Ain Shams Engineering Journal最新文献_第4页

Unveiling solitons and traveling wave solutions with modulation instability analysis for extended (3+1)-dimensional seventh-order standard Ito and modified Ito equations 用调制不稳定性分析揭示扩展（3+1）维七阶标准Ito方程和修正Ito方程的孤子和行波解

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-16 DOI: 10.1016/j.asej.2025.103475

Noha M. Kamel , Hamdy M. Ahmed , Wafaa B. Rabie

{"title":"Unveiling solitons and traveling wave solutions with modulation instability analysis for extended (3+1)-dimensional seventh-order standard Ito and modified Ito equations","authors":"Noha M. Kamel , Hamdy M. Ahmed , Wafaa B. Rabie","doi":"10.1016/j.asej.2025.103475","DOIUrl":"10.1016/j.asej.2025.103475","url":null,"abstract":"<div><div>In this study, the extended (3+1)-dimensional seventh-order standard Ito and modified Ito equations are investigated. The study applied, for the first time, the modified Sardar sub-equation technique (MSSET) to the extended standard Ito equation and the extended modified Ito equation. Various types of solutions are achieved by MSSET for both types of the Ito equations. Among the obtained solutions are the bright, dark and singular soliton solutions as well as hyperbolic solutions, exponential solutions, rational solutions and singular periodic solutions. The MSSET, with robustness, direct calculations and low computational cost properties, succeeded to provide a variety of solution forms. In this work, novel solutions for extended seventh-order modified Ito equation are achieved that were not available in the literature before. Also, this work investigated the extended seventh-order standard Ito equation for the first time and provided novel solutions for it. The achieved solutions in this work were verified by direct substitution into the investigated Ito equations and proved to satisfy them. Also, the novelty of this work was the derivation of modulation instability analysis for the equations under study using linear stability analysis for the first time in the literature. For graphical representation, two-dimensional, three-dimensional graphics and contour plots of some achieved analytic solutions, for both of the investigated Ito equations, were provided with suitable values of parameters satisfying the limiting conditions.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103475"},"PeriodicalIF":6.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Empirical analysis of predicting heart disease using diverse datasets and classification procedures of machine learning 使用不同数据集和机器学习分类程序预测心脏病的实证分析

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-16 DOI: 10.1016/j.asej.2025.103470

Geetha Narasimhan, Akila Victor

{"title":"Empirical analysis of predicting heart disease using diverse datasets and classification procedures of machine learning","authors":"Geetha Narasimhan, Akila Victor","doi":"10.1016/j.asej.2025.103470","DOIUrl":"10.1016/j.asej.2025.103470","url":null,"abstract":"<div><div>Cardiovascular disease (CVD) poses a significant threat due to its complexity and fatality, necessitating early intervention. Fortunately, the rapidly evolving field of machine learning (ML) offers an array of algorithms for disease diagnosis and prediction. This research aims to develop and identify a model that assists radiologists in predicting heart disease, a two-phased approach. Phase 1: Feature Selection with SelectKBest: The first phase utilizes the SelectKBest method to select the most relevant features for prediction. This method combines individual feature rankings based on three statistical tests: chi-squared, mutual information, and F-statistic. The final selection is based on the overall rank obtained by each feature. Phase 2: Classification Algorithm Exploration: The second phase applies various classification algorithms, including Random Forest, k-nearest neighbors (KNN), decision tree (DT), support vector machine (SVM), Naïve Bayes (NB), Logistic Regression (LR), Random Forest Grid search, Gradient Boost, and Neural Network. The performance of these models is evaluated using three standard heart disease datasets: Cleveland, Faisalabad, and Framingham, retrieved from UCI and Kaggle. Each dataset undergoes pre-processing before applying the SelectKBest feature selection and all ML algorithms. Across all three datasets, Random Forest emerged as the champion, achieving accuracy rates of 90.16%, 90%, and 84%, respectively. Additionally, it demonstrated consistently lower classification errors compared to other algorithms. This research highlights the effectiveness of feature selection, particularly the SelectKBest filter-based method, in improving heart disease prediction accuracy using machine learning models like Random Forest. This paves the way for integrating such models into clinical settings, empowering radiologists with valuable decision-making tools for early CVD detection and intervention.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103470"},"PeriodicalIF":6.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On metric dimension of generalized subdivision prism graph 广义细分棱镜图的度量维数

