quality of the corpora has
become the main focus to increase the accuracy of the NMT results. This paper proposes
a new method to improve the quality of data by… More >
Open Access
ARTICLE
Caifeng Cheng1, 2, Xiang’e Sun1, *, Deshu Lin3, Yiliu Tu4
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 651-664, 2020, DOI:10.32604/cmc.2020.09874
Abstract In actual exploration, the demand for 3D seismic data collection is increasing,
and the requirements for data are becoming higher and higher. Accordingly, the collection
cost and data volume also increase. Aiming at this problem, we make use of the nature of
data sparse expression, based on the theory of compressed sensing, to carry out the research
on the efficient collection method of seismic data. It combines the collection of seismic
data and the compression in data processing in practical work, breaking through the
limitation of the traditional sampling frequency, and the sparse characteristics of the
seismic signal are utilized… More >
Open Access
ARTICLE
Haijun Geng1, Jiangyuan Yao2, *, Yangyang Zhang3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 665-679, 2020, DOI:10.32604/cmc.2020.09912
Abstract Loop free alternate (LFA) is a routing protection scheme that is currently
deployed in commercial routers. However, LFA cannot handle all single network
component failure scenarios in traditional networks. As Internet service providers have
begun to deploy software defined network (SDN) technology, the Internet will be in a
hybrid SDN network where traditional and SDN devices coexist for a long time.
Therefore, this study aims to deploy the LFA scheme in hybrid SDN network architecture
to handle all possible single network component failure scenarios. First, the deployment
of LFA scheme in a hybrid SDN network is described as a 0-1… More >
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