Hung-Hsiang Wang¹, Chih-Ping Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 685-709, 2024, DOI:10.32604/cmes.2024.047630

Abstract This paper presents a new method of using a convolutional neural network (CNN) in machine learning to identify brand consistency by product appearance variation. In Experiment 1, we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions. Results show that it is a challenge to distinguish periods for the subtle evolution of the mouse devices with such traditional methods as time series analysis and principal component analysis (PCA). In Experiment 2, we applied deep learning to predict the extent… More >

Chun Mao¹, Ji He^1,*, Xuefeng Wen¹, Yangzhou Xiang², Jihong Feng¹, Yingge Shu¹

Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 487-502, 2024, DOI:10.32604/phyton.2024.048246

Abstract The contents of carbon (C), nitrogen (N), and phosphorus (P) in soil-microorganisms-plant significantly affect tea quality by altering the main quality components of tea, such as tea polyphenols, amino acids, and caffeine. However, few studies have quantified the effects of these factors on the main quality components of tea. The study aimed to explore the interactions of C, N, and P in soil-microorganisms-plants and the effects of these factors on the main quality components of tea by using the path analysis method. The results indicated that (1) The contents of C, N, and P in soil, microorganisms, and tea plants… More >

Shuai Chen¹, Yinwei Ma², Zhongshu Wang², Zongmei Xu³, Song Zhang¹, Jianle Li¹, Hao Xu¹, Zhanjun Wu^1,*

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 125-141, 2024, DOI:10.32604/sdhm.2024.042594

Abstract The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life. To this end, distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages, such as lightweight and ease of embedding. However, identifying the precise location of damage from the optical fiber signals remains a critical challenge. In this paper, a novel approach which namely Modified Sliding Window Principal Component Analysis (MSWPCA) was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors. The proposed method is able to extract signal… More > Graphic Abstract

Yizhao Wang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3029-3045, 2024, DOI:10.32604/cmes.2024.046270

Abstract Near-fault impulsive ground-shaking is highly destructive to engineering structures, so its accurate identification ground-shaking is a top priority in the engineering field. However, due to the lack of a comprehensive consideration of the ground-shaking characteristics in traditional methods, the generalization and accuracy of the identification process are low. To address these problems, an impulsive ground-shaking identification method combined with deep learning named PCA-LSTM is proposed. Firstly, ground-shaking characteristics were analyzed and ground-shaking the data was annotated using Baker’s method. Secondly, the Principal Component Analysis (PCA) method was used to extract the most relevant features related to impulsive ground-shaking. Thirdly, a… More >

Lifeng Liu¹, Menghe Shi², Jianhui Wang³, Wendong Wang^2,*, Yuliang Su², Xinyu Zhuang²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 595-607, 2024, DOI:10.32604/fdmp.2023.041962

Abstract Ultra-low permeability reservoirs are characterized by small pore throats and poor physical properties, which are at the root of well-known problems related to injection and production. In this study, a gas injection flooding approach is analyzed in the framework of numerical simulations. In particular, the sequence and timing of fracture channeling and the related impact on production are considered for horizontal wells with different fracture morphologies. Useful data and information are provided about the regulation of gas channeling and possible strategies to delay gas channeling and optimize the gas injection volume and fracture parameters. It is shown that in order… More >

Zakarya Abdullah Alzamil^*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3139-3161, 2023, DOI:10.32604/cmc.2023.042711

Abstract Measuring software quality requires software engineers to understand the system’s quality attributes and their measurements. The quality attribute is a qualitative property; however, the quantitative feature is needed for software measurement, which is not considered during the development of most software systems. Many research studies have investigated different approaches for measuring software quality, but with no practical approaches to quantify and measure quality attributes. This paper proposes a software quality measurement model, based on a software interconnection model, to measure the quality of software components and the overall quality of the software system. Unlike most of the existing approaches, the… More >

Mohammad Mazyad Hazzazi¹, Muhammad Sajjad², Zaid Bassfar³, Tariq Shah^2,*, Ashwag Albakri⁴

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3659-3675, 2023, DOI:10.32604/cmc.2023.039013

Abstract In block ciphers, the nonlinear components, also known as substitution boxes (S-boxes), are used with the purpose to induce confusion in cryptosystems. For the last decade, most of the work on designing S-boxes over the points of elliptic curves, chaotic maps, and Gaussian integers has been published. The main purpose of these studies is to hide data and improve the security levels of crypto algorithms. In this work, we design pair of nonlinear components of a block cipher over the residue class of Eisenstein integers (EI). The fascinating features of this structure provide S-boxes pair at a time by fixing… More >

Viraj S. Shirodkar^*

Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-8, 2016, DOI:10.5098/hmt.7.5

Abstract Urea-water solution droplet evaporation is modelled using multi-component droplet evaporation approach. The heat and mass transfer process of a multi-component droplet is implemented in the Langrangian framework through a custom code in ANSYS-Fluent R15. The evaporation process is defined by a convection-diffusion controlled model which includes the effect of Stefan flow. A rapid mixing model assumption is used for the droplet internal physics. The code is tested on a single multi-component droplet and the predicted evaporation rates at different ambient temperatures are compared with the experimental data in the literature. The approach is used to model the injection of urea-water… More >

Nazia Afrin^a, Yijin Mao^a, Yuwen Zhang^a,*, J. K. Chen^a, Robin Ritter^b, Alan Lampson^b, Jonathan Stohs^c

Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-8, 2016, DOI:10.5098/hmt.7.7

Abstract A three-dimensional numerical simulation is conducted for a complex process in a laser-material system, which involves heat and mass transfer in a compressible gaseous phase and chemical reaction during laser irradiation on a urethane paint coated on a stainless steel substrate. A finite volume method (FVM) with a co-located grid mesh that discretizes the entire computational domain is employed to simulate the heating process. The results show that when the top surface of the paint reaches a threshold temperature of 560 K, the polyurethane starts to decompose through chemical reaction. As a result, combustion products CO₂, H₂O and NO₂ are… More >

Yongzhi Min^1,2,*, Jiafeng Li³, Yaxing Li¹

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 941-962, 2023, DOI:10.32604/cmc.2023.041182

Abstract To guarantee the safety of railway operations, the swift detection of rail surface defects becomes imperative. Traditional methods of manual inspection and conventional nondestructive testing prove inefficient, especially when scaling to extensive railway networks. Moreover, the unpredictable and intricate nature of defect edge shapes further complicates detection efforts. Addressing these challenges, this paper introduces an enhanced Unified Perceptual Parsing for Scene Understanding Network (UPerNet) tailored for rail surface defect detection. Notably, the Swin Transformer Tiny version (Swin-T) network, underpinned by the Transformer architecture, is employed for adept feature extraction. This approach capitalizes on the global information present in the image… More >