Pub Date : 2025-02-01DOI: 10.1016/j.asej.2025.103283
Zhengjie Zhan , Pan Xia , Dongtao Xia , Yan Hu
This study tackles the multi-objective optimization (MOP) challenges in constructing steel–concrete columns by introducing a novel TCQE model that considers time, cost, quality, and carbon emissions. Employing relative deviation theory with dynamic weighting, the model normalizes MOP and applies an improved ant colony algorithm (IACA) to generate optimized solutions. Empirical research validates the model’s efficiency and applicability. Furthermore, a decision-making framework based on AHP-TOPSIS is proposed, demonstrating superior weight distribution and fairness in the decision process. Compared to the ideal point method and VIKOR, the proposed approach consistently identifies optimal solutions, affirming its scientific validity and effectiveness. The findings suggest broad application prospects in practical construction projects and provide valuable insights for construction management research, highlighting the theoretical and practical significance of the model and framework.
{"title":"Multi-Objective optimization in the construction of steel-concrete composite columns with carbon emission considerations: Pareto front development and decision-making","authors":"Zhengjie Zhan , Pan Xia , Dongtao Xia , Yan Hu","doi":"10.1016/j.asej.2025.103283","DOIUrl":"10.1016/j.asej.2025.103283","url":null,"abstract":"<div><div>This study tackles the multi-objective optimization (MOP) challenges in constructing steel–concrete columns by introducing a novel TCQE model that considers time, cost, quality, and carbon emissions. Employing relative deviation theory with dynamic weighting, the model normalizes MOP and applies an improved ant colony algorithm (IACA) to generate optimized solutions. Empirical research validates the model’s efficiency and applicability. Furthermore, a decision-making framework based on AHP-TOPSIS is proposed, demonstrating superior weight distribution and fairness in the decision process. Compared to the ideal point method and VIKOR, the proposed approach consistently identifies optimal solutions, affirming its scientific validity and effectiveness. The findings suggest broad application prospects in practical construction projects and provide valuable insights for construction management research, highlighting the theoretical and practical significance of the model and framework.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103283"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.asej.2024.103252
Xiaofang Zhao , Yuchi Leng , Faisal Nazir , Jawad Ahmed , Abdullah Mohamed , Ilyas Khan , Mohamed Abdelghany Elkotb
A promising material for improving heat transfer is titanium dioxide (), which has great chemical and physical stability. In numerous types of heat exchangers, including circular tubes, double tubes, and shell and tubes, nanoparticles dispersed in ordinary fluids were widely used. The present work is to investigate the behavior of titanium dioxide copper oxide hybrid type of nanofluid flow for enhancing thermal transfer by a horizontal rotating cylinder surface under solar radiation, viscous dissipation and Lorentz forces. Here, the combinations of as hybrid nanofluids and as nanofluid are implemented. The slip and convective conditions are imposed at the surface of the rotating cylinder. The computational MATLAB software’s bvp4c solver is used to numerically integrate the resulting dimensionless equations. According to the results, higher Reynolds number values upsurge the system’s inertial force, which counteracts the force accelerating the liquid and reduces velocities as well as heat transfer. The thermal profile benefits from the nonlinear radiation and decays for growing estimations of nanoparticle volume fraction. The rate of heat transfer is higher for hybrid nanofluid as compared to nanofluid.