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-16 DOI: 10.1016/j.asej.2025.103452

Sandeep Kumar, Sahil Sharma, Sunny Kumar Sharma, Vijay Kumar Bhat

{"title":"On metric dimension of generalized subdivision prism graph","authors":"Sandeep Kumar, Sahil Sharma, Sunny Kumar Sharma, Vijay Kumar Bhat","doi":"10.1016/j.asej.2025.103452","DOIUrl":"10.1016/j.asej.2025.103452","url":null,"abstract":"<div><div>A convex polytope is a type of polytope that is defined as a convex set in <em>n</em>-dimensional Euclidean space. A graph is a mathematical structure formed up of a collection of interconnections between items called edges and a set of objects called vertices. In general, a graph is represented as an ordered pair <span><math><mi>G</mi><mo>=</mo><mo>(</mo><mi>V</mi><mo>,</mo><mi>E</mi><mo>)</mo></math></span>, where <em>V</em> stands for the set of vertices and <em>E</em> for the set of edges which are defined as unordered pairings of vertices. If for each pair of different vertices <span><math><mi>x</mi><mo>,</mo><mi>y</mi><mo>∈</mo><mi>V</mi></math></span>, there exists a vertex <span><math><mi>w</mi><mo>∈</mo><mi>S</mi></math></span> such that the distance from <em>w</em> to <em>x</em> is not equal to the distance from <em>w</em> to <em>y</em>, then a set <span><math><mi>S</mi><mo>⊆</mo><mi>V</mi></math></span> is a resolving set. The minimum cardinality of the resolving set is known as the metric dimension of a graph <em>G</em>. The computation of metric dimension for any graph is an essential concept with applications in mathematics, computer science, geometry, chemical science, etc. Metric dimension involves the smallest set of points needed to uniquely identify all other points in a network. In this research article, we take a family of a convex polytope, viz. generalized subdivision prism graph <span><math><mi>J</mi><mo>(</mo><msub><mrow><mi>F</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>)</mo></math></span> and investigate its metric basis and metric dimension.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103452"},"PeriodicalIF":6.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the knowledge structure of building information modeling (BIM) adoption in construction scheduling: A bibliometric analysis from 2008 to 2024 建筑信息模型（BIM）在施工调度中的知识结构探讨：2008 - 2024年文献计量分析

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-15 DOI: 10.1016/j.asej.2025.103446

Kevin Torres , Omar Sánchez , Karen Castañeda , Mario Noguera , Daniela Carrasco-Beltrán , Sofía Vidal-Méndez , Natalia E. Lozano-Ramírez

{"title":"Exploring the knowledge structure of building information modeling (BIM) adoption in construction scheduling: A bibliometric analysis from 2008 to 2024","authors":"Kevin Torres , Omar Sánchez , Karen Castañeda , Mario Noguera , Daniela Carrasco-Beltrán , Sofía Vidal-Méndez , Natalia E. Lozano-Ramírez","doi":"10.1016/j.asej.2025.103446","DOIUrl":"10.1016/j.asej.2025.103446","url":null,"abstract":"<div><div>Effective construction schedule planning is essential for project success. Building Information Modeling (BIM) is a methodology with high potential to enhance planning processes and benefit construction management. Although extensive research has examined BIM’s application in schedule planning from various perspectives, a knowledge gap exists in studies that synthesize and analyze the knowledge structure in this area. Therefore, this study addresses this gap through a bibliometric analysis of 489 journal articles published from 2008 to 2024, utilizing performance metrics, science mapping, and trend analysis techniques. Based on centrality and density metrics, the science mapping reveals five key areas of the knowledge structure of BIM adoption in construction scheduling: BIM construction scheduling, advanced construction monitoring and data integration, supply chain management in sustainable and safe construction, project management and productivity, and earthworks and intelligent construction. Furthermore, trend analysis shows that the integration of BIM with artificial intelligence has been increasing due to its potential to optimize and improve construction planning. BIM enables enhanced project control and monitoring by integrating real-time data updates and visual simulations, supporting proactive decision-making during construction execution. The findings provide an overview of the knowledge field for professionals and researchers, offering information into the current state of BIM adoption in construction scheduling. It highlights current research trends and identifies gaps, suggesting directions for future studies to advance the field.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103446"},"PeriodicalIF":6.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fractional thermophotovoltaic with spacetime nonlocality model for a rotating semiconductor solid sphere 旋转半导体实心球的分式热光伏时空非定域模型

