Valuing credit default swap in a non-homogeneous semi-Markovian rating based model

In this paper, we use a discrete time non-homogeneous semi-Markov model for the rating evolution of the credit quality of a firm C (see D’Amico, Janssen, and Manca Proceedings of the II international workshop in applied probablity, 2004a) and we determine the credit default swap spread for a contract between two parties, A and B that, respectively, sell and buy a protection about the failure of the firm C. We work both in the case of deterministic and stochastic recovery rate. We also highlight the link between credit risk and reliability theory.     

Learners' evaluation of a navigation support tool in distance education

Abstract   This article investigates the usability of a navigation support tool, which guides learners by generating advice on the next best step to take in a self-study e-learning course. The article draws on log data and responses from online questionnaires to provide insights into learners' evaluation of the tool, their adherence to the advice and their expectations of self-efficacy. The theoretical underpinnings of the work are described together with the experimental set-up. Results show that more than half of the learners in the experimental group adhered to the advice and held the opinion that the advice stimulated them to proceed with the course. Learners expressed a need to know what the advice was based on which can be seen as an essential element in future development of the tool.     

Visualization of participation: Does it contribute to successful computer-supported collaborative learning?

This study investigated the effects of visualization of participation during computer-supported collaborative learning (CSCL). It is hypothesized that visualization of participation could contribute to successful CSCL. A CSCL-environment was augmented with the Participation Tool (PT). The PT visualizes how much each group member contributes to his or her group’s online communication. Using a posttest-only design with a treatment (N = 52) and a control group (N = 17), it was examined whether students with access to the PT participated more and more equally during collaboration, reported higher awareness of group processes and activities, collaborated differently, and performed better than students without access to the PT. The results show that students used the PT quite intensively. Furthermore, compared to control group students, treatment group students participated more and engaged more in coordination and regulation of social activities during collaboration by sending more statements that addressed the planning of social activities. However, equality of participation, awareness of group processes and quality of the group products was not higher in the treatment condition. Still, the results of this study demonstrate that visualization of participation can contribute to successful CSCL.     

Node similarity in the citation graph

Published scientific articles are linked together into a graph, the citation graph, through their citations. This paper explores the notion of similarity based on connectivity alone, and proposes several algorithms to quantify it. Our metrics take advantage of the local neighborhoods of the nodes in the citation graph. Two variants of link-based similarity estimation between two nodes are described, one based on the separate local neighborhoods of the nodes, and another based on the joint local neighborhood expanded from both nodes at the same time. The algorithms are implemented and evaluated on a subgraph of the citation graph of computer science in a retrieval context. The results are compared with text-based similarity, and demonstrate the complementarity of link-based and text-based retrieval. Wangzhong Lu holds a Bachelor's degree from Hefei University of Technology (1993), and a Master's degree from Dalhousie University (2001), both in computer science. From 1993 to 1999 he worked as a developer with China National Computer Software and Technical Service Corp. in Beijing. From 2001 to 2005 he held industrial positions as a senior software architect in Atlantic Canada. He is currently with DST Systems, Charlotte, NC, as a senior data architect. Jeannette Janssen's research area is applied graph theory. She has worked on the problem of frequency assignment in cellular and digital broadcasting networks. Her current interest is in graph theory applied to the World Wide Web and other networked information spaces. Dr. Janssen did her Master's studies at Eindhoven University of Technology in the Netherlands, and her doctorate at Lehigh University, USA. She is currently an associate professor at Dalhousie University, Canada. Evangelos Milios received a diploma in electrical engineering from the National Technical University of Athens, and Master's and Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology. He held faculty positions at the University of Toronto and York University. He is currently a professor of computer science at Dalhousie University, Canada, where he was Director of the Graduate Program. He has served on the committees of the ACM Dissertation Award, and the AAAI/SIGART Doctoral Consortium. He has worked on the interpretation of visual and range signals for landmark-based positioning, navigation and map construction in single- and multi-agent robotics. His current research activity is centered on Networked Information Spaces, Web information retrieval, and aquatic robotics. He is a senior member of the IEEE. Nathalie Japkowicz is an associate professor at the School of Information Technology and Engineering of the University of Ottawa. She obtained her Ph.D. from Rutgers University, her M.Sc. from the University of Toronto, and her B.Sc. from McGill University. Prior to joining the University of Ottawa, she taught at Ohio State University and Dalhousie University. Her area of specialization is Machine Learning and her most recent research interests focused on the class imbalance problem. She made over 50 contributions in the form of journal articles, conference articles, workshop articles, magazine articles, technical reports or edited volumes. Yongzheng Zhang obtained a B.E. in computer applications from Southeast University, China, in 1997 and a M.S. in computer science from Dalhousie University in 2002. From 1997 to 1999 he was an instructor and undergraduate advisor at Southeast University. He also worked as a software engineer in Ricom Information and Telecommunications Co. Ltd., China. He is currently a Ph.D. candidate at Dalhousie University. His research interests are in the areas of Information Retrieval, Machine Learning, Natural Language Processing, and Web Mining, particularly centered on Web Document Summarization. A paper based on his Master's thesis received the best paper award at the 2003 Canadian Artificial Intelligence conference.     

