Analytical model for fault section estimation and state identification of unobserved protective relays in power systems [电力系统故障诊断与不可观测保护状态识别的解析模型]

In recent years, some models have been proposed for the fault section estimation and state identification of unobserved protective relays (FSE-SIUPR) under the condition of incomplete state information of protective relays. In these models, the temporal alarm information from a faulted power system is not well explored although it is very helpful in compensating the incomplete state information of protective relays, quickly achieving definite fault diagnosis results and evaluating the operating status of protective relays and circuit breakers in complicated fault scenarios. In order to solve this problem, an integrated optimization mathematical model for the FSE-SIUPR, which takes full advantage of the temporal characteristics of alarm messages, is developed in the framework of the well-established temporal constraint network. With this model, the fault evolution procedure can be explained and some states of unobserved protective relays identified. The model is then solved by means of the Tabu search (TS) and finally verified by test results of fault scenarios in a practical power system.

Investigation into the noise map based on traffic flow prediction in the citywide road network

As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. This paper first presents a brief review of the most inherent uncertainties of the SHM-oriented WSN platforms and then investigates their effects on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when employing merged data from multiple tests. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and Data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Experimental accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as clean data before being contaminated by different data pollutants in sequential manner to simulate practical SHM-oriented WSN uncertainties. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with SHM-WSN uncertainties. Finally, the use of the measurement channel projection for the time-domain OMA techniques and the preferred combination of the OMA techniques to cope with the SHM-WSN uncertainties is recommended.

Investigating effective wayfinding in airports : a Bayesian network approach

Effective Wayfinding is the successful interplay of human and environmental factors resulting in a person successfully moving from their current position to a desired location in a timely manner. To date this process has not been modelled to reflect this interplay. This paper proposes a complex modelling system approach of wayfinding by using Bayesian Networks to model this process, and applies the model to airports. The model suggests that human factors have a greater impact on effective wayfinding in airports than environmental factors. The greatest influences on human factors are found to be the level of spatial anxiety experienced by travellers and their cognitive and spatial skills. The model also predicted that the navigation pathway that a traveller must traverse has a larger impact on the effectiveness of an airport’s environment in promoting effective wayfinding than the terminal design.

Compaction control of topography and fault network structure along strike-slip faults in sedimentary basins

Strike-slip faults commonly display structurally complex areas of positive or negative topography. Understanding the development of such areas has important implications for earthquake studies and hydrocarbon exploration. Previous workers identified the key factors controlling the occurrence of both topographic modes and the related structural styles. Kinematic and stress boundary conditions are of first-order relevance. Surface mass transport and material properties affect fault network structure. Experiments demonstrate that dilatancy can generate positive topography even under simple-shear boundary conditions. Here, we use physical models with sand to show that the degree of compaction of the deformed rocks alone can determine the type of topography and related surface fault network structure in simple-shear settings. In our experiments, volume changes of ∼5% are sufficient to generate localized uplift or subsidence. We discuss scalability of model volume changes and fault network structure and show that our model fault zones satisfy geometrical similarity with natural flower structures. Our results imply that compaction may be an important factor in the development of topography and fault network structure along strike-slip faults in sedimentary basins.

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.

Investigating epidermogenesis in a human skin equivalent model

Skin is the largest, and arguably, the most important organ of the body. It is a complex and multi-dimensional tissue, thus making it essentially impossible to fully model in vitro in conventional 2-dimensional culture systems. In view of this, rodents or pigs are utilised to study wound healing therapeutics or to investigate the biological effects of treatments on skin. However, there are many differences between the wound healing processes in rodents compared to humans (contraction vs. re-epithelialisation) and there are also ethical issues associated with animal testing for scientific research. Therefore, the development of skin equivalent (HSE) models from surgical discard human skin has become an important area of research. The studies in this thesis compare, for the first time, native human skin and the epidermogenesis process in a HSE model. The HSE was reported to be a comparable model for human skin in terms of expression and localisation of key epidermal cell markers. This validated HSE model was utilised to study the potential wound healing therapeutic, hyperbaric oxygen (HBO) therapy. There is a significant body of evidence suggesting that lack of cutaneous oxygen results in and potentiates the chronic, non-healing wound environment. Although the evidence is anecdotal, HBO therapy has displayed positive effects on re-oxygenation of chronic wounds and the clinical outcomes suggest that HBO treatment may be beneficial. Therefore, the HSE was subjected to a daily clinical HBO regime and assessed in terms of keratinocyte migration, proliferation, differentiation and epidermal thickening. HBO treatment was observed to increase epidermal thickness, in particular stratum corneum thickening, but it did not alter the expression or localisation of standard epidermal cell markers. In order to elucidate the mechanistic changes occurring in response to HBO treatment in the HSE model, gene microarrays were performed, followed by qRT-PCR of select genes which were differentially regulated in response to HBO treatment. The biological diversity of the HSEs created from individual skin donors, however, overrode the differences in gene expression between treatment groups. Network analysis of functional changes in the HSE model revealed general trends consistent with normal skin growth and maturation. As a more robust and longer term study of these molecular changes, protein localisation and expression was investigated in sections from the HSEs undergoing epidermogenesis in response to HBO treatment. These proteins were CDCP1, Metallothionein, Kallikrein (KLK) 1 and KLK7 and early growth response 1. While the protein expression within the HSE models exposed to HBO treatment were not consistent in all HSEs derived from all skin donors, this is the first study to detect and compare both KLK1 and CDCP1 protein expression in both a HSE model and native human skin. Furthermore, this is the first study to provide such an in depth analysis of the effect of HBO treatment on a HSE model. The data presented in this thesis, demonstrates high levels of variation between individuals and their response to HBO treatment, consistent with the clinical variation that is currently observed.

