A statistical model for combustion resonance from a DI diesel engine with applications

Introduced in this paper is a Bayesian model for isolating the resonant frequency from combustion chamber resonance. The model shown in this paper focused on characterising the initial rise in the resonant frequency to investigate the rise of in-cylinder bulk temperature associated with combustion. By resolving the model parameters, it is possible to determine: the start of pre-mixed combustion, the start of diffusion combustion, the initial resonant frequency, the resonant frequency as a function of crank angle, the in-cylinder bulk temperature as a function of crank angle and the trapped mass as a function of crank angle. The Bayesian method allows for individual cycles to be examined without cycle-averaging|allowing inter-cycle variability studies. Results are shown for a turbo-charged, common-rail compression ignition engine run at 2000 rpm and full load.

Numeracy and statistical reasoning on entering university

The relationship between mathematics and statistical reasoning frequently receives comment (Vere-Jones 1995, Moore 1997); however most of the research into the area tends to focus on mathematics anxiety. Gnaldi (2003) showed that in a statistics course for psychologists, the statistical understanding of students at the end of the course depended on students’ basic numeracy, rather than the number or level of previous mathematics courses the student had undertaken. As part of a study into the development of statistical thinking at the interface between secondary and tertiary education, students enrolled in an introductory data analysis subject were assessed regarding their statistical reasoning, basic numeracy skills, mathematics background and attitudes towards statistics. This work reports on some key relationships between these factors and in particular the importance of numeracy to statistical reasoning.

Numeracy counts in the statistical reasoning equation

The relationship between mathematics and statistical reasoning frequently receives comment (Vere-Jones 1995, Moore 1997); however most of the research into the area tends to focus on maths anxiety. Gnaldi (Gnaldi 2003) showed that in a statistics course for psychologists, the statistical understanding of students at the end of the course depended on students’ basic numeracy, rather than the number or level of previous mathematics courses the student had undertaken. As part of a study into the development of statistical thinking at the interface between secondary and tertiary education, students enrolled in an introductory data analysis subject were assessed regarding their statistical reasoning ability, basic numeracy skills and attitudes towards statistics. This work reports on the relationships between these factors and in particular the importance of numeracy to statistical reasoning.

Investigation of the effects of the fatty acid profile on fuel properties using a Multi-Criteria Decision Analysis

The structural features of fatty acids in biodiesel, including degree of unsaturation, percentage of saturated fatty acids and average chain length, influence important fuel properties such as cetane number, iodine value, density, kinematic viscosity, higher heating value and oxidation stability. The composition of fatty acid esters within the fuel should therefore be in the correct ratio to ensure fuel properties are within international biodiesel standards such as ASTM 6751 or EN 14214. This study scrutinises the influence of fatty acid composition and individual fatty acids on fuel properties. Fuel properties were estimated based on published equations, and measured according to standard procedure ASTM D6751 and EN 14214 to confirm the influences of the fatty acid profile. Based on fatty acid profile-derived calculations, the cetane number of the microalgal biodiesel was estimated to be 11.6, but measured 46.5, which emphasises the uncertainty of the method used for cetane number calculation. Multi-criteria decision analysis (MCDA), PROMETHEE-GAIA, was used to determine the influence of individual fatty acids on fuel properties in the GAIA plane. Polyunsaturated fatty acids increased the iodine value and had a negative influence on cetane number. Kinematic viscosity was negatively influenced by some long chain polyunsaturated fatty acids such as C20:5 and C22:6 and some of the more common saturated fatty acids C14:0 and C18:0. The positive impact of average chain length on higher heating value was also confirmed in the GAIA plane

Decision support system for infrastructure sustainability in operations

There is an increasing awareness of sustainability and climate change and its impact on infrastructure and engineering asset management in design, construction, and operations. Sustainability rating tools have been proposed and/or developed that provide ratings of infrastructure projects in differing phases of their life cycle on sustainability. This paper provides an overview of decision support systems using sustainability rating framework that can be used to prioritize or select tasks and activities within projects to enhance levels of sustainability outcomes. These systems can also be used to prioritize projects within an organization to optimize sustainability outcomes within an allocated budget.

Clinical data warehousing for evidence based decision making

Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

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

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

Prior and posterior linear pooling for combining expert opinions: Uses and impact on Bayesian Networks

The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.

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

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

School based experiences as contributors to career decision-making: Findings from a cross-sectional survey of high-school students

This paper is based on a study examining the impact of young people’s backgrounds and educational experiences on career choice capability with the aim of informing education policy. A total of 706 students from secondary schools (Years 9-12) in New South Wales, Australia took part in an online survey. This paper focuses on the differences found between groups on the basis of their educational experiences. Participants who were uncertain of their future career plans were more likely to attend non-selective, non-metropolitan schools and were more likely to hold negative attitudes towards school. Career ‘uncertain’ students were also less likely to be satisfied with the elective subjects offered at their school and reported less access to career education sessions. It is concluded that timely career information and guidance should be provided to students and their families in order to allow them to more meaningfully make use of the resources and opportunities available to them with a view toward converting these into real world benefits.

Sartrean existentialism and ethical decision-making in business

A wide range of decision-making models have been offered to assist in making ethical decisions in the workplace. Those that are based on normative moral frameworks typically include elements of traditional moral philosophy such as consequentialist and/or deontological␣ethics. This paper suggests an alternative model drawing on Jean-Paul Sartre’s existentialism. Accordingly, the model focuses on making decisions in full awareness of one’s freedom and responsibility. The steps of the model are intended to encourage reflection of one’s projects and one’s situation and the possibility of refusing the expectations of others. A case study involving affirmative action in South Africa is used to demonstrate the workings of the model and a number of strengths and weaknesses are identified. Despite several weaknesses that can be raised regarding existential ethics, the model’s success lies in the way that it reframes ethical dilemmas in terms of individual freedom and responsibility, and in its acceptance and analysis of subjective experiences and personal situations

Competitive Smart Cities through Healthy Decision-making

This chapter examines the challenges and opportunities associated with planning for competitive, smart and healthy cities. The chapter is based on the assumptions that a healthy city is an important prerequisite for a competitive city and a fundamental outcome of smart cities. Thus, it is preeminent to understand the planning decision support system based on local determinants of health, economic and social factors. One of the major decision support systems is e-health and this chapter will focus on the role of e-health planning, by utilising web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access online information for a better decision-making while empowering community participation. The chapter also highlights the need for a comprehensive conceptual framework to guide the decision process of planning for healthy cities in association with opportunities and limitations. In summary, this chapter provides the critical insights of using information science-based framework and suggest online decision support methods, as part of a broader e-health approach for creating a healthy, competitive and smart city.

The influence of financial risk tolerance and risk perception on individual investment decision-making in a financial advice context

The aim of this thesis is to examine how risk tolerance and risk perception, two important but often misunderstood constructs, jointly influence client investment decisions in a financial advice context. By distinguishing the roles of these two risk constructs in client decision-making, in this thesis a new direction in studying financial/investment risks is provided while practice and regulation in the financial services industry is potentially informed. Based on the literature relating to risks and individual decision-making, a theoretical framework is developed and relevant hypotheses are tested in two studies with financial adviser clients in Australia. Results reveal that financial risk tolerance influences asset allocation both directly and indirectly through risk perception. The intervening role of risk perception suggests that risk tolerance affects how clients perceive the riskiness of an investment product which influences client decision-making.

Medical education and law: Withholding/withdrawing treatment from adults without capacity

BACKGROUND Law is increasingly involved in clinical practice, particularly at the end of life, but undergraduate and postgraduate education in this area remains unsystematic. We hypothesised that attitudes to and knowledge of the law governing withholding/withdrawing treatment from adults without capacity (the WWLST law) would vary and demonstrate deficiencies among medical specialists. AIMS We investigated perspectives, knowledge and training of medical specialists in the three largest (populations and medical workforces) Australian states, concerning the WWLST law. METHODS Following expert legal review, specialist focus groups, pre-testing and piloting in each state, seven specialties involved with end-of-life care were surveyed, with a variety of statistical analyses applied to the responses. RESULTS Respondents supported the need to know and follow the law. There were mixed views about its helpfulness in medical decision-making. Over half the respondents conceded poor knowledge of the law; this was mirrored by critical gaps in knowledge that varied by specialty. There were relatively low but increasing rates of education from the undergraduate to continuing professional development (CPD) stages. Mean knowledge score did not vary significantly according to undergraduate or immediate postgraduate training, but CPD training, particularly if recent, resulted in greater knowledge. Case-based workshops were the preferred CPD instruction method. CONCLUSIONS Teaching of current and evolving law should be strengthened across all stages of medical education. This should improve understanding of the role of law, ameliorate ambivalence towards the law, and contribute to more informed deliberation about end-of-life issues with patients and families.

Case Studies in Bayesian Statistical Modelling and Analysis

Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: •Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. •Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. •Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.