Search Results - (( program implementation case algorithm ) OR ( variable detection based algorithm ))

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    Observer-based fault detection with fuzzy variable gains and its application to industrial servo system by Eissa, Magdy Abdullah, Sali, Aduwati, Hassan, Mohd Khair, Bassiuny, A. M., Darwish, Rania R.

    Published 2020
    “…The proposed fault detection algorithm employs a fuzzy logic-based approach with the objective of finding the appropriate observer gains that could cope with the different working conditions. …”
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    Article
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    Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti... by Mohd Sayud, Nur Asikin

    Published 2018
    “…In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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    Thesis
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    Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm by Nikfal, Shima

    Published 2007
    “…Then the algorithm gathers all the test cases based on the definition occurrence and def-use pair if they cover same definition occurrence of one variable but they don’t cover def-use pair of the same variable. …”
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    Thesis
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    An improved algorithm in test case generation from UML activity diagram using activity path by Hashim, Nor Laily, Salman, Yasir D.

    Published 2011
    “…This paper proposed an improved algorithm to automatically generate test cases directly from UML activity diagram using an activity graph.This algorithm has been implemented as a prototype using UML activity diagrams as inputs to generate test cases.These generated test cases are generated automatically are compared to test cases that are generated manually in order to evaluate the algorithm’s usability and reliability.The result shows that the test cases generated by the developed test case generator program are the same as the one manually derived.…”
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    Conference or Workshop Item
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    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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    Conference or Workshop Item
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    Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

    Published 2014
    “…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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    Undergraduates Project Papers
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    Potential norms detection in social agent societies by Mahmoud M.A., Mustapha A., Ahmad M.S., Ahmad A., Yusoff M.Z.M., Hamid N.H.A.

    Published 2023
    “…In this paper, we propose a norms mining algorithm that detects a domain's potential norms, which we called the Potential Norms Mining Algorithm (PNMA). …”
    Article
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    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…With respect to all the algorithms, V-Detector proved to be superior and surpassed all other algorithms based on performance and execution time.…”
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    Thesis
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    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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    Thesis
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    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud M.A., Ahmad M.S., Ahmad A., Mustapha A., Yusoff M.Z.M., Hamid N.H.A.

    Published 2023
    “…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent's belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent's belief base with new normative protocol. …”
    Short Survey
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    Automatic marking system for programming subject by Chan, Jin Yee

    Published 2023
    “…This project is a web application designed for lecturer that teaching programming subject to automatically mark programming algorithm exercise. …”
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    Final Year Project / Dissertation / Thesis
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    Shape-based Road Sign Detection and Recognition for Embedded Application Using MATLAB by Md Sallah, Siti Sarah, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2010
    “…The algorithm is based on the Hough transform method to detect lines in order to identify and determine the shape of the road sign. …”
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    Conference or Workshop Item
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    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…It has been applied in many practical applications. For most of the cases of the shortest route finding, the Dijkstra's algorithm is known to be an optimal search algorithm. …”
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    Thesis
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    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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    Thesis
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    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud, Moamin Ahmed, Ahmad, Mohd Sharifuddin, Ahmad, Azhana, Mustapha, Aida, Mohd Yusoff, Mohd Zaliman, Abdul Hamid, Nurzeatul Hamimah

    Published 2013
    “…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent’s belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent’s belief base with new normative protocol. …”
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    Article
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