Ain Shams Engineering Journal最新文献

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Development of a novel wireless telemetric brain stimulator for behavioral studies in rodents

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-07 DOI: 10.1016/j.asej.2025.103290

V. Milner Paul , Jijo Francis , Smriti Menon , Loitongbam Surajkumar Singh , Adarsh V. Parekkattil , Shuma Adhikari

Brain simulators are moving the field of neuroscience at a rapid pace due to their wide applicability in treating neurodegenerative disorders. Although continuing advances in the field have made significant breakthroughs, most brain simulators remain too expensive for general clinical applications We developed a user friendly, cost effective, multi-channel wireless brain stimulator that delivers output with high precision. The multichannel output of this device makes it amenable to conducting behavioral studies on different regions of the brain in rodents. The efficacy of our head-mountable device is substantiated by conducting intracranial and intracortical experiments in rats. We tested the output of the device by changing the ifrequency (100 Hz–400 Hz), amplitude, pulse width and current (10 µA – 1 mA) of the stimulator by altering the ON time period of the pulses and resistor values. We have defined optimum frequency (140 Hz) for the intracranial experiment and lower and upper threshold currents for the intracortical experiment. The successful feasibility of this device has been demonstrated invivo in rats and invitro in saline solution. Real-time experiments like Intracranial Self Stimulation (ICSS) and Intracortical Microstimulation (ICMS) tests were successful during the animal experiment to evaluate this brain stimulator. Our device has widespread applicability in conducting behavior-based studies and deriving insights into various mechanistic pathways in rodent brain.

{"title":"Development of a novel wireless telemetric brain stimulator for behavioral studies in rodents","authors":"V. Milner Paul , Jijo Francis , Smriti Menon , Loitongbam Surajkumar Singh , Adarsh V. Parekkattil , Shuma Adhikari","doi":"10.1016/j.asej.2025.103290","DOIUrl":"10.1016/j.asej.2025.103290","url":null,"abstract":"<div><div>Brain simulators are moving the field of neuroscience at a rapid pace due to their wide applicability in treating neurodegenerative disorders. Although continuing advances in the field have made significant breakthroughs, most brain simulators remain too expensive for general clinical applications We developed a user friendly, cost effective, multi-channel wireless brain stimulator that delivers output with high precision. The multichannel output of this device makes it amenable to conducting behavioral studies on different regions of the brain in rodents. The efficacy of our head-mountable device is substantiated by conducting intracranial and intracortical experiments in rats. We tested the output of the device by changing the ifrequency (100 Hz–400 Hz), amplitude, pulse width and current (10 µA – 1 mA) of the stimulator by altering the ON time period of the pulses and resistor values. We have defined optimum frequency (140 Hz) for the intracranial experiment and lower and upper threshold currents for the intracortical experiment. The successful feasibility of this device has been demonstrated invivo in rats and invitro in saline solution. Real-time experiments like Intracranial Self Stimulation (ICSS) and Intracortical Microstimulation (ICMS) tests were successful during the animal experiment to evaluate this brain stimulator. Our device has widespread applicability in conducting behavior-based studies and deriving insights into various mechanistic pathways in rodent brain.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103290"},"PeriodicalIF":6.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349072","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

Predicting hydropower generation: A comparative analysis of Machine learning models and optimization algorithms for enhanced forecasting accuracy and operational efficiency

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-07 DOI: 10.1016/j.asej.2025.103299

Chunyang Wang, Chao Li, Yudong Feng, Shoufeng Wang

Exponential global population growth and rapid technological advancements have increased electricity demand, strained the fossil fuel-reliant energy infrastructure, and exacerbated environmental issues like greenhouse gas emissions and climate change. Transitioning to sustainable energy sources is essential for balancing energy needs with environmental conservation. Hydropower is a significant renewable resource due to its cost-effectiveness, low environmental impact, and capability to meet peak electricity demands. Optimizing hydropower generation is crucial for addressing economic and environmental concerns, though it requires comprehensive monitoring and understanding of energy conversion processes. Machine Learning techniques such as integrated Gradient Boosting and Categorical Gradient Boosting, optimized with Hunger Games search, Chaos game optimization, and Archimedes Optimization Algorithm algorithms, are used to forecast and optimize hydropower generation. The dataset involved hydropower generation data from 1819 records gathered from a particular watershed. The framework is designed to tackle challenges in the prediction of hydropower generation by effectively managing complex, multivariate data. Between the tested models, the integrated CatBoost- hunger Games search model brings out exceptional predictive accuracy, with a Coefficient of Determination of 0.9075 and a Root Mean Square Error of 45.2130 during testing. This examination’s contributions comprise the creation of a scalable, data-driven method for hydropower optimization, the illustration of its capability to decrease prediction errors remarkably, and its practical application in renewable energy management. These reports highlight the potential of the proposed configuration to elevate hydropower prediction accuracy and support the transition to sustainable energy frameworks.

