This paper addresses the problem of detecting and characterizing local variability in time series. Since such data are always corrupted by observational errors, the goal is to find statistically any significant variations and ignore the inevitable random noise fluctuations. We present a simple nonparametric modeling technique and an algorithm implementing it—an improved and generalized version ...

Human health is highly dependent on the condition of health-related physical fitness and particularly body composition. Adolescence is unique in this regard, especially when the adolescents are mentally retarded, about whom information on physical fitness is limited. Thus, the objective of this paper was to study the components of health-related physical fitness with emphasis on body composit...

This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA) in X-ray angiograms. Since the single-scale Gabor filters (SSG) are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary a...

Seemingly similar individuals often experience drastically different success trajectories, with some repeatedly failing and others consistently succeeding. One explanation is preexisting variability along unobserved fitness dimensions that is revealed gradually through differential achievement. Alternatively, positive feedback operating on arbitrary initial advantages may increasingly set apart...

Evolutionary algorithms (EA) have become a standard tool for the optimization of complex composite structures because of their ability to solve combinatorial problems. However, several studies have shown that simpler algorithms, such as stochastic hill climbers (SHC) can be more efficient even on problems designed to demonstrate EAs superiority, such as the Royal Road problem. The present paper...

The ability of genetic isolation to block gene flow plays a key role in the speciation of sexually reproducing organisms. This paper analyses the hybrid zone dynamics affected by"weak"Haldane's rule, namely the incomplete hybrids inferiority (sterility/inviability) against the heterogametic (XY or ZW) sex caused by a Dobzhansky-Muller incompatibility. Different strengths of incompatibility, dis...

Most neural network hydrological modelling has used split-sample validation to ensure good out-of-sample generalisation and thus safeguard each potential solution against the danger of overfitting. However, given that each sub-set is required to provide a comprehensive and sufficient representation of both environmental inputs and hydrological processes, then to partition the data could create ...

The evolution of multicellular organisms from unicellular counterparts involved a transition in Darwinian individuality from single cells to groups. A particular challenge is to understand the nature of the earliest groups, the causes of their evolution, and the opportunities for emergence of Darwinian properties. Here we outline a conceptual framework based on a logical set of possible pathway...

FDA (the Factorized Distribution Algorithm) is an evolutionary algorithm that combines mutation and recombination by using a distribution. The distribution is estimated from a set of selected points. It is then used to generate new points for the next generation. In general a distribution defined forn binary variables has 2n parameters. Therefore it is too expensive to compute. For additively d...

A mixed order associative neural network with n neurons and a modified Hebbian learning rule can learn any function f : {−1, 1}n → R and reproduce its output as the network’s energy function. The network weights are equal to Walsh coefficients, the fixed point attractors are local maxima in the function, and partial sums across the weights of the network calculate averages for hyperplanes throu...