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  1. 1
    Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations

    Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations by Siri, Zailan

    Published 2004
    “…The method used here is actually have been tailored made for the purpose of parallel machine where the subsequent functions evaluations do not depend on the previous function evaluations. …”
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  2. 2
    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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  3. 3
    Enhancing performance of XTS cryptography mode of operation using parallel design

    Enhancing performance of XTS cryptography mode of operation using parallel design by Ahmed Alomari, Mohammad

    Published 2009
    “…In addition, the parallel XTS mode was also simulated using Twofish and RC6 encryption algorithms. …”
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  4. 4
    Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.

    Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs. by Ismail, Fudziah, Siri, Zailan, Othman, Mohamad, Suleiman, Mohamed

    Published 2009
    “…Diagonally Implicit Runge-Kutta (DIRK) methods are amongst the most useful and cost-effective methods for solving initial value problems but the dependency of the functions evaluations on the previous functions evaluations makes DIRK method not so favourable for parallel computers. …”
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  5. 5
    Communication and computational cost on parallel algorithm of PDE elliptic type

    Communication and computational cost on parallel algorithm of PDE elliptic type by Alias, Norma

    Published 2009
    “…Due to this needs, this paper presents the parallel performance evaluations of algorithms that will be discussed in term of communication and computational cost.…”
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  6. 6
    An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification

    An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification by Wan Azman,, Wan Nur Fadhlina Syamimi, Ku Azir, Ku Nurul Fazira, Mohd Khairuddin, Adam

    Published 2024
    “…Several studies have examined the factors influencing food waste behaviour and management. This work was motivated by the lack of previous research on machine learning and electronic noses to detect contamination from leftover cooked food. …”
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  7. 7
    A Distributed Memory Parallel Fourth-Order IADEMF Algorithm

    A Distributed Memory Parallel Fourth-Order IADEMF Algorithm by Mansor N.A., Zulkifle A.K., Alias N., Hasan M.K.

    Published 2023
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  8. 8
    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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  9. 9
    Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems

    Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems by Shakeel Ahmed, Kamboh, Zubair, Ahmed Kalhoro, Kashif, Ali Abro, Jane, Labadin

    Published 2017
    “…For that reason, a Data Parallel Algorithm for EHD model (DPA-EHD) is designed. …”
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  10. 10
    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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  11. 11
    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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  12. 12
    Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha

    Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha by Mustapha, Muhammad Firdaus

    Published 2018
    “…Finally, this research designs and implements an enhanced parallel SOM architecture through combining two parallel methods which are network and data partitioning. …”
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  13. 13
    A spark-based parallel fuzzy C median algorithm for web log big data

    A spark-based parallel fuzzy C median algorithm for web log big data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Sarkar, Rashal, Chalil, Aboosalih Kakkat

    Published 2022
    “…Based on the Rand Index and SSE (sum of squared error), the parallel Fuzzy C median algorithm's performance is evaluated in the PySpark platform. …”
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  14. 14
    Automation of plastic waste sorting through robotic technology

    Automation of plastic waste sorting through robotic technology by Chong, Yoong Kiat

    Published 2025
    “…A YOLOv8 deep learning model, trained on a custom dataset of waste images, was integrated with the ByteTrack algorithm to provide real-time object detection and tracking. …”
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  15. 15
    IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management

    IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management by Eugine Teh, Yin Jie, Chee Soon, Chong, Rozaimi, Ghazali, Hazriq Izzuan, Jaafar, Muhamad Fadli, Ghani, Howe Cheng, Teng, Nur Farhanah, Zulkipli, Siaw Hong, Liew

    Published 2025
    “…A Convolutional Neural Network (CNN) trained on a dataset of aluminium cans and plastic bottles is deployed for waste identification. Real-time monitoring is enabled by IoT sensors and machine vision algorithms, facilitating precise detection of waste levels and material types. …”
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  16. 16
    Smart waste management system with IoT monitoring

    Smart waste management system with IoT monitoring by Kalitazan, Sachein, Muniswaran, Suvarshan, Velan, Sheshan, Muniswaran, Suvathithan, Shah, Dhanesh

    Published 2023
    “…Through advanced data analytics and machine learning algorithms, the platform predicts waste accumulation patterns, optimizes collection routes, schedules pickups based on fill-level data, and detects any abnormal conditions. …”
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  17. 17
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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  18. 18
    A review of the parallel algorithms for solving multidimensional PDE problems

    A review of the parallel algorithms for solving multidimensional PDE problems by Alias, Norma, Islam, Md. Rajibul

    Published 2010
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  19. 19
    Solving ordinary differential equations using block multistep method

    Solving ordinary differential equations using block multistep method by Mehrkanoon, Siamak

    Published 2011
    “…The parallelism across the system is considered for the implementation of the parallel block methods. …”
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  20. 20
    Energy-Aware Clustering Routing for Mobile Ad-Hoc Sensor Networks (MASNETS)

    Energy-Aware Clustering Routing for Mobile Ad-Hoc Sensor Networks (MASNETS) by Amanda, Hendrick

    Published 2020
    “…There are many potential applications of MASNETs such as military sensor networks to detect and gather information about enemy movements and some sensor nodes are also mounted on animals or other moving objects, which can sense and collect information such as body temperature. …”
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