Prediction interval-based neural network controller for nonlinear processes

Prediction interval (PI) has been extensively used to predict the forecasts for nonlinear systems as PI-based forecast is superior over point-forecast to quantify the uncertainties and disturbances associated with the real processes. In addition, PIs bear more information than point-forecasts, such as forecast accuracy. The aim of this paper is to integrate the concept of informative PIs in the control applications to improve the tracking performance of the nonlinear controllers. In the present work, a PI-based controller (PIC) is proposed to control the nonlinear processes. Neural network (NN) inverse model is used as a controller in the proposed method. Firstly, a PI-based model is developed to construct PIs for every sample or time instance. The PIs are then fed to the NN inverse model along with other effective process inputs and outputs. The PI-based NN inverse model predicts the plant input to get the desired plant output. The performance of the proposed PIC controller is examined for a nonlinear process. Simulation results indicate that the tracking performance of the PIC is highly acceptable and better than the traditional NN inverse model-based controller.

Innovative model for clinical education in dietetics

Aim: Professional practice placement programs in dietetics face a number of challenges in respect of quantity, quality and sustainability. The aim of the present study is to report on the development of an innovative placement model based on a variety of training and supervision approaches to address these aforementioned challenges.

Methods: The model was developed following an investigation of existing practice and the literature with approaches that were identified as important to the requirements and constraints of dietetics clinical training incorporated into the model.

Results: Although one-on-one supervision is the predominant approach in Australian dietetic education, the educational literature and the authors' experience showed that a variety of approaches are represented in some form. The model developed involves the pairing of two students with one supervisor with students changing peer partners and supervisors every three weeks during the nine-week placement to diversify exposure to working and learning styles. The model integrates four customised approaches: incremental exposure to tasks; use of a clinical reasoning framework to help structure student understanding of the methods and judgements involved in patient care; structured enquiry in group discussions; and peer observation and feedback.

Conclusions: The model has potential to achieve efficiencies in supervisors' involvement by coordinating the skill development activities of students as a group and promoting peer-assisted learning.

A decision-making model to choose business intelligence platforms for organizations

In recent time, technology applications in different fields, especially Business Intelligence (BI) have been developed rapidly and considered to be one of the most significant uses of information technology with special position reserved. The application of BI systems provides organizations with a sense of superiority in the competitive environment. Despite many advantages, the companies applying such systems may also encounter problems in decision-making process because of the highly diversified interactions within the systems. Hence, the choice of a suitable BI platform is important to take the great advantage of using information technology in all organizational fields. The current research aims at addressing the problems existed in the organizational decision-making process, proposing and implementing a suitable BI platform using Iranian companies as case study. The paper attempts to present a solitary model based on studying different methods in BI platform choice and applying the chosen BI platform for different decisionmaking processes. The results from evaluating the effectiveness of subsequently implementing the model for Iranian Industrial companies are discussed.

OST : A transaction based online social trust model for social network and file sharing security

The continuous growth of the users pool of Social Networking web sites such as Facebook and MySpace, and their incessant augmentation of services and capabilities will in the future, meet and compare in contrast with today's Content distribution Networks (CDN) and Peer-to-Peer File sharing applications such as Kazaa and BitTorrent, but how can these two main streams applications, that already encounter their own security problems cope with the combined issues, trust for Social Networks, content and index poisoning in CDN? We will address the problems of Social Trust and File Sharing with an overlay level of trust model based on social activity and transactions, this can be an answer to enable users to increase the reliability of their online social life and also enhance the content distribution and create a better file sharing example. The aim of this research is to lower the risk of malicious activity on a given Social Network by applying a correlated trust model, to guarantee the validity of someone's identity, privacy and trustfulness in sharing content.

Towards a diversity justice management model : integrating organizational justice and diversity management

Purpose – Contemporary organizations are increasingly paying attention to incorporate diversity management practices into their systems in order to promote socially responsible actions and equitable employment outcomes for minority groups. The aim of this paper is to seek to address a major oversight in diversity management literature, the integration of organizational justice principles.

Design/methodology/approach – Drawing upon the existing literature on workforce diversity and organizational justice, the authors develop a model based on normative principles of organizational justice for justice-based diversity management processes and outcomes.

Findings – The paper proposes that effective diversity management results from a decision-making process that meets the normative principles of organizational justice (i.e. interactional, procedural and distributive justice). The diversity justice management model introduced in this article provides important theoretical and practical implications for establishing more moral and just workplaces.

Research limitations/implications – The authors have not tested the conceptual framework of the diversity justice management model, and recommend future research to take up the challenge. The payoff for doing so is to enable the establishment of socially responsible workplaces where individuals, regardless of their background, are given an equal opportunity to flourish in their assigned jobs.

Practical implications – The diversity justice management model introduced in this paper provides organizational justice (OJ)-based guidelines for managers to ensure that OJ can be objectively benchmarked and discussed amongst diversity stakeholders to continuously improve actual and perceived OJ outcomes.

Social implications – The social implication of this conceptual paper is reduction of workforce marginalization and establishment of socially responsible organizations whereby those marginalized (e.g. people with disabilities) can effectively work in their organizations.

Originality/value – This is the first attempt to establish a diveristy justice management model, which incorporates normative principles of organizational justice into diversity management processes and outcomes.

Fear of self, doubt and obsessive compulsive symptoms

BACKGROUND AND OBJECTIVES: Following observations in the literature that obsessions often contain or imply negative evaluative information about the self, Aardema et al. (2013) recently developed a measure of feared-self relevant to OCD. The current study aimed to provide further examination of the relevance of such feared self-beliefs to obsessive compulsive processes - in particular whether they partially underlie doubt in OCD-relevant situations. METHOD: Nonclinical participants (N = 463; 291 females; Mage = 25.17, SD = 7.47), were presented with three vignettes, related to washing, checking and non-OCD relevant themes, which assessed doubt through providing alternating sensory and possibility-based information. RESULTS: Higher levels of OCD symptoms and feared-self beliefs both significantly predicted both higher baseline levels of doubt and greater fluctuation in levels of doubt in both the contamination and checking scenarios, and to a much lesser extent in the control scenario. Feared-self beliefs did not predict fluctuation in doubt over-and-above OCD symptoms, consistent with a mediation model. LIMITATIONS: The main limitation was the use of a non-clinical sample, although this allowed sufficient participant numbers to test hypotheses. CONCLUSIONS: The findings provided further experimental support for reasoning processes in OCD, and suggested that feared self-beliefs may make individuals vulnerable to experiencing doubt. Additionally, these results suggested that individuals with high OCD symptoms and those with high feared self-beliefs are unable to recognise the improbable nature of possibility-based statements. Implications for treatment and theory are discussed.

Core components of communication of clinical reasoning: a qualitative study with experienced Australian physiotherapists

Communication is an important area in health professional education curricula, however it has been dealt with as discrete skills that can be learned and taught separate to the underlying thinking. Communication of clinical reasoning is a phenomenon that has largely been ignored in the literature. This research sought to examine how experienced physiotherapists communicate their clinical reasoning and to identify the core processes of this communication. A hermeneutic phenomenological research study was conducted using multiple methods of text construction including repeated semi-structured interviews, observation and written exercises. Hermeneutic analysis of texts involved iterative reading and interpretation of texts with the development of themes and sub-themes. Communication of clinical reasoning was perceived to be complex, dynamic and largely automatic. A key finding was that articulating reasoning (particularly during research) does not completely represent actual reasoning processes but represents a (re)construction of the more complex, rapid and multi-layered processes that operate in practice. These communications are constructed in ways that are perceived as being most relevant to the audience, context and purpose of the communication. Five core components of communicating clinical reasoning were identified: active listening, framing and presenting the message, matching the co-communicator, metacognitive aspects of communication and clinical reasoning abilities. We propose that communication of clinical reasoning is both an inherent part of reasoning as well as an essential and complementary skill based on the contextual demands of the task and situation. In this way clinical reasoning and its communication are intertwined, providing evidence for the argument that they should be learned (and explicitly taught) in synergy and in context.

Extra relationship involvement among women: are they different from men?

