The importance of supplier selection is nowadays highlighted more than ever as companies have realized that efficient supplier selection can significantly improve the performance of their supply chain. In this paper, an integrated model that applies Data Envelopment Analysis (DEA) and Support Vector Machine (SVM) is developed to select efficient suppliers based on their predicted efficiency sco...

The right and left hand Motor Imagery (MI) analysis based on the electroencephalogram (EEG) signal can directly link the central nervous system to a computer or a device. This study aims to identify a set of robust and nonlinear effective brain connectivity features quantified by transfer entropy (TE) to characterize the relationship between brain regions from EEG signals and create a hierarchi...

Educational games can induce a wide range of emotions, and so recognizing specific emotions may be valuable for an intelligent system that aims to adapt to varying student needs so as to improve learning. The long-term goal of this work is to understand how user affect impacts overall learning in an educational game. The main contribution of this paper is an investigation into the use of an uns...

As a feature selection method, support vector machinesrecursive feature elimination (SVM-RFE) can remove irrelevance features but don’t take redundant features into consideration. In this paper, it is shown why this method can’t remove redundant features and an improved technique is presented. Correlation coefficient is introduced to measure the redundancy in the selected subset with SVM-RFE. T...

No learner is generally better than another learner. If a learner performs better than another learner on some learning situations, then the first learner usually performs worse than the second learner on other situations. In other words, no single learning algorithm can perform well and uniformly outperform other algorithms over all learning or data mining tasks. There is an increasing number ...

The objective of the current study is to automatically identify the role played by the speaker in a dialogue. By using machine learning procedures over acoustic feature, we wish to automatically trace the footprints of this information through the speech signal. The acoustic feature set was selected from a large statistic-based feature sets including 1,583 dimension features. The analysis is ca...

A most basic and puzzling enigma in surface science is the description of the dissociative adsorption of O2 at the (111) surface of Al. Already for the sticking curve alone, the disagreement between experiment and results of state-of-the-art first-principles calculations can hardly be more dramatic. In this paper we show that this is caused by hitherto unaccounted spin selection rules, which gi...

We consider the problem of classifying business process instances based on structural features derived from event logs. The main motivation is to provide machine learning based techniques with quick response times for interactive computer assisted root cause analysis. In particular, we create structural features from process mining such as activity and transition occurrence counts, and ordering...

Machine translation is the task of automatically nding the translation of a source sentence in the target language. Statistical machine translation (SMT) use parallel corpora or bilingual paired corpora that are known to be translations of each other to nd a likely translation for a given source sentence based on the observed translations. The task of machine translation can be seen as an insta...