Open Access
ARTICLE
Shiqi Wang1, Yimin Yang1, *, Ruizhong Wei1, Qingming Jonathan Wu2
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1081-1091, 2020, DOI:10.32604/cmc.2020.09648
Abstract Human motion recognition plays a crucial role in the video analysis
framework. However, a given video may contain a variety of noises, such as an unstable
background and redundant actions, that are completely different from the key actions.
These noises pose a great challenge to human motion recognition. To solve this problem,
we propose a new method based on the 3-Dimensional (3D) Bag of Visual Words
(BoVW) framework. Our method includes two parts: The first part is the video action
feature extractor, which can identify key actions by analyzing action features. In the
video action encoder, by analyzing the action… More >
Open Access
ARTICLE
Muhammad Zubair Asghar1, Fazli Subhan2, Muhammad Imran1, Fazal Masud Kundi1, Adil Khan3, Shahboddin Shamshirband4, 5, *, Amir Mosavi6, 7, 8, Peter Csiba8, Annamaria R. Varkonyi Koczy8
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1093-1118, 2020, DOI:10.32604/cmc.2020.07709
Abstract Emotion detection from the text is a challenging problem in the text analytics.
The opinion mining experts are focusing on the development of emotion detection
applications as they have received considerable attention of online community including
users and business organization for collecting and interpreting public emotions. However,
most of the existing works on emotion detection used less efficient machine learning
classifiers with limited datasets, resulting in performance degradation. To overcome this
issue, this work aims at the evaluation of the performance of different machine learning
classifiers on a benchmark emotion dataset. The experimental results show the
performance of different machine… More >
Open Access
ARTICLE
Nazeran Idrees1, *, Raghisa Khalid1, Fozia Bashir Farooq2, Sumiya Nasir3
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1119-1132, 2020, DOI:10.32604/cmc.2020.08166
Abstract A numerical parameter mathematically derived from the graph structure is a
topological index. The topological index is the first actual choice in QSAR research and
these indices are used to build the correlation model between the chemical structures of
various chemicals compounds. Here, we investigate some old degree-based topological
indices like Randic index, sum connectivity index, ABC index, GA index, 1st and 2nd
Zagreb indices, modified second Zagreb index, redefined version of 1st, 2nd and 3rd
Zagreb indices, hyper and augmented Zagreb indices, forgotten index and symmetric
division degree index, and some new degree-based indices like SK index, SK1 index,… More >
Open Access
ARTICLE
Ravi Samikannu1, *, Rohini Ravi2, Sivaram Murugan3, Bakary Diarra4
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1133-1142, 2020, DOI:10.32604/cmc.2020.08578
Abstract The identification of brain tumors is multifarious work for the separation of the
similar intensity pixels from their surrounding neighbours. The detection of tumors is
performed with the help of automatic computing technique as presented in the proposed
work. The non-active cells in brain region are known to be benign and they will never
cause the death of the patient. These non-active cells follow a uniform pattern in brain and
have lower density than the surrounding pixels. The Magnetic Resonance (MR) image
contrast is improved by the cost map construction technique. The deep learning algorithm
for differentiating the normal brain… More >
Open Access
ARTICLE
Wafaa Alharbi1, Abdulrahman Aljohani1, Essam El-Zahar2, 3, *, Abdelhalim Ebaid1
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1143-1157, 2020, DOI:10.32604/cmc.2020.08875
Abstract In this paper, the mathematical model describing the third-grade nonNewtonian blood flow suspended with nanoparticles through porous arteries is exactly
solved. The present physical model was solved in the research literature via the optimal
homotopy analysis method and the collocation method, where the obtained solution was
compared with the numerical fourth-order Runge-Kutta solution. However, the present
paper only introduces a new approach to obtain the exact solution of the concerned
system and implements such exact solution as a reference to validate the published
approximate solutions. Several remarks on the previously published results are observed
and discussed in detail through tables… More >
Open Access
ARTICLE
