973 resultados para minimum cost


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ROBERT EVAPORATORS in Australian sugar factories are traditionally constructed with 44.45 mm outside diameter stainless steel tubes of ~2 m length for all stages of evaporation. There are a few vessels with longer tubes (up to 2.8 m) and smaller and larger diameters (38.1 and 50.8 mm). Queensland University of Technology is undertaking a study to investigate the heat transfer performance of tubes of different lengths and diameters for the whole range of process conditions typically encountered in the evaporator set. Incorporation of these results into practical evaporator designs requires an understanding of the cost implications for constructing evaporator vessels with calandrias having tubes of different dimensions. Cost savings are expected for tubes of smaller diameter and longer length in terms of material, labour and installation costs in the factory. However these savings must be considered in terms of the heat transfer area requirements for the evaporation duty, which will likely be a function of the tube dimensions. In this paper a capital cost model is described which provides a relative cost of constructing and installing Robert evaporators of the same heating surface area but with different tube dimensions. Evaporators of 2000, 3000, 4000 and 5000 m2 are investigated. This model will be used in conjunction with the heat transfer efficiency data (when available) to determine the optimum tube dimensions for a new evaporator at a specified evaporation duty. Consideration is also given to other factors such as juice residence time (and implications for sucrose degradation and control) and droplet de-entrainment in evaporators of different tube dimensions.

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Objective To summarise how costs and health benefits will change with the adoption of total laparoscopic hysterectomy compared to total abdominal hysterectomy for the treatment of early stage endometrial cancer. Design Cost-effectiveness modelling using the information from a randomised controlled trial. Participants Two hypothetical modelled cohorts of 1000 individuals undergoing total laparoscopic hysterectomy and total abdominal hysterectomy. Outcome measures Surgery costs; hospital bed days used; total healthcare costs; quality-adjusted life years; and net monetary benefits. Results For 1000 individuals receiving total laparoscopic hysterectomy surgery, the costs were $509 575 higher, 3548 hospital fewer bed days were used and total health services costs were reduced by $3 746 221. There were 39.13 more quality-adjusted life years for a 5 year period following surgery. Conclusions The adoption of total laparoscopic hysterectomy is almost certainly a good decision for health services policy makers. There is 100% probability that it will be cost saving to health services, a 86.8% probability that it will increase health benefits and a 99.5% chance that it returns net monetary benefits greater than zero.

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Aims To provide the best available evidence to determine the impact of nurse practitioner services on cost, quality of care, satisfaction and waiting times in the emergency department for adult patients. Background The delivery of quality care in the emergency department is one of the most important service indicators in health delivery. Increasing service pressures in the emergency department have resulted in the adoption of service innovation models: the most common and rapidly expanding of these is emergency nurse practitioner services. The rapid uptake of emergency nurse practitioner service in Australia has outpaced the capacity to evaluate this service model in terms of outcomes related to safety and quality of patient care. Previous research is now outdated and not commensurate with the changing domain of delivering emergency care with nurse practitioner services. Data A comprehensive search of four electronic databases from 2006-­‐2013 was conducted to identify research evaluating nurse practitioner service impact in the emergency department. English language articles were sought using MEDLINE, CINAHL, Embase and Cochrane and included two previous systematic reviews completed five and seven years ago. Methods A three step approach was used. Following a comprehensive search, two reviewers assessed identified studies against the inclusion criteria. From the original 1013 studies, 14 papers were retained for critical appraisal on methodological quality by two independent reviewers and data extracted using standardised tools. Results Narrative synthesis was conducted to summarise and report the findings as insufficient data was available for meta-­‐analysis of results. This systematic review has shown that emergency nurse practitioner service has a positive impact on quality of care, patient satisfaction and waiting times. There was insufficient evidence to draw conclusions regarding impact on costs. Conclusion Synthesis of the available research attempts to provide an evidence base for emergency nurse practitioner service to guide healthcare leaders, policy makers and clinicians in reforming emergency department service provision. The findings suggest that further quality research is required for comparative measures of clinical and service effectiveness of emergency nurse practitioner service. In the context of increased health service demand and the need to provide timely and effective care to patients, such measures will assist in delivering quality patient care.

