Data and process requirements for product recall coordination

When an organisation becomes aware that one of its products may pose a safety risk to customers, it must take appropriate action as soon as possible or it can be held liable. The ability to automatically trace potentially dangerous goods through the supply chain would thus help organisations fulfill their legal obligations in a timely and effective manner. Furthermore, product recall legislation requires manufacturers to separately notify various government agencies, the health department and the public about recall incidents. This duplication of effort and paperwork can introduce errors and data inconsistencies. In this paper, we examine traceability and notification requirements in the product recall domain from two perspectives: the activities carried out during the manufacturing and recall processes and the data collected during the enactment of these processes. We then propose a workflow-based coordination framework to support these data and process requirements.

Using reputation management in participatory sensing for data classification

Participatory sensing enables collection, processing, dissemination and analysis of environmental sensory data by ordinary citizens, through mobile devices. Researchers have recognized the potential of participatory sensing and attempted applying it to many areas. However, participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data quality has become a significant issue. This study proposes using reputation management to classify the gathered data and provide useful information for campaign organizers and data analysts to facilitate their decisions.

Clinical factors and technological barriers as determinants for the intention to use wireless handheld technology in healthcare environment: an Indian case study

Abstract]: Traditional technology adoption models identified ‘ease of use’ and ‘usefulness’ as the dominating factors for technology adoption. However, recent studies in healthcare have established that these two factors are not always reliable on their own and other factors may influence technology adoption. To establish the identity of these additional factors, a mixed method approach was used and data were collected through interviews and a survey. The survey instrument was specifically developed for this study so that it is relevant to the Indian healthcare setting. We identified clinical management and technological barriers as the dominant factors influencing the wireless handheld technology adoption in the Indian healthcare environment. The results of this study showed that new technology models will benefit by considering the clinical influences of wireless handheld technology, in addition to known factors. The scope of this study is restricted to wireless handheld devices such as PDAs, smart phones, and handheld PCs Gururajan, Raj and Hafeez-Baig, Abdul and Gururajan, Vijaya

The PSS : From Flat Maps to Layered Perspectives - the contribution of the Airport Metropolis Planning Support System (PSS) to sub-regional planning in the Brisbane Airport case environment

Conventional planning and decision making, with its sectoral and territorial emphasis and flat-map based processes are no longer adequate or appropriate for the increased complexity confronting airport/city interfaces. These crowed and often contested governance spaces demand a more iterative and relational planning and decision-making approach. Emergent GIS based planning and decision-making tools provide a mechanism which integrate and visually display an array of complex data, frameworks and scenarios/expectations, often in ‘real time’ computations. In so doing, these mechanisms provide a common ground for decision making and facilitate a more ‘joined-up’ approach to airport/city planning. This paper analyses the contribution of the Airport Metropolis Planning Support System (PSS) to sub-regional planning in the Brisbane Airport case environment.

Analysis of productive performance of crop and animal production systems : an integrated analytical framework

This article presents a two-stage analytical framework that integrates ecological crop (animal) growth and economic frontier production models to analyse the productive efficiency of crop (animal) production systems. The ecological crop (animal) growth model estimates "potential" output levels given the genetic characteristics of crops (animals) and the physical conditions of locations where the crops (animals) are grown (reared). The economic frontier production model estimates "best practice" production levels, taking into account economic, institutional and social factors that cause farm and spatial heterogeneity. In the first stage, both ecological crop growth and economic frontier production models are estimated to calculate three measures of productive efficiency: (1) technical efficiency, as the ratio of actual to "best practice" output levels; (2) agronomic efficiency, as the ratio of actual to "potential" output levels; and (3) agro-economic efficiency, as the ratio of "best practice" to "potential" output levels. Also in the first stage, the economic frontier production model identifies factors that determine technical efficiency. In the second stage, agro-economic efficiency is analysed econometrically in relation to economic, institutional and social factors that cause farm and spatial heterogeneity. The proposed framework has several important advantages in comparison with existing proposals. Firstly, it allows the systematic incorporation of all physical, economic, institutional and social factors that cause farm and spatial heterogeneity in analysing the productive performance of crop and animal production systems. Secondly, the location-specific physical factors are not modelled symmetrically as other economic inputs of production. Thirdly, climate change and technological advancements in crop and animal sciences can be modelled in a "forward-looking" manner. Fourthly, knowledge in agronomy and data from experimental studies can be utilised for socio-economic policy analysis. The proposed framework can be easily applied in empirical studies due to the current availability of ecological crop (animal) growth models, farm or secondary data, and econometric software packages. The article highlights several directions of empirical studies that researchers may pursue in the future.

