519 resultados para optimisation methods
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This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.
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Integration of biometrics is considered as an attractive solution for the issues associated with password based human authentication as well as for secure storage and release of cryptographic keys which is one of the critical issues associated with modern cryptography. However, the widespread popularity of bio-cryptographic solutions are somewhat restricted by the fuzziness associated with biometric measurements. Therefore, error control mechanisms must be adopted to make sure that fuzziness of biometric inputs can be sufficiently countered. In this paper, we have outlined such existing techniques used in bio-cryptography while explaining how they are deployed in different types of solutions. Finally, we have elaborated on the important facts to be considered when choosing appropriate error correction mechanisms for a particular biometric based solution.
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We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.
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Internationally there is interest in developing the research skills of pre-service teachers as a means of ongoing professional renewal with a distinct need for systematic and longitudinal investigation of student learning. The current study takes a unique perspective by exploring the research learning journey of pre-service teachers participating in a transnational degree programme. Using a case-study design that includes both a self-reported and direct measure of research knowledge, the results indicate a progression in learning, as well as evidence that this research knowledge is continued or maintained when the pre-service teachers return to their home university. The findings of this study have implications for both pre-service teacher research training and transnational programmes.
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One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.
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In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression. Clustering and classification of such data can, indeed, highlight patterns and provide insight on biological processes. A common approach is to consider genes and samples of microarray datasets as nodes in a bipartite graphs, where edges are weighted e.g. based on the expression levels. In this paper, using a previously-evaluated weighting scheme, we focus on search algorithms and evaluate, in the context of biclustering, several variations of Genetic Algorithms. We also introduce a new heuristic “Propagate”, which consists in recursively evaluating neighbour solutions with one more or one less active conditions. The results obtained on three well-known datasets show that, for a given weighting scheme,optimal or near-optimal solutions can be identified.
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Background: Overviews of systematic reviews (SRs) are useful for public health policy; however there is an absence of Cochrane Overviews covering public health (PH) topics. Objectives: We sought to analyze the methodological approaches used in existing Cochrane Overviews and Protocols for overviews (primarily clinical in nature), and compare these to the methods and approaches used in PH overviews (non-Cochrane). The intent was to identify issues that would be relevant for undertaking Cochrane overviews. Methods: We conducted a descriptive analysis of overviews published between 1999 and 2014. We searched the Cochrane Database of Systematic Reviews for Cochrane Protocols for overviews and Cochrane Overviews, and the HealthEvidence.org for PH overviews. The primary characteristics of the overviews and elements of the methodology were extracted and compared. Results: A total of 61 overviews of SRs were included in our analysis; specifically, this included 21 Cochrane Protocols for overviews, 15 Cochrane Overviews, and 27 non-Cochrane PH overviews. Amongst the overviews, the most significant differences are that PH overviews (non-Cochrane) tend to: include earlier and more reviews, greater number of participants, allow lower levels of evidence, use assessment tools other than AMSTAR (A Measurement Tool to Assess Systematic Reviews, i.e. a tool for assessing quality of SRs), not assess quality of evidence in reviews, search more databases overall, specify search limits including English-only reviews, and not consider recent primary studies for inclusion. Some of these differences clearly related to quality, however many relate to the nuances of PH interventions. Conclusions: The methodology in Cochrane overviews and PH overviews varies widely. Future PH overviews may benefit from the Cochrane methodology but the Cochrane approach requires modification to accommodate PH research methodology. Additionally, the use of databases that pre-screen and quality assess relevant PH systematic reviews may help expedite the search process.
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We performed a contingent valuation survey to elicit the opportunity cost of bed-days consumed by healthcare-associated infections in 11 European hospitals. The opportunity cost of a bed-day was significantly lower than the accounting cost; median values were i72 and i929, respectively (P ! .001). Accounting methods overestimate the opportunity cost of bed-days...
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Unlicensed driving is a serious problem in many countries, despite ongoing improvements in traffic law enforcement practices and technology. The term ‘unlicensed driver' is generally used to refer to people who operate a motor vehicle or motorcycle without a valid driver's licence, including those who: • have let their licence expire; • have been disqualified or suspended from driving; • hold an inappropriate class of licence for the vehicle they drive; • drive outside the restrictions of a special licence; • don’t currently hold a licence; or • have never held a licence.
