Family caregivers of the mentally ill and adaptive coping

The issue investigated in this thesis concerned the adaptive coping strategies that caregivers of the mentally ill adopt at different stages of encounter with their family member’s illness. Specifically, family caregivers’ responses to the illness were investigated within the parameters of the Spaniol and Zipple (1994) 4-stage model of the evolution of caregivers’ responses to mental illness. The accuracy of the model’s representation of the experience of caregivers across all kinship relationships to the care-recipient was evaluated. Spaniol and Zipple proposed four stages which they termed (1) Discovery/Denial, (2) Recognition/Acceptance, (3) Coping and (4) Personal/Political Advocacy. The first stage is characterised by persistent denial of mental illness and seeking answers from multiple sources. The second stage involves caregivers’ expectations of professionals providing answers when the illness is recognised. At this stage caregivers experience guilt, embarrassment and blame. The cyclical nature of the illness impedes acceptance and caregivers experience a deep sense of loss and crisis of meaning as they gradually accept the reality of the situation. In the third stage coping replaces grieving and the issues encountered include loss of faith in professionals, disruption to family life and recurrent crises. Belief in family expertise grows and the focus of coping changes. The fourth stage proposes that caregivers become more assertive, self-blame decreases and the focus is upon changing the system. New meanings and values are integrated. This study found that the model did not accurately describe the experience of all caregivers. Caregiver did not deny mental illness and adaptive coping occurred throughout all stages. Coping evolved as the issues encountered changed and was independent of resolution of grief. The issues encountered were more extensive than the model proposed and differed according to kinship relationship to the care recipient. The ways in which adaptive coping evolved were identified, as were the issues and their accompanying responses. Caregivers coped by adaptively responding to the requirements of care provision, maintaining a sense of self worth and generating positive effect.

Factors affecting success in undergraduate computer programming

The aim of the research is to investigate factors that may explain success in elementary computer programming at the tertiary level. The first phase of the research included the identification of possible explanatory factors through a literature review, a survey of students studying introductory computing, a focus-group session with teachers of computer programming and interviews with programming students. The second phase of the research that was called the main study, involved testing the identified factors. Two different groups of programming students - one group majoring in business computing and another majoring in computer science - completed a survey questionnaire. The findings of the research are as follows. Gender is of little significance for business students but there is an adverse gender penalty for females in computer science. Secondary school assessment is inversely related to outcomes in business computing but directly influences outcomes in the first programming unit in the computer science course. As in prior research, previous knowledge and experience were demonstrated to matter, A range of other variables was found to be of little importance. The research suggests that different problem-solving techniques might be relevant in business compared with those of use in computer science.

Stereo image matching using wavelet scale-space representation

A multi-resolution technique for matching a stereo pair of images based on translation invariant discrete multi-wavelet transform is presented. The technique uses the well known coarse to fine strategy, involving the calculation of matching points at the coarsest level with consequent refinement up to the finest level. Vector coefficients of the wavelet transform modulus are used as matching features, where modulus maxima defines the shift invariant high-level features (multiscale edges) with phase pointing to the normal of the feature surface. The technique addresses the estimation of optimal corresponding points and the corresponding 2D disparity maps. Illuminative variation that can exist between the perspective views of the same scene is controlled using scale normalization at each decomposition level by dividing the details space coefficients with approximation space and then using normalized correlation. The problem of ambiguity, explicitly, and occlusion, implicitly, is addressed by using a geometric topological refinement procedure and symbolic tagging.

A novel monotonic fixed-point algorithm for l1-regularized least square vector and matrix problem

Least square problem with l₁ regularization has been proposed as a promising method for sparse signal reconstruction (e.g., basis pursuit de-noising and compressed sensing) and feature selection (e.g., the Lasso algorithm) in signal processing, statistics, and related fields. These problems can be cast as l₁-regularized least-square program (LSP). In this paper, we propose a novel monotonic fixed point method to solve large-scale l₁-regularized LSP. And we also prove the stability and convergence of the proposed method. Furthermore we generalize this method to least square matrix problem and apply it in nonnegative matrix factorization (NMF). The method is illustrated on sparse signal reconstruction, partner recognition and blind source separation problems, and the method tends to convergent faster and sparser than other l₁-regularized algorithms.

