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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
    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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  3. 3
    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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    Citation Index Journal
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  4. 4
    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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  5. 5
    Agent-based extraction algorithm for computational problem solving

    Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

    Published 2015
    “…Several statistical tests such as normality test and reliability analysis were conducted. …”
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  6. 6
    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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    Conference or Workshop Item
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  7. 7
    Automatic Classification of Cervix Type

    Automatic Classification of Cervix Type by Muktiar Singh, Jasdeep Singh

    Published 2019
    “…There are three different types of cervix, these different types of cervix in our data set are all considered normal (not cancerous, but some are pre-cancerous), but since the transformation zones are not always visible, some of the patients require further testing while some do not. …”
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    Final Year Project
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  8. 8
    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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  9. 9
    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, Muzahid, Abu Jafar Md, 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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  10. 10
    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
    “…This thesis aimed to investigate and develop a novel parameterized architecture design for SENSE algorithm. The proposed design is implemented on Field Programmable Gate Arrays (FPGAs) platform, which can provide real-time SENSE reconstruction right on the receiver coil data acquisition system with no need to transfer data to the MRI server. …”
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  11. 11
    Preliminary study on fault detection using artificial neural network for water-cooled reactors

    Preliminary study on fault detection using artificial neural network for water-cooled reactors by Abdul Karim, Julia, Lanyau, Tony, Maskin, Masleha, Anuar, M. A. S., Che Soh, Azura, Abdul Rahman, Ribhan Zafira

    Published 2020
    “…This work was carried out to discover the use of an artificial neural network (ANN) to model and develop a fault detection programme in the RTP cooling system. Using actual data from the reactor to train the multilayer network model with backpropagation algorithm. …”
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  12. 12
    Challenges of hidden data in the unused area two within executable files

    Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

    Published 2009
    “…Results: The programs were coded in Java computer language and implemented on Pentium PC. The designed algorithms were intended to help in proposed system aim to hide and retract information (data file) with in unused area 2 of any execution file(exe.file). …”
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  13. 13
    Self routing traffic light for traffic light controller using priority method based on volume of vehicles

    Self routing traffic light for traffic light controller using priority method based on volume of vehicles by Tan, Swee Tiang

    Published 2015
    “…This research uses data at a cross traffic junction in Perak between Jalan Taiping and Kuala Sepatang with the primary data provided by Jabatan Kerja Raya, JKR Larut Matang & Selama, Taiping. …”
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