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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    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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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

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

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    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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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  8. 8
    Identify texture of MRI human brain using Adaptive Fuzzy C-Means (AFCM) Algorithm / Faridatul Akma Mohd Noor

    Identify texture of MRI human brain using Adaptive Fuzzy C-Means (AFCM) Algorithm / Faridatul Akma Mohd Noor by Faridatul Akma, Mohd Noor

    Published 2010
    “…The main objective of this research is to develop a prototype that use Adaptive Fuzzy C-Means (AFCM) algorithm to identify texture of human brain.…”
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  9. 9
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Therefore, these algorithms can be improved upon. A neighbourhood-based noise-reduction algorithm which uses the edges of an image is proposed. …”
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  10. 10
    Eye-state analysis using an interdependence and adaptive scale mean shift (IASMS) algorithm

    Eye-state analysis using an interdependence and adaptive scale mean shift (IASMS) algorithm by Mat Ibrahim, Masrullizam

    Published 2014
    “…The design is based on an interdependence and adaptive scale mean shift (IASMS) algorithm. IASMS uses moment features to track and estimate the iris area in order to quantify the state of the eye. …”
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  11. 11
    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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  12. 12
    A combinatory algorithm of univariate and multivariate gene selection

    A combinatory algorithm of univariate and multivariate gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2009
    “…The results show that the mean of misclassification error of training samples in 100 iteration are almost equal in two algorithms but our algorithm have the better ability to classify independent samples.…”
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  13. 13
    Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri

    Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri by Nik Mohd Asri, Nik Asyraniasna

    Published 2024
    “…Through the analysis of various customer data sets, such as people, products, promotion, place, the K-means algorithm can detect clusters that correspond to consistent client groups. …”
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  14. 14
    Design of nonlinear adaptive interaction algorithm controller for improvement of tracking performance of X-Y table ball screw drive system

    Design of nonlinear adaptive interaction algorithm controller for improvement of tracking performance of X-Y table ball screw drive system by Retas, Zain

    Published 2023
    “…The contribution is Nonlinear Adaptive Interaction Algorithm (NAIA). The controller is developed based on the enhancement and modification of the basic Adaptive Interaction Algorithm Controller (AIA). …”
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  15. 15
    Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia

    Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia by Martono, Martono, Sudiro, Sudiro, Satino, Satino

    Published 2018
    “…The statistic test used in this research is t-test. The results reveals that simulation model using algorithm influences the improvement of traffic volunteers’ emergency management capabilities with p-value of < 0.05 and mean score difference of 34.5%, and the model is highly effective to be implemented to improve the capability of traffic assistant volunteers to manage trauma emergency with the mean score difference of 11.5%. …”
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  16. 16
    Development of an effective clustering algorithm for older fallers

    Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

    Published 2022
    “…A total of 1279 subjects and 9 variables were selected for clustering after the data pre-possessing stage. Using feature extraction with the t-SNE and the K-means clustering algorithm, subjects were clustered into low, intermediate A, intermediate B and high fall risk groups which corresponded with fall occurrence of 13%, 19%, 21% and 31% respectively. …”
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  17. 17
    Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh

    Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh by Seef Saadi , Fiyadh

    Published 2019
    “…The NARX algorithm is used for the modelling of Hg2+ removal. …”
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  18. 18
    Friend recommendation using collaborative filtering / Nurfatini Atiqah Hamidi

    Friend recommendation using collaborative filtering / Nurfatini Atiqah Hamidi by Hamidi, Nurfatini Atiqah

    Published 2021
    “…Lastly, the evaluation of the accuracy of the recommendation is done by using Mean Absolute Error and on average the predictive value of Collaborative Filtering algorithm distance from the actual value is 0.046. …”
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  19. 19
    Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI

    Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI by Abang Mohd Arif Anaqi, Abang Isa, Kuryati, Kipli, Ahmad Tirmizi, Jobli, Muhammad Hamdi, Mahmood, Siti Kudnie, Sahari, Aditya Tri, Hernowo, Sinin, Hamdan

    Published 2021
    “…The greyscale image is converted to pseudo-colour is to intensify the visual perception and deliver more information. Then, the algorithm segments the region of interest (ROI) using K-means clustering. …”
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  20. 20
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…The best mapping percentage of 62.7 obtained using the proposed algorithm when k = 15 is obtained to outperform the performance of the generic k-means. …”
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