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Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments by Findi, Ahmed H. M., Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil, Hassan, Mohd Khair

“…The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. …”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…As a consequence, the agent is expected to have trained behaviors and navigation without crashing. The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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Optimized processing of satellite signal via evolutionary search algorithm by Hassan, Azmi, Othman, Rusli, Tang, Kieh Ming

“…Researchers from the Satellite Navigation Research Group (SNAG) of UTM are currently conducting a research program that mitigates the effect of the Anti-Spoofing (AS) policy. …”
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LinguaBridge – academic digital scaffold by Gnanasagaran, Puvana, Jamaludin, Syaliana

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Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

“…Machine learning frameworks have been utilised to facilitate intelligence as operational mechanism in intelligence embedded system such as learning system, prediction protocol and robot navigation system. …”
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

“…Firstly, a Priority-Based Fair Scheduling (PBFS) algorithm has been introduced to schedule jobs so that jobs can access the required resources at optimal times. …”
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Robotics in Education by Norashikin, M. Thamrin, Addie, Irawan, Zurita, Zulkifli, Syed Abdul Mutalib, Al Junid, Megat Syahirul Amin, Megat Ali, Anwar P. P., Abdul Majeed

“…The AI section discusses machine learning, path-planning algorithms (e.g., A* search, SLAM), and classroom case studies. …”
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A real-time traffic sign recognition system for autonomous vehicle using Yolo / Nurul Paudziah Aida Mohd Paudzi by Mohd Paudzi, Nurul Paudziah Aida

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Double Deep RL-based strategy for UAV-assisted energy harvesting optimization in disaster-resilient IoT networks by Elmadina, Nahla Nur, Saeed, Rashid A, Saeid, Elsadig, Ali, Elmustafa Sayed, Nafea, Ibtehal, Ahmed, Mayada A, Mokhtar, Rania A, Khalifa, Othman Omran

“…Due to the problem's complexity, we propose a lightweight DDRL solution capable of efficiently learning system dynamics. Extensive simulations and comparisons with Deep RL and DDPG algorithms demonstrate the superior performance of DDRL in enhancing EH, covering strategic locations effectively, and achieving high satisfaction and accuracy rates.…”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

“…Re-execution of all test cases can be expensive as there might be wasting resources, could be costly and time consuming. …”
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