Signal classification through multifractal analysis and complex domain neural networks

This paper describes a system capable of classifying stochastic self-affine nonstationary signals produced by nonlinear systems. The classification and the analysis of these signals are important because these are generated by many real-world processes. The first stage of the signal classification process entails the transformation of the signal into the multifractal dimension domain, through the computation of the variance fractal dimension trajectory (VFDT). Features can then be extracted from the VFDT using a Kohonen self-organizing feature map. The second stage involves the use of a complex domain neural network and a probabilistic neural network to determine the class of a signal based on these extracted features. The results of this paper show that these techniques can be successful in creating a classification system which can obtain correct classification rates of about 87% when performing classification of such signals without knowing the number of classes.     

Thermoplastic vulcanizates obtained by reaction-induced phase separation: Interplay between phase separation dynamics,final morphology and mechanical properties

Reaction-induced phase separation (RIPS) of miscible blends of poly(?-caprolactone) (PCL) and an epoxy resin based on poly(propylene oxide) (PPO) was used to prepare thermoplastic vulcanizates (TPVs) with fine rubber dispersions. Scanning electron microscopy (SEM) confirmed the formation of cross-linked rubber particles dispersed in the thermoplastic matrix at PCL contents ≥20 wt%. The morphology development during phase separation was studied by optical microscopy (OM) and time-resolved small-angle light scattering (SALS). It was shown that higher curing temperatures lead to a decrease in rubber particle size, but at the same time lead to an increase in the extent of particle connectivity. In some cases, gelation of the PPO-rich phase limits full structure development, which leads to extensive connectivity between the dispersed rubber particles and a strong deterioration in tensile properties.     

A Multisite Comparison of Actuarial Risk Instruments for Sex Offenders.

Four actuarial instruments for the prediction of violent and sexual reoffending (the Violence Risk Appraisal Guide [VRAG], Sex Offender Risk Appraisal Guide [SORAG], Rapid Risk Assessment for Sex Offender Recidivism [RRASOR], and Static-99) were evaluated in 4 samples of sex offenders (N = 396). Although all 4 instruments predicted violent (including sexual) recidivism and recidivism known to be sexually motivated, areas under the receiver operating characteristic (ROC) were consistently higher for the VRAG and the SORAG. The instruments performed better when there were fewer missing items and follow-up time was fixed, with an ROC area up to .84 for the VRAG, for example, under such favorable conditions. Predictive accuracy was higher for child molesters than for rapists, especially for the Static-99 and the RRASOR. Consistent with past research, survival analyses revealed that those offenders high in both psychopathy and sexual deviance were an especially high-risk group. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Performance evaluation of a biotrickling filter degrading mixtures of hydrophobic and hydrophilic compounds

The removal of a mixture of painting solvents from waste air using a biofiltration process was evaluated in this project. The pollutants removed included hydrophobic (aromatic hydrocarbons) and hydrophilic (water soluble ketones and esters) compounds. A trickle bed reactor with a defined immobilized mixed culture on polyethylene Pall rings was utilized in this biodegradation study. The removal efficiencies (RE) of the individual groups of pollutants during loading experiments were determined. An increase of the aromatic hydrocarbons loading resulted in a drop of their RE_AROM with no effect on the RE value of ketones. The overloading of ketones caused a rapid drop in RE_AROM and a small drop in RE_KET. To achieve a restoration of the biocatalyst degradation properties after the increase in loading, an addition of phosphate to the aqueous medium was implemented which successfully restored the removal efficiency.     

On the effectiveness of early life cycle defect prediction with Bayesian Nets

Standard practice in building models in software engineering normally involves three steps: collecting domain knowledge (previous results, expert knowledge); building a skeleton of the model based on step 1 including as yet unknown parameters; estimating the model parameters using historical data. Our experience shows that it is extremely difficult to obtain reliable data of the required granularity, or of the required volume with which we could later generalize our conclusions. Therefore, in searching for a method for building a model we cannot consider methods requiring large volumes of data. This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. The approach supports (1) and (2), does not require (3), yet still makes accurate defect predictions (an R ² of 0.93 between predicted and actual defects). Since our method does not require detailed domain knowledge it can be applied very early in the process life cycle. The model incorporates a set of quantitative and qualitative factors describing a project and its development process, which are inputs to the model. The model variables, as well as the relationships between them, were identified as part of a major collaborative project. A dataset, elicited from 31 completed software projects in the consumer electronics industry, was gathered using a questionnaire distributed to managers of recent projects. We used this dataset to validate the model by analyzing several popular evaluation measures (R ², measures based on the relative error and Pred). The validation results also confirm the need for using the qualitative factors in the model. The dataset may be of interest to other researchers evaluating models with similar aims. Based on some typical scenarios we demonstrate how the model can be used for better decision support in operational environments. We also performed sensitivity analysis in which we identified the most influential variables on the number of residual defects. This showed that the project size, scale of distributed communication and the project complexity cause the most of variation in number of defects in our model. We make both the dataset and causal model available for research use.     

Perceived employment barriers and their relation to workforce-entry intent among people with HIV/AIDS.

As treatments have improved health and quality of life for people with HIV/AIDS, many have contemplated workforce reentry. Workforce reentry rarely occurs among people with illness-related disability. The authors mailed a survey that included workforce-entry-related concerns to 1,991 HIV/AIDS clients. Factor analysis extracted 6 areas of concern (benefits loss, work-related health, job skills, discrimination, personal health care, workplace accommodation). Levels of concern generally increased with HIV acuity level and time since last worked. Work-related health concerns predicted consideration of workforce entry, and work-related health concerns and benefits-loss concerns predicted estimated time to return to work. Findings provide quantitative validation of intuitive categories of workforce-entry concerns among people with HIV/AIDS and suggest that concerns may shift with progress toward workforce entry. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modellierung in der Lehre an Hochschulen: Thesen und Erfahrungen

Zusammenfassung  Nicht erst seit Modellierung zum Modewort geworden ist, ist Modellierung ein wichtiges Thema in der Informatikausbildung. Dieser Beitrag beleuchtet in zw?lf Thesen das Warum, Was, Wie viel, Wo, Wann und Wie von Modellierung in der Lehre im Rahmen informatikbezogener Studieng?nge. Die Thesen basieren auf der Erfahrung des Verfassers mit einer seit über zehn Jahren gehaltenen Modellierungsvorlesung an der Universit?t Zürich sowie dem Gedankenaustausch mit anderen Hochschullehrerinnen und -lehrern im Rahmen der GI-Workshopreihe ,,Modellierung“. Zus?tzlich liefert eine Befragung von Absolventinnen und Absolventen an der Universit?t Zürich empirische Evidenz für eine Reihe der Thesen.     

Numerische Berechnung von Holzkonstruktionen unter Verwendung eines orthotropen elasto-plastischen Werkstoffmodells

To be able to perform more realistic simulations of timber constructions with modern numerical simulation methods like the finite element method (FEM), a suitable constitutive material model is required. Such a material model was developed by Mackenzie-Helnwein et al. (2005) for clear spruce wood. This paper presents an application-oriented adaption and usage of the mentioned material model, its implementation in a FE software as well as performing ultimate load analyses using FEM and the validation of the material model by means of the comparison of results of FE Simulations and experiments on the structure level (Fleischmann 2005). Further, some aspects with respect to the standardisation are discussed in one of the two examples.