Coordinated probabilistic optimal decision-making model for multi-area ATC with risk control

In the decision-making of multi-area ATC (Available Transfer Capacity) in electricity market environment, the existing resources of transmission network should be optimally dispatched and coordinately employed on the premise that the secure system operation is maintained and risk associated is controllable. The non-sequential Monte Carlo simulation is used to determine the ATC probability density distribution of specified areas under the influence of several uncertainty factors, based on which, a coordinated probabilistic optimal decision-making model with the maximal risk benefit as its objective is developed for multi-area ATC. The NSGA-II is applied to calculate the ATC of each area, which considers the risk cost caused by relevant uncertainty factors and the synchronous coordination among areas. The essential characteristics of the developed model and the employed algorithm are illustrated by the example of IEEE 118-bus test system. Simulative result shows that, the risk of multi-area ATC decision-making is influenced by the uncertainties in power system operation and the relative importance degrees of different areas.

Reliability of the Five Factor Wellness Inventory among male adolescents

Measuring adolescent wellness can assist researchers and practitioners in determining lifestyle behaviors in which adolescents are deficient. An appropriate objective assessment may assist male adolescents who feel uncomfortable revealing behaviors that may indicate wellness deficits. The authors examined the test-retest reliability of the Five Factor Wellness Inventory (5F-Wel) with a sample of male adolescents. Thirty-five participants self-completed the 5F-Wel on two separate occasions, 7 days apart. Limits of agreement, intraclass correlation coefficients, and paired t tests were calculated to investigate agreement and whether systematic differences existed between administrations. The initial findings indicate the 5F-Wel is reliable for use among male adolescents and support its use in research.

Multi-criteria ranking and source apportionment of airborne particulate matter

Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

A multi-layered approach for site detection in UAS emergency landing scenarios using geometry-based image segmentation

This paper presents an alternative approach to image segmentation by using the spatial distribution of edge pixels as opposed to pixel intensities. The segmentation is achieved by a multi-layered approach and is intended to find suitable landing areas for an aircraft emergency landing. We combine standard techniques (edge detectors) with novel developed algorithms (line expansion and geometry test) to design an original segmentation algorithm. Our approach removes the dependency on environmental factors that traditionally influence lighting conditions, which in turn have negative impact on pixel-based segmentation techniques. We present test outcomes on realistic visual data collected from an aircraft, reporting on preliminary feedback about the performance of the detection. We demonstrate consistent performances over 97% detection rate.

Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm

Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

Effects of free flow state highway traffic parameters on the performance of amplify and forward cooperative multi-hop vehicular networks

In this paper we analyse the effects of highway traffic flow parameters like vehicle arrival rate and density on the performance of Amplify and Forward (AF) cooperative vehicular networks along a multi-lane highway under free flow state. We derive analytical expressions for connectivity performance and verify them with Monte-Carlo simulations. When AF cooperative relaying is employed together with Maximum Ratio Combining (MRC) at the receivers the average route error rate shows 10-20 fold improvement compared to direct communication. A 4-8 fold increase in maximum number of traversable hops can also be observed at different vehicle densities when AF cooperative communication is used to strengthen communication routes. However the theorical upper bound of maximum number of hops promises higher performance gains.

Acute illness is a risk factor for impaired respiratory function during nurse-administered procedural sedation and analgesia in the cardiac catheterization laboratory

Impaired respiratory function (IRF) during procedural sedation and analgesia (PSA) poses considerable risk to patient safety as it can lead to inadequate oxygenation and ventilation. Risk factors that can be screened prior to the procedure have not been identified for the cardiac catheterization laboratory (CCL).