{"title":"Improved heat conduction in hybrid nanofluid across a slippery rotating cylinder with solar radiation and Lorentz forces","authors":"Xiaofang Zhao , Yuchi Leng , Faisal Nazir , Jawad Ahmed , Abdullah Mohamed , Ilyas Khan , Mohamed Abdelghany Elkotb","doi":"10.1016/j.asej.2024.103252","DOIUrl":"10.1016/j.asej.2024.103252","url":null,"abstract":"<div><div>A promising material for improving heat transfer is titanium dioxide (<span><math><mrow><mi>Ti</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></math></span>), which has great chemical and physical stability. In numerous types of heat exchangers, including circular tubes, double tubes, and shell and tubes, <span><math><mrow><mi>Ti</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></math></span> nanoparticles dispersed in ordinary fluids were widely used. The present work is to investigate the behavior of titanium dioxide <span><math><mrow><mi>Ti</mi><msub><mi>O</mi><mn>2</mn></msub><mo>-</mo></mrow></math></span> copper oxide <span><math><mrow><mi>CuO</mi><mo>/</mo><msub><mi>H</mi><mn>2</mn></msub><mi>O</mi></mrow></math></span> hybrid type of nanofluid flow for enhancing thermal transfer by a horizontal rotating cylinder surface under solar radiation, viscous dissipation and Lorentz forces. Here, the combinations of <span><math><mrow><mi>Ti</mi><msub><mi>O</mi><mn>2</mn></msub><mo>-</mo><mi>C</mi><mi>u</mi><mi>O</mi><mo>/</mo><msub><mi>H</mi><mn>2</mn></msub><mi>O</mi></mrow></math></span> as hybrid nanofluids and <span><math><mrow><mi>Ti</mi><msub><mi>O</mi><mn>2</mn></msub><mo>/</mo><msub><mi>H</mi><mn>2</mn></msub><mi>O</mi></mrow></math></span> as nanofluid are implemented. The slip and convective conditions are imposed at the surface of the rotating cylinder. The computational MATLAB software’s bvp4c solver is used to numerically integrate the resulting dimensionless equations. According to the results, higher Reynolds number values upsurge the system’s inertial force, which counteracts the force accelerating the liquid and reduces velocities as well as heat transfer. The thermal profile benefits from the nonlinear radiation and decays for growing estimations of nanoparticle volume fraction. The rate of heat transfer is higher for <span><math><mrow><mi>Ti</mi><msub><mi>O</mi><mn>2</mn></msub><mo>-</mo><mi>C</mi><mi>u</mi><mi>O</mi><mo>/</mo><msub><mi>H</mi><mn>2</mn></msub><mi>O</mi></mrow></math></span> hybrid nanofluid as compared to <span><math><mrow><mi>Ti</mi><msub><mi>O</mi><mn>2</mn></msub><mo>/</mo><msub><mi>H</mi><mn>2</mn></msub><mi>O</mi></mrow></math></span> nanofluid.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103252"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.asej.2024.103243
Ahmed H. Arnous , Muhammad Amin S. Murad , Anjan Biswas , Yakup Yildirim , Puiu Lucian Georgescu , Luminita Moraru , Anwar Jaafar Mohamad Jawad , Layth Hussein
This paper recovers the optical solitons for the concatenation model that comes with fractional temporal evolution and Kerr–law of self–phase modulation by the usage of the enhanced direct algebraic approach. This study goes beyond previous efforts by incorporating fractional temporal evolution instead of linear temporal evolution in the concatenation model. This would facilitate the regulation of the internet bottleneck phenomenon by enabling the deceleration of internet traffic in one direction at a node while maintaining its full flow in the other direction. The model presents a novel approach that contributes to a deeper understanding of potential applications in the telecommunication industry. The implemented technique presents several solitons. In addition to those solitons, the method presents solutions in terms of Jacobi and Weierstrass elliptic functions. A full spectrum of optical solitons are thus recovered. This will include bright solitons, dark solitons, singular solitons, and straddled solitons. The existence criteria of such solitons, in the form of parameters constraints, that naturally emerged during the course of derivation, are presented. The recovered solitons will be presented in the paper that can be efficiently implemented to mitigate the internet bottleneck effect. A few numerical simulations supplement the mathematical analysis.
