A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…However, it limits the critical problems of high time complexity, computational cost, difficulty to understand, and reduced level of security. …”

FPGA-based Parallel Hardware Architecture for Real-time Object Classification by Qasaimeh, Murad Mohammad

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Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing by Xin Li (51274)

Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine by Majd A. AbuAlrob (22392505)

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

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

“…Then, we provide a comprehensive review of the most widely used DRL algorithms to address RRAM problems, including the value- and policy-based algorithms. …”

Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers by Zain Ul Abideen Tariq (17984107)

“…<p dir="ltr">The evolving landscape of beyond 5G and 6G wireless communication systems in smart urban environments faces numerous interference-related challenges posed by legitimate and illicit devices. …”

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas by Marwan Dhuheir (19170898)

“…In this context, we formulate the problem as a non-linear programming (NLP) optimization problem aimed at maximizing the total EH IoT devices and determining the optimal trajectory paths for UAVs while adhering to the constraints related to the maximum time duration, the UAVs’ maximum energy consumption, and the minimum data rate to achieve a reliable transmission. Due to the complexity of the problem, the combinatorial nature of the formulated problem, and the difficulty of obtaining the optimal solution using conventional optimization problems, we propose a lightweight meta-RL solution capable of solving the problem by learning the system dynamics. …”

Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique by Iqbal Hassan (22155274)

Multigrid solvers in reconfigurable hardware. (c2006) by Kasbah, Safaa J.

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Measuring ripple effect for object-oriented programs. (c2004) by Salem, Hani Hassan

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UML-based regression testing for OO software by Mansour, Nashat

“…For the second phase, we present algorithms for detecting system level changes in the interaction overview diagram. …”
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Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials by Ghouti, Lahouari

“…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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Collision-Free Autonomous Navigation Solution for Mobile Wheeled by Elsergany, Ahmed Moataz Mahmoud

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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

“…Link prediction aims to identify missing or future connections between entities of a complex system, when modeled as a network. This research problem has attracted significant attention due to its relevance in numerous fields. …”
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Assigning proctors to exams using scatter search. (c2006) by Zeidan, Moujab Moustapha

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DRL-Based IRS-Assisted Secure Visible Light Communications by Danya A. Saifaldeen (19498705)

“…Therefore, we proposed a Deep Reinforcement Learning (DRL) solution based on Deep Deterministic Policy Gradient (DDPG) algorithm to solve the highly complex SC problem by adjusting the BF weights and mirror orientations. …”

A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants by Khan, T.

“…The use of U-model alleviates the computational complexity of on-line nonlinear controller design that arises when using other modelling frame works such as NARMAX model. …”
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Improving Rule Set Based Software Quality Prediction by Azar, Danielle

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