Model as you do : engaging an S-BPM vendor on process modelling in 3D virtual worlds

Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Metasonic GmbH has developed a process elicitation tool for their process suite. As part of a research engagement with Metasonic, staff from QUT, Australia have developed a 3D virtual world approach to the same problem, viz. eliciting process models from stakeholders in an intuitive manner. This book chapter tells the story of how QUT staff developed a 3D Virtual World tool for process elicitation, took the outcomes of their research project to Metasonic for evaluation, and finally, Metasonic’s response to the initial proof of concept.

An innovative online intervention: The Steering Clear First Offender Drink Driving Program

Drink driving remains a substantial public health issue warranting investigation. First offender drink drivers are seen to be less risky than repeat offenders, though the majority of first offenders report drink driving prior to detection, and many continue to drink drive following conviction. Few first offenders are offered treatment programs, and as such there is a need to address drink driving behaviour at this stage. A comprehensive approach including first offender treatment is needed to address the problem. Online interventions have demonstrated effectiveness in reducing risky behaviours such as harmful substance use. Such interventions allow for personalised tailored content to be delivered to individuals targeting specific mechanisms of behavioural change. This method also allows for targeting screening to ensure relevance of content on an individual level. However, there have been no research based online programs to date aimed at reducing repeat drink driving by first offenders. The Steering Clear First Offender Drink Driving Program is a self-guided, research based online program aimed at reducing recidivism by first time drink driving offenders. It includes a specialised web app to track drinks and build plans to prevent future drink driving. This allows for elongation of learning and encouragement of sustained behavioural change using self-monitoring after initial program completion. An outline of the program is discussed and the qualitative experience of the program on a sample of first offenders recruited at the time of court appearance is described.

A critical evaluation of literature on robot path planning in dynamic environment

Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

Needs for applied climate education in agriculture

This paper reports on a purposive survey study which aimed to identify needs for the development, delivery and evaluation of applied climate education for targeted groups, to improve knowledge and skills to better manage under variable climatic conditions. The survey sample consisted of 80 producers and other industry stakeholders in Australia (including representatives from consulting, agricultural extension and agricultural education sectors), with a 58% response rate to the survey. The survey included an assessment of (i) knowledge levels of the Southern Oscillation Index and sea surface temperatures, and (ii) skill and ability in interpreting weather and climate parameters. Results showed that despite many of the respondents having more than 20 years experience in their industry, the only formal climate education or training undertaken by most was a 1-day workshop. Over 80% of the applied climate skills listed in the survey were regarded by respondents as essential or important, but only 42% of educators, 30% of consultants and 28% of producers rated themselves as competent in applying such skills. Essential skills were deemed as those that would enable respondents or their clients to be better prepared for the next extended wet or dry meteorological event, and improved capability in identifying and capitalising on key decision points from climate information and a seasonal climate outlook. The complex issue of forecast accuracy is a confounding obstacle for many in the application of climate information and forecasts in management. Addressing this problem by describing forecast 'limitations and skill' can help to overcome this problem. The survey also highlighted specific climatic tactical and strategic information collated from grazing, cropping and agribusiness enterprises, and showed the value of such information from a users perspective.

A Hierarchical System of Learning Automata

A learning automaton operating in a random environment updates its action probabilities on the basis of the reactions of the environment, so that asymptotically it chooses the optimal action. When the number of actions is large the automaton becomes slow because there are too many updatings to be made at each instant. A hierarchical system of such automata with assured c-optimality is suggested to overcome that problem.The learning algorithm for the hierarchical system turns out to be a simple modification of the absolutely expedient algorithm known in the literature. The parameters of the algorithm at each level in the hierarchy depend only on the parameters and the action probabilities of the previous level. It follows that to minimize the number of updatings per cycle each automaton in the hierarchy need have only two or three actions.

Ethical values and the global carbon integrity system

There are many excellent books on climate justice and ethics, and their theorizing is a crucial and natural step in moving towards a justified response to this urgent problem. However, the purpose of this book lies elsewhere; it explores how ethical values can and should work in driving and structuring the global carbon integrity system.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

The multidimensional causal factors of ‘wet litter’ in chicken-meat production

The problem of ‘wet litter’, which occurs primarily in grow-out sheds for meat chickens (broilers), has been recognised for nearly a century. Nevertheless, it is an increasingly important problem in contemporary chicken-meat production as wet litter and associated conditions, especially footpad dermatitis, have developed into tangible welfare issues. This is only compounded by the market demand for chicken paws and compromised bird performance. This review considers the multidimensional causal factors of wet litter. While many causal factors can be listed it is evident that the critical ones could be described as micro-environmental factors and chief amongst them is proper management of drinking systems and adequate shed ventilation. Thus, this review focuses on these environmental factors and pays less attention to issues stemming from health and nutrition. Clearly, there are times when related avian health issues of coccidiosis and necrotic enteritis cannot be overlooked and the development of efficacious vaccines for the latter disease would be advantageous. Presently, the inclusion of phytate-degrading enzymes in meat chicken diets is routine and, therefore, the implication that exogenous phytases may contribute to wet litter is given consideration. Opinion is somewhat divided as how best to counter the problem of wet litter as some see education and extension as being more beneficial than furthering research efforts. However, it may prove instructive to assess the practice of whole grain feeding in relation to litter quality and the incidence of footpad dermatitis. Additional research could investigate the relationships between dietary concentrations of key minerals and the application of exogenous enzymes with litter quality.

Energy use in Indian household sector - An actor-oriented approach

Over the years, significant changes have taken place with regard to the type as well the quantity of energy used in Indian households. Many factors have contributed in bringing these changes. These include availability of energy, security of supplies, efficiency of use, cost of device, price of energy carriers, ease of use, and external factors like technological development, introduction of subsidies, and environmental considerations. The present paper presents the pattern of energy consumption in the household sector and analyses the causalities underlying the present usage patterns. It identifies specific (groups of) actors, study their specific situations, analyse the constraints and discusses opportunities for improvement. This can be referred to ``actor-oriented'' analysis in which we understand how various actors of the energy system are making the system work, and what incentives and constraints each of these actors is experiencing. It analyses actor linkages and their impact on the fuel choice mechanism. The study shows that the role of actors in household fuel choice is significant and depends on the level of factors - micro, meso and macro. It is recommended that the development interventions should include actor-oriented tools in energy planning, implementation, monitoring and evaluation. The analysis is based on the data from the national sample survey (NSS), India. This approach provides a spatial viewpoint which permits a clear assessment of the energy carrier choice by the households and the influence of various actors. The scope of the paper is motivated and limited by suggesting and formulating a powerful analytical technique to analyse the problem involving the role of actors in the Indian household sector.

Design of multiunit electronic exchanges through decomposition

In this paper, we exploit the idea of decomposition to match buyers and sellers in an electronic exchange for trading large volumes of homogeneous goods, where the buyers and sellers specify marginal-decreasing piecewise constant price curves to capture volume discounts. Such exchanges are relevant for automated trading in many e-business applications. The problem of determining winners and Vickrey prices in such exchanges is known to have a worst-case complexity equal to that of as many as (1 + m + n) NP-hard problems, where m is the number of buyers and n is the number of sellers. Our method proposes the overall exchange problem to be solved as two separate and simpler problems: 1) forward auction and 2) reverse auction, which turns out to be generalized knapsack problems. In the proposed approach, we first determine the quantity of units to be traded between the sellers and the buyers using fast heuristics developed by us. Next, we solve a forward auction and a reverse auction using fully polynomial time approximation schemes available in the literature. The proposed approach has worst-case polynomial time complexity. and our experimentation shows that the approach produces good quality solutions to the problem. Note to Practitioners- In recent times, electronic marketplaces have provided an efficient way for businesses and consumers to trade goods and services. The use of innovative mechanisms and algorithms has made it possible to improve the efficiency of electronic marketplaces by enabling optimization of revenues for the marketplace and of utilities for the buyers and sellers. In this paper, we look at single-item, multiunit electronic exchanges. These are electronic marketplaces where buyers submit bids and sellers ask for multiple units of a single item. We allow buyers and sellers to specify volume discounts using suitable functions. Such exchanges are relevant for high-volume business-to-business trading of standard products, such as silicon wafers, very large-scale integrated chips, desktops, telecommunications equipment, commoditized goods, etc. The problem of determining winners and prices in such exchanges is known to involve solving many NP-hard problems. Our paper exploits the familiar idea of decomposition, uses certain algorithms from the literature, and develops two fast heuristics to solve the problem in a near optimal way in worst-case polynomial time.

Non-linear couette flow with heat transfer using the B-G-K model

In recent years a large number of investigators have devoted their efforts to the study of flow and heat transfer in rarefied gases, using the BGK [1] model or the Boltzmann kinetic equation. The velocity moment method which is based on an expansion of the distribution function as a series of orthogonal polynomials in velocity space, has been applied to the linearized problem of shear flow and heat transfer by Mott-Smith [2] and Wang Chang and Uhlenbeck [3]. Gross, Jackson and Ziering [4] have improved greatly upon this technique by expressing the distribution function in terms of half-range functions and it is this feature which leads to the rapid convergence of the method. The full-range moments method [4] has been modified by Bhatnagar [5] and then applied to plane Couette flow using the B-G-K model. Bhatnagar and Srivastava [6] have also studied the heat transfer in plane Couette flow using the linearized B-G-K equation. On the other hand, the half-range moments method has been applied by Gross and Ziering [7] to heat transfer between parallel plates using Boltzmann equation for hard sphere molecules and by Ziering [83 to shear and heat flow using Maxwell molecular model. Along different lines, a moment method has been applied by Lees and Liu [9] to heat transfer in Couette flow using Maxwell's transfer equation rather than the Boltzmann equation for distribution function. An iteration method has been developed by Willis [10] to apply it to non-linear heat transfer problems using the B-G-K model, with the zeroth iteration being taken as the solution of the collisionless kinetic equation. Krook [11] has also used the moment method to formulate the equivalent continuum equations and has pointed out that if the effects of molecular collisions are described by the B-G-K model, exact numerical solutions of many rarefied gas-dynamic problems can be obtained. Recently, these numerical solutions have been obtained by Anderson [12] for the non-linear heat transfer in Couette flow,

Technology-related peso problems in stock returns

Although empirical evidence suggests the contrary, many asset pricing models assume stock returns to be symmetrically distributed. In this paper it is argued that the occurrence of negative jumps in a firm's future earnings and, consequently, in its stock price, is positively related to the level of network externalities in the firm's product market. If the ex post frequency of these negative jumps in a sample does not equal the ex ante assessed probability of occurrence, the sample is subject to a peso problem. The hypothesis is tested for by regressing the skewness coefficient of a firm’s realised stock return distribution on the firm’s R&D intensity, i.e. the ratio of the firm’s research and development expenditure to its net sales. The empirical results support the technology-related peso problem hypothesis. In samples subject to such a peso problem, the returns are biased up and the variance is biased down.

Task assignment in a multiprocessor system

One of the key problems in the design of any incompletely connected multiprocessor system is to appropriately assign the set of tasks in a program to the Processing Elements (PEs) in the system. The task assignment problem has proven difficult both in theory and in practice. This paper presents a simple and efficient heuristic algorithm for assigning program tasks with precedence and communication constraints to the PEs in a Message-based Multiple-bus Multiprocessor System, M3, so that the total execution time for the program is minimized. The algorithm uses a cost function: “Minimum Distance and Parallel Transfer” to minimize the completion time. The effectiveness of the algorithm has been demonstrated by comparing the results with (i) the lower bound on the execution time of a program (task) graph and (ii) a random assignment.

Singing from the same hymn sheet? A closer look at the framing of human trafficing by counter-trafficing actors in Lao PDR

As disparities in wealth levels between and within countries become greater many poor people migrate in search of better earning opportunities. Some of this migration is legal but, in many cases, the difficulties involved in securing the necessary documentation mean that would-be migrants resort to illegal methods. This, in turn, makes them vulnerable to human trafficking, a phenomenon that has received growing attention from NGOs, governments and the media in recent years. Despite the attention being given to human trafficking, however, there remains a certain amount of confusion over what exactly it entails though it is generally understood to refer to the transportation and subsequent exploitation of vulnerable people through means of force or deception. The increased attention that has been given to the issue of human trafficking over the last decade has resulted in new discourses emerging which attempt to explain what human trafficking entails, what the root causes of the phenomenon are and how best to tackle the problem. While a certain degree of conceptual clarity has been attained since human trafficking rose to prominence in the 1990s, it could be argued that human trafficking remains a poorly defined concept and that there is frequently confusion concerning the difference between it and related concepts such as people smuggling, migration and prostitution. The thesis examines the ways in which human trafficking has been conceptualised or framed in a specific national context- that of Lao PDR. Attention is given to the task of locating the major frames within which the issue has been situated, as well as considering the diagnoses and prognoses that the various approaches to trafficking suggest. The research considers which particular strands of trafficking discourse have become dominant in Lao PDR and the effect this has had on the kinds of trafficking interventions that have been undertaken in the country. The research is mainly qualitative and consists of an analysis of key texts found in the Lao trafficking discourse.

Redistribution Mechanisms for Assignment of Heterogeneous Objects

There are p heterogeneous objects to be assigned to n competing agents (n > p) each with unit demand. It is required to design a Groves mechanism for this assignment problem satisfying weak budget balance, individual rationality, and minimizing the budget imbalance. This calls for designing an appropriate rebate function. When the objects are identical, this problem has been solved which we refer as WCO mechanism. We measure the performance of such mechanisms by the redistribution index. We first prove an impossibility theorem which rules out linear rebate functions with non-zero redistribution index in heterogeneous object assignment. Motivated by this theorem,we explore two approaches to get around this impossibility. In the first approach, we show that linear rebate functions with non-zero redistribution index are possible when the valuations for the objects have a certain type of relationship and we design a mechanism with linear rebate function that is worst case optimal. In the second approach, we show that rebate functions with non-zero efficiency are possible if linearity is relaxed. We extend the rebate functions of the WCO mechanism to heterogeneous objects assignment and conjecture them to be worst case optimal.