929 resultados para Multi-service assets
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Bactrocera dorsalis sensu stricto, B. papayae, B. philippinensis and B. carambolae are serious pest fruit fly species of the B. dorsalis complex that predominantly occur in south-east Asia and the Pacific. Identifying molecular diagnostics has proven problematic for these four taxa, a situation that cofounds biosecurity and quarantine efforts and which may be the result of at least some of these taxa representing the same biological species. We therefore conducted a phylogenetic study of these four species (and closely related outgroup taxa) based on the individuals collected from a wide geographic range; sequencing six loci (cox1, nad4-3′, CAD, period, ITS1, ITS2) for approximately 20 individuals from each of 16 sample sites. Data were analysed within maximum likelihood and Bayesian phylogenetic frameworks for individual loci and concatenated data sets for which we applied multiple monophyly and species delimitation tests. Species monophyly was measured by clade support, posterior probability or bootstrap resampling for Bayesian and likelihood analyses respectively, Rosenberg's reciprocal monophyly measure, P(AB), Rodrigo's (P(RD)) and the genealogical sorting index, gsi. We specifically tested whether there was phylogenetic support for the four 'ingroup' pest species using a data set of multiple individuals sampled from a number of populations. Based on our combined data set, Bactrocera carambolae emerges as a distinct monophyletic clade, whereas B. dorsalis s.s., B. papayae and B. philippinensis are unresolved. These data add to the growing body of evidence that B. dorsalis s.s., B. papayae and B. philippinensis are the same biological species, which poses consequences for quarantine, trade and pest management.
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Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.
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Service bundles, in the context of e-government, are used to group services together that relate to a certain citizen need. These bundles can then be presented on a governmental one-stop portal to structure the available service offerings according to citizen expectations. In order to ensure that citizens utilise the one-stop portal and comprised service bundles for future transactions, the quality of these service bundles needs to be managed and maximised accordingly. Consequently, models and tools that focus on assessing service bundle quality play an important role, when it comes to increasing or retaining usage behaviour of citizens. This study focuses on providing a rigorous and structured literature review of e-government outlets with regards to their coverage of service bundle quality and e-service quality themes. The study contributes to academia and practice by providing a framework that allows structuring and classifying existing studies relevant for the assessment of quality for government portals. Furthermore, this study provides insights into the status quo of quality models that can be used by governments to assess the quality of their service bundles. Directions for future research and limitations of the present study are provided as well.
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The HS program consists of a voluntary health screening and personalised feedback (via a website) which incorporates physical measurements, psychological stress assessment and blood tests. The following report describes the results of a research project that evaluated the effectiveness of the QPS-HS program and examines the health benefits it offers its participants. This report has three main areas that correspond to the research questions and includes three primary aims: 1.Review the literature pertaining to the health, social and economic value of wellness programs in workplaces. In particular, we reviewed policing worksites and other safety sensitive workplaces, to understand best-practice wellness programming and return on investment, in terms of value to employees, social value to the community, and economic value to employers; 2.Evaluate health outcomes of participants in the HS program, including physical measurements, such as blood tests and psychological well-being. These measures were to form an outcome evaluation and assess the effectiveness of the HS program in positively impacting physical and psychological health of HS participants; and 3.Assess employee awareness and perceptions of the HS program for a process evaluation.
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Project work has grown significantly in volume and recognition in recent decades as projects have ‘become a common form of work organization in all sectors of the economy’ (Lindgren & Packendorff, 2006: 841). This increase in project-based work is just one of the many changes that have been affecting the nature of work, the employment relationship and the associated conceptualization and experience of careers (Baruch, 2004b; Söderlund & Bredin, 2006). A career can be defined as a process of development along a path of work experience and roles in one or more organizations (Baruch & Rosenstein, 1992), and careers involving project-based work take place within multi layered institutional settings. Projects are generally undertaken by small temporary organizations (Ekstedt, Lundin, Söderholm & Wirdenius, 1999; Pettigrew, 2003; Söderlund, 2012) which in turn may form part of larger, permanent entities; involve people drawn from a number of disciplines and organizations; or be formed as partnerships, joint ventures or strategic alliances between two or more organizations (Scott, 2007).
