938 resultados para Backache -- Diagnosis -- Evaluation
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This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2013. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the effect of using additional information such as the discharge summaries and external resources such as medical ontologies on the IR effectiveness. The participants were allowed to submit up to seven runs, one mandatory run using no additional information or external resources, and three each using or not using discharge summaries.
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In recent years, the imperative to communicate organisational impacts to a variety of stakeholders has gained increasing importance within all sectors. Despite growing external demands for evaluation and social impact measurement, there has been limited critically informed analysis about the presumed importance of these activities to organisational success and the practical challenges faced by organisations in undertaking such assessment. In this paper, we present the findings from an action research study of five Australian small to medium social enterprises’ practices and use of evaluation and social impact analysis. Our findings have implications for social enterprise operators, policy makers and social investors regarding when, why and at what level these activities contribute to organisational performance and the fulfilment of mission.
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A new wave energy flow (WEF) map concept was proposed in this work. Based on it, an improved technique incorporating the laser scanning method and Betti’s reciprocal theorem was developed to evaluate the shape and size of damage as well as to realize visualization of wave propagation. In this technique, a simple signal processing algorithm was proposed to construct the WEF map when waves propagate through an inspection region, and multiple lead zirconate titanate (PZT) sensors were employed to improve inspection reliability. Various damages in aluminum and carbon fiber reinforced plastic laminated plates were experimentally and numerically evaluated to validate this technique. The results show that it can effectively evaluate the shape and size of damage from wave field variations around the damage in the WEF map.
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In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.
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Rakaposhi is a synchronous stream cipher, which uses three main components: a non-linear feedback shift register (NLFSR), a dynamic linear feedback shift register (DLFSR) and a non-linear filtering function (NLF). NLFSR consists of 128 bits and is initialised by the secret key K. DLFSR holds 192 bits and is initialised by an initial vector (IV). NLF takes 8-bit inputs and returns a single output bit. The work identifies weaknesses and properties of the cipher. The main observation is that the initialisation procedure has the so-called sliding property. The property can be used to launch distinguishing and key recovery attacks. The distinguisher needs four observations of the related (K,IV) pairs. The key recovery algorithm allows to discover the secret key K after observing 29 pairs of (K,IV). Based on the proposed related-key attack, the number of related (K,IV) pairs is 2(128 + 192)/4 pairs. Further the cipher is studied when the registers enter short cycles. When NLFSR is set to all ones, then the cipher degenerates to a linear feedback shift register with a non-linear filter. Consequently, the initial state (and Secret Key and IV) can be recovered with complexity 263.87. If DLFSR is set to all zeros, then NLF reduces to a low non-linearity filter function. As the result, the cipher is insecure allowing the adversary to distinguish it from a random cipher after 217 observations of keystream bits. There is also the key recovery algorithm that allows to find the secret key with complexity 2 54.
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This report describes the evaluation of the Refugee Antenatal Clinic (Mater Mothers' Hospital, Brisbane) which was established in November 2008
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Fisheries and aquaculture are important for food security, income generation and are critical to long term sustainability of many countries. Freshwater prawns have been harvested in the streams and creeks in Vanuatu, however due to over-exploitation catches have declined in recent years. To satisfy high demand for this product, Vanuatu government intends to establish economically viable small-scale aquaculture industries. The current project showed that wild Macrobrachium lar in Vanuatu constitute a single population for management purposes and that M. rosenbergii grows much faster than M. lar in simple pond grow-out systems, hence is a better species for culture in Vanuatu.
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There has been a greater focus on strengthening evaluation capacity building (ECB) within development organisations in recent years. This can be attributed in part to the growing appreciation of the value of participatory and collaborative forms of evaluation. Evaluation is increasingly seen as an ongoing learning process and an important means of strengthening capacity and improving organisational performance (Horton et al., 2003:7). While there are many benefits of using participatory methodologies in ECB projects, our experiences and a review of the literature in this area highlight the many challenges, issues and contradictions that can affect the success of such ECB efforts. We discuss these issues, drawing on our learnings from the ongoing participatory action research (PAR) project 'Assessing Communication for Social Change’ (AC4SC). This four year project, which began in 2007, is a collaboration between communication and development academics and evaluation specialists from two Australian universities and communication for development practitioners and monitoring and evaluation (M&E) staff in the NGO Equal Access Nepal (EAN). The aim is to develop, implement, and evaluate a participatory methodology for assessing the social change impacts of community radio programs produced by EAN. It builds on previous projects that used ethnographic action research (EAR) methodology (Tacchi et al., 2007).
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"In this chapter the authors present a critique of Participatory Evaluation as worked in development projects, in this case, in Nepal. The article works between established claims that Participatory Evaluation builds capacity at programmatic and organisational levels, and the specific experiences of these claims in the authors’ current work. They highlight the need to address key difficulties such as high turn-over of staff and resulting loss of capacity to engage in Participatory Evaluation, and the difficulty of communication between academic as compared with local practical wisdoms. A key issue is the challenge of addressing the inevitable issues of power inequities that such approaches encounter. While Participatory Evaluation has been around for some time, it has only enjoyed more widespread recognition of its value in comparatively recent times, with its uptake in international development environments. To this extent, the practice is still in its early stages of development, and Jo, June and Michael’s work contributes to strengthening and more comprehensively understanding it. With regard to the meta-theme of this publication, this chapter is an example of how context not only influences the methodology to be used and the praxis of how it is to be used, but contributes to early explication of the core nature of an emerging methodology."
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This paper presents the blast response, damage mechanism and evaluation of residual load capacity of a concrete–steel composite (CSC) column using dynamic computer simulation techniques. This study is an integral part of a comprehensive research program which investigated the vulnerability of structural framing systems to catastrophic and progressive collapse under blast loading and is intended to provide design information on blast mitigation and safety evaluation of load bearing vulnerable columns that are key elements in a building. The performance of the CSC column is compared with that of a reinforced concrete (RC) column with the same dimensions and steel ratio. Results demonstrate the superior performance of the CSC column, compared to the RC column in terms of residual load carrying capacity, and its potential for use as a key element in structural systems. The procedure and results presented herein can be used in the design and safety evaluation of key elements of multi-storey buildings for mitigating the impact of blast loads.
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Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.
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The Foetal Alcohol Syndrome has long gone unrecognised and undiagnosed in Australia. In the last few years of the 21st Century (2010-14) health practitioners are finally seeking ways of diagnosing the effects of alcohol in pregnancy on the next generation. The author offers a power point presentation which gives guidance on making an accurate diagnosis.
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Reframe is changing our approach to the evaluation of courses, units, teaching and student experience at QUT. We are moving away from a single survey tool to a richer, more holistic and customisable approach. This approach will help our academics design and deliver high-quality learning experiences, and review the impact of their teaching practice on student learning. Through it, we will also be able to provide more timely access to specialised support and meet external reporting requirements.
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Reframe is changing our approach to the evaluation of courses, units, teaching and student experience at QUT. We are moving away from a single survey tool to a richer, more holistic and customisable approach. These protocols allows academic staff and administrators access to the ways in which the policy is enacted through process.
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In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.