Urban transit quality of service : user perception and behaviour

Despite its potential multiple contributions to sustainable policy objectives, urban transit is generally not widely used by the public in terms of its market share compared to that of automobiles, particularly in affluent societies with low-density urban forms like Australia. Transit service providers need to attract more people to transit by improving transit quality of service. The key to cost-effective transit service improvements lies in accurate evaluation of policy proposals by taking into account their impacts on transit users. If transit providers knew what is more or less important to their customers, they could focus their efforts on optimising customer-oriented service. Policy interventions could also be specified to influence transit users’ travel decisions, with targets of customer satisfaction and broader community welfare. This significance motivates the research into the relationship between urban transit quality of service and its user perception as well as behaviour. This research focused on two dimensions of transit user’s travel behaviour: route choice and access arrival time choice. The study area chosen was a busy urban transit corridor linking Brisbane central business district (CBD) and the St. Lucia campus of The University of Queensland (UQ). This multi-system corridor provided a ‘natural experiment’ for transit users between the CBD and UQ, as they can choose between busway 109 (with grade-separate exclusive right-of-way), ordinary on-street bus 412, and linear fast ferry CityCat on the Brisbane River. The population of interest was set as the attendees to UQ, who travelled from the CBD or from a suburb via the CBD. Two waves of internet-based self-completion questionnaire surveys were conducted to collect data on sampled passengers’ perception of transit service quality and behaviour of using public transit in the study area. The first wave survey is to collect behaviour and attitude data on respondents’ daily transit usage and their direct rating of importance on factors of route-level transit quality of service. A series of statistical analyses is conducted to examine the relationships between transit users’ travel and personal characteristics and their transit usage characteristics. A factor-cluster segmentation procedure is applied to respodents’ importance ratings on service quality variables regarding transit route preference to explore users’ various perspectives to transit quality of service. Based on the perceptions of service quality collected from the second wave survey, a series of quality criteria of the transit routes under study was quantitatively measured, particularly, the travel time reliability in terms of schedule adherence. It was proved that mixed traffic conditions and peak-period effects can affect transit service reliability. Multinomial logit models of transit user’s route choice were estimated using route-level service quality perceptions collected in the second wave survey. Relative importance of service quality factors were derived from choice model’s significant parameter estimates, such as access and egress times, seat availability, and busway system. Interpretations of the parameter estimates were conducted, particularly the equivalent in-vehicle time of access and egress times, and busway in-vehicle time. Market segmentation by trip origin was applied to investigate the difference in magnitude between the parameter estimates of access and egress times. The significant costs of transfer in transit trips were highlighted. These importance ratios were applied back to quality perceptions collected as RP data to compare the satisfaction levels between the service attributes and to generate an action relevance matrix to prioritise attributes for quality improvement. An empirical study on the relationship between average passenger waiting time and transit service characteristics was performed using the service quality perceived. Passenger arrivals for services with long headways (over 15 minutes) were found to be obviously coordinated with scheduled departure times of transit vehicles in order to reduce waiting time. This drove further investigations and modelling innovations in passenger’ access arrival time choice and its relationships with transit service characteristics and average passenger waiting time. Specifically, original contributions were made in formulation of expected waiting time, analysis of the risk-aversion attitude to missing desired service run in the passengers’ access time arrivals’ choice, and extensions of the utility function specification for modelling passenger access arrival distribution, by using complicated expected utility forms and non-linear probability weighting to explicitly accommodate the risk of missing an intended service and passenger’s risk-aversion attitude. Discussions on this research’s contributions to knowledge, its limitations, and recommendations for future research are provided at the concluding section of this thesis.

Letter : anxiety score as a risk factor for radial artery vasospasm during radial interventions : a pilot study

I read with interest the article in Angiology that determined the role of anxiety level on radial artery spasm during transradial coronary angiography.1 As the importance of conducting more randomised controlled trials using anxiolytics to define the relation between anxiety and vasospasm was noted by the authors, I offer the following insights for investigators to consider when conducting such research. While previous research has already identified that moderate procedural sedation and opioid analgesia reduces the incidence of vasospasm,2 the identification of risk factors in the present study is hypothesis generating as to how outcomes might be even further improved. It is possible that selectively applying either even more intensive sedation and analgesia or complementary non-pharmacological stress-reducing therapies, such as music therapy or visualisation and attentive behaviour, to patients ‘at-risk’ of vasospasm (women and those with high levels of anxiety prior to the procedure) might lead to even better patient outcomes...

Property case competition : multi-stakeholder reflection

Pacific Rim Real Estate Society has conducted four property case competitions from 2009 to 2012. The competition provides opportunities for undergraduate students to present their proposal on a given case study. All students were locked down with their four team members for five hours without external help to ensure a level playing field across participants. Students prepared their presentation and defended their arguments in front of experts in property industry and academia. The aim of this paper is reflecting on the feedback received from stakeholders involved in the case competition. Besides exploring what students have gained from the competitions, this paper provides an insight on the opportunities and challenges for the new format of competition to be introduced in 2013. Over the last four competitions, there were three universities participated in all the four consecutive events, four universities partook in two events and another four universities only competed once. Some universities had a great advantage by having previous experiences by participating in similar international business competitions. Findings show that the students have benefited greatly from the event including improving their ability in problem solving and other non-technical skills. Despite the aforementioned benefits, the PRRES closed-book case competition is proven not viable thus future competition needs to minimise the travel and logistic cost.

