511 resultados para Epoxy resin system


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One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.

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Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

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This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

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Background: Traditional causal modeling of health interventions tends to be linear in nature and lacks multidisciplinarity. Consequently, strategies for exercise prescription in health maintenance are typically group based and focused on the role of a common optimal health status template toward which all individuals should aspire. ----- ----- Materials and methods: In this paper, we discuss inherent weaknesses of traditional methods and introduce an approach exercise training based on neurobiological system variability. The significance of neurobiological system variability in differential learning and training was highlighted.----- ----- Results: Our theoretical analysis revealed differential training as a method by which neurobiological system variability could be harnessed to facilitate health benefits of exercise training. It was observed that this approach emphasizes the importance of using individualized programs in rehabilitation and exercise, rather than group-based strategies to exercise prescription.----- ----- Conclusion: Research is needed on potential benefits of differential training as an approach to physical rehabilitation and exercise prescription that could counteract psychological and physical effects of disease and illness in subelite populations. For example, enhancing the complexity and variability of movement patterns in exercise prescription programs might alleviate effects of depression in nonathletic populations and physical effects of repetitive strain injuries experienced by athletes in elite and developing sport programs.

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Three different methods of inclusion of current measurements by phasor measurement units (PMUs) in a power sysetm state estimator is investigated. A comprehensive formulation of the hybrid state estimator incorporating conventional, as well as PMU measurements, is presented for each of the three methods. The behaviour of the elements because of the current measurements in the measurement Jacobian matrix is examined for any possible ill-conditioning of the state estimator gain matrix. The performance of the state estimators are compared in terms of the convergence properties and the varian in the estimated states. The IEEE 14-bus and IEEE 300-bus systems are used as test beds for the study.

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Background: The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories. Methods: We describe the methods and rationale for assigning detailed MET estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5,323 (2,917 males and 2,406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day. Results: Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared to using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations. Conclusions: Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.

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Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

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This report examines the involvement of manufacturers in value-adding through service-enhancement of product offerings. This focus has been prompted by:  emphasis in the knowledge-economy literature on the increasing role played by services in economic growth; and  recent analysis which suggests that the most dynamic sector of many economies is an integrated manufacturing-services sector (see Part One of this report). The report initially describes the emergence of an integrated manufacturing-services sector in the context of increasingly knowledge-based economic systems. Part Two reports on the results of a survey of manufacturers in the building and construction product system, investigating their involvement in service provision. Parts Three and Four present two case studies of exemplary manufacturers involved in adding value to their manufacturing operations through services offered on building and construction projects. The report examines manufacturers of materials, products, equipment and machinery used on building and construction projects. The two case study sections of the report, in part, focus on a major project undertaken by each of the manufacturers. This project element of activity is focussed on (as opposed to wholesale or retail supply), because this area of activity involves a broader array of service-enhancement mechanisms and more complex bundling of products and services.

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This report examines the conditions surrounding the emergence and growth of innovative new firms in the building and construction product system. The focus on innovative new firms was prompted by diverse literatures which highlight the pivotal roles of innovation and new business activity in driving economic growth. 9 The literature concludes that the founders of new firms are likely to be innovative and that new firms are likely to promote industry innovation and efficiency. New businesses have also been found to have positive employment impacts and to grow faster than established firms.

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This Preliminary Report has been prepared by researchers at The Australian Expert Group in Industry Studies (AEGIS) for the Commonwealth Department of Industry, Science and Resources. It is intended to provide a preliminary 'product system map' of the building and construction industries which defines the system, identifies the major segments, describes key industry players and institutions and provides the basis for exploring relationships, innovation and information flows within the industries. This Preliminary Report is the first of a series of five which will explore the building and construction product system in some depth. This first report does not present original research, although it does include some new interview data and analysis of a variety of written sources. This report is rather a reformulation of existing statistical and analytical material from a product system-based perspective. It is intended to provide the basis for subsequent studies by putting what is already known into an alternative framework and allowing us to see it through a new lens.

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This paper provides a framework for analysing the role of Australia’s research system in promoting national economic development. The paper is in two parts. Part One focuses on knowledge diffusion and technological development and emphasises the systemic nature of innovation processes within the emerging context of ‘learning economies’. The key understandings relevant to a nation’s research system are drawn out from contemporary developments in the international literature on ‘learning economies’. Some of the implications for Australia are discussed. The aim is to provide readers with some indications of what to look for in considering options for the future of Australia’s research system. More detailed information on relevant aspects of Australia’s industrial and trade structure, the extent of the R&D effort in industry and on issues such as management capability can be obtained from (Marceau et al 1997). In the second part, broad elements of the Australian research system are reviewed in the light of findings from the literature. The central role of universities in the innovation and research systems is described. Actions that can be taken by both universities and governments are suggested, particularly regarding the need to build and maintain efficient information flows at local, national and international levels. The paper briefly points to the nature of a research system capable of contributing effectively to the wealth of the nation and indicates some possible directions for enabling Australia to meet the demands of, and profit from, a knowledge-based economy.

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During 1999 the Department of Industry, Science and Resources (ISR) published 4 research reports it had commissioned from the Australian Expert Group in Industry Studies (AEGIS), a research centre of the University of Western Sydney, Macarthur. ISR will shortly publish the fifth and final report in this series. The five reports were commissioned by the Department, as part of the Building and Construction Action Agenda process, to investigate the dynamics and performance of the sector, particularly in relation its innovative capacity. Professor Jane Marceau, PVCR at the University of Western Sydney and Director of AEGIS, led the research team. Dr Karen Manley was the researcher and joint author on three of the five reports. This paper outlines the approach and key findings of each of the five reports. The reports examined 5 key elements of the ‘building and construction product system’. The term ‘product system’ reflects the very broad range of industries and players we consider to contribute to the performance of the building and construction industries. The term ‘product system’ also highlights our focus on the systemic qualities of the building and construction industries. We were most interested in the inter-relationships between key segments and players and how these impacted on the innovation potential of the product system. The ‘building and construction product system’ is hereafter referred to as ‘the industry’ for ease of presentation. All the reports are based, at least in part, on an interviewing or survey research phase which involved gathering data from public and private sector players nationally. The first report ‘maps’ the industry to identify and describe its key elements and the inter-relationships between them. The second report focuses specifically on the linkages between public-sector research organisations and firms in the industry. The third report examines the conditions surrounding the emergence of new businesses in the industry. The fourth report examines how manufacturing businesses are responding to customer demands for ‘total solutions’ to their building and construction needs, by providing various services to clients. The fifth report investigates the capacity of the industry to encourage and undertake energy efficient building design and construction.

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Nonprofit organizations are not exempt from the imperatives of employee attraction, retention, and motivation. As competition for staff, donors, and funding increases, the need to manage employee performance will continue to be a critical human resource management issue. This article outlines a study of the introduction of a performance management system in an Australian nonprofit organization and analyzes its design and implementation. It explores how performance management can be introduced and used effectively within a nonprofit environment to benefit staff and the organization. However, the use of performance management is not without its challenges, and the research also identified initial employee resistance and a resulting initial spike in labor turnover. However, findings indicate that if nonprofit organizations are willing to undertake consultation with staff and ensure that the organization's specific context, values, and mission are reflected in the performance management system, it can be a useful tool for managers and a direct benefit to employees.

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Smart matrices are required in bone tissueengineered grafts that provide an optimal environment for cells and retain osteo-inductive factors for sustained biological activity. We hypothesized that a slow-degrading heparin-incorporated hyaluronan (HA) hydrogel can preserve BMP-2; while an arterio–venous (A–V) loop can support axial vascularization to provide nutrition for a bioartificial bone graft. HA was evaluated for osteoblast growth and BMP-2 release. Porous PLDLLA–TCP–PCL scaffolds were produced by rapid prototyping technology and applied in vivo along with HA-hydrogel, loaded with either primary osteoblasts or BMP-2. A microsurgically created A–V loop was placed around the scaffold, encased in an isolation chamber in Lewis rats. HA-hydrogel supported growth of osteoblasts over 8 weeks and allowed sustained release of BMP-2 over 35 days. The A–V loop provided an angiogenic stimulus with the formation of vascularized tissue in the scaffolds. Bone-specific genes were detected by real time RT-PCR after 8 weeks. However, no significant amount of bone was observed histologically. The heterotopic isolation chamber in combination with absent biomechanical stimulation might explain the insufficient bone formation despite adequate expression of bone-related genes. Optimization of the interplay of osteogenic cells and osteo-inductive factors might eventually generate sufficient amounts of axially vascularized bone grafts for reconstructive surgery.

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Item folksonomy or tag information is popularly available on the web now. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. In this paper, we propose to combine item taxonomy and folksonomy to reduce the noise of tags and make personalized item recommendations. The experiments conducted on the dataset collected from Amazon.com demonstrated the effectiveness of the proposed approaches. The results suggested that the recommendation accuracy can be further improved if we consider the viewpoints and the vocabularies of both experts and users.