In this paper, I describe the theoretical background that led to the creation of software for interactive dance performance that interprets rhythm in dance movement as musical rhythm. This software was implemented as a library of external objects for Max/MSP[12] that processes data from an object or library that performs frame-differencing analysis of a video stream in real time in this program...

We analyze the effects on prediction intervals of fitting ARIMA models to series with stochastic trends, when the underlying components are heteroscedastic. We show that ARIMA prediction intervals may be inadequate when only the transitory component is heteroscedastic. In this case, prediction intervals based on the unobserved component models tend to the homoscedastic intervals as the predicti...

Analysing and modelling efforts on production throughput are getting more complex due to random variables in today’s dynamic production systems. The objective of this study is to take multiple random variables of production into account when aiming for production throughput with higher accuracy of prediction. In the dynamic manufacturing environment, production lines have to cope with changes i...

This paper reexamines the time series properties of the US ex post real interest rate. The estimation of the ARFIMA model using the Conditional Sum of Squares (CSS) method reveals that the ex post real interest rate can be well described using a fractionally integrated process.  2000 Elsevier Science S.A. All rights reserved.

The ability to create forecasts and discover trends is a value to almost any industry. The challenge comes in finding the right data and the appropriate tools to analyze and model such data. This paper aims to demonstrate that it may be possible to create technology forecasting models through the use of patent groups. The focus will be on applying time series modeling techniques to a collection...

In traffic video, background differencing is frequently applied for detecting moving vehicles. Therefore, background extraction is a key technology in traffic flow video detection system. In this paper, the way of modeling for background with single Gaussian model is introduced, and a simple experimental system for the background extraction in traffic video is designed and realized. Furthermore...

In a recent article (Larsen, Morel, and Miller, J .Comput. Phys. 69, 283 (1987)), a theoretical method is described for assessing the accuracy of transport differencing schemes in highly scattering media with optically thick spatial meshes. In the present article, this method is extended to enable one to determine the accuracy of such schemes in the presence of numerically unresolved boundary l...

A state–space approach provides a general unified framework for calculation of the Beveridge–Nelson decomposition for a wide variety of time series models, including all univariate and vector ARIMA models.  2002 Elsevier Science B.V. All rights reserved.

In this paper, we study the dual long memory property of the Korean stock market. For this purpose, the ARFIMA–FIGARCH model is applied to two daily Korean stock price indices (KOSPI and KOSDAQ). Our empirical results indicate that long memory dynamics in the returns and volatility can be adequately estimated by the joint ARFIMA–FIGARCH model. We also found that the assumption of a skewed Stude...

In the framework of TEI@I methodology, this paper proposes a combined forecast method integrating contextual knowledge (CFMIK). With the help of contextual knowledge, this method considers the effects of those factors that cannot be explicitly included in the forecast model, and thus it can efficiently decrease the forecast error resulted from the irregular events. Through a container throughpu...