Search Results - (( simulation utilisation detection algorithm ) OR ( java implication based algorithm ))

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    Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection by Sze Sin, Voon, Kho, Lee Chin, Ngu, Sze Song, Annie, Joseph, Kuryati, Kipli

    Published 2024
    “…The proposed model leverages machine learning algorithms for autonomous detection of insulators. To determine the optimal stopping point and safety distance between the UAV and the insulator, a mathematical model is presented that utilises the captured images and the machine learning algorithm. …”
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    Article
  2. 2

    Nearfield Electromagnetic Imaging Technique For Brain Tumour Detection by Eustacius Jude, Anak Joseph Linggong

    Published 2019
    “…A program has been developed in C++ to execute the simulation of a head imaging. The simulation consists of two main techniques; a FDTD technique for computational electromagnetics, and Forward-Backward Time-Stepping (FBTS) technique, an algorithm to solve inverse problems. …”
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    Thesis
  3. 3

    Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Roslinazairimah, Zakaria

    Published 2018
    “…Single-linkage is one of the algorithms in agglomerative clustering technique that can be used to detect outliers. …”
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    Conference or Workshop Item
  4. 4

    The summer heat of cryptojacking season : Detecting cryptojacking using heatmap and fuzzy by Ahmad Firdaus, Zainal Abidin, Aldharhani, Ghassan Saleh, Zahian, Ismail, Mohd Faizal, Ab Razak

    Published 2022
    “…This experiment utilised actual cryptojacking samples and achieved a 100 percent detection accuracy rate in simulation.…”
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    Conference or Workshop Item
  5. 5
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    Modified sequential fences for identifying univariate outliers by Wong, Hui Shein

    Published 2016
    “…Sequential fences method is modified by replacing interquartile range with various robust scales such as semi-interquartile range, , median absolute deviation ( ) and Gini’s mean difference ( ) in order to improve outlier detection in symmetric distribution. Ultimately, the utilisation of in sequential fences seems to demonstrate a comparable accuracy in detecting the contaminated data. …”
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    Thesis
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