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Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.
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This paper aims to address the knowledge gap in regards to the potential intermediary role tertiary institutions can play in developing generic design thinking/design led innovation capabilities in non-designers. Specifically, it investigates the value derived from the contribution of postgraduate design students as facilitators/educators for undergraduate non-design student cohorts. It examines a design immersion workshop designed to encourage the use of design thinking capabilities for project brief development for undergraduate multi-disciplinary student teams involved in a community service learning project for a social enterprise. The workshop was facilitated by design led innovation masters students embedded in industry organisations to research the integration of design led innovation capabilities in business. Data was collected from participating non-design students and postgraduate facilitators’ in the form of reflective journals and semi-structured interviews. The thematic analysis provided insight into the value of design thinking/design led innovation immersion programs for both the postgraduate facilitators and the undergraduate non-design students. The research results will inform a tentative foundation prototype framework to allow for ongoing program developments and research in design thinking/design led innovation integration in higher education, facilitating the development of generic capabilities required to empower future generations for business innovation and active citizenship in the 21st century knowledge economy.
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A design for a cascaded multilevel DC-DC converter is proposed. The applications of a multilevel converter and the design issues involved in changing from a single converter to multiple converters are discussed. Implementation of the multilevel system using multiple Cuk converters is suggested and explanations of design decisions are given. The merits of the proposed design are discussed.
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Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.
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Emergency management and climate change adaptation will increasingly challenge all levels of government because of three main factors. First, Australia is extremely vulnerable to the impacts of climate change, particularly through the increasing frequency, duration and/or intensity of disasters such as floods and bushfires. Second, the system of government that divides powers by function and level can often act as a barrier to a well-integrated response. Third, policymaking processes struggle to cope with such complex inter-jurisdictional issues. This paper discusses these factors and explores the nature of the challenge for Australian governments. Investigations into the 2009 Victorian bushfires, the 2011 Perth Hills bushfires, and the 2011 Brisbane floods offer an indication of the challenges ahead and it is argued that there is a need to: improve community engagement and communication; refocus attention on resilience; improve interagency communication and collaboration; and, develop institutional arrangements that support continual improvement and policy learning. These findings offer an opportunity for improving responses as well as a starting point for integrating disaster risk management and climate change adaptation policies. The paper is based on the preliminary findings of an NCCARF funded research project: The Right Tool for the Job: Achieving climate change adaptation outcomes through improved disaster management policies, planning and risk management strategies involving Griffith University and RMIT. It should be noted from the outset that the purpose of this research project is not to criticise the actions of emergency service workers and volunteers who do an incredible job under extreme circumstances, often risking their own lives in the process. The aim is simply to offer emergency management agencies the opportunity to step back and rethink their overall approach to the challenge they face in the light of the impacts of climate change.
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An Application Specific Instruction-set Processor (ASIP) is a specialized processor tailored to run a particular application/s efficiently. However, when there are multiple candidate applications in the application’s domain it is difficult and time consuming to find optimum set of applications to be implemented. Existing ASIP design approaches perform this selection manually based on a designer’s knowledge. We help in cutting down the number of candidate applications by devising a classification method to cluster similar applications based on the special-purpose operations they share. This provides a significant reduction in the comparison overhead while resulting in customized ASIP instruction sets which can benefit a whole family of related applications. Our method gives users the ability to quantify the degree of similarity between the sets of shared operations to control the size of clusters. A case study involving twelve algorithms confirms that our approach can successfully cluster similar algorithms together based on the similarity of their component operations.
