760 resultados para POWER FACTORS


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Games and related virtual environments have been a much-hyped area of the entertainment industry. The classic quote is that games are now approaching the size of Hollywood box office sales [1]. Books are now appearing that talk up the influence of games on business [2], and it is one of the key drivers of present hardware development. Some of this 3D technology is now embedded right down at the operating system level via the Windows Presentation Foundations – hit Windows/Tab on your Vista box to find out... In addition to this continued growth in the area of games, there are a number of factors that impact its development in the business community. Firstly, the average age of gamers is approaching the mid thirties. Therefore, a number of people who are in management positions in large enterprises are experienced in using 3D entertainment environments. Secondly, due to the pressure of demand for more computational power in both CPU and Graphical Processing Units (GPUs), your average desktop, any decent laptop, can run a game or virtual environment. In fact, the demonstrations at the end of this paper were developed at the Queensland University of Technology (QUT) on a standard Software Operating Environment, with an Intel Dual Core CPU and basic Intel graphics option. What this means is that the potential exists for the easy uptake of such technology due to 1. a broad range of workers being regularly exposed to 3D virtual environment software via games; 2. present desktop computing power now strong enough to potentially roll out a virtual environment solution across an entire enterprise. We believe such visual simulation environments can have a great impact in the area of business process modeling. Accordingly, in this article we will outline the communication capabilities of such environments, giving fantastic possibilities for business process modeling applications, where enterprises need to create, manage, and improve their business processes, and then communicate their processes to stakeholders, both process and non-process cognizant. The article then concludes with a demonstration of the work we are doing in this area at QUT.

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In a power network, when a propagation energy wave caused by a disturbance hits a weak link, a reflection is appeared and some of energy is transferred across the link. In this work, an analytical descriptive methodology is proposed to study the dynamical stability of a large scale power system. For this purpose, the measured electrical indices (angle, or voltage/frequency) following a fault in different points among the network are used, and the behaviors of the propagated waves through the lines, nodes and buses are studied. This work addresses a new tool for power system stability analysis based on a descriptive study of electrical measurements. The proposed methodology is also useful to detect the contingency condition and synthesis of an effective emergency control scheme.

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The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

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Cyber bullying – or bullying through the use of technology – is a growing phenomenon which is currently most commonly experienced by young people and the consequences manifested in schools. Cyber bullying shares many of the same attributes as face-to-face bullying such as a power imbalance and a sense of helplessness on the part of the target. Not surprisingly, targets of face-to-face bullying are increasingly turning to the law, and it is likely that targets of cyber bullying may also do so in an appropriate case. This article examines the various criminal, civil and vilification laws that may apply to cases of cyber bullying and assesses the likely effectiveness of these laws as a means of redressing that power imbalance between perpetrator and target.

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This chapter looks at issues of non-stationarity in determining when a transient has occurred and when it is possible to fit a linear model to a non-linear response. The first issue is associated with the detection of loss of damping of power system modes. When some control device such as an SVC fails, the operator needs to know whether the damping of key power system oscillation modes has deteriorated significantly. This question is posed here as an alarm detection problem rather than an identification problem to get a fast detection of a change. The second issue concerns when a significant disturbance has occurred and the operator is seeking to characterize the system oscillation. The disturbance initially is large giving a nonlinear response; this then decays and can then be smaller than the noise level ofnormal customer load changes. The difficulty is one of determining when a linear response can be reliably identified between the non-linear phase and the large noise phase of thesignal. The solution proposed in this chapter uses “Time-Frequency” analysis tools to assistthe extraction of the linear model.

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Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

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This paper employs empirical evidence from a survey of Queensland secondary school students to examine their knowledge about their wages and working conditions. It does so within the theoretical lens of the Gagne (or Gagne-Briggs) theory of instruction, which centres on the content of learning and how learning is acquired (Gagne, Briggs & Wager, 1988). While Gagne articulates five categories of learning, our focus here is on two; verbal information or declarative knowledge (facts that people can declare), and procedural knowledge (the rules and procedures for achieving outcomes). We show that student workers know little about the instruments governing their employment, or their workplace entitlements. Of the total sample of year 9 and year 11 students surveyed (n=892), those students who worked, or who had worked in the past year (n=438), were asked to identify whether they were employed under an award, collective agreement or AWA. Eighty three per cent of students did not know which industrial instrument set their wages. We argue that if young workers do not have declarative knowledge of their entitlements, nor basic procedural knowledge about redress, then they are not in a position to deploy Gagne’s ‘cognitive strategies’ that would enable them to take action to ensure their working conditions meet legal minima. We advocate that young workers should be given summary information on their wages and other entitlements on appointment and that such summary information should be readily available on employers’ noticeboards and electronically on company websites, and that the information should include a brief summary of avenues for redressing issues of underpayment or sub-standard conditions.

