999 resultados para Electronic conductor


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Information and communications technologies are a significant component of the healthcare domain and electronic health records play a major role within it. As a result, it is important that they are accepted en masse by healthcare professionals. How healthcare professionals perceive the usefulness of electronic health records and their attitudes towards them have been shown to have significant effects on their overall acceptance. This paper investigates the role of perceived usefulness and attitude on the intention to use electronic health records by future healthcare professionals using polynomial regression with response surface analysis. Results show that the relationship is more complex than predicted in prior research. The paper concludes that the predicting properties of the above determinants must be further investigated to clearly understand their role in predicting the intention to use electronic health records and in designing systems that are better adopted by healthcare professionals of the future.

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Accuracy of dose delivery in external beam radiotherapy is usually verified with electronic portal imaging (EPI) in which the treatment beam is used to check the positioning of the patient. However the resulting megavoltage x-ray images suffer from poor quality. The image quality can be improved by developing a special operating mode in the linear accelerator. The existing treatment beam is modified such that it produces enough low-energy photons for imaging. In this work the problem of optimizing the beam/detector combination to achieve optimal electronic portal image quality is addressed. The linac used for this study was modified to produce two experimental photon beams. These beams, named Al6 and Al10, were non-flat and were produced by 4MeV electrons hitting aluminum targets, 6 and 10mm thick respectively. The images produced by a conventional EPI system (6MV treatment beam and camera-based EPID with a Cu plate & Gd2O2S screen ) were compared with the images produced by the experimental beams and various screens with the same camera). The contrast of 0.8cm bone equivalent material in 5 cm water increased from 1.5% for the conventional system to 11% for the combination of Al6 beam with a 200mg/cm2 Gd2O2S screen. The signal-to-noise ratio calculated for 1cGy flood field images increased by about a factor of two for the same EPI systems. The spatial resolution of the two imaging systems was comparable. This work demonstrates that significant improvements in portal image contrast can be obtained by simultaneous optimization of the linac spectrum and EPI detector.

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We have taken a new method of calibrating portal images of IMRT beams and used this to measure patient set-up accuracy and delivery errors, such as leaf errors and segment intensity errors during treatment. A calibration technique was used to remove the intensity modulations from the images leaving equivalent open field images that show patient anatomy that can be used for verification of the patient position. The images of the treatment beam can also be used to verify the delivery of the beam in terms of multileaf collimator leaf position and dosimetric errors. A series of controlled experiments delivering an IMRT anterior beam to the head and neck of a humanoid phantom were undertaken. A 2mm translation in the position of the phantom could be detected. With intentional introduction of delivery errors into the beam this method allowed us to detect leaf positioning errors of 2mm and variation in monitor units of 1%. The method was then applied to the case of a patient who received IMRT treatment to the larynx and cervical nodes. The anterior IMRT beam was imaged during four fractions and the images calibrated and investigated for the characteristic signs of patient position error and delivery error that were shown in the control experiments. No significant errors were seen. The method of imaging the IMRT beam and calibrating the images to remove the intensity modulations can be a useful tool in verifying both the patient position and the delivery of the beam.

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Background Knowledge of current trends in nurse-administered procedural sedation and analgesia (PSA) in the cardiac catheterisation laboratory (CCL) may provide important insights into how to improve safety and effectiveness of this practice. Objective To characterise current practice as well as education and competency standards regarding nurse-administered PSA in Australian and New Zealand CCLs. Design A quantitative, cross-sectional, descriptive survey design was used. Methods Data were collected using a web-based questionnaire on practice, educational standards and protocols related to nurse-administered PSA. Descriptive statistics were used to analyse data. Results A sample of 62 nurses, each from a different CCL, completed a questionnaire that focused on PSA practice. Over half of the estimated total number of CCLs in Australia and New Zealand was represented. Nurse-administered PSA was used in 94% (n = 58) of respondents CCLs. All respondents indicated that benzodiazepines, opioids or a combination of both is used for PSA (n = 58). One respondent indicated that propofol was also used. 20% (n = 12) indicated that deep sedation is purposefully induced for defibrillation threshold testing and cardioversion without a second medical practitioner present. Sedation monitoring practices vary considerably between institutions. 31% (n = 18) indicated that comprehensive education about PSA is provided. 45% (n = 26) indicated that nurses who administer PSA should undergo competency assessment. Conclusion By characterising nurse-administered PSA in Australian and New Zealand CCLs, a baseline for future studies has been established. Areas of particular importance to improve include protocols for patient monitoring and comprehensive PSA education for CCL nurses in Australia and New Zealand.

