665 resultados para monitoring design


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Introduction: Nursing clinicians are primarily responsible for the monitoring and treatment of increased body temperature. The body temperature of patients during their acute care hospital stay is measured at regular repeated intervals. In the event a patient is assessed with an elevated temperature, a multitude of decisions are required. The action of instigating temperature reducing strategies is based upon the assumption that elevated temperature is harmful and that the strategy employed will have some beneficial effect. Background and Significance: The potential harmful effects of increased body temperature (fever, hyperthermia) following neurological insult are well recognised. Although few studies have investigated this phenomenon in the diagnostic population of non-traumatic subarachnoid haemorrhage, it has been demonstrated that increased body temperature occurs in 41 to 72% of patients with poor clinical outcome. However, in the Australian context the frequency, or other characteristics of increased body temperature, as well as the association between increased body temperature with poor clinical outcome has not been established. Design: This study used a correlational study design to: describe the frequency, duration and timing of increased body temperature; determine the association between increased body temperature and clinical outcome; and describe the clinical interventions used to manage increased body temperature in patients with non-traumatic subarachnoid haemorrhage. A retrospective clinical chart audit was conducted on 43 patients who met the inclusion criteria. Findings: The major findings of this study were: increased body temperature occurred frequently; persisted for a long time; and onset did not occur until 20 hours after primary insult; increased body temperature was associated with death or dependent outcome; and no intervention was recorded in many instances. Conclusion: This study has quantified in a non-traumatic subarachnoid haemorrhage patient population the characteristics of increased body temperature, established an association between increased body temperature with death or dependent outcome and described the current management of elevated temperatures in the Australian context to improve nursing practice, education and research.

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An Australian manufacturer has recently developed an innovative group of cold-formed steel hollow flange sections, one of them is LiteSteel Beams (LSBs). The LSB sections are produced from thin and high strength steels by a patented manufacturing process involving simultaneous cold-forming and dual electric resistance welding. They have a unique geometry consisting of rectangular hollow flanges and a relatively slender web. The LSB flexural members are subjected to lateral distortional buckling effects and hence their capacities are reduced for intermediate spans. The current design rules for lateral distortional buckling were developed based on the lower bound of numerical and experimental results. The effect of LSB section geometry was not considered although it could influence the lateral distortional buckling performance. Therefore an accurate finite element model of LSB flexural members was developed and validated using experimental and finite strip analysis results. It was then used to investigate the effect of LSB geometry. The extensive moment capacity data thus developed was used to develop improved design rules for LSBs with one of them considering the LSB geometry effects through a modified slenderness parameter. The use of the new design rules gave higher lateral distortional buckling capacities for LSB sections with intermediate slenderness. The new design rule is also able to accurately predict the lateral distortional buckling moment capacities of other hollow flange beams (HFBs).

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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The paper describes three design models that make use of generative and evolutionary systems. The models describe overall design methods and processes. Each model defines a set of tasks to be performed by the design team, and in each case one of the tasks requires a generative or evolutionary design system. The architectures of these systems are also broadly described.

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This paper documents the empowering process of a group of public housing residents through different design probing exercises. These exercises worked along with existing social processes without any involvement of designers. This paper shows how a design researcher devised a series of probing tools called "empowerment games" with a group of active users. These games are self-learning tools for making the abstract language of design legible to users. The main purpose of this intitiative was to change the preconception of govenmental bodies and professional designers of the passivity of the users with regard to their designed environment. This was the first case of the application of a participatory design process in Hong Kong subsidized housing. Design empathy is a central skill when working with users throughout the whole design research project.

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Ethnography has gained wide acceptance in the industrial design profession and curriculum as a means of understanding the user. However, there is considerable confusion about the particularities of its practice accompanied by the absence of an interoperable vocabulary. The consequent interdisciplinary effort is a power play between disciplines whereby the methodological view of ethnography marginalises its theoretical and analytical components. In doing so, it restricts the potential of ethnography suggesting the need for alternative methods of informing the design process. This article suggests that activity theory, with an emphasis on human activity as the fundamental unit of study, is an appropriate methodology for the generation of user requirements. The process is illustrated through the adaptation of an ethnographic case study, for the design of classroom furniture in India.