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引用次数: 0

A study on state dependent single server queue with Markov modulated arrival under hyper exponential service times using block matrix structured approach

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-06 DOI: 10.1016/j.asej.2025.103293

Raghavendran. R, V. Vidhya

In this research work we study the correlation impact between the inter arrival time and service time of packets arriving to the system for transmission. By assuming the arrival in modulated form the service utilization provided by server acts with varying rate of service. The queuing quantities are obtained in closed form by using matrix geometric method. The expected waiting length of packets and other performance measures are calculated in the stationary state distribution of the process. We establish the analytic frame work of the Markov model between the inter arrival and service time to get correlation impact to study the behavioural effect in queue length, time and other performance measures.

引用次数: 0

An efficient way to represent the processors and their connections in omega networks

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-06 DOI: 10.1016/j.asej.2025.103287

Savari Prabhu , T. Jenifer Janany , Paul Manuel

The understanding of the structure of a network can be enhanced efficiently with distance-reliant parameters. The metric dimension is one such parameter with numerous variations and a rich source of literature. The subject of our study pertains to the metric dimension and a few of its variants for a broadly used interconnection network-omega network. Omega networks provide a structured and scalable interconnect solution for distributed memory architectures. In large-scale data centers where massive amounts of data are processed and analyzed, omega networks are used in the network infrastructure to interconnect servers and storage systems. The key feature of omega networks is their ability to provide multiple disjoint paths between any pair of nodes in the network. This characteristic helps reduce congestion and improve overall system performance, especially in large-scale parallel computing environments where data communication is a critical factor. Along with metric dimension, we provide the exact values of edge metric dimension, fault-tolerant metric and edge metric dimensions for this widely known network. We also compare these parameters with those of other predominant interconnection networks, such as the butterfly, Beneš, and fractal cubic networks, and we observe that the omega network has significantly lower values for these parameters compared to the other networks.

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引用次数: 0

Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-06 DOI: 10.1016/j.asej.2025.103301

Mushtaq Muhammad Umer , Hein Venter , Owais Muhammad , Tamoor Shafique , Fuad A. Awwad , Emad A.A. Ismail

Many sectors in aerial transportation use unmanned aircraft vehicles (UAVs) extensively. This becomes even more challenging in complex environments where not only it is required to avoid obstacles, but it also must be maintained for a prolonged period of time. This paper presents a novel approach to increase UAV autonomy through safe and efficient flight trajectory design. An optimization problem is formulated with external and internal safety constraints, and traversing collision free paths. The proposed work offers an energy efficient RRT algorithm, which is used to assess multiple trajectory alternatives. The simulation results confirm the achieved performance in finding the optimal energy path while obeying to the safety constraint. The data and performance metrics, show the system operated in a safe and energy efficient manner. This work provides a unified framework for UAV trajectory planning that guarantees a trade-off between safety and energy efficiency.

引用次数: 0

FractalNet-based key generation for authentication in Voice over IP using Blockchain

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-05 DOI: 10.1016/j.asej.2025.103286

Vajjala Sreenivasulu, Chinthaginjala Ravikumar

Voice over Internet Protocol (VoIP) has seen significant growth since the proliferation of the Internet, primarily due to its low-cost structure and simplicity in deployment. However, VoIP systems face critical security challenges, including threats to integrity, authenticity, and confidentiality. Addressing these concerns necessitates the development of a secure and efficient key agreement and authentication framework. Thus, this paper proposes a new deep learning technique called FractalNet-based key generation (FractalNet-keyGen) for authentication in VoIP using Blockchain. The implementation of the proposed methodology is as follows: Here, several entities, such as VoIP users, admin, smart contract, as well as minor nodes are considered. Moreover, the steps that are considered include Blockchain association, Registration, Initialization, Authentication, Key generation, as well as Verification. Besides, the established FractalNet-keyGen approach attained improved performance with values of validation time, memory usage, response time, key complexity, packet loss ratio, latency, and jitter of 20.37 sec, 15.35 MB, 2.06 sec, 0.942, 1.85%, 0.302s, and 0.275s.

