Drawing out critical thinking : testing the methodological value of drawing collaboratively

Early childhood research has long established that drawing is a central, and important activity for young children. Less common are investigations into the drawing activity of adults involved in early childhood. A team of adult early childhood researchers, with differing exposures and familiarities with drawing, experimented with intergenerational collaborative drawing with colleagues, students, family members and others, to explore the effectiveness of drawing as a research process and as an arts-based methodology. This testing prompted critical thinking into how drawing might facilitate research that involves young children, to operate in more communicable ways, and how research-focused drawings might occur in reference to a research project.

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.

Optimal Irrigation and N-fertilizer Management for Sustainable Winter Wheat Production in Khorezm, Uzbekistan

The efficiency of the nitrogen (N) application rates 0, 120, 180 and 240 kg N ha−1 in combination with low or medium water levels in the cultivation of winter wheat (Triticum aestivum L.) cv. Kupava was studied for the 2005–2006 and 2006–2007 growing seasons in the Khorezm region of Uzbekistan. The results show an impact of the initial soil Nmin (NO3-N + NH4-N) levels measured at wheat seeding on the N fertilizer rates applied. When the Nmin content in the 0–50 cm soil layer was lower than 10 mg kg−1 during wheat seeding in 2005, the N rate of 180 kg ha−1 was found to be the most effective for achieving high grain yields of high quality. With a higher Nmin content of about 30 mg kg−1 as was the case in the 2006 season, 120 kg N ha−1 was determined as being the technical and economical optimum. The temporal course of N2O emissions of winter wheat cultivation for the two water-level studies shows that emissions were strongly influenced by irrigation and N-fertilization. Extremely high emissions were measured immediately after fertilizer application events that were combined with irrigation events. Given the high impact of N-fertilizer and irrigation-water management on N2O emissions, it can be concluded that present N-management practices should be modified to mitigate emissions of N2O and to achieve higher fertilizer use efficiency.

Testing the effects of the Japanese vehicle emission-control law on the international palladium futures market

This paper tested the effects of the 2005 vehicle emission-control law issued in Japan on the market linkages between the U.S. and Japanese palladium futures markets, To determine these effects, we applied a cointegration test both with and without break points in the time series and found that the market linkages between the two countries changed after the break in October 2005. Our results show that the 2005 long-term regulation of vehicle emissions enacted in Japan influenced the international palladium futures market.

Total factor productivity growth and convergence in the petroleum industry : empirical analysis testing for convexity

While economic theory acknowledges that some features of technology (e.g., indivisibilities, economies of scale and specialization) can fundamentally violate the traditional convexity assumption, almost all empirical studies accept the convexity property on faith. In this contribution, we apply two alternative flexible production technologies to measure total factor productivity growth and test the significance of the convexity axiom using a nonparametric test of closeness between unknown distributions. Based on unique field level data on the petroleum industry, the empirical results reveal significant differences, indicating that this production technology is most likely non-convex. Furthermore, we also show the impact of convexity on answers to traditional convergence questions in the productivity growth literature.

Testing the international linkage in the platinum-group metal futures markets

This study tests whether an international market exists in the platinum-group metal (PGM) futures markets. For this purpose, we tested the law of one price (LOP) and the causality between the U.S. and Japanese platinum and palladium futures markets. We also performed the test when structural breaks are considered. Long-run price relationships were found in both platinum and palladium markets but the LOP only sustained in the palladium market. The causality test revealed that it is the U.S. market that leads the price to transmit information between the U.S. and Japanese markets. Structural breaks had large impacts on the test results, suggesting that incorporating breaks is important when investigating the international price linkage in the PGM futures markets.

License scheme : an optimal waste management policy under asymmetric information

A system requiring a waste management license from an enforcement agency has been introduced in many countries. A license system is usually coupled with fines, a manifest, and a disposal tax. However, these policy devices have not been integrated into an optimal policy. In this paper we derive an optimal waste management policy by using those policy devices. Waste management policies are met with three difficult problems: asymmetric information, the heterogeneity of waste management firms, and non-compliance by waste management firms and waste disposers. The optimal policy in this paper overcomes all three problems.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

Malaria rapid diagnostic test performance : results of WHO product testing of malaria RDTs : round 5 (2013)

WHO estimates that half the world’s population is at risk of malaria. In 2012, there were an estimated 207 million cases (with an uncertainty range of 135 million to 287 million) and an estimated 627 000 deaths (with an uncertainty range of 473 000 to 789 000). Approximately 90% of all malaria deaths occur in sub-Saharan Africa, and 77% occur in children under 5 years. Malaria remains endemic in 104 countries, and, while parasite-based diagnosis is increasing, most suspected cases of malaria are still not properly confirmed, resulting in over-use of antimalarial drugs and poor disease monitoring (1)...

Gender and entrepreneurial performance : testing a holistic framework

The aim of this study was to test a holistic framework for assessing new venture performance outcomes that incorporates the impact of gender on internal resource availability (human, financial and social capital) and how, in turn, this impacts: the entrepreneurs’ goals; the investment (both money and time) they make in their new ventures; and the performance outcomes of those ventures. Our results indicate that a majority of the paths examined (using structural equation modeling) are significant and in the expected direction. For example: an entrepreneur’s human capital (comprising management work experience, start-up experience and industry experience) is significantly related to her/his growth goal (in terms of employee numbers); the entrepreneur’s growth goal is positively related to the time invested in the new venture; and the time invested in the new venture is positively related to new venture outcomes.

Development of a dragline in-bucket bulk density monitor

This paper details the implementation and trialling of a prototype in-bucket bulk density monitor on a production dragline. Bulk density information can provide feedback to mine planning and scheduling to improve blasting and consequently facilitating optimal bucket sizing. The bulk density measurement builds upon outcomes presented in the AMTC2009 paper titled ‘Automatic In-Bucket Volume Estimation for Dragline Operations’ and utilises payload information from a commercial dragline monitor. While the previous paper explains the algorithms and theoretical basis for the system design and scaled model testing this paper will focus on the full scale implementation and the challenges involved.

Making optimal and justifiable asset maintenance decisions

Maintenance decisions for large-scale asset systems are often beyond an asset manager's capacity to handle. The presence of a number of possibly conflicting decision criteria, the large number of possible maintenance policies, and the reality of budget constraints often produce complex problems, where the underlying trade-offs are not apparent to the asset manager. This paper presents the decision support tool "JOB" (Justification and Optimisation of Budgets), which has been designed to help asset managers of large systems assess, select, interpret and optimise the effects of their maintenance policies in the presence of limited budgets. This decision support capability is realized through an efficient, scalable backtracking- based algorithm for the optimisation of maintenance policies, while enabling the user to view a number of solutions near this optimum and explore tradeoffs with other decision criteria. To assist the asset manager in selecting between various policies, JOB also provides the capability of Multiple Criteria Decision Making. In this paper, the JOB tool is presented and its applicability for the maintenance of a complex power plant system.