Malnutrition and chemotherapy-induced nausea and vomiting : implications for practice

PURPOSE/OBJECTIVES: To determine the prevalence of malnutrition and chemotherapy-induced nausea and vomiting (CINV) limiting dietary intake in a chemotherapy unit. DESIGN Cross sectional descriptive audit. SETTING: Chemotherapy ambulatory care unit in an Australian teaching hospital. SAMPLE 121 patients receiving chemotherapy for malignancies, ≥18yrs and able to provide verbal consent. METHODS: An Accredited Practicing Dietitian collected all data. Chi-square tests were used to determine the relationship of malnutrition with variables and demographic data. MAIN RESEARCH VARIABLES: Nutritional status, weight change, BMI, prior dietetic input, CINV and CINV that limited dietary intake. FINDINGS Thirty one (26%) participants were malnourished, 12 (10%) had intake-limiting CINV, 22 (20%) reported significant weight loss and 20 (18%) required improved nutrition symptom management. High nutrition risk diagnoses, CINV, BMI and weight loss were significantly associated with malnutrition. Thirteen (35%) participants with malnutrition, significant weight loss, intake-limiting CINV and/or critically requiring improved symptom management reported no dietetic input; the majority of whom were overweight or obese. CONCLUSIONS: This audit determined over one quarter of patients receiving chemotherapy in this ambulatory setting were malnourished and the majority of patients reporting intake-limiting CINV were malnourished. IMPLICATIONS FOR NURSING Patients with malnutrition and/or intake-limiting CINV and in need of improved nutrition symptom management may be overlooked, especially patients who are overweight or obese - an increasing proportion of the Australian population. Evidence-based practice guidelines recommend implementing validated nutrition screening tools, such as the Malnutrition Screening Tool, in patients undergoing chemotherapy to identify those at risk of malnutrition requiring dietitian referral.

Identifying differences in safe roads and crash prone roads using clustering data mining

Road asset managers are overwhelmed with a high volume of raw data which they need to process and utilise in supporting their decision making. This paper presents a method that processes road-crash data of a whole road network and exposes hidden value inherent in the data by deploying the clustering data mining method. The goal of the method is to partition the road network into a set of groups (classes) based on common data and characterise the class crash types to produce a crash profiles for each cluster. By comparing similar road classes with differing crash types and rates, insight can be gained into these differences that are caused by the particular characteristics of their roads. These differences can be used as evidence in knowledge development and decision support.

Determinants and effects of information sharing with key suppliers

This paper focuses on information sharing with key suppliers and seeks to explore the factors that might influence its extent and depth. We also investigate how information sharing affects a company’s performance with regards to resource usage, output, and flexibility. Drawing from transaction cost- and contingency theories, several factors, namely environmental uncertainty, demand uncertainty, dependency and, the product life cycle stage are proposed to explain the level of information shared with key suppliers. We develop a model where information sharing mediates the (contingent) factors and company performance. A mail survey was used to collect data from Finnish and Swedish companies. Partial Least Squares analysis was separately performed for each country (n=119, n=102). There was consistent evidence that environmental uncertainty, demand uncertainty and supplier/buyer dependency had explanatory power, whereas no significance was found for the relationship between product life cycle stage and information sharing. The results also confirm previous studies by providing support for a positive relationship between information sharing and performance, where output performance was found to be the most strongly related.

