850 resultados para Broadly-based assessment


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Damage assessment (damage detection, localization and quantification) in structures and appropriate retrofitting will enable the safe and efficient function of the structures. In this context, many Vibration Based Damage Identification Techniques (VBDIT) have emerged with potential for accurate damage assessment. VBDITs have achieved significant research interest in recent years, mainly due to their non-destructive nature and ability to assess inaccessible and invisible damage locations. Damage Index (DI) methods are also vibration based, but they are not based on the structural model. DI methods are fast and inexpensive compared to the model-based methods and have the ability to automate the damage detection process. DI method analyses the change in vibration response of the structure between two states so that the damage can be identified. Extensive research has been carried out to apply the DI method to assess damage in steel structures. Comparatively, there has been very little research interest in the use of DI methods to assess damage in Reinforced Concrete (RC) structures due to the complexity of simulating the predominant damage type, the flexural crack. Flexural cracks in RC beams distribute non- linearly and propagate along all directions. Secondary cracks extend more rapidly along the longitudinal and transverse directions of a RC structure than propagation of existing cracks in the depth direction due to stress distribution caused by the tensile reinforcement. Simplified damage simulation techniques (such as reductions in the modulus or section depth or use of rotational spring elements) that have been extensively used with research on steel structures, cannot be applied to simulate flexural cracks in RC elements. This highlights a big gap in knowledge and as a consequence VBDITs have not been successfully applied to damage assessment in RC structures. This research will address the above gap in knowledge and will develop and apply a modal strain energy based DI method to assess damage in RC flexural members. Firstly, this research evaluated different damage simulation techniques and recommended an appropriate technique to simulate the post cracking behaviour of RC structures. The ABAQUS finite element package was used throughout the study with properly validated material models. The damaged plasticity model was recommended as the method which can correctly simulate the post cracking behaviour of RC structures and was used in the rest of this study. Four different forms of Modal Strain Energy based Damage Indices (MSEDIs) were proposed to improve the damage assessment capability by minimising the numbers and intensities of false alarms. The developed MSEDIs were then used to automate the damage detection process by incorporating programmable algorithms. The developed algorithms have the ability to identify common issues associated with the vibration properties such as mode shifting and phase change. To minimise the effect of noise on the DI calculation process, this research proposed a sequential order of curve fitting technique. Finally, a statistical based damage assessment scheme was proposed to enhance the reliability of the damage assessment results. The proposed techniques were applied to locate damage in RC beams and slabs on girder bridge model to demonstrate their accuracy and efficiency. The outcomes of this research will make a significant contribution to the technical knowledge of VBDIT and will enhance the accuracy of damage assessment in RC structures. The application of the research findings to RC flexural members will enable their safe and efficient performance.

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Police in-vehicle systems include a visual output mobile data terminal (MDT) with manual input via touch screen and keyboard. This study investigated the potential for voice-based input and output modalities for reducing subjective workload of police officers while driving. Nineteen experienced drivers of police vehicles (one female) from New South Wales (NSW) Police completed four simulated urban drives. Three drives included a concurrent secondary task: an imitation licence number search using an emulated MDT. Three different interface output-input modalities were examined: Visual-Manual, Visual-Voice, and Audio-Voice. Following each drive, participants rated their subjective workload using the NASA - Raw Task Load Index and completed questions on acceptability. A questionnaire on interface preferences was completed by participants at the end of their session. Engaging in secondary tasks while driving significantly increased subjective workload. The Visual-Manual interface resulted in higher time demand than either of the voice-based interfaces and greater physical demand than the Audio-Voice interface. The Visual-Voice and Audio-Voice interfaces were rated easier to use and more useful than the Visual-Manual interface, although not significantly different from each other. Findings largely echoed those deriving from the analysis of the objective driving performance data. It is acknowledged that under standard procedures, officers should not drive while performing tasks concurrently with certain invehicle policing systems; however, in practice this sometimes occurs. Taking action now to develop voice-based technology for police in-vehicle systems has potential to realise visions for potentially safer and more efficient vehicle-based police work.

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Purpose Videokeratoscopy images can be used for the non-invasive assessment of the tear film. In this work the applicability of an image processing technique, textural-analysis, for the assessment of the tear film in Placido disc images has been investigated. Methods In the presence of tear film thinning/break-up, the reflected pattern from the videokeratoscope is disturbed in the region of tear film disruption. Thus, the Placido pattern carries information about the stability of the underlying tear film. By characterizing the pattern regularity, the tear film quality can be inferred. In this paper, a textural features approach is used to process the Placido images. This method provides a set of texture features from which an estimate of the tear film quality can be obtained. The method is tested for the detection of dry eye in a retrospective dataset from 34 subjects (22-normal and 12-dry eye), with measurements taken under suppressed blinking conditions. Results To assess the capability of each texture-feature to discriminate dry eye from normal subjects, the receiver operating curve (ROC) was calculated and the area under the curve (AUC), specificity and sensitivity extracted. For the different features examined, the AUC value ranged from 0.77 to 0.82, while the sensitivity typically showed values above 0.9 and the specificity showed values around 0.6. Overall, the estimated ROCs indicate that the proposed technique provides good discrimination performance. Conclusions Texture analysis of videokeratoscopy images is applicable to study tear film anomalies in dry eye subjects. The proposed technique appears to have demonstrated its clinical relevance and utility.

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Carrying capacity assessments model a population’s potential self-sufficiency. A crucial first step in the development of such modelling is to examine the basic resource-based parameters defining the population’s production and consumption habits. These parameters include basic human needs such as food, water, shelter and energy together with climatic, environmental and behavioural characteristics. Each of these parameters imparts land-usage requirements in different ways and varied degrees so their incorporation into carrying capacity modelling also differs. Given that the availability and values of production parameters may differ between locations, no two carrying capacity models are likely to be exactly alike. However, the essential parameters themselves can remain consistent so one example, the Carrying Capacity Dashboard, is offered as a case study to highlight one way in which these parameters are utilised. While examples exist of findings made from carrying capacity assessment modelling, to date, guidelines for replication of such studies in other regions and scales have largely been overlooked. This paper addresses such shortcomings by describing a process for the inclusion and calibration of the most important resource-based parameters in a way that could be repeated elsewhere.

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Background: Charcot Neuro-Arthropathy (CN) is one of the more devastating complications of diabetes. To the best of the authors' knowledge, it appears that no clinical tools based on a systematic review of existing literature have been developed to manage acute CN. Thus, the aim of this paper was to systematically review existing literature and develop an evidence-based clinical pathway for the assessment, diagnosis and management of acute CN in patients with diabetes. Methods: Electronic databases (Medline, PubMed, CINAHL, Embase and Cochrane Library), reference lists, and relevant key websites were systematically searched for literature discussing the assessment, diagnosis and/or management of acute CN published between 2002-2012. At least two independent investigators then quality rated and graded the evidence of each included paper. Consistent recommendations emanating from the included papers were then fashioned in a clinical pathway. Results: The systematic search identified 267 manuscripts, of which 117 (44%) met the inclusion criteria for this study. Most manuscripts discussing the assessment, diagnosis and/or management of acute CN constituted level IV (case series) or EO (expert opinion) evidence. The included literature was used to develop an evidence-based clinical pathway for the assessment, investigations, diagnosis and management of acute CN. Conclusions: This research has assisted in developing a comprehensive, evidence-based clinical pathway to promote consistent and optimal practice in the assessment, diagnosis and management of acute CN. The pathway aims to support health professionals in making early diagnosis and providing appropriate immediate management of acute CN, ultimately reducing its associated complications such as amputations and hospitalisations.

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Nontechnical skills relating to team functioning are vital to the effective delivery of patient care and safety. In this study, we develop a reliable behavioral marker tool for assessing nontechnical skills that are critical to the success of ward-based multidisciplinary healthcare teams. The Team Functioning Assessment Tool (TFAT) was developed and refined using a literature review, focus groups, card-sorting exercise, field observations, and final questionnaire evaluation and refinement process. Results demonstrated that Clinical Planning, Executive Tasks, and Team Relations are important facets of effective multidisciplinary healthcare team functioning. The TFAT was also shown to yield acceptable inter-rater agreement.

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The team functioning assessment tool (TFAT) has been shown to be a reliable behavioral marker tool for assessing nontechnical skills that are critical to the success of ward-based healthcare teams. This paper aims to refine and shorten the length of the TFAT to improve usability, and establish its reliability and construct validity. Psychometric testing based on 110 multidisciplinary healthcare teams demonstrated that the TFAT is a reliable and valid tool for measuring team members’ nontechnical skills in regards to Clinical Planning, Executive Tasks, and Team Functioning. Providing support for concurrent validity, high TFAT ratings were predicted by low levels of organizational constraints and high levels of group potency. There was also partial support for the negative relationships between time pressure, leadership ambiguity, and TFAT ratings. The paper provides a discussion on the applicability of the tool for assessing multidisciplinary healthcare team functioning in the context of improving team effectiveness and patient safety for ward-based hospital teams.

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Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

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Classical ballet requires dancers to exercise significant muscle control and strength both while stationary and when moving. Following the Royal Academy of Dance (RAD) syllabus, 8 male and 27 female dancers (aged 20.2 + 1.9 yr) in a fulltime university undergraduate dance training program were asked to stand in first position for 10 seconds and then perform 10 repeats of a demi-plié exercise to a counted rhythm. Accelerometer records from the wrist, sacrum, knee and ankle were compared with the numerical scores from a professional dance instructor. The sacrum mounted sensor detected lateral tilts of the torso in dances with lower scores (Spearman’s rank correlation coefficient r = -0.64, p < 0.005). The RMS acceleration amplitude of wrist mounted sensor was linearly correlated to the movement scores (Spearman’s rank correlation coefficient r = 0.63, p < 0.005). The application of sacrum and wrist mounted sensors for biofeedback during dance training is a realistic, low cost option.

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Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

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Pain is common in residential aged care facilities (RACFs). In 2005, the Australian Pain Society developed 27 recommendations for good practice in the identification, assessment, and management of pain in these settings. This study aimed to address implementation of the standards and evaluate outcomes. Five facilities in Australia participated in a comprehensive evaluation of RACF pain practice and outcomes. Pre-existing pain management practices were compared with the 27 recommendations, before an evidence-based pain management program was introduced that included training and education for staff and revised in-house pain-management procedures. Post-implementation audits evaluated the program's success. Aged care staff teams also were assessed on their reports of self-efficacy in pain management. The results show that before the implementation program, the RACFs demonstrated full compliance on 6 to 12 standards. By the project's completion, RACFs demonstrated full compliance with 10 to 23 standards and major improvements toward compliance in the remaining standards. After implementation, the staff also reported better understanding of the standards (p < .001) or of facility pain management guidelines (p < .001), increased confidence in therapies for pain management (p < .001), and increased confidence in their training to assess pain (p < .001) and recognize pain in residents with dementia who are nonverbal (p = .003). The results show that improved evidence-based practice in RACFs can be achieved with appropriate training and education. Investing resources in the aged care workforce via this implementation program has shown improvements in staff self-efficacy and practice.

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Background Knowledge about genital Chlamydia trachomatis (CT) infections in the Pacific is limited. In this study we investigated CT infection in Samoan women. Methods We recruited women having unprotected sex aged 18 to 29 years from 41 Samoan villages. They completed a questionnaire and provided a urine sample for CT testing by PCR. Associations between CT infection and possible risk factors were explored using logistic regression. Results Altogether, 239 women were recruited; 86 (36.0%; weighted estimate of prevalence: 41.9%; 95% CI: 33.4–50.5%) were positive for CT infection. A higher proportion of women aged 18 to 24 were positive (54/145; 37.2%) than those aged 25 to 29 (32/94; 34.0%; p=0.20). Being single (OR 1.92; 95% CI: 1.02–3.63) and having two or more lifetime sexual partners (OR 3.02; 95% CI: 1.19–7.67) were associated with CT infection; 27.6% of those with one lifetime partner were positive. Participants who had a previous pregnancy were less likely to be positive (OR 0.49; 95% CI: 0.27–0.87). Primiparous and multiