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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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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
    A Toolkit for Simulation of Desktop Grid Environment

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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  4. 4
    Group formation using genetic algorithm

    Group formation using genetic algorithm by Che Ani, Zhamri, Husin, Mohd Zabidin, Yasin, Azman

    Published 2009
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  5. 5
    Effect of normalization and effect of normalization and training algorithm on radial basis training algorithm on radial basis function network performance function network performance

    Effect of normalization and effect of normalization and training algorithm on radial basis training algorithm on radial basis function network performance function network performa... by Wani, Eddie

    Published 2007
    “…To recognize the effect of normalization of data and training algorithm on Radial Basis Function (RBF) performance.…”
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  6. 6
    Network game (Literati) / Chung Mei Kuen

    Network game (Literati) / Chung Mei Kuen by Chung, Mei Kuen

    Published 2003
    “…The possible applications of multimedia-networked system are endless, as the demand to support interactive communication among groups of users has increased significantly. …”
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  7. 7
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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  8. 8
    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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  9. 9
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. The proposed method can be applied in smart cities, monitoring, health delivery, augmented reality, and gaming among others.…”
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  10. 10
    A study on advanced statistical analysis for network anomaly detection

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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  11. 11
    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma

    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

    Published 2017
    “…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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  12. 12
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  13. 13
    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural

    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

    Published 2006
    “…The system is built to classify some certain data into two classes, which are normal or abnormal cells. …”
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  14. 14
    Optimizing lossless compression by normalized data length in Huffman Algorithm

    Optimizing lossless compression by normalized data length in Huffman Algorithm by Tonny, Hidayat

    Published 2022
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  15. 15
    Algorithm for calculation of cephalometric soft tissue facial traits

    Algorithm for calculation of cephalometric soft tissue facial traits by Azam Rana, Mohammad, Setan, Halim, Majid, Zulkepli, Chong, Albert K.

    Published 2007
    “…The source data used to get 3D digital models of human soft tissues include CT data and 3D laser scanner data. …”
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  16. 16
    Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach

    Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach by Sumiati, ., Hoga, Saragih, T.K.A, Rahman, Viktor Vekky, Ronald Repi, Agung, Triayudi

    Published 2021
    “…This research contributes to the world of health, where we classify the Electrocardiogram (ECG) data, so that it can classify abnormal and normal cardiac disorders using the Fuzzy Cognitive Map (FCM) algorithm.…”
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  17. 17
    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…Consequently, to handle these data, computer algorithms must adapt to their characteristics. …”
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  18. 18
    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream

    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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  19. 19
    Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach

    Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach by Selvarajah, Gayathri Thevi, Bonestroo, Floor A. S., Timmermans Sprang, Elpetra P. M., Kirpensteijn, Jolle, Mol, Jan A.

    Published 2017
    “…Previous gene expression studies involving canine OS have used one or two reference genes to normalize gene expression. This study aimed to validate a panel of reference genes commonly used for normalization of canine OS gene expression data using the geNorm algorithm. qPCR analysis of nine canine reference genes was performed on 40 snap-frozen primary OS tumors and seven cell lines. …”
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  20. 20
    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer

    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer by Ahmad, Noor Ashikin

    Published 2015
    “…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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