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Class E Resonant Inverters are theoretically capable of delivering any power to a load and achieve 100% efficiency at any frequency of operation. In practice efficiency in the “high 90's” can be achieved into megahertz frequencies regardless of inverter output powers. The topology also allows the manipulation of output power through sub-optimal operation, with a negligible efficiency penalty. The 24W inverter discussed in this paper was specifically designed to harness the benefits, and discuss the shortcomings, of the Class E topology for use in the growing market for portable, battery powered lighting. It exhibits a peak recorded power efficiently of over 98%, and a conservatively measured efficiency of 95% across a range of dimming settings.

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Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

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Information privacy is a critical success/failure factor in information technology supported healthcare (eHealth). eHealth systems utilise electronic health records (EHR) as the main source of information, thus, implementing appropriate privacy preserving methods for EHRs is vital for the proliferation of eHealth. Whilst information privacy may be a fundamental requirement for eHealth consumers, healthcare professionals demand non-restricted access to patient information for improved healthcare delivery, thus, creating an environment where stakeholder requirements are contradictory. Therefore, there is a need to achieve an appropriate balance of requirements in order to build successful eHealth systems. Towards achieving this balance, a new genre of eHealth systems called Accountable-eHealth (AeH) systems has been proposed. In this paper, an access control model for EHRs is presented that can be utilised by AeH systems to create information usage policies that fulfil both stakeholders’ requirements. These policies are used to accomplish the aforementioned balance of requirements creating a satisfactory eHealth environment for all stakeholders. The access control model is validated using a Web based prototype as a proof of concept.

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Non-periodic structural variation has been found in the high Tc cuprates, YBa2Cu3O7-x and Hg0.67Pb0.33Ba2Ca2Cu 3O8+δ, by image analysis of high resolution transmission electron microscope (HRTEM) images. We use two methods for analysis of the HRTEM images. The first method is a means for measuring the bending of lattice fringes at twin planes. The second method is a low-pass filter technique which enhances information contained by diffuse-scattered electrons and reveals what appears to be an interference effect between domains of differing lattice parameter in the top and bottom of the thin foil. We believe that these methods of image analysis could be usefully applied to the many thousands of HRTEM images that have been collected by other workers in the high temperature superconductor field. This work provides direct structural evidence for phase separation in high Tc cuprates, and gives support to recent stripes models that have been proposed to explain various angle resolved photoelectron spectroscopy and nuclear magnetic resonance data. We believe that the structural variation is a response to an opening of an electronic solubility gap where holes are not uniformly distributed in the material but are confined to metallic stripes. Optimum doping may occur as a consequence of the diffuse boundaries between stripes which arise from spinodal decomposition. Theoretical ideas about the high Tc cuprates which treat the cuprates as homogeneous may need to be modified in order to take account of this type of structural variation.

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Voltammetric techniques have been introduced to monitor the formation of gold nanoparticles produced via the reaction of the amino acid glycyl-L-tyrosine with Au(III) (bromoaurate) in 0.05 M KOH conditions. The alkaline conditions facilitate amino acid binding to Au(III), inhibit the rate of reduction to Au(0), and provide an excellent supporting electrolyte for voltammetric studies. Data obtained revealed that a range of time-dependent gold solution species are involved in gold nanoparticle formation and that the order in which reagents are mixed is critical to the outcome. Concomitantly with voltammetric measurements, the properties of gold nanoparticles formed are probed by examination of electronic spectra in order to understand how the solution environment present during nanoparticle growth affects the final distribution of the nanoparticles. Images obtained by the ex situ transmission electron microscopy (TEM) technique enable the physical properties of the nanoparticles isolated in the solid state to be assessed. Use of this combination of in situ and ex situ techniques provides a versatile framework for elucidating the details of nanoparticle formation.

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Gambling activities and the revenues derived have been seen as a way to increase economic development in deprived areas. There are also, however, concerns about the effects of gambling in general and electronic gaming machines (EGMs) in particular, on the resources available to the localities in which they are situated. This paper focuses on the factors that determine the extent and spending of community benefit-related EGM-generated resources within Victoria, Australia, focusing in particular on the relationships between EGM activity and socio-economic and social capital indicators, and how this relates to the community benefit resources generated by gaming.

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We present an approach to automatically de-identify health records. In our approach, personal health information is identified using a Conditional Random Fields machine learning classifier, a large set of linguistic and lexical features, and pattern matching techniques. Identified personal information is then removed from the reports. The de-identification of personal health information is fundamental for the sharing and secondary use of electronic health records, for example for data mining and disease monitoring. The effectiveness of our approach is first evaluated on the 2007 i2b2 Shared Task dataset, a widely adopted dataset for evaluating de-identification techniques. Subsequently, we investigate the robustness of the approach to limited training data; we study its effectiveness on different type and quality of data by evaluating the approach on scanned pathology reports from an Australian institution. This data contains optical character recognition errors, as well as linguistic conventions that differ from those contained in the i2b2 dataset, for example different date formats. The findings suggest that our approach compares to the best approach from the 2007 i2b2 Shared Task; in addition, the approach is found to be robust to variations of training size, data type and quality in presence of sufficient training data.