Human emotions can be expressed as negativeto a particular stimulus. In this paper recognition based on Electroencephalogram (EEG) signals electrodes namely F3 and F4 for classification International Affective Picture System (IAPS). Hz), theta (4–8 Hz), alpha (8–16 Hz), beta (16 has been extractedfor every class of emotions combinations of the Entropy attribute extracted from the different freq...

In this paper we present gender and authorship categorisationusing the Prediction by Partial Matching (PPM) compression scheme for text from Twitter written in Arabic. The PPMD variant of the compression scheme with different orders was used to perform the categorisation. We also applied different machine learning algorithms such as Multinational Naïve Bayes (MNB), K-Nearest Neighbours (KNN), a...

In this paper, we describe our system for the topic-based Chinese message polarity classification in SIGHAN 8 Task 2. Our system integrates two SVM classifiers which consist of LinearSVC and LibSVM to train the classification model and predict the results of Chinese message polarity in the restricted resource and the unrestricted resource, respectively. In order to assure our feature engineerin...

Due to the harsh working environment of tractor, transmission can often be faulty. In order ensure reliability its operation, it must monitored and fault discovered. this paper, support vector machine (SVM) method is used. The eigenvector conversion original data uses following eigenvectors: Three modes (leakage shift clutch hydraulic cylinder, blockage oil passage, proportional valve spool) ar...

We propose an improved version of the SMO algorithm for training classification and regression SVMs, based on a Conjugate Descent procedure. This new approach only involves modest increase computational cost each iteration but, in turn, usually results substantial decrease number iterations required to converge given precision. Besides, we prove convergence iterates this as well linear rate whe...

Recent progress in the development of techniques to optimize large-scale classification problems has extended the use of multi-class classification. Specifically the use of multi-class classification algorithms when the dataset is to large to fit into limited memory available of most computers. The most prominent algorithms used today solve the multi-class classification problem through an opti...

Reduction of bit error rates in optical transmission systems is an important task that is difficult to achieve. As speeds increase, the difficulty in reducing bit error rates also increases. Channels have differing characteristics, which may change over time, and any error correction employed must be capable of operating at extremely high speeds. In this paper, a linear support vector machine i...

This paper presents the participation of the BUAA AUDR group at ImageCLEF 2012 at the Medical Image classification and Retrieval task. We performed two subtasks: modality classification and ad-hoc image-based retrieval. It was our first time to select modality classification task and we concentrated on mono-modal visual-based image classifier. We used LibSVM to train the classifier, and edge hi...

High-speed railway is a very important part of transportation industry in China, and travel choice has key effect on the development of high-speed railway. Therefore,research on travel behavior of passengers and prediction their travel choice, will offer valuable suggestion for high-speed railway running. In this paper, support vector machine (SVM) is the main method being used to predict. Supp...

The first contribution of this paper is architecture of a multipurpose system, which delegates a range of object detection tasks to a classifier, applied in special grid positions of the tested image. The second contribution is Gray Level-Radius Co-occurrence Matrix, which describes local image texture and topology and, unlike common second order statistics methods, is robust to image resolutio...