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  • Open AccessOpen Access

    REVIEW

    A Comparison of Shale Gas Fracturing Based on Deep and Shallow Shale Reservoirs in the United States and China

    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 >

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    824

  • Open AccessOpen Access

    REVIEW

    6G-Enabled Internet of Things: Vision, Techniques, and Open Issues

    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 >

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  • Open AccessOpen Access

    ARTICLE

    Prediction of Photosynthetic Carbon Assimilation Rate of Individual Rice Leaves under Changes in Light Environment Using BLSTM-Augmented LSTM

    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 >

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    585

  • Open AccessOpen Access

    ARTICLE

    Systematic Approach for Web Protection Runtime Tools’ Effectiveness Analysis

    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 >

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    635

  • Open AccessOpen Access

    ARTICLE

    Structural Optimization of Metal and Polymer Ore Conveyor Belt Rollers

    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 >

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    623

  • Open AccessOpen Access

    ARTICLE

    Continuous Symmetry Analysis of the Effects of City Infrastructures on Invariant Metrics for House Market Volatilities

    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 >

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    1211

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    637

  • Open AccessOpen Access

    ARTICLE

    Prerequisite Relations among Knowledge Units: A Case Study of Computer Science Domain

    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 >

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    1384

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    640

  • Open AccessOpen Access

    ARTICLE

    Frenet Curve Couples in Three Dimensional Lie Groups

    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 >

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  • Open AccessOpen Access

    ARTICLE

    A Dynamic Management Scheme for Internet of Things (IoT) Environments: Simulation and Performance Evaluation

    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 >

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    1228

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    528

  • Open AccessOpen Access

    ARTICLE

    Regarding Deeper Properties of the Fractional Order Kundu-Eckhaus Equation and Massive Thirring Model

    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 >

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    602

  • Open AccessOpen Access

    ARTICLE

    Static Analysis of Doubly-Curved Shell Structures of Smart Materials and Arbitrary Shape Subjected to General Loads Employing Higher Order Theories and Generalized Differential Quadrature Method

    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

    Static Analysis of Doubly-Curved Shell Structures of Smart Materials and Arbitrary Shape Subjected to General Loads Employing Higher Order Theories and Generalized Differential Quadrature Method

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    550

  • Open AccessOpen Access

    ARTICLE

    Rock Strength Estimation Using Several Tree-Based ML Techniques

    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 >

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  • Open AccessOpen Access

    ARTICLE

    Some Properties of Degenerate r-Dowling Polynomials and Numbers of the Second Kind

    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 >

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    626

  • Open AccessOpen Access

    REVIEW

    Explainable Artificial Intelligence–A New Step towards the Trust in Medical Diagnosis with AI Frameworks: A 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 >

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    1716

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    688

  • Open AccessOpen Access

    ARTICLE

    A New Childhood Pneumonia Diagnosis Method Based on Fine-Grained Convolutional Neural Network

    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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