{"title":"Optical solitons for the concatenation model with fractional temporal evolution","authors":"Ahmed H. Arnous , Muhammad Amin S. Murad , Anjan Biswas , Yakup Yildirim , Puiu Lucian Georgescu , Luminita Moraru , Anwar Jaafar Mohamad Jawad , Layth Hussein","doi":"10.1016/j.asej.2024.103243","DOIUrl":"10.1016/j.asej.2024.103243","url":null,"abstract":"<div><div>This paper recovers the optical solitons for the concatenation model that comes with fractional temporal evolution and Kerr–law of self–phase modulation by the usage of the enhanced direct algebraic approach. This study goes beyond previous efforts by incorporating fractional temporal evolution instead of linear temporal evolution in the concatenation model. This would facilitate the regulation of the internet bottleneck phenomenon by enabling the deceleration of internet traffic in one direction at a node while maintaining its full flow in the other direction. The model presents a novel approach that contributes to a deeper understanding of potential applications in the telecommunication industry. The implemented technique presents several solitons. In addition to those solitons, the method presents solutions in terms of Jacobi and Weierstrass elliptic functions. A full spectrum of optical solitons are thus recovered. This will include bright solitons, dark solitons, singular solitons, and straddled solitons. The existence criteria of such solitons, in the form of parameters constraints, that naturally emerged during the course of derivation, are presented. The recovered solitons will be presented in the paper that can be efficiently implemented to mitigate the internet bottleneck effect. A few numerical simulations supplement the mathematical analysis.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103243"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.asej.2024.103241
Mohamed G. Khattap , Mohammed Sallah , Abdelghani Dahou , Mohamed Abd Elaziz , Ahmed Elgarayhi , Ahmad O. Aseeri , Agostino Forestiero , Hend Galal Eldeen Mohamed Ali Hassan
The rising global incidence of Multiple Sclerosis (MS), an autoimmune disorder that impacts the central nervous system, demands novel diagnostic approaches for early detection and intervention. Given the challenges of irreversible MS progression and the complexity of traditional diagnosis methods, this study introduces a hybrid Artificial Intelligence (AI) framework that enhances MS diagnosis accuracy using MRI scans. Our model integrates a multi-view ResNet architecture with novel attention mechanisms—View Space Attention Block (VSAB) and View Channel Attention Block (VCAB)—to extract detailed features from 2D brain images. Additionally, we developed the Quantum RIME (QRIME) algorithm, which combines RIME and Quantum Behaved Particle Swarm Optimization (QPSO) for efficient dimensionality reduction, optimizing both accuracy and computational efficiency. The model was rigorously evaluated using sixteen UCI benchmark datasets and a dedicated brain MRI dataset of 425 scans (262 MS patients and 163 healthy controls), achieving a notable accuracy of 98.29%, precision of 96.49%, specificity of 97.65%, and an F1-score of 97.85%. These results not only demonstrate our model's exceptional capability in identifying MS with high precision but also highlight its potential applicability in diagnosing other neurological disorders. By emphasizing the transformative potential of AI in medical diagnostics, our work underlines the significance of innovative AI applications in enhancing early detection, ultimately aiming to enhance patient outcomes in the neurodegenerative disease domain.
{"title":"Advancing multiple sclerosis diagnosis through an innovative hybrid AI framework incorporating Multi-view ResNet and quantum RIME-inspired metaheuristics","authors":"Mohamed G. Khattap , Mohammed Sallah , Abdelghani Dahou , Mohamed Abd Elaziz , Ahmed Elgarayhi , Ahmad O. Aseeri , Agostino Forestiero , Hend Galal Eldeen Mohamed Ali Hassan","doi":"10.1016/j.asej.2024.103241","DOIUrl":"10.1016/j.asej.2024.103241","url":null,"abstract":"<div><div>The rising global incidence of Multiple Sclerosis (MS), an autoimmune disorder that impacts the central nervous system, demands novel diagnostic approaches for early detection and intervention. Given the challenges of irreversible MS progression and the complexity of traditional diagnosis methods, this study introduces a hybrid Artificial Intelligence (AI) framework that enhances MS diagnosis accuracy using MRI scans. Our model integrates a multi-view ResNet architecture with novel attention mechanisms—View Space Attention Block (VSAB) and View Channel Attention Block (VCAB)—to extract detailed features from 2D brain images. Additionally, we developed the Quantum RIME (QRIME) algorithm, which combines RIME and Quantum Behaved Particle Swarm Optimization (QPSO) for efficient dimensionality reduction, optimizing both accuracy and computational efficiency. The model was rigorously evaluated using sixteen UCI benchmark datasets and a dedicated brain MRI dataset of 425 scans (262 MS patients and 163 healthy controls), achieving a notable accuracy of 98.29%, precision of 96.49%, specificity of 97.65%, and an F1-score of 97.85%. These results not only demonstrate our model's exceptional capability in identifying MS with high precision but also highlight its potential applicability in diagnosing other neurological disorders. By emphasizing the transformative potential of AI in medical diagnostics, our work underlines the significance of innovative AI applications in enhancing early detection, ultimately aiming to enhance patient outcomes in the neurodegenerative disease domain.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103241"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.asej.2024.103251
