Improving an inverse model of sheet metal forming by neural network based regression

An inverse model for a sheet meta l forming process aims to determine the initial parameter levels required to form the final formed shape. This is a difficult problem that is usually approached by traditional methods such as finite element analysis. Formulating the problem as a classification problem makes it possible to use well established classification algorithms, such as decision trees. Classification is, however, generally based on a winner-takes-all approach when associating the output value with the corresponding class. On the other hand, when formulating the problem as a regression task, all the output values are combined to produce the corresponding class value. For a multi-class problem, this may result in very different associations compared with classification between the output of the model and the corresponding class. Such formulation makes it possible to use well known regression algorithms, such as neural networks. In this paper, we develop a neural network based inverse model of a sheet forming process, and compare its performance with that of a linear model. Both models are used in two modes, classification mode and a function estimation mode, to investigate the advantage of re-formulating the problem as a function estimation. This results in large improvements in the recognition rate of set-up parameters of a sheet metal forming process for both models, with a neural network model achieving much more accurate parameter recognition than a linear model.

Time for a change : applying the Good Lives Model of rehabilitation to a high-risk violent offender

In this article we operationalise the theoretical concepts of the Good Lives Model (GLM) of offender rehabilitation by providing a step-by-step framework for assessment, formulation, treatment planning, and monitoring with a high-risk violent offender residing in the community. The case study illustrates how the GLM can be applied to complement and enhance traditional Risk-Management interventions and shows how the GLM's clinical relevance extends from sex offending to broader offending typologies.

A model of organizational ethics education

Purpose – This paper aims to propose a model of ethics education for corporate organizations framed as an holistic approach to the problem of how to teach ethics.

Design/methodology/approach – As a conceptual/viewpoint piece, this paper recognizes that for ethics education to be successful, individuals and corporations must have an appreciation of their role in the society at large. In addition, there needs to be preparedness on the part of the corporation to engage in an ethical manner with the marketplace with which it interacts.

Findings – Ethics education should not exist in a vacuum, that is just within the organization, but it should reflect the values of the organization as they impact upon and are impacted upon by society in general.

Research/limitations/implications – This model is predicated on a belief that organizations must craft their ethics education program with as much care and enthusiasm as they craft their strategic plan. The employees are the organization's representatives and they need to be made as clear as one can make them as to the ethical philosophy of the company and what is expected of them. Adults have a capacity for greater reasoning and reflection on their life experiences than children and thus the concept of “andragogy” provides a more satisfactory method to fashion education programs for adults than some more traditional methods that focus on training and not education.

Practical implications – When considering the ethics education of its employees, corporations need to place that education in context as it relates to the organization and the wider society as a whole. It is suggested that an ethics education program needs to provide a framework for understanding the concepts of ethics and moral development. Using this framework as the basis for the education offered, the education program is then expanded into an examination of a range of ethical issues presented in a variety of ways.

Originality/value – This paper proposes an integrated way to approach ethics education that ensures that the antecedents of the program are considered in the context of the ethics of individuals, the society and in turn the organization, hence the holistic approach.

The microcosmic model of worm propagation

Each year, large amounts of money and labor are spent on patching the vulnerabilities in operating systems and various popular software to prevent exploitation by worms. Modeling the propagation process can help us to devise effective strategies against those worms' spreading. This paper presents a microcosmic analysis of worm propagation procedures. Our proposed model is different from traditional methods and examines deep inside the propagation procedure among nodes in the network by concentrating on the propagation probability and time delay described by a complex matrix. Moreover, since the analysis gives a microcosmic insight into a worm's propagation, the proposed model can avoid errors that are usually concealed in the traditional macroscopic analytical models. The objectives of this paper are to address three practical aspects of preventing worm propagation: (i) where do we patch? (ii) how many nodes do we need to patch? (iii) when do we patch? We implement a series of experiments to evaluate the effects of each major component in our microcosmic model. Based on the results drawn from the experiments, for high-risk vulnerabilities, it is critical that networks reduce the number of vulnerable nodes to below 80%. We believe our microcosmic model can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.

A comparative study of the constant observation model of care

This study investigated two different nursing models of care for ‘at-risk’ patients requiring constant observation. One patient group was managed with a specialised nursing team and the other with a traditional custodial model utilising attendants and agency nurses. Patients cared for with the specialist team had fewer adverse events and a shorter period under constant observation.

We do not see things as they are, we see them as we are : a multidimensional worldview model of obsessive-compulsive disorder

Cognitive-behavioral models of obsessive-compulsive disorder (OCD) assign a central role to specific beliefs and coping strategies in the development, maintenance and exacerbation of obsessive-compulsive (OC) symptoms. These models also implicate perceptions of self and the world in the development and maintenance of OC phenomena (e.g., overestimation of threat, sociotropy, ambivalent or sensitive sense of self, looming vulnerability), although such self and world domains have not always been emphasized in recent research. Following recent recommendations (Doron & Kyrios, 2005), the present study undertook a multifaceted investigation of self and world perceptions in a nonclinical sample, using a coherent worldview framework (Janoff-Bulman, 1989, 1991). Beliefs regarding the self and the world were found to predict OC symptom severity over and above beliefs outlined in traditional cognitive-behavioral models of OCD. Self and world beliefs were also related to other OC-relevant beliefs. Implications of these findings for theory and treatment of OCD are discussed.

Developing teachers of inquiry: an emerging humanities model of inquiry (HMI)

Inquiry pedagogies have been an integral mode by which understandings connected to the Humanities have been developed in primary classrooms. For the purposes of this paper, the Humanities incorporates areas of learning associated with Civics and Citizenship, History, Geography and Economics. In primary classrooms, these discipline areas have often been taught in interdisciplinary ways through other iterations such as Social Studies and Studies of Society and Environment. This paper is a reflection on the work with pre-service teachers in a quest to disrupt more traditional and transmissive pedagogies for teaching and learning in this area. It proposes a new way of conceptualising inquiry for rigorous and disciplinary learning.

Determining the sensitivity of the Antarctic amphipod Orchomenella pinguides to metals using a joint model of survival response to exposure concentration and duration

Developing water quality guidelines for Antarctic marine environments requires understanding the sensitivity of local biota to contaminant exposure. Antarctic invertebrates have shown slower contaminant responses in previous experiments compared to temperate and tropical species in standard toxicity tests. Consequently, test methods which take into account environmental conditions and biological characteristics of cold climate species need to be developed. This study investigated the effects of five metals on the survival of a common Antarctic amphipod, Orchomenella pinguides. Multiple observations assessing mortality to metal exposure were made over the 30 days exposure period. Traditional toxicity tests with quantal data sets are analysed using methods such as maximum likelihood regression (probit analysis) and Spearman–Kärber which treat individual time period endpoints independently. A new statistical model was developed to integrate the time-series concentration–response data obtained in this study. Grouped survival data were modelled using a generalized additive mixed model (GAMM) which incorporates all the data obtained from multiple observation times to derive time integrated point estimates. The sensitivity of the amphipod, O. pinguides, to metals increased with increasing exposure time. Response times varied for different metals with amphipods responding faster to copper than to cadmium, lead or zinc. As indicated by 30 days lethal concentration (LC50) estimates, copper was the most toxic metal (31 µg/L), followed by cadmium (168 µg/L), lead (256 µg/L) and zinc (822 µg/L). Nickel exposure (up to 1.12 mg/L) did not affect amphipod survival. Using longer exposure durations and utilising the GAMM model provides an improved methodology for assessing sensitivities of slow responding Antarctic marine invertebrates to contaminants.

DeepSoft: a vision for a deep model of software

Although software analytics has experienced rapid growth as a research area, it has not yet reached its full potential for wide industrial adoption. Most of the existing work in software analytics still relies heavily on costly manual feature engineering processes, and they mainly address the traditional classification problems, as opposed to predicting future events. We present a vision for \emph{DeepSoft}, an \emph{end-to-end} generic framework for modeling software and its development process to predict future risks and recommend interventions. DeepSoft, partly inspired by human memory, is built upon the powerful deep learning-based Long Short Term Memory architecture that is capable of learning long-term temporal dependencies that occur in software evolution. Such deep learned patterns of software can be used to address a range of challenging problems such as code and task recommendation and prediction. DeepSoft provides a new approach for research into modeling of source code, risk prediction and mitigation, developer modeling, and automatically generating code patches from bug reports.