Decision boundary setting and classifier combination for text classification

This thesis presents a promising boundary setting method for solving challenging issues in text classification to produce an effective text classifier. A classifier must identify boundary between classes optimally. However, after the features are selected, the boundary is still unclear with regard to mixed positive and negative documents. A classifier combination method to boost effectiveness of the classification model is also presented. The experiments carried out in the study demonstrate that the proposed classifier is promising.

Structural damage alarming and localization of cable-supported bridges using multi-novelty indices: A feasibility study

This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.

An improved computational method in structural dynamics

Purpose – In structural, earthquake and aeronautical engineering and mechanical vibration, the solution of dynamic equations for a structure subjected to dynamic loading leads to a high order system of differential equations. The numerical methods are usually used for integration when either there is dealing with discrete data or there is no analytical solution for the equations. Since the numerical methods with more accuracy and stability give more accurate results in structural responses, there is a need to improve the existing methods or develop new ones. The paper aims to discuss these issues. Design/methodology/approach – In this paper, a new time integration method is proposed mathematically and numerically, which is accordingly applied to single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems. Finally, the results are compared to the existing methods such as Newmark’s method and closed form solution. Findings – It is concluded that, in the proposed method, the data variance of each set of structural responses such as displacement, velocity, or acceleration in different time steps is less than those in Newmark’s method, and the proposed method is more accurate and stable than Newmark’s method and is capable of analyzing the structure at fewer numbers of iteration or computation cycles, hence less time-consuming. Originality/value – A new mathematical and numerical time integration method is proposed for the computation of structural responses with higher accuracy and stability, lower data variance, and fewer numbers of iterations for computational cycles.

Process visualization techniques for multi-perspective process comparisons

Organizations executing similar business processes need to understand the differences and similarities in activities performed across work environments. Presently, research interest is directed towards the potential of visualization for the display of process models, to support users in their analysis tasks. Although recent literature in process mining and comparison provide several methods and algorithms to perform process and log comparison, few contributions explore novel visualization approaches. This paper analyses process comparison from a design perspective, providing some practical visualization techniques as anal- ysis solutions (/to support process analysis). The design of the visual comparison has been tackled through three different points of view: the general model, the projected model and the side-by-side comparison in order to support the needs of business analysts. A case study is presented showing the application of process mining and visualization techniques to patient treatment across two Australian hospitals.

Back to normal: A retrospective, cross-sectional study of the multi-factorial determinants of normal birth in Queensland, Australia

Background Currently, care providers and policy-makers internationally are working to promote normal birth. In Australia, such initiatives are being implemented without any evidence of the prevalence or determinants of normal birth as a multidimensional construct. This study aimed to better understand the determinants of normal birth (defined as without induction of labour, epidural/spinal/general anaesthesia, forceps/vacuum, caesarean birth, or episiotomy) using secondary analyses of data from a population survey of women in Queensland, Australia. Methods Women who birthed in Queensland during a two-week period in 2009 were mailed a survey approximately three months after birth. Women (n=772) provided retrospective data on their pregnancy, labour and birth preferences and experiences, socio-demographic characteristics, and reproductive history. A series of logistic regressions were conducted to determine factors associated with having labour, having a vaginal birth, and having a normal birth. Findings Overall, 81.9% of women had labour, 66.4% had a vaginal birth, and 29.6% had a normal birth. After adjusting for other significant factors, women had significantly higher odds of having labour if they birthed in a public hospital and had a pre-existing preference for a vaginal birth. Of women who had labour, 80.8% had a vaginal birth. Women who had labour had significantly higher odds of having a vaginal birth if they attended antenatal classes, did not have continuous fetal monitoring, felt able to ‘take their time’ in labour, and had a pre-existing preference for a vaginal birth. Of women who had a vaginal birth, 44.7% had a normal birth. Women who had a vaginal birth had significantly higher odds of having a normal birth if they birthed in a public hospital, birthed outside regular business hours, had mobility in labour, did not have continuous fetal monitoring, and were non-supine during birth. Conclusions These findings provide a strong foundation on which to base resources aimed at increasing informed decision-making for maternity care consumers, providers, and policy-makers alike. Research to evaluate the impact of modifying key clinical practices (e.g., supporting women׳s mobility during labour, facilitating non-supine positioning during birth) on the likelihood of a normal birth is an important next step.

