489 resultados para Real needs
Resumo:
Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.
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Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.
Creation of a new evaluation benchmark for information retrieval targeting patient information needs
Resumo:
Searching for health advice on the web is becoming increasingly common. Because of the great importance of this activity for patients and clinicians and the effect that incorrect information may have on health outcomes, it is critical to present relevant and valuable information to a searcher. Previous evaluation campaigns on health information retrieval (IR) have provided benchmarks that have been widely used to improve health IR and record these improvements. However, in general these benchmarks have targeted the specialised information needs of physicians and other healthcare workers. In this paper, we describe the development of a new collection for evaluation of effectiveness in IR seeking to satisfy the health information needs of patients. Our methodology features a novel way to create statements of patients’ information needs using realistic short queries associated with patient discharge summaries, which provide details of patient disorders. We adopt a scenario where the patient then creates a query to seek information relating to these disorders. Thus, discharge summaries provide us with a means to create contextually driven search statements, since they may include details on the stage of the disease, family history etc. The collection will be used for the first time as part of the ShARe/-CLEF 2013 eHealth Evaluation Lab, which focuses on natural language processing and IR for clinical care.
Resumo:
Ninety-seven percent of children who have special health care needs are cared for by their mothers. These mothers cite that their informal care work can be intrinsically rewarding, however, the role is not without substantial difficulties and consequences. We investigated differences in the health and well-being of mothers whose young children do and do not have special health care needs. Quantitative data are drawn from Growing Up in Australia: The Longitudinal Study of Australian Children. This study employs a matched-case control methodology to compare the experiences of a group of 292 mothers whose children are identified as having long term special health care needs to those mothers whose children are typically developing at two time points; Wave 1 (2004) and Wave 3 (2008). The findings support previous research that mothers of children with special health care needs have poorer general health and mental health than mothers whose children do not have special needs. Mothers of children with special health care needs also perceived life as more difficult. Longitudinally, this study also shows that maternal well-being remains relatively stable during the years when children are transitioning to formal schooling. Implications for policy makers, practitioners and early childhood professionals are discussed.
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The design of society’s major infrastructure systems are generally based on anthropogenic learnings and seldom encapsulate learning from nature. This results from a pervading attitude of superiority of human-designed systems, particularly since the Industrial Revolution. Problems created by such behaviours have previously not been thought to present a serious threat to humanity. However, many built environment professionals are now reconsidering the impact of such systems on the environment and their vulnerability to issues such as climate change. This paper presents an approach to delivering sustainable urban infrastructure that addresses 21st Century needs by emulating natural form, function and process - biomimicry – in infrastructure design. The analysis reveals the context for infrastructure change and the need for sustainable solutions, detailing the current inquiry into biomimicry informed design and highlighting potential applications from literature that demonstrate precedence for nature to inspire the design of urban infrastructure, in particular water and energy systems.
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A survey of nurses working in critical care units in 89 Queensland hospitals was conducted to investigate their perceptions of critical care nurses' educational needs. Two thirds of the 62 respondents were from rural units and one third were from metropolitan units. Most respondents, irrespective of geographic location, wanted critical care education to be located in hospitals and to be accredited as a graduate diploma course. Rural and metropolitan nurses had similar educational needs and many worked for hospitals that were not offering adequate orientation or inservice critical care education. The findings that nursing staff turnover was a problem in metropolitan units and that the rural workforce was more stable have implications for the development of educational programs.
Resumo:
This paper presents the details of experimental studies on the effect of real support conditions on the shear strength of LiteSteel beams (LSB). The LSB has a unique shape of a channel beam with two rectangular hollow flanges, made using a unique manufacturing process. In some applications in the building industry LSBs are used with only one web side plate (WSP) at their supports and are not used with full height web side plates (WSP) at their supports. Past research studies showed that theses real support connections did not provide simply supported conditions. Many studies have been carried out to evaluate the behaviour and design of LSBs with simply supported conditions subject to pure bending and predominant shear actions. To date, however, no investigation has been conducted into the effect of real support conditions on the shear strength of LSBs. Hence detailed experimental studies were undertaken to investigate the shear behaviour and strength of LSBs with real support conditions. A total of 28 experimental tests were conducted as part of the studies. Simply supported test specimens of LSBs with aspect ratios of 1.0 and 1.5 were loaded at mid-span until failure. It was found that the effect of using one WSP on the shear behaviour of LSB is significant and there is about 25% shear capacity reduction due to the lateral movement of the bottom flange at the supports. Shear capacity of LSB was also found to decrease when full height WSPs were not used. Suitable support connections were developed to improve the shear capacity of LSBs based on test results.
