Ownerships for reasoning about parallelism : type system and semantics

Technical Report to accompany Ownership for Reasoning About Parallelism. Documents type system which captures effects and the operational semantics for the language which is presented as part of the paper.

Towards executable specification : combining i* and AgentSpeak(L).

Agent-oriented conceptual modelling (AoCM) approaches in Requirements Engineering (RE) have received considerable attention recently. Semi-formal modeling frameworks such as i* assist analysts in requirements elicitation and reasoning of early-phase RE. AgentSpeak(L) is a widely accepted agent programming language. The Strategic Rationale (SR) model of the i* framework naturally lends itself to AgentSpeak(L) programs. Furthermore, the Strategic Dependency (SD) component of the i* framework prescribes the interaction between the agents in a multi-agent environment. This paper proposes a formal methodology for transforming a SR model to an AgentS- peak(L) agent. The constructed AgentSpeak(L) agents will then form the essential components of a multi-agent system, MAS.

Automating human thought processes for a UAV forced landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

The logic of ADHD : a brief review of fallacious reasoning

This paper has two central purposes: the first is to survey some of the more important examples of fallacious argument, and the second is to examine the frequent use of these fallacies in support of the psychological construct: Attention Deficit Hyperactivity Disorder (ADHD). The paper divides 12 familiar fallacies into three different categories—material, psychological and logical—and contends that advocates of ADHD often seem to employ these fallacies to support their position. It is suggested that all researchers, whether into ADHD or otherwise, need to pay much closer attention to the construction of their arguments if they are not to make truth claims unsupported by satisfactory evidence, form or logic.

Alternative schooling programs for at risk youth : three case studies

This thesis develops a critical realist explanatory critique of alternative schooling programs for youth at risk taking place at three case study sites. Throughout the thesis the author pursues the question, \Are alternative provisions of schooling working academically and socially for youth at risk?. The academic lens targets literacy learning and associated pedagogies. Social outcomes are posited as positive social behaviours and continued engagement in learning. A four phased analysis, drawing on critical realism, interpretive and subject specific theories is used to elicit explanations for the research question. An overall framework is a critical realist methodology as set out by Danermark, Ekstrom, Jakobsen and Karlsson (2002, p. 129). Consequently phase one describes the phenomena of alternative schooling programs taking place at three case study sites. This is reported first as staff narratives that are resolved into imaginable historical causal components of \generative events., \prior schooling structures., \models of alternative schooling., \purpose., \individual agency., and \relations with linked community organisations.. Then transcendental questions are posed about each component using retroduction to uncover structures, underlying mechanisms and powers, and individual agency. In the second phase the researcher uses modified grounded theory methodology to theoretically redescribe causal categories related to a \needed different teaching and administrative approach. that emerged from the previous critique. A transcendental question is then applied to this redescription. The research phenomena are again theoretically redescribed in the third phase, this time using three theoretically based constructs associated with literacy and literacy pedagogies; the NRS, the 4 Resources Model, and Productive Pedagogies. This redescription is again questioned in terms of its core or \necessary. components. The fourth phase makes an explanatory critique by comparing and critiquing all previous explanations, recontextualising them in a wider macro reality of alternative schooling. Through this critical realist explanatory critiquing process, a response emerges not only to whether alternative provisions of schooling are working, but also how they are working, and how they are not working, with realistically based implications for future improvement.

An evaluation of brief correspondence programs for problem drinkers

The provision of accessible and cost-effective treatment to a large number of problem drinkers is a significant challenge to health services. Previous data suggest that a correspondence intervention may assist in these efforts. We recruited 277 people with alcohol abuse problems and randomly allocated them to immediate cognitive behavioral treatment by correspondence (ICBT), 2 months in a waiting list (WL2-CBT), self-monitoring (SM2-CBT), or extended self-monitoring (SM6-CBT). Everyone received correspondence CBT after the control period. Over 2 months later, no drop in alcohol intake occurred in the waiting list, and CBT had a greater impact than SM. No further gains from SM were seen after 2 months. Effects of CBT were well maintained and were equivalent, whether it was received immediately or after 2 to 6 months of self-monitoring. Weekly alcohol intake fell 48% from pretreatment to 18.6 alcohol units at 12 months. Our results confirmed that correspondence CBT for alcohol abuse was accessible and effective for people with low physical dependence.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

Investigating functional thinking in the elementary classroom : foundations of early algebraic reasoning

This paper examines the development of student functional thinking during a teaching experiment that was conducted in two classrooms with a total of 45 children whose average age was nine years and six months. The teaching comprised four lessons taught by a researcher, with a second researcher and classroom teacher acting as participant observers. These lessons were designed to enable students to build mental representations in order to explore the use of function tables by focusing on the relationship between input and output numbers with the intention of extracting the algebraic nature of the arithmetic involved. All lessons were videotaped. The results indicate that elementary students are not only capable of developing functional thinking but also of communicating their thinking both verbally and symbolically.

Realism and control : problem-based learning programs as a data source for work-related research

Problem-based learning (PBL) is a pedagogical methodology that presents the learner with a problem to be solved to stimulate and situate learning. This paper presents key characteristics of a problem-based learning environment that determines its suitability as a data source for workrelated research studies. To date, little has been written about the availability and validity of PBL environments as a data source and its suitability for work-related research. We describe problembased learning and use a research project case study to illustrate the challenges associated with industry work samples. We then describe the PBL course used in our research case study and use this example to illustrate the key attributes of problem-based learning environments and show how the chosen PBL environment met the work-related research requirements of the research case study. We propose that the more realistic the PBL work context and work group composition, the better the PBL environment as a data source for a work-related research. The work context is more realistic when relevant and complex project-based problems are tackled in industry-like work conditions over longer time frames. Work group composition is more realistic when participants with industry-level education and experience enact specialized roles in different disciplines within a professional community.

Public health and clinical dilemmas resulting from imprecise vitamin D tests

Objective: To determine whether there are clinical and public health dilemmas resulting from the reproducibility of routine vitamin D assays. Methods: Blinded agreement studies were conducted in eight clinical laboratories using two commonly used assays to measure serum 25-hydroxyvitamin D (25(OH)D) levels in Australasia and Canada (DiaSorin Radioimmunoassay (RIA) and DiaSorin LIAISON® one). Results: Only one laboratory measured 25(OH)D with excellent precision. Replicate 25(OH)D measurements varied by up to 97% and 15% of paired results differed by more than 50%. Thirteen percent of subjects received one result indicating insufficiency [25-50 nmol/l] and another suggesting adequacy [>50 nmol/l]). Agreement ranged from poor to excellent for laboratories using the manual RIA, while the precision of the semi-automated Liaison® system was consistently poor. Conclusions: Recent interest in the relevance of vitamin D to human health has increased demand for 25(OH)D testing and associated costs. Our results suggest clinicians and public health authorities are making decisions about treatment or changes to public health policy based on imprecise data. Clinicians, researchers and policy makers should be made aware of the imprecision of current 25(OH)D testing so that they exercise caution when using these assays for clinical practice, and when interpreting the findings of epidemiological studies based on vitamin D levels measured using these assays. Development of a rapid, reproducible, accurate and robust assay should be a priority due to interest in populationbased screening programs and research to inform public health policy about the amount of sun exposure required for human health. In the interim, 25(OH)D results should routinely include a statement of measurement uncertainty.

Manufacturing management programs : are developing economies bridging the strategic gap?

Over the past decade there have been a large number of significant innovations in manufacturing which have resulted in more flexible and cost efficient methods and higher quality products, as manufacturers have set about upgrading their processes, systems and performance. This study compares the use of technologies and improvement programs between OECD and Non-OECD countries, and also between small and large firms, and examines differences in the use and outcomes across the economies and different sized firms. The empirical analysis provides an opportunity to test whether the ‘capabilities’ or strengths of a firm can be linked to these activities and examines if developing economies are using technology or management programs such as quality management and business process re-engineering to catch up to manufacturers in developed economies. The analysis utilises data from the second International Manufacturing Strategy Survey (IMSS), which encompasses 703 firms in 23 countries.