Supreme Court Decision Results in a Change to Standard Contracts

The decision of Dalton J in Lai v Soineva [2011] QSC 247 has resulted in a change in the latest versions of the Real Estate Institute of Queensland (REIQ) contracts.

The four principles: Can they be measured and do they predict ethical decision making?

Background The four principles of Beauchamp and Childress - autonomy, non-maleficence, beneficence and justice - have been extremely influential in the field of medical ethics, and are fundamental for understanding the current approach to ethical assessment in health care. This study tests whether these principles can be quantitatively measured on an individual level, and then subsequently if they are used in the decision making process when individuals are faced with ethical dilemmas. Methods The Analytic Hierarchy Process was used as a tool for the measurement of the principles. Four scenarios, which involved conflicts between the medical ethical principles, were presented to participants and they made judgments about the ethicality of the action in the scenario, and their intentions to act in the same manner if they were in the situation. Results Individual preferences for these medical ethical principles can be measured using the Analytic Hierarchy Process. This technique provides a useful tool in which to highlight individual medical ethical values. On average individuals have a significant preference for non-maleficence over the other principles, however, and perhaps counter-intuitively, this preference does not seem to relate to applied ethical judgements in specific ethical dilemmas. Conclusions People state they value these medical ethical principles but they do not actually seem to use them directly in the decision making process. The reasons for this are explained through the lack of a behavioural model to account for the relevant situational factors not captured by the principles. The limitations of the principles in predicting ethical decision making are discussed.

Improving trust and securing data accessibility for e-health decision making by using data encryption techniques

In the medical and healthcare arena, patients‟ data is not just their own personal history but also a valuable large dataset for finding solutions for diseases. While electronic medical records are becoming popular and are used in healthcare work places like hospitals, as well as insurance companies, and by major stakeholders such as physicians and their patients, the accessibility of such information should be dealt with in a way that preserves privacy and security. Thus, finding the best way to keep the data secure has become an important issue in the area of database security. Sensitive medical data should be encrypted in databases. There are many encryption/ decryption techniques and algorithms with regard to preserving privacy and security. Currently their performance is an important factor while the medical data is being managed in databases. Another important factor is that the stakeholders should decide more cost-effective ways to reduce the total cost of ownership. As an alternative, DAS (Data as Service) is a popular outsourcing model to satisfy the cost-effectiveness but it takes a consideration that the encryption/ decryption modules needs to be handled by trustworthy stakeholders. This research project is focusing on the query response times in a DAS model (AES-DAS) and analyses the comparison between the outsourcing model and the in-house model which incorporates Microsoft built-in encryption scheme in a SQL Server. This research project includes building a prototype of medical database schemas. There are 2 types of simulations to carry out the project. The first stage includes 6 databases in order to carry out simulations to measure the performance between plain-text, Microsoft built-in encryption and AES-DAS (Data as Service). Particularly, the AES-DAS incorporates implementations of symmetric key encryption such as AES (Advanced Encryption Standard) and a Bucket indexing processor using Bloom filter. The results are categorised such as character type, numeric type, range queries, range queries using Bucket Index and aggregate queries. The second stage takes the scalability test from 5K to 2560K records. The main result of these simulations is that particularly as an outsourcing model, AES-DAS using the Bucket index shows around 3.32 times faster than a normal AES-DAS under the 70 partitions and 10K record-sized databases. Retrieving Numeric typed data takes shorter time than Character typed data in AES-DAS. The aggregation query response time in AES-DAS is not as consistent as that in MS built-in encryption scheme. The scalability test shows that the DBMS reaches in a certain threshold; the query response time becomes rapidly slower. However, there is more to investigate in order to bring about other outcomes and to construct a secured EMR (Electronic Medical Record) more efficiently from these simulations.

Developing tools to support complex infrastructure decision-making

Purpose – The rapidly changing role of capital city airports has placed demands on surrounding infrastructure. The need for infrastructure management and coordination is increasing as airports and cities grow and share common infrastructure frameworks. The purpose of this paper is to document the changing context in Australia, where the privatisation of airports has stimulated considerable land development with resulting pressures on surrounding infrastructure provision. It aims to describe a tool that is being developed to support decision-making between various stakeholders in the airport region. The use of planning support systems improves both communication and data transfer between stakeholders and provides a foundation for complex decisions on infrastructure. Design/methodology/approach – The research uses a case study approach and focuses on Brisbane International Airport and Brisbane City Council. The research is primarily descriptive and provides an empirical assessment of the challenges of developing and implementing planning support systems as a tool for governance and decision-making. Findings – The research assesses the challenges in implementing a common data platform for stakeholders. Agency data platforms and models, traditional roles in infrastructure planning, and integrating similar data platforms all provide barriers to sharing a common language. The use of a decision support system has to be shared by all stakeholders with a common platform that can be versatile enough to support scenarios and changing conditions. The use of iPadss for scenario modelling provides stakeholders the opportunity to interact, compare scenarios and views, and react with the modellers to explore other options. Originality/value – The research confirms that planning support systems have to be accessible and interactive by their users. The Airport City concept is a new and evolving focus for airport development and will place continuing pressure on infrastructure servicing. A coordinated and efficient approach to infrastructure decision-making is critical, and an interactive planning support system that can model infrastructure scenarios provides a sound tool for governance.

Developing a framework for planning healthy communities : the Logan Beaudesert health decision support system

In the last few decades, the focus on building healthy communities has grown significantly (Ashton, 2009). There is growing evidence that new approaches to planning are required to address the challenges faced by contemporary communities. These approaches need to be based on timely access to local information and collaborative planning processes (Murray, 2006; Scotch & Parmanto, 2006; Ashton, 2009; Kazda et al., 2009). However, there is little research to inform the methods that can support this type of responsive, local, collaborative and consultative health planning (Northridge et al., 2003). Some research justifies the use of decision support systems (DSS) as a tool to support planning for healthy communities. DSS have been found to increase collaboration between stakeholders and communities, improve the accuracy and quality of the decision-making process, and improve the availability of data and information for health decision-makers (Nobre et al., 1997; Cromley & McLafferty, 2002; Waring et al., 2005). Geographic information systems (GIS) have been suggested as an innovative method by which to implement DSS because they promote new ways of thinking about evidence and facilitate a broader understanding of communities. Furthermore, literature has indicated that online environments can have a positive impact on decision-making by enabling access to information by a broader audience (Kingston et al., 2001). However, only limited research has examined the implementation and impact of online DSS in the health planning field. Previous studies have emphasised the lack of effective information management systems and an absence of frameworks to guide the way in which information is used to promote informed decisions in health planning. It has become imperative to develop innovative approaches, frameworks and methods to support health planning. Thus, to address these identified gaps in the knowledge, this study aims to develop a conceptual planning framework for creating healthy communities and examine the impact of DSS in the Logan Beaudesert area. Specifically, the study aims to identify the key elements and domains of information that are needed to develop healthy communities, to develop a conceptual planning framework for creating healthy communities, to collaboratively develop and implement an online GIS-based Health DSS (i.e., HDSS), and to examine the impact of the HDSS on local decision-making processes. The study is based on a real-world case study of a community-based initiative that was established to improve public health outcomes and promote new ways of addressing chronic disease. The study involved the development of an online GIS-based health decision support system (HDSS), which was applied in the Logan Beaudesert region of Queensland, Australia. A planning framework was developed to account for the way in which information could be organised to contribute to a healthy community. The decision support system was developed within a unique settings-based initiative Logan Beaudesert Health Coalition (LBHC) designed to plan and improve the health capacity of Logan Beaudesert area in Queensland, Australia. This setting provided a suitable platform to apply a participatory research design to the development and implementation of the HDSS. Therefore, the HDSS was a pilot study examined the impact of this collaborative process, and the subsequent implementation of the HDSS on the way decision-making was perceived across the LBHC. As for the method, based on a systematic literature review, a comprehensive planning framework for creating healthy communities has been developed. This was followed by using a mixed method design, data were collected through both qualitative and quantitative methods. Specifically, data were collected by adopting a participatory action research (PAR) approach (i.e., PAR intervention) that informed the development and conceptualisation of the HDSS. A pre- and post-design was then used to determine the impact of the HDSS on decision-making. The findings of this study revealed a meaningful framework for organising information to guide planning for healthy communities. This conceptual framework provided a comprehensive system within which to organise existing data. The PAR process was useful in engaging stakeholders and decision-making in the development and implementation of the online GIS-based DSS. Through three PAR cycles, this study resulted in heightened awareness of online GIS-based DSS and openness to its implementation. It resulted in the development of a tailored system (i.e., HDSS) that addressed the local information and planning needs of the LBHC. In addition, the implementation of the DSS resulted in improved decision- making and greater satisfaction with decisions within the LBHC. For example, the study illustrated the culture in which decisions were made before and after the PAR intervention and what improvements have been observed after the application of the HDSS. In general, the findings indicated that decision-making processes are not merely informed (consequent of using the HDSS tool), but they also enhance the overall sense of ‗collaboration‘ in the health planning practice. For example, it was found that PAR intervention had a positive impact on the way decisions were made. The study revealed important features of the HDSS development and implementation process that will contribute to future research. Thus, the overall findings suggest that the HDSS is an effective tool, which would play an important role in the future for significantly improving the health planning practice.

Intuitionistic fuzzy Choquet integral operator-based approach for black-start decision-making

Determining the optimal of black-start strategies is very important for speeding the restoration speed of a power system after a global blackout. Most existing black-start decision-making methods are based on the assumption that all indexes are independent of each other, and little attention has been paid to the group decision-making method which is more reliable. Given this background, the intuitionistic fuzzy set and further intuitionistic fuzzy Choquet integral operator are presented, and a black-start decision-making method based on this integral operator is presented. Compared to existing methods, the proposed algorithm cannot only deal with the relevance among the indexes, but also overcome some shortcomings of the existing methods. Finally, an example is used to demonstrate the proposed method. © 2012 The Institution of Engineering and Technology.

Extending persistent monitoring by combining ocean models and Markov decision processes

Ocean processes are complex and have high variability in both time and space. Thus, ocean scientists must collect data over long time periods to obtain a synoptic view of ocean processes and resolve their spatiotemporal variability. One way to perform these persistent observations is to utilise an autonomous vehicle that can remain on deployment for long time periods. However, such vehicles are generally underactuated and slow moving. A challenge for persistent monitoring with these vehicles is dealing with currents while executing a prescribed path or mission. Here we present a path planning method for persistent monitoring that exploits ocean currents to increase navigational accuracy and reduce energy consumption.

Decision support for the safe design and operation of unmanned aircraft systems

Unmanned Aircraft Systems (UAS) describe a diverse range of aircraft that are operated without a human pilot on-board. Unmanned aircraft range from small rotorcraft, which can fit in the palm of your hand, through to fixed wing aircraft comparable in size to that of a commercial passenger jet. The absence of a pilot on-board allows these aircraft to be developed with unique performance capabilities facilitating a wide range of applications in surveillance, environmental management, agriculture, defence, and search and rescue. However, regulations relating to the safe design and operation of UAS first need to be developed before the many potential benefits from these applications can be realised. According to the International Civil Aviation Organization (ICAO), a Risk Management Process (RMP) should support all civil aviation policy and rulemaking activities (ICAO 2009). The RMP is described in International standard, ISO 31000:2009 (ISO, 2009a). This standard is intentionally generic and high-level, providing limited guidance on how it can be effectively applied to complex socio-technical decision problems such as the development of regulations for UAS. Through the application of principles and tools drawn from systems philosophy and systems engineering, this thesis explores how the RMP can be effectively applied to support the development of safety regulations for UAS. A sound systems-theoretic foundation for the RMP is presented in this thesis. Using the case-study scenario of a UAS operation over an inhabited area and through the novel application of principles drawn from general systems modelling philosophy, a consolidated framework of the definitions of the concepts of: safe, risk and hazard is made. The framework is novel in that it facilitates the representation of broader subjective factors in an assessment of the safety of a system; describes the issues associated with the specification of a system-boundary; makes explicit the hierarchical nature of the relationship between the concepts and the subsequent constraints that exist between them; and can be evaluated using a range of analytic or deliberative modelling techniques. Following the general sequence of the RMP, the thesis explores the issues associated with the quantified specification of safety criteria for UAS. A novel risk analysis tool is presented. In contrast to existing risk tools, the analysis tool presented in this thesis quantifiably characterises both the societal and individual risk of UAS operations as a function of the flight path of the aircraft. A novel structuring of the risk evaluation and risk treatment decision processes is then proposed. The structuring is achieved through the application of the Decision Support Problem Technique; a modelling approach that has been previously used to effectively model complex engineering design processes and to support decision-making in relation to airspace design. The final contribution made by this thesis is in the development of an airworthiness regulatory framework for civil UAS. A novel "airworthiness certification matrix" is proposed as a basis for the definition of UAS "Part 21" regulations. The outcome airworthiness certification matrix provides a flexible, systematic and justifiable method for promulgating airworthiness regulations for UAS. In addition, an approach for deriving "Part 1309" regulations for UAS is presented. In contrast to existing approaches, the approach presented in this thesis facilitates a traceable and objective tailoring of system-level reliability requirements across the diverse range of UAS operations. The significance of the research contained in this thesis is clearly demonstrated by its practical real world outcomes. Industry regulatory development groups and the Civil Aviation Safety Authority have endorsed the proposed airworthiness certification matrix. The risk models have also been used to support research undertaken by the Australian Department of Defence. Ultimately, it is hoped that the outcomes from this research will play a significant part in the shaping of regulations for civil UAS, here in Australia and around the world.

A decision table method for randomness measurement

Data quality has become a major concern for organisations. The rapid growth in the size and technology of a databases and data warehouses has brought significant advantages in accessing, storing, and retrieving information. At the same time, great challenges arise with rapid data throughput and heterogeneous accesses in terms of maintaining high data quality. Yet, despite the importance of data quality, literature has usually condensed data quality into detecting and correcting poor data such as outliers, incomplete or inaccurate values. As a result, organisations are unable to efficiently and effectively assess data quality. Having an accurate and proper data quality assessment method will enable users to benchmark their systems and monitor their improvement. This paper introduces a granules mining for measuring the random degree of error data which will enable decision makers to conduct accurate quality assessment and allocate the most severe data, thereby providing an accurate estimation of human and financial resources for conducting quality improvement tasks.

The influence of service quality and trade show effectiveness on post-show purchase intention

Purpose The purpose of this paper is to develop and test an integrative services framework to investigate the role of perceived trade show effectiveness on overall trade show service outcome, conceptualised as the intention to purchase a related product after, rather than during, a show. Design/methodology/approach Drawing on the services marketing and trade show literature, the authors test a model of trade show effectiveness with data collected from 592 attendees at a major automotive trade show in a large metropolitan centre. Findings Results show that improving trade show visitors' perceived service quality positively affects visitor perceptions of trade show effectiveness. Furthermore, both trade show effectiveness and service quality directly influence future purchase intention. Research limitations/implications Employing a services theoretical framework to evaluate trade show visitor experiences provides an alternative to the traditional marketing communications approach. By viewing such visits as service encounters, managers must inevitably consider the effects of service quality and service outcomes in determining the likely success of their shows. The study primarily focuses on one large consumer show and therefore does not constitute a complete, nor necessarily representative, sample of the trade show industry. Originality/value The original contribution of the paper stems from the paucity of research conceptualising trade shows as services and the comparative lack of emphasis placed on visitors rather than exhibitors in the literature. The research not only has utility for trade show organisers but also provides necessary theory-based research in the trade show domain.

Modelling passenger flow at airport terminals : individual agent decision model for stochastic passenger behaviour

Airport system is complex. Passenger dynamics within it appear to be complicate as well. Passenger behaviours outside standard processes are regarded more significant in terms of public hazard and service rate issues. In this paper, we devised an individual agent decision model to simulate stochastic passenger behaviour in airport departure terminal. Bayesian networks are implemented into the decision making model to infer the probabilities that passengers choose to use any in-airport facilities. We aim to understand dynamics of the discretionary activities of passengers.

An ingenious decision support system for remote health monitoring of pregnant women

Maternal deaths have been a critical issue for women living in rural and remote areas. The need to travel long distances, the shortage of primary care providers such as physicians, specialists and nurses, and the closing of small hospitals have been problems identified in many rural areas. Some research work has been undertaken and a few techniques have been developed to remotely measure the physiological condition of pregnant women through sophisticated ultrasound equipment. There are numerous ways to reduce maternal deaths, and an important step is to select the right approaches to achieving this reduction. One such approach is the provision of decision support systems in rural and remote areas. Decision support systems (DSSs) have already shown a great potential in many health fields. This thesis proposes an ingenious decision support system (iDSS) based on the methodology of survey instruments and identification of significant variables to be used in iDSS using statistical analysis. A survey was undertaken with pregnant women and factorial experimental design was chosen to acquire sample size. Variables with good reliability in any one of the statistical techniques such as Chi-square, Cronbach’s á and Classification Tree were incorporated in the iDSS. The decision support system was developed with significant variables such as: Place of residence, Seeing the same doctor, Education, Tetanus injection, Baby weight, Previous baby born, Place of birth, Assisted delivery, Pregnancy parity, Doctor visits and Occupation. The ingenious decision support system was implemented with Visual Basic as front end and Microsoft SQL server management as backend. Outcomes of the ingenious decision support system include advice on Symptoms, Diet and Exercise to pregnant women. On conditional system was sent and validated by the gynaecologist. Another outcome of ingenious decision support system was to provide better pregnancy health awareness and reduce long distance travel, especially for women in rural areas. The proposed system has qualities such as usefulness, accuracy and accessibility.