Heterogeneous cooperative co-evolution memetic differential evolution algorithms for big data optimisation problems

Evolutionary algorithms (EAs) have recently been suggested as candidate for solving big data optimisation problems that involve very large number of variables and need to be analysed in a short period of time. However, EAs face scalability issue when dealing with big data problems. Moreover, the performance of EAs critically hinges on the utilised parameter values and operator types, thus it is impossible to design a single EA that can outperform all other on every problem instances. To address these challenges, we propose a heterogeneous framework that integrates a cooperative co-evolution method with various types of memetic algorithms. We use the cooperative co-evolution method to split the big problem into sub-problems in order to increase the efficiency of the solving process. The subproblems are then solved using various heterogeneous memetic algorithms. The proposed heterogeneous framework adaptively assigns, for each solution, different operators, parameter values and local search algorithm to efficiently explore and exploit the search space of the given problem instance. The performance of the proposed algorithm is assessed using the Big Data 2015 competition benchmark problems that contain data with and without noise. Experimental results demonstrate that the proposed algorithm, with the cooperative co-evolution method, performs better than without cooperative co-evolution method. Furthermore, it obtained very competitive results for all tested instances, if not better, when compared to other algorithms using a lower computational times.

A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

Difference-based meta-analytic procedures for between-participant and/or within-participant designs : a tutorial review for sports and exercise scientists

The aim of this paper is to provide a contemporary summary of statistical and non-statistical meta-analytic procedures that have relevance to the type of experimental designs often used by sport scientists when examining differences/change in dependent measure(s) as a result of one or more independent manipulation(s). Using worked examples from studies on observational learning in the motor behaviour literature, we adopt a random effects model and give a detailed explanation of the statistical procedures for the three types of raw score difference-based analyses applicable to between-participant, within-participant, and mixed-participant designs. Major merits and concerns associated with these quantitative procedures are identified and agreed methods are reported for minimizing biased outcomes, such as those for dealing with multiple dependent measures from single studies, design variation across studies, different metrics (i.e. raw scores and difference scores), and variations in sample size. To complement the worked examples, we summarize the general considerations required when conducting and reporting a meta-analysis, including how to deal with publication bias, what information to present regarding the primary studies, and approaches for dealing with outliers. By bringing together these statistical and non-statistical meta-analytic procedures, we provide the tools required to clarify understanding of key concepts and principles.

Effectiveness of current treatment approaches for benzodiazepine discontinuation : a meta-analysis.

Aims: To assess the effectiveness of current treatment approaches to assist benzodiazepine discontinuation. Methods: A systematic review of approaches to benzodiazepine discontinuation in general practice and out-patient settings was undertaken. Routine care was compared with three treatment approaches: brief interventions, gradual dose reduction (GDR) and psychological interventions. GDR was compared with GDR plus psychological interventions or substitutive pharmacotherapies. Results: Inclusion criteria were met by 24 studies, and a further eight were identified by future search. GDR [odds ratio (OR) = 5.96, confidence interval (CI) = 2.08–17.11] and brief interventions (OR = 4.37, CI = 2.28–8.40) provided superior cessation rates at post-treatment to routine care. Psychological treatment plus GDR were superior to both routine care (OR = 3.38, CI = 1.86–6.12) and GDR alone (OR = 1.82, CI = 1.25–2.67). However, substitutive pharmacotherapies did not add to the impact of GDR (OR = 1.30, CI = 0.97– 1.73), and abrupt substitution of benzodiazepines by other pharmacotherapy was less effective than GDR alone (OR = 0.30, CI = 0.14–0.64). Few studies on any technique had significantly greater benzodiazepine discontinuation than controls at follow-up. Conclusions: Providing an intervention is more effective than routine care. Psychological interventions may improve discontinuation above GDR alone. While some substitutive pharmacotherapies may have promise, current evidence is insufficient to support their use.

Indigenous men's support groups and social and emotional wellbeing : a meta-synthesis of the evidence

Indigenous men’s support groups are designed to empower men to take greater control and responsibility for their health and wellbeing. They provide health education sessions, counselling, men’s health clinics, diversionary programs for men facing criminal charges, cultural activities, drug- and alcohol-free social events, and advocacy for resources. Despite there being ~100 such groups across Australia, there is a dearth of literature on their strategies and outcomes. This paper is based on participatory action research involving two north Queensland groups which were the subject of a series of five ‘phased’ evaluative reports between 2002 and 2007. By applying ‘meta-ethnography’ to the five studies, we identified four themes which provide new interpretations of the data. Self-reported benefits included improved social and emotional wellbeing, modest lifestyle modifications and willingness to change current notions of ‘gendered’ roles within the home, such as sharing housework. Our qualitative research to date suggests that through promoting empowerment, wellbeing and social cohesion for men and their families, men’s support groups may be saving costs through reduced expenditure on health care, welfare, and criminal justice costs, and higher earnings. Future research needs to demonstrate this empirically.

A meta-study of SAP financials in the Queensland Government

This thesis consists of three related studies: an ERP Major Issues Study; an Historical Study of the Queensland Government Financial Management System; and a Meta-Study that integrates these and other related studies conducted under the umbrella of the Cooperative ERP Lifecycle Knowledge Management research program. This research provides a comprehensive view of ERP lifecycle issues encountered in SAP R/3 projects across the Queensland Government. This study follows a preliminary ERP issues study (Chang, 2002) conducted in five Queensland Government agencies. The Major Issues Study aims to achieve the following: (1) identify / explicate major issues in relation to the ES life-cycle in the public sector; (2) rank the importance of these issues; and, (3) highlight areas of consensus and dissent among stakeholder groups. To provide a rich context for this study, this thesis includes an historical recount of the Queensland Government Financial Management System (QGFMS). This recount tells of its inception as a centralised system; the selection of SAP and subsequent decentralisation; and, its eventual recentralisation under the Shared Services Initiative and CorpTech. This historical recount gives an insight into the conditions that affected the selection and ongoing management and support of QGFMS. This research forms part of a program entitled Cooperative ERP Lifecycle Knowledge Management. This thesis provides a concluding report for this research program by summarising related studies conducted in the Queensland Government SAP context: Chan (2003); Vayo et al (2002); Ng (2003); Timbrell et al (2001); Timbrell et al (2002); Chang (2002); Putra (1998); and, Niehus et al (1998). A study of Oracle in the United Arab Emirates by Dhaheri (2002) is also included. The thesis then integrates the findings from these studies in an overarching Meta-Study. The Meta-Study discusses key themes across all of these studies, creating an holistic report for the research program. Themes discussed in the meta-study include common issues found across the related studies; knowledge dynamics of the ERP lifecycle; ERP maintenance and support; and, the relationship between the key players in the ERP lifecycle.