Factors related to three types ofExtra Relationship Involvement (ERI) in women were explored: emotional ERI, sexual ERJ, and II combination ofsexual and emotional ERIs . A model, based on a decision-making model of male ERI and the additional variable of commitment, was evaluated. The research involved two studies with female participants (N = 112, N = 44) who had been involved in heterosexual relationships of at least 6-month duration. The major finding was that women engage in emotional and combined ERIs but rarely enter into solely sexual ERIs. It was demonstrated that social norms, planning, relationship satisfaction, and commitment were influential in predicting emotional and combined ERI intentions. Past ERI behavior was a strong predictor offuture emotional and combined ERI behavior, but planning also added to the prediction of combined ERI behavior. Women who had engaged in emotional ERIs and combined ERIs indicated romantic affect as the main reasonfor their ERI behavior. Overall, it was demonstrated that women's intentions to engage in ERI were related to cognitive processes and relationship variables, and that ERI behavior, although generally habitual, was also predicted by cognitive processes.

A partnership model of corporate ethics

The stock market crash of 1987 had a profound effect on corporate Australia and the Australian community in general. The fall-out revealed that some of our most respected business figures had not been as ethical, or even as lawful, as we would have hoped. This impropriety produced in Australia an awakening to business ethics. Whilst many companies endeavoured to introduce ethical practices into their corporations, they perceived ethics as a way of minimising damage to the corporation and in some cases as a means of competitive advantage. What was lost was the reason that one should embark on business ethics; and that is to make the society and corporate Australia a more ethical place in which to exist.This paper proposes a model based on 2 factors: commitment and partnerships, as a means of enabling corporate Australia to refocus attention on the main purpose of being inherently ethical in all that we do. This ethical model requires a commitment to partnerships with all stakeholders both internal and external in an attempt to enhance the level of ethical business practices that are contemplated and pursued within corporate Australia. Whilst the research agenda and the information collected is Australian-based, it is hoped that the ideas contained within this paper will have a wider appeal to corporations in similar cultural settings.

Fuzzy logic based metric in software testing

How to provide cost-effective strategies for Software Testing has been one of the research focuses in Software Engineering for a long time. Many researchers in Software Engineering have addressed the effectiveness and quality metric of Software Testing, and many interesting results have been obtained. However, one issue of paramount importance in software testing – the intrinsic imprecise and uncertain relationships within testing metrics – is left unaddressed. To this end, a new quality and effectiveness measurement based on fuzzy logic is proposed. The software quality features and analogy-based reasoning are discussed, which can deal with quality and effectiveness consistency between different test projects. Experimental results are also provided to verify the proposed measurement.

Understanding requirements engineering process: a challenge for practice and education

Reviews of the state of the professional practice in Requirements Engineering (RE) stress that the RE process is both complex and hard to describe, and suggest there is a significant difference between competent and "approved" practice. "Approved" practice is reflected by (in all likelihood, in fact, has its genesis in) RE education, so that the knowledge and skills taught to students do not match the knowledge and skills required and applied by competent practitioners.

A new understanding of the RE process has emerged from our recent study. RE is revealed as inherently creative, involving cycles of building and major reconstruction of the models developed, significantly different from the systematic and smoothly incremental process generally described in the literature. The process is better characterised as highly creative, opportunistic and insight driven. This mismatch between approved and actual practice provides a challenge to RE education - RE requires insight and creativity as well as technical knowledge. Traditional learning models applied to RE focus, however, on notation and prescribed processes acquired through repetition. We argue that traditional learning models fail to support the learning required for RE and propose both a new model based on cognitive flexibility and a framework for RE education to support this model.

A morphological model for sexing nestling peregrine falcons (Falco Peregrinus Macropus) verified through genetic analysis

Adult peregrine falcons (Falco peregrinus macropus) have monotypic plumage and display strong reversed sexual dimorphism, with females significantly larger than males. Reversed sexual dimorphism is measurable among nestlings in the latter stages of their development and can therefore be used to differentiate between sexes. In the early stages of development, however, nestlings cannot be sexed with any degree of certainty because morphological differentiation between the sexes is not well developed. During this study we developed a model for sexing younger nestlings based on genetic analysis and morphometric data collected as part of a long-term banding study of this species. A discriminant function model based on morphological characteristics was developed for determining the sex of nestlings (n = 150) in the field and was shown to be 96.0% accurate. This predictive model was further tested against an independent morphometric dataset taken from a second group of nestlings (n = 131). The model correctly allocated sex to 96.2% of this second group of nestlings. Sex can reliably be determined (98.6% accurate) for nestlings that have a wing length of at least 9 cm using this model. Application of this model, therefore, allows the banding of younger nestlings and, as such, significantly increases the period of time over which banding can occur. Another important implication of this model is that by banding nestlings earlier, they are less likely to jump from the nest, therefore reducing the risk of injury to both the brood and the bander.

