510 resultados para ELECTRICAL CHARACTERISTICS


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China's National Health and Family Planning Commission announced 3 deaths caused by avian-origin influenza A(H7N9) virus in March, which was the first time that the H7N9 strain has been found in humans [1]. This is of major public health significance and raises urgent questions and global concerns [2, 3]. To explore epidemic characteristics of human infections with H7N9 virus, data on individual cases from 19 February 2013 (onset date of first case) to 14 April 2013 were collected from the China Information System for Disease Control and Prevention, which included information about sex; age; occupation; residential address; and day of symptom onset, diagnosis, and outcome for each case. The definition of an unconfirmed probable H7N9 case is a patient with epidemiologic evidence of contact …

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Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

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Aims Corneal nerve morphology and corneal sensation threshold have recently been explored as potential surrogate markers for the evaluation of diabetic neuropathy. We present the baseline findings of the ‘Longitudinal Assessment of Neuropathy in type 1 Diabetes using novel ophthalmic Markers’(LANDMark) study. Methods The LANDMark study is a 4-year, two-site, natural history study of three participant groups: type 1 diabetes with neuropathy (T1W), type 1 diabetes without neuropathy (T1WO) and control participants without diabetes or neuropathy. All participants undergo a detailed annual assessment of neuropathy including corneal nerve parameters measured using corneal confocal microscopy and corneal sensitivity measured using non-contact corneal aesthesiometry. Results 76 T1W, 166 T1WO and 154 control participants were enrolled into the study. Corneal sensation threshold (mbars) was significantly higher (i.e. sensitivity was lower) in T1W (1.0 ± 1.1) than T1WO (0.7 ± 0.7) and controls (0.6 ± 0.4) (p < 0.001), with no difference between T1WO and controls. Corneal nerve fibre length was lower in T1W (14.0 ± 6.4 mm/mm2) compared to T1WO (19.1 ± 5.8 mm/mm2) and controls (23.2 ± 6.3 mm/mm2) (p < 0.001). Corneal nerve fibre length was lower in T1WO compared to controls. Conclusions The LANDMark baseline findings confirm a reduction in corneal sensitivity only in Type 1 patients with neuropathy. However, corneal nerve fibre length is reduced even in Type 1 patients without neuropathy with an even greater deficit in Type 1 patients with neuropathy.

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MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation in cloud computing. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NP-complete. Thus, in this paper we propose a new heuristic algorithm for the mappers/reducers placement problem in cloud computing and evaluate it by comparing with other several heuristics on solution quality and computation time by solving a set of test problems with various characteristics. The computational results show that our heuristic algorithm is much more efficient than the other heuristics and it can obtain a better solution in a reasonable time. Furthermore, we verify the effectiveness of our heuristic algorithm by comparing the mapper/reducer placement for a benchmark problem generated by our heuristic algorithm with a conventional mapper/reducer placement which puts a fixed number of mapper/reducer on each machine. The comparison results show that the computation using our mapper/reducer placement is much cheaper than the computation using the conventional placement while still satisfying the computation deadline.

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This work aims at developing a planetary rover capable of acting as an assistant astrobiologist: making a preliminary analysis of the collected visual images that will help to make better use of the scientists time by pointing out the most interesting pieces of data. This paper focuses on the problem of detecting and recognising particular types of stromatolites. Inspired by the processes actual astrobiologists go through in the field when identifying stromatolites, the processes we investigate focus on recognising characteristics associated with biogenicity. The extraction of these characteristics is based on the analysis of geometrical structure enhanced by passing the images of stromatolites into an edge-detection filter and its Fourier Transform, revealing typical spatial frequency patterns. The proposed analysis is performed on both simulated images of stromatolite structures and images of real stromatolites taken in the field by astrobiologists.

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Modern health information systems can generate several exabytes of patient data, the so called "Health Big Data", per year. Many health managers and experts believe that with the data, it is possible to easily discover useful knowledge to improve health policies, increase patient safety and eliminate redundancies and unnecessary costs. The objective of this paper is to discuss the characteristics of Health Big Data as well as the challenges and solutions for health Big Data Analytics (BDA) – the process of extracting knowledge from sets of Health Big Data – and to design and evaluate a pipelined framework for use as a guideline/reference in health BDA.

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Largely as a result of mass unemployment problems in many European countries, the dynamics of job creation has in recent years attracted increased interest on the part of academics as well as policy-makers. In connection to this, a large number of studies carried out in various countries have concluded that SMEs play a very large and/or growing role as job creators (Birch, 1979; Baldwin and Picot, 1995; Davidsson, 1995a; Davidsson, Lindmark and Olofsson, 1993; 1994; 1995; 1997a; 1997b; Fumagelli and Mussati, 1993; Kirchhoff and Phillips, 1988; Spilling, 1995; for further reference to studies carried out in a large number of countries see also Aiginger and Tichy, 1991; ENSR, 1994; Loveman and Sengenberger, 1991; OECD, 1987; Storey and Johnson, 1987). While most researchers agree on the importance of SMEs, there is some controversy as regards whether this is mainly a result of many small start-ups and incremental expansions, or if a small minority of high growth SMEs contribute the lion’s share of new employment. This is known as the ‘mice vs. gazelles’ or ‘flyers vs. trundlers’ debate. Storey strongly advocates the position that the small group of high growth SMEs are the ‘real’ job creators (Storey, 1994; Storey & Johnson, 1987), whereas, e.g., the Davidsson et al research in Sweden (cf. above) gives more support for the ‘mice’ hypothesis.

