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  1. 1
    A comprehensive analysis of surface electromyography for control of lower limb exoskeleton

    A comprehensive analysis of surface electromyography for control of lower limb exoskeleton by Abdelhakim, Deboucha

    Published 2016
    “…A parametric model based on Hill Muscle Model (HMM) to estimate the knee joint moment is developed for both experiments protocols. …”
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  2. 2
    Semiparametric estimation with profile algorithm for longitudinal binary data

    Semiparametric estimation with profile algorithm for longitudinal binary data by Suliadi, Suliadi, Ibrahim, Noor Akma, Daud, Isa

    Published 2013
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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  3. 3
    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data

    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

    Published 2011
    “…The major research findings were as follows: 1) the non-parametric and parametric estimation methods using the right and interval censoring types produced highly efficient cure rate parameters when the censoring rate was decreased to the minimum possible; 2) Non-parametric estimation of the cure fraction using interval censored data based on Turnbull estimator resulted in more precise cure fraction than the Kaplan Meier estimator considering the interval midpoint to represent the exact life time; 3) The parametric estimation of the cure fraction based on the exponential distribution and right and interval censoring types produced more consistent estimates than the Weibull distribution especially in case of heavy censoring; 4) Parametric estimation of the cure fraction was more efficient when some covariates had been involved in the analysis than when covariates had been excluded; and 5) the nonparametric estimation method is the viable alternative to the parametric one when the data set contains substantial censored observations while in the case of low censoring the parametric method is more attractive.…”
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  4. 4
    Non-parametric maximum likelihood estimation of cure fraction for interval survival data.

    Non-parametric maximum likelihood estimation of cure fraction for interval survival data. by I. Aljawadi, Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2011
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  5. 5
    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper

    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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  6. 6
    Parameter adaptation for ant colony system in wireless sensor network

    Parameter adaptation for ant colony system in wireless sensor network by Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana, Kamioka, Eiji

    Published 2019
    “…The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). …”
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  7. 7
    Parametric maximum likelihood estimation of cure fraction using interval-censored data

    Parametric maximum likelihood estimation of cure fraction using interval-censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Al-Omari, Mohamad

    Published 2013
    “…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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  8. 8
    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.

    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data. by I. Aljawadi , Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2011
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  9. 9
    An intelligent framework for modelling and active vibration control of flexible structures

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…Parametric approaches include linear parametric modelling of the system using recursive least squares (RLS) and genetic algorithms (GAS); and non-parametric approaches include multi-layered perceptron neural networks (MLP-NNs) and adaptive neuro-fuzzy inference systems (ANFIS) are employed. …”
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  10. 10
    GEE-smoothing spline in semiparametric model with correlated nominal data

    GEE-smoothing spline in semiparametric model with correlated nominal data by Ibrahim, Noor Akma, Suliadi

    Published 2010
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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  11. 11
    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques

    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

    Published 2003
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  12. 12
    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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  13. 13
    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…The IDBA-AFW evaluates the fitness of relay nodes based on multiple criteria, such as energy efficiency, throughput, and end-to-end delay. Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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  14. 14
    Semiparametric binary model for clustered survival data

    Semiparametric binary model for clustered survival data by Arlin, Rifina, Ibrahim, Noor Akma, Arasan, Jayanthi, Abu Bakar, Mohd Rizam

    Published 2014
    “…A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. …”
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  15. 15
    Analysis of the ECG signal using SVD-based parametric modelling technique

    Analysis of the ECG signal using SVD-based parametric modelling technique by Baali, Hamza, Salami, Momoh Jimoh Emiyoka, Akmeliawati, Rini, Aibinu, Abiodun Musa

    Published 2011
    “…A two-stage procedure is then used to estimate the EDS model parameters. Prony’s algorithm is first used to obtain initial estimates of the model, while the Gauss-Newton method is applied to solve the non-linear least-square optimisation problem. …”
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  16. 16
    Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold

    Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold by Ali Taweab, Fauzia

    Published 2015
    “…The proposed model has sound motivation in relapse of cancer and can be used in other disease models. The parametric maximum likelihood estimation method is employed to verify the performance of the MCM within the framework of the expectation-maximization (EM) algorithm while the estimation methods for other models are employed in a simpler and straightforward setting. …”
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  17. 17
    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. In particular, the focus is on the non-parametric estimation of the slope parameter and the robustness of this technique is compared with the maximum likelihood estimation and the Al-Nasser and Ebrahem (2005) method. …”
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  18. 18
    Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm

    Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm by Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Zuwairie, Ibrahim

    Published 2021
    “…In this work, these parameters are optimized using dynamic inertia weight artificial bees colony (DIW-ABC) optimization algorithm. …”
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  19. 19
    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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  20. 20
    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model

    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model by MuhamadSafiih, L, Kamil, A.A., Abu Osman, M.T.

    Published 2014
    “…Through this approach, a flexible fuzzy concept hybrid with the semi-parametric sample selection models known as Fuzzy Semi-Parametric Sample Selection Model (FSPSSM). …”
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