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...

Recent within-twin estimates of the return to schooling that use instrumental variables to correct for measurement error are considerably higher than existing estimates. This paper extends Griliches’ [Griliches (1979) Sibling models and data in economics: beginnings of a survey, Journal of Political Economy 87, S37–S64]. analysis of sibling or twin estimates of the return to schooling to show t...

This paper presents a new method of statistical differencing for the enhancement of contrast images. Our approach controls the sharpening effect using two constants in such a way that enhancement occurs in intensity edges areas and very little in uniform areas. It has been proven that our method is superior to similar existent and can be applied to pre-process satellite images.

In this paper I review three key topics in CFD that have kept researchers busy for half a century. First, the concept of upwind differencing, evident for 1-D linear advection. Second, its implementation for nonlinear systems in the form of highresolution schemes, now regarded as classical. Third, its genuinely multidimensional implementation in the form of residual-distribution schemes, the mos...

enables to reconstruct the whole sequence X1, ...,Xn (rather than the sample up to a permutation) makes of Pn a very flexible tool to represent complex and highly non-symmetric statistics. One can, for instance think of two-sample sequential rank statistics, V -statistics or fractional ARIMA processes as treated in Barbe and Broniatowski [1997] , [1998a] and [1998b]. In these references, sequen...

An approach to support the sustained evolution of traceability links is proposed and outlined. A fine-grained differencing approach on the link endpoints is used to maintain the links in a scalable manner. Here scalable refers to large software systems with thousands of links. Details of the link model and representation are given followed by the process used to evolve traceability links.

In practice, signal extraction is based on finite samples X1, ..., XT and, very often, current estimates of the interesting components (t = T ) import: a socalled ‘concurrent’ or ‘real-time’ estimate of the trend or of its turning-points has a strong prospective content, since the future evolution of the time series is likely to be conditioned by this component. Whereas forecasting tools genera...

Steganography is a way of hiding the information transmitting from sender to receiver and making the communication invisible. To enlarge the capacity of hidden secret information and to produce indistinguishable stego-image from original image with human eye, a new steganographic approach using improved pixel value differencing in a segment of four pixels and range table using perfect square nu...