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Background Influenza infection during pregnancy is associated with significant morbidity and mortality. Immunisation against influenza is recommended during pregnancy in several countries but uptake of vaccine is poor. There are limited data on vaccine uptake, and the determinants of vaccination, in Australian Aboriginal and/or Torres Islander women during pregnancy. This study aimed to establish an appropriate methodology and collect pilot data on vaccine uptake and attitudes towards, and perceptions of, maternal influenza vaccination in that population in order to inform the development of larger studies. Methods A mixed-methods study comprised of a cross-sectional survey and yarning circles (focus groups) amongst Aboriginal and Torres Strait Islander women attending two primary health care services. The women were between 28 weeks gestation and less than 16 weeks post-birth. These data were supplemented by data collected in an ongoing national Australian study of maternal influenza vaccination. Aboriginal research officers collected community data and data from the yarning circles which were based on a narrative enquiry framework. Descriptive statistics were used to analyse quantitative data and thematic analyses were applied to qualitative data. Results Quantitative data were available for 53 women and seven of these women participated in the yarning circles. The proportion of women who reported receipt of an influenza vaccine during their pregnancy was 9/53. Less than half of the participants (21/53) reported they had been offered the vaccine in pregnancy. Forty-three percent reported they would get a vaccine if they became pregnant again. Qualitative data suggested perceived benefits to themselves and their infants were important factors in the decision to be vaccinated but there was insufficient information available to women to make that choice. Conclusions The rates of influenza immunisation may continue to remain low for Aboriginal and/or Torres Strait Islander women during pregnancy. Access to services and recommendations by a health care worker may be factors in the lower rates. Our findings support the need for larger studies directed at monitoring and understanding the determinants of maternal influenza vaccine uptake during pregnancy in Australian Aboriginal and Torres Strait Islander women. This research will best be achieved using methods that account for the social and cultural contexts of Aboriginal and Torres Strait Islander communities in Australia.
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This paper examines the feasibility of using vertical light pipes to naturally illuminate the central core of a multilevel building not reached by window light. The challenges addressed were finding a method to extract and distribute equal amounts of light at each level and designing collectors to improve the effectiveness of vertical light pipes in delivering low elevation sunlight to the interior. Extraction was achieved by inserting partially reflecting cones within transparent sections of the pipes at each floor level. Theory was formulated to estimate the partial reflectance necessary to provide equal light extraction at each level. Designs for daylight collectors formed from laser cut panels tilted above the light pipe were developed and the benefits and limitations of static collectors as opposed to collectors that follow the sun azimuth investigated. Performance was assessed with both basic and detailed mathematical simulation and by observations made with a five level model building under clear sky conditions.
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Purpose/Objectives: To examine and compare the reliability of four body composition methods commonly used in assessing breast cancer survivors. Design: Cross-sectional. Setting: A rehabilitation facility at a university-based comprehensive cancer center in the southeastern United States. Sample: 14 breast cancer survivors aged 40-71 years. Methods: Body fat (BF) percentage was estimated via bioelectric impedance analysis (BIA), air displacement plethysmography (ADP), and skinfold thickness (SKF) using both three- and seven-site algorithms, where reliability of the methods was evaluated by conducting two tests for each method (test 1 and test 2), one immediately after the other. An analysis of variance was used to compare the results of BF percentage among the four methods. Intraclass correlation coefficient (ICC) was used to test the reliability of each method. Main Research Variable: BF percentage. Findings: Significant differences in BF percentage were observed between BIA and all other methods (three-site SKF, p < 0.001; seven-site SKF, p < 0.001; ADP, p = 0.002). No significant differences (p > 0.05) in BF percentage between three-site SKF, seven-site SKF, and ADP were observed. ICCs between test 1 and test 2 for each method were BIA = 1, ADP = 0.98, three-site SKF = 0.99, and seven-site SKF = 0.94. Conclusions: ADP and both SKF methods produce similar estimates of BF percentage in all participants, whereas BIA overestimated BF percentage relative to the other measures. Caution is recommended when using BIA as the body composition method for breast cancer survivors who have completed treatment but are still undergoing adjuvant hormonal therapy. Implications for Nursing: Measurements of body composition can be implemented very easily as part of usual care and should serve as an objective outcome measure for interventions designed to promote healthy behaviors among breast cancer survivors. - See more at: https://onf.ons.org/onf/38/4/comparison-body-composition-assessment-methods-breast-cancer-survivors#sthash.5djfTS1Q.dpuf
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This paper presents a study on the effectiveness of two forms of reinforced grout confining systems for hollow concrete block masonry. The systems considered are: (1) a layer of grout directly confining the unreinforced masonry, and (2) a layer of grout indirectly confining the unreinforced masonry through block shells. The study involves experimental testing and finite-element (FE) modeling of six diagonally loaded masonry panels containing the two confining systems. The failure mode, the ultimate load, and the load-deformation behaviors of the diagonally loaded panels were successfully simulated using the finite-element model. In-plane shear strength and stiffness of the masonry thus determined are used to evaluate some selected models of the confined masonry shear including the strut-and-tie model reported in the literature. The evaluated strut width is compared with the prediction of the FE model and then extended for rational prediction of the strength of confined masonry shear walls.
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This project is a step forward in developing effective methods to mitigate voltage unbalance in urban residential networks. The method is proposed to reduce energy losses and improve quality of service in strongly unbalanced low-voltage networks. The method is based on phase swapping as well as optimal placement and sizing of Distribution Static Synchronous Compensator (D-STATCOM) using a Particle Swarm Optimisation method.
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This paper describes the use of exploratory focus groups to inform the development of a survey instrument in a sequential phase mixed methods study investigating differences in secondary students’ career choice capability. Five focus groups were conducted with 23 year 10 students in the state of New South Wales (NSW), Australia. Analysis of the focus group data informed the design of the instrument for the second phase of the research project: a large-scale cross-sectional survey. In this paper, we discuss the benefits of using sequential phase mixed method approaches when inquiring into complex phenomena such as human capability.