A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

“…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”

Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries by Assayed, Suha Khalil

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Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

“…Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (38/47, 81%), and the most used algorithm was the neural network (23/47, 49%). …”

Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

“…The two movies are Wahed Tani which translates to (someone else) and Amahom which translate to (their uncle), Three datasets were employed, and several categorization models were compared across them. Prior to performing sentiment analysis, it is necessary to prepare the data so that it may be used to train machine learning (ML) algorithms. …”
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Adaptive Federated Learning Architecture To Mitigate Non-IID Through Multi-Objective GA-Based Efficient Client Selection by Ajaj, Mohamad

“…Existing solutions still have several constraints leading to suboptimal model performance and slow convergence. In this paper, we propose a novel approach that incorporates genetic algorithms with an enhanced client selection strategy, utilizing client metadata rather than raw data. …”
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Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles by Warren, Thomas

“…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …”
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Video Streaming over D2D Networks by Ahmed, Ibtihal Mohamed Taha

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Estimating Bridge Deterioration Age Using Artificial Neural Networks by AL HUSSEIN, ASEEL

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A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem by Abu Zitar, Raed

“…To evaluate the modified CHIO, twosets of data sets are used: the first data set has ten Synthetic CVRP models while the second is an ABEFMPdata set which has 27 instances with different models. …”
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Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”

Scheduling and allocation in high-level synthesis using stochastic techniques by Sait, Sadiq M.

“…High-level synthesis is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. …”
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A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications by Sharafeddine, Sanaa

“…However, the computational as well as memory access requirements of compression algorithms could consume more energy than simply transmitting data uncompressed. …”
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Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants by Hamad Al Shamsi, Jawaher

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Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”

A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…This review synthesizes evidence from more than 500 peer-reviewed studies published between 2020 and 2026, mapping DRL applications across distributed generation, transmission, distribution, energy storage systems, energy markets, local energy management, grid security, and data privacy. We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”

Structural similarity evaluation between XML documents and DTDs by Tekli, J.

“…Our approach is based on the concept of tree edit distance, as an effective and efficient means for comparing tree structures, XML documents and DTDs being modeled as ordered labeled trees. It is of polynomial complexity, in comparison with existing exponential algorithms. …”
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Performance Prediction Using Classification by MOOLIYIL, GITA

“…A comprehensive evaluation requires that multiple models with different algorithms were analyzed using key performance measures. …”
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