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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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Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

“…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”

The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques by Mohammad Syawaludin Syafiq, Hassan

“…In this study, a tracking algorithm is developed by means of image processing technique in detecting ambulance. …”
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Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation by Muhammad Zuhair Bolqiah, Edris, Zahriladha, Zakaria, Mohd Shahril Izuan, Mohd Zin, Mohammed Saeed, Jawad

“…As a consequence, this problem is focussed to derive a lot of good-quality deform detected from the surface images. These detections should discriminate the various surface deforms when fed to suitable image processing algorithms. …”
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Detection and Monitoring of Power Line Corridor from Satellite Imagery Using RetinaNet and K-Mean Clustering by Haroun F.M.E., Deros S.N.M., Din N.M.

K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning by Othman, E.S., Faye, I., Babiker, A., Hussaan, A.M.

“…This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. …”
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Face recognition and identification system (FaceRec) / Khew Jye Huei by Khew , Jye Huei

“…Face recognition is a technique to identify an individual by his/her physical characteristic and has been of interest to a growing number of researchers due to its applications on security. Several different algorithms have been proposed for computer recognition of human faces. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

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Optimised content-social based features for fake news detection in social media using text clustering approach by Yahya, Adnan Hussein Ali

“…In general, the process of fake news detection was conducted in two different phases, the topic detection phase using a graph-based unsupervised clustering method based on HFPA and Markov Clustering Algorithm (MCL) called (HFPA-MCL) and the fake news detection phase using an unsupervised clustering method based on K-means algorithm. …”
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Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

“…The performance of the developed system has been compared with the existing intelligent skin detection systems. …”
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Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map by Sumiati, .

“…This research has 3 objectives To develop algorithms for detecting heart conditions as either abnormal or normal using the modified cognitive map (CM) approach, To develop detection algorithms for anomalous heart conditions based on the enhancement of Certainty Factor (CF) technique, and To evaluate and validate the effectiveness of the new proposed model specifically the Certainty Cognitive Map (CCM) for identifying heart defects. …”
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Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals by Ahmed, Ahmed Elsayed Elmahdy

“…This project aims at developing an automated epileptic seizure event detection algorithm. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…The combined method is called Hybrid K-MeansCGA. Modifications of K-Means structures were done by inserting genetic algorithm operators and tuning the population. …”
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Fetal heart rate monitoring during pregnancy for assessing the well-being of the fetus by Ibrahimy, Muhammad Ibn

“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Robust overlapping community detection in complex networks with graph convolutional networks and fuzzy C-means by Mohammed Al-Andoli, Mohammed Nasser, Che Ku Mohd, Che Ku Nuraini, Harny, Irianto, Jamil Alsayaydeh, Jamil Abedalrahim, Alwayle, Ibrahim M., Ahmed Abuhoureyah, Fahd Saad

“…Existing methods often struggle to capture both network topology and node features, leading to suboptimal overlapping community detection. In this paper, we propose an efficient method called GCNFCM, which utilizes Graph Convolutional Networks (GCNs), Fuzzy C-means (FCM), and the modularity Q algorithm for overlapping community detection. …”
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Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

“…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

“…It is a method of extracting second-order statistical texture features to detect diseases more efficiently. Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

“…High recognition of developed fall detection model is very significance for the elderly to detect the falls. …”
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