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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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  6. 6
    Modified damage location indices in beam-like structure: Analytical study

    Modified damage location indices in beam-like structure: Analytical study by Fayyadh, M.M., Razak, H.A.

    Published 2011
    “…The Curvature Damage Factor (CDF) developed by Wahab and Roeck (1999) computes the change in mode shape curvature between two sets of mode vectors, i.e. undamaged and damaged conditions. …”
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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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  8. 8
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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  9. 9
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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  10. 10
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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  11. 11
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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  12. 12
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2023
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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  13. 13
    Performance Analysis Of Different Hash Functions Using Bloom Filter For Network Intrusion Detection Systems In 32-Bit And 64-Bit Computer Operation Mode.

    Performance Analysis Of Different Hash Functions Using Bloom Filter For Network Intrusion Detection Systems In 32-Bit And 64-Bit Computer Operation Mode. by Tan , Beng Ghee

    Published 2016
    “…A Bloom Filter pattern matching algorithm with fast hashing functions is developed for 32-bit and 64-bit computer system. …”
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  14. 14
    Focal and non-focal epilepsy localization: a review

    Focal and non-focal epilepsy localization: a review by Hussein, Ahmed Faeq, N., Arunkumar, Gomes, Gorakanage Arosha Chandima, Alzubaidi, Abbas K., Habash, Qais Ahmed, Granados, Luz Santamaria, Moreno, Juan Francisco Mendoza, Gonzalez, Gustavo Ramirez

    Published 2018
    “…Generally, the techniques developed for detecting the epileptic seizures were based on tensors, entropy, empirical mode decomposition, wavelet transform and dynamic analysis. …”
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  15. 15
    Stiffness reduction index for detection of damage location: Analytical study

    Stiffness reduction index for detection of damage location: Analytical study by Fayyadh, M.M., Razak, H.A.

    Published 2011
    “…The study has adopted the first four bending modes to examine the sensitivity of both existing as well as developed damage location indices. …”
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  16. 16
    Combined modal parameters-based index for damage identification in a beamlike structure: theoretical development and verification

    Combined modal parameters-based index for damage identification in a beamlike structure: theoretical development and verification by Fayyadh, M.M., Razak, H.A., Ismail, Z.

    Published 2011
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  17. 17
    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms

    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms by Mahmud, Mohd. Razali, Mohd. Yusof, Othman

    Published 2005
    “…A remarkable result can be achieved by filtering these far outliers using automatic detection mode. This paper elaborates the techniques used for the detection and elimination of the far outliers in the MBES dataset, known as robust detection algorithms. …”
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  18. 18
    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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  19. 19
    Collision avoidance algorithm design for UAV base on parametric theorem and circle overlapping method / Nur Fadzilah Mohamad Radzi

    Collision avoidance algorithm design for UAV base on parametric theorem and circle overlapping method / Nur Fadzilah Mohamad Radzi by Nur Fadzilah, Mohamad Radzi

    Published 2013
    “…Finally, the collision avoidance algorithm is verified through MATLAB software. Various cases are tested to demonstrate the robustness of both collision detection and avoidance algorithms.…”
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  20. 20
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In this research, a fault diagnosis methodology based on Cross Industry Standard Process for Data Mining (CRISP-DM) model was proposed for the purpose of damage detection. In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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