Search Results - (( parallel extraction method algorithm ) OR ( pattern detection method algorithm ))

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  1. 1

    Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis by Siti Nur Hidayah, Mazelan

    Published 2022
    “…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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    Undergraduates Project Papers
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    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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    Thesis
  4. 4

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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    Final Year Project / Dissertation / Thesis
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    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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    Thesis
  7. 7

    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

    Published 2014
    “…To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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    Thesis
  8. 8

    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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    Monograph
  9. 9

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

    Published 2023
    “…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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    Thesis
  10. 10

    Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

    Published 2013
    “…The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. …”
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    Conference or Workshop Item
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    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The first stage is to apply reverse engineering method to obtain the specific patterns of individual jammers. …”
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    Thesis
  12. 12

    Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…The pattern recognition results showed that the AR algorithm is more effective in defect identification. …”
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    Article
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    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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    Article
  15. 15

    Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

    Published 2022
    “…Then, the segmented cabbage sample will use the GLCM method for feature extraction. It is a method of extracting second-order statistical texture features to detect diseases more efficiently. …”
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    Academic Exercise
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    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column by Othman, M. R., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2003
    “…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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    Conference or Workshop Item
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    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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    Article
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    Analytical method for forensic investigation of social networking applications on smartphones by Dezfouli, Farhood Norouzizadeh

    Published 2016
    “…The identified patterns are then used to design an algorithm for detecting social networking data remnants automatically. …”
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    Thesis
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    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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    Thesis