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.

UNCLOS and regional action for protection of the marine environment : perspectives of the South Asian Seas region

In very clear language the United Nations Convention on the Law of the Sea (UNCLOS) calls upon the parties to initiate regional action for protection of marine environment. Although the UNCLOS gives special recognition in various ways to developing countries, the South Asian developing countries continue to encounter some bottlenecks in complying with the provisions of the Convention relating to marine environment. Against this backdrop, this paper tends to examine the need for a regional approach towards conservation of marine environment. Moreover, the paper aims to explore possible ways to establish a regional legal framework for conservation of marine environment in South Asian region. In doing so, the paper critically examines existing mechanisms already in place including the South Asian Seas Programme and South Asian Seas Action Plan

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.

Discussion paper and working paper series : Motivations, expectations and experiences of Australian rural and regional planners

Despite playing an extremely important role in shaping communities, the role and contribution of planners is not widely understood or acknowledged. At the same time, there is a shortage of planners in Australia, especially in non-urban areas. Thus, though an online survey of 185 rural and regional planners, this research explores their motivations, expectations and experiences. Most enjoyed and felt confident in their role, explaining that they valued the relaxed family orientated rural lifestyle and the varied nature of the planning work. Although they sometimes felt isolated, the non-urban location provided quicker progression to senior roles, the ability to engage directly with the community and to see the consequences of their decisions. Only half felt their education had prepared them well for their role, citing gaps in terms of computerised modelling, team leadership and conflict resolution skills. Their feedback centred on providing a more practical course, focussing more on regional planning, and encouraging urban and rural experience placements. As the first study to quantifiably explore rural and regional Australian planners perceptions of their role and challenges, the findings illustrate current experiences, key planning challenges, perceived educational gaps and future priorities.

Determinants of regional innovation capacity in China

Since the 1980s, when the concept of innovation systems(IS) was first presented(Freeman, 2004), a large body of work has been done on IS. IS is a framework that consists of elements related to innovation activities, such as innovation actors,institutional environments, and the relationship between those elements (Lundvall,1992; Nelson, 1993). Studies on NIS/RIS aim to understand the structures and dynamics of IS (Lundvall, 1992; Nelson, 1993), mainly through case studies and comparative case studies(Archibugi, 1996; MacDowall, 1984; Mowery, 1998;Radosevic, 2000). Research on IS has extended from the national level (NIS) to the regional level (RIS) (Cooke, Uranga, & Etxebarria, 1997; Cooke, Uranga, & Etxebarria, 1998), and from developed economies to developing economies. RIS is vital, especially for a large and diverse countries(Edquist, 2004) like China. More recently, based on the literature of NIS, Furman, Porter and Scott (2002)introduced the framework of national innovation capacity (NIC), which employs a quantitative approach to understanding to what degree elements of NIS impact on innovation capacity. Regional innovation capacity (RIC) is the adaption of NIC at the regional level. Although regional level research is important there is limited work done on RIC and there is even less in transitional economies, which are different to developed countries. To better understand RIC in transitional countries this thesis conducted a study of 30 administrative regions in Mainland China between 1991 and 2005. To establish the key factors driving RIC in China the study explored the impact of three elements in the innovation system;(a) innovation actors, (b) innovation inputs, and (c)international and domestic innovation system interactions.

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.

Knowledge that matters : identifying regional knowledge assets of tampere region

The extant literature considers knowledge as one of the key drivers of regional development. The idiosyncratic nature of regional knowledge is also acknowledged: each region possesses its unique knowledge assets which act as the basis of value creation. However, what is currently not well-known is how the region-specific knowledge assets can be identified, for example, for the purposes of managing and developing them. Thus, this paper aims, first, to explore how the relevant knowledge assets can be identified for a given region and, second, to describe what the context-specific knowledge assets are. These objectives are pursued using a qualitative case approach. As a case region, this study focuses on Tampere Region in Finland. This study makes a contribution by providing new insight regarding the contextual identification of regional knowledge assets and by illustrating the key knowledge assets of the case region. These insights are considered valuable for regional actors who are responsible for carrying out similar initiatives in their regions.

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.

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.