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  1. 1

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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    Thesis
  2. 2

    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

    Published 2019
    “…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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    Thesis
  3. 3

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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    Article
  4. 4

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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    Final Year Project / Dissertation / Thesis
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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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    Thesis
  7. 7

    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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    Conference or Workshop Item
  8. 8

    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
  9. 9

    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
  10. 10

    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
  11. 11

    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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    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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    Monograph
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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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    Conference or Workshop Item
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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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    Thesis
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    WEBCAM MOTION DETECTION USINGVISUAL BASIC by Abdullah, Ilyana

    Published 2005
    “…The main focus of the system is to ensure that the motion can be detected only using the skin tones. Combination of several related algorithms helps in developing the skin tones algorithm. …”
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    Final Year Project
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    Real-time measurement and gait detection algorithm for motion control of active ankle foot orthosis / Aminuddin Hamid by Hamid, Aminuddin

    Published 2015
    “…From the result analysis, the developed control algorithm shows that the realtime GRF measurement has the ability to enhance the AAFO functional performance and improve the patient gait.…”
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    Thesis
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    Development of a user-adaptable human fall detection based on fall risk levels using depth sensor by Nizam, Yoosuf, Haji Mohd, Mohd Norzali, Abdul Jamil, M. Mahadi

    Published 2018
    “…There are various approaches used to classify human activities for fall detection. Related studies have employed wearable, non-invasive sensors, video cameras and depth sensor-based approaches to develop such monitoring systems. …”
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    Article
  19. 19

    Development of a user-adaptable human fall detection based on fall risk levels using depth sensor by Nizam, Yoosuf, Haji Mohd, Mohd Norzali, Abdul Jamil, Muhammad Mahadi

    Published 2018
    “…There are various approaches used to classify human activities for fall detection. Related studies have employed wearable, non-invasive sensors, video cameras and depth sensor-based approaches to develop such monitoring systems. …”
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    Article
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