The conceptual and operational compatibility of data breach notification and information privacy laws

Mandatory data breach notification laws are a novel and potentially important legal instrument regarding organisational protection of personal information. These laws require organisations that have suffered a data breach involving personal information to notify those persons that may be affected, and potentially government authorities, about the breach. The Australian Law Reform Commission (ALRC) has proposed the creation of a mandatory data breach notification scheme, implemented via amendments to the Privacy Act 1988 (Cth). However, the conceptual differences between data breach notification law and information privacy law are such that it is questionable whether a data breach notification scheme can be solely implemented via an information privacy law. Accordingly, this thesis by publications investigated, through six journal articles, the extent to which data breach notification law was conceptually and operationally compatible with information privacy law. The assessment of compatibility began with the identification of key issues related to data breach notification law. The first article, Stakeholder Perspectives Regarding the Mandatory Notification of Australian Data Breaches started this stage of the research which concluded in the second article, The Mandatory Notification of Data Breaches: Issues Arising for Australian and EU Legal Developments (‘Mandatory Notification‘). A key issue that emerged was whether data breach notification was itself an information privacy issue. This notion guided the remaining research and focused attention towards the next stage of research, an examination of the conceptual and operational foundations of both laws. The second article, Mandatory Notification and the third article, Encryption Safe Harbours and Data Breach Notification Laws did so from the perspective of data breach notification law. The fourth article, The Conceptual Basis of Personal Information in Australian Privacy Law and the fifth article, Privacy Invasive Geo-Mashups: Privacy 2.0 and the Limits of First Generation Information Privacy Laws did so for information privacy law. The final article, Contextualizing the Tensions and Weaknesses of Information Privacy and Data Breach Notification Laws synthesised previous research findings within the framework of contextualisation, principally developed by Nissenbaum. The examination of conceptual and operational foundations revealed tensions between both laws and shared weaknesses within both laws. First, the distinction between sectoral and comprehensive information privacy legal regimes was important as it shaped the development of US data breach notification laws and their subsequent implementable scope in other jurisdictions. Second, the sectoral versus comprehensive distinction produced different emphases in relation to data breach notification thus leading to different forms of remedy. The prime example is the distinction between market-based initiatives found in US data breach notification laws compared to rights-based protections found in the EU and Australia. Third, both laws are predicated on the regulation of personal information exchange processes even though both laws regulate this process from different perspectives, namely, a context independent or context dependent approach. Fourth, both laws have limited notions of harm that is further constrained by restrictive accountability frameworks. The findings of the research suggest that data breach notification is more compatible with information privacy law in some respects than others. Apparent compatibilities clearly exist as both laws have an interest in the protection of personal information. However, this thesis revealed that ostensible similarities are founded on some significant differences. Data breach notification law is either a comprehensive facet to a sectoral approach or a sectoral adjunct to a comprehensive regime. However, whilst there are fundamental differences between both laws they are not so great to make them incompatible with each other. The similarities between both laws are sufficient to forge compatibilities but it is likely that the distinctions between them will produce anomalies particularly if both laws are applied from a perspective that negates contextualisation.

Impact of a data warehouse model for improved decision-making process in healthcare

