Concordia University

About: Concordia University is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Context (language use) & Control theory. The organization has 13565 authors who have published 31084 publications receiving 783525 citations. The organization is also known as: Sir George Williams University & Loyola College, Montreal.

The 2016 Thermal Spray Roadmap

Abstract: Considerable progress has been made over the last decades in thermal spray technologies, practices and applications. However, like other technologies, they have to continuously evolve to meet new problems and market requirements. This article aims to identify the current challenges limiting the evolution of these technologies and to propose research directions and priorities to meet these challenges. It was prepared on the basis of a collection of short articles written by experts in thermal spray who were asked to present a snapshot of the current state of their specific field, give their views on current challenges faced by the field and provide some guidance as to the R&D required to meet these challenges. The article is divided in three sections that deal with the emerging thermal spray processes, coating properties and function, and biomedical, electronic, aerospace and energy generation applications.

Fast SVM training algorithm with decomposition on very large data sets

Abstract: Training a support vector machine on a data set of huge size with thousands of classes is a challenging problem. This paper proposes an efficient algorithm to solve this problem. The key idea is to introduce a parallel optimization step to quickly remove most of the nonsupport vectors, where block diagonal matrices are used to approximate the original kernel matrix so that the original problem can be split into hundreds of subproblems which can be solved more efficiently. In addition, some effective strategies such as kernel caching and efficient computation of kernel matrix are integrated to speed up the training process. Our analysis of the proposed algorithm shows that its time complexity grows linearly with the number of classes and size of the data set. In the experiments, many appealing properties of the proposed algorithm have been investigated and the results show that the proposed algorithm has a much better scaling capability than Libsvm, SVM/sup light/, and SVMTorch. Moreover, the good generalization performances on several large databases have also been achieved.

Viability of the "Technology Acceptance Model" in Multimedia Learning Environments: A Comparative Study

Abstract: In recent years, more and more higher education institutions have interests of integrating internetbased technologies in the classroom as part of the learning environment. Compared to studies on other information technologies, users’ behavior towards this type of systems, however, has not been assessed and understood thoroughly. In order to get more experience about human behaviors on multimedia learning environment, we conducted a comparative study consisting of 362 students, which is almost three times the sample size of the previous study, participating to test the theoretical model. Results suggest that TAM is a solid theoretical model where its validity can extend to the multimedia and e-learning context. The study provides a more intensive view of the multimedia learning system users and is an important step towards a better understanding of the user behavior on the system and a multimedia acceptance model.