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  1. 1
    A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment

    A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment by Ahmad, Idawaty, K. Subramaniam, Shamala, Othman, Mohamed, Ahmad Zukarnain, Zuriati

    Published 2011
    “…GUS is one of the existing TUF/UA scheduling algorithms that consider the Time/Utility Function (TUF) of the executed tasks in its scheduling decision. …”
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  2. 2
    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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  3. 3
    A discrete event simulation for utility accrual scheduling in uniprocessor environment

    A discrete event simulation for utility accrual scheduling in uniprocessor environment by Ahmad, Idawaty, K. Subramaniam, Shamala, Othman, Mohamed, Ahmad Zukarnain, Zuriati

    Published 2011
    “…GUS is one of the existing TUF/UA scheduling algorithms that consider the Time/Utility Function (TUF) of the executed tasks in its scheduling decision in a uniprocessor environment. …”
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  4. 4
    An enhanced ant colony system algorithm for dynamic fault tolerance in grid computing

    An enhanced ant colony system algorithm for dynamic fault tolerance in grid computing by Saufi, Bukhari

    Published 2020
    “…However, ACS algorithm does not consider the resource fitness during task scheduling which leads to poor load balancing and lower execution success rate. …”
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  5. 5
    Hybrid scheduling and dual queue scheduling

    Hybrid scheduling and dual queue scheduling by Mahmood, Ahmad Kamil

    Published 2009
    “…Our research work involves the design and development of new CPU scheduling algorithms (the Hybrid Scheduling Algorithm and the Dual Queue Scheduling Algorithm) with a view to optimization. …”
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  6. 6
    Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids

    Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

    Published 2009
    “…The first stage is to develop new DLT based models for multiple sources scheduling. …”
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  7. 7
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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  8. 8
    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem

    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem by Ibrahim Abaker , Targio Hashem

    Published 2017
    “…The proposed algorithm is evaluated using tasks scheduling in the scheduling load simulator and validated using statistical modeling. …”
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  9. 9
    Hybrid scheduling and dual queue scheduling

    Hybrid scheduling and dual queue scheduling by A., Oxley, S.N.M., Shah, A.K., Mahmood

    Published 2009
    “…Our research work involves the design and development of new CPU scheduling algorithms (the Hybrid Scheduling Algorithm and the Dual Queue Scheduling Algorithm) with a view to optimization. …”
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  10. 10
    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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  11. 11
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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  12. 12
    Café Web Based System Using Priority Scheduling Approach

    Café Web Based System Using Priority Scheduling Approach by Fatimah, Ghazali, Rohana, Ismail, Mohamad Hariz, Hasni

    Published 2017
    “…The priority scheduling algorithm is based on Control Processing Unit scheduling algorithm where it has a priority to execute tasks. …”
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  13. 13
    Crosstalk-Free Scheduling Algorithms for Routing in Optical Multistage Interconnection Networks

    Crosstalk-Free Scheduling Algorithms for Routing in Optical Multistage Interconnection Networks by Raja Mohd Auzar, Tengku Dian Shahida

    Published 2009
    “…Based on Zero algorithms, a Modified Zero algorithm is developed to achieve a crosstalk-free version of the algorithm. …”
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  14. 14
    AI powered asthma prediction towards treatment formulation: an android app approach

    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. …”
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  15. 15
    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…While numerous methods have been proposed, machine learning (ML) is the most popular approach that has been applied across the globe. …”
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  16. 16
    Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction

    Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction by Roslan M.F., Hannan M.A., Jern Ker P., Begum R.A., Indra Mahlia T.M., Dong Z.Y.

    Published 2023
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  17. 17
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…LACE algorithm is executed in 1000, 2000, 3000 and 4000 servers to see the performance in Cloud datacenter. …”
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  18. 18
    Greedyzero-based scheduling algorithm to route in optical low stage interconnection networks

    Greedyzero-based scheduling algorithm to route in optical low stage interconnection networks by Moudi, Mehrnaz

    Published 2012
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  19. 19
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  20. 20
    Comparative study on job scheduling using priority rule and machine learning

    Comparative study on job scheduling using priority rule and machine learning by Murad, Saydul Akbar, Zafril Rizal, M Azmi, Abu Jafar, Md Muzahid, Al-Imran, Md.

    Published 2021
    “…Implementation of a suitable scheduling algorithm is critical in order to properly use cloud resources. …”
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