Bernstein estimation for a copula derivative with application to conditional distribution and regression functionals

Bernstein estimators attracted considerable attention as smooth nonparametric estimators for distribution functions, densities, copulas and copula densities. The present paper adds a parallel result for the first-order derivative of a copula function. This result then leads to Bernstein estimators for a conditional distribution function and its important functionals such as the regression and quantile functions. Results of independent interest have been derived such as an almost sure oscillation behavior of the empirical copula process and a Bahadur-type almost sure asymptotic representation for the Bernstein estimator of a regression quantile function. Simulations demonstrate the good performance of the proposed estimators.     

What stimulates teachers to integrate ICT in their pedagogical practices? The use of digital learning materials in education

The question ‘What stimulates teachers to integrate Information and Communication Technologies (ICTs) in their pedagogical practices?’ was addressed in the context of teachers’ usage of digital learning materials (DLMs). We adopted Fishbein’s Integrative Model of Behavior Prediction (IMBP), to investigate the various relationships between distal and proximal variables and intention. Mediation analysis revealed that the proximal variables attitude, subjective norm, and self-efficacy towards DLMs were significant predictors of teachers’ intention to use DLMs. The contribution of subjective norm, however, was modest. Attitude, subjective norm and self-efficacy mediated the effects of the following three distal variables on intention: previous use of DLMs, perceived knowledge and skills to use DLMs, and colleagues’ usage of DLMs. Persuasive communication and skills based training seem, therefore, appropriate interventions to promote a positive attitude towards DLMs and improve self-efficacy in using DLMs.     

Controlling droplet size variability of a digital lab-on-a-chip for improved bio-assay performance

Although several applications of electrowetting on dielectric digital lab-on-a-chips are reported in literature, there is still a lack of knowledge about the influence of operational and design parameters on the performance of an analytical assay. This paper investigates how droplet size variability, introduced by droplet dispensing and splitting, influences the assay performance with respect to repeatability and accuracy and presents a novel method to reduce this variability. Both a theoretical and experimental approach were followed. Monte Carlo simulations were applied to study the cumulative effect of the variability caused by different droplet manipulations on the final assay performance. It is shown that a highly controllable droplet generation and manipulation is achieved with respect to droplet size variability through an accurate control of actuation voltage, activation time, relaxation time, and electrode size. As a case study, it is illustrated that through optimization of these parameters a complete on-chip calibration curve is obtained for a d-glucose assay with an average CV-value of 2%. These new insights aim to bring the digital lab-on-a-chip technology closer to researchers in the field of diagnostics offering them a valuable and accessible alternative to standard analysis platforms.     

Platinum as a Weak Interphase for Fiber-Reinforced Oxide-Matrix Composites

Alumina/zirconia matrix composites with platinum-coated sapphire fibers were fabricated using the technology of reaction bonding of aluminum oxide (RBAO) as the synthesis route. The interfacial behavior of both sintered and annealed specimens was investigated by crack path observations and fiber pushout tests. The results show that precious metals like platinum or related alloys can be used as high-temperature interphases for oxide/oxide composites. Weak interfaces were obtained both between fiber and coating as well as between matrix and coating, which should be suitable to achieve a damage-tolerant behavior of the composite.