Search Results - parallel integration ((conversion algorithm) OR (prediction algorithm))

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    Parallel Kalman filter-based multi-human tracking in surveillance video by Yussiff, A.-L., Yong, S.-P., Baharudin, B.B.

    Published 2014
    “…A Kalman filter is a recursive algorithm which predict the state variables and further uses the observed data to correct the predicted value. …”
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    Conference or Workshop Item
  3. 3

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. This study integrates the Black-winged Kite Algorithm (BKA), Finite Element Analysis (FEA), Backpropagation Neural Network (BPNN), and response surface optimization techniques. …”
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    Article
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    Integrated OBF-NN models with enhanced extrapolation capability for nonlinear systems by H., Zabiri, M., Ramasamy, T. D. , Lemma, Maulud, Abdulhalim

    Published 2013
    “…For this purpose, a residuals-based identification algorithm using parallel integration of linear orthonormal basis filters (OBF) and neural networks model is developed and analyzed under range extrapolations. …”
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    Citation Index Journal
  6. 6

    An integrated priority-based cell attenuation model for dynamic cell sizing by Amphawan, Angela, Omar, Mohd Nizam, Din, Roshidi

    Published 2012
    “…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
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    Article
  7. 7

    Design and implementation of multimedia digital matrix system by Chui, Yew Leong, Ramli, Abdul Rahman, Perumal, Thinagaran, Sulaiman, Mohd Yusof, Ali, Mohd Liakot

    Published 2005
    “…Due to the issues of signal integrity in high-speed digital design, a new adaptive channel synchronization algorithm has been developed. …”
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  8. 8

    Constant lock circuit for DC micro-grid system by Mohammed, Asaad Abduljabbar

    Published 2017
    “…So,it requires voltage compatibility of all sources associated with the DC link bus for keeping the stability of the DC link at a constant value, Moreover, parallel sources connection for sharing power at a DC micro-grid have problems such as reverse current, and degradation of power conversion efficiency, due to a slight difference between output voltages. …”
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    Thesis
  9. 9

    Computational prediction of changes in brain metabolic fluxes during Parkinson’s disease from mRNA expression by Supandi, Farahaniza, Van Beek, Johannes H.G.M.

    Published 2018
    “…To this end we apply the Least-squares with Equalities and Inequalities algorithm integrated with Flux Balance Analysis (Lsei-FBA). …”
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    Article
  10. 10

    Super resolution imaging using modified lanr based on separable filtering by Somadina, Ike Chidiebere

    Published 2019
    “…The underlying idea is to process and reconstruct information in low and high frequency sub-bands based on separable property of neighbourhood filtering to achieve fast parallel and vectorized operation, while enhancing algorithmic performance by reducing computational burden resulting from computing the weighted function of every pixel for each pixel in an image. …”
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    Thesis
  11. 11

    Unified GPU Technique to Boost Confidentiality, Integrity and Trim Data Loss in Big Data Transmission by Bhattacharjee, S., Rahim, L.B.A., Watada, J., Roy, A.

    Published 2020
    “…Moreover, multiple executions of distinct security algorithms for maintaining confidentiality and integrity reduce throughput and add a large number of additional bits as security overhead that hampers the robustness against data loss. …”
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    Article
  12. 12

    An Efficient Energy Aware Adaptive System-On-Chip Architecture For Real-Time Video Analytics by Ahmed, Hisham Ahmed Ali

    Published 2016
    “…A careful analysis of the algorithm and efficient utilization of Zynq resources results in highly parallelized and pipelined architecture outperforms the state-of-the-art. …”
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    Thesis
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    Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model by Megat Syahirul Amin, Megat Ali, Azlee, Zabidi, Nooritawati, Md Tahir, Ihsan, Mohd Yassin, Eskandari, Farzad, Azlinda, Saadon, Mohd Nasir, Taib, Abdul Rahim, Ridzuan

    Published 2024
    “…System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. …”
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    Article
  14. 14

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…In parallel, the automated performance and manual delineation for WMH identification is validated to determine the degree of similarity between both the methods. …”
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    Book Section
  15. 15

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…In parallel, the automated performance and manual delineation for WMH identification is validated to determine the degree of similarity between both the methods. …”
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    Thesis
  16. 16

    WiFi-based human activity recognition through wall using deep learning by Wong, Yan Chiew, Ahmed Abuhoureyah, Fahd Saad, Mohd Isira, Ahmad Sadhiqin

    Published 2023
    “…Furthermore, a deep learning algorithm based on RNN with an LSTM algorithm is used to classify the activity instances indoors, achieving up to 97.5% accuracy in classifying seven activities. …”
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    Article