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  1. 1
    Enhancement of parallel thinning algorithm for handwritten characters using neural network

    Enhancement of parallel thinning algorithm for handwritten characters using neural network by Engkamat, Adeline

    Published 2005
    “…This project aims to improve a parallel thinning algorithm that satisfies two fundamental requirements of thinning, namely the processing speed and the quality of skeletons. …”
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  2. 2
    Image based autonomous indoor parallel parking assist on omni-directional vehicle (ODV)

    Image based autonomous indoor parallel parking assist on omni-directional vehicle (ODV) by Edwind, Liaw Yee Kang

    Published 2016
    “…The image processing algorithm is first developed using Visual Studio C++ and OpenCV. …”
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    Undergraduates Project Papers
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  3. 3
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…Parallel processing and matrix convolution inside wavelet transform process is the most prominent study in this research. …”
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    Final Year Project / Dissertation / Thesis
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  4. 4
    Local search approaches for patient scheduling problem in parallel operating theatre

    Local search approaches for patient scheduling problem in parallel operating theatre by Alimin, Nur Neesha

    Published 2020
    “…In the first phase, pre-processing stage, combination of pre-processing stage with low-level heuristic and genetic algorithm are used.The different types of LS are applied in the second phase of scheduling. …”
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  5. 5
    Thermal Properties And Ground-State Structures Of Pure And Alloy Nanoclusters Via Molecular Dynamics Simulation

    Thermal Properties And Ground-State Structures Of Pure And Alloy Nanoclusters Via Molecular Dynamics Simulation by Ong, Yee Pin

    Published 2018
    “…However, the methods of post-processing and determining the pre-melting and melting range of nanoclusters at specific composition differ in every research. …”
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  6. 6
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, Norshuhani, Oxley, Alan, Abu Bakar, Zainab

    Published 2012
    “…Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc.This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism.A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism.The English corpus is the translated version of the Malay corpus.Hence, these two corpora are treated as parallel corpora. …”
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  7. 7
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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  8. 8
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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  9. 9
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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  10. 10
    Studies on flat CORDIC implementation in field programmable gate arrays (FPGA) / Meera Subramaniam

    Studies on flat CORDIC implementation in field programmable gate arrays (FPGA) / Meera Subramaniam by Meera , Subramaniam

    Published 2004
    “…The successive replacement of the basic CORDIC equations to generate the parallelized Flat CORDIC ones requires that the direction of all the rotations be pre-computed. …”
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  11. 11
    A novel association rule mining approach using TID intermediate itemset

    A novel association rule mining approach using TID intermediate itemset by Aqra, Iyad, Herawan, Tutut, Ghani, Norjihan Abdul, Akhunzada, Adnan, Ali, Akhtar, Bin Razali, Ramdan, Ilahi, Manzoor, Raymond Choo, Kim-Kwang

    Published 2018
    “…Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. …”
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  12. 12
    Dynamic force-directed graph with weighted nodes for scholar network visualization

    Dynamic force-directed graph with weighted nodes for scholar network visualization by Mohd. Aris, Khalid Al-Walid, Ramasamy, Chitra, Mohd Aris, Teh Noranis, Zolkepli, Maslina

    Published 2022
    “…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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  13. 13
    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Under-sampled data is acquired in parallel imaging to expedite the MRI scan process, which leads to aliased images. …”
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  14. 14
    A novel association rule mining approach using TID intermediate itemset

    A novel association rule mining approach using TID intermediate itemset by Aqra, Iyad, Herawan, Tutut, Norjihan, Abdul Ghani, Akhunzada, Adnan, Ali, Akhtar, Ramdan, Razali, Ilahi, Manzoor, Choo, Kim-Kwang Raymond

    Published 2018
    “…Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. …”
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  15. 15
    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata

    K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

    Published 2018
    “…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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  16. 16
    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living

    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

    Published 2024
    “…At the initial stage, the AOADL-TC model pre-processes tweet data to convert uniform data into a useful format. …”
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  17. 17
    Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider

    Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider by Omer Fadlelmola Elkhider, Samih

    Published 2011
    “…The studies show beyond technical algorithms, physical aspects plays a big rule in client server model. …”
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  18. 18
    Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems

    Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems by Ooi , Woi Seng

    Published 2007
    “…Image segmentation is an important pre-processing step which has a great influence on the performance of CBIR systems. …”
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  19. 19
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

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

    Published 2018
    “…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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    Book Section
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  20. 20
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

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

    Published 2018
    “…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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