Regression trees are tree-based models used to solve those prediction problems in which the response variable is numeric. They differ from the better-known classification or decision trees only in that they have a numeric value rather than a class label associated with the leaves. Model trees are an extension of regression trees in the sense that they associate leaves with multivariate linear m...

The action system formalism 4] is a state-based approach to distributed computing. In this paper, it is shown how the action system formalism may be used to describe systems that communicate with their environment through synchronised value-passing. Deenitions and rules are presented for reening and decomposing such action systems into distributed implementations in which internal communication...

Linear Discriminant Analysis (LDA) is a popular feature extraction technique in statistical pattern recognition. However, it often suffers from the small sample size problem when dealing with the high dimensional data. Moreover, while LDA is guaranteed to find the best directions when each class has a Gaussian density with a common covariance matrix, it can fail if the class densities are more ...

S tepwise refinement remains a popular approach to program-design implementation, primarily because of its flexibility. As originally proposed by Niklaus Wirth, the technique involves successively decomposing design decisions into target code. With each re6nement step, the designer must + note the interdependence of subproblems, + attempt to preserve the design’s functional correctness, and + d...

An algorithm for switchbox routing, called PACKER, is presented. In an initial phase, the connectivity of each net is established in a fast way without taking the other nets into account. In general this will give rise to conflicts (short circuits). In the second stage the conflicts are removed iteratively using Connectivity preserving local transformations (CPLT’s). They “reshape” a net by dis...

Model checking complex systems always suffers from the state explosion problem. Over the last 10 years there has been lots of researches on how to mitigate the state explosion problem. As a result, many techniques have been emerged such as absiraction, compositional reasoning, and exploiting symmetry. In line with these efforts, this paper proposes stepwise model checking which exploits hierarc...

M énière’s disease is characterised by recurrent attacks of vertigo accompanied by fluctuating sensorineural hearing loss, tinnitus and a sense of aural fullness. Prosper Ménière in 1861 correctly attributed the attacks to a disorder of the inner ear, suggesting that the mechanism of causation could be similar to migraine or inner ear vasospasm, a differential diagnosis which is still relevant ...

Gene expression data are characterized by thousands even tens of thousands of measured genes on only a few tissue samples. This can lead either to possible overfitting and dimensional curse or even to a complete failure in analysis of microarray data. Gene selection is an important component for gene expression-based tumor classification systems. In this paper, we develop a hybrid particle swar...

We propose a new method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis (ICA). Secondly, the most discriminant eigenassays extracted by ICA are selected by the sequential floating forward selection technique. Finally, support vector machine is used to cl...

Studies of mild traumatic brain injury (MTBI) suggest that most individuals recover rapidly and return to their everyday activities. However, a percentage of MTBI patients report persistent problems with cognitive, physical, and emotional symptoms. There is also evidence that some experience changes in occupational functioning following MTBI. The current study used a stepwise discriminant funct...