The health system is one sector dealing with a deluge of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Also, there are many healthcare organisations, which still have stand-alone systems, not integrated for management of information and decision-making. This shows, there is a need for an effective system to capture, collate and distribute this health data. Therefore, implementing the data warehouse concept in healthcare is potentially one of the solutions to integrate health data. Data warehousing has been used to support business intelligence and decision-making in many other sectors such as the engineering, defence and retail sectors. The research problem that is going to be addressed is, "how can data warehousing assist the decision-making process in healthcare". To address this problem the researcher has narrowed an investigation focusing on a cardiac surgery unit. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. The cardiac surgery unit at TPCH uses a stand-alone database of patient clinical data, which supports clinical audit, service management and research functions. However, much of the time, the interaction between the cardiac surgery unit information system with other units is minimal. There is a limited and basic two-way interaction with other clinical and administrative databases at TPCH which support decision-making processes. The aims of this research are to investigate what decision-making issues are faced by the healthcare professionals with the current information systems and how decision-making might be improved within this healthcare setting by implementing an aligned data warehouse model or models. As a part of the research the researcher will propose and develop a suitable data warehouse prototype based on the cardiac surgery unit needs and integrating the Intensive Care Unit database, Clinical Costing unit database (Transition II) and Quality and Safety unit database [electronic discharge summary (e-DS)]. The goal is to improve the current decision-making processes. The main objectives of this research are to improve access to integrated clinical and financial data, providing potentially better information for decision-making for both improved from the questionnaire and by referring to the literature, the results indicate a centralised data warehouse model for the cardiac surgery unit at this stage. A centralised data warehouse model addresses current needs and can also be upgraded to an enterprise wide warehouse model or federated data warehouse model as discussed in the many consulted publications. The data warehouse prototype was able to be developed using SAS enterprise data integration studio 4.2 and the data was analysed using SAS enterprise edition 4.3. In the final stage, the data warehouse prototype was evaluated by collecting feedback from the end users. This was achieved by using output created from the data warehouse prototype as examples of the data desired and possible in a data warehouse environment. According to the feedback collected from the end users, implementation of a data warehouse was seen to be a useful tool to inform management options, provide a more complete representation of factors related to a decision scenario and potentially reduce information product development time. However, there are many constraints exist in this research. For example the technical issues such as data incompatibilities, integration of the cardiac surgery database and e-DS database servers and also, Queensland Health information restrictions (Queensland Health information related policies, patient data confidentiality and ethics requirements), limited availability of support from IT technical staff and time restrictions. These factors have influenced the process for the warehouse model development, necessitating an incremental approach. This highlights the presence of many practical barriers to data warehousing and integration at the clinical service level. Limitations included the use of a small convenience sample of survey respondents, and a single site case report study design. As mentioned previously, the proposed data warehouse is a prototype and was developed using only four database repositories. Despite this constraint, the research demonstrates that by implementing a data warehouse at the service level, decision-making is supported and data quality issues related to access and availability can be reduced, providing many benefits. Output reports produced from the data warehouse prototype demonstrated usefulness for the improvement of decision-making in the management of clinical services, and quality and safety monitoring for better clinical care. However, in the future, the centralised model selected can be upgraded to an enterprise wide architecture by integrating with additional hospital units’ databases.

Safeguarding rural Australia : addressing masculinity and violence in rural settings : suicide and other violent self-harm in an Australian rural context : analysis of secondary data

This report is an update of an earlier one produced in September 2009 (see Carrington et al. 2009) which remains as an ePrint through the project’s home page. The report focuses on our examination of extant data which have been sourced with respect to self-harm and suicide among males living in regional and remote Australia and which were available in public data bases at production time. Moreover, specific areas of concern regarding elevated rates of suicide for rural males and data anomalies which emerged during our examination of these data are discussed.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Optimal sitting and sizing of distributed generators considering plug-in electric vehicles

Some uncertainties such as the stochastic input/output power of a plug-in electric vehicle due to its stochastic charging and discharging schedule, that of a wind unit and that of a photovoltaic generation source, volatile fuel prices and future uncertain load growth, all together could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distributed systems. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal sitting and sizing problem of DGs. First, a mathematical model of CCP is developed with the minimization of DGs investment cost, operational cost and maintenance cost as well as the network loss cost as the objective, security limitations as constraints, the sitting and sizing of DGs as optimization variables. Then, a Monte Carolo simulation embedded genetic algorithm approach is developed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is employed to verify the feasibility and effectiveness of the developed model and method. This work is supported by an Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Project on Intelligent Grids Under the Energy Transformed Flagship, and Project from Jiangxi Power Company.

Finding and matching communities in social networks using data mining

The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.

Association between prostinogen (KLK15) genetic variants and prostate cancer risk and aggressiveness in Australia and a meta-analysis of GWAS data

Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.