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  1. 1
    A traffic signature-based algorithm for detecting scanning internet worms

    A traffic signature-based algorithm for detecting scanning internet worms by M. Rasheed, Mohammad, Ghazali, Osman, Md Norwawi, Norita, M. Kadhum, Mohammed

    Published 2009
    “…The proposed method has two algorithms. The first part is an Intelligent Failure Connection Algorithm (IFCA) using Artificial Immune System; IFCA is concerned with detecting the internet worm and stealthy worm. …”
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  2. 2
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  3. 3
    An automated signature generation method for zero-day polymorphic worms based on multilayer perceptron model

    An automated signature generation method for zero-day polymorphic worms based on multilayer perceptron model by Mohammed, Mohssen M. Z. E., Chan, H. Anthony, Ventura , Neco, Pathan, Al-Sakib Khan

    Published 2013
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  4. 4
    Automated feature selection using boruta algorithm to detect mobile malware

    Automated feature selection using boruta algorithm to detect mobile malware by Che Akmal, Che Yahaya, Ahmad Firdaus, Zainal Abidin, Salwana, Mohamad, Ernawan, Ferda, Mohd Faizal, Ab Razak

    Published 2020
    “…This research proposed automated feature selection using Boruta algorithm to detect the malware. The proposed method adopts machine learning prediction and optimizes the selecting features in order to reduce the model of machine learning complexity. …”
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  5. 5
    Ensemble based categorization and adaptive model for malware detection

    Ensemble based categorization and adaptive model for malware detection by Ahmad Zabidi, Muhammad Najmi, Maarof, Mohd Aizaini, Zainal, Anazida

    Published 2011
    “…Current malware detection method involved string search algorithm which based on the pattern detection. …”
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  6. 6
    Hybrid group decision making method based on multi-granular information using fusion algorithms and consistent fuzzy preference relation / Siti Amnah Mohd Ridzuan

    Hybrid group decision making method based on multi-granular information using fusion algorithms and consistent fuzzy preference relation / Siti Amnah Mohd Ridzuan by Mohd Ridzuan, Siti Amnah

    Published 2017
    “…Both algorithm been illustrated in textbook selection. The proposed methods can be utilized as another option to solve a decision making problem.…”
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  7. 7
    Evaluation of the effectiveness of clustering algorithm in retrieving Malay documents / Aminah Mahmood

    Evaluation of the effectiveness of clustering algorithm in retrieving Malay documents / Aminah Mahmood by Mahmood, Aminah

    Published 2004
    “…First experiment use exact match, which is no method, is applied. Second experiment use stenmiing method. …”
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  8. 8
    Mobile botnet classification by using hybrid analysis

    Mobile botnet classification by using hybrid analysis by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

    Published 2024
    journal::journal article
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  9. 9
    Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended solution

    Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended so... by Mohammed, R. T., Yaakob, R., Zaidan, A. A., Sharef, N. M., Abdullah, R. H., Zaidan, B. B., Dawood, K. A.

    Published 2020
    “…Evaluation and benchmarking of many-objective optimization (MaOO) methods are complicated. …”
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  10. 10
    Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison

    Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison by Zeb Shah, Jehan, Salim, Naomie

    Published 2006
    “…The results of the SOM neural networks, Wards and Group-Average methods are evaluated for the clustering of different biologically active chemical molecules that can be used as drug like compounds based on topological descriptors. …”
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  11. 11
    Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison

    Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison by Zeb Shah, Jehan, Salim, Naomie

    Published 2006
    “…The results of the SOM neural networks, Wards and Group-Average methods are evaluated for the clustering of different biologically active chemical molecules that can be used as drug like compounds based on topological descriptors. …”
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  12. 12
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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  13. 13
    Group method of data handling with artificial bee colony in combining forecasts

    Group method of data handling with artificial bee colony in combining forecasts by Yahya, Nurhaziyatul Adawiyah, Samsudin, Ruhaidah, Darmawan, Irfan, Kasim, Shahreen

    Published 2018
    “…This study is done by combining individual forecasts of Group Method of Data Handling models using the weighted-based combine approach. …”
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  14. 14
    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…The results of the evaluation show that the proposed approach exemplified the state-of-the-art method with significant differences in most of the datasets tested.…”
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  15. 15
    Enhancing performance of XTS cryptography mode of operation using parallel design

    Enhancing performance of XTS cryptography mode of operation using parallel design by Ahmed Alomari, Mohammad

    Published 2009
    “…Performance evaluation shows that XTS exhibits faster speed when an RC6 encryption algorithm is used, compared to other encryption algorithms such as AES and Twofish. …”
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  16. 16
    Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection

    Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli

    Published 2011
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  17. 17
    Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data

    Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data by Tian, Ying

    Published 2024
    “…The complexity of compositional data with missing values renders traditional estimation methods inadequate. In this thesis, a compositional data imputation method designed based on LASSO is proposed combining group LASSO and adaptive LASSO analysis methods. …”
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  18. 18
    Inchworm robot grippers in clothes manipulation - Optimizing the tracing algorithm

    Inchworm robot grippers in clothes manipulation - Optimizing the tracing algorithm by Salleh K., Seki H., Kamiya Y., Hikizu M.

    Published 2023
    Conference paper
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  19. 19
    Grouping based radio frequency identification anti-collision protocols for dense internet of things application

    Grouping based radio frequency identification anti-collision protocols for dense internet of things application by Umelo, Nnamdi H., Noordin, Nor K., A. Rasid, Mohd Fadlee, Geok, Tan K., Hashim, Fazirulhisyam

    Published 2022
    “…This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. …”
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  20. 20
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…The developed algorithm weighted the n objects contribution in explaining the separation between groups. …”
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