Ain Shams Engineering Journal最新文献

英文中文

Fractional Moore-Gibson-Thomson model for mass diffusion and thermal dynamics: Application to an infinite viscoelastic medium with a cylindrical cavity

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 10.1016/j.asej.2025.103276

Yazeed Alhassan

This article presented an innovative fractional model that integrated mass diffusion and thermal diffusion equations within thermo-viscoelastic Kelvin-Voigt materials, providing a deeper understanding of material behavior. The model employed the Atangana-Baleanu-Caputo (ABC) fractional derivative in conjunction with the Moore-Gibson-Thomson (MGT) equation, effectively capturing non-local and memory-dependent processes that were often overlooked in traditional models. By incorporating these advanced concepts, the model offered a more accurate representation of material responses, particularly in scenarios involving complex thermal and mass diffusion effects. The model utilized advanced mathematical techniques, including Laplace transforms and Mathematica, to solve the resulting complex differential equations, ensuring computational efficiency and accuracy. Validation of the model was conducted through comparisons with previous studies, demonstrating its improvements over existing approaches, and confirming its practical applicability. The article also provided graphical results and analysis, emphasizing the significant effects of heat transfer, viscoelasticity, and mass diffusion on material performance. These contributions were crucial for advancing engineering applications, especially in systems where traditional models fell short, such as in microelectronics, aerospace, and energy systems. The novelty of this work lay in its ability to address the limitations of conventional models by incorporating memory-dependent effects and non-local interactions, which significantly enhanced the prediction and design of materials under complex loading conditions.

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引用次数: 0

Hybrid LSTM-PSO optimization techniques for enhancing wind power bidding efficiency in electricity markets

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 10.1016/j.asej.2025.103285

Viet Anh Truong , Ngoc Sang Dinh , Thanh Long Duong , Ngoc Thien Le , Cong Dinh Truong , Linh Tung Nguyen

Past research has predominantly focused on utilizing meta-heuristic algorithms to optimize neural network structures, while the exploration of deep learning in optimization has remained relatively limited. The proposed hybrid approach seeks to enhance wind power bidding strategies, improving profitability by predicting optimal output power for day-ahead electricity markets. This method integrates Long Short-Term Memory (LSTM) with Particle Swarm Optimization (PSO), leveraging LSTM’s ability to predict the active movement tendencies of particles for more efficient and faster optimization. Experiments conducted on the IEEE 30-bus power system show that the LSTM-PSO hybrid outperforms mathematical models and standalone PSO algorithms. It also delivers an optimal wind power bidding strategy, yielding peak annual revenue, while recommending a 16 % reduction in bidding output power variance in models that integrate wind power with thermal power and energy storage systems (ESS). Ultimately, this approach fosters confidence in wind energy investment, contributing to sustainable development.

{"title":"Hybrid LSTM-PSO optimization techniques for enhancing wind power bidding efficiency in electricity markets","authors":"Viet Anh Truong , Ngoc Sang Dinh , Thanh Long Duong , Ngoc Thien Le , Cong Dinh Truong , Linh Tung Nguyen","doi":"10.1016/j.asej.2025.103285","DOIUrl":"10.1016/j.asej.2025.103285","url":null,"abstract":"<div><div>Past research has predominantly focused on utilizing meta-heuristic algorithms to optimize neural network structures, while the exploration of deep learning in optimization has remained relatively limited. The proposed hybrid approach seeks to enhance wind power bidding strategies, improving profitability by predicting optimal output power for day-ahead electricity markets. This method integrates Long Short-Term Memory (LSTM) with Particle Swarm Optimization (PSO), leveraging LSTM’s ability to predict the active movement tendencies of particles for more efficient and faster optimization. Experiments conducted on the IEEE 30-bus power system show that the LSTM-PSO hybrid outperforms mathematical models and standalone PSO algorithms. It also delivers an optimal wind power bidding strategy, yielding peak annual revenue, while recommending a 16 % reduction in bidding output power variance in models that integrate wind power with thermal power and energy storage systems (ESS). Ultimately, this approach fosters confidence in wind energy investment, contributing to sustainable development.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103285"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178415","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}

