Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks by Amirhossein Taherpour (19273879)

“…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …”

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

“…<p>The energy internet (EI) is evolving toward decentralized, data-rich, and time-critical operation, where legacy optimization often fails to meet complexity, scalability, and real-time constraints. …”

A novel network-based SIS framework for improved GA performance by Tohme, Rawane

“…Genetic algorithms have long been used to solve complex optimization problems by mimicking natural selection processes. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”

ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints by Mohammed Al Disi (16855407)

“…However, it is usually associated with computational complexity at the decoding end, increasing the latency of the system. …”

Computational evluation of protein energy functions by Mansour, Nashat

“…Proteins are organic compounds made up of chains of amino acids that fold into complex 3-dimensional structures based on their chemical and physical properties. …”
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A Stochastic Approach To Solving The Weight Setting Problem in OSPF Networks by Shaik, Muzibur Rehman

“…OSPF calculates the shortest paths from each source to all destinations using the Dijkstra’s algorithm based on the weights assigned to the links. …”
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A hybrid approach for XML similarity by Tekli, Joe

“…Various algorithms for comparing hierarchically structured data, e.g. …”
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Leveraging UAVs for Coverage in Cell-Free Vehicular Networks by Samir, Moataz

“…Then, we leverage deep reinforcement learning to propose an approach for learning the optimal trajectories of the deployed UAVs to efficiently maximize the coverage, where we adopt Actor-Critic algorithm to learn the vehicular environment and its dynamics to handle the complex continuous action space. …”
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Advancing Interpretability in Sequential Models Through Generative AI Rationalization Using GPT-4 by Mohammed Rasol Al Saidat

“…Additionally, we devise a rationale generation algorithm that achieves a balance between succinctness and informativeness. …”
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Exploring Digital Competitiveness through Bayesian Belief Networks by Qazi, Abroon

“…Unlike conventional ranking models that assume equal weighting of pillars, this study uses Bayesian belief network (BBN) models to capture complex, non-linear relationships, offering a more precise identification of critical determinants. …”
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A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem by Abu Zitar, Raed

“…Capacitated Vehicle routing problem is NP-hard scheduling problem in which the main concern is to findthe best routes with minimum cost for a number of vehicles serving a number of scattered customersunder some vehicle capacity constraint. Due to the complex nature of the capacitated vehicle routingproblem, metaheuristic optimization algorithms are widely used for tackling this type of challenge.Coronavirus Herd Immunity Optimizer (CHIO) is a recent metaheuristic population-based algorithm thatmimics the COVID-19 herd immunity treatment strategy. …”
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A Concurrency control model for multilevel secure object-oriented databases by Haraty, Ramzi

“…However, with the emergence of new and complex applications, research in object-oriented security is gaining more prominence. …”
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Active distribution network type identification method of high proportion new energy power system based on source-load matching by Qinlin, Shi

“…A large number of distributed new energy and flexible loads are connected to the distribution network, resulting in increasingly complex source load characteristics and supply and demand situations. …”
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Online Control and Optimization of Directional Drilling by unknown

“…Gravitational Search Algorithm (GSA) is developed to search for optimal settings of the proposed controller. …”
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Hybrid Deep Learning-based Models for Crop Yield Prediction by Alexandros Oikonomidis (12050497)

“…<p dir="ltr">Predicting crop yield is a complex task since it depends on multiple factors. …”

Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

“…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

“…Conventional Building Energy Management methods suffer from a high dimensional and complex control environment. In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”

User-centric strategies for resource management in heterogeneous wireless networks with QoS considerations by Abbas, Nadine Fawaz

“…We formulate the problem as an optimization that aims at maximizing the number of served users while maintaining target quality of service using device-to-device cooperation, in-device caching, and intelligent channel allocation. Due to the complexity of the problem, we design sub-optimal hierarchical tree-based algorithms for real-time operation taking into account realistic constraints. …”
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Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…In this study, I conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM, CNN-BILSTM-LSTM, and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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