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-15 DOI: 10.1016/j.asej.2025.103461

Faisal Alsharif

{"title":"Fractional thermophotovoltaic with spacetime nonlocality model for a rotating semiconductor solid sphere","authors":"Faisal Alsharif","doi":"10.1016/j.asej.2025.103461","DOIUrl":"10.1016/j.asej.2025.103461","url":null,"abstract":"<div><div>Spinning semiconductors are essential for advanced technologies such as thermoelectric devices, plasma processes for etching and deposition, and satellite navigation systems. However, their complex responses to heat, mechanical stress, and rotation remain inadequately captured by existing models, motivating this research to develop a more accurate framework for understanding these materials’ behavior, particularly under dynamic conditions. This study introduces a novel mathematical model to analyze plasma interactions, heat flow, and elastic responses in a rotating semiconductor sphere, such as silicon, subjected to thermal shock with a traction-free surface. The model builds on the Green-Naghdi Type III framework by incorporating a relaxation factor and the Moore-Gibson-Thompson equation for improved heat conduction modeling. Additionally, it employs spacetime nonlocality to account for size-dependent and memory effects, and the Atangana-Baleanu fractional derivative to capture intricate dynamic behavior. By solving the model using the Laplace transform technique, the research reveals the impact of rotation speed, nonlocality, and fractional derivatives on temperature, displacement, stress, and charge carrier distribution. Key contributions include the development of an advanced model that surpasses traditional approaches, the demonstration of smoother thermal gradients, reduced deformation, and more uniform stress and charge distributions for enhanced thermal management and mechanical stability. These findings offer practical insights for designing reliable semiconductor devices in nanoelectronics, optoelectronics, and microelectromechanical systems, addressing critical gaps in current research and advancing semiconductor technology.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103461"},"PeriodicalIF":6.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A low-power, high accuracy digital design of batch normalized non-linear neuron models: Synthetic experiments and FPGA evaluation 批量归一化非线性神经元模型的低功耗、高精度数字化设计：综合实验与FPGA评估

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-15 DOI: 10.1016/j.asej.2025.103469

S. Kavitha , C. Kumar , Abdullah Alwabli

引用次数: 0

Effect of the CO2 curing on a certain recycled concrete with the mineral-added binary and ternary cementitious systems 掺矿二、三元胶凝体系CO2养护对再生混凝土的影响

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-15 DOI: 10.1016/j.asej.2025.103476

Cheng Wang, Jianjun Zhao, Yu Liu, Xiao Zhao, Xuejin Ying

{"title":"Effect of the CO2 curing on a certain recycled concrete with the mineral-added binary and ternary cementitious systems","authors":"Cheng Wang, Jianjun Zhao, Yu Liu, Xiao Zhao, Xuejin Ying","doi":"10.1016/j.asej.2025.103476","DOIUrl":"10.1016/j.asej.2025.103476","url":null,"abstract":"<div><div>Demolition waste and cement production account for 36 % of the total waste generated on earth and 8 % of the world’s CO<sub>2</sub> emissions, respectively, while considering that studies on CO<sub>2</sub> curing of recycled concrete (RC) containing ternary cementitious systems (fly ash (FA) and slag) are limited. In this paper, the effects of adding FA and slag as binary and ternary cementitious systems on the unit carbon sequestration, carbon sequestration rate, compressive strength and microstructure of RC under CO<sub>2</sub> curing were investigated. Finally, the overall benefit is evaluated by combining three indicators: compressive strength, CO<sub>2</sub> emission and cost. The results showed that the unit carbon sequestration of RC with binary cementitious systems peaked at 45 % mineral replacement, reaching 16.69 g/kg (FA + cement) and 14.46 g/kg (slag + cement), respectively, while compressive strength peaked at 30 % mineral replacement. At the same replacement rate, the unit carbon sequestration (17.56 g/kg) and compressive strength of ternary cementitious system RC were superior to those of binary systems when FA and slag were incorporated at ratios of 7.5 % and 37.5 %, respectively. From a microstructural perspective, after CO<sub>2</sub> curing, the addition of FA does not significantly affect the calcite diffraction peak intensity in RC, while the calcite diffraction peak in slag RC is significantly enhanced. In ternary cementitious system RC, the calcite diffraction peak no longer shows significant changes once the FA content reaches a certain level. In addition, the ternary cementitious system offers better overall benefits in terms of CO<sub>2</sub> emissions, cost, and compressive strength.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103476"},"PeriodicalIF":6.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting compressive and tensile strength of concrete with different sand types using machine learning 使用机器学习预测不同砂类型混凝土的抗压和抗拉强度