Classifier selection using sequential error ratio criterion for multi-instance and multi-sample fusion

Classifier selection is a problem encountered by multi-biometric systems that aim to improve performance through fusion of decisions. A particular decision fusion architecture that combines multiple instances (n classifiers) and multiple samples (m attempts at each classifier) has been proposed in previous work to achieve controlled trade-off between false alarms and false rejects. Although analysis on text-dependent speaker verification has demonstrated better performance for fusion of decisions with favourable dependence compared to statistically independent decisions, the performance is not always optimal. Given a pool of instances, best performance with this architecture is obtained for certain combination of instances. Heuristic rules and diversity measures have been commonly used for classifier selection but it is shown that optimal performance is achieved for the `best combination performance' rule. As the search complexity for this rule increases exponentially with the addition of classifiers, a measure - the sequential error ratio (SER) - is proposed in this work that is specifically adapted to the characteristics of sequential fusion architecture. The proposed measure can be used to select a classifier that is most likely to produce a correct decision at each stage. Error rates for fusion of text-dependent HMM based speaker models using SER are compared with other classifier selection methodologies. SER is shown to achieve near optimal performance for sequential fusion of multiple instances with or without the use of multiple samples. The methodology applies to multiple speech utterances for telephone or internet based access control and to other systems such as multiple finger print and multiple handwriting sample based identity verification systems.

Predicate encryption for multi-inner-products

Predicate encryption is a new primitive that supports flexible control over access to encrypted data. We study predicate encryption systems, evaluating a wide class of predicates. Our systems are more expressive than the existing attribute-hiding systems in the sense that the proposed constructions support not only all existing predicate evaluations but also arbitrary conjunctions and disjunctions of comparison and subset queries. Toward our goal, we propose encryption schemes supporting multi-inner-product predicate and provide formal security analysis. We show how to apply the proposed schemes to achieve all those predicate evaluations.

Development of the palliative care needs assessment tool (PC-NAT) for use by multi-disciplinary health professionals

Needs assessment strategies can facilitate prioritisation of resources. To develop a needs assessment tool for use with advanced cancer patients and caregivers, to prompt early intervation. A convenience sample of 103 health professionals viewed three videotaped consultations involving a simulated patient, his/her caregiver and a health professional, completed the Palliative Care Needs Assessment Tool (PC-NAT) and provided feedback on clarity, content and acceptability of the PC-NAT. Face and content validity, acceptability and feasibility of the PC-NAT were confirmed. Kappa scores indicated adequate inter-rater reliability for the majority of domains; the patient spirituality domain and the caregiver physical and family and relationship domains had low reliability. The PC-NAT can be used by health professionals with a range of clinical expertise to identify individuals' needs, thereby enabling early intervention. Further psychometric testing and an evaluation to assess the impact of the systematic use of the PC-NAT on quality of life, unmet needs and service utilisation of patients and caregivers are underway.

Repeated intrauterine exposures to inflammatory stimuli attenuated transforming growth factor-β signaling in the ovine fetal lung

Background: Bronchopulmonary dysplasia (BPD) is one of the most common complications after preterm birth and is associated with intrauterine exposure to bacteria. Transforming growth factor-β (TGFβ) is implicated in the development of BPD. Objectives: We hypothesized that different and/or multiple bacterial signals could elicit divergent TGFβ signaling responses in the developing lung. Methods: Time-mated pregnant Merino ewes received an intra-amniotic injection of lipopolysaccharide (LPS) and/or Ureaplasma parvum serovar 3 (UP) at 117 days' and/or 121/122 days' gestational age (GA). Controls received an equivalent injection of saline and or media. Lambs were euthanized at 124 days' GA (term = 150 days' GA). TGFβ1, TGFβ2, TGFβ3, TGFβ receptor (R)1 and TGFβR2 protein levels, Smad2 phosphorylation and elastin deposition were evaluated in lung tissue. Results: Total TGFβ1 and TGFβ2 decreased by 24 and 51% after combined UP+LPS exposure, whereas total TGFβ1 increased by 31% after 7 days' LPS exposure but not after double exposures. Alveolar expression of TGFβR2 decreased 75% after UP, but remained unaltered after double exposures. Decreased focal elastin deposition after single LPS exposure was prevented by double exposures. Conclusions: TGFβ signaling components and elastin responded differently to intrauterine LPS and UP exposure. Multiple bacterial exposures attenuated TGFβ signaling and normalized elastin deposition.