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  1. 1
    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
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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  2. 2
    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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  3. 3
    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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  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
    “…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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  5. 5
    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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    Conference or Workshop Item
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  6. 6
    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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  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
    An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi

    An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi by Suhaimi, Hamizan

    Published 2021
    “…The performance of the proposed method and other existing techniques (Genetic Algorithm, Artificial Immune System and Immune-Genetic Algorithm) were analysed to evaluate and determine its efficiency in terms of maximum intrusion detection rate and the highest true positive rate. …”
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  9. 9
    Pre-processing methods for vehicle lane detection / Muhammad Naim Mazani ... [et al.]

    Pre-processing methods for vehicle lane detection / Muhammad Naim Mazani ... [et al.] by Mazani, Muhammad Naim, Abdul-Rahman, Shuzlina, Mutalib, Sofianita

    Published 2020
    “…The experimental results showed that the proposed algorithms could be practical in terms of effectively detecting road lines and generate lane detection…”
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  10. 10
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Moreover, shortage of reliable methods on a new dataset for the intrusion detection system and anomaly detection in terms of classification is an issue. …”
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  11. 11
    Vertical-edge-based car-license-plate detection method

    Vertical-edge-based car-license-plate detection method by Al-Ghaili, Abbas Mohammed Ali, Mashohor, Syamsiah, Ramli, Abdul Rahman, Ismail, Alyani

    Published 2013
    “…The first contribution is that we propose a fast vertical edge detection algorithm (VEDA) based on the contrast between the grayscale values, which enhances the speed of the CLPD method. …”
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  12. 12
    Weighting method for modal parameter based damage detection algorithms

    Weighting method for modal parameter based damage detection algorithms by Fayyadh, M.M., Abdul Razak, H.

    Published 2011
    “…Normally, there is a variance in the sensitivity of different modes and the global stiffness change is derived by taking the algebraic average, which is equivalent to the mean in statistical analysis terms. This study proposes weighting method for damage detection algorithms based on the bending mode shapes for beam structures. …”
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  13. 13
    Microcrack Detection And Noise Reduction In Integrated Circuit Packages

    Microcrack Detection And Noise Reduction In Integrated Circuit Packages by Koh, Ye Sheng

    Published 2018
    “…Therefore, a better algorithm is desired to improve the detection performance in terms of time and accuracy. …”
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    Monograph
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  14. 14
    An adept edge detection algorithm for human knee osteoarthritis images

    An adept edge detection algorithm for human knee osteoarthritis images by Zahurul S., Zahidul S., Jidin R.

    Published 2023
    “…In this paper, Sobel edge detection operator and its enhanced algorithm are first discussed in terms of optimal thresholding in C language under Linux platform. …”
    Conference Paper
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  15. 15
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
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  16. 16
    Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors

    Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

    Published 2020
    “…The results showed that the amplitude-independent algorithm performed better in terms of detecting weak muscle activity and resisting false alarms.…”
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  17. 17
    An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]

    An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.] by Rastogi, Sarthak, Shrotriya, Archit, Singh, Mitul Kumar, Potukuchi, Raghu Vamsi

    Published 2022
    “…The findings reveal which method performed better in terms of accuracy and running time.…”
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  18. 18
    Analysis of artificial neural network and viola-jones algorithm based moving object detection

    Analysis of artificial neural network and viola-jones algorithm based moving object detection by Rashidan, M. Ariff, Mohd Mustafah, Yasir, Zainal Abidin, Zulkifli, Zainuddin, N. Afiqah, A. Aziz, Nor Nadirah

    Published 2014
    “…Analysis of moving object detection methods is presented in this paper, includes Artificial Neural Network (ANN) and Viola-Jones algorithm. …”
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    Proceeding Paper
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  19. 19
    An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents

    An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents by Al-Dyani, Wafa Zubair Abdullah

    Published 2022
    “…This work focuses on the FS problem by automatically detecting events through a novel wrapper FS method based on Adapted Binary Bat Algorithm (ABBA) and Adapted Markov Clustering Algorithm (AMCL), termed ABBA-AMCL. …”
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  20. 20
    Rao-SVM machine learning algorithm for intrusion detection system

    Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

    Published 2020
    “…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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