Data driven and practice-based evidence : design and development of efficient and effective clinical decision support system

Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

Effective communication during disasters: What effects community decision making & action?

Study/Objective This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. Background In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. Methods To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Results Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. Conclusion The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.

Not learning from the past: Adaptive governance challenges for Australian natural resource management

Australia’s governance arrangements for NRM have evolved considerably over the last thirty years. The impact of changes in governance on NRM planning and delivery requires assessment. We undertake a multi-method program evaluation using adaptive governance principles as an analytical frame and apply this to Queensland to assess the impacts of governance change on NRM planning and governance outcomes. Data to inform our analysis includes: 1) a systematic review of sixteen audits/evaluations of Australian NRM over a fifteen-year period; 2) a review of Queensland’s first generation NRM Plans; and 3) outputs from a Queensland workshop on NRM planning. NRM has progressed from a bottom-up grassroots movement into a collaborative regional NRM model that has been centralised by the Australian Government. We found that while some adaptive governance challenges have been addressed, others remained unresolved. Results show that collaboration and elements of multi-level governance under the regional model were positive moves, but also that NRM arrangements contained structural deficiencies across multiple governance levels in relation to public involvement in decision-making and knowledge production for problem responsiveness. These problems for adaptive governance have been exacerbated since 2008. We conclude that the adaptive governance framework for NRM needs urgent attention so that important environmental management problems can be addressed.

A normal-distribution based rating aggregation method for generating product reputations

With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.

A finite element modelling method for thin layer mortared masonry systems

This paper deals with a finite element modelling method for thin layer mortared masonry systems. In this method, the mortar layers including the interfaces are represented using a zero thickness interface element and the masonry units are modelled using an elasto-plastic, damaging solid element. The interface element is formulated using two regimes; i) shear-tension and ii) shearcompression. In the shear-tension regime, the failure of joint is consiedered through an eliptical failure criteria and in shear-compression it is considered through Mohr Coulomb type failure criterion. An explicit integration scheme is used in an implicit finite element framework for the formulation of the interface element. The model is calibrated with an experimental dataset from thin layer mortared masonry prism subjected to uniaxial compression, a triplet subjected to shear loads a beam subjected to flexural loads and used to predict the response of thin layer mortared masonry wallettes under orthotropic loading. The model is found to simulate the behaviour of a thin layer mortated masonry shear wall tested under pre-compression and inplane shear quite adequately. The model is shown to reproduce the failure of masonry panels under uniform biaxial state of stresses.

Selection criteria in the search for a sperm donor: Behavioural traits versus physical appearance

Despite extensive literature on female mate choice, empirical evidence on women’s mating preferences in the search for a sperm donor is scarce, even though this search, by isolating a male’s genetic impact on offspring from other factors like paternal investment, offers a naturally ”controlled” research setting. In this paper, we work to fill this void by examining the rapidly growing online sperm donor market, which is raising new challenges by offering women novel ways to seek out donor sperm. We not only identify individual factors that influence women’s mating preferences but find strong support for the proposition that behavioural traits (inner values) are more important in these choices than physical appearance (exterior values). We also report evidence that physical factors matter more than resources or other external cues of material success, perhaps because the relevance of good character in donor selection is part of a female psychological adaptation throughout evolutionary history. The lack of evidence on a preference for material resources, on the other hand, may indicate the ability of peer socialization and better access to resources to rapidly shape the female decision process. Overall, the paper makes useful contributions to both the literature on human behaviour and that on decision-making in extreme and highly important situations.