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Clinical experience, or experience in the ‘real world’ of practice, is a fundamental component of many health professional courses. It often involves students undertaking practical experience in clinical workplace settings, typically referred to as clinical placements, under the supervision of health professionals. Broadly speaking, the role of clinical supervisors, or teachers, is aimed at assisting students to integrate the theoretical and skills based components of the curriculum within the context of patient/client care (Erstzen et al 2009). Clinical experience also provides students with the opportunity to assimilate the attitudes, values and skills which they require to become appropriately skilled professionals in the environments in which they will eventually practise. However, clinical settings are particularly challenging learning environments for students. Unlike classroom learning, students in the clinical setting frequently find themselves involved in unplanned and often complex activities with patients and other health care providers, being supervised by a variety of clinical staff who have very different methods and styles of teaching, and negotiating bureaucratic or hierarchical structures in busy clinical workplaces where they may only be spending a limited amount of time. Kilminster et al (2007) also draw attention to tensions that may exist between the learning needs of students and the provision of quality care or need to prevent harm to the patient (e.g. Elkind et al 2007). All of these factors complicate the realisation of clinical education goals and underscore the need for effective clinical teaching practices that maximise student learning in clinical environments. This report provides a summary of work that has been achieved in relation to ALTC projects and fellowships associated with clinical teaching, and a review of scholarly publications relevant to this field. The report also makes recommendations based on issues identified and/or where further work is indicated. The projects and fellowships reviewed cover a range of discipline areas including Biology, Paramedic Practice, Clinical Exercise Physiology, Occupational Therapy, Speech Pathology, Physiotherapy, Pharmacy, Nursing and Veterinary Science. The main areas of focus cover issues related to curriculum, particularly in relation to industry expectations of ‘work-ready’ graduates and the implications for theoretical and practical, or clinical preparation; development of competency assessment tools that are nationally applicable across discipline-specific courses; and improvement of clinical learning through strategies targeting the clinical learning environment, building the teaching capacity of clinical supervisors and/or enhancing the clinical learning/teaching process.
Service encounter needs theory : a dyadic, psychosocial approach to understanding service encounters
Resumo:
Interactions between customers and service providers are ubiquitous. Some of these encounters are routine, but many are characterized by conflict and intense emotions. This chapter introduces a new theory, service encounter needs theory (SENT) that aims to elucidate the mechanisms through which service encounter behaviors affect outcomes for customers and employees. Evidence is presented for the preeminence within these encounters of eight psychosocial needs, and propositions are advanced regarding likely antecedents to fulfillment and violation of these needs. Emotional experiences and displays are viewed as important consequences of need fulfillment and violation, as are numerous cognitive, behavioral, and health-related outcomes.
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Orthotopic or intracardiac injection of human breast cancer cell lines into immunocompromised mice allows study of the molecular basis of breast cancer metastasis. We have established a quantitative real-time PCR approach to analyze metastatic spread of human breast cancer cells inoculated into nude mice via these routes. We employed MDA-MB-231 human breast cancer cells genetically tagged with a bacterial β-galactosidase (Lac-Z) retroviral vector, enabling their detection by TaqMan® real-time PCR. PCR detection was linear, specific, more sensitive than conventional PCR, and could be used to directly quantitate metastatic burden in bone and soft organs. Attesting to the sensitivity and specificity of the PCR detection strategy, as few as several hundred metastatic MDA-MB-231 cells were detectable in 100 μm segments of paraffin-embedded lung tissue, and only in samples adjacent to sections that scored positive by histological detection. Moreover, the measured real-time PCR metastatic burden in the bone environment (mouse hind-limbs, n = 48) displayed a high correlation to the degree of osteolytic damage observed by high resolution X-ray analysis (r2 = 0.972). Such a direct linear relationship to tumor burden and bone damage substantiates the so-called 'vicious cycle' hypothesis in which metastatic tumor cells promote the release of factors from the bone which continue to stimulate the tumor cells. The technique provides a useful tool for molecular and cellular analysis of human breast cancer metastasis to bone and soft organs, can easily be extended to other cell/marker/organ systems, and should also find application in preclinical assessment of anti-metastatic modalities.
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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.
Resumo:
Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.
Resumo:
This paper elaborates on the Cybercars-2 Wireless Communication Framework for driverless city vehicles, which is used for Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication. The developed framework improves the safety and efficiency of driverless city vehicles. Furthermore, this paper also elaborates on the vehicle control software architecture. On-road tests of both the communication framework and its application for real-time decision making show that the communication framework is reliable and useful for improving the safe operation of driverless city vehicles.
Resumo:
This work elaborates on the topic of decision making for driverless city vehicles, particularly focusing on the aspects on how to develop a reliable approach which meets the requirements of safe city traffic. Decision making in this context refers to the problem of identifying the most appropriate driving maneuver to be performed in a given traffic situation. The overall decision making problem is decomposed into two consecutive stages. The first stage is safety-crucial, representing the decision regarding the set of feasible driving maneuvers. The second stage represents the decision regarding the most appropriate driving maneuver from the set of feasible ones. The developed decision making approach has been implemented in C++ and initially tested in a 3D simulation environment and, thereafter, in real-world experiments. The real-world experiments also included the integration of wireless communication between vehicles.