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  1. 1

    A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.] by Wan Xing, Sultan Mohd, Mohd Rizman, Johari, Juliana, Ahmat Ruslan, Fazlina

    Published 2023
    “…Deep learning-based object detection algorithms can be categorized into three main types: end-to-end algorithms, two-stage algorithms, and one-stage algorithms. …”
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  2. 2

    Evolution, design, and future trajectories on bipedal wheel-legged robot: A comprehensive review by Zulkifli, Mansor, Irawan, Addie, Mohammad Fadhil, Abas

    Published 2023
    “…Emphasizing the need for adaptable, terrain-aware control algorithms, the review explores the untapped potential of machine learning and soft robotics in enhancing performance across diverse operational scenarios. …”
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    Machine learning modeling for radiofrequency electromagnetic fields (RF-EMF) signals from mmWave 5G signals by Al-Jumaily, Abdulmajeed, Sali, Aduwati, Riyadh, Mohammed, Wali, Sangin Qahtan, Li, Lu, Osman, Anwar Faizd

    Published 2023
    “…5G is the next-generation mobile communication technology that is expected to deliver better data rates than Long-Term Evolution (LTE). …”
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  7. 7

    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

    Published 2026
    “…In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). …”
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    Automating commercial video game development using computational intelligence by Tse, Guan Tan, Teo, Jason Tze Wi, Patricia Anthony

    Published 2011
    “…Pac-man. The resulting algorithm is referred to as an Evolution Strategies Neural Network or ESNet. …”
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    Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

    Published 2015
    “…These algorithms can improve mobile stations’ quality of service as well as guarantee seamless mobility across the Long-Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) technologies. …”
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    A conceptual Malaysian private healthcare university-of-the-future business model: staying relevant in the digital and post-covid era by Saiid, Muhammad, Bah, Ahmadou Pathe, Ahmad Dahlan, Abdul Rahman

    Published 2022
    “…The results from the analysis and design of the BMC and SC indicate that the principal changes required to digitally transform the university to a UotF include: the adoption of an open learning system for flexible and lifelong learning; transitioning the campus to a more 'smart', eco-friendly and sustainable campus; incorporating the latest artificial intelligence, machine learning algorithms, and data analytics to improve the university‘s management systems and enhance delivery mechanisms for teaching and learning; and to improve community engagement relationships and partnerships to deliver value to the economic, health and safety of the society, as well as to leverage the open learning system to provide curated courses to niche categories of students locally and globally.…”
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    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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    An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S. M. M Yassin, S. M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

    Published 2018
    “…The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry.The malicious software which is specifically designed to disrupt,damage,or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective.To solve the problem,this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately.The integrated classifier algorithm applied to examine,classify and generate rules of the pattern and program behaviour of system call information.The outcome then revealed the integrated classifier of J48 and JRip outperforming the other classifier with 100% detection of attack rate. …”
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    An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S.M.M Yassin, S.M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

    Published 2018
    “…The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry. …”
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