A model of the Australia-US exchange rate

This paper develops a model of exchange rate determination within an error correction framework. The intention is to identify both long and short term determinants that can be used to forecast the AUD/US exchange rate. The paper identifies a set of significant variables associated with exchange rate movements over a twenty year period from 1984 to 2004. Specifically, the overnight interest rate differential, Australia's foreign trade-weighted exposure to commodity prices as well as exchange rate volatility are variables identified that are able explain movements in the AUDIUS dollar relationship. An error correction model is subsequently constructed that incorporates an equilibrium correction term, a short-term interest rate differential variable, a commodity price variable and a proxy for exchange rate volatility. The model is then used to forecast out of sample and is found to dominate a naIve random walk model based on three different metrics.

Application of identification techniques to determine effect of carbon content in steels on rheological parameters during hot deformation

The objective of the present work is searching for the correlation between the carbon content in steels and the parameters of the rheological models, which are used to describe the materials behavior during hot plastic deformation. This correlation can be expected in the internal variable models, which are based on physical phenomena occurring in the material. Such a model, based on the dislocation density as the internal variable, is investigated in this work. The experiments including hot torsion tests are used for the analysis.
The procedure is composed of three parts. Plastometric tests were performed for steels with various carbon content. Optimization techniques were applied next to determine the coefficients in the internal variable rheological model for these steels. Two versions of the model are considered. One is based on the average dislocation density and the second accounts for the distribution of dislocation densities. Evaluation of correlation between carbon content and such coefficients in the models as activation energy for self diffusion, activation energy for recrystallization, grain boundary mobility, recovery coefficient etc. was the main objective of the work. In consequence, the model which may be used for simulation of hot forming processes for steels with various chemical compositions, is proposed.

Hypothesis generation for management intelligence

Investigation of the role of hypothesis formation in complex (business) problem solving has resulted in a new approach to hypothesis generation. A prototypical hypothesis generation paradigm for management intelligence has been developed, reflecting a widespread need to support management in such areas as fraud detection and intelligent decision analysis. This dissertation presents this new paradigm and its application to goal directed problem solving methodologies, including case based reasoning. The hypothesis generation model, which is supported by a dynamic hypothesis space, consists of three components, namely, Anomaly Detection, Abductive Reasoning, and Conflict Resolution models. Anomaly detection activates the hypothesis generation model by scanning anomalous data and relations in its working environment. The respective heuristics are activated by initial indications of anomalous behaviour based on evidence from historical patterns, linkages with other cases, inconsistencies, etc. Abductive reasoning, as implemented in this paradigm, is based on joining conceptual graphs, and provides an inference process that can incorporate a new observation into a world model by determining what assumptions should be added to the world, so that it can explain new observations. Abductive inference is a weak mechanism for generating explanation and hypothesis. Although a practical conclusion cannot be guaranteed, the cues provided by the inference are very beneficial. Conflict resolution is crucial for the evaluation of explanations, especially those generated by a weak (abduction) mechanism.The measurements developed in this research for explanation and hypothesis provide an indirect way of estimating the ‘quality’ of an explanation for given evidence. Such methods are realistic for complex domains such as fraud detection, where the prevailing hypothesis may not always be relevant to the new evidence. In order to survive in rapidly changing environments, it is necessary to bridge the gap that exists between the system’s view of the world and reality.Our research has demonstrated the value of Case-Based Interaction, which utilises an hypothesis structure for the representation of relevant planning and strategic knowledge. Under, the guidance of case based interaction, users are active agents empowered by system knowledge, and the system acquires its auxiliary information/knowledge from this external source. Case studies using the new paradigm and drawn from the insurance industry have attracted wide interest. A prototypical system of fraud detection for motor vehicle insurance based on an hypothesis guided problem solving mechanism is now under commercial development. The initial feedback from claims managers is promising.