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-14 DOI: 10.1016/j.asej.2025.103474

Tarek Salem Abdennaji , Rupesh Kumar Tipu , Yahya Alassaf

{"title":"Predicting compressive and tensile strength of concrete with different sand types using machine learning","authors":"Tarek Salem Abdennaji , Rupesh Kumar Tipu , Yahya Alassaf","doi":"10.1016/j.asej.2025.103474","DOIUrl":"10.1016/j.asej.2025.103474","url":null,"abstract":"<div><div>The study evaluates the prediction accuracy of concrete compressive and tensile strength using machine learning and deep learning models with diverse sand materials, cement types, and filler combinations. A dataset of 587 concrete mix samples was compiled from literature. Seven prediction algorithms, including Linear Regression, Support Vector Regression, Decision Tree Regressor, Random Forest Regressor, Gradient Boosting Regressor, Extreme Gradient Boosting, and Multi-Layer Perceptron, were employed. Preprocessing involved handling missing data, outlier detection, encoding, and feature normalization for Principal Component Analysis. Performance was assessed using coefficient of determination (R<sup>2</sup>), root mean squared error, mean absolute error, and mean absolute percentage error with cross-validation. Extreme Gradient Boosting showed superior accuracy (R<sup>2</sup> = 0.954 for compressive and 0.952 for tensile strength). SHapley Additive Explanations identified curing age, water-to-binder ratio, and filler density as key features. A real-time GitHub interface allows strength predictions, aiding sustainable construction optimization.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103474"},"PeriodicalIF":6.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-data driven and space syntax approach to urban heritage revitalization: Insights from Zhongshan Rd. Historic District, China 城市遗产振兴的多数据驱动和空间句法方法——来自中山路历史街区的启示

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-14 DOI: 10.1016/j.asej.2025.103473

Yuyan Lyu, Mohd Iskandar Abd Malek, Nor Haslina Binti Ja’afar, Chengyu Liu, Zhangjingyi Liu, Ziyi Han

{"title":"Multi-data driven and space syntax approach to urban heritage revitalization: Insights from Zhongshan Rd. Historic District, China","authors":"Yuyan Lyu, Mohd Iskandar Abd Malek, Nor Haslina Binti Ja’afar, Chengyu Liu, Zhangjingyi Liu, Ziyi Han","doi":"10.1016/j.asej.2025.103473","DOIUrl":"10.1016/j.asej.2025.103473","url":null,"abstract":"<div><div>Historic urban areas, with their distinctive regional characteristics and profound cultural significance, are crucial for urban heritage preservation and the sustainable development of cities. However, the complexity of their spatial structure poses challenges for conventional research methods to effectively capture their unique spatial characteristics. This study aims to address these challenges by proposing an innovative approach that integrates multi-source data with quantitative spatial analysis techniques, with a specific focus on the Zhongshan Road Historic and Cultural District in Qingdao, China. By integrating space syntax techniques with Point of Interest (POI) data, this research provides a comprehensive analysis of the district’s spatial patterns and functional attributes. The findings identify potential development zones and offer quantitative evidence to support revitalization strategies for historic districts. This study provides scientific guidance for urban heritage revitalization projects, aiming to enhance the precision of urban analysis and design.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 8","pages":"Article 103473"},"PeriodicalIF":6.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An innovative hybrid power model for protecting tethered drones in case of wired power failures 一种创新的混合动力模型，用于在有线电源故障的情况下保护系留无人机

IF 6 2区工程技术

Ain Shams Engineering Journal Pub Date : 2025-05-14 DOI: 10.1016/j.asej.2025.103471

Tarık Ünler

引用次数: 0