Liufeng Du^1,*, Shaoru Shang¹, Linghua Zhang², Chong Li¹, Jianing Yang³, Xiyan Tian¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1749-1767, 2024, DOI:10.32604/cmes.2023.030144 - 17 November 2023

Abstract Due to the fine-grained communication scenarios characterization and stability, Wi-Fi channel state information (CSI) has been increasingly applied to indoor sensing tasks recently. Although spatial variations are explicitly reflected in CSI measurements, the representation differences caused by small contextual changes are easily submerged in the fluctuations of multipath effects, especially in device-free Wi-Fi sensing. Most existing data solutions cannot fully exploit the temporal, spatial, and frequency information carried by CSI, which results in insufficient sensing resolution for indoor scenario changes. As a result, the well-liked machine learning (ML)-based CSI sensing models still struggling with stable More >

Muhammad Shoaib Arif^1,2,*, Kamaleldin Abodayeh¹, Yasir Nawaz²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1405-1425, 2024, DOI:10.32604/cmes.2023.028946 - 17 November 2023

Abstract This work aimed to construct an epidemic model with fuzzy parameters. Since the classical epidemic model does not elaborate on the successful interaction of susceptible and infective people, the constructed fuzzy epidemic model discusses the more detailed versions of the interactions between infective and susceptible people. The next-generation matrix approach is employed to find the reproduction number of a deterministic model. The sensitivity analysis and local stability analysis of the system are also provided. For solving the fuzzy epidemic model, a numerical scheme is constructed which consists of three time levels. The numerical scheme has More >

Dhananjay P. Mehendale^1,*, Madhav R. Modak²

Journal of Quantum Computing, Vol.5, pp. 15-24, 2023, DOI:10.32604/jqc.2023.043370 - 05 December 2023

Abstract A multi-qubit pure quantum state is called separable when it can be factored as the tensor product of 1-qubit pure quantum states. Factorizing a general multi-qubit pure quantum state into the tensor product of its factors (pure states containing a smaller number of qubits) can be a challenging task, especially for highly entangled states. A new criterion based on the proportionality of the rows of certain associated matrices for the existence of certain factorization and a factorization algorithm that follows from this criterion for systematically extracting all the factors is developed in this paper. 3-qubit More >

Ye Fu¹, Liwen Deng^1,*, Jinbo Hu^2,3,*, Ti Li³, Shanshan Chang²

Journal of Renewable Materials, Vol.11, No.12, pp. 4025-4038, 2023, DOI:10.32604/jrm.2023.028454 - 10 November 2023

Abstract In the study, it is proposed that a coordinate-parametric matrix model is performed to a square-conjoint pattern of cross woven (SCPCW) in the bamboo mat. The patterns of SCPCW are firstly detected according to the perspective of configuration, which is divided into the basic-monomer shape and the basic combination shape. Secondly, the compositions of design patterns in SCPCW are analyzed to attain the trend of curve shape. Based on the coordinate-parametric matrix model, the specimens of SCPCW are subsequently accomplished to elaborate the woven logic of bamboo mats. The digital innovation of SCPCW, defined by More > Graphic Abstract

Fayaz Muhammad¹, Jahangir Khan¹, Asad Ullah¹, Fasee Ullah¹, Razaullah Khan², Inayat Khan², Mohammed ElAffendi³, Gauhar Ali^3,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 647-664, 2023, DOI:10.32604/cmc.2023.038748 - 31 October 2023

Abstract IIF (Indirect Immune Florescence) has gained much attention recently due to its importance in medical sciences. The primary purpose of this work is to highlight a step-by-step methodology for detecting autoimmune diseases. The use of IIF for detecting autoimmune diseases is widespread in different medical areas. Nearly 80 different types of autoimmune diseases have existed in various body parts. The IIF has been used for image classification in both ways, manually and by using the Computer-Aided Detection (CAD) system. The data scientists conducted various research works using an automatic CAD system with low accuracy. The… More >

Louis F. Marie^*, Karina Sałek, Tadhg S. O’Donovan

Energy Engineering, Vol.120, No.10, pp. 2193-2209, 2023, DOI:10.32604/ee.2023.043075 - 28 September 2023

Abstract Composite thermochemical energy storage (TCES) represents an exciting field of thermal energy storage which could address the issue of seasonal variance in renewable energy supply. However, there are open questions about their performance and the root cause of some observed phenomena. Some researchers have observed the breakdown of particles in their production phase, and in their use. This study seeks to investigate the underlying cause of this breakdown. SEM and EDX analysis have been conducted on MgCl₂ impregnated 13X zeolite composites of differing diameters, as well as LiX zeolite. This was done in order to study… More > Graphic Abstract

Zhengmao Yang^1,*, Junjie Yang², Yang Chen³, Fulei Jing⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09229

Abstract Woven ceramic matrix composites (CMCs), exhibiting excellent thermomechanical properties at high temperatures, are promising as alternative materials to the conventional nickel-based superalloys in the hot section components of aero-engines. Therefore, understanding and predicting the lifetime of CMCs is critical. Fatigue prediction of woven CMCs currently involves long-term and costly testing. A feasible alternative is to use predictive modelling based on a deep understanding of the damage mechanisms. Therefore, this study develops a multiscale analysis modelling method for predicting the fatigue life of CMC materials at high temperature by investigating the thermomechanical fatigue damage evolution. To… More >

Haiming Zhang^1,2,*, Shilin Zhao^1,2, Zhenshan Cui^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.08884

Abstract Particle-reinforced aluminum matrix composites (PRAMCs) have great potential for application in aerospace, automobile, defense, and electronics due to their high specific strength and stiffness and good resistance to wear and corrosion. Achieving a superior trade-off between the strength and ductility of PRAMCs necessitates an elaborative control of the microstructures, like the size and distribution of particles, as well as grain size, morphology, and texture of the matrix. The multiscale interaction between the particles and the matrix’s microstructure is insufficiently understood due to the lagging of high-resolved in-situ characterization. This work proposes a nonlocal physically based… More >

Fei Li¹, Haci Mehmet Baskonus^2,*, S. Kumbinarasaiah³, G. Manohara³, Wei Gao⁴, Esin Ilhan⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2381-2408, 2023, DOI:10.32604/cmes.2023.028069 - 03 August 2023

Abstract This article considers three types of biological systems: the dengue fever disease model, the COVID-19 virus model, and the transmission of Tuberculosis model. The new technique of creating the integration matrix for the Bernoulli wavelets is applied. Also, the novel method proposed in this paper is called the Bernoulli wavelet collocation scheme (BWCM). All three models are in the form system of coupled ordinary differential equations without an exact solution. These systems are converted into a system of algebraic equations using the Bernoulli wavelet collocation scheme. The numerical wave distributions of these governing models are More >

Loc Vu-Quoc^1,*, Alexander Humer²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1069-1343, 2023, DOI:10.32604/cmes.2023.028130 - 26 June 2023

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… More >