Quality in accounting education and low English standards among overseas students : is there a link?

Two studies of stakeholders in university education for accounting professionals in Australia provide evidence of a decline in the quality of accounting education as perceived by accounting academics. This decline may be linked to increasing enrolments of international students with poor English language skills. Some university lecturers indicate that the quality of students entering their courses has declined, as has the quality of those graduating. In an environment increasingly dominated by the need to publish or perish, assessment tasks such as essays, case studies, and research reports, designed to improve the English language and communications skills of graduates, may have been compromised. This may contribute to the fact that many employers of graduates are concerned about the low levels of English language and communication skills displayed by accounting graduates, particularly international students.

A psychological contract perspective to the link between non-profit organizations' management practices and volunteer sustainability

This study applies the concept of the psychological contract to the relationship between management practices and volunteers. Formalization of the voluntary sector is impacting on volunteers’ experiences and may breach the psychological contract from the volunteers’ perspective. This mixed method study interviewed 67 volunteers and volunteer coordinators/administrators, and collected mail survey information from 152 volunteer organizations. The transactional management practices of keeping formal records and not paying volunteers out of pocket expenses are negatively associated with volunteer recruitment and retention. Alternatively, publicly recognizing volunteers through a volunteer newsletter supports volunteers’ relational expectations and is positively linked to adequate volunteer numbers. Our findings have important implications for the human resource development practices of non-profit organizations in dealing with their volunteers: they suggest that the relational expectations of volunteers are an important aspect of the psychological contract, which could be used by organizations as a framework for developing management practices that fit the volunteer ethos of trust and networks.

Does cigarette promotion increase susceptibility to smoking? : a re-test of the link between tobacco industry promotion and adolescent susceptibility to cigarette use

In 1998, using the Index of Receptivity to Tobacco Industry Promotion (IRTIP), it was claimed that tobacco promotion increased youth susceptibility to smoking. Arguably, this claim started the belief that ?cigarette advertising causes smoking? and led to many countries severely restricting cigarette promotion. The problem is, ten years lat... more »er, youth are still lighting up. Could they have gotten it wrong? The IRTIP procedure is widely used to model the link between promotional activities and susceptibility to product use. It is now being used for other products like alcohol, fast-food and colas. This book reports the results of a verification and re-test of the IRTIP model. Using the original data, it was found that IRTIP magnifies Response-Style and Respondent Drop-Out Biases. These biases are shown to lead to the finding of a positive link between tobacco promotion and susceptibility to smoking. Because the IRTIP process is biased, it may be prudent to revisit the many research studies that have used this procedure. The faulty 1998 claim may have harmed efforts to control and limit the use of cigarettes.

Re-testing the link between youth receptivity to tobacco promotion and their susceptibility to smoke

The Index of Receptivity to Tobacco Industry Promotion (IRTIP) is a model that is used by hundreds of articles. The causal claim based on findings from this model is even more pervasive, and has resulted in much of the modern post 1998 tobacco legislation that is still enforced. This thesis tested the link between adolescent receptivity to tobacco industry promotion and susceptibility to smoking. Pierce et al. (1998) reported that they had found a positive and causal association between receptivity and susceptibility by using IRTIP. They claimed that receptivity to tobacco industry promotion was the only significant causal factor affecting adolescent susceptibility to smoking. Exposure to peer and parental smoking was not found to be a significant effect. A review of the literature found that many sections of IRTIP differ from accepted marketing theory on how cigarette advertising and promotions affect adolescent adoption of cigarette smoking. The proxy measures used in IRTIP were shown to diverge from those previously used for measuring the constructs of Attention, Intention, Desire and Action (AIDA) in marketing communications. IRTIP also differs from previous theory by including measures that attempt to quantify the effect of tobacco premiums into a model that was designed to measure the effects of advertising.

Questioning the construct of 'susceptibility' in the causal link between tobacco industry promotion and adolescent smoking

The first article to report on a causal connection between tobacco industry promotion and adolescent smoking (Pierce et al. 1998) had, and continues to have, a significant influence on the marketing of cigarettes in many parts of the world. A key construct in determining causality was the ability to identify the respondents’ “susceptibility to smoke”. Through an analysis of the questions, and reanalysis of the original data used by Pierce et al. (1998), it is shown that the construct is flawed, and needs revision before a causal link can be claimed with the original data.

Release of allergens in respirable aerosols : a link between grass pollen and asthma

Background: Asthma incidence has long been linked to pollen, even though pollen grains are too large to penetrate into the airways where asthmatic responses originate. Pollen allergens found in small, respirable particles have been implicated in a number of asthma epidemics, particularly ones following rainfall or thunderstorms.

Objective: The aim of this study was to determine how pollen allergens form the respirable aerosols necessary for triggering asthma.

Methods: Flowering grasses were humidified and then dried in a controlled-environment chamber connected to a cascade impactor and an aerosol particle counter. Particles shed from the flowers were analyzed with high-resolution microscopy and immunolabeled with rabbit anti-Phl p 1 antibody, which is specific for group 1 pollen allergens.

Results: Contrary to what has been reported in other published accounts, most of the pollen in this investigation remained on the open anthers of wind pollinated plants unless disturbed—eg, by wind. Increasing humidity caused anthers to close. After a cycle of wetting and drying followed by wind disturbance, grasses flowering within a chamber produced an aerosol of particles that were collected in a cascade impactor. These particles consisted of fragmented pollen cytoplasm in the size range 0.12 to 4.67 μm; they were loaded with group 1 allergens.

Conclusion: Here we provide the first direct observations of the release of grass pollen allergens as respirable aerosols. They can emanate directly from the flower after a moisture-drying cycle. This could explain asthmatic responses associated with grass pollination, particularly after moist weather conditions.

Growing community : the impact of the Stephanie Alexander kitchen garden program on the social and learning environment in primary schools

This article presents results from a mixed-method evaluation of a structured cooking and gardening program in Australian primary schools, focusing on program impacts on the social and learning environment of the school. In particular, we address the Stephanie Alexander Kitchen Garden Program objective of providing a pleasurable experience that has a positive impact on student engagement, social connections, and confidence within and beyond the school gates. Primary evidence for the research question came from qualitative data collected from students, parents, teachers, volunteers, school principals, and specialist staff through interviews, focus groups, and participant observations. This was supported by analyses of quantitative data on child quality of life, cooperative behaviors, teacher perceptions of the school environment, and school-level educational outcome and absenteeism data. Results showed that some of the program attributes valued most highly by study participants included increased student engagement and confidence, opportunities for experiential and integrated learning, teamwork, building social skills, and connections and links between schools and their communities. In this analysis, quantitative findings failed to support findings from the primary analysis. Limitations as well as benefits of a mixed-methods approach to evaluation of complex community interventions are discussed.

Clarifying the link between social capital and MSME innovation performance : the role of absorptive capacity

A conceptual framework is proposed in this article showing how the social capital of a community shapes the innovation performance of micro, small and medium enterprises (MSMEs) through the exercise of absorptive capacity as the mediating phenomenon between the two. Its significance stems from the unprecedented effort of explaining how community social capital matters in the innovation performance of MSMEs, a departure from previous studies which typically examined market-related or hierarchical social capital in the form of formal networks and directly linking them to firm innovation without due regard to knowledge management within the firm as an antecedent of organizational innovation. The aim is to stimulate further thinking and empirical research on the subject of social capital of a community in an MSME and/or entrepreneurial context.

Policy recognition in the Abstract Hidden Markov Model

In this paper, we present a method for recognising an agent's behaviour in dynamic, noisy, uncertain domains, and across multiple levels of abstraction. We term this problem on-line plan recognition under uncertainty and view it generally as probabilistic inference on the stochastic process representing the execution of the agent's plan. Our contributions in this paper are twofold. In terms of probabilistic inference, we introduce the Abstract Hidden Markov Model (AHMM), a novel type of stochastic processes, provide its dynamic Bayesian network (DBN) structure and analyse the properties of this network. We then describe an application of the Rao-Blackwellised Particle Filter to the AHMM which allows us to construct an efficient, hybrid inference method for this model. In terms of plan recognition, we propose a novel plan recognition framework based on the AHMM as the plan execution model. The Rao-Blackwellised hybrid inference for AHMM can take advantage of the independence properties inherent in a model of plan execution, leading to an algorithm for online probabilistic plan recognition that scales well with the number of levels in the plan hierarchy. This illustrates that while stochastic models for plan execution can be complex, they exhibit special structures which, if exploited, can lead to efficient plan recognition algorithms. We demonstrate the usefulness of the AHMM framework via a behaviour recognition system in a complex spatial environment using distributed video surveillance data.

Tracking and surveillance in wide-area spatial environments using the abstract hidden markov model.

In this paper, we consider the problem of tracking an object and predicting the object's future trajectory in a wide-area environment, with complex spatial layout and the use of multiple sensors/cameras. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. We employ the Abstract Hidden Markov Models (AHMM), an extension of the well-known Hidden Markov Model (HMM) and a special type of Dynamic Probabilistic Network (DPN), as our underlying representation framework. The AHMM allows us to explicitly encode the hierarchy of connected spatial locations, making it scalable to the size of the environment being modeled. We describe an application for tracking human movement in an office-like spatial layout where the AHMM is used to track and predict the evolution of object trajectories at different levels of detail.

AdaBoost.MRF: boosted Markov random forests and application to multilevel activity recognition

Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov random field (MRF), known as the dynamic conditional random field (DCRF). Parameter estimation in general MRFs using maximum likelihood is known to be computationally challenging (except for extreme cases), and thus we propose an efficient boosting-based algorithm AdaBoost.MRF for this task. Distinct from most existing work, our algorithm can handle hidden variables (missing labels) and is particularly attractive for smarthouse domains where reliable labels are often sparsely observed. Furthermore, our method works exclusively on trees and thus is guaranteed to converge. We apply the AdaBoost.MRF algorithm to a home video surveillance application and demonstrate its efficacy.

Human behavior recognition with generic exponential family duration modeling in the hidden semi-Markov model

The ability to learn and recognize human activities of daily living (ADLs) is important in building pervasive and smart environments. In this paper, we tackle this problem using the hidden semi-Markov model. We discuss the state-of-the-art duration modeling choices and then address a large class of exponential family distributions to model state durations. Inference and learning are efficiently addressed by providing a graphical representation for the model in terms of a dynamic Bayesian network (DBN). We investigate both discrete and continuous distributions from the exponential family (Poisson and Inverse Gaussian respectively) for the problem of learning and recognizing ADLs. A full comparison between the exponential family duration models and other existing models including the traditional multinomial and the new Coxian are also presented. Our work thus completes a thorough investigation into the aspect of duration modeling and its application to human activities recognition in a real-world smart home surveillance scenario.

Activity recognition and abnormality detection with the switching hidden semi-Markov model

This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a pervasive and smart environment. In dealing with ADL, we argue that it is beneficial to exploit both the inherent hierarchical organization of the activities and their typical duration. To this end, we introduce the Switching Hidden Semi-Markov Model (S-HSMM), a two-layered extension of the hidden semi-Markov model (HSMM) for the modeling task. Activities are modeled in the S-HSMM in two ways: the bottom layer represents atomic activities and their duration using HSMMs; the top layer represents a sequence of high-level activities where each high-level activity is made of a sequence of atomic activities. We consider two methods for modeling duration: the classic explicit duration model using multinomial distribution, and the novel use of the discrete Coxian distribution. In addition, we propose an effective scheme to detect abnormality without the need for training on abnormal data. Experimental results show that the S-HSMM performs better than existing models including the flat HSMM and the hierarchical hidden Markov model in both classification and abnormality detection tasks, alleviating the need for presegmented training data. Furthermore, our discrete Coxian duration model yields better computation time and generalization error than the classic explicit duration model.