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Keyword: K-Nearest NeighborHuman Emotion Recognition Based on EEG Signal Using Fast Fourier Transform and K-Nearest Neighbor
Human emotional states can transform naturally and are recognizable through facial expressions, voices, or body movements, influenced by received stimuli. However, the articulation of emotions is not practicable by every individual, even when feelings of joy, sadness, or otherwise are experienced. Biomedically, emotions affect brain wave activities, as the continuously functioning brain cells communicate through…
Read MoreEfficiency Comparison in Prediction of Normalization with Data Mining Classification
In research project, efficiency comparison study in prediction of normalization with data mining classification. The purpose of the research was to compare three normalization methods in term of classification accuracy that the normalized data provided: Z-Score, Decimal Scaling and Statistical Column. The six known classifications: K-Nearest Neighbor, Decision Tree, Artificial Neural Network, Support Vector Machine,…
Read MoreImproved Detection of Advanced Persistent Threats Using an Anomaly Detection Ensemble Approach
Rated a high-risk cyber-attack type, Advanced Persistent Threat (APT) has become a cause for concern to cyber security experts. Detecting the presence of APT in order to mitigate this attack has been a major challenge as successful attacks to large organizations still abound. Our approach combines static rule anomaly detection through pattern recognition and machine…
Read MoreClassification of Wing Chun Basic Hand Movement using Virtual Reality for Wing Chun Training Simulation System
To create a Virtual Reality (VR) system for Wing Chun’s basic hand movement training, capturing, and classifying movement data is an important step. The main goal of this paper is to find the best possible method of classifying hand movement, particularly Wing Chun’s basic hand movements, to be used in the VR training system. This…
Read MoreIndoor Positioning System using WKNN and LSTM Combined via Ensemble Learning
Indoor positioning system (IPS) has become a high demand research field to be developed and has made considerable progress in recent years. Wi-Fi fingerprinting is the most promising technique that produces an acceptable result. However, despite the large amount of research that has been done using Wi-Fi fingerprinting, only a few Wi-Fi based IPS in…
Read MoreReview on Smart Electronic Nose Coupled with Artificial Intelligence for Air Quality Monitoring
With the advent of the Internet of Things Technologies (IOT), smart homes, and smart city applications, E-Nose was created. Almost of gas sensors consisting the electronic nose system suffer from cross sensitivity and lack of selectivity. Coupling smart gas sensors with artificial intelligence algorithms can thus empower conventional gas sensing technologies and increase accuracy in…
Read MoreSkin Tissue Oxygen Saturation Prediction: A Comparison Study of Artificial Intelligence Techniques
Noninvasive measurement of skin tissue oxygen saturation, StO2, is of interest especially in the studies of wound healing and detection of vascular diseases. This work aims to compare Partial Least Square (PLS) regression, K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN) technique in the prediction of StO2 using spectral data obtained from Monte Carlo simulations.…
Read MorePredictive Modelling of Student Dropout Using Ensemble Classifier Method in Higher Education
Currently, one of the challenges of educational institutions is drop-out student issues. Several factors have been found and determined potentially capable to stimulate dropouts. Many researchers have been applied data mining methods to analyze, predict dropout students and also optimize finding dropout variables in advance. The main objective of this study is to find the…
Read MoreFeature Selection for Musical Genre Classification Using a Genetic Algorithm
Music genre classification is an important multimedia research domain, including aspects of music piece representation, distances between genres, and categorization of music databases. The objective of this study was to develop a model for automatic classification of musical genres from audio data by using features from low-level time and frequency domains. These features can highlight…
Read MoreHuman Sit Down Position Detection Using Data Classification and Dimensionality Reduction
The analysis of human sit down position is a research area allows for preventing health physical problems in the back. Many works have proposed systems that detect the sitting position, some open issues are still to be dealt with, such as: Cost, computational load, accuracy, portability, and among others. In this work, we present an…
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