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  1. 1
    Teaching and learning via chatbots with immersive and machine learning capabilities

    Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

    Published 2019
    “…These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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  2. 2
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…On the other hand, the superior performance of the genetic algorithm that implements an extended diversity control mechanism demonstrates that more competent genetic algorithms can be designed through customized operators. …”
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  3. 3
    Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization

    Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization by Nur Iffah, Mohamed Azmi, Kamal Arifin, Mat Piah, Wan Azhar, Wan Yusoff, F. R. M., Romlay

    Published 2017
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  4. 4
    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0

    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0 by Chong, Agnes Wen Lin

    Published 2023
    “…Framework can facilitate the performanceofManufacturing Firms. The purpose is to interpret the implementation of businessanalytic ultimately affects the overall performance of the organization. and creatingafeasible framework. …”
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  5. 5
    Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines

    Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines by Noroziroshan, Alireza

    Published 2009
    “…Mixed model assembly line is a kind of manufacturing systems which is able to deal with variable market demand. …”
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  6. 6
    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes

    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes by Nor Atiqah, Zolpakar, Lodhi, Swati Singh, Pathak, Sunil, Sharma, Mohita Anand

    Published 2020
    “…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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  7. 7
    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
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  8. 8
    A proposed variable parameter control chart for monitoring the multivariate coefficient of variation

    A proposed variable parameter control chart for monitoring the multivariate coefficient of variation by Chew, X. Y., Khoo, B. C., Khaw, K. W., Yeong, W. C. *, Chong, Z. L.

    Published 2019
    “…Formulae and algorithms to optimize the various performance measures are discussed. …”
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  9. 9
    Optimization machining parameters in pocket milling using genetic algorithm and mastercam

    Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

    Published 2023
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  10. 10
    DESIGN AND DEVELOPMENT OF HIGH-ACCURACY MACHINE FOR WIRE BENDING

    DESIGN AND DEVELOPMENT OF HIGH-ACCURACY MACHINE FOR WIRE BENDING by Mustafa F.F., Hussein O., Fakhri O.F., Sabri A.H.

    Published 2023
    “…Firstly, using the proposed bending machine, in which the proposed algorithm is applied. Secondly, using the bending machine implemented without applying the proposed algorithm. …”
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  11. 11
    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…The proposed strategy is dependent on modified Zimmermanns approach for handling all inexact operating costs, data capacities, and demand variables. The SD algorithm is employed to balance exploitation and exploration in MSA, thereby resulting in efficient and effective (speed and quality) solution for the APP model. …”
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  12. 12
    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain

    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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  13. 13
    Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms

    Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms by Fauzi, Nur Faiqah, Mohamad Jaya, Abdul Syukor, Mohammad Jarrah, Mu’ath Ibrahim, Akbar, Habibullah

    Published 2017
    “…In this study, an approach in modeling surface roughness of Titanium Nitrite (TiN) coating using Response Surface Method (RSM) has been implemented to obtain a proper output result. In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. …”
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  14. 14
    IMPLEMENTATION OF ADVANCED PROCESS CONTROL FOR FLOW CONTROL APPLICATION

    IMPLEMENTATION OF ADVANCED PROCESS CONTROL FOR FLOW CONTROL APPLICATION by ROSLI, NURFATIHAH SYALWIAH

    Published 2013
    “…A general MPC control algorithm is developed using MATLAB/Simulink Toolboxes. …”
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  15. 15
    Revolutionizing video analytics: a review of action recognition using 3D

    Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

    Published 2024
    “…It also addresses the practicalities of implementing action recognition algorithms in real-world situations, which include tools like deep learning frameworks, pre-trained models, open-source libraries, cloud services, GPU acceleration, and evaluation metrics. …”
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  16. 16
    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC) manufacturing

    Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)... by Mohd Fazil, Azlan Faizal, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

    Published 2019
    “…This new framework will be able to provide range of possible recall rate from minimum to maximum, to identify which classifier algorithm performs the best for given dataset. The selected model can be implemented into actual manufacturing flow to screen predicted bad die for maximum cost scrapping avoidance and capacity savings.…”
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  17. 17
    Optimizing Neural Network Prediction of Composite Fatigue Life Under Variable Amplitude Loading Using Bayesian Regularization

    Optimizing Neural Network Prediction of Composite Fatigue Life Under Variable Amplitude Loading Using Bayesian Regularization by Megat-Yusoff, Puteri Sri Melor

    Published 2009
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  18. 18
    Dynamics and control of a biodiesel transesterification reactor

    Dynamics and control of a biodiesel transesterification reactor by Mjalli, F.S., San, L.K., Yin, K.C., Hussain, Mohd Azlan

    Published 2009
    “…The input-output relationship between the effective process variables was studied and the control system synthesis revealed a two-by-two control system. …”
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  19. 19
    Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology

    Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

    Published 2015
    “…Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected, namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. …”
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  20. 20
    Production quantity estimation using an improved artificial neural network

    Production quantity estimation using an improved artificial neural network by Dzakiyullah, Raden Nur Rachman

    Published 2015
    “…However, this decision cannot be implemented on the next production due to uncertainty/fluctuated condition. …”
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