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

Comparison of eight published static finite element models of the intact lumbar spine : predictive power of models improves when combined together

Finite element (FE) model studies have made important contributions to our understanding of functional biomechanics of the lumbar spine. However, if a model is used to answer clinical and biomechanical questions over a certain population, their inherently large inter-subject variability has to be considered. Current FE model studies, however, generally account only for a single distinct spinal geometry with one set of material properties. This raises questions concerning their predictive power, their range of results and on their agreement with in vitro and in vivo values. Eight well-established FE models of the lumbar spine (L1-5) of different research centres around the globe were subjected to pure and combined loading modes and compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges, and their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with published median in vitro values. However, the ranges of predictions were larger and exceeded those reported in vitro, especially for the facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with measured in vivo values. In light of high inter-subject variability, the generalization of results of a single model to a population remains a concern. This study demonstrated that the pooled median of individual model results, similar to a probabilistic approach, can be used as an improved predictive tool in order to estimate the response of the lumbar spine.

The game of clones and the Australia tax : divergent views about copyright business models and the willingness of Australian consumers to infringe

It is often said that Australia is a world leader in rates of copyright infringement for entertainment goods. In 2012, the hit television show, Game of Thrones, was the most downloaded television show over bitorrent, and estimates suggest that Australians accounted for a plurality of nearly 10% of the 3-4 million downloads each week. The season finale of 2013 was downloaded over a million times within 24 hours of its release, and again Australians were the largest block of illicit downloaders over BitTorrent, despite our relatively small population. This trend has led the former US Ambassador to Australia to implore Australians to stop 'stealing' digital content, and rightsholders to push for increasing sanctions on copyright infringers. The Australian Government is looking to respond by requiring Internet Service Providers to issue warnings and potentially punish consumers who are alleged by industry groups to have infringed copyright. This is the logical next step in deterring infringement, given that the operators of infringing networks (like The Pirate Bay, for example) are out of regulatory reach. This steady ratcheting up of the strength of copyright, however, comes at a significant cost to user privacy and autonomy, and while the decentralisation of enforcement reduces costs, it also reduces the due process safeguards provided by the judicial process. This article presents qualitative evidence that substantiates a common intuition: one of the major reasons that Australians seek out illicit downloads of content like Game of Thrones in such numbers is that it is more difficult to access legitimately in Australia. The geographically segmented way in which copyright is exploited at an international level has given rise to a ‘tyranny of digital distance’, where Australians have less access to copyright goods than consumers in other countries. Compared to consumers in the US and the EU, Australians pay more for digital goods, have less choice in distribution channels, are exposed to substantial delays in access, and are sometimes denied access completely. In this article we focus our analysis on premium film and television offerings, like Game of Thrones, and through semi-structured interviews, explore how choices in distribution impact on the willingness of Australian consumers to seek out infringing copies of copyright material. Game of Thrones provides an excellent case study through which to frame this analysis: it is both one of the least legally accessible television offerings and one of the most downloaded through filesharing networks of recent times. Our analysis shows that at the same time as rightsholder groups, particularly in the film and television industries, are lobbying for stronger laws to counter illicit distribution, the business practices of their member organisations are counter-productively increasing incentives for consumers to infringe. The lack of accessibility and high prices of copyright goods in Australia leads to substantial economic waste. The unmet consumer demand means that Australian consumers are harmed by lower access to information and entertainment goods than consumers in other jurisdictions. The higher rates of infringement that fulfils some of this unmet demand increases enforcement costs for copyright owners and imposes burdens either on our judicial system or on private entities – like ISPs – who may be tasked with enforcing the rights of third parties. Most worryingly, the lack of convenient and cheap legitimate digital distribution channels risks undermining public support for copyright law. Our research shows that consumers blame rightsholders for failing to meet market demand, and this encourages a social norm that infringing copyright, while illegal, is not morally wrongful. The implications are as simple as they are profound: Australia should not take steps to increase the strength of copyright law at this time. The interests of the public and those of rightsholders align better when there is effective competition in distribution channels and consumers can legitimately get access to content. While foreign rightsholders are seeking enhanced protection for their interests, increasing enforcement is likely to increase their ability to engage in lucrative geographical price-discrimination, particularly for premium content. This is only likely to increase the degree to which Australian consumers feel that their interests are not being met and, consequently, to further undermine the legitimacy of copyright law. If consumers are to respect copyright law, increasing sanctions for infringement without enhancing access and competition in legitimate distribution channels could be dangerously counter-productive. We suggest that rightsholders’ best strategy for addressing infringement in Australia at this time is to ensure that Australians can access copyright goods in a timely, affordable, convenient, and fair lawful manner.

From words to models : a bibliometric approach to designing agent-based models in entrepreneurship

Agent-based modeling and simulation (ABMS) may fit well with entrepreneurship research and practice because the core concepts and basic premises of entrepreneurship coincide with the characteristics of ABMS. However, it is difficult to find cases where ABMS is applied to entrepreneurship research. To apply ABMS to entrepreneurship and organization studies, designing a conceptual model is important; thus to effectively design a conceptual model, various mixed method approaches are being attempted. As a new mixed method approach to ABMS, this study proposes a bibliometric approach to designing agent based models, which establishes and analyzes a domain corpus. This study presents an example on the venture creation process using the bibliometric approach. This example shows us that the results of the multi-agent simulations on the venturing process based on the bibliometric approach are close to each nation’s surveyed data on the venturing activities. In conclusion, by the bibliometric approach proposed in this study, all the agents and the agents’ behaviors related to a phenomenon can be extracted effectively, and a conceptual model for ABMS can be designed with the agents and their behaviors. This study contributes to the entrepreneurship and organization studies by promoting the application of ABMS.

Psychological capital as moderator of organizational change demands on nursing stress

Healthcare organizations in all OECD countries have continued to undergo change. These changes have been found to have a negative effect on work engagement of nursing staff. While the extent to which nursing staff dealt with these changes has been documented in the literature, little is known of how they utilized their personal resources to deal with the consequences of these changes. This study will address this gap by integrating the Job Demands-Resources theoretical perspective with Positive Psychology, in particular, psychological capital (PsyCap). PsyCap is operationalized as a source of personal resources. Data were collected from 401 nurses from Australia and analyses were undertaken using Partial Least Squares modelling and moderation analysis. Two types of changes on the nursing work were identified. There was an increase in changes to the work environment of nursing. These changes, included increasing administrative workload and the amount of work, resulted in more job demands and job resources. On the other hand, another type of changes relate to reduction to training and management support, which resulted in less job demands. Nurses with more job demands utilized more job resources to address these increasing demands. We found PsyCap to be a crucial source of personal resources that has a moderating effect on the negative effects of job demands and role stress. PsyCap and job resources were both critical in enhancing the work engagement of nurses, as they encountered changes to nursing work. These findings provided empirical support for a positive psychological perspective of understanding nursing engagement.

Extending building information models to specifications and cost planning

This digital poster (which was on display at "The Cube", Queensland University of Technology) demonstrates how specification parameters can be extracted from a product library repository for use in augmenting the information contents of the objects in a local BIM tool (Revit in this instance).

Purposeful program theory: Effective use of theories of change and logic models [Book Review]

The purpose of this book by two Australian authors is to: introduce the audience to the full complement of contextual elements found within program theory; offer practical suggestions to engage with theories of change, theories of action and logic models; and provide substantial evidence for this approach through scholarly literature, practice case studies together with the authors' combined experience of 60 years.

A policy model for access control using building information models

Building information models have created a paradigm shift in how buildings are built and managed by providing a dynamic repository for building data that is useful in many new operational scenarios. This change has also created an opportunity to use building information models as an integral part of security operations and especially as a tool to facilitate fine-grained access control to building spaces in smart buildings and critical infrastructure environments. In this paper, we identify the requirements for a security policy model for such an access control system and discuss why the existing policy models are not suitable for this application. We propose a new policy language extension to XACML, with BIM specific data types and functions based on the IFC specification, which we call BIM-XACML.

Graph theory based representation of building information models for access control applications

Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.