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Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates a novel way to identify potential efficiency gains in business operations by observing how they are carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach's feasibility. The findings demonstrate that a genetic algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.

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Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

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The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

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This study elucidated the shadow price of greenhouse gas (GHG) emissions for 1,024 international companies worldwide that were surveyed from 15 industries in 37 major countries. Our results indicate that the shadow price of GHG at the firm level is much higher than indicated in previous studies. The higher shadow price was found in this study as a result of the use of Scope 3 GHG emissions data. The results of this research indicate that a firm would carry a high cost of GHG emissions if Scope 3 GHG emissions were the focus of the discussion of corporate social responsibility. In addition, such shadow prices were determined to differ substantially among countries, among sectors, and within sectors. Although a number of studies have calculated the shadow price of GHG emissions, these studies have employed country-level or industry-level data or a small sample of firm-level data in one country. This new data from a worldwide firm analysis of the shadow price of GHG emissions can play an important role in developing climate policy and promoting sustainable development.

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This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000-2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. © 2012 Elsevier B.V.

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Japan's fishery harvest peaked in the late 1980s. To limit the race for fish, each fisherman could be provided with specific catch limits in the form of individual transferable quotas (ITQs). The market for ITQs would also help remove the most inefficient fishers. In this article we estimate the potential cost reduction associated with catch limits, and find that about 300 billion yen or about 3 billion dollars could be saved through the allocation and trading of individual-specific catch shares.

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This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

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Government contracts for services typically include terms requiring contractors to comply with minimum labour standards laws. Procurement contract clauses specify reporting procedures and sanctions for non-compliance, implying that government contracting agencies will monitor and enforce minimum labour standards within contract performance management. In this article, the case of school cleaners employed under New South Wales government contracts between 2010 and 2011 is the vehicle for exploring the effectiveness of these protective clauses. We find that the inclusion of these protective clauses in procurement contracts is unnecessary in the Australian context, and any expectations that government contracting agencies will monitor and enforce labour standards are misleading. At best, the clauses are rhetoric, and at worst, they are a distraction for parties with enforcement powers.

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Australian households currently pay the second highest “honesty tax” in the world at $290 per household per year, levied by retailers to offset the $AU1.86 billion in losses they incur from customer theft. Theft is only one type of consumer deviance, which can include behaviours that are against the law, an organisation’s policy, or behaviours that violate normally accepted conduct. An individual’s “deviant behaviour” can vary from one person to the next. My research exploring consumer definitions of right and wrong has found a number of things can inform what an individual thinks is “deviant behaviour”, beyond what the law or organisational policy states as right or wrong. Consumers then use their own justifications to excuse their actions...

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The overarching research work is based on two approaches: - Conceptual Analysis, Extraction and Linking - Experimentation with Product Libraries - Conceptual Analysis, Extraction and Linking: This aspect of the research has been achieved through the development of a conceptual framework for facilitating the understanding of the constituting components of BIM, Specifications and Cost Planning under investigation. The framework builds on theories spanning the constituent research themes and was used as a basis for justifying the elected approaches adopted throughout the research work. By means of tags and codes, a system for classifying building specification information has been developed as a differentiator between the chosen research approach and existing classification strategies in industry. Furthermore, syntactic links between extracted classes of specification information and cost planning have been established and will be adopted as a basis for authenticating the impact of specification information within BIM models. - Experimentation with Product Libraries Following the extraction and classification of BIM, Specifications and Cost Planning information, early experimentation on linking specifications to BIM models by means of a raas-based product library have been successful. A comparative analysis between a range of existing product libraries has also been realised. The outcomes have been amply documented in papers, all of which have received positive reviews. Ongoing experiments and analysis with the product library involve integrating the cost planning component for authenticating the completeness, relevance and impact of embedded specification within BIM models.

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