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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
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Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

“…Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

“…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing by Hajyyev, Abdyrahym

“…The images obtained from MIVIA dataset has been manually segmented to cell level from the image level. Developing an automated segmentation algorithm might give better results.…”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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MRI brain tumor detection methods using contourlet transform based on time adaptive self-organizing map by Ali Farzamnia, Seyed Hamidreza Hazaveh, Seyede Safieh Siadat, Ervin Gubin Moung

“…Our method is compared to other methods used in past research and shows promising results for the precise classification of MRI brain images. …”
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FIS-PNN: a hybrid computational method for protein-protein interactions prediction using the secondary structure information by Sakhinah Abu Bakar, Javid Taheri, Albert Y Zomaya

“…As a result, they must interact with each other. In this study we used our approach, namely FIS-PNN, to predict the interacting proteins in yeast from the information of their secondary structures using hybrid machine learning algorithms. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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Supervised neural network classifier for voice pathology by Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Hariharan, Muthusamy

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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

“…It is also robust to the measurement noise of level as much as 0 dB. Compared to state-of-the-art algorithms and other common methods, our method outperformed them in terms of sensitivity, specificity, and accuracy. …”
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Detection of sweetness level for fruits (watermelon) with machine learning by Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah

“…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. This study applies image processing techniques to detect the color and shape of watermelon’s skin for grading based on the sweetness level using K-means clustering method via the Python platform. 13 samples of watermelon images are used to test the functionality of the proposed detection system in this study. …”
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Auditory Evoked Potentials (AEPs) Response Classification: A Fast Fourier Transform (FFT) and Support Vector Machine (SVM) Approach by Islam, Md Nahidul, Norizam, Sulaiman, Rashid, Mamunur, Mahfuzah, Mustafa, Md Jahid, Hasan

“…Then, the features have extracted with the help of Fast Fourier Transform (FFT), Power Spectral Density (PSD), Spectral Centroids, Standard Deviation algorithms. To classify the extracted features, the Support Vector Machine (SVM) approach using Radial Basis Kernel Function (RBF) has been used. …”
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An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions by Gerhana, Yana Aditia

“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease by Sadiq, A., Yahya, N., Tang, T.B., Hashim, H., Naseem, I.

“…From this matrix, significant connections evaluated using the p-value are selected as an input to a classifier for the classification of Alzheimerâ��s vs. normal controls. …”
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Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

“…This gives a more practical functionality for such a system to be used in a wearable fashion over the existing Electroencephalogram (EEG) based seizure detection systems due to their complex pattern classification methodologies. …”
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Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

“…This gives a more practical functionality for such a system to be used in a wearable fashion over the existing Electroencephalogram (EEG) based seizure detection systems due to their complex pattern classification methodologies. …”
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Neurons to heartbeats: spiking neural networks for electrocardiogram pattern recognition by Wong, Yan Chiew, Mohamad Noor, Nor Amalia Dayana, Mohd Noh, Zarina, Sarban Singh, Ranjit Singh

“…Establishing functioning spiking neural networks (SNN) involves figuring out the neuron’s state through its activity level, challenging due to its resemblance to the human brain’s data processing, yet appealing due to factors like improved unsupervised learning methods, with ten parameters chosen for the learning algorithm of SNN. …”
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Extrema Points Application In Determining Iris Region Of Interest by Othman, Zuraini, Kasmin, Fauziah, Syed Ahmad, Sharifah Sakinah, Abdullah, Azizi

“…In this study, the algorithm was based on finding the classification for the region of interest (ROI) with the help of a Support Vector Machine (SVM) by applying a histogram of grey level values as a descriptor in each region from the region growing technique. …”
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Drone-based surveillance of palm tress ecosystems by Mansor, Ya’akob, Baki, Sharudin Omar, Sahwee, Zulhilmy, Mengyue, Cheng, Wu, Yuanyuan

“…The study aims to improve the accuracy and efficiency of palm health detection by integrating MATLAB's initial object recognition with advanced deep learning algorithms. The initial phase of the research focuses on elucidating the challenges associated with detecting palm tree health issues using conventional image processing methods in MATLAB. …”
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