105 resultados para Refrigeration and refrigerating machinery


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The rise of videosharing and self-(re)broadcasting Web services is posing new threats to a television industry already struggling with the impact of filesharing networks. This paper outlines these threats, focussing especially on the DIY re-broadcasting of live sports using Websites such as Justin.tv and a range of streaming media networks built on peer-to-peer filesharing technology.

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Security-critical communications devices must be evaluated to the highest possible standards before they can be deployed. This process includes tracing potential information flow through the device's electronic circuitry, for each of the device's operating modes. Increasingly, however, security functionality is being entrusted to embedded software running on microprocessors within such devices, so new strategies are needed for integrating information flow analyses of embedded program code with hardware analyses. Here we show how standard compiler principles can augment high-integrity security evaluations to allow seamless tracing of information flow through both the hardware and software of embedded systems. This is done by unifying input/output statements in embedded program execution paths with the hardware pins they access, and by associating significant software states with corresponding operating modes of the surrounding electronic circuitry.

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This paper reports on a replication of earlier studies into a possible hierarchy of programming skills. In this study, the students from whom data was collected were at a university that had not provided data for earlier studies. Also, the students were taught the programming language Python, which had not been used in earlier studies. Thus this study serves as a test of whether the findings in the earlier studies were specific to certain institutions, student cohorts, and programming languages. Also, we used a non–parametric approach to the analysis, rather than the linear approach of earlier studies. Our results are consistent with the earlier studies. We found that students who cannot trace code usually cannot explain code, and also that students who tend to perform reasonably well at code writing tasks have also usually acquired the ability to both trace code and explain code.

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This thesis is a documented energy audit and long term study of energy and water reduction in a ghee factory. Global production of ghee exceeds 4 million tonnes annually. The factory in this study refines dairy products by non-traditional centrifugal separation and produces 99.9% pure, canned, crystallised Anhydrous Milk Fat (Ghee). Ghee is traditionally made by batch processing methods. The traditional method is less efficient, than centrifugal separation. An in depth systematic investigation was conducted of each item of major equipment including; ammonia refrigeration, a steam boiler, canning equipment, pumps, heat exchangers and compressed air were all fine-tuned. Continuous monitoring of electrical usage showed that not every initiative worked, others had pay back periods of less than a year. In 1994-95 energy consumption was 6,582GJ and in 2003-04 it was 5,552GJ down 16% for a similar output. A significant reduction in water usage was achieved by reducing the airflow in the refrigeration evaporative condensers to match the refrigeration load. Water usage has fallen 68% from18ML in 1994-95 to 5.78ML in 2003-04. The methods reported in this thesis could be applied to other industries, which have similar equipment, and other ghee manufacturers.

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This report focuses on our examination of extant data which have been sourced with respect to personally and socially risky behaviour associated with males living in regional and remote Australia . The AIHW (2008: PHE 97:89) defines personally risky behaviour, on the one hand, as working, swimming, boating, driving or operating hazardous machinery while intoxicated with alcohol or an illicit drug. Socially risky behaviour, on the other hand, is defined as creating a public disturbance, damaging property, stealing or verbally or physically abusing someone while intoxicated with alcohol or an illicit drug. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

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XML document clustering is essential for many document handling applications such as information storage, retrieval, integration and transformation. An XML clustering algorithm should process both the structural and the content information of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. This paper introduces a novel approach that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The proposed method reduces the high dimensionality of input data by using only the structure-constrained content. The empirical analysis reveals that the proposed method can effectively cluster even very large XML datasets and outperform other existing methods.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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We describe the design and evaluation of a platform for networks of cameras in low-bandwidth, low-power sensor networks. In our work to date we have investigated two different DSP hardware/software platforms for undertaking the tasks of compression and object detection and tracking. We compare the relative merits of each of the hardware and software platforms in terms of both performance and energy consumption. Finally we discuss what we believe are the ongoing research questions for image processing in WSNs.

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Public transportation is an environment with great potential for applying location-based services through mobile devices. This paper provides the underpinning rationale for research that will be looking at how the real-time passenger information system deployed by the Translink Transit Authority across all of South East Queensland in Australia can provide a core platform to improve commuters’ user experiences. This system relies on mobile computing and GPS technology to provide accurate information on transport vehicle locations. The proposal builds on this platform to inform the design and development of innovative social media, mobile computing and geospatial information applications. The core aim is to digitally augment the public transport environment to enhance the user experience of commuters for a more enjoyable journey.

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Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

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Anecdotal evidence from the infrastructure and building sectors highlights issues of drugs and alcohol and its association with safety risk on construction sites. Operating machinery and mobile equipment, proximity to live traffic together with congested sites, electrical equipment and operating at heights conspire to accentuate the potential adverse impact of drugs and alcohol in the workplace. While most Australian jurisdictions have identified this as a critical safety issue, information is limited regarding the prevalence of alcohol and other drugs in the workplace and there is limited evidential guidance regarding how to effectively and efficiently address such an issue. No known study has scientifically evaluated the relationship between the use of drugs and alcohol and safety impacts in construction, and there has been only limited adoption of nationally coordinated strategies, supported by employers and employees to render it socially unacceptable to arrive at a construction workplace with impaired judgement from drugs and alcohol. A nationally consistent collaborative approach across the construction workforce - involving employers and employees; clients; unions; contractors and sub-contractors is required to engender a cultural change in the construction workforce – in a similar manner to the on-going initiative in securing a cultural change to drink-driving in our society where peer intervention and support is encouraged. This study has four key objectives. Firstly, using the standard World Health Organisation AUDIT, a national qualitative and quantitative assessment of the use of drugs and alcohol will be carried out. This will build upon similar studies carried out in the Australian energy and mining sectors. Secondly, the development of an appropriate industry policy will adopt a non-punitive and rehabilitative approach developed in consultation with employers and employees across the infrastructure and building sectors, with the aim it be adopted nationally for adoption at the construction workplace. Thirdly, an industry-specific cultural change management program will be developed through a nationally collaborative approach to reducing the risk of impaired performance on construction sites and increasing workers’ commitment to drugs and alcohol safety. Finally, an implementation plan will be developed from data gathered from both managers and construction employees. Such an approach stands to benefit not only occupational health and safety, through a greater understanding of the safety impacts of alcohol and other drugs at work, but also alcohol and drug use as a wider community health issue. This paper will provide an overview of the background and significance of the study as well as outlining the proposed methodology that will be used to evaluate the safety impacts of alcohol and other drugs in the construction industry.