The role of emotional intelligence on the resolution of disputes involving the electronic health record

Numerous authors have expressed concerns that the introduction of the Personally Controlled Electronic Health Record (PCEHR) will lead to an escalation of disputes. Some disputes will concern the accuracy of the record whereas others will arise simply due to greater access to health care records. Online dispute resolution (ODR) programs have been successfully applied to cost-effectively help disputants resolve commercial, insurance and other legal disputes, and can also facilitate the resolution of health care related disputes. However, we expect that health differs from other application domains in ODR because of the emotional engagement patients have with their health and those of loved ones. In this study we will be looking at whether the success of an online negotiation is related to how people recognise and manage emotions, and in particular, their Emotional intelligence score.

The roses of success

Sometimes success can be detrimental to learning while failure can be good. What appears as a disaster can often lay the foundations for future success.

Usually, educators and students focus on building confidence through successful completion of learning tasks, summarised by Vygotsky’s zone of proximal development. A positive feedback loop is established if learners are successful in mastering new ideas and skills. The problem is if teachers, trainers and instructors never challenge students to the fullest extent of their abilities, as this might also ensure overconfidence, slow progress and boredom.

We should not avoid the risk of failure; science is all about the possible risk of failure. Testable hypotheses have the potential to fail an experimental or computational test; ideas that are not testable are considered to be outside the realm of science. The occasional failure shows the limits and scope of an idea’s validity and enables us to advance scientific ideas.

There is a need to find the balance between challenge that extends students, and over-extension. The former results in greater and true confidence and ability, while the latter leads to catastrophic failure and crises of confidence. Education, like life and like all scientific endeavour is about taking responsible risks safely. When we cultivate the roses of success that grow from the ashes of disaster, we must not forget that roses have thorns, or that the occasional setback or failure is just as important for learning as a succession of successes.

Learning to think, learning to learn : super teaching for super success

The early childhood years are a busy, exciting time. New discoveries, skills and competencies are a regular part of life for a young child. Early childhood teachers have the opportunity to optimise these amazing and important years. In this paper, I will discuss teaching strategies that can turn children’s possibilities into realities. The practices that will be discussed involve expanding thinking, problem-solving and developing hypotheses. These teaching strategies can build on children’s learning dispositions and their strengths and interests to put the ‘wow factor’ into learning.

Murder or manslaughter? NSW ponders the provocation problem

In Parliament last week, NSW took steps towards better understanding, and potentially solving, the problems posed by the partial defence of provocation. This comment analyses key arguments presented to the Parliamentary Select Committee for the retention and abolition of the partial defence of provocation.

A manifold approach to face recognition from low quality video across illumination and pose using implicit super-resolution

We consider the problem of matching a face in a low resolution query video sequence against a set of higher quality gallery sequences. This problem is of interest in many applications, such as law enforcement. Our main contribution is an extension of the recently proposed Generic Shape-Illumination Manifold (gSIM) framework. Specifically, (i) we show how super-resolution across pose and scale can be achieved implicitly, by off-line learning of subsampling artefacts; (ii) we use this result to propose an extension to the statistical model of the gSIM by compounding it with a hierarchy of subsampling models at multiple scales; and (iii) we describe an extensive empirical evaluation of the method on over 1300 video sequences – we first measure the degradation in performance of the original gSIM algorithm as query sequence resolution is decreased and then show that the proposed extension produces an error reduction in the mean recognition rate of over 50%.

Improving the outcomes of the South Australian mental health court: an examination of the predictors of success

 This thesis investigated the role that mental health problem-solving courts play within the Australian criminal justice system. It demonstrated that these courts can be an effective solution in the delivery of effective justice responses to vulnerable offenders, if administered in a manner that focuses on risk rather than clinical variables.

