Search Results - (( developing activation detection algorithm ) OR ( java machine learning algorithm ))

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  1. 1

    Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

    Published 2019
    “…These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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  3. 3

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…While numerous methods have been proposed, machine learning (ML) is the most popular approach that has been applied across the globe. …”
    Conference Paper
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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    Amplitude independent muscle activity detection algorithm of soft robotic glove system for hemiparesis stroke patients using single sEMG channel by Hameed, Husamuldeen Khalid

    Published 2020
    “…Many algorithms have been developed in the literature to detect muscle activities; however, most of these algorithms depend on amplitude features in the detection process. …”
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  10. 10

    Soft robotic glove system controlled with amplitude independent muscle activity detection algorithm by using single sEMG channel by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina

    Published 2018
    “…In this paper, a real time muscle activity detection algorithm has been developed to control a pneumatic actuated soft robotic glove intended for patients with grasping impairment. …”
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    Detection of muscle activities in the sEMG signal by using frequency features and adaptive decision threshold by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

    Published 2020
    “…In this paper, an amplitude-independent algorithm had been developed with an adaptive decision threshold; the algorithm employed only frequency features of the sEMG signal to detect muscle activities. …”
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    Article
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    Fetal R-Wave detection in the ambulatory monitoring of maternal abdominal signal by Mohd Alauddin Mohd Ali, Crowe, J.A., Hayes-Gill, B.R.

    Published 1995
    “…An algorithm for the real-time measurement of the fetal and maternal RR intervals from a single-lead abdominal signal has been developed on a low power TMS32010 digital signal processor development system. …”
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    Article
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    Detection of muscle activities in the sEMG signal by using frequency features and adaptive decision threshold by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

    Published 2020
    “…In this paper, an amplitude-independent algorithm had been developed with an adaptive decision threshold; the algorithm employed only frequency features of the sEMG signal to detect muscle activities. …”
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    Article
  15. 15

    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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    Intelligent DNA signature detection for internet worms by Ghazali, Osman

    Published 2011
    “…Internet scanning worms are widely regarded to be a major security threat faced by the Internet community today. Active worms spread in an automated fashion flooding the Internet in a very short time.Slammer worm infected more than 90% of vulnerable machines within 10 minutes on January 25th, 2003.Hence it is necessary to monitor and detect the worms as soon as they are introduced to minimize the damage caused by them.This project concentrates on developing an anti-scanning worm detection system that can automatically detect and control the spread of internet scanning worms without any manual intervention.The Intelligent Failure Connection Algorithm (IFCA) developed in this project can detect both stealth and normal worms within a short time.Experiments conducted as part of the evaluation shows that IFCA detects a worm within two scanning cycles of the worm.This is faster than any of the currently available algorithms or mechanisms reported in the literature.The IFCA uses Artificial Immune System (AIS) for the purpose of monitoring and detecting the worms.The Traffic Signature Algorithm (TSA) developed in the project captures the traffic signature of the worm from the infector when it sends the traffic to the victim.The Intelligent DNA Signature Detection Algorithm (IDNASDA) algorithm works by breaking an infection session into different infection phases, each phase containing a number of different traffic such as Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), or User Datagram Protocol (UDP).Finally it converts the traffic signature to DNA signature.The tests carried out show that the IDNASD could detect DNA signature for MSBlaster worm.…”
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    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…On the Construction phase, the development of the prototype has been started. All the algorithm for the engine has been developed by using Java script language. …”
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    Smart object detection using deep learning algorithm and jetson nano for blind people by Tan, Mei Yan, Anis Farihan, Mat Raffei, Mohd Arfian, Ismail

    Published 2021
    “…Therefore, this project develops a smart object detection using deep learning algorithm and jetson nano to improve object detection for blind people. …”
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    Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD) by Gilani Mohamed, Mohamed Ahmed

    Published 2022
    “…This study indicates developing an algorithm for detecting and progressing through the hippocampus of patients with Alzheimer's disease in MRI images. …”
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