Faezeh Jafari, Sattar Dorafshan
Monitoring a stockpile plays a vital role in material inventories at the State Departments of Transportation (DOTs). Various technologies, such as Total Stations (TST), Light Detection and Ranging (LiDAR), and Global Positioning Systems, are conventionally used to obtain stockpile volumes; however, DOTs seek a faster, safer way to obtain an object’s volume with minimal workforce training. Uncrewed Aircraft Systems (UAS), coupled with visual imagery, have the potential to address these limitations; however, UAS visual has not been effectively developed to account for flight parameters in measurements, such as Ground Sampling Distance (GSD). Images of regular and irregular objects were collected in several flights to measure their geometries. The measurements were performed using a computer vision algorithm and a common commercially available photogrammetry tool (Pix4D) as UAS visual and UAS LiDAR. The results indicated that UAS visual is a viable technology that provides consistently accurate measurements of stockpiles of various sizes. The authors used Pix4D to measure volumes ranging from 0.45 m3 to 2838 m3 with errors ranging from 4 % to 6 %. The results indicated that ensuring a GSD value of 0.80 cm in visual imagery can lead to accurate volumetric measurements of irregular objects. To reduce the processing time, a deep leaning-based point cloud classification model was developed to detect the objects of interest, stockpiles, and separate them from irrelevant objects. The average volume difference between the volume predicted using Pix4D and point cloud classification was less than 5.5 %. Finally, we compared the advantages and challenges of UAS with traditional methods and UAS LiDAR in terms of data collection time, cost, limitations, and safety. The results demonstrate that using UAS for stockpile volume measurement is safer and more time-consuming and cost-effective.
{"title":"Vision based stockpile inventory measurement using uncrewed aerial systems","authors":"Faezeh Jafari, Sattar Dorafshan","doi":"10.1016/j.asej.2024.103251","DOIUrl":"10.1016/j.asej.2024.103251","url":null,"abstract":"<div><div>Monitoring a stockpile plays a vital role in material inventories at the State Departments of Transportation (DOTs). Various technologies, such as Total Stations (TST), Light Detection and Ranging (LiDAR), and Global Positioning Systems, are conventionally used to obtain stockpile volumes; however, DOTs seek a faster, safer way to obtain an object’s volume with minimal workforce training. Uncrewed Aircraft Systems (UAS), coupled with visual imagery, have the potential to address these limitations; however, UAS visual has not been effectively developed to account for flight parameters in measurements, such as Ground Sampling Distance (GSD). Images of regular and irregular objects were collected in several flights to measure their geometries. The measurements were performed using a computer vision algorithm and a common commercially available photogrammetry tool (Pix4D) as UAS visual and UAS LiDAR. The results indicated that UAS visual is a viable technology that provides consistently accurate measurements of stockpiles of various sizes. The authors used Pix4D to measure volumes ranging from 0.45 m<sup>3</sup> to 2838 m<sup>3</sup> with errors ranging from 4 % to 6 %. The results indicated that ensuring a GSD value of 0.80 cm in visual imagery can lead to accurate volumetric measurements of irregular objects. To reduce the processing time, a deep leaning-based point cloud classification model was developed to detect the objects of interest, stockpiles, and separate them from irrelevant objects. The average volume difference between the volume predicted using Pix4D and point cloud classification was less than 5.5 %. Finally, we compared the advantages and challenges of UAS with traditional methods and UAS LiDAR in terms of data collection time, cost, limitations, and safety. The results demonstrate that using UAS for stockpile volume measurement is safer and more time-consuming and cost-effective.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103251"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research explores the epidemiology of widespread monkeypox virus (MPV) transmission using a modified Atanagana-Baleanu-Caputo (mABC) fractional derivative mathematical model in the sense of a generalized Mittag-Leffler kernel. The stability of the disease-free equilibrium in the fractional MPV model is provided, demonstrating the result for . The Jacobian matrix technique shows the global stability of model equilibrium. We conduct sensitivity evaluations to find important factors affecting illness eradication and provide the results. Moreover, we investigate the existence, uniqueness, and Hyers-Ulam (HU) stability of the generalized fractional order nonlinear framework for the MPV model. The solution's uniqueness and stability are demonstrated using fixed point theory and within the HU context. We provide numerical representations for analysis employing Lagrange polynomials. The optimality criteria are produced by applying Pontryagin's maximal argument to prove the validity of the most effective control. Experiments show the approach's usefulness, predictive capabilities, and confirmation of mABC fractional orders.
