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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
    A variable combinatorial test suite strategy based on modified greedy algorithm

    A variable combinatorial test suite strategy based on modified greedy algorithm by Homaid, Ameen A. Ba, Alsewari, Abdulrahman A.

    Published 2015
    “…A variable strength interaction is the interaction between some of software features which have higher priority than the interaction between the others software features. …”
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  3. 3
    A new variable strength t-way strategy based on the cuckoo search algorithm

    A new variable strength t-way strategy based on the cuckoo search algorithm by Abdullah, Nasser, Kamal Z., Zamli

    Published 2019
    “…Despite much progress, existing strategies have not sufficiently dealt with more than one interaction between input parameters (termed variable strength tway). …”
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  4. 4
    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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  5. 5
    CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm

    CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm by Ng, Yeong Khang

    Published 2019
    “…Combinatorial testing is the way to encounter exhaustive testing through the testing of every input values and every combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). …”
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  6. 6
    Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation

    Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

    Published 2018
    “…In real-world software testing, the input variables may vary in how strongly they interact, variable strength combinatorial interaction testing (VS-CIT) can exploit this for higher effectiveness. …”
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  7. 7
    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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  8. 8
    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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  9. 9
    CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm

    CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm by Alsewari, Abdulrahman A., Ng, Yeong Khang, Kamal Z., Zamli, Mohammed E., Younis

    Published 2019
    “…Combinatorial testing is the way to encounter exhaustive testing through the testing of every input values and every combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). …”
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  10. 10
    A Two Pressure-Velocity Approach for Immersed Boundary Methods in Three Dimensional Incompressible Flows

    A Two Pressure-Velocity Approach for Immersed Boundary Methods in Three Dimensional Incompressible Flows by Tuan Mohammad Yusoff, Tuan Ya, Sabir, O., Norhafizan, Ahmed, Y., Nukman

    Published 2013
    “…The algorithm calculates the interactions between incompressible viscous flows and a solid shape in three-dimensional domain. …”
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  11. 11
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Due to a fixed and restricted predetermined design array, the orthogonal array is unable to give higher-order interactions between variables, resulting in inferior T-method prediction accuracy. …”
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  12. 12
    HABC: Hybrid artificial bee colony for generating variable T-way test sets

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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  13. 13
    HABC: Hybrid artificial bee colony for generating variable T-way test sets

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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  14. 14
    A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia

    A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia by Lim, San Yee

    Published 2018
    “…However, the economic information from other variables may inaccurate if the analysis is conducted by applying single variable only. …”
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  15. 15
    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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  16. 16
    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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  17. 17
    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
    “…The occurrence of falls are usually attributed to the interaction between multiple risk factors. The clinical evaluation of falls risks is time-consuming as a result, hence limiting its availability. …”
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  18. 18
    Survey on input output relation based combination test data generation strategies

    Survey on input output relation based combination test data generation strategies by Alsewari, Abdulrahman A., Tairan, Nasser M., Kamal Z., Zamli

    Published 2015
    “…Combinatorial test data generation strategies have been known to be effective to detect the fault in the product due to the interaction between the product’s features. Over the years, many combinatorial test data generation strategies have been developed supporting uniform and variable strength interactions. …”
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  19. 19
    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm

    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

    Published 2020
    “…However, control accuracy is insufficient because the secretion rate and control variable error are not able to interact directly and limits the controller capability. …”
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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, 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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