The information contents of vix index and range-based volatility on volatility forecasting performance of s&p 500

In this paper, we investigate the information contents of S&P 500 VIX index and range-based volatilities by comparing their benefits on the GJR-based volatility forecasting performance. To reveal the statistical significance and ensure obtaining robust results, we employ Hansen's SPA test (2005) to examine the forecasting performances of GJR and GJR-X models for the S&P500 stock index. The results indicate that combining VIX and range-based volatilities into GARCH-type model can both enhance the one-step-ahead volatility forecasts while evaluating with different kinds of loss functions. Moreover, regardless of under-prediction, GJR-VIX model appears to be the most preferred, which implies that VIX index has better information content for improving volatility forecasting performance.Range-based volatilities; GJR-based volatility forecasting; VIX index; SPA test

System modeling and vibration reduction of a flexible beam under rotary motion

The objective of this thesis work is to reduce the end-point vibration of a flexible beam using the feedback control of the partial state variables. The dynamic model is derived from the assumed-modes method. The new feature of this model is that it is applicable to control system analysis and synthesis. A practical example is presented to illustrate the use of control law to improve the transient response --Abstract, page ii

Information Transmission Effects between Large and Small Capitalization Indices in Tokyo Stock Exchange

[[abstract]]This paper explores the information transmission effects by examining the mean and volatility spillovers between large- and small-cap stock indices in Tokyo Stock Exchange. A systematic VAR model and the bivariate VC-GJR-GARCH model (Tse and Tsui, 2002) are used to investigate the mean and volatility spillovers, respectively. The empirical results exhibit that there are no strong evidences for any mean spillovers between large- and small-cap stock indices, which is consistent with Reyes (2001). For the volatility spillovers, bidirectional information transmissions between large- and small-cap stock indices are observed. In the further research, the volatility of large-cap stock index is only affected by the positive shocks of small-cap stock index. However, the volatility of small-cap stock index is significantly affected by both positive and negative shocks of large-cap stock index. These results may provide some implications for predicting the short-term dynamics of volatility for large- and small-cap stock indices.[[journaltype]]國內[[booktype]]紙本[[countrycodes]]TW

Immersive Learning Environment with Integrated Interactive Video and Ubiquitous Technologies

100學年度沈俊毅升等參考著作[[abstract]]Information technology is an integral part of daily life in many domains, including communication, computing, entertainment, and education. However, despite its pervasiveness, digitalization in various purposes and application in many human-based activities, it still plays the role of assisting and supporting people in manipulating and acquiring information. This study developed a ubiquitous learning environment based on the connection between digital and physical information. By using mobile learning technologies, including interactive video-based multimedia technology, GPS, GIS, and the electronic map service, learners can perform location-aware learning activities and experience corresponding appearances regarding a particular location. Accordingly learners can acquire new knowledge by participating in location-aware learning activities. We also demonstrate a ubiquitous learning activity of introducing the history of Tamkang University, Taiwan, and assess the effectiveness of the proposed ubiquitous learning environment.[[journaltype]]國外[[incitationindex]]EI[[booktype]]紙本[[countrycodes]]KO

Data Mining in Online Professional Development Program Evaluation: An Exploratory Case Study

This case study explored the potential applications of data mining in the educational program evaluation of online professional development workshops for pre K-12 teachers. Multiple data mining analyses were implemented in combination with traditional evaluation instruments and student outcomes to determine learner engagement and more clearly understand the relationship between logged activities and learner experiences. Data analysis focused on the following aspects: 1) Shared learning characteristics, 2) frequent learning paths, 3) engagement prediction, 4) expectation prediction, 5) workshop satisfaction prediction, and 6) instructor quality prediction. Results indicated that interaction and engagement were important factors in learning outcomes for this workshop. In addition, participants who had online teaching experience could be expected to have a higher engagement level but prior online learning experience did NOT show a similar relationship

ProKware: integrated software for presenting protein structural properties in protein tertiary structures

Protein tertiary structure plays an essential role in deciphering protein functions, especially protein structural properties, including domains, active sites and post-translational modifications. These properties typically yield useful clues for understanding protein functions. This work presents an integrated software, named ProKware, that presents protein structural properties in protein tertiary structures, such as domains, functional sites, families, active sites, binding sites, post-translational modifications and domain–domain interaction. Using this web-based and Windows-based interface, users can manipulate and visualize three-dimensional protein structures, as well as the supported structural properties that are curated in the protein knowledge database. ProKware is an effective and convenient solution for investigating protein functions and structural relationships. This software can be accessed on the internet at

Revealing Online Learning Behaviors and Activity Patterns and Making Predictions with Data Mining Techniques in Online Teaching

This study was conducted with data mining (DM) techniques to analyze various patterns of online learning behaviors, and to make predictions on learning outcomes. Statistical models and machine learning DM techniques were conducted to analyze 17,934 server logs to investigate 98 undergraduate students’ learning behaviors in an online business course in Taiwan. The study scientifically identified students’ behavioral patterns and preferences in the online learning processes, differentiated active and passive learners, and found important parameters for performance prediction. The results also demonstrated how data mining techniques might be utilized to help improve online teaching and learning with suggestions for online instructors, instructional designers and courseware developers

The Validation of an Instrument for Evaluating the Effectiveness of Professional Development Program on Teaching Online

Attending professional development (PD) on teaching online is becoming popular for teachers in today’s K-12 online education. Due to the unique characteristics of the online instructional environments, surveys become the most feasible approach to evaluate the effectiveness of PD programs. However, there is no validated, open-access instrument available to satisfy the needs. Purpose of this study is to conduct construct validity, content validity, concurrent validity, and reliability tests on an open-access instrument for K–12 PD for online teaching. With the exception of a few items that have minor issues on content and construct validity, results show that the survey is, in general, a valid and reliable instrument. Suggestions and potential applications of the instrument are also discussed