{"title":"Spatiotemporal dynamics of a novel hybrid modified ABC fractional monkeypox virus involving environmental disturbance and their stability analysis","authors":"Maysaa Al-Qurashi , Sehrish Ramzan , Sobia Sultana , Saima Rashid , Sayed K. Elagan","doi":"10.1016/j.asej.2025.103273","DOIUrl":"10.1016/j.asej.2025.103273","url":null,"abstract":"<div><div>This research explores the epidemiology of widespread monkeypox virus (MPV) transmission using a modified Atanagana-Baleanu-Caputo (mABC) fractional derivative mathematical model in the sense of a generalized Mittag-Leffler kernel. The stability of the disease-free equilibrium in the fractional MPV model is provided, demonstrating the result for <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub><mo><</mo><mn>1</mn></math></span>. The Jacobian matrix technique shows the global stability of model equilibrium. We conduct sensitivity evaluations to find important factors affecting illness eradication and provide the results. Moreover, we investigate the existence, uniqueness, and Hyers-Ulam (HU) stability of the generalized fractional order nonlinear framework for the MPV model. The solution's uniqueness and stability are demonstrated using fixed point theory and within the HU context. We provide numerical representations for analysis employing Lagrange polynomials. The optimality criteria are produced by applying Pontryagin's maximal argument to prove the validity of the most effective control. Experiments show the approach's usefulness, predictive capabilities, and confirmation of mABC fractional orders.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103273"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.asej.2025.103281
Iyad Katib, Emad Albassam, Sanaa A. Sharaf, Mahmoud Ragab
Internet of Things (IoT) security is paramount for enterprises, as it includes several strategies, techniques, actions, and protocols that aim to alleviate the high vulnerability of cutting-edge businesses. IoT consumer devices, from smart home appliances to wearable gadgets, have become ubiquitous daily, facilitating automation and seamless connectivity. However, ensuring their reliability and security presents a tremendous challenge. Anomaly detection methods offer a promising solution, especially those powered by TinyML (Machine Learning (ML) on Tiny Devices). These IoT devices can autonomously identify unusual behaviours or patterns that diverge from regular operation by leveraging the proficiencies of deep learning (DL) techniques enhanced for resource-constraint environments, like neural networks. Incorporating DL, anomaly detection, and TinyML allows real-time monitoring and proactive mitigation of malfunctions or security breaches in IoT devices. This advanced technology ensures improved reliability, privacy, and overall user experience in the dynamic landscape of connected devices, whether identifying irregular health data or detecting unauthorized access attempts on a smart door lock from the wearable fitness tracker. Therefore, this study develops a new Deep Learning technique to secure IoT consumer devices with TinyML Driven Real-time Anomaly Detection for Predictive Maintenance (DLTML-RTADPM). The DLTML-RTADPM technique aims to recognize and categorize the anomalies in IoT consumer devices. At the primary phase, the DLTML-RTADPM model normalizes the input data using Z-score normalization. In the DLTML-RTADPM method, the Fennec Fox Optimization Algorithm (FFA) is used for a high dimensionality reduction process where the optimal feature set is chosen. The DLTML-RTADPM technique implements gradient least mean squares with a bidirectional long short-term memory (GLMS-BiLSTM) approach for anomaly detection. To further improve the detection results of the DLTML-RTADPM technique, the Jaya optimization algorithm (JOA)-based hyperparameter tuning process is utilized. A series of simulations are performed on the benchmark dataset to ensure better detection outcomes of the DLTML-RTADPM model. The investigational validation of the DLTML-RTADPM method portrayed a superior accuracy value of 98.11% over other techniques.
