Ain Shams Engineering Journal最新文献

{"title":"Optimization of steady-state target tracking for hybrid dual-type CV systems based on integral slope balance constraints","authors":"Hongrui Wang ,&nbsp;Pengbin Zhang ,&nbsp;Jingyang Wang ,&nbsp;Mingzhe Yuan ,&nbsp;Jingguang Li","doi":"10.1016/j.asej.2025.103743","DOIUrl":"10.1016/j.asej.2025.103743","url":null,"abstract":"<div><div>To address the application gap in target tracking for complex systems featuring hybrid integral-type and stable-type controlled variables, this paper proposes an improved steady-state target tracking method within a double-layer model predictive control framework. To overcome the challenge of accurately characterizing the integral properties of existing decision variables, novel decision variables <span><math><mi>Δ</mi><msub><mrow><mi>u</mi></mrow><mrow><mi>a</mi></mrow></msub></math></span> and <span><math><mi>Δ</mi><msub><mrow><mi>u</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span> are introduced. These variables enable the precise characterization of integral-type controlled variables' steady-state predictions by indirectly expressing <span><math><mi>Δ</mi><msub><mrow><mi>u</mi></mrow><mrow><mi>s</mi></mrow></msub></math></span>. A novel feasibility determination and soft constraint adjustment strategy is subsequently proposed based on <span><math><mi>Δ</mi><msub><mrow><mi>u</mi></mrow><mrow><mi>a</mi></mrow></msub></math></span> and <span><math><mi>Δ</mi><msub><mrow><mi>u</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span>. Furthermore, to resolve the infeasibility issues arising from the dynamic slope balance constraints of integral-type controlled variables, the paper introduces new steady-state slope balance constraints that ensure multi-period slope equilibrium. Simulation results demonstrate that the proposed double-layer model predictive control method significantly enhances the feasibility of the steady-state optimization problem compared to the traditional point-model-based approach. This study provides an innovative solution for steady-state optimization in target tracking of complex systems.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103743"},"PeriodicalIF":5.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096581","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}

{"title":"Analysis of the application of generative artificial intelligence in interior design education","authors":"Yao Liu ,&nbsp;Beiyuan Xu ,&nbsp;Jiarong Feng ,&nbsp;Pengjun Wu","doi":"10.1016/j.asej.2025.103757","DOIUrl":"10.1016/j.asej.2025.103757","url":null,"abstract":"<div><div>The rapid advancement of artificial intelligence (AI) has introduced generative AI tools as transformative resources in interior design education, enhancing creativity, aesthetic quality, and practical design outcomes. Traditional interior design education often limits students’ theoretical knowledge, aesthetic skills, and technical abilities development. Generative AI tools such as Stable Diffusion and Midjourney, which utilize big data and deep learning, offer innovative design concepts to address these limitations. This study applies established models—UTAUT and AHP—in a novel educational context to evaluate generative AI tools in terms of creativity, aesthetics, practicality, and feasibility, offering empirically grounded insights for interior design pedagogy. Results showed that Stable Diffusion excelled in creativity, while Midjourney outperformed in aesthetics and functionality, with both tools proved more feasible than traditional methods. Despite challenges such as limited technical support and high hardware requirements, generative AI tools can significantly enhance interior design education by fostering innovation and improving design efficiency.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103757"},"PeriodicalIF":5.9,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059926","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}

{"title":"An explainable hybrid deep learning-optimization framework for robust phishing attack detection using GAN and transformer-based feature learning","authors":"Raheleh Ghadami (Melisa Rahebi) ,&nbsp;Javad Rahebi","doi":"10.1016/j.asej.2025.103745","DOIUrl":"10.1016/j.asej.2025.103745","url":null,"abstract":"<div><div>This study proposes to improve accuracy of phishing detection by proposing a new hybrid deep learning framework that combines data augmentation, feature transformation, and optimization-based feature selection. The proposed approach integrates a Generative Adversarial Network (GAN) to generate synthetic phishing samples, followed by feature extraction using a combination of feature extraction using a combination of Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), Fully Modified Residual Convolutional Neural Network (FMRCNN), and Transformer models. To reduce feature dimensionality, <strong>the</strong> Black-Winged Kite Algorithm (BKA) <strong>is applied</strong>, while classification is performed using a Support Vector Machine (SVM). Experimental findings on Phishtank dataset demonstrate that the suggested model achieves an accuracy of 98.67%, outperforming other approaches in terms of precision, recall, and F1-score. The novelty of this work lies in the unique combination of GAN with <strong>CNN–GRU–FMRCNN</strong> architectures for phishing detection, further enhanced by hybrid optimization techniques and interpretability via SHAP (SHapley Additive exPlanations) analysis.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103745"},"PeriodicalIF":5.9,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059927","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}

{"title":"Tilt Integral Derivative-Based Sliding Mode Control for Nonlinear Two Interacting Tanks","authors":"Osama Elshazly ,&nbsp;Omar Shaheen ,&nbsp;Hossam Khalil","doi":"10.1016/j.asej.2025.103758","DOIUrl":"10.1016/j.asej.2025.103758","url":null,"abstract":"<div><div>Controlling nonlinear dynamic processes presents serious difficulties due to uncertainties and external disturbances. For better control performance, advanced strategies are required to enhance tracking accuracy and disturbance rejection. This study proposes a novel tilt-integral derivative sliding-mode control strategy (TIDSMC), which merges the benefits of tilt-integral derivative (TID) control for fast response and better noise rejection with the robustness of sliding mode control (SMC) in handling external disturbances. The designed TIDSMC is introduced for controlling a nonlinear two-tank system, and the stability is verified based on the Lyapunov stability method. Effectiveness and robustness of TIDSMC are verified for various scenarios, including variable reference, external disturbance, parameter uncertainties, and noise effect. Also, evaluation of TIDSMC’s performance is conducted through a comparative analysis with other techniques in terms of error and time response performance indices. The comparative results explicitly demonstrate significant improvements in the responses and highlight the superiority of the developed TIDSMC technique.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103758"},"PeriodicalIF":5.9,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059928","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}

{"title":"Research on virtual emergency lane optimization and control strategy based on VISSIM expressway","authors":"Yue Wang","doi":"10.1016/j.asej.2025.103750","DOIUrl":"10.1016/j.asej.2025.103750","url":null,"abstract":"<div><div>Following highway accidents, obstructed rescue access and delayed information dissemination severely limit emergency response efficiency. This study proposes a Virtual Emergency Lane (VEL) strategy that dynamically reallocates lane usage based on real-time traffic data to facilitate rescue vehicle passage under congestion. Using the VISSIM microscopic simulation platform, multiple accident scenarios-varying in lane closure numbers and volume-to-capacity (v/C) ratios-were modeled to evaluate VEL performance. A regression-based predictive model quantified optimization benefits across traffic loads and revealed a performance peak with increasing demand. Results show that VEL significantly reduces travel time, queue length, stop frequency, and vehicle delay. Optimal performance occurs at v/C ratios of 0.9, 0.75, and 0.35 for single-, double-, and triple-lane closures, respectively. The findings validate VEL’s effectiveness and adaptability in various congestion scenarios, offering theoretical support and practical insight for intelligent emergency lane control strategies in highway incident management.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103750"},"PeriodicalIF":5.9,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049799","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}

{"title":"High-speed and accurate detection of high-impedance arcing faults in renewable energy microgrids using a master-slave ADALINE algorithm","authors":"Mohsen Jannati ,&nbsp;Hamidreza Toodeji","doi":"10.1016/j.asej.2025.103673","DOIUrl":"10.1016/j.asej.2025.103673","url":null,"abstract":"<div><div>High-Impedance Arcing Faults (HIAFs) in electrical microgrids are among the abnormal conditions that are difficult to detect by conventional protective devices due to low current and non-linear behavior. In addition, the behavioral similarity of HIAFs to other transient events (TEs) in microgrids leads to classification challenges. This study addresses this issue by proposing a new protective algorithm for the fast and accurate detection of HIAFs and their differentiation from other TEs. The proposed method uses the third harmonic angle of the residual current (THARC) as a key identification feature, which is extracted using a fast, accurate two-layer Master-Slave ADALINE (MS-ADALINE) architecture. The THARC is then smoothed using the Moving Average (MWA) technique, and a new index is introduced for fault detection. Simulations conducted in the EMTP-RV software environment demonstrate that the proposed algorithm can distinguish HIAFs from other TEs under noisy and complex conditions with an accuracy of 99.17% and a detection time of 20 msec. Low computational cost and simple, practical implementation are additional significant advantages of the proposed method.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 11","pages":"Article 103673"},"PeriodicalIF":5.9,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048957","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}

{"title":"Experimental and machine learning assessment of sustainable natural fiber reinforced concrete incorporating waste brick powder as an alternative binder materials","authors":"Md. Hamidul Islam,&nbsp;Shuvo Dip Datta,&nbsp;Sanjoy Mondol,&nbsp;Md. Habibur Rahman Sobuz,&nbsp;Jawad Ashraf,&nbsp;Rahat Aayaz,&nbsp;Abu Sayed Mohammad Akid,&nbsp;Md. Kawsarul Islam Kabbo","doi":"10.1016/j.asej.2025.103755","DOIUrl":"10.1016/j.asej.2025.103755","url":null,"abstract":"<div><div>The rising demand for sustainable construction has prompted the use of natural fibers and waste brick powder (WBP) as eco-efficient alternatives in concrete production. This work aims to determine the feasibility of adding jute fiber (JF) as a reinforcing agent and waste brick powder (WBP) as a partial replacement for cement in concrete. Fresh, non-destructive, and microstructural tests for varying percentages of JF and WBP content, whereas compressive strength (CS) and splitting tensile strength were assessed for mechanical performance. Results show that concrete workability decreased as the replacement percentage of WBP and the addition of JF increased. Test results showed strength improvements of about 9.5% and 31.36% in splitting and compressive strength over the control specimen. Afterward, three machine learning models (RF, XGB, and SVR) were applied to predict the CS. RF achieved best performance with R² of 0.957, while XGB yielded an R² of 0.954. Furthermore, microstructural assessment showed WBP densified matrix by filling pores which enhanced strength.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103755"},"PeriodicalIF":5.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049798","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}

{"title":"Residual Bi-RNN driven adaptive deep learning-optimization for the joint power allocation and signal detection in a secure MIMO-NOMA system","authors":"P. Vineela,&nbsp;Chinthaginjala Ravikumar","doi":"10.1016/j.asej.2025.103752","DOIUrl":"10.1016/j.asej.2025.103752","url":null,"abstract":"<div><div>In Sixth Generation (6G) mobile networks, the Non-Orthogonal Multiple Access (NOMA) serves as a qualified member, which has been obtaining relatively high research interests because of its massive connectivity as well as high spectral efficiency. Different from the existing OMA, like Time Division Multiple Access (TDMA), the NOMA utilizes the power sector to serve distinct users continuously. The previous works on NOMA have highly concentrated on the spectral efficiency improvement. Meanwhile, this experiment concentrates on improving the Secrecy Sum Rate (SSR) in MIMO-NOMA systems by addressing the underlying nonlinear characteristics of both power allocation and signal detection tasks. In the MIMO-NOMA system, the Singular Value Decomposition (SVD) technique is employed to break down the channels in the network. The complex and nonlinear nature of the communication environment, most importantly under secrecy constraints and the multi-user interference, demands a hybrid optimization and a learning-aided solution. To this end, the designed framework leverages the Fitness-based Random Number Swarm Bipolar Algorithm (FitRand SBA) to fine tune the power allocation for near and far users, maximizing the SSR in a nonlinear multi-dimensional search space. Simultaneously, a deep learning-assisted signal detection mechanism utilizing an Adaptive Residual Bi-directional Recurrent Neural Network (AR-BiRNN) is designed to handle the nonlinear temporal dependencies and inter-reference in the signal decoding. The FitRand SBA is employed to optimize the AR-BiRNN parameters, adapting to the wireless channel’s nonlinear behavior. The nonlinear modeling, optimization, and detection methods collectively improve the communication functionality of the MIMO-NOMA system. The simulation results on a 2x2 MIMO-NOMA setup demonstrate that the suggested model attains 28.94 % SSR improvement over conventional optimization algorithms and achieves 95.16 % accuracy contrasted to the existing models. The analytical insights supported by the symbolic computation estimate the optimization process and the detection mechanism. The joint method provides a robust and effective solution for secure, high-performance MIMO-NOMA communications.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103752"},"PeriodicalIF":5.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049797","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}

{"title":"Seismic performance evaluation of continuous reinforced concrete bridge structures based on the integrated approach of machine learning and symbolic regression","authors":"Hanbo Zhu ,&nbsp;Ying Hou ,&nbsp;Qiang Xu ,&nbsp;Jian Wang ,&nbsp;Chuanzhi Sun ,&nbsp;Jibing Deng ,&nbsp;Lei Tong ,&nbsp;Jinsheng Cheng","doi":"10.1016/j.asej.2025.103653","DOIUrl":"10.1016/j.asej.2025.103653","url":null,"abstract":"<div><div>In recent years, the performance-based seismic assessment method using general decision-making indicators has become the mainstream approach for evaluating the seismic safety of structures. However, there are still some deficiencies when assessing the seismic performance of continuous reinforced concrete bridge structures: 1) Insufficient consideration of the randomness of structural materials and geometric dimensions in stochastic finite element analysis; 2) Subjectivity in selecting and constructing seismic intensity measures (IM) during component fragility analysis, with significant variability in the functional relationship between IM and Engineering Demand Parameters (EDP); 3) Lack of a database for repair measures and decision criteria (such as repair time and repair cost) for bridge component categories and damage states based on national specifications. The study aims to investigate the seismic performance of a continuous beam bridge by considering the randomness of material and component parameters, as well as the randomness of seismic ground motion, through stochastic finite element analysis. Machine learning and symbolic regression algorithms will be employed to perform component-level fragility analysis for different bridge elements. Targeting a continuous girder bridge, this study conducts stochastic finite element analysis incorporating material/component parameter variability and ground motion randomness. Machine learning algorithms (Ridge Regression, K-means/CLA clustering, Pearson/Spearman/Kendall correlation coefficients, Distance/Maximal Information Coefficients) combined with symbolic regression via Genetic Programming (GP) are employed for component-level fragility analysis. A repair strategy database incorporating cost and time metrics is subsequently established to assess bridge seismic performance using decision indicators (repair/reconstruction costs, downtime). The results indicate that bridge repair costs and time exhibit pronounced nonlinear growth with increasing PGA. At low intensities (PGA &lt; 0.5 g), longitudinal-direction costs slightly exceed transverse-direction values (four components, e.g., piers, contributing 90 % of total costs), while transverse-direction repair complexity surges at high intensities (PGA &gt; 0.5 g) due to shear key failures. The coefficient of variation (COV) peaks at moderate-high intensities (0.5–0.8 g) and declines thereafter as structural collapse modes converge. Critical cost-effectiveness equilibrium thresholds are identified at 0.92 g (transverse) and 0.93 g (longitudinal), beyond which repair costs (&gt;1.5171 million yuan) surpass reconstruction expenses, serving as pivotal criteria for post-earthquake decision-making.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103653"},"PeriodicalIF":5.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049800","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}

{"title":"Power measurements based on hybrid Haar transform-Prony method","authors":"Nedim Aktan Yalcin ,&nbsp;Fahri Vatansever","doi":"10.1016/j.asej.2025.103736","DOIUrl":"10.1016/j.asej.2025.103736","url":null,"abstract":"<div><div>Power and power quality are among the most important concepts in electrical systems. This paper introduces a novel approach for power measurements or calculations in energy systems, employing the discrete Haar transform and Prony method. The technique stands out by offering an enhanced representation of the power spectrum. This improvement is achieved through the successful decomposition of the frequency spectrum. Unlike Fourier series, this method captures frequencies that are not merely integer multiples of the main harmonic, leading to a more comprehensive depiction of the power spectrum. To verify the effectiveness of the proposed method, simulations were performed on synthetic and real data and results with high accuracy were obtained. The technique demonstrates its prowess in accurately characterizing power spectra, showcasing its potential for applications in electrical systems where a more nuanced and precise analysis of frequency components is essential for a comprehensive understanding of the system behavior.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 11","pages":"Article 103736"},"PeriodicalIF":5.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048956","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}