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Objective: To examine the impact on dental utilisation following the introduction of a participating provider scheme (Regional and Rural Oral Health Program {RROHP)). In this model dentists receive higher third party payments from a private health insurance fund for delivering an agreed range of preventive and diagnostic benefits at no out-ofpocket cost to insured patients. Data source/Study setting: Hospitals Contribution Fund of Australia (HCF) dental claims for all members resident in New South Wales over the six financial years from l99811999 to 200312004. Study design: This cohort study involves before and after analyses of dental claims experience over a six year period for approximately 81,000 individuals in the intervention group (HCF members resident in regional and rural New South Wales, Australia) and 267,000 in the control group (HCF members resident in the Sydney area). Only claims for individuals who were members of HCF at 31 December 1997 were included. The analysis groups claims into the three years prior to the establishment of the RROHP and the three years subsequent to implementation. Data collection/Extraction methods: The analysis is based on all claims submitted by users of services for visits between 1 July 1988 and 30 June 2004. In these data approximately 1,000,000 services were provided to the intervention group and approximately 4,900,000 in the control group. Principal findings: Using Statistical Process Control (SPC) charts, special cause variation was identified in total utilisation rate of private dental services in the intervention group post implementation. No such variation was present in the control group. On average in the three years after implementation of the program the utilisation rate of dental services by regional and rural residents of New South Wales who where members of HCF grew by 12.6%, over eight times the growth rate of 1.5% observed in the control group (HCF members who were Sydney residents). The differences were even more pronounced in the areas of service that were the focus of the program: diagnostic and preventive services. Conclusion: The implementation of a benefit design change, a participating provider scheme, that involved the removal of CO-payments on a defined range of preventive and diagnostic dental services combined with the establishment and promotion of a network of dentists, appears to have had a marked impact on HCF members' utilisation of dental services in regional and rural New South Wales, Australia.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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In a typical large office block, by far the largest lifetime expense is the salaries of the workers - 84% for salaries compared with : office rent (14%), total energy (1%), and maintenance (1%). The key drive for business is therefore the maximisation of the productivity of the employees as this is the largest cost. Reducing total energy use by 50% will not produce the same financial return as 1% productivity improvement? The aim of the project which led to this review of the literature was to understand as far as possible the state of knowledge internationally about how the indoor environment of buildings does influence occupants and the impact this influence may have on the total cost of ownership of buildings. Therefore one of the main focus areas for the literature has been identifying whether there is a link between productivity and health of building occupants and the indoor environment. Productivity is both easy to define - the ratio of output to input - but at the same time very hard to measure in a relatively small environment where individual contributions can influence the results, in particular social interactions. Health impacts from a building environment are also difficult to measure well, as establishing casual links between the indoor environment and a particular health issue can be very difficult. All of those issues are canvassed in the literature reported here. Humans are surprisingly adaptive to different physical environments, but the workplace should not test the limits of human adaptability. Physiological models of stress, for example, accept that the body has a finite amount of adaptive energy available to cope with stress. The importance of, and this projects' focus on, the physical setting within the integrated system of high performance workplaces, means this literature survey explores research which has been undertaken on both physical and social aspects of the built environment. The literature has been largely classified in several different ways, according to the classification scheme shown below. There is still some inconsistency in the use of keywords, which is being addressed and greater uniformity will be developed for a CD version of this literature, enabling searching using this classification scheme.

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An important aspect of designing any product is validation. Virtual design process (VDP) is an alternative to hardware prototyping in which analysis of designs can be done without manufacturing physical samples. In recent years, VDP have been generated either for animation or filming applications. This paper proposes a virtual reality design process model on one of the applications when used as a validation tool. This technique is used to generate a complete design guideline and validation tool of product design. To support the design process of a product, a virtual environment and VDP method were developed that supports validation and an initial design cycle performed by a designer. The product model car carrier is used as illustration for which virtual design was generated. The loading and unloading sequence of the model for the prototype was generated using automated reasoning techniques and was completed by interactively animating the product in the virtual environment before complete design was built. By using the VDP process critical issues like loading, unloading, Australian Design rules (ADR) and clearance analysis were done. The process would save time, money in physical sampling and to large extent in complete math generation. Since only schematic models are required, it saves time in math modelling and handling of bigger size assemblies due to complexity of the models. This extension of VDP process for design evaluation is unique and was developed, implemented successfully. In this paper a Toll logistics and J Smith and Sons car carrier which is developed under author’s responsibility has been used to illustrate our approach of generating design validation via VDP.

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Deficiencies in the design and operation of office buildings can give rise to high social, environmental and economic (triple bottom line) costs. As a result, there are significant pressures and incentives to develop ‘smart building’ technologies that can facilitate improved indoor environment quality (IEQ), and more energy efficient operation of office buildings. IEQ indicators include lighting, ventilation, thermal comfort, indoor air quality and noise. In response to this, the CRC for Construction Innovation commissioned a six-month scoping study (Project no. 2002-043) to examine how different technologies could be used to improve the ‘triple bottom line’ for office buildings. The study was supported by three industry partners, Bovis Lend Lease, Arup, and The Queensland Department of Public Works. The objective of the study was to look at the history, trends, drivers, new technologies and potential application areas related to the operation of healthy and efficient office buildings. The key output from the study was a recommendation for a prototype system for intelligent monitoring and control of an office environment, based on identified market, technical and user requirements and constraints.

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Objectives The objectives of this project were two-fold: • Assess the ease with which current architectural CAD systems supported the use ofparametric descriptions in defining building shape, engineering system performance and cost at the early stages of building design; • Assess the feasibility of implementing a software decision support system that allowed designers to trade-off the characteristics and configuration of various engineering systems to move towards a “global optimum” rather than considering each system in isolation and expecting humans to weigh up all of the costs and benefits. The first stage of the project consisted of using four different CAD systems to define building shells (envelopes) with different usages. These models were then exported into a shared database using the IFC information exchange specifications. The second stage involved the implementation of small computer programs that were able to estimate relevant system parameters based on performance requirements and the constraints imposed by the other systems. These are presented in a unified user interface that extracts the appropriate building shape parameters from the shared database Note that the term parametric in this context refers to the relationships among and between all elements of the building model - not just geometric associations - which will enable the desired coordination.