{"title":"Safeguarding IoT consumer devices: Deep learning with TinyML driven real-time anomaly detection for predictive maintenance","authors":"Iyad Katib, Emad Albassam, Sanaa A. Sharaf, Mahmoud Ragab","doi":"10.1016/j.asej.2025.103281","DOIUrl":"10.1016/j.asej.2025.103281","url":null,"abstract":"<div><div>Internet of Things (IoT) security is paramount for enterprises, as it includes several strategies, techniques, actions, and protocols that aim to alleviate the high vulnerability of cutting-edge businesses. IoT consumer devices, from smart home appliances to wearable gadgets, have become ubiquitous daily, facilitating automation and seamless connectivity. However, ensuring their reliability and security presents a tremendous challenge. Anomaly detection methods offer a promising solution, especially those powered by TinyML (Machine Learning (ML) on Tiny Devices). These IoT devices can autonomously identify unusual behaviours or patterns that diverge from regular operation by leveraging the proficiencies of deep learning (DL) techniques enhanced for resource-constraint environments, like neural networks. Incorporating DL, anomaly detection, and TinyML allows real-time monitoring and proactive mitigation of malfunctions or security breaches in IoT devices. This advanced technology ensures improved reliability, privacy, and overall user experience in the dynamic landscape of connected devices, whether identifying irregular health data or detecting unauthorized access attempts on a smart door lock from the wearable fitness tracker. Therefore, this study develops a new Deep Learning technique to secure IoT consumer devices with TinyML Driven Real-time Anomaly Detection for Predictive Maintenance (DLTML-RTADPM). The DLTML-RTADPM technique aims to recognize and categorize the anomalies in IoT consumer devices. At the primary phase, the DLTML-RTADPM model normalizes the input data using Z-score normalization. In the DLTML-RTADPM method, the Fennec Fox Optimization Algorithm (FFA) is used for a high dimensionality reduction process where the optimal feature set is chosen. The DLTML-RTADPM technique implements gradient least mean squares with a bidirectional long short-term memory (GLMS-BiLSTM) approach for anomaly detection. To further improve the detection results of the DLTML-RTADPM technique, the Jaya optimization algorithm (JOA)-based hyperparameter tuning process is utilized. A series of simulations are performed on the benchmark dataset to ensure better detection outcomes of the DLTML-RTADPM model. The investigational validation of the DLTML-RTADPM method portrayed a superior accuracy value of 98.11% over other techniques.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103281"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study introduces an inverse lubrication analysis (ILA) method, a novel approach for simulating the lubrication state of sliding bearings under various load conditions. By integrating experimental pressure data from sliding bearings with an adaptive genetic optimization algorithm, this method precisely calculates the eccentricity, attitude angle, and global pressure distribution of the lubrication film. Unlike traditional forward lubrication analysis (FLA) methods, which indirectly estimate the lubrication film status through loads, the ILA method utilizes direct pressure measurements, ensuring accurate and timely raw data for inverse calculations. This approach rapidly and accurately converts measured data into key parameters, closely aligning simulation results with experimental data. The lubrication states of the experimental sliding bearing under loads of 100 N, 200 N, 300 N, and 400 N were successfully predicted, highlighting the method’s reliability in real-world applications. This study provides a new approach and perspective for health monitoring and fault diagnosis of sliding bearings, especially under extreme conditions.
