A review of modern computational algorithms for Bayesian optimal design

Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte Carlo and approximate Bayes methods, facilitating more complex design problems to be solved. The Bayesian framework provides a unified approach for incorporating prior information and/or uncertainties regarding the statistical model with a utility function which describes the experimental aims. In this paper, we provide a general overview on the concepts involved in Bayesian experimental design, and focus on describing some of the more commonly used Bayesian utility functions and methods for their estimation, as well as a number of algorithms that are used to search over the design space to find the Bayesian optimal design. We also discuss other computational strategies for further research in Bayesian optimal design.

A case study in flood fatality : Beijing July 2012 flood

Background The aim of this study is to examine the flood fatality with a view to identifying risks which may inform public policy responses to future flood. On July 21st, 2012, Beijing suffered the heaviest rain since 1963. The average rainfall was 215 mm over a 24 hour period in the central city (301mm in Fangshan District). The rain resulted in a flood that caused severe health, social and financial impact. Results This flood caused 79 deaths. Of the 71 deaths for which a specific cause could be identified, 5 were rescue team members, 42 were killed by drowning (11 in the car), and the others by electricity shock, fallen house, falling items and lightning. The total financial cost was estimated to be US$ 1.7 billion. The causations of the deaths inform the risks associated with the flood. Discussion This flood had a catastrophic impact on Beijing, mainly due to the intensity of the rain (the rain was the heaviest in the modern Beijing history; possibly due to global warming and urban heat island effect), the vulnerability of the infrastructure (poor standards of drainage, disorganized water management systems and decreased permeability of the earth as a result of the city���s rapid development), and the capacity of the response system (mainly dependent on the awareness of the citizens, warning systems and the capacity of the emergency rescue). Implication Many risk management measures have been implemented as a result of this flood, including water level warning marks, flood safety education and warnings sent to mobile phones, a project to move about 74,500 farmers away from the flood-prone areas within 5 years. However, further measures targeted at the fundamental issues identified by this analysis are necessary, especially those targeting at health issues. These may include better planning, improved drainage systems and ecological development to increase permeability etc..

Detection of rain in acoustic recordings of the environment

Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

Statutory occupational health and safety workplace arrangements for the modern labour market

Over the past 20 years there has been a significant refashioning of the labour market within Australia and other industrialised countries. This paper examines the implications of the growth of more flexible work arrangements for mechanisms designed to facilitate worker involvement in occupational health and safety at the workplace���a pivotal feature of post-Robens OHS legislation in Australia. It is argued that the growth of subcontracting, casual and home-based work has undermined both coverage and the effectiveness of these provisions, especially in a context where union membership and influence has also been declining. Looking at international experience, the paper examines a number of ways of remedying these deficiencies.

eHealth and the modern society

The integration of Information and Communication Technologies (ICT) into healthcare processes ���eHealth��� is driving enormous change in healthcare delivery and productivity. The transformations empower patients and present opportunities for new synergies between healthcare professionals, clinical decision makers, policy makers and educators. Technologies that are directly driving changes include Tele-medicine, Electronic health records (EHR), Standards to ensure computer systems inter-operate, Decision support systems, Data mining and easy access to medical information. This workshop provides an introduction to key informatics initiatives in eHealth using real examples and suggests how applications can be applied to modern society.

How Modern Governments Made Prostitution a Social Problem: Creating a Responsible Prostitute Population

Table of Contents Acknowledgments Preface by Dr. Pat Carlen Introduction 1. Political Languages of Prostitution 2. Genealogical Analysis: Documenting The Disorder of Things 3. From Death Rituals to Health Practices 4. Policing Female Prostitutes 5. Private Remedies for Public Concerns 6. The Emergence of the Male Prostitute 7. From Procreation to Pleasure 8. HIV/AIDS and Prostitution Conclusion Bibliography Index

Entrepreneurship Programs and the Modern University

Entrepreneurship Programs and the Modern University is an excellent resource for those who intend to set up an entrepreneurship program or centre, and arguably even more so for those who wish to coordinate or expand such activities into an effective "entrepreneurship eco-system" across the university and its external stakeholders. Morris, Kuratko, and Cornwall's intention in writing this book is to "advocate a more strategic and integrative framework for building the curricular, co-curricular, research, community engagement, and infrastructure components of a program" (p. xii).

Pollen image classification using the classifynder system: Algorithm comparison and a case study on New Zealand honey

We describe an investigation into how Massey University���s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University���s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder���s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

A comparison of classification algorithms within the Classifynder pollen imaging system

We describe an investigation into how Massey University's Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University's pollen reference collection (2890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set. In addition to the Classifynder's native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples. �� 2013 AIP Publishing LLC.

Grateful fateful sunshine rain

Grateful Fateful Sunshine Rain is a permanent public artwork commissioned by Aria Property Group through a competitive process for the Austin apartment building in South Brisbane. Artist Statement: Residents of Brisbane have a complex relationship with weather. As the capital of the Sunshine State, weather is an integral part of the city���s cultural identity. Weather deeply affects the mood of the city ��� from the excitement of scantily clad partygoers on balmy December evenings and late February���s lethargy, to the deepening anxiety that emerges after 100 days of rain (or more commonly, 100 days without rain). With a brief nod to the city���s ��� now decommissioned ��� iconic MCL weather beacon, Grateful Fateful Sunshine Rain taps into this aspect of Brisbane���s psyche with poetic, illuminated visualisations of real-time weather forecasts issued by the Bureau of Meteorology. Each evening, the artwork downloads tomorrow���s forecast from the Bureau of Meteorology website. Data including, current local temperature, humidity, wind speed & direction, precipitation (rain, hail etc), are used to generate a lighting display that conveys how tomorrow will feel. The artwork���s background colour indicates the expected temperature ��� from cold blues through mild pastel pinks and blues to bright hot oranges and reds. White fluffy clouds roll across the artwork if cloud is predicted. The density of these clouds indicates the level of cover whilst movement indicates expected wind speed and direction. If rain is predicted, sparkles of white light will appear on top of whichever background colour is chosen for the next day���s temperature. Sparkles appear constantly before wet, drizzly days, and intermittently if scattered showers are predicted. Intermittent, but more intense sparkles appear before rain storms or thunderstorms. Research Contribution: The work has made contributions to the field in the way it rethinks approaches to the conceptualization, design and realization of illuminated urban media. This has led to new theorizations of urban media, which consider light and illumination can be used to convey meaningful data. The research has produced new methods for controlling illumination systems using tools and techniques typically employed in computation arts. It has also develop methods and processes for the design and production of illuminated urban media architectures that are connected to real time data sources, and do which not follow the assumed logics of screen based media and displays.

A framework for sustainable energy reduction in modern breweries

This thesis examines the existing frameworks for energy management in the brewing industry and details the design, development and implementation of a new framework at a modern brewery. The aim of the research was to develop an energy management framework to identify opportunities in a systematic manner using Systems Engineering concepts and principles. This work led to a Sustainable Energy Management Framework, SEMF. Using the SEMF approach, one of Australia's largest breweries has achieved number 1 ranking in the world for water use for the production of beer and has also improved KPI's and sustained the energy management improvements that have been implemented during the past 15 years. The framework can be adapted to other manufacturing industries in the Australian context and is considered to be a new concept and a potentially important tool for energy management.