Nguyen Long Giang¹, Tran Thanh Dai², Le Hoang Son³, Tran Thi Ngan⁴, Nguyen Nhu Son¹, Cu Nguyen Giap^5,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3097-3124, 2024, DOI:10.32604/cmc.2024.057383 - 18 November 2024

Abstract Attribute reduction through the combined approach of Rough Sets (RS) and algebraic topology is an open research topic with significant potential for applications. Several research works have introduced a strong relationship between RS and topology spaces for the attribute reduction problem. However, the mentioned recent methods followed a strategy to construct a new measure for attribute selection. Meanwhile, the strategy for searching for the reduct is still to select each attribute and gradually add it to the reduct. Consequently, those methods tended to be inefficient for high-dimensional datasets. To overcome these challenges, we use the… More >

Kunrong Shen^*, Wanchun Jin, Jin Wang

Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1361-1379, 2024, DOI:10.32604/fhmt.2024.057372 - 30 October 2024

Abstract The modified Siemens method is the dominant process for the production of polysilicon, yet it is characterised by high energy consumption. Two models of laboratory-grade Siemens reduction furnace and 12 pairs of rods industrial-grade Siemens chemical vapor deposition (CVD) reduction furnace were established, and the effects of factors such as the diameter of silicon rods, the surface temperature of silicon rods, the air inlet velocity and temperature on the heat transfer process inside the reduction furnace were investigated by numerical simulation. The results show that the convective and radiant heat losses in the furnace increased… More >

Xin Luan^1,*, Guoqing Su¹, Hailong Chen¹, Min Kuang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.11, pp. 2459-2473, 2024, DOI:10.32604/fdmp.2024.054621 - 28 October 2024

Abstract The proper selection of a relevant mixer generally requires an effective assessment of several models against the application requirements. This is a complex task, as traditional evaluation methods generally focus only on a single aspect of performance, such as pressure loss, mixing characteristics, or heat transfer. This study assesses a urea-based selective catalytic reduction (SCR) system installed on a ship, where the installation space is limited and the distance between the urea aqueous solution injection position and the reactor is low; therefore, the static mixer installed in this pipeline has special performance requirements. In particular,… More >

Xinyi Guan¹, Shaoqiang Tang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.010869

Abstract Inheriting a convergence difficulty explained by the Kolmogorov N-width [1], the advection-diffusion equation is not effectively solved by the Proper Generalized Decomposition [2] (PGD) method. In this paper, we propose a new strategy: Proper Generalized Decomposition with Coordinate Transformation (CT-PGD). Converting the mixed hyperbolic-parabolic equation to a parabolic one, it resumes the efficiency of convergence for advection-dominant problems. Combining PGD with CT-PGD, we solve advection-diffusion equation by much fewer degrees of freedom, hence improve the efficiency. The advection-dominant regime and diffusion-dominant regime are quantitatively classified by a threshold, computed numerically. Moreover, we find that appropriate More >

Aline Ferreira Knihs, Larissa Klen Aragão, Miguel Angelo Granato, Andrea Cristiane Krause Bierhalz^*, Rita de Cassia Siqueira Curto Valle

Journal of Renewable Materials, Vol.12, No.9, pp. 1557-1571, 2024, DOI:10.32604/jrm.2024.052963 - 25 September 2024

Abstract The textile industry generates large volumes of waste throughout its production process. Most of this waste is colored, therefore, discoloration is an important step toward recycling and reusing this waste. This study focused on the chemical reductive discoloration of textile waste composed of cotton dyed with reactive dye. The experimental design demonstrated the significant influence of the concentration of reducing agent and time of reaction on the degree of whiteness of the cotton fibers. The concentration of the alkaline agent was not significant in the process. The optimization of the reaction conditions lead to Berger… More > Graphic Abstract

Mahmoud E. Farfoura^1,*, Ahmad Alkhatib¹, Deema Mohammed Alsekait^2,*, Mohammad Alshinwan^3,7, Sahar A. El-Rahman⁴, Didi Rosiyadi⁵, Diaa Salama AbdElminaam^6,7

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4833-4857, 2024, DOI:10.32604/cmc.2024.054849 - 12 September 2024

Abstract The article describes a new method for malware classification, based on a Machine Learning (ML) model architecture specifically designed for malware detection, enabling real-time and accurate malware identification. Using an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique (IFDRT), the authors have significantly reduced the feature space while retaining critical information necessary for malware classification. This technique optimizes the model’s performance and reduces computational requirements. The proposed method is demonstrated by applying it to the BODMAS malware dataset, which contains 57,293 malware samples and 77,142 benign samples, each with a 2381-feature… More >

Kaveh Heidary^1,*, Venkata Atluri¹, John Bland²

Journal of Cyber Security, Vol.6, pp. 69-87, 2024, DOI:10.32604/jcs.2024.051196 - 28 August 2024

Abstract This paper investigates the impact of reducing feature-vector dimensionality on the performance of machine learning (ML) models. Dimensionality reduction and feature selection techniques can improve computational efficiency, accuracy, robustness, transparency, and interpretability of ML models. In high-dimensional data, where features outnumber training instances, redundant or irrelevant features introduce noise, hindering model generalization and accuracy. This study explores the effects of dimensionality reduction methods on binary classifier performance using network traffic data for cybersecurity applications. The paper examines how dimensionality reduction techniques influence classifier operation and performance across diverse performance metrics for seven ML models. Four… More >

Mesut Ulu^1,*, Yusuf Sait Türkan², Kenan Mengüç³, Ersin Namlı², Tarık Küçükdeniz²

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2259-2281, 2024, DOI:10.32604/cmc.2024.052323 - 15 August 2024

Abstract Today, urban traffic, growing populations, and dense transportation networks are contributing to an increase in traffic incidents. These incidents include traffic accidents, vehicle breakdowns, fires, and traffic disputes, resulting in long waiting times, high carbon emissions, and other undesirable situations. It is vital to estimate incident response times quickly and accurately after traffic incidents occur for the success of incident-related planning and response activities. This study presents a model for forecasting the traffic incident duration of traffic events with high precision. The proposed model goes through a 4-stage process using various features to predict the… More >

Yousef Ibrahim Daradkeh^1,*, Volodymyr Gorokhovatskyi², Iryna Tvoroshenko^2,*, Medien Zeghid^1,3

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3085-3106, 2024, DOI:10.32604/cmc.2024.051709 - 15 August 2024

Abstract The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint descriptors. The main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification efficiency. The class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric transformations. It is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content criterion.… More >

Maan Habib^1,*, Ahed Habib², Mohammad Abboud³

Revue Internationale de Géomatique, Vol.33, pp. 247-271, 2024, DOI:10.32604/rig.2024.053857 - 07 August 2024

Abstract Digital elevation models (DEMs) are essential tools in environmental science, particularly for hazard assessments and landscape analyses. However, their application across multiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management. This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards, namely floods, landslides, and coastal erosion. In this regard, it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced More >