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Introduction Malnutrition is common among hospitalised patients, with poor follow-up of nutrition support post-discharge. Published studies on the efficacy of ambulatory nutrition support (ANS) for malnourished patients post-discharge are scarce. The aims of this study were to evaluate the rate of dietetics follow-up of malnourished patients post-discharge, before (2008) and after (2010) implementation of a new ANS service, and to evaluate nutritional outcomes post-implementation. Materials and Methods Consecutive samples of 261 (2008) and 163 (2010) adult inpatients referred to dietetics and assessed as malnourished using Subjective Global Assessment (SGA) were enrolled. All subjects received inpatient nutrition intervention and dietetic outpatient clinic follow-up appointments. For the 2010 cohort, ANS was initiated to provide telephone follow-up and home visits for patients who failed to attend the outpatient clinic. Subjective Global Assessment, body weight, quality of life (EQ-5D VAS) and handgrip strength were measured at baseline and five months post-discharge. Paired t-test was used to compare pre- and post-intervention results. Results In 2008, only 15% of patients returned for follow-up with a dietitian within four months post-discharge. After implementation of ANS in 2010, the follow-up rate was 100%. Mean weight improved from 44.0 ± 8.5kg to 46.3 ± 9.6kg, EQ-5D VAS from 61.2 ± 19.8 to 71.6 ± 17.4 and handgrip strength from 15.1 ± 7.1 kg force to 17.5 ± 8.5 kg force; p<0.001 for all. Seventy-four percent of patients improved in SGA score. Conclusion Ambulatory nutrition support resulted in significant improvements in follow-up rate, nutritional status and quality of life of malnourished patients post-discharge.
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Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with the use of data mining. This research develops two-way recommendation methods for people-to-people recommendation for large online social networks such as online dating networks. This research discovers the characteristics of the online dating networks and utilises these characteristics in developing efficient people-to-people recommendation methods. Methods developed support improved recommendation accuracy, can handle data sparsity that often comes with large data sets and are scalable for handling online networks with a large number of users.
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Background Rates of chronic disease are escalating around the world. To date health service evaluations have focused on interventions for single chronic diseases. However, evaluations of the effectiveness of new intervention strategies that target single chronic diseases as well as multimorbidity are required, particularly in areas outside major metropolitan centres where access to services, such as specialist care, is difficult and where the retention and recruitment of health professionals affects service provision. Methods This study is a longitudinal investigation with a baseline and three follow-up assessments comparing the health and health costs of people with chronic disease before and after intervention at a chronic disease clinic, in regional Australia. The clinic is led by students under the supervision of health professionals. The study will provide preliminary evidence regarding the effectiveness of the intervention, and evaluate the influence of a range of factors on the health outcomes and costs of the patients attending the clinic. Patients will be evaluated at baseline (intake to the service), and at 3-, 6-, and 12-months after intake to the service. Health will be measured using the SF-36 and health costs will be measured using government and medical record sources. The intervention involves students and health professionals from multiple professions working together to treat patients with programs that include education and exercise therapy programs for back pain, and Healthy Lifestyle programs; as well as individual consultations involving single professions. Discussion Understanding the effect of a range of factors on the health state and health costs of people attending an interdisciplinary clinic will inform health service provision for this clinical group and will determine which factors need to be controlled for in future observational studies. Preliminary evidence regarding changes in health and health costs associated with the intervention will be a platform for future clinical trials of intervention effectiveness. The results will be of interest to teams investigating new chronic disease programs particularly for people with multimorbidity, and in areas outside major metropolitan centres.
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A controlled layer of multi-wall carbon nanotubes (MWCNT) was grown directly on top of fluorine-doped tin oxide (FTO) glass electrodes as a surface modifier for improving the performance of polymer solar cells. By using low-temperature chemical vapor deposition with short synthesis times, very short MWCNTs were grown, these uniformly decorating the FTO surface. The chemical vapor deposition parameters were carefully refined to balance the tube size and density, while minimizing the decrease in conductivity and light harvesting of the electrode. As created FTO/CNT electrodes were applied to bulk-heterojunction polymer solar cells, both in direct and inverted architecture. Thanks to the inclusion of MWCNT and the consequent nano-structuring of the electrode surface, we observe an increase in external quantum efficiency in the wavelength range from 550 to 650 nm. Overall, polymer solar cells realized with these FTO/CNT electrodes attain power conversion efficiency higher than 2%, outclassing reference cells based on standard FTO electrodes.