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The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.

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The approach adopted for investigating the relationship between rainfall characteristics and pollutant wash-off process is commonly based on the use of parameters which represent the entire rainfall event. This does not permit the investigation of the influence of rainfall characteristics on different sectors of the wash-off process such as first flush where there is a high pollutant wash-off load at the initial stage of the runoff event. This research study analysed the influence of rainfall characteristics on the pollutant wash-off process using two sets of innovative parameters by partitioning wash-off and rainfall characteristics. It was found that the initial 10% of the wash-off process is closely linked to runoff volume related rainfall parameters including rainfall depth and rainfall duration while the remaining part of the wash-off process is primarily influenced by kinetic energy related rainfall parameters, namely, rainfall intensity. These outcomes prove that different sectors of the wash-off process are influenced by different segments of a rainfall event.

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In this chapter, the role of State Estimation (SE) in smart power grids is presented. The trend of SE error with respect to the increasing of the smart grids implementation investigated. The observability analysis as a prior task of SE is demonstrated and an analytical method to consider the impedance values of the branches is developed and discussed by examples. Since most principles of smart power grids are appropriate to distribution networks, the Distribution SE (DSE)considering load correlation is argued and illustrated by an example. The main features of smart grid SE, which is here named as “Smart Distributed SE” (SDSE), are discussed. Some characteristics of proposed SDES are distributed, hybrid, multi-micro grid and islanding support, Harmonic State Estimation (HSE), observability analysis and restore, error processing, and network parameter estimation. Distribution HSE (DHSE) and meter placement for SDSE are also presented.

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Reforms to the basic education system in China have reflected an increasing awareness of and openness to new ideas from the global education sphere. Many of the concepts involved in the development and implementation of these reforms, including adopting holistic perspectives of student development; decentralising school governance to facilitate local decision-making to address local needs; and, an increased focus on practical, lifelong learning for all involved in schools, have been promoted in research and policies throughout the world. While working within this global context, the system of schooling in China has retained a unique character that is quite different from education in the West. Drawing on an international project on school transformation, this chapter aims to examine how five secondary schools in Chongqing, a municipality in Southwestern China, have harnessed and aligned their resources to provide effective school governance following the curriculum reforms. Furthermore, the chapter will examine the similarities and differences between the organisational structures and cultures of these schools in China and successful schools in Australia, England, Finland, Wales and the United States.

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In many ways, China’s education system is quite different from systems of education in the West. Rich descriptions of school transformation, however, have revealed that the factors that fuelled transformation in schools in China are also evident in schools in Australia, England, Finland, Wales and the United States. This paper draws on an international project that examined how secondary schools from six countries achieved success by developing and drawing on their resources, referred to as four forms of capital: financial, intellectual, social and spiritual. It describes how five secondary schools in Chongqing, Western China, viewed each form of capital and how the four forms of capital were strengthened and aligned through outstanding governance to support the success of all students. The case is made that, although some aspects of the forms of capital found in schools in China may be viewed differently, the approaches adopted by these schools share a number of common elements with approaches to school transformation identified in Western schools. It is argued that these common elements from a range of international settings constitute a rich evidence base for understanding school transformation and for new insights in governance and leadership.

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This thesis is the first comprehensive study of important parameters relating to aerosols' impact on climate and human health, namely spatial variation, particle size distribution and new particle formation. We determined the importance of spatial variation of particle number concentration in microscale environments, developed a method for particle size parameterisation and provided knowledge about the chemistry of new particle formation. This is a significant contribution to our understanding of processes behind the transformation and dynamics of urban aerosols. This PhD project included extensive measurements of air quality parameters using state of the art instrumentation at each of the 25 sites within the Brisbane metropolitan area and advanced statistical analysis.

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For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

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A largely overlooked aspect of creative design practices is how physical space in design studios plays a role in supporting designers' everyday work. In particular, studio surfaces such as designers' desks, office walls, notice boards, clipboards and drawing boards are full of informative, inspirational and creative artefacts such as, sketches, drawings, posters, story-boards and Post-it notes. Studio surfaces are not just the carriers of information but importantly they are sites of methodic design practices, i.e. they indicate, to an extent, how design is being carried out. This article describes the results of an ethnographic study on the use of workplace surfaces in design studios, from two academic design departments. Using the field study results, the article introduces an idea of ‘artful surfaces’. Artful surfaces emphasise how artfully designers integrate these surfaces into their everyday work and how the organisation of these surfaces comes about helping designers in accomplishing their creative and innovative design practices. Using examples from the field study, the article shows that artful surfaces have both functional and inspirational characteristics. From the field study, three types of artful surfaces are identified: personal; shared; and project-specific. The article suggests that a greater insight into how these artful surfaces are created and used could lead to better design of novel display technologies to support designers' everyday work.