{"title":"A novel inverse method for Advanced monitoring of lubrication conditions in sliding bearings through adaptive genetic algorithm","authors":"Zhenpeng Wu , Bowen Dong , Liangyi Nie , Adnan Kefal","doi":"10.1016/j.asej.2025.103291","DOIUrl":"10.1016/j.asej.2025.103291","url":null,"abstract":"<div><div>This study introduces an inverse lubrication analysis (ILA) method, a novel approach for simulating the lubrication state of sliding bearings under various load conditions. By integrating experimental pressure data from sliding bearings with an adaptive genetic optimization algorithm, this method precisely calculates the eccentricity, attitude angle, and global pressure distribution of the lubrication film. Unlike traditional forward lubrication analysis (FLA) methods, which indirectly estimate the lubrication film status through loads, the ILA method utilizes direct pressure measurements, ensuring accurate and timely raw data for inverse calculations. This approach rapidly and accurately converts measured data into key parameters, closely aligning simulation results with experimental data. The lubrication states of the experimental sliding bearing under loads of 100 N, 200 N, 300 N, and 400 N were successfully predicted, highlighting the method’s reliability in real-world applications. This study provides a new approach and perspective for health monitoring and fault diagnosis of sliding bearings, especially under extreme conditions.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103291"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143234239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.asej.2024.103255
Kazi Sajedur Rahman , Camellia Doroody , Puvaneswaran Chelvanathan , Norasikin Ahmad Ludin , Mohd Adib Ibrahim , Nowshad Amin
Cadmium Telluride (CdTe) is a potential material for thin-film solar cell fabrication due to its good optoelectronic characteristics, widespread availability, and inexpensive manufacturing costs. However, optimizing the deposition process to generate high-quality CdTe devices remains a challenge since deposition factors such as pressure have a substantial impact on the structural, optical, and electrical properties of the films, eventually influencing device performance. This study explores the effects of deposition pressure during the Close-Spaced Sublimation (CSS) process on the structural, morphological, optical and electrical characteristics of CdTe thin films, with an emphasis on pressures ranging from 1 to 10 Torr. High-quality CdTe films with large grain sizes (∼3 µm), cubic (111) preferential crystallite orientation, low dislocation density, and decreased strain are grown at deposition pressures ranging from 1.5 to 2 Torr, according to structural studies. These properties are appropriate for producing high-performance p-type CdTe absorber layers for solar cells. The optimized films has a band gap of 1.49 eV, a Voc of 0.64 V, a Jsc of over 18 mA/cm2, and solar cell efficiencies above 5 % under normal AM1.5 conditions. Films deposited at higher pressures (≥5 Torr) exhibit poor electrical performance, including poorer carrier mobility, higher recombination losses, and low Jsc due to carrier dispersion and grain boundary defects. This work emphasizes the importance of deposition pressure in managing the balance of crystallinity, grain size, and carrier concentration, all of which are required for optimal solar cell performance. The findings present a systematic approach for optimizing CSS deposition parameters in order to achieve higher-efficiency CdTe thin-film solar cells. Furthermore, this study provides the groundwork for future research focusing on pressure-dependent manufacturing processes and post-deposition treatments to increase the efficiency, stability, and scalability of CdTe-based solar cells.