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We evaluated sustainability of an intervention to reduce women’s cardiovascular risk factors, determined the influence of self-efficacy, and described women’s current health. We used a mixed method approach that utilized forced choice and open-ended questionnaire items about health status, habits, and self-efficacy. Sixty women, average age 61, returned questionnaires. Women in the original intervention group continued health behaviors intended to reduce cardiovascular disease (CVD) at a higher rate than the control group, supporting the feasibility of a targeted intervention built around women’s individual goals. The role of self-efficacy in behavior change is unclear. The original intervention group reported higher self-reported health.

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Objective: To evaluate the importance of contextual and policy factors on nurses’ judgment about medication administration practice.---------- Design: A questionnaire survey of responses to a number of factorial vignettes in June 2004. These vignettes considered a combination of seven contextual and policy factors that were thought to influence nurses’ judgments relating to medication administration.---------- Participants: 185 (67% of eligible) clinical paediatric nursing staff returned completed questionnaires.--------- Setting: A tertiary paediatric hospital in Brisbane, Australia.---------- Results: Double checking the patient, double checking the drug and checking the legality of the prescription were the three strongest predictors of nurses’ actions regarding medication administration.--------- Conclusions: Policy factors and not contextual factors drive nurses’ judgment in response to hypothetical scenarios.

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This paper analyzes the common factor structure of US, German, and Japanese Government bond returns. Unlike previous studies, we formally take into account the presence of country-specific factors when estimating common factors. We show that the classical approach of running a principal component analysis on a multi-country dataset of bond returns captures both local and common influences and therefore tends to pick too many factors. We conclude that US bond returns share only one common factor with German and Japanese bond returns. This single common factor is associated most notably with changes in the level of domestic term structures. We show that accounting for country-specific factors improves the performance of domestic and international hedging strategies.

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Aims and objectives: The purpose of this study is to explore the social construction of cultural issues in palliative care amongst oncology nurses. ---------- Background: Australia is a nation composed of people from different cultural origins with diverse linguistic, spiritual, religious and social backgrounds. The challenge of working with an increasingly culturally diverse population is a common theme expressed by many healthcare professionals from a variety of countries. ---------- Design: Grounded theory was used to investigate the processes by which nurses provide nursing care to cancer patients from diverse cultural backgrounds. ---------- Methods: Semi-structured interviews with seven Australian oncology nurses provided the data for the study; the data was analysed using grounded theory data analysis techniques. ---------- Results: The core category emerging from the study was that of accommodating cultural needs. This paper focuses on describing the series of subcategories that were identified as factors which could influence the process by which nurses would accommodate cultural needs. These factors included nurses' views and understandings of culture and cultural mores, their philosophy of cultural care, nurses' previous experiences with people from other cultures and organisational approaches to culture and cultural care. ---------- Conclusions: This study demonstrated that previous experiences with people from other cultures and organisational approaches to culture and cultural care often influenced nurses' views and understandings of culture and cultural mores and their beliefs, attitudes and behaviours in providing cultural care. ---------- Relevance to clinical practice: It is imperative to appreciate how nurses' experiences with people from other cultures can be recognised and built upon or, if necessary, challenged. Furthermore, nurses' cultural competence and experiences with people from other cultures need to be further investigated in clinical practice.

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While board involvement in strategy is seen as increasingly important, our understanding of how boards fulfil this role is limited. This article draws on indepth qualitative research with directors and senior managers to develop a Strategy as Practice view on how boards "do" strategy. Two different but complementary strategising practices - Procedural Strategising and Interactive Strategising - are identified and elaborated in terms of their underlying micro-activities. The internal boardroom factors that affect the relative emphasis on these strategies practices - the strategic stance of the board, board power and perceive legitimacy of each practice - are also identified and discussed. These findings are then integrated into a typology of board strategising. A key implication of this paper is that boards need to consciously choose the nature and extent of their involvement in strategy.

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Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies.