Inspiration and strength

Thoughts on Aborignal women's leadership.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Wind uplift strength of trapezoidal steel cladding with closely spaced ribs

When crest-fixed thin trapezoidal steel cladding with closely spaced ribs is subjected to wind uplift/suction forces, local dimpling or pull-through failures occur prematurely at their screw connections because of the large stress concentrations in the cladding under the screw heads. Currently, the design of crest-fixed profiled steel cladding is mainly based on time consuming and expensive laboratory tests due to the lack of adequate design rules. In this research, a shell finite element model of crest-fixed trapezoidal steel cladding with closely spaced ribs was developed and validated using experimental results. The finite element model included a recently developed splitting criterion and other advanced features including geometric imperfections, buckling effects, contact modelling and hyperelastic behaviour of neoprene washers, and was used in a detailed parametric study to develop suitable design formulae for local failures. This paper presents the details of the finite element analyses, large scale experiments and their results including the new wind uplift design strength formulae for trapezoidal steel cladding with closely spaced ribs. The new design formulae can be used to achieve both safe and optimised solutions.

Effect of vitamin D supplementation on muscle strength: a systematic review and meta-analysis

Summary This systematic review demonstrates that vitamin D supplementation does not have a significant effect on muscle strength in vitamin D replete adults. However, a limited number of studies demonstrate an increase in proximal muscle strength in adults with vitamin D deficiency. Introduction The purpose of this study is to systematically review the evidence on the effect of vitamin D supplementation on muscle strength in adults. Methods A comprehensive systematic database search was performed. Inclusion criteria included randomised controlled trials (RCTs) involving adult human participants. All forms and doses of vitamin D supplementation with or without calcium supplementation were included compared with placebo or standard care. Outcome measures included evaluation of strength. Outcomes were compared by calculating standardised mean difference (SMD) and 95% confidence intervals. Results Of 52 identified studies, 17 RCTs involving 5,072 participants met the inclusion criteria. Meta-analysis showed no significant effect of vitamin D supplementation on grip strength (SMD −0.02, 95%CI −0.15,0.11) or proximal lower limb strength (SMD 0.1, 95%CI −0.01,0.22) in adults with 25(OH)D levels >25 nmol/L. Pooled data from two studies in vitamin D deficient participants (25(OH)D <25 nmol/L) demonstrated a large effect of vitamin D supplementation on hip muscle strength (SMD 3.52, 95%CI 2.18, 4.85). Conclusion Based on studies included in this systematic review, vitamin D supplementation does not have a significant effect on muscle strength in adults with baseline 25(OH)D >25 nmol/L. However, a limited number of studies demonstrate an increase in proximal muscle strength in adults with vitamin D deficiency. Keywords Muscle – Muscle fibre – Strength – Vitamin D

Manufacturing Yield Improvement by Clustering

Dealing with product yield and quality in manufacturing industries is getting more difficult due to the increasing volume and complexity of data and quicker time to market expectations. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large databases. Growing self-organizing map (GSOM) is established as an efficient unsupervised datamining algorithm. In this study some modifications to the original GSOM are proposed for manufacturing yield improvement by clustering. These modifications include introduction of a clustering quality measure to evaluate the performance of the programme in separating good and faulty products and a filtering index to reduce noise from the dataset. Results show that the proposed method is able to effectively differentiate good and faulty products. It will help engineers construct the knowledge base to predict product quality automatically from collected data and provide insights for yield improvement.

The Biodex Isokinetic Dynamometer for knee strength assessment in children : advantages and limitations

Objective: To critically appraise the Biodex System 4 isokinetic dynamometer for strength assessment of children. Methods: Appraisal was based on experiences from two independent laboratories involving testing of 213 children. Issues were recorded and the manufacturer was consulted regarding appropriate solutions. Results: The dynamometer had insufficient height adjustment for alignment of the knee for some children, requiring the construction of padding to better fit the child within the dynamometer. Potential for entrapment of the non-testing leg was evident in the passive and eccentric modes and a leg bracket restraint was constructed. Automated gravity correction did not operate when protocols were linked or data was exported to an external device. Conclusions: Limitations were noted, some of which were applicable to knee strength testing in general and others which were specific to use with children. However, most of these obstacles could be overcome, making the Biodex System 4 suitable for assessment of knee strength in children.