{"title":"Exploring the impact of deposition pressure in CdTe thin film solar cells fabrication","authors":"Kazi Sajedur Rahman , Camellia Doroody , Puvaneswaran Chelvanathan , Norasikin Ahmad Ludin , Mohd Adib Ibrahim , Nowshad Amin","doi":"10.1016/j.asej.2024.103255","DOIUrl":"10.1016/j.asej.2024.103255","url":null,"abstract":"<div><div>Cadmium Telluride (CdTe) is a potential material for thin-film solar cell fabrication due to its good optoelectronic characteristics, widespread availability, and inexpensive manufacturing costs. However, optimizing the deposition process to generate high-quality CdTe devices remains a challenge since deposition factors such as pressure have a substantial impact on the structural, optical, and electrical properties of the films, eventually influencing device performance. This study explores the effects of deposition pressure during the Close-Spaced Sublimation (CSS) process on the structural, morphological, optical and electrical characteristics of CdTe thin films, with an emphasis on pressures ranging from 1 to 10 Torr. High-quality CdTe films with large grain sizes (∼3 µm), cubic (111) preferential crystallite orientation, low dislocation density, and decreased strain are grown at deposition pressures ranging from 1.5 to 2 Torr, according to structural studies. These properties are appropriate for producing high-performance p-type CdTe absorber layers for solar cells. The optimized films has a band gap of 1.49 eV, a Voc of 0.64 V, a Jsc of over 18 mA/cm<sup>2</sup>, and solar cell efficiencies above 5 % under normal AM1.5 conditions. Films deposited at higher pressures (≥5 Torr) exhibit poor electrical performance, including poorer carrier mobility, higher recombination losses, and low Jsc due to carrier dispersion and grain boundary defects. This work emphasizes the importance of deposition pressure in managing the balance of crystallinity, grain size, and carrier concentration, all of which are required for optimal solar cell performance. The findings present a systematic approach for optimizing CSS deposition parameters in order to achieve higher-efficiency CdTe thin-film solar cells. Furthermore, this study provides the groundwork for future research focusing on pressure-dependent manufacturing processes and post-deposition treatments to increase the efficiency, stability, and scalability of CdTe-based solar cells.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103255"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.asej.2024.103250
Reza Askarizad , Jinliao He
Urban furniture plays a crucial role in shaping public spaces, influencing how people interact and engage in social activities. Its design may impact gender equality by either facilitating or hindering equal access to public amenities for both men and women. The entrenched constraints on equal opportunities for women in establishing social activities, particularly in ideologically traditional developing countries like Iran, create observable disparities in the usage of public amenities. This research aimed to develop a comprehensive framework fostering equal opportunities for both men and women in static social activities around street furniture. To achieve this, the research employed a mixed-methods approach. The study combined empirical field observations, space syntax analysis, and interviews with users of public spaces. The space syntax analysis was used to evaluate spatial integration and connectivity, while interviews provided qualitative insights into how men and women interact with urban furniture. Observational data helped identify patterns in the use of street furniture by different genders. The results indicated that street furniture positively influences the social logic of space by enhancing spatial integration and connectivity, thus improving overall accessibility to public spaces for social activities. However, a significant gender imbalance was observed, with men predominantly using street furniture more frequently than women. This disparity highlights conflicting perspectives on gender equality in public space usage. The findings suggest that achieving a more equitable gender distribution in public spaces requires designing street furniture that reduces visual integration and connection while increasing the visual clustering coefficient and entropy, thereby creating more inclusive environments.
{"title":"The role of urban furniture in promoting gender equality and static social activities in public spaces","authors":"Reza Askarizad , Jinliao He","doi":"10.1016/j.asej.2024.103250","DOIUrl":"10.1016/j.asej.2024.103250","url":null,"abstract":"<div><div>Urban furniture plays a crucial role in shaping public spaces, influencing how people interact and engage in social activities. Its design may impact gender equality by either facilitating or hindering equal access to public amenities for both men and women. The entrenched constraints on equal opportunities for women in establishing social activities, particularly in ideologically traditional developing countries like Iran, create observable disparities in the usage of public amenities. This research aimed to develop a comprehensive framework fostering equal opportunities for both men and women in static social activities around street furniture. To achieve this, the research employed a mixed-methods approach. The study combined empirical field observations, space syntax analysis, and interviews with users of public spaces. The space syntax analysis was used to evaluate spatial integration and connectivity, while interviews provided qualitative insights into how men and women interact with urban furniture. Observational data helped identify patterns in the use of street furniture by different genders. The results indicated that street furniture positively influences the social logic of space by enhancing spatial integration and connectivity, thus improving overall accessibility to public spaces for social activities. However, a significant gender imbalance was observed, with men predominantly using street furniture more frequently than women. This disparity highlights conflicting perspectives on gender equality in public space usage. The findings suggest that achieving a more equitable gender distribution in public spaces requires designing street furniture that reduces visual integration and connection while increasing the visual clustering coefficient and entropy, thereby creating more inclusive environments.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103250"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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