Open Access
ARTICLE
Jinlan Xu*, Shuxin Xiao, Gang Xu, Renshu Gu
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028665
（This article belongs to this Special Issue: Integration of Geometric Modeling and Numerical Simulation)
Abstract In this paper, we propose a parameterization transfer algorithm for planar domains bounded by B-spline curves,
where the shapes of the planar domains are similar. The domain geometries are considered to be similar if their
simplified skeletons have the same structures. One domain we call source domain, and it is parameterized using
multi-patch B-spline surfaces. The resulting parameterization is C1 continuous in the regular region and G1
continuous around singular points regardless of whether the parameterization of the source domain is C1/G1
continuous or not. In this algorithm, boundary control points of the source domain are extracted from its
parameterization… More >
Open Access
REVIEW
Apurva Sonavane1, Aditya Khamparia2,*, Deepak Gupta3
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028203
（This article belongs to this Special Issue: Intelligent Biomedical Image Processing and Computer Vision)
Abstract IoT usage in healthcare is one of the fastest growing domains all over the world which applies to every age
group. Internet of Medical Things (IoMT) bridges the gap between the medical and IoT field where medical
devices communicate with each other through a wireless communication network. Advancement in IoMT makes
human lives easy and better. This paper provides a comprehensive detailed literature survey to investigate different
IoMT-driven applications, methodologies, and techniques to ensure the sustainability of IoMT-driven systems. The
limitations of existing IoMT frameworks are also analyzed concerning their applicability in real-time driven systems
or applications. In addition to… More >
Open Access
ARTICLE
Ali S. Alghamdi1, Mohana Alanazi2, Abdulaziz Alanazi3, Yazeed Qasaymeh1,*, Muhammad Zubair1,4, Ahmed Bilal Awan5, M. G. B. Ashiq6
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.029453
Abstract To maximize energy profit with the participation of electricity, natural gas, and district heating networks in the
day-ahead market, stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and
wind resources, has been carried out. This has been done using a new meta-heuristic algorithm, improved artificial
rabbits optimization (IARO). In this study, the uncertainty of solar and wind energy sources is modeled using
Hang’s two-point estimating method (TPEM). The IARO algorithm is applied to calculate the best capacity of hub
energy equipment, such as solar and wind renewable energy sources, combined heat and power (CHP) systems,
steam… More >
Open Access
ARTICLE
Lei Ling1, Lijun Huang2, Jie Wang2, Li Zhang2, Yue Wu2, Yizhang Jiang1, Kaijian Xia2,3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028828
（This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
Abstract In recent years, the soft subspace clustering algorithm has shown good results for high-dimensional data, which
can assign different weights to each cluster class and use weights to measure the contribution of each dimension
in various features. The enhanced soft subspace clustering algorithm combines interclass separation and intraclass
tightness information, which has strong results for image segmentation, but the clustering algorithm is vulnerable
to noisy data and dependence on the initialized clustering center. However, the clustering algorithm is susceptible to
the influence of noisy data and reliance on initialized clustering centers and falls into a local optimum; the clustering
effect… More >
Open Access
ARTICLE
Muzi Li*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.026827
（This article belongs to this Special Issue: AI and Machine Learning Modeling in Civil and Building Engineering)
Abstract Modular construction as an innovative method aids the construction industry in transforming to off-site construction production with high efficiency and environmental friendliness. Despite the obvious advantages, the uptake of
modular construction is not booming as expected. However, previous studies have investigated and summarized the
barriers to the adoption of modular construction. In this research, a Large-Scale Group Decision Making (LSGDM)-
based analysis is first made of the severity of barriers to modular construction adoption from the perspective of
construction stakeholders. In addition, the Technology-Organization-Environment (TOE) framework is utilized
to identify the barriers based on three contexts (technology, organization, and environment).… More >
Open Access
ARTICLE
Mahmood Hussain Mir1,*, Sanjay Jamwal1, Ummer Iqbal2, Abolfazl Mehbodniya3, Julian Webber3, Umar Hafiz Khan4
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027173
（This article belongs to this Special Issue: Smart and Secure Solutions for Medical Industry)
Abstract The lack of modern technology in healthcare has led to the death of thousands of lives worldwide due to COVID-
19 since its outbreak. The Internet of Things (IoT) along with other technologies like Machine Learning can
revolutionize the traditional healthcare system. Instead of reactive healthcare systems, IoT technology combined
with machine learning and edge computing can deliver proactive and preventive healthcare services. In this study,
a novel healthcare edge-assisted framework has been proposed to detect and prognosticate the COVID-19 suspects
in the initial phases to stop the transmission of coronavirus infection. The proposed framework is based on edge
computing… More >
Open Access
ARTICLE
Cuiyu Wang, Xinyu Li, Yiping Gao*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028098
（This article belongs to this Special Issue: Computing Methods for Industrial Artificial Intelligence)
