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  1. 1
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  2. 2
    Multi-dimensional Data Visualisation using Mobile Augmented Reality

    Multi-dimensional Data Visualisation using Mobile Augmented Reality by Rehman Ullah, Khan, Yin, Bee Oon, Ahmad Sofian, Shminan, Lee, Jun Choi, Chen, Jacqueline How Ting

    Published 2020
    “…Therefore, this algorithm uses AR to provide a multi-display solution for improved data visualisation after processing, summarising and classifying data. …”
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  3. 3
    Effectiveness of silhouette rendering algorithms in terrain visualisation

    Effectiveness of silhouette rendering algorithms in terrain visualisation by Che Mat, Ruzinoor, Visvalingam, Mahes

    Published 2002
    “…Silhouette Rendering Algorithms have been successfully used in various applications such as communicating shape and cartoon rendering.This paper explores how effective silhouette rendering algorithms could be used in terrain visualisation. …”
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  4. 4
    Visualisation System of COVID-19 Data in Malaysia

    Visualisation System of COVID-19 Data in Malaysia by Rehman Ullah, Khan, NOR SYAZA, SYAMIMI, CLADIA SIMBUT, MAMBANG, IVY, THOMAS, TZI NI, WEE

    Published 2021
    “…Pandemics are highly unlikely events, therefore, we need a system to understand the statistics about the pandamic. Machine learning algorithms can analyse the data and then we can plan for handling the pandamic. …”
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  5. 5
    3D terrain visualisation for GIS: A comparison of different techniques

    3D terrain visualisation for GIS: A comparison of different techniques by Ruzinoor, Che Mat, Mohamed Shariff, Abdul Rashid, Mahmud, Ahmad Rodzi, Pradhan, Biswajeet

    Published 2011
    “…The results of this paper will be of help to the users in identifying the best technique of terrain visualisation suitable for GIS data.…”
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  6. 6
    Visualisation System of COVID-19 Data in Malaysia

    Visualisation System of COVID-19 Data in Malaysia by Rehman Ullah, Khan, NOR SYAZA, SYAMIMI, CLADIA SIMBUT, MAMBANG, IVY, THOMAS, NI WEE, TZI

    Published 2021
    “…Pandemics are highly unlikely events, therefore, we need a system to understand the statistics about the pandamic. Machine learning algorithms can analyse the data and then we can plan for handling the pandamic. …”
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  7. 7
    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets

    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

    Published 2021
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  8. 8
    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets

    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

    Published 2021
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  9. 9
    A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES

    A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES by Ling, Chien

    Published 2020
    “…Clustering is used to identify the intrinsic grouping of a set of unlabelled data. It can be applied in data mining exploration and statistical data analysis. …”
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  10. 10
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  11. 11
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  12. 12
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  13. 13
    A case study : 2D Vs 3D parallel differential equation toward tumor cell detection on multi-core parallel computing atmosphere

    A case study : 2D Vs 3D parallel differential equation toward tumor cell detection on multi-core parallel computing atmosphere by Islam, Md. Rajibul, Alias, Norma

    Published 2010
    “…In order to detect tumour cells, 2D and 3D Partial Differential Equations (PDE) are considered and compared by using Multi-Core parallel computing atmosphere with visualisation, communication and data analysis. The performance analysis of Multi-Core computing is presented in provisions of speedup, efficiency, effectiveness and temporal performance where the use of 2D and 3D PDEs and parallel algorithms was found to give in remarkable results.…”
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  14. 14
    Dynamic modeling by usage data for personalization systems

    Dynamic modeling by usage data for personalization systems by Aghabozorgi, S.R., Teh, Y.W.

    Published 2009
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  15. 15
    PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER

    PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER by Tay, Guo Hong

    Published 2019
    “…This is because both Naive Bayes and SVM are baseline algorithm used in text classification. In the end, a visualisation of HFMD Disease Map is presented to visualize the city that suffer HFMD outbreak using geo-located tweet that related with HFMD. …”
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  16. 16
    Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area

    Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area by Teoh, Chin Chuang, Dr., Shattri, Mansor, Abdul Rashid, Mohamed Shariff, Noordin, Ahmad

    Published 2011
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  17. 17
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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  18. 18
    Secured agriculture sensor data based on end-to-end encryption using raspberry pi

    Secured agriculture sensor data based on end-to-end encryption using raspberry pi by Choo, Jia Huey

    Published 2025
    “…The system integrates multiple robust encryption algorithms—AES-128, AES-256, ChaCha20, and Twofish—for end-to-end data protection. …”
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  19. 19
    A web usage mining approach based on LCS algorithm in online predicting recommendation systems

    A web usage mining approach based on LCS algorithm in online predicting recommendation systems by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2008
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  20. 20
    AI powered asthma prediction towards treatment formulation: an android app approach

    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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