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Many studies in automatic facial expression recognitions merely limit their focus on recognizing basic emotions, ignoring the fact that humans show various emotions in their daily life. Moreover, from psychological perspective humans express multiple emotions simultaneously. Up to now, researchers recognize two basic emotions at the same time, called mixed emotions. Nevertheless, the mixed emotion...
Facial expression recognition is an active research area in the field of signal social processing. The goal is to distinguish human emotion. The problem is similar emotion, variation of emotion, and independent object through face image. The existing research using various method for modeling human facial to entirely describe facial expression through face image. We consider to variation analysis...
Emotion recognition from facial expression is the subfield of social signal processing which is applied in wide variety of areas, specifically for human and computer interaction. Many researches have been proposed for automatic emotion recognition, which is fundamentally using machine learning approach. However, recognizing basic emotions such as angry, happy, disgust, fear, sad, and surprise is still...
In this paper we present a simulation environment for the study of hierarchical job scheduling on distributed systems. The environment provides a multi-level mechanism to simulate various types of jobs. An execution model of jobs is implemented to simulate the behaviour of jobs to obtain an accurate performance prediction. For parallel jobs, two execution models have been implemented: one in which...
Human emotion recognition is an emerging research area in the field of social signal processing. Facial expression is an important means to detect human emotion. The problem is some facial expressions represent similar emotions. Thus, the recognition must consider the ambiguity in the way human expresses emotions through face. Existing methods do not take into account the level of expression's ambiguity...
Faculty of Computer Science Universitas Indonesia (Fasilkom UI) implemented an e-Learning environment, Student Centered E-Learning Environment (SCELE), to complement the conventional approach of teaching and learning since 2005. Evaluations regarding effectiveness of the e-Learning system used by lecturers have been made. However, the students have not evaluated yet the user experience while using...
Remote sensing technology plays an important role in agriculture applications, especially for paddy growth stages classification, which is a critical process in predicting crop production. The analysis of multi bands data covering very large swath areas using iterative methods such as neural network or SVM will certainly cost much computation time. This paper addresses this problem by taking advantage...
Electrocardiogram (ECG) plays an important role in monitoring and preventing heart attacks. In this paper, we propose a new method Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ) that integrated feature extraction and classification for the automatic classification of heartbeats in an ECG signal. Since this task has specific characteristics such as, inconsistency optimization...
Recently, hyperspectral images are used to estimate the yield of food crops. The images consist of a large number of bands which requires sophisticated method for its analysis. One approach to reduce computational cost and to accelerate knowledge discovery is by eliminating bands that do not add value to the analysis. In this paper, a genetic algorithm based new sequence of principal component regression...
This paper presents a paddy growth stages classification using MODIS remote sensing images with support vector machines (SVMs). We collected the paddy growth stages data samples from a series of MODIS mages acquired from March to July 2012 along paddy field area only. The data are collected based on growth stages phenology of paddy using spectral profile which consists of at least 9 classes for growth...
QR decomposition of matrix is one of the important problems in the field of matrix theory. Besides, there are also so many extensive applications that using QR decomposition. Because of that, there are many researchers have been studying about algorithm for this decomposition. Two of those researchers are Feng Tianxiang and Liu Hongxia. In their paper, they proposed new algorithm to make QR decomposition...
The electrocardiogram (ECG) plays an important role in monitoring and preventing heart attacks. In this paper, we propose and compare the use of Daubechies WT (Daubechies Wavelet Transformation), Kernel PCA (Principal Component Analysis), and PCA as feature extraction methods in improving arrhythmia signals classification. The Kernel PCA employs linear, polynomial, and Gaussian kernels. We examine...
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