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引用次数: 0

Laplace Adomian decomposition method for integro differential equations on time scale

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.2025.103271

Shafiq Hussain, Feroz Khan

The aim of this work is to probe the Laplace Adomian decomposition method (LADM) for some certain linear and non-linear integro-differential equations on an arbitrary time scales. Although, several researchers have treated integro-differential equations (linear/nonlinear) utilizing different techniques, but most of them were based on classical calculus. In particular, [10] have catered the integro-differential equations on time scale using Adomian decomposition method (ADM). Whereas [28] have entertained the initial value problems with ADM on time scales. However, there exist no piece of work in literature that addressed integro-differential equations using LADM on time scales. Hence, in this work, that gap is covered. Moreover, the proposed method on time scale is effective in the sense that it mitigates the integration steps which otherwise come while solving with ADM. Lastly, examples and solutions in Sections 3 and 4 that exactly match those found by ADM are used to validate the suggested approach.

引用次数: 0

A framework for enhancing safety planning in oil and gas construction projects

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.2024.103257

Abdullah Alsehaimi , Ahsan Waqar , Dorin Radu , Ciprian Bratu , Hamad Almujibah , Omrane Benjeddou

The construction and building industry is a major driver of economic growth; however, safety performance remains a key challenge. This research aimed to develop an effective framework to improve safety planning for oil and gas construction projects. A mixed methods approach was utilized, including a questionnaire survey of 167 construction practitioners and interviews with project engineers. Results showed materials/equipment factors as most significant, with “damaged equipment” having the highest RII of 0.821. The second highest factor was “poor equipment condition” (RII = 0.814), followed by “limited material transportation protections” (RII = 0.804). Among management factors, “performance pressure” scored highest (RII = 0.871), while “insufficient staffing” was lowest (RII = 0.775). For worker factors, “poor communication” ranked first (RII = 0.818) and “lack of knowledge” last (RII = 0.779). In terms of site factors, “accidents from carelessness” was predominant (RII = 0.811) but “limited workspace” was least considerable (RII = 0.768). Further statistical analysis using Spearman’s correlation coefficient showed that the perspectives of contractors, consultants, and safety/health officers had positive and significant correlations in the range of 0.35 to 0.45. This research provides empirical evidence on the most influential safety factors in oil and gas projects and proposes a practical framework for contractors and managers to improve safety planning and performance. The framework offers a proactive risk-based approach to reducing accidents and protecting workers in this hazardous industry.

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引用次数: 0

Detection of community emotions through Sound: An Investigation using the FF-Orbital Chaos-Based feature extraction model

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.2024.103248

Li Xu , Arif Metehan Yildiz , Ilknur Tuncer , Fatih Ozyurt , Sengul Dogan , Turker Tuncer

Community Emotion Detection (CED) is important to public safety and sound forensics. It enables the analysis of collective emotions in dynamic environments such as public events, protests, and emergencies.

This research presents a new, cost-effective, automatic, and self-organized classification model for CED. The major objective of this research is to show the effectiveness of signal processing in the CED research area. The largest known CED sound dataset was constructed for this study. This dataset was curated to investigate the presented automated CED model’s classification capability. The curated CED sound dataset consists of 5,051 three-second overlapping sound samples categorized as negative, neutral, and positive emotions. This dataset increases the model’s generalizability by reflecting diverse acoustic and emotional scenarios.

A self-organized feature extraction function, called the Forward-Forward Pattern-Based Feature Generator (FF-Orbital), is introduced. The FF-Orbital autonomously selects the most suitable pattern from six predefined patterns. This eliminates the need for manual feature engineering. Additionally, a multi-level feature extraction method is enabled by integrating the Unbalanced Tree Multilevel Discrete Wavelet Transform (UTMDWT). This method generates frequency bands that provide extract spatial and frequency-domain features. Iterative Neighborhood Component Analysis (INCA) has selected the most informative features. INCA is a self-organized feature selector. Classification is then performed using a Bayesian-optimized Support Vector Machine (SVM).

Tests were conducted using 10-fold cross-validation. The model achieved a classification accuracy of 98.81%. These results demonstrate the usability of the CED model and its effectiveness in digital forensics, public safety, and community-level sentiment analysis.

This work makes a significant contribution to the CED research domain by providing a feature-engineering-based alternative to resource-intensive deep learning models. The results show that the proposed model is valuable for signal processing and sound forensics.

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引用次数: 0

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

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Ain Shams Engineering Journal

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