The problem of tracking targets in clutter naturally leads to a Gaussian mixture representation of the probability density function of the target state vector. Stateof-the-art Multiple Hypothesis Tracking (MHT) techniques maintain the mean, covariance and probability weight corresponding to each hypothesis, yet they rely on ad hoc merging and pruning rules to control the growth of hypotheses. T...

Fingerprint patterns are full of ridges and valleys and these structures provide essential information for matching, recognition, and classi"cation. Conventionally, most researchers use minutiae, a group of ridge endings and bifurcations, as the features of "ngerprint patterns [1]. Unfortunately, the minutia-based approach contains many time-consumption steps and relies heavily on the quality o...

Multi-dimensional transfer functions are widely used to provide appropriate data classification for direct volume rendering. Nevertheless, the design of a multi-dimensional transfer function is a complicated task. In this paper, we propose to use parallel coordinates, a powerful tool to visualize high-dimensional geometry and analyze multivariate data, for multi-dimensional transfer function de...

This paper analyzes reduction of fractional ideals in a purely cubic function field of unit rank one. The algorithm is used for generating all the reduced principal fractional ideals in the field, thereby finding the fundamental unit or the regulator, as well as computing a reduced fractional ideal equivalent to a given nonreduced one. It is known how many reduction steps are required to achiev...

Several studies (Crespi, 1942; Zeaman, 1949) have shown that performance in instrumental appetitive conditioning is directly related to the magnitude of reward contingent upon the response. Moreover, these studies have indicated that shifts in amount of reinforcement (amount of food or water) lead to rapid and appropriate changes in performance level. The results of a study by Campbell and Krae...

Noise disturbance in training data prevents a good approximation of a function by neural networks. To achieve better approximation results we combine neural networks with noise reduction algorithms. We compare different methods to distinguish between samples with high noise level (outliers) in a dataset and samples with low noise level. Drawbacks of common outlier detection approaches are analy...

Drowsiness is thought as crucial risk factor which may result in severer traffic accidents. Recently driver’s psychosomatic state adaptive driving support safety function has been highlighted to further reduce the number of traffic accidents. Consequently, reduction effect of psychosomatic adaptive safety function should be clarified to foster its penetration into commercial market. This resear...

Recent years have seen considerable interest in procedures for computing finite models of first-order logic specifications. One of the major paradigms, MACE-style model building, is based on reducing model search to a sequence of propositional satisfiability problems and applying (efficient) SAT solvers to them. A problem with this method is that it does not scale well, as the propositional for...