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  1. 1

    Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz

    Published 2015
    “…In this paper, an approach termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is basically based on Gravitational Search Algorithm (GSA), is proposed to combine these two parts into a simultaneous solution. …”
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    Article
  2. 2

    Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images by Ali Hussein Aboali, Maged Yahya

    Published 2018
    “…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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    Thesis
  3. 3

    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

    Published 2022
    “…Artificial neural network (ANN)-field-oriented control (FOC) was used in the hybrid flux system. The function of the ANN was to improve speed-tracking performance, and the learning rate of the ANN inside the indirect FOC’s structure trained using the Levenberg-Marquardt (LM) algorithm was varied in order to increase speed-tracking accuracy when combined with the improved ANN speed controller. …”
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    Thesis
  4. 4

    Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

    Published 2012
    “…A series of training patterns are constructed by employing between two images.Moreover,the work takes accomplishing maximum robustness and transparency into consideration.HPSO method is used to estimate the multiple parameters involved in the model. …”
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    Thesis
  5. 5

    Comparative study of 3D reconstruction methods from 2D sequential images in sports by Azrulhizam Shapi’i, Pichak, Sanaz, Mohd Syazwan Baharuddin, Iida, Hiroyuki

    Published 2020
    “…Six recent methods were selected based on they focused on recovery fully automated system for estimating 3D human pose for 2D joint location. …”
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    Article
  6. 6

    Enhancing navigation accuracy of Turtlebot3 Burger mobile robot by Muhammad Haniff, Gusrial, Muhammad Luqman Hakim, Abdullah, Nur Aqilah, Othman, Hamzah, Ahmad

    Published 2024
    “…To address this challenge, the Kalman Filter algorithm is implemented in this robot, as it is widely used for mobile robot navigation and system integration. …”
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    Conference or Workshop Item
  7. 7

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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    Book Chapter
  8. 8

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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    Thesis
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    Performance Analysis of Motion Estimation Algorithms on Digital Video Images by Ali, Nur Alisa, Ja'afar, Abd Shukur, Abd Rahim, Rosman, Mohammed Napiah, Zul Atfyi Fauzan, Md Yusop, Azdiana, Meor Said, Maizatul Alice

    Published 2011
    “…In the BMME, search patterns with different shapes or sizes and the center-biased characteristics of motion vector (MV) have large impact on the search speed (search points) and peak signal-to-noise ratio (PSNR) as the quality of video images. These basic algorithms are Full Search and other two fast search methods. …”
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    Article
  12. 12

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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    Thesis
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    JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation by Abu, Ahmad Zaidee

    Published 2008
    “…The proposed approach uses a frequency domain combinational framework of coefficients scrambling with Key Scheduling Algorithm based (KSA-based) permutation. …”
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    Thesis
  17. 17

    Effort Estimation Model for Function Point Measurement by Koh, Tieng Wei

    Published 2007
    “…This research work has generated an algorithmic effort estimation model for function points measurement. …”
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    Thesis
  18. 18

    Parametric coefficient genetic algorithm for domestic water consumption / Nurul Nadia Hani by Hani, Nurul Nadia

    Published 2019
    “…Previous method which employs per capita water consumption (PCC) basically finding average of water consumption in different state of Malaysia which-is largely inaccurate. …”
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    Thesis
  19. 19

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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    Thesis
  20. 20

    Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm by Abdul Rahman, Azrul Azwan, Joe Yee, Tan, A Rahman, Muhamad Arfauz, Salleh, Mohd Rizal, Bilge, Pinar

    Published 2020
    “…The predictive part determines the feasible schedule to be used for a flow shop which is generated using a combination of rule-based simulation and optimization: first, using the optimization algorithm to compute a rough plan, followed by using a rule based simulation system to locally fine tune the plan to obtain the final schedule. …”
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    Article