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  1. 1
    On a new transmuted three-parameter lindley distribution and its applications

    On a new transmuted three-parameter lindley distribution and its applications by Xi, Yuhang, Lu, Hezhi, Liang, Fei

    Published 2024
    “…In this paper, a new transmuted three-parameter Lindley distribution (TTHPLD) is established using the transmutation map method, which includes the Lindley distribution, two-parameter Lindley distribution, transmuted two-parameter Lindley distribution and three-parameter Lindley distribution as special cases. …”
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  2. 2
    A new Gompertz-three-parameter-lindley distribution for modeling survival time data

    A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

    Published 2025
    “…In this paper, a new survival distribution is introduced. It is a mixture of the Gompertz distribution and three-parameter-Lindley distribution. …”
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  3. 3
    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach

    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

    Published 2024
    “…Poverty prediction was conducted using a random forest (RF) algorithm and poverty mapping was conducted using the K-Means algorithm. …”
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  4. 4
    Surface and Near-surface Moisture Content Assessment using Multi-Temporal Satellite Images over Perak Tengah and Manjung Regions, Malaysia

    Surface and Near-surface Moisture Content Assessment using Multi-Temporal Satellite Images over Perak Tengah and Manjung Regions, Malaysia by A. Hassaballa , Abdalhaleem, Matori , Abdul Nasir, M. Shafri, Helmi Z.

    Published 2013
    “…Secondly, a success rate curve based on spatiostatistical technique was used for validating the generalized maps in order to study the high-low distribution of θ within NOAA and MODIS generalized maps. …”
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  5. 5
    Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm

    Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm by Rashid, Roslina, Jamaluddin, Hishamuddin, Saidina Amin, Nor Aishah

    Published 2005
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  6. 6
    Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm

    Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm by Roslina, Rashid, Hishamuddin, Jamaluddin, Nor Aishah, Saidina Amin

    Published 2011
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  7. 7
    Surface Moisture Content Retrieval from Visible/Thermal Infrared Images and Field Measurements

    Surface Moisture Content Retrieval from Visible/Thermal Infrared Images and Field Measurements by Abdalla HASSABALLA, Abdalhaleem, MATORI , Abdul Nasir, Mohd SHAFRI, Helmi Zulhaidi

    Published 2013
    “…In this study, NOAA/AVHRR satellite was used to estimate the surface temperature and satellite estimated soil moisture content as input parameters leading to estimate the evapotranspiration over Perak Tengah & Majung regions in Malaysia. …”
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  8. 8
    Optimization algorithms for multipath transfer over asymmetric paths using concurrent multipath transfer stream control transmission protocol

    Optimization algorithms for multipath transfer over asymmetric paths using concurrent multipath transfer stream control transmission protocol by Abass, Abdulridha Hanash

    Published 2016
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  9. 9
    The Newton-like properties of the updating mechanism of a model-reality differences algorithm

    The Newton-like properties of the updating mechanism of a model-reality differences algorithm by Ahmad, Rohanin, Abd. Aziz, Mohd. Ismail

    Published 2003
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  10. 10
    Missing value estimation methods for data in linear functional relationship model

    Missing value estimation methods for data in linear functional relationship model by Adilah Abdul Ghapor, Yong Zulina Zubairi, A.H.M. Rahmatullah Imon

    Published 2017
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  11. 11
    Using Machine Learning Algorithms to Estimate the Compressive Property of High Strength Fiber Reinforced Concrete

    Using Machine Learning Algorithms to Estimate the Compressive Property of High Strength Fiber Reinforced Concrete by Dai, L., Wu, X., Zhou, M., Ahmad, W., Ali, M., Sabri, M.M.S., Salmi, A., Ewais, D.Y.Z.

    Published 2022
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  12. 12
    Optimum MV Feeder Routing and Substation siting and rating in Distribution Network

    Optimum MV Feeder Routing and Substation siting and rating in Distribution Network by Hasan, Ihsan Jabbar, Ab Ghani, Mohd Ruddin, Gan, Chin Kim

    Published 2014
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  13. 13
    The impact of executive function and aerobic exercise recognition in obese children under deep learning

    The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

    Published 2025
    “…The OpenPose motion recognition model optimized with STN and Lucas–Kanade optical flow algorithm not only exhibits superior performance in keypoint detection and pose estimation but also positively influences the physical health and functional capacity of children.…”
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  14. 14
    An intelligent method to estimate the inertia matrix of a robot arm for active force control using on-line neural network training scheme

    An intelligent method to estimate the inertia matrix of a robot arm for active force control using on-line neural network training scheme by Hussein, Shamsul Bahri, Jamaluddin, Hishamuddin, Mailah, Musa

    Published 1999
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  15. 15
    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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  16. 16
    Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data

    Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data by Jayapal V., Zain A.F.M.

    Published 2024
    “…A multilayer feed-forward network with a back propagation algorithm is applied to estimate the TEC over Parit Raja (Lat. 1�52?…”
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  17. 17
    Traffic management algorithms for LEO satellite networks

    Traffic management algorithms for LEO satellite networks by Huyop @ Ayop, Fahrul Hakim

    Published 2016
    “…The important parameters measured in the simulation are delay rate, throughput rate and fair traffic distribution rate. …”
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  18. 18
    Time Synchronization Using Distributed Observer Algorithm With Sliding Mode Control For Wireless Sensor Network

    Time Synchronization Using Distributed Observer Algorithm With Sliding Mode Control For Wireless Sensor Network by Yew, Tze Hui

    Published 2015
    “…This research describes a novel distributed observer algorithm which uses augmented sliding mode control element to compensate for clock skew for wireless sensor network (WSN), in the world of Internet of Things (IoT). …”
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  19. 19
    Static and self-scalable filter range selection algorithms for peer-to-peer networks

    Static and self-scalable filter range selection algorithms for peer-to-peer networks by Kweh, Yeah Lun

    Published 2011
    “…The static filter range selection algorithm and the self-scalable selection algorithm are able to reduce the number of rounds and the number of messages needed, increase the success rate but longer execution time compared to the Loo (2005) selection algorithm. …”
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  20. 20
    Dynamic replication aware load blanced scheduling in distributed environment / Said Bakhshad

    Dynamic replication aware load blanced scheduling in distributed environment / Said Bakhshad by Said Bakhshad, Bakhshad

    Published 2018
    “…Grid computing is an effective distributed and adaptable processing network that manages a huge number of data applications. …”
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