Abstract Job shop scheduling (JS) is an important technology for modern manufacturing. Flexible job shop scheduling (FJS)
is critical in JS, and it has been widely employed in many industries, including aerospace and energy. FJS enables
any machine from a certain set to handle an operation, and this is an NP-hard problem. Furthermore, due to the
requirements in real-world cases, multi-objective FJS is increasingly widespread, thus increasing the challenge of
solving the FJS problems. As a result, it is necessary to develop a novel method to address this challenge. To achieve
this goal, a novel collaborative evolutionary algorithm with two-population based… More >
Open Access
ARTICLE
Ibtehal Alazman1, Kholoud Saad Albalawi1, Pranay Goswami2,*, Kuldeep Malik2
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028674
（This article belongs to this Special Issue: Recent Developments on Computational Biology-I)
Abstract This paper presents a restricted SIR mathematical model to analyze the evolution of a contagious infectious disease
outbreak (COVID-19) using available data. The new model focuses on two main concepts: first, it can present
multiple waves of the disease, and second, it analyzes how far an infection can be eradicated with the help of
vaccination. The stability analysis of the equilibrium points for the suggested model is initially investigated by
identifying the matching equilibrium points and examining their stability. The basic reproduction number is
calculated, and the positivity of the solutions is established. Numerical simulations are performed to determine
if… More >
Open Access
ARTICLE
Jiaqun Zhu1, Hongda Chen2, Yiqing Fan1, Tongguang Ni1,2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027709
（This article belongs to this Special Issue: Computer Modeling for Smart Cities Applications)
Abstract To create a green and healthy living environment, people have put forward higher requirements for the refined
management of ecological resources. A variety of technologies, including satellite remote sensing, Internet of
Things, artificial intelligence, and big data, can build a smart environmental monitoring system. Remote sensing
image classification is an important research content in ecological environmental monitoring. Remote sensing
images contain rich spatial information and multi-temporal information, but also bring challenges such as difficulty
in obtaining classification labels and low classification accuracy. To solve this problem, this study develops a
transductive transfer dictionary learning (TTDL) algorithm. In the TTDL, the… More >
Open Access
ARTICLE
Qingyue Zhao1, Qiaoyu Gu2, Zhijun Gao3,*, Shipian Shao1, Xinyuan Zhang1
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027500
（This article belongs to this Special Issue: Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract Building indoor dangerous behavior recognition is a specific application in the field of abnormal human recognition. A human dangerous behavior recognition method based on LSTM-GCN with attention mechanism (GLA)
model was proposed aiming at the problem that the existing human skeleton-based action recognition methods
cannot fully extract the temporal and spatial features. The network connects GCN and LSTM network in series,
and inputs the skeleton sequence extracted by GCN that contains spatial information into the LSTM layer for
time sequence feature extraction, which fully excavates the temporal and spatial features of the skeleton sequence.
Finally, an attention layer is designed… More >
Open Access
REVIEW
Jiaqi Wang1, Pengfei Sun1, Leilei Chen2, Jianfeng Yang3, Zhenghe Liu1, Haojie Lian1,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.023693
Abstract Geological hazard is an adverse geological condition that can cause loss of life and property. Accurate prediction
and analysis of geological hazards is an important and challenging task. In the past decade, there has been a great
expansion of geohazard detection data and advancement in data-driven simulation techniques. In particular, great
efforts have been made in applying deep learning to predict geohazards. To understand the recent progress in
this field, this paper provides an overview of the commonly used data sources and deep neural networks in the
prediction of a variety of geological hazards. More >
Open Access
ARTICLE
Hao Cui, Yanling Guo*, Yaning Xiao, Yangwei Wang*, Jian Li, Yapeng Zhang, Haoyu Zhang
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.026019
（This article belongs to this Special Issue: Bio-inspired Computer Modelling: Theories and Applications in Engineering and Sciences)
Abstract Harris Hawks Optimization (HHO) is a novel meta-heuristic algorithm that imitates the predation characteristics
of Harris Hawk and combines Lévy flight to solve complex multidimensional problems. Nevertheless, the basic
HHO algorithm still has certain limitations, including the tendency to fall into the local optima and poor
convergence accuracy. Coot Bird Optimization (CBO) is another new swarm-based optimization algorithm. CBO
originates from the regular and irregular motion of a bird called Coot on the water’s surface. Although the
framework of CBO is slightly complicated, it has outstanding exploration potential and excellent capability to
avoid falling into local optimal solutions. This paper… More >
Open Access
ARTICLE
Ning Hu1, Ling Liu1, Xin Liu3, Kaijun Wu2, Yue Zhao2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.026939
（This article belongs to this Special Issue: Emerging Trends on Blockchain: Architecture and Dapp Ecosystem)
Abstract With the widespread application of cloud computing and network virtualization technologies, more and more
enterprise applications are directly deployed in the cloud. However, the traditional TCP/IP network transmission
model does not fully consider the information security issues caused by the uncontrollable internet environment.
Network security communication solutions represented by encrypted virtual private networks (VPN) are facing
multiple security threats. In fact, during the communication process, the user application needs to protect not
only the content of the communication but also the behavior of the communication, such as the communication
relationship, the communication protocol, and so on. Inspired by blockchain and… More >
Open Access
ARTICLE
Zaihe Cheng1, Yuwen Tao2, Xiaoqing Gu3, Yizhang Jiang2, Pengjiang Qian2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027708
Abstract Through semi-supervised learning and knowledge inheritance, a novel Takagi-Sugeno-Kang (TSK) fuzzy system
framework is proposed for epilepsy data classification in this study. The new method is based on the maximum
mean discrepancy (MMD) method and TSK fuzzy system, as a basic model for the classification of epilepsy data.
First, for medical data, the interpretability of TSK fuzzy systems can ensure that the prediction results are traceable
and safe. Second, in view of the deviation in the data distribution between the real source domain and the target
domain, MMD is used to measure the distance between dierent data distributions. The objective… More >
Open Access
ARTICLE
Zeyuan Zhou, Ming Yu, Xinfeng Wang*, Zaixing Huang
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027384
（This article belongs to this Special Issue: Peridynamics and its Current Progress)
Abstract How to simulate fracture mode and crack propagation path in a plate with multiple cracks is an attractive but
dicult issue in fracture mechanics. Peridynamics is a recently developed nonlocal continuum formulation that
can spontaneously predict the crack nucleation, branch and propagation in materials and structures through a
meshfree discrete technique. In this paper, the peridynamic motion equation with boundary traction is improved
by simplifying the boundary transfer functions. We calculate the critical cracking load and the fracture angles of
the plate with multiple cracks under uniaxial tension. The results are consistent with those predicted by classical
fracture mechanics. The… More >
Open Access
ARTICLE
Pavel Trojovský*, Mohammad Dehghani
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028314
（This article belongs to this Special Issue: Computational Intelligent Systems for Solving Complex Engineering Problems: Principles and Applications)
Abstract This paper introduces a new metaheuristic algorithm called Migration Algorithm (MA), which is helpful in solving
optimization problems. The fundamental inspiration of MA is the process of human migration, which aims to
improve job, educational, economic, and living conditions, and so on. The mathematical modeling of the proposed
MA is presented in two phases to empower the proposed approach in exploration and exploitation during the search
process. In the exploration phase, the algorithm population is updated based on the simulation of choosing the
migration destination among the available options. In the exploitation phase, the algorithm population is updated
based on… More >
Open Access
ARTICLE
Yuyan Luo1,2, Xiaoxu Zhang1,*, Tao Tong1, Yong Qin3,*, Zheng Yang1
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.025413
（This article belongs to this Special Issue: Linguistic Approaches for Multiple Criteria Decision Making and Applications)
Abstract Graduate education is the main way to train high-level innovative talents, the basic layout to cope with the
global talent competition, and the important cornerstone for implementing the innovation-driven development
strategy and building an innovation-driven country. Therefore, graduate education is of great remarkably to the
development of national education. As an important manifestation of graduate education, the quality of a graduate
thesis should receive more attention. It is conducive to promoting the quality of graduates by supervising and
examining the quality of the graduate thesis. For this purpose, this work is based on text mining, expert interviews,
and questionnaire surveys… More >
Open Access
REVIEW
Zipu Yan1,2, Honghua Dai1,2,*, Qisi Wang1,2, Satya N. Atluri3
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028198
Abstract The harmonic balance (HB) method is one of the most commonly used methods for solving periodic solutions of
both weakly and strongly nonlinear dynamical systems. However, it is confined to low-order approximations due
to complex symbolic operations. Many variants have been developed to improve the HB method, among which the
time domain HB-like methods are regarded as crucial improvements because of their fast computation and simple
derivation. So far, there are two problems remaining to be addressed. i) A dozen of different versions of HB-like
methods, in frequency domain or time domain or in hybrid, have been developed; unfortunately, misclassification… More >
Open Access
REVIEW
Yanjun Yan, Kai Chen*, Hang Geng, Wenqian Fan, Xinrui Zhou
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027252
Abstract With increasing global concerns about clean energy in smart grids, the detection of power quality disturbances
(PQDs) caused by energy instability is becoming more and more prominent. It is well acknowledged that the PQD
effects on power grid equipment are destructive and hazardous, which causes irreversible damage to underlying
electrical/electronic equipment of the concerned intelligent grids. In order to ensure safe and reliable equipment
implementation, appropriate PQD detection technologies must be adopted to avoid such adverse effects. This paper
summarizes the newly proposed and traditional PQD detection techniques in order to give a quick start to new
researchers in the… More >
Open Access
ARTICLE
Maha Noorwali1, Mohammed Shehu Shagari2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028239
（This article belongs to this Special Issue: Computational Aspects of Nonlinear Operator and Fixed Point Theory with Applications)
Abstract The real world is filled with uncertainty, vagueness, and imprecision. The concepts we meet in everyday life
are vague rather than precise. In real-world situations, if a model requires that conclusions drawn from it have
some bearings on reality, then two major problems immediately arise, viz. real situations are not usually crisp
and deterministic; complete descriptions of real systems often require more comprehensive data than human
beings could recognize simultaneously, process and understand. Conventional mathematical tools which require
all inferences to be exact, are not always efficient to handle imprecisions in a wide variety of practical situations.
Following the latter… More >
Open Access
ARTICLE
Mohammed M. Ali Al-Shamiri1,2, Ghous Ali3,*, Muhammad Zain Ul Abidin3, Arooj Adeel3
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027844
（This article belongs to this Special Issue: Decision making Modeling, Methods and Applications of Advanced Fuzzy Theory in Engineering and Science)
Abstract Spherical fuzzy soft expert set (SFSES) theory blends the perks of spherical fuzzy sets and group decision-making
into a unified approach. It allows solutions to highly complicated uncertainties and ambiguities under the unbiased
supervision and group decision-making of multiple experts. However, SFSES theory has some deficiencies such
as the inability to interpret and portray the bipolarity of decision-parameters. This work highlights and overcomes
these limitations by introducing the novel spherical fuzzy bipolar soft expert sets (SFBSESs) as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets (BSESs). Followed by the development of certain
set-theoretic operations and… More >
Open Access
EDITORIAL
Yudong Zhang1,*, Huiling Chen2
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.029710
（This article belongs to this Special Issue: Bio-inspired Optimization in Engineering and Sciences)
Abstract This article has no abstract. More >
Open Access
ARTICLE
Hang Deng, Jimin Ye*, Wei Li*, Dongmei Huang
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028334
（This article belongs to this Special Issue: Vibration Control and Utilization)
Abstract In this paper, the response properties of galloping energy harvesters under bounded random parameter excitation
are studied theoretically. The first-order approximate solution of the galloping energy harvester is derived by
applying the multi-scales method. The expression for the largest Lyapunov exponent that determines the trivial
solution is derived, and the corresponding simulation diagrams, including the largest Lyapunov exponent diagrams
and time domain diagrams, verify our results. Then the steady-state response moments of the nontrivial solution
are studied using the moment method, and the analytical expressions for the first-order and second-order moments
of the voltage amplitude are obtained, respectively. The corresponding… More >
Open Access
ARTICLE
Xinzong Wang1, Xiaofang Kang1,2,*, Qingguan Lei1
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.027745
（This article belongs to this Special Issue: Vibration Control and Utilization)
Abstract The chaotic motion behavior of the rectangular conductive thin plate that is simply supported on four sides by
airflow and mechanical external excitation in a magnetic field is studied. According to Kirchhoff ’s thin plate theory,
considering geometric nonlinearity and using the principle of virtual work, the nonlinear motion partial differential
equation of the rectangular conductive thin plate is deduced. Using the separate variable method and Galerkin’s
method, the system motion partial differential equation is converted into the general equation of the Duffing
equation; the Hamilton system is introduced, and the Melnikov function is used to analyze the Hamilton system,… More >
Open Access
REVIEW
Loc Vu-Quoc1,*, Alexander Humer2
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2023.028130
Abstract Three recent breakthroughs due to AI in arts and science serve as motivation: An award winning digital image,
protein folding, fast matrix multiplication. Many recent developments in artificial neural networks, particularly
deep learning (DL), applied and relevant to computational mechanics (solid, fluids, finite-element technology)
are reviewed in detail. Both hybrid and pure machine learning (ML) methods are discussed. Hybrid methods
combine traditional PDE discretizations with ML methods either (1) to help model complex nonlinear constitutive relations, (2) to nonlinearly reduce the model order for efficient simulation (turbulence), or (3) to accelerate
the simulation by predicting certain components in the traditional… More >
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