Search Results - (( parameter notification system algorithm ) OR ( code classification modified algorithm ))

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  1. 1
    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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    Proceeding Paper
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  2. 2
    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping by Ahmed Asal Kzar, Ahmed Asal Kzar, M Jafri, Mohd Zubir, Mutter, Kussay N., Anwar, Saumi Syahreza

    Published 2016
    “…The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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  3. 3
    Enhancement load balancing in failover web server by using HTTP-response status techniques with pfsense opensource / Muhammad Hafiz Ramli

    Enhancement load balancing in failover web server by using HTTP-response status techniques with pfsense opensource / Muhammad Hafiz Ramli by Ramli, Muhammad Hafiz

    Published 2020
    “…Meanwhile, an email notification was introduced in ICMP and HTTP based monitoring as a notification to the administrator when the failure occurs.…”
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    Thesis
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  4. 4
    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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    Working Paper
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  5. 5
    Study of machine learning in computer vision using Raspberry Pi

    Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

    Published 2024
    text::Final Year Project
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  6. 6
    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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  7. 7
    Traffic monitoring system with emergency support using SOM

    Traffic monitoring system with emergency support using SOM by Tan, Hoai Thang

    Published 2020
    “…This paper proposed a system of emergency notification to alert the driver. …”
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    Final Year Project / Dissertation / Thesis
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  8. 8
    Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line

    Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

    Published 2020
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  9. 9
    IoT-Based intelligent system for headwater phenomenon detection and alerts using ESP32 / Rozan Boudville … [et al]

    IoT-Based intelligent system for headwater phenomenon detection and alerts using ESP32 / Rozan Boudville … [et al] by Boudville, Rozan, Abdul Wahab, Afif Luqmanulhakim, Wan Zukenani, Wan Izzat Hakimi, Mohd Khelmy, Muhammad Adly Hisyam, Khiruddin, Nur Raihah

    Published 2025
    “…The proposed system integrates multiple ESP32 microcontrollers with water level and rainfall sensors to monitor environmental parameters continuously. …”
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  10. 10
    Incremental learning for large-scale stream data and its application to cybersecurity

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. Incremental learning has an ability to process large data in chunk and update the parameters after learning each chunk. …”
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