A hybrid of modified PSO and local search on a multi-robot search system

Particle swarm optimization (PSO), a new population based algorithm, has recently been used on multi-robot systems. Although this algorithm is applied to solve many optimization problems as well as multi-robot systems, it has some drawbacks when it is applied on multi-robot search systems to find a target in a search space containing big static obstacles. One of these defects is premature convergence. This means that one of the properties of basic PSO is that when particles are spread in a search space, as time increases they tend to converge in a small area. This shortcoming is also evident on a multi-robot search system, particularly when there are big static obstacles in the search space that prevent the robots from finding the target easily; therefore, as time increases, based on this property they converge to a small area that may not contain the target and become entrapped in that area.Another shortcoming is that basic PSO cannot guarantee the global convergence of the algorithm. In other words, initially particles explore different areas, but in some cases they are not good at exploiting promising areas, which will increase the search time.This study proposes a method based on the particle swarm optimization (PSO) technique on a multi-robot system to find a target in a search space containing big static obstacles. This method is not only able to overcome the premature convergence problem but also establishes an efficient balance between exploration and exploitation and guarantees global convergence, reducing the search time by combining with a local search method, such as A-star.To validate the effectiveness and usefulness of algorithms,a simulation environment has been developed for conducting simulation-based experiments in different scenarios and for reporting experimental results. These experimental results have demonstrated that the proposed method is able to overcome the premature convergence problem and guarantee global convergence.

The importance of group-fit in new director selection

Purpose Director selection is an important yet under-researched topic. The purpose of this paper is to contribute to extant literature by gaining a greater understanding into how and why new board members are recruited. Design/methodology/approach This exploratory study uses in-depth interviews with Australian non-executive directors to identify what selection criteria are deemed most important when selecting new director candidates and how selection practices vary between organisations. Findings The findings indicate that appointments to the board are based on two key attributes: first, the candidates’ ability to contribute complementary skills and second, the candidates’ ability to work well with the existing board. Despite commonality in these broad criteria, board selection approaches vary considerably between organisations. As a result, some boards do not adequately assess both criteria when appointing a new director hence increasing the chance of a mis-fit between the position and the appointed director. Research limitations/implications The study highlights the importance of both individual technical capabilities and social compatibility in director selections. The authors introduce a new perspective through which future research may consider director selection: fit. Originality/value The in-depth analysis of the director selection process highlights some less obvious and more nuanced issues surrounding directors’ appointment to the board. Recurrent patterns indicate the need for both technical and social considerations. Hence the study is a first step in synthesising the current literature and illustrates the need for a multi-theoretical approach in future director selection research.

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer's disease

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles in brain MRI scans, providing an efficient approach to monitor degenerative disease in clinical studies and drug trials. First, we used a set of parameterized surfaces to represent the ventricles in four subjects' manually labeled brain MRI scans (atlases). We fluidly registered each atlas and mesh model to MRIs from 17 Alzheimer's disease (AD) patients and 13 age- and gender-matched healthy elderly control subjects, and 18 asymptomatic ApoE4-carriers and 18 age- and gender-matched non-carriers. We examined genotyped healthy subjects with the goal of detecting subtle effects of a gene that confers heightened risk for Alzheimer's disease. We averaged the meshes extracted for each 3D MR data set, and combined the automated segmentations with a radial mapping approach to localize ventricular shape differences in patients. Validation experiments comparing automated and expert manual segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease- and gene-related alterations improved, as the number of atlases, N, was increased from 1 to 9. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases. We formulated a statistical stopping criterion to determine the optimal number of atlases to use. Healthy ApoE4-carriers and those with AD showed local ventricular abnormalities. This high-throughput method for morphometric studies further motivates the combination of genetic and neuroimaging strategies in predicting AD progression and treatment response. © 2007 Elsevier Inc. All rights reserved.

Scoring rules and abnormally low bids criteria in construction tenders: A taxonomic review

In the global construction context, the Best Value or Most Economically Advantageous Tender is becoming a widespread approach for contractor selection, as an alternative to other traditional awarding criteria such as the Lowest Price. In these multi-attribute tenders, the owner or auctioneer solicits proposals containing both a price bid and additional technical features. Once the proposals are received, each bidder's price bid is given an economic score according to a scoring rule, generally called an Economic Scoring Formula (ESF) and a technical score according to pre-specified criteria. Eventually, the contract is awarded to the bidder with the highest weighted overall score (economic + technical). However, Economic Scoring Formula selection by auctioneers is invariably and paradoxically a highly intuitive process in practice, involving few theoretical or empirical considerations, despite having being considered traditionally and mistakenly as objective, due to its mathematical nature. This paper provides a taxonomic classification of a wide variety of ESF and Abnormally Low Bid Criteria (ALBC) gathered in several countries with different tendering approaches. Practical implications concern the optimal design of price scoring rules in construction contract tenders, as well as future analyses of the effects of ESF and ALBC on competitive bidding behaviour.