Object tracking is commonly used in video surveillance, but typically video with full frame rate is sent. We previously have shown that full frame rate is not needed, but it is unclear what the appropriate frame rate to send or whether we can further reduce the frame rate. This paper answers these questions for two commonly used object tracking algorithms (frame-differencing-based blob tracking...

We present a generalisation of the double long memory ARFIMA-FIGARCH model introducing time-varying memory coefficients both in the mean and in the variance. The model satisfies the empirical evidence of changing memory observed in average temperature series and can provide useful improvements in the forecasting, simulation and pricing issues related to weather derivatives. We provide an applic...

The authors present a new convolution-type kernel estimator of the marginal density of an MA(1) process with general error distribution. They prove the √ n-consistency of the nonparametric estimator and give asymptotic expressions for the mean square and the integrated mean square error of some unobservable version of the estimator. An extension to MA(q) processes is presented in the case of th...

A tiie-differencing scheme consisting of an initializing step and N repetitions of a set of steps is proposed. For linear equations, the scheme is of Nth order. It is easily programmed and uses a minimal amount of storage space. The order may be changed by changing one parameter. An improved scheme is of Nth order even for nonlinear equations , for N 54.

This paper analyzes U.S. university press datasets (2001-2007) to determine net publishers’ revenues and net publishers’ units, the major markets and channels of distribution (libraries and institutions; college adoptions; and general retailer sales) that these presses relied on, and the intense competition these presses confronted from commercial scholarly, trade, and college textbook publishe...

In this paper we present a simple yet effective temporal differencing based moving region detection scheme which can be used in limited resource condition such as in ad-hoc sensor network. Our objective is to achieve realtime detection in these low-end image sensor nodes. By double-threshold temporal differencing we can exclude the effect of global motion as well as detect the real motion regio...

Morehead City, North Carolina, faced a moratorium on new construction because of problems with its sewage system. We developed an autoregressive integrated moving average (ARIMA) transfer function-intervention model to help town officials explain the sources of variation in the volume of sewage-treatment-plant discharge to the state officials who had imposed the moratorium on extending the sewa...

This paper examines the forecasting performance of ARIMA and artificial neural networks model with published stock data obtained from New York Stock Exchange. The empirical results obtained reveal the superiority of neural networks model over ARIMA model. The findings further resolve and clarify contradictory opinions reported in literature over the superiority of neural networks and ARIMA mode...

This paper tackles the problem of robust change detection in image sequences from static cameras. Motion cues are detected using frame differencing with an adaptive background estimation modelled by a mixture of Gaussians. Illumination invariance and elimination or detection of shadows is achieved by using a colour chromaticity representation of the image data.

This paper presents a synthetic traffic modeling approach to generate bursty, long-range dependent (LRD) traffic flows for ATM network simulations. The approach uses Fractional-ARIMA processes and a set of mathematical transformations to generate traffic streams with a wide range of user-specified traffic characteristics. With this modeling approach, the user can control the short-range and lon...