Parametrized Architecture for Hough Transform Recursive Evaluation

Paper submitted to International Workshop on Spectral Methods and Multirate Signal Processing (SMMSP), Barcelona, España, 2003.

Hough Transform recursive evaluation using Distributed Arithmetic

Paper submitted to the IFIP International Conference on Very Large Scale Integration (VLSI-SOC), Darmstadt, Germany, 2003.

Motivational profiles Spanish students of Compulsory Secondary Education: Differential analysis of academic self-attributions

Academic goals and academic self-attributions are relevant variables in school settings. The objective of this study is to identify whether there are combinations of multiple goals that lead to different motivational profiles and to determine whether there are significant differences between the groups obtained regarding causal attributions of success and failure (ability, effort, or external causes) in Mathematics and Language and Literature, and in overall academic performance. The Goal Achievement Tendencies Questionnaire (AGTQ) and the Sydney Attribution Scale (SAS) were administered to a sample of 2022 students of compulsory secondary education, ranging in age from 12 to 16 years (M = 13.81, SD = 1.35). Cluster analysis identified four motivational profiles: a group of students with a high generalized motivation profile, a group of students with low generalized motivation profile, a group of students with predominance of learning goals and achievement goals, and a final group of students with predominance of social reinforcement goals. Results revealed statistically significant differences between the profiles obtained in academic self-attributions.

Characterization and electrochemical properties of conducting nanocomposites synthesized from p-anisidine and aniline with titanium carbide by chemical oxidative method

A novel polymer/TiC nanocomposites “PPA/TiC, poly(PA-co-ANI)/TiC and PANI/TiC” was successfully synthesized by chemical oxidation polymerization at room temperature using p-anisidine and/or aniline monomers and titanium carbide (TiC) in the presence of hydrochloric acid as a dopant with ammonium persulfate as oxidant. These nanocomposites obtained were characterized by Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and thermogravimetric analysis (TGA). XRD indicated the presence of interactions between polymers and TiC nanoparticle and the TGA revealed that the TiC nanoparticles improve the thermal stability of the polymers. The electrical conductivity of nanocomposites is in the range of 0.079–0.91 S cm−1. The electrochemical behavior of the polymers extracted from the nanocomposites has been analyzed by cyclic voltammetry. Good electrochemical response has been observed for polymer films; the observed redox processes indicate that the polymerisation on TiC nanoparticles produces electroactive polymers. These nanocomposite microspheres can potentially used in commercial applications as fillers for antistatic and anticorrosion coatings.

Overcoming performance and convergence issues of discrete transform based modeling of crosslinking classical and reversible deactivated radical polymerizations

Population balances of polymer species in terms 'of discrete transforms with respect to counts of groups lead to tractable first order partial differential equations when ali rate constants are independent of chain length and loop formation is negligible [l]. Average molecular weights in the absence ofgelation are long known to be readily found through integration of an initial value problem. The extension to size distribution prediction is also feasible, but its performance is often lower to the one provided by methods based upon real chain length domain [2]. Moreover, the absence ofagood starting procedure and a higher numerical sensitivity hás decisively impaired its application to non-linear reversibly deactivated polymerizations, namely NMRP [3].

Riemann's method of integration: its extensions with an application.

Mode of access: Internet.

An iterative method for solving nonsymmetric linear systems with dynamic estimation of parameters /

Vita.

An efficient iterative procedure for use with the finite element method,

Vita.

Generalized decomposition of incomplete finite automata /

Vita.

Reservoir area-capacity table by conic method : Hydrologic Engineering Center computer program 23-J2-L233.

At head of cover title: Generalized computer program.

Examining the Differential Effects of a Universal SEL Curriculum on Student Functioning on a Dual Continua Model of Mental Health

Thesis (Ph.D.)--University of Washington, 2016-06

Psychometric properties of the drinking expectancy questionnaire: A review of the factor structure and a proposed new scoring method

Objective: Expectancies about the outcomes of alcohol consumption are widely accepted as important determinants of drinking. This construct is increasingly recognized as a significant element of psychological interventions for alcohol-related problems. Much effort has been invested in producing reliable and valid instruments to measure this construct for research and clinical purposes, but very few have had their factor structure subjected to adequate validation. Among them, the Drinking Expectancies Questionnaire (DEQ) was developed to address some theoretical and design issues with earlier expectancy scales. Exploratory factor analyses, in addition to validity and reliability analyses, were performed when the original questionnaire was developed. The object of this study was to undertake a confirmatory analysis of the factor structure of the DEQ. Method: Confirmatory factor analysis through LISREL 8 was performed using a randomly split sample of 679 drinkers. Results: Results suggested that a new 5-factor model, which differs slightly from the original 6-factor version, was a more robust measure of expectancies. A new method of scoring the DEQ consistent with this factor structure is presented. Conclusions: The present study shows more robust psychometric properties of the DEQ using the new factor structure.

Implicit stochastic Runge-Kutta methods for stochastic differential equations

In this paper we construct implicit stochastic Runge-Kutta (SRK) methods for solving stochastic differential equations of Stratonovich type. Instead of using the increment of a Wiener process, modified random variables are used. We give convergence conditions of the SRK methods with these modified random variables. In particular, the truncated random variable is used. We present a two-stage stiffly accurate diagonal implicit SRK (SADISRK2) method with strong order 1.0 which has better numerical behaviour than extant methods. We also construct a five-stage diagonal implicit SRK method and a six-stage stiffly accurate diagonal implicit SRK method with strong order 1.5. The mean-square and asymptotic stability properties of the trapezoidal method and the SADISRK2 method are analysed and compared with an explicit method and a semi-implicit method. Numerical results are reported for confirming convergence properties and for comparing the numerical behaviour of these methods.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focussed recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the best choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy. (C) 2004 Elsevier B.V. All rights reserved.

A genetic estimation algorithm for parameters of stochastic ordinary differential equations

A generic method for the estimation of parameters for Stochastic Ordinary Differential Equations (SODEs) is introduced and developed. This algorithm, called the GePERs method, utilises a genetic optimisation algorithm to minimise a stochastic objective function based on the Kolmogorov-Smirnov statistic. Numerical simulations are utilised to form the KS statistic. Further, the examination of some of the factors that improve the precision of the estimates is conducted. This method is used to estimate parameters of diffusion equations and jump-diffusion equations. It is also applied to the problem of model selection for the Queensland electricity market. (C) 2003 Elsevier B.V. All rights reserved.