A neural-network based flight controller for UASs

This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.

Spatiotemporal model or time series model for assessing city-wide temperature effects on mortality?

Most studies examining the temperature–mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.

A Hybrid Queue-based Bayesian Network Framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Smart grid-demand side response model to mitigate prices and peak impact on the electrical system

The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load considering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

Building Healthy Communities : GP Network, Medicare Local and Primary Health Care in the Wheatbelt Region of Western Australia

• Government reports consistently recognise the importance of Primary Health Care to an efficient health system. Barriers identified in Australia’s Primary Health Care include workforce pressures, increase rate of chronic disease, and equitable access to Primary Health Care services. • General Practitioners (GPs) are the key to the successful delivery of Primary Health Care especially in rural and remote regions such as the Wheatbelt region in Western Australia (WA). • The Wheatbelt region of WA is vast: some 72,500 residents spread across 150,000km2 in 43 Local Government Authorities catchments. Majority of the Wheatbelt residents live in small towns. There is a higher reported rates of chronic disease, more at risk of chronic diseases and less utilisation of Primary Health Care services in this region. • General practice patients in the Wheatbelt are among those most in need of Primary Health Care services. • Wheatbelt GP Network (the “Network”) was established in 1998. It is a key health service delivery stakeholder in the Wheatbelt. • The Network has responded to the health needs of the community by creating a mobile Allied Health Team that works closely with GPs and is adaptive to ensure priority needs are met. • The Medicare Local model introduced by the Australian Government in 2011 aimed to improve the delivery of Primary Health Care services by improved health planning and coordinating service delivery. • Little if any recognition has been given to the outstanding work that many Divisions of General Practice have done in improving the delivery of Primary Health Care services such as the Network. • The Network has continued to support GPs and general practices and created a complementary system that integrated general practice with the work of an Allied Health Team. Its program mix is extensive. • The Network has consistently delivered on-required contract outputs and has a fifteen (15) years history of operating successfully in a large geographical area comprising in the main smaller communities that cannot support the traditional health services model. • The complexity of supporting International Medical Graduates in the region requires special attention. • The introduction of the Medicare Local in the South West of WA and their intention to take over the delivery of health services, thus effectively shutting the Network will have catastrophic consequences and cannot be supported economically. • The Network proposes to create a new model, built on its past work that increases the delivery of Primary Health Care services through its current Allied Health Team. • The proposal uses the Wheatbelt GP Super Clinic currently under construction in Northam, part of the Network and funded by the Australian Government is a key to the proposed new model. • Wheatbelt GP Super Clinic is different from existing models of GP Super Clinics around Australia which focus predominately on co-location of services. Wheatbelt GP Super Clinic utilises a hub and spoke model of service outreach to small rural towns to ensure equitable Primary Health Care coverage and continuum of care in a financially responsible and viable manner. In particular, the Wheatbelt GP Super Clinic recognises the importance of Allied Health Professionals and will involve them in a collaborative model with rural general practice. • The proposed model advocated by the Network aims to substitute the South West WA Medicare Local direct service delivery proposed for the Wheatbelt. The Network’s proposed model is to expand on the current hub and spoke model of Primary Health Care delivery to otherwise small unviable Wheatbelt towns. A flexible and adaptive skill mix of Allied Health Professionals, Nurse Practitioners and GPs ensure equitable access to service. Expanded scope of practices are utilised to reduce duplication of service and concentration of services in major towns. This involves a partnership approach. • If the proposed model not funded, the Network and the Wheatbelt region will stand to lose 16 Allied Health Professionals and defeats the purpose of Australian Government current funding for the construction of the Wheatbelt GP Super Clinic. • The Network has considered how its model can best be funded. It proposes a re-allocation of funds made available to the South West WA Medicare Local. • This submission argues that the proposal for the South West WA Medicare Local to take over the service delivery of Primary Health Care services in the Wheatbelt makes no economic sense when an existing agency (the Network) has the infrastructure in place, is experienced in working in this geographical area that has special needs and is capable to expand its programs to meet demand.

Enterprise social networks : a business model perspective

Enterprise Social Networks continue to be adopted by organisations looking to increase collaboration between employees, customers and industry partners. Offering a varied range of features and functionality, this technology can be distinguished by the underlying business models that providers of this software deploy. This study identifies and describes the different business models through an analysis of leading Enterprise Social Networks: Yammer, Chatter, SharePoint, Connections, Jive, Facebook and Twitter. A key contribution of this research is the identification of consumer and corporate models as extreme approaches. These findings align well with research on the adoption of Enterprise Social Networks that has discussed bottom-up and top-down approaches. Of specific interest are hybrid models that wrap a corporate model within a consumer model and may, therefore, provide synergies on both models. From a broader perspective, this can be seen as the merging of the corporate and consumer markets for IT products and services.