Integrability and the demand for monetary assets: an alternative approach to an old problem

This note provides necessary and su¢cient conditions for some speci…c multidimensional consumer’s surplus welfare measures to be well posed (path independent). We motivate the problem by investigating partial-equilibrium measures of the welfare costs of in‡ation. The results can also be used for checking path independence of alternative de…nitions of Divisia indexes of monetary services. Consumer theory classically approaches the integrability problem by considering compensated demands, homothetic preferences or quasi-linear utility functions. Here, instead, we consider demands of monetary assets generated from a shopping-time perspective. Paralleling the above mentioned procedure, of …nding special classes of utility functions that satisfy the integrability conditions, we try to infer what particular properties of the transacting technology could assure path independence of multidimensional welfare measures. We show that the integrability conditions are satis…ed if and only if the transacting technology is blockwise weakly separable. We use two examples to clarify the point.

Global stabilizing feedback law for a problem of biological control of mosquito-borne diseases

The control of the spread of dengue fever by introduction of the intracellular parasitic bacterium Wolbachia in populations of the vector Aedes aegypti, is presently one of the most promising tools for eliminating dengue, in the absence of an efficient vaccine. The success of this operation requires locally careful planning to determine the adequate number of mosquitoes carrying the Wolbachia parasite that need to be introduced into the natural population. The latter are expected to eventually replace the Wolbachia-free population and guarantee permanent protection against the transmission of dengue to human. In this paper, we propose and analyze a model describing the fundamental aspects of the competition between mosquitoes carrying Wolbachia and mosquitoes free of the parasite. We then introduce a simple feedback control law to synthesize an introduction protocol, and prove that the population is guaranteed to converge to a stable equilibrium where the totality of mosquitoes carry Wolbachia. The techniques are based on the theory of monotone control systems, as developed after Angeli and Sontag. Due to bistability, the considered input-output system has multivalued static characteristics, but the existing results are unable to prove almost-global stabilization, and ad hoc analysis has to be conducted.

Algoritmo Q-learning como estratégia de exploração e/ou explotação para metaheurísticas GRASP e algoritmo genético

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, don t guarantee the determination of the global optimum. Beyond the inherent difficulties related to the complexity that characterizes the optimization problems, the metaheuristics still face the dilemma of xploration/exploitation, which consists of choosing between a greedy search and a wider exploration of the solution space. A way to guide such algorithms during the searching of better solutions is supplying them with more knowledge of the problem through the use of a intelligent agent, able to recognize promising regions and also identify when they should diversify the direction of the search. This way, this work proposes the use of Reinforcement Learning technique - Q-learning Algorithm - as exploration/exploitation strategy for the metaheuristics GRASP (Greedy Randomized Adaptive Search Procedure) and Genetic Algorithm. The GRASP metaheuristic uses Q-learning instead of the traditional greedy-random algorithm in the construction phase. This replacement has the purpose of improving the quality of the initial solutions that are used in the local search phase of the GRASP, and also provides for the metaheuristic an adaptive memory mechanism that allows the reuse of good previous decisions and also avoids the repetition of bad decisions. In the Genetic Algorithm, the Q-learning algorithm was used to generate an initial population of high fitness, and after a determined number of generations, where the rate of diversity of the population is less than a certain limit L, it also was applied to supply one of the parents to be used in the genetic crossover operator. Another significant change in the hybrid genetic algorithm is the proposal of a mutually interactive cooperation process between the genetic operators and the Q-learning algorithm. In this interactive/cooperative process, the Q-learning algorithm receives an additional update in the matrix of Q-values based on the current best solution of the Genetic Algorithm. The computational experiments presented in this thesis compares the results obtained with the implementation of traditional versions of GRASP metaheuristic and Genetic Algorithm, with those obtained using the proposed hybrid methods. Both algorithms had been applied successfully to the symmetrical Traveling Salesman Problem, which was modeled as a Markov decision process

A dense GNSS meteorological network for observing deep convection in the Amazon

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An Efficient Codification to Solve Distribution Network Reconfiguration for Loss Reduction Problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)