引用次数: 0

Report on optimisation for efficient dynamic task distribution in drone swarms using QRDPSO algorithm

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 10.1016/j.asej.2024.103237

Giuseppe Converso , Duaa Mehiar , Alexander Rukovich , Rashit Brzhanov

The primary aim was to develop a Quantum Robot Darwinian Particle Swarm Optimisation (QRDPSO) algorithm and assess its performance against the conventional RDPSO. Using MATLAB-based mathematical modelling, QRDPSO was evaluated for its efficiency in dynamic task distribution and inter-drone communication stability. The results demonstrate that QRDPSO finds optimal solutions 16.3% faster than RDPSO, with performance improvements as the swarm size increases. Specifically, when the number of drones was increased from 5 to 20, the number of iterations required for QRDPSO changed from 384 to 189. However, for RDPSO, the number of iterations changed from 439 to 242. Additionally, QRDPSO showed a 27.1% reduction in drone loss rates, outperforming RDPSO in terms of maintaining operational resources, especially in larger swarms. These findings have practical implications, as QRDPSO’s efficiency and stability can support extensive drone applications requiring synchronised, reliable swarm behaviour.

引用次数: 0

A simulation of integrated gasification, energy generation, and GIS from solid waste in Jazan Municipalities, KSA (Part 1: Gasification)

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 10.1016/j.asej.2025.103282

Mohamed Hassan , Salih Eltahir Elmarud Ali , Mahmoud Abdelrahim Abdelgiom

This paper aims to use GIS software to choose the energy plant’s ideal location based on side selection criteria and to build a simulation using Aspen Plus software to estimate the gas production. The outcome of this spatial analysis using GIS will typically encompass a prioritized list of potential sites, accompanied by visual maps that illustrate suitable locations, constraints, and accessibility. The simulation was validated using experimental and simulation data from the literature on plasma gasification. The results of this study showed good matching with the literature data. After the simulation was validated, it was used to study the case of Jazan region MSW. The results showed that the gas composition is 12.93 % H₂, 8.68 % CO₂, 3.08 % N₂, 0.08 % H₂S, and 31.11 % CO, with a temperature of 1210 °C. This gas was transferred to energy production simulation to generate energy, which will be discussed in part 2 of this paper.

引用次数: 0

Pentagonal fuzzy fractional three-stage sustainable transportation network problem incorporating extension principle

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 10.1016/j.asej.2025.103261

B. Baranidharan , Gunji Bala Murali , Zechun Cao , G.S. Mahapatra

This study presents a framework for addressing the fuzzy fractional three-stage transportation network (FFTSTN) in the context of sustainable conveyance. The proposed model considers the transportation costs and profits involved in moving goods from manufacturers to storage godowns, storage godowns to distributors, and distributors to consumers. The primary aim of this study is to mitigate transportation expenses and assess transportation's environmental viability through reducing emissions. A generalized pentagonal fuzzy number (GPFN) is employed to address the uncertainty of parameters of the three-stage transportation network. The study established a methodology to explore solutions for the FFTSTN model without de-fuzzifying GPFNs. Additionally, it explored the economic sustainability and future transportation prospects using the extension principle to solve the proposed FFTSTN system. This solution approach considers the nonlinearity of the objective function by utilizing the Charnes-Cooper transformation technique for the problem. A numerical example shows applicability, validity, and comparison between the compromise solutions.

