A platform - independent product library for BIM

There is considerable interest internationally in developing product libraries to support the use of BIM. Product library initiatives are driven by national bodies, manufacturers and private companies who see their potential. A major issue with the production and distribution of product information for BIM is that separate library objects need to be produced for all of the different software systems that are going to use the library. This increases the cost of populating product libraries and also increases the difficulty in maintaining consistency between the representations for the different software over time. This paper describes a project which uses “software transformation” technology from the field of software engineering to support the definition of a single generic representation of a product which can then be automatically converted to the format required by receiving software. The paper covers the current state of implementation of the product library, the technology underlying the transformations for the currently supported software and the business model for creating a national library in Australia. This is placed within the context of other current product library systems to highlight the differences. The responsibilities of the various actors involved in supporting the product library are also discussed.

Vertical alignment of process models – how can we get there?

There is a wide variety of drivers for business process modelling initiatives, reaching from business evolution and process optimisation over compliance checking and process certification to process enactment. That, in turn, results in models that differ in content due to serving different purposes. In particular, processes are modelled on different abstraction levels and assume different perspectives. Vertical alignment of process models aims at handling these deviations. While the advantages of such an alignment for inter-model analysis and change propagation are out of question, a number of challenges has still to be addressed. In this paper, we discuss three main challenges for vertical alignment in detail. Against this background, the potential application of techniques from the field of process integration is critically assessed. Based thereon, we identify specific research questions that guide the design of a framework for model alignment.

Validation of a framework for measuring hospital disaster resilience using factor analysis

Hospital disaster resilience can be defined as “the ability of hospitals to resist, absorb, and respond to the shock of disasters while maintaining and surging essential health services, and then to recover to its original state or adapt to a new one.” This article aims to provide a framework which can be used to comprehensively measure hospital disaster resilience. An evaluation framework for assessing hospital resilience was initially proposed through a systematic literature review and Modified-Delphi consultation. Eight key domains were identified: hospital safety, command, communication and cooperation system, disaster plan, resource stockpile, staff capability, disaster training and drills, emergency services and surge capability, and recovery and adaptation. The data for this study were collected from 41 tertiary hospitals in Shandong Province in China, using a specially designed questionnaire. Factor analysis was conducted to determine the underpinning structure of the framework. It identified a four-factor structure of hospital resilience, namely, emergency medical response capability (F1), disaster management mechanisms (F2), hospital infrastructural safety (F3), and disaster resources (F4). These factors displayed good internal consistency. The overall level of hospital disaster resilience (F) was calculated using the scoring model: F = 0.615F1 + 0.202F2 + 0.103F3 + 0.080F4. This validated framework provides a new way to operationalise the concept of hospital resilience, and it is also a foundation for the further development of the measurement instrument in future studies.

Semiparametric estimation of count regression models

This paper develops a semiparametric estimation approach for mixed count regression models based on series expansion for the unknown density of the unobserved heterogeneity. We use the generalized Laguerre series expansion around a gamma baseline density to model unobserved heterogeneity in a Poisson mixture model. We establish the consistency of the estimator and present a computational strategy to implement the proposed estimation techniques in the standard count model as well as in truncated, censored, and zero-inflated count regression models. Monte Carlo evidence shows that the finite sample behavior of the estimator is quite good. The paper applies the method to a model of individual shopping behavior. © 1999 Elsevier Science S.A. All rights reserved.

Defining and Accounting for Fundraising Income and Expenses

Charities' fundraising financial transactions should be reported in the interests of accountability, and the report should be publicly available. However, research shows that at present there is little consistency in how fundraising is defined or in how such transactions are reported, and little guidance from accounting standards. This report examines whether the current reporting of fundraising in annual financial statements by Australian charities is fit for the purposes of informing the donating public and other stakeholders, whether through the Australian Charities and Not-for-profits Commission’s registry strategy or through other means such as private ratings agencies. The authors endeavour to suggest a way forward if it is not.

Effect of pupil dilation and constriction on the distribution of bit errors within the iris

Texture information in the iris image is not uniform in discriminatory information content for biometric identity verification. The bits in an iris code obtained from the image differ in their consistency from one sample to another for the same identity. In this work, errors in bit strings are systematically analysed in order to investigate the effect of light-induced and drug-induced pupil dilation and constriction on the consistency of iris texture information. The statistics of bit errors are computed for client and impostor distributions as functions of radius and angle. Under normal conditions, a V-shaped radial trend of decreasing bit errors towards the central region of the iris is obtained for client matching, and it is observed that the distribution of errors as a function of angle is uniform. When iris images are affected by pupil dilation or constriction the radial distribution of bit errors is altered. A decreasing trend from the pupil outwards is observed for constriction, whereas a more uniform trend is observed for dilation. The main increase in bit errors occurs closer to the pupil in both cases.

A pilot study on affective classification of facial images for emerging news topics

The proliferation of news reports published in online websites and news information sharing among social media users necessitates effective techniques for analysing the image, text and video data related to news topics. This paper presents the first study to classify affective facial images on emerging news topics. The proposed system dynamically monitors and selects the current hot (of great interest) news topics with strong affective interestingness using textual keywords in news articles and social media discussions. Images from the selected hot topics are extracted and classified into three categorized emotions, positive, neutral and negative, based on facial expressions of subjects in the images. Performance evaluations on two facial image datasets collected from real-world resources demonstrate the applicability and effectiveness of the proposed system in affective classification of facial images in news reports. Facial expression shows high consistency with the affective textual content in news reports for positive emotion, while only low correlation has been observed for neutral and negative. The system can be directly used for applications, such as assisting editors in choosing photos with a proper affective semantic for a certain topic during news report preparation.

Detection of sinkhole attack in wireless sensor networks

Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

Legislative impact on the mortgagee’s exercise of power of sale : the need for rationalisation

Throughout Australia, regulation of the power of sale is highly inconsistent. In response to the uncertain nature of the mortgagee’s duty at common law, many legislatures have intervened. As a result, there has been a proliferation of statutory formula conferring varying degrees of protection on mortgagors. The differences in approach indicate a lack of consensus as to the best method of regulation. This article exposes the extent of the inconsistency and provides a comparative assessment of the various provisions with reference to the policy concerns that underpin legislative intervention. The article identifies a number of deficiencies associated with existing provisions and concludes that mortgagees and mortgagors alike would benefit from improved clarity and consistency. To that end, the article proposes a model provision that seeks to address the deficiencies identified.

Influence and increased funding in Canadian public libraries : the case of Alberta in fiscal year 2009–10

This exploratory case study examined the role of social influence in the decision-making process to increase public library funding in the Canadian province of Alberta in the 2009–10 fiscal year. Using Robert Cialdini’s theory of factors of influence (i.e., commitment and consistency, authority, liking, social proof, scarcity, and reciprocity) as a framework for analysis, findings show that consistency and commitment and authority were relevant and that liking was also important. These findings are consistent with Cialdini’s theory, which suggests that the quality of relationships is one factor that can most strongly influence a decision maker. This study gives insight into the factors motivating those involved in public library funding allocation decisions. No prior studies have examined the construct of influence in decision making about funding for public libraries at any level of government.

The role of interpersonal influence in budget decision making: The Canadian public library experience

This study determined factors which influenced Canadian provincial (state) politicians when making funding decisions for public libraries. Using the case study methodology, Canadian provincial/state-level funding for public libraries in the 2009-2010 fiscal year was examined. The data were analyzed to determine whether Cialdini’s theory of influence and specifically any of the six tactics of influence (i.e., commitment and consistency, authority, liking, social proof, scarcity, and reciprocity) were instrumental in these budgetary decision-making processes. Findings show the principles of “authority,” “consistency and commitment,” and “liking” were relevant, and that “liking” was especially important to these decisions.

Alignment and differences between the Australian Water Accounting Standard and the Water Accounting Framework for the Minerals Industry

In 2012, the Bureau of Meteorology under the banner of the Water Accounting Standards Board released the Australian Water Accounting Standard 1 (AWAS 1). This standard has been in development since 2007 with key milestones being the release of the Preliminary Australian Water Accounting Standard in 2009, and the exposure draft of the Australian Water Accounting Standard in 2010. Throughout this period, the Minerals Council of Australia’s Water Accounting Framework has developed concurrently with the Australian standards and the standards have informed elements of the framework. However, the framework is not identical to the standard as the objectives between the two are different. The objective of the Water Accounting Framework is to create consistency in water reporting of the minerals industry and to assist companies reporting to corporate sustainability initiatives. The objective of AWAS 1 is to provide information to water management bodies to facilitate decisions about the allocation of water resources. Companies are to report on an annual basis, not only physical flows of water but contractual requirements to supply and obtain water, regardless of whether the transaction has been fulfilled in the reporting period. In contrast, the Water Accounting Framework only reports on flows that have physically happened. The paper will provide summary information on aspects of AWAS 1 that are most relevant to the minerals industry, show the alignment and differences between AWAS 1 and the Water Accounting Framework and explain how to obtain the information for the AWAS 1 reporting statements.

The validity and reliability of the Parent Fever Management Scale: A study from Palestine

Background Parental fever phobia and overuse of antipyretics to control fever is increasing. Little is known about childhood fever management among Arab parents. No scales to measure parents’ fever management practices in Palestine are available. Aims The aims of this study were to translate and examine the psychometric properties of the Arabic version of the Parent Fever Management Scale (PFMS). Methods A standard “forward–backward” procedure was used to translate PFMS into Arabic language. It was then validated on a convenience sample of 402 parents between July and October 2012. Descriptive statistics were used, and instrument reliability was assessed for internal consistency using Cronbach's alpha coefficient. Validity was confirmed using convergent and known group validation. Results Applying the recommended scoring method, the median (interquartile range) score of the PFMS was 26 (23-30). Acceptable internal consistency was found (Cronbach’s alpha = 0.733) and the test–retest reliability value was 0.92 (P < 0.001). The chi-squared (χ2) test showed a significant relationship between PFMS groups and frequent daily administration of antipyretic groups (χ2 = 52.86; P < 0.001). The PFMS sensitivity and specificity were 77.67% and 57.75%, respectively. The positive and negative predictive values were 67.89% and 32.11%, respectively. Conclusions The findings of this validation study indicate that the Arabic version of the PFMS is a reliable and valid measure which can be used as a useful tool for health professionals to identify parents’ fever management practices and thus provide targeted education to reduce the unnecessary burden of care they place on themselves when concerned for a febrile child.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.