Sex offenders in denial : a study into a group of forensic psychologists' attitudes regarding the corresponding impact upon risk assessment calculations and parole eligibility

A considerable proportion of convicted sex offenders maintain a stance of innocence and thus do not engage in recommended treatment programs. As a result, such offenders are often deemed to have outstanding criminogenic needs which may negatively impact upon risk assessment procedures and parole eligibility. This paper reports on a study that aimed to investigate a group of forensic psychologists’ attitudes regarding the impact of denial on risk assessment ratings as well as parole eligibility. Participants completed a confidential open-ended questionnaire. Analysis indicated that considerable variability exists among forensic psychologists in regards to their beliefs about the origins of denial and what impact such denial should have on post-prison release eligibility. In contrast, there was less disparity regarding beliefs about the percentage of innocent yet incarcerated sex offenders. This paper also reviews current understanding regarding the impact of denial on recidivism as well as upon general forensic assessments.

Calculations of capacitive couplings in induction generators to analyse shaft voltage

This paper deals with the analysis of the parameters which are effective in shaft voltage generation of induction generators. It focuses on different parasitic capacitive couplings by mathematical equations, finite element simulations and experiments. The effects of different design parameters have been studied on proposed capacitances and resultant shaft voltage. Some parameters can change proposed capacitive coupling such as: stator slot tooth, the gap between slot tooth and winding, and the height of the slot tooth, as well as the air gap between the rotor and the stator. This analysis can be used in a primary stage of a generator design to reduce motor shaft voltage and avoid additional costs of resultant bearing current mitigation.

Development of new evaluation methods for qualitative alternatives, using fuzzy calculations

Evaluation, selection and finally decision making are all among important issues, which engineers face in long run of projects. Engineers implement mathematical and nonmathematical methods to make accurate and correct decisions, whenever needed. As extensive as these methods are, effects of any selected method on outputs achieved and decisions made are still suspicious. This is more controversial and challengeable, where evaluation is made among non-quantitative alternatives. In civil engineering and construction management problems, criteria include both quantitative and qualitative ones, such as aesthetic, construction duration, building and operation costs, and environmental considerations. As the result, decision making frequently takes place among non-quantitative alternatives. It should be noted that traditional comparison methods, including clear-cut and inflexible mathematics, have always been criticized. This paper demonstrates a brief review of traditional methods of evaluating alternatives. It also offers a new decision making method using, fuzzy calculations. The main focus of this research is some engineering issues, which have flexible nature and vague borders. Suggested method provides analyzability of evaluation for decision makers. It is also capable to overcome multi criteria and multi-referees problems. In order to ease calculations, a program named DeMA is introduced.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.