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引用次数: 0

Development of Fe-reinforced PLA-based composite filament for 3D printing: Process parameters, mechanical and microstructural characterization

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 10.1016/j.asej.2025.103279

Melisa Memiş, Dilşad Akgümüş Gök

The most used raw materials in 3D printers, commonly known as Fused Deposition Modeling (FDM), are filaments. These filaments are obtained by going through heating, injection, cooling, winding and coiling stages in the filament extruder machine. FDM technology, which is used especially for prototype production purposes, is expected to be used more widely due to its increased mass production capacity, recyclability, environmental friendliness and waste reduction. In this study, before the production of composite filament, preliminary tests were carried out with polylactic acid (PLA), acrylonitrile butadiene styrene (ABS) and polyethylene terephthalate glycol (PET-G) polymer granules in a laboratory type filament extruder machine, and the process parameters were determined for each polymer filament. Since the optimum process parameters (temperature, injection rate, extrusion rate, and winding rate) were obtained in PLA, composite filament was produced by reinforcing 5% iron (Fe) powder into the PLA matrix in the same extruder machine. The produced filaments were subjected to tensile, hardness, FTIR, surface roughness and SEM-EDS analyses. Analysis has shown that Fe-reinforced PLA-based composite filament increases the hardness of pure PLA filament by 21.15%, tensile strength by 49.60% and increases the surface roughness by 4 times. As a result, it was determined that 5%Fe powder added to PLA improved the mechanical properties but negatively affected the surface roughness.

{"title":"Development of Fe-reinforced PLA-based composite filament for 3D printing: Process parameters, mechanical and microstructural characterization","authors":"Melisa Memiş, Dilşad Akgümüş Gök","doi":"10.1016/j.asej.2025.103279","DOIUrl":"10.1016/j.asej.2025.103279","url":null,"abstract":"<div><div>The most used raw materials in 3D printers, commonly known as Fused Deposition Modeling (FDM), are filaments. These filaments are obtained by going through heating, injection, cooling, winding and coiling stages in the filament extruder machine. FDM technology, which is used especially for prototype production purposes, is expected to be used more widely due to its increased mass production capacity, recyclability, environmental friendliness and waste reduction. In this study, before the production of composite filament, preliminary tests were carried out with polylactic acid (PLA), acrylonitrile butadiene styrene (ABS) and polyethylene terephthalate glycol (PET-G) polymer granules in a laboratory type filament extruder machine, and the process parameters were determined for each polymer filament. Since the optimum process parameters (temperature, injection rate, extrusion rate, and winding rate) were obtained in PLA, composite filament was produced by reinforcing 5% iron (Fe) powder into the PLA matrix in the same extruder machine. The produced filaments were subjected to tensile, hardness, FTIR, surface roughness and SEM-EDS analyses. Analysis has shown that Fe-reinforced PLA-based composite filament increases the hardness of pure PLA filament by 21.15%, tensile strength by 49.60% and increases the surface roughness by 4 times. As a result, it was determined that 5%Fe powder added to PLA improved the mechanical properties but negatively affected the surface roughness.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 2","pages":"Article 103279"},"PeriodicalIF":6.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178413","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}

引用次数: 0

Multi-Objective optimization in the construction of steel-concrete composite columns with carbon emission considerations: Pareto front development and decision-making

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 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.

引用次数: 0

Improved heat conduction in hybrid nanofluid across a slippery rotating cylinder with solar radiation and Lorentz forces

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 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 (

Ti O_{2}

), which has great chemical and physical stability. In numerous types of heat exchangers, including circular tubes, double tubes, and shell and tubes,

Ti O_{2}

nanoparticles dispersed in ordinary fluids were widely used. The present work is to investigate the behavior of titanium dioxide

Ti O_{2} -

copper oxide

CuO / H_{2} O

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

Ti O_{2} - C u O / H_{2} O

as hybrid nanofluids and

Ti O_{2} / H_{2} O

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

Ti O_{2} - C u O / H_{2} O

hybrid nanofluid as compared to

Ti O_{2} / H_{2} O

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}

引用次数: 0

Optical solitons for the concatenation model with fractional temporal evolution

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 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.

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引用次数: 0

Advancing multiple sclerosis diagnosis through an innovative hybrid AI framework incorporating Multi-view ResNet and quantum RIME-inspired metaheuristics

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-01 DOI: 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}

引用次数: 0

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数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Ain Shams Engineering Journal

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