Ahmed Y. Hamed1, Monagi H. Alkinani2, M. R. Hassan3, *
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1159-1173, 2020, DOI:10.32604/cmc.2020.09176
Abstract In the distributed networks, many applications send information from a source
node to multiple destination nodes. To support these applications requirements, the paper
presents a multi-objective algorithm based on ant colonies to construct a multicast tree
for data transmission in a computer network. The proposed algorithm simultaneously
optimizes total weight (cost, delay and hop) of the multicast tree. Experimental results
prove the proposed algorithm outperforms a recently published Multi-objective Multicast
Algorithm specially designed for solving the multicast routing problem. Also, it is able to
find a better solution with fast convergence speed and high reliability. More >
Open Access
ARTICLE
Amin Bemani1, Alireza Baghban2, Shahaboddin Shamshirband3, 4, *, Amir Mosavi5, 6, 7, Peter Csiba7, Annamaria R. Varkonyi-Koczy5, 7
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1175-1204, 2020, DOI:10.32604/cmc.2020.07723
Abstract In the present work, a novel machine learning computational investigation is
carried out to accurately predict the solubility of different acids in supercritical carbon
dioxide. Four different machine learning algorithms of radial basis function, multi-layer
perceptron (MLP), artificial neural networks (ANN), least squares support vector machine
(LSSVM) and adaptive neuro-fuzzy inference system (ANFIS) are used to model the
solubility of different acids in carbon dioxide based on the temperature, pressure, hydrogen
number, carbon number, molecular weight, and the dissociation constant of acid. To
evaluate the proposed models, different graphical and statistical analyses, along with novel
sensitivity analysis, are carried out.… More >
Open Access
ARTICLE
Hongqiong Tang1, 2, Xiaoyuan Yang1, 2, *, Yingnan Zhang1, Ke Niu1, 2
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1205-1219, 2020, DOI:10.32604/cmc.2020.010075
Abstract H.264/AVC video is one of the most popular multimedia and has been widely
used as the carriers of video steganography. In this paper, a novel motion vector (MV)
based steganographic algorithm is proposed for the H.264/AVC compressed video
without distortion. Four modules are introduced to eliminate the distortion caused by the
modifications of motion vectors and guarantee the security of the algorithm. In the
embedding block, the motion vector space encoding is used to embed a (2n+1)-ary
notational number into an n-dimension vector composed of motion vectors generated
from the selection block. Scrambling is adopted to disturb the order of… More >
Open Access
ARTICLE
Zhichun Jia1, 2, Qiuyang Han1, Yanyan Li1, Yuqiang Yang1, Xing Xing1, 2, *
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1221-1235, 2020, DOI:10.32604/cmc.2020.09722
Abstract With the development of the service-oriented computing (SOC), web service
has an important and popular solution for the design of the application system to various
enterprises. Nowadays, the numerous web services are provided by the service providers
on the network, it becomes difficult for users to select the best reliable one from a large
number of services with the same function. So it is necessary to design feasible selection
strategies to provide users with the reliable services. Most existing methods attempt to
select services according to accurate predictions for the quality of service (QoS) values.
However, because the network and… More >
Open Access
ARTICLE
Yue Ruan1, *, Samuel Marsh2, Xilin Xue1, Zhihao Liu3, Jingbo Wang2, *
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1237-1247, 2020, DOI:10.32604/cmc.2020.010001
Abstract The Quantum Approximate Optimization Algorithm (QAOA) is an
algorithmic framework for finding approximate solutions to combinatorial optimization
problems. It consists of interleaved unitary transformations induced by two operators
labelled the mixing and problem Hamiltonians. To fit this framework, one needs to
transform the original problem into a suitable form and embed it into these two
Hamiltonians. In this paper, for the well-known NP-hard Traveling Salesman Problem
(TSP), we encode its constraints into the mixing Hamiltonian rather than the conventional
approach of adding penalty terms to the problem Hamiltonian. Moreover, we map edges
(routes) connecting each pair of cities to qubits,… More >
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