Search Results - (( java implementation case algorithm ) OR ( pattern classification sensor algorithm ))

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  1. 1

    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition by M. A., Ameedeen, Marhaini, M. S.

    Published 2016
    “…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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    Conference or Workshop Item
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    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

    Published 2007
    “…Region growing segmentation and radial basis function algorithms are considered a powerful tool to minimize the mixed pixel classification error.…”
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    Conference or Workshop Item
  3. 3

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

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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    Thesis
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    A Distributed Event Detection Scheme for Wireless Sensor Networks by Muhamad Amin , Anang Hudaya, Khan, Asad I., Raja Mahmood, Raja Azlina

    Published 2009
    “…Many of the existing event detection schemes in wireless sensor networks that employ classification or clustering approaches suffer from high communication and computational overheads. …”
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    Conference or Workshop Item
  5. 5

    Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

    Published 2019
    “…However, the EMG signal pattern classification was done by SVM has better performance than LDA due to less significant difference in the accuracy percentage, and a fewer number of sensors used by the SVM. …”
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    Thesis
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    A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

    Published 2007
    “…It is well known that the use of a gas sensor array and pattern recognition system offers an effective technique for the identification of volatile organic molecules because of the poor selectivity of a lot of other gas sensors. …”
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    Research Reports
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    Classification of Agarwood using ANN by M. S., Najib, N. A., Mohd Ali, M. N., Mat Arip, M., Abd Jalil, M. N., Taib

    Published 2012
    “…The data analysis using Principal Component Analysis (PCA) was done to find significant input selection from 32 sensors of the E-nose and to recognize pattern variations from different number of Agarwood samples as inputs to ANN training. …”
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    Article
  10. 10

    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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    Sistem Pengecaman Bentuk Berdasarkan FPGA by Zainal Ariffin, Nur Bayani

    Published 2005
    “…Pattern recognition means that the definition, identification and the classification by deciding the characteristics of that pattern which is need to be known. …”
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    Monograph
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    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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    Article
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    Detection of tube defect using the autoregressive algorithm by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. …”
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    Article
  15. 15

    Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

    Published 2013
    “…In this paper, we develop a technology for the materials selection system using Java based expert system. The weighted-range method (WRM) was implemented to identify the range value and to scrutinise the candidate materials. …”
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    Article
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    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…According to the simulation results, the proposed algorithm produces the best solution among all algorithms in the proposed cases. � 2021 Little Lion Scientific…”
    Review
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    E-nose for basal stem rot detection by Ali Yeon, Md Shakaff, Prof. Dr., Mazlee Noor, Ahmad. Dr., Marni Azira, Markom, Abdul Hamid, Adom, Wahyu, Hidayat, Abu Hassan, Abdullah, N., Ahmad Fikri

    Published 2010
    “…An electronic nose is an intelligent device, able to mimic human olfaction functions and may be used for detection, recognition and classification of volatile compounds and odours. An e-nose consists of an array of sensors, signal collecting unit(s) and suitable pattern recognition algorithm.…”
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    Article
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    Classification of agarwood using ANN / Muhammad Sharfi Najib ...[et al.] by Najib, Muhammad Sharfi, Md Ali, Nor Azah (Dr.), Mat Arip, Mohd Nasir, Jalil, Abd Majid, Taib, Mohd Nasir

    Published 2012
    “…The data analysis using Principal Component Analysis (PCA) was done to find significant input selection from 32 sensors of the E-nose and to recognize pattern variations from different number of Agarwood samples as inputs to ANN training. …”
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    Article
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