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An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina

“…A new algorithm has been developed to detect the presence of muscle activities in weak and noisy sEMG signals. …”
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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

“…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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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

“…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

“…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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Fetal R-Wave detection in the ambulatory monitoring of maternal abdominal signal by Mohd Alauddin Mohd Ali, Crowe, J.A., Hayes-Gill, B.R.

“…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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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

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

“…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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Moving object detection and tracking from video sequence : an analysis between canny edge detection and active contour technique / Mohd Anuar Mohd Salleh by Mohd Salleh, Mohd Anuar

“…Canny edge detection and active contour was developed using C++ language. …”
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Intelligent DNA signature detection for internet worms by Ghazali, Osman

“…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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Smart object detection using deep learning algorithm and jetson nano for blind people by Tan, Mei Yan, Anis Farihan, Mat Raffei, Mohd Arfian, Ismail

“…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

“…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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WEBCAM MOTION DETECTION USINGVISUAL BASIC by Abdullah, Ilyana

“…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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Real-time measurement and gait detection algorithm for motion control of active ankle foot orthosis / Aminuddin Hamid by Hamid, Aminuddin

“…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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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

“…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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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

“…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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Two-factor authentication smart entryway using modified LBPH algorithm by Ayop, Zakiah, Othman, Nur Fadzilah, Anawar, Syarulnaziah, Wan Mohamad Rosdi, Wan Mohamad Hariz, Looi, Wei Hua

“…Many face detection models have been developed in smart entryways using IoT. …”
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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES by HANIZAM, MOHD HAZIQ NAZMI

“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob by Yaakob, Mohd Amiruddin Fikri

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Detection of Counterfeit Telecommunication Products using Luhn Checksum Algorithm and an Adapted IMEI Authentication Method by Amusa, Morufu, Bamidele, Oluwade

“…The first authentication method is the Luhn checksum algorithm, otherwise called Luhn formula or mod 10 algorithm. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

“…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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