The 2006 CSRC guidelines for articles of Association of Chinese listed companies : critiquing from an Australian perspective

Compares the Chinese Securities and Regulatory Commission's guidelines for articles of association of listed companies issued in 2006 with 'replaceable' rules in the Australian Corporations Act 2001. Discusses the provisions of the Chinese guidelines and the Australian rules on corporate constitution, interpretation, a company's representative, object clauses, shareholders' powers and meetings and directors. Questions whether the Chinese guidelines facilitate effective corporate governance.

On the cognitive effectiveness of routing symbols in process modeling languages

Process models provide visual support for analyzing and improving complex organizational processes. In this paper, we discuss differences of process modeling languages using cognitive effectiveness considerations, to make statements about the ease of use and quality of user experience. Aspects of cognitive effectiveness are of importance for learning a modeling language, creating models, and understanding models. We identify the criteria representational clarity, perceptual discriminability, perceptual immediacy, visual expressiveness, and graphic parsimony to compare and assess the cognitive effectiveness of different modeling languages. We apply these criteria in an analysis of the routing elements of UML Activity Diagrams, YAWL, BPMN, and EPCs, to uncover their relative strengths and weaknesses from a quality of user experience perspective. We draw conclusions that are relevant to the usability of these languages in business process modeling projects.

An Integrative framework of the factors affecting process model understanding : a learning perspective

Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies.

Homophobia, heteronormativism and hegemonic masculinity : male same-sex intimate violence from the perspective of Brisbane service providers

Few studies have explored the problem of male same-sex intimate partner violence, especially in the context of Australia. Utilizing in-depth interviews with gay-friendly service providers in Brisbane, the research presented in this article sought to ascertain whether (a) intimate partner violence occurs in male same-sex intimate relationships, (b)if so, what form this violence takes,(c) what contextual triggers underpin this violence,(d) what barriers victims face in exiting abusive relationships and seeking support, and (e) what services are available and appropriate to the needs of men in violent intimate relationships with other men. Results suggest that the prevalence, types and contextual triggers of violence in male same-sex relationships parallel abuse in opposite-sex relationships. Heteronormativism, homophobia, and its close association with hegemonic masculinity, however, emerge as features unique to the male same-sex intimate partner violence experience.

Health, endogenous time preference, and inequality : a political economy perspective

We study an overlapping-generations model in which agents' mortality risks, and consequently impatience, are endogenously determined by private and public investment in health care. Revenues allocated for public health care arc determined by a voting process. We find that the degree of substitutability between public and private health expenditures matters for macroeconomic outcomes of the model. Higher substitutability implies a “crowding-out" effect, which in turn impacts adversely on morality risks and impatience leading to lower public expenditures on health care in the political equilibrium. Consequently, higher substitutability is associated with greater polarization in wealth, and long-run distributions that are bimodal.

A political economy perspective on persistent inequality, inflation, and redistribution

In this paper we examine the dynamics of the link between inequality and inflation from a political economy perspective. We consider a simple dynamic general equilibrium model in which agents vote over the desired inflation rate in each period, and inequality is persistent. Inflation in our model is a mechanism of redistribution, and we find that the link between inequality and inflation within any period or over time depends on institutional and preference related parameters. Furthermore, we find that differences in the initial distributions of wealth can yield a diverse set of patterns for the evolution of the inflation and inequality link. Relative to existing literature, our model leads to more precise predictions about the inflation-inequality correlation. To that end, results in the extant empirical literature on the inflation and inequality link need to be interpreted with caution.

A national evaluation of the Australian Occupational Therapy Competency Standards (1994): a multistakeholder perspective

This paper summarises results from an evaluation of the adequacy and utility of the Australian Competency Standards for Entry-Level Occupational Therapists © (OT AUSTRALIA, 1994a). It comprised a two-part study, incorporating an online survey of key national stakeholders (n = 26), and 13 focus groups (n = 152) conducted throughout Australia with occupational therapy clinicians, academics, OT AUSTRALIA association and Occupational Therapy Registration Board representatives, as well as university program accreditors. The key recommendations were that: (i) urgent revision to reflect contemporary practice, paradigms, approaches and frameworks is required; (ii) the standards should exemplify basic competence at graduation (not within two years following); (iii) a revision cycle of five years is required; (iv) the Australian Qualifications Framework should be retained, preceded by an introduction describing the scope and nature of occupational therapy practice in the national context; (v) access to the standards should be free and unrestricted to occupational therapists, students and the public via the OT AUSTRALIA (national) website; (vi) the standards should incorporate a succinct executive summary and additional tools or templates formatted to enable occupational therapists to develop professional portfolios and create working documents specific to their workplace; and (vii) language must accommodate contextual variation while striking an appropriate balance between providing instruction and encouraging innovation in practice.

Choice of image features for depth-axis control in image based visual servo control

This paper is concerned with choosing image features for image based visual servo control and how this choice influences the closed-loop dynamics of the system. In prior work, image features tend to be chosen on the basis of image processing simplicity and noise sensitivity. In this paper we show that the choice of feature directly influences the closed-loop dynamics in task-space. We focus on the depth axis control of a visual servo system and compare analytically various approaches that have been reported recently in the literature. The theoretical predictions are verified by experiment.

Adaptive depth estimation in image based visual servo control of dynamic systems

This paper considers the question of designing a fully image based visual servo control for a dynamic system. The work is motivated by the ongoing development of image based visual servo control of small aerial robotic vehicles. The observed targets considered are coloured blobs on a flat surface to which the normal direction is known. The theoretical framework is directly applicable to the case of markings on a horizontal floor or landing field. The image features used are a first order spherical moment for position and an image flow measurement for velocity. A fully non-linear adaptive control design is provided that ensures global stability of the closed-loop system. © 2005 IEEE.

Omnidirectional visual odometry for a planetary rover

Position estimation for planetary rovers has been typically limited to odometry based on proprioceptive measurements such as the integration of distance traveled and measurement of heading change. Here we present and compare two methods of online visual odometry suited for planetary rovers. Both methods use omnidirectional imagery to estimate motion of the rover. One method is based on robust estimation of optical flow and subsequent integration of the flow. The second method is a full structure-from-motion solution. To make the comparison meaningful we use the same set of raw corresponding visual features for each method. The dataset is an sequence of 2000 images taken during a field experiment in the Atacama desert, for which high resolution GPS ground truth is available.

Robust outdoor visual localization using a three-dimensional-edge map

Visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. Changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. To confront the problem, we have developed a visual localization system that uses a surveyed three-dimensional (3D)-edge map of permanent structures in the environment. The map has the invariant properties necessary to achieve long-term robust operation. Previous 3D-edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. A multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. A novel observation function for the particle filter is developed and evaluated against two existing functions. The new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. An intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. Results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. The conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions.

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

Effect of representation size and visual ambiguity on RatSLAM system performance

RatSLAM is a vision-based SLAM system based on extended models of the rodent hippocampus. RatSLAM creates environment representations that can be processed by the experience mapping algorithm to produce maps suitable for goal recall. The experience mapping algorithm also allows RatSLAM to map environments many times larger than could be achieved with a one to one correspondence between the map and environment, by reusing the RatSLAM maps to represent multiple sections of the environment. This paper describes experiments investigating the effects of the environment-representation size ratio and visual ambiguity on mapping and goal navigation performance. The experiments demonstrate that system performance is weakly dependent on either parameter in isolation, but strongly dependent on their joint values.

Featureless vehicle-based visual SLAM with a consumer camera

The Simultaneous Localisation And Mapping (SLAM) problem is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision-only approaches. We present an alternative approach to the leading existing techniques, which extracts approximate rotational and translation velocity information from a vehicle-mounted consumer camera, without tracking landmarks. When coupled with an existing SLAM system, the vision module is able to map a 45 metre long indoor loop and a 1.6 km long outdoor road loop, without any parameter or system adjustment between tests. The work serves as a promising pilot study into ground-based vision-only SLAM, with minimal geometric interpretation of the environment.

Augmenting RatSLAM using FAB-MAP-based visual data association

This paper investigates the use of the FAB-MAP appearance-only SLAM algorithm as a method for performing visual data association for RatSLAM, a semi-metric full SLAM system. While both systems have shown the ability to map large (60-70km) outdoor locations of approximately the same scale, for either larger areas or across longer time periods both algorithms encounter difficulties with false positive matches. By combining these algorithms using a mapping between appearance and pose space, both false positives and false negatives generated by FAB-MAP are significantly reduced during outdoor mapping using a forward-facing camera. The hybrid FAB-MAP-RatSLAM system developed demonstrates the potential for successful SLAM over large periods of time.