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  1. 1
    Virtual reality in algorithm programming course: practicality and implications for college students

    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
    “…The reliability of VR supports various variations in learning, including learning programming algorithms. …”
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  2. 2
    The impact of virtual reality on programming algorithm courses on student learning outcomes

    The impact of virtual reality on programming algorithm courses on student learning outcomes by Dewi, Ika Parma, Ambiyar, Effendi, Hansi, Giatman, Muhammad, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
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  3. 3
    Cognitive benefits of employing multiple AI voices as specialist virtual tutors in a multimedia learning environment

    Cognitive benefits of employing multiple AI voices as specialist virtual tutors in a multimedia learning environment by Liew, Tze Wei, Tan, Su Mae, Chan, Tak Jie, Tian, Yang, Ahmad, Faizan

    Published 2025
    “…To address this gap, we draw on multimedia learning and cognitive models to investigate the effects of using multiple AI voices as specialist virtual tutors for distinct programming algorithm subtopics on cognitive load and learning outcomes. …”
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  4. 4
    Deep Reinforcement Learning For Control

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…Learning a model in a virtual environment might potentially fail to generalize to the actual world. …”
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    Monograph
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  5. 5
    An empirical study of density and distribution functions for ant swarm optimized rough reducts

    An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…The density and distribution functions are two common types of Gaussian distribution representation. …”
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  6. 6
    Facilitating English Language teaching through AI- based drama in Palestine

    Facilitating English Language teaching through AI- based drama in Palestine by Bsharat, Tahani, Sheikh Ahmad, Ismail

    Published 2025
    “…Artificial Intelligence (AI) has the potential to significantly reshape the landscape of education through the integration of AI- powered tools, personalized learning algorithms, and virtual and augmented reality. …”
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  7. 7
    Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system

    Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system by Krishnan P.S., Kiong T.S., Koh J., Yap D.

    Published 2023
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  8. 8
    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…The simulations of single and multi-objective function optimisations have been carried out using MATLAB for meta-heuristic techniques on the IEEE 33-bus and 69-bus radial distribution networks. …”
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  9. 9
    Assessing the potential of laboratory instructional tool through Synthesia AI: a case study on student learning outcome / Jacqueline Joseph

    Assessing the potential of laboratory instructional tool through Synthesia AI: a case study on student learning outcome / Jacqueline Joseph by Joseph, Jacqueline

    Published 2023
    “…Synthesia AI is a cutting-edge technology that revolutionizes students’ immersive learning experience. With its advanced machine learning algorithms, Synthesia AI can generate photorealistic video content featuring virtual actors and presenters that can be programmed to speak in multiple languages, accents, and even emotional tones. …”
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  10. 10
    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems

    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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  11. 11
    A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms

    A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms by Pesaran H.A M., Huy P.D., Ramachandaramurthy V.K.

    Published 2023
    “…Circuit theory; Energy efficiency; Optimization; Dg siting; Dg sizings; Distributed generators; Distributed resources; Objective functions; Optimal allocation; Optimal DG allocation; Optimization algorithms; Distributed power generation…”
    Review
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  12. 12
    Levy slime mould algorithm for solving numerical and engineering optimization problems

    Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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  13. 13
    Distributed generation allocation to reduce losses and improve voltage profile genetic algorithm: article

    Distributed generation allocation to reduce losses and improve voltage profile genetic algorithm: article by Abdol Azis, Hazriq Syahmie

    Published 2010
    “…Genetic Algorithm (GA) was used as the solving tool, which referring two determined aim the problem is defined and objective function is introduced. …”
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  14. 14
    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale

    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

    Published 2021
    “…The application aims to develop a machine learning program using the algorithm of Support Vector Machine or Gaussian Process Regression to successfully predict the contact angle. …”
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  15. 15
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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  16. 16
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. …”
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  17. 17
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. …”
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  18. 18
    Slice sampler algorithm for generalized pareto distribution

    Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

    Published 2018
    “…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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  19. 19
    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm

    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

    Published 2017
    “…Therefore, there are various algorithms that could be applied in order to integrate distribution generation units into the distribution network. …”
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  20. 20
    Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft

    Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft by Salvinder Singh, Karam Singh, Shahrum, Abdullah, Nik Abdullah, Nik Mohamed

    Published 2015
    “…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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