Open Access
REVIEW
Qixing Zhang1,2, Bing Hou1,2,*, Huiwen Pang1,2, Shan Liu1,2, Yue Zeng1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 471-507, 2022, DOI:10.32604/cmes.2022.020831
Abstract China began to build its national shale gas demonstration area in 2012. The central exploration, drilling, and
development technologies for medium and shallow marine shale reservoirs with less than 3,500 m of buried depth
in Changning-Weiyuan, Zhaotong, and other regions had matured. In this study, we macroscopically investigated
the development history of shale gas in the United States and China and compared the physical and mechanical
conditions of deep and shallow reservoirs. The comparative results revealed that the main reasons for the order-ofmagnitude difference between China’s annual shale gas output and the United States could be attributed to three
aspects:… More >
Open Access
REVIEW
Mehdi Hosseinzadeh1, Atefeh Hemmati2, Amir Masoud Rahmani3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 509-556, 2022, DOI:10.32604/cmes.2022.021094
Abstract There are changes in the development of wireless technology systems every decade. 6G (sixth generation) wireless
networks improve on previous generations by increasing dependability, accelerating networks, increasing available
bandwidth, decreasing latency, and increasing data transmission speed to standardize communication signals. The
purpose of this article is to comprehend the current directions in 6G studies and their relationship to the Internet of
Things (IoT). Also, this paper discusses the impacts of 6G on IoT, critical requirements and trends for 6G-enabled
IoT, new service classes of 6G and IoT technologies, and current 6G-enabled IoT studies selected by the systematic
literature review (SLR)… More >
Open Access
ARTICLE
Masayuki Honda1, Kenichi Tatsumi2,*, Masaki Nakagawa3
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 557-577, 2022, DOI:10.32604/cmes.2022.020623
Abstract A model to predict photosynthetic carbon assimilation rate (A) with high accuracy is important for forecasting
crop yield and productivity. Long short-term memory (LSTM), a neural network suitable for time-series data,
enables prediction with high accuracy but requires mesophyll variables. In addition, for practical use, it is desirable
to have a technique that can predict A from easily available information. In this study, we propose a BLSTMaugmented LSTM (BALSTM) model, which utilizes bi-directional LSTM (BLSTM) to indirectly reproduce the
mesophyll variables required for LSTM. The most significant feature of the proposed model is that its hybrid
architecture uses only three… More >
Open Access
ARTICLE
Tomás Sureda Riera1,*, Juan Ramón Bermejo Higuera2, Javier Bermejo Higuera2, Juan Antonio Sicilia Montalvo2, José Javier Martínez Herráiz1
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 579-599, 2022, DOI:10.32604/cmes.2022.020976
Abstract Web applications represent one of the principal vehicles by which attackers gain access to an organization’s network
or resources. Thus, different approaches to protect web applications have been proposed to date. Of them, the two
major approaches areWeb Application Firewalls (WAF) and Runtime Application Self Protection (RASP). It is, thus,
essential to understand the differences and relative effectiveness of both these approaches for effective decisionmaking regarding the security of web applications. Here we present a comparative study between WAF and RASP
simulated settings, with the aim to compare their effectiveness and efficiency against different categories of attacks.
For this, we… More >
Open Access
ARTICLE
João Pedro Ceniz, Rodrigo de Sá Martins, Marco Antonio Luersen*, Tiago Cousseau
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 601-618, 2022, DOI:10.32604/cmes.2022.021011
Abstract Ore conveyor belt rollers operate in harsh environments, making them prone to premature failure. Their service lives are highly dependent on the stress field and bearing misalignment angle, for which limit values are defined in a standard. In this work, an optimization methodology using metamodels based on radial basis functions is implemented to reduce the mass of two models of rollers. From a structural point of view, one of the rollers is made completely of metal, while the other also has some components made of polymeric material. The objective of this study is to develop and apply a parametric structural… More >
Open Access
ARTICLE
Chien-Wen Lin1, Jen-Cheng Wang2, Bo-Yan Zhong3, Joe-Air Jiang4,5, Ya-Fen Wu6, Shao-Wei Leu1, Tzer-En Nee3,7,*
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 619-638, 2022, DOI:10.32604/cmes.2022.021324
Abstract The invariant metrics of the effects of park size and distance to public transportation on housing value volatilities in Boston, Milwaukee, Taipei and Tokyo are investigated. They reveal a Cobb-Douglas-like behavior. The scale-invariant exponents corresponding to the percentage of a green area (a) are 7.4, 8.41, 14.1 and 15.5 for Boston, Milwaukee, Taipei and Tokyo, respectively, while the corresponding direct distances to the nearest metro station (d) are −5, −5.88, −10 and −10, for Boston, Milwaukee, Taipei and Tokyo, respectively. The multiphysics-based analysis provides a powerful approach for the symmetry characterization of market engineering. The scaling exponent ratio between park… More >
Open Access
ARTICLE
Fatema Nafa1,*, Amal Babour2, Austin Melton3
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 639-652, 2022, DOI:10.32604/cmes.2022.020084
（This article belongs to this Special Issue: Soft Computing Techniques in Materials Science and Engineering)
Abstract The importance of prerequisites for education has recently become a promising research direction. This work proposes a statistical model for measuring dependencies in learning resources between knowledge units. Instructors are
expected to present knowledge units in a semantically well-organized manner to facilitate students’ understanding
of the material. The proposed model reveals how inner concepts of a knowledge unit are dependent on each other
and on concepts not in the knowledge unit. To help understand the complexity of the inner concepts themselves,
WordNet is included as an external knowledge base in this model. The goal is to develop a model that… More >
Open Access
ARTICLE
Osman Zeki Okuyucu*
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 653-671, 2022, DOI:10.32604/cmes.2022.021081
（This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
Abstract In this study, we examine the possible relations between the Frenet planes of any given two curves in three
dimensional Lie groups with left invariant metrics. We explain these possible relations in nine cases and then
introduce the conditions that must be met to coincide with the planes of these curves in nine theorems. More >
Open Access
ARTICLE
Omar Said*
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 673-695, 2022, DOI:10.32604/cmes.2022.021160
（This article belongs to this Special Issue: Artificial Intelligence of Things (AIoT): Emerging Trends and Challenges)
Abstract In recent years, the Internet of Things (IoT) technology has been considered one of the most attractive fields for
researchers due to its aspirations and implications for society and life as a whole. The IoT environment contains
vast numbers of devices, equipment, and heterogeneous users who generate massive amounts of data. Furthermore,
things’ entry into and exit from IoT systems occur dynamically, changing the topology and content of IoT networks
very quickly. Therefore, managing IoT environments is among the most pressing challenges. This paper proposes
an adaptive and dynamic scheme for managing IoT environments is proposed. This management scheme depends… More >
Open Access
ARTICLE
Yaya Wang1, P. Veeresha2, D. G. Prakasha3, Haci Mehmet Baskonus4,*, Wei Gao5
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 697-717, 2022, DOI:10.32604/cmes.2022.021865
（This article belongs to this Special Issue: Advanced Numerical Methods for Fractional Differential Equations)
Abstract In this paper, the fractional natural decomposition method (FNDM) is employed to find the solution for the KunduEckhaus equation and coupled fractional differential equations describing the massive Thirring model. The massive
Thirring model consists of a system of two nonlinear complex differential equations, and it plays a dynamic role
in quantum field theory. The fractional derivative is considered in the Caputo sense, and the projected algorithm
is a graceful mixture of Adomian decomposition scheme with natural transform technique. In order to illustrate
and validate the efficiency of the future technique, we analyzed projected phenomena in terms of fractional order.
Moreover,… More >
Open Access
ARTICLE
Francesco Tornabene*, Matteo Viscoti, Rossana Dimitri
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 719-798, 2022, DOI:10.32604/cmes.2022.022210
（This article belongs to this Special Issue: Theoretical and Computational Modeling of Advanced Materials and Structures)
Abstract The article proposes an Equivalent Single Layer (ESL) formulation for the linear static analysis of arbitrarily-shaped
shell structures subjected to general surface loads and boundary conditions. A parametrization of the physical
domain is provided by employing a set of curvilinear principal coordinates. The generalized blending methodology
accounts for a distortion of the structure so that disparate geometries can be considered. Each layer of the stacking
sequence has an arbitrary orientation and is modelled as a generally anisotropic continuum. In addition, re-entrant
auxetic three-dimensional honeycomb cells with soft-core behaviour are considered in the model. The unknown
variables are described employing a… More >
Graphic Abstract
Open Access
ARTICLE
Zida Liu1, Danial Jahed Armaghani2,*, Pouyan Fakharian3, Diyuan Li4, Dmitrii Vladimirovich Ulrikh5, Natalia Nikolaevna Orekhova6, Khaled Mohamed Khedher7,8
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 799-824, 2022, DOI:10.32604/cmes.2022.021165
（This article belongs to this Special Issue: Soft Computing Techniques in Materials Science and Engineering)
Abstract The uniaxial compressive strength (UCS) of rock is an essential property of rock material in different relevant
applications, such as rock slope, tunnel construction, and foundation. It takes enormous time and effort to obtain
the UCS values directly in the laboratory. Accordingly, an indirect determination of UCS through conducting
several rock index tests that are easy and fast to carry out is of interest and importance. This study presents
powerful boosting trees evaluation framework, i.e., adaptive boosting machine, extreme gradient boosting machine
(XGBoost), and category gradient boosting machine, for estimating the UCS of sandstone. Schmidt hammer
rebound number, P-wave velocity,… More >
Open Access
ARTICLE
Hye Kyung Kim1,*, Dae Sik Lee2
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 825-842, 2022, DOI:10.32604/cmes.2022.022103
（This article belongs to this Special Issue: Algebra, Number Theory, Combinatorics and Their Applications: Mathematical Theory and Computational Modelling)
Abstract The generating functions of special numbers and polynomials have various applications in many fields as well
as mathematics and physics. In recent years, some mathematicians have studied degenerate version of them
and obtained many interesting results. With this in mind, in this paper, we introduce the degenerate r-Dowling
polynomials and numbers associated with the degenerate r-Whitney numbers of the second kind. We derive
many interesting properties and identities for them including generating functions, Dobinski-like formula, integral
representations, recurrence relations, differential equation and various explicit expressions. In addition, we explore
some expressions for them that can be derived from repeated applications… More >
Open Access
REVIEW
Nilkanth Mukund Deshpande1,2, Shilpa Gite6,7,*, Biswajeet Pradhan3,4,5, Mazen Ebraheem Assiri4
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 843-872, 2022, DOI:10.32604/cmes.2022.021225
（This article belongs to this Special Issue: AI-Driven Engineering Applications)
Abstract Machine learning (ML) has emerged as a critical enabling tool in the sciences and industry in recent years.
Today’s machine learning algorithms can achieve outstanding performance on an expanding variety of complex
tasks–thanks to advancements in technique, the availability of enormous databases, and improved computing
power. Deep learning models are at the forefront of this advancement. However, because of their nested nonlinear
structure, these strong models are termed as “black boxes,” as they provide no information about how they arrive
at their conclusions. Such a lack of transparencies may be unacceptable in many applications, such as the medical
domain. A… More >
Open Access
ARTICLE
Yang Zhang1, Liru Qiu2, Yongkai Zhu1, Long Wen1,*, Xiaoping Luo2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 873-894, 2022, DOI:10.32604/cmes.2022.022322
（This article belongs to this Special Issue: Computing Methods for Industrial Artificial Intelligence)
Abstract Pneumonia is part of the main diseases causing the death of children. It is generally diagnosed through chest X-ray images. With the development of Deep Learning (DL), the diagnosis of pneumonia based on DL has received extensive attention. However, due to the small difference between pneumonia and normal images, the performance of DL methods could be improved. This research proposes a new fine-grained Convolutional Neural Network (CNN) for children’s pneumonia diagnosis (FG-CPD). Firstly, the fine-grained CNN classification which can handle the slight difference in images is investigated. To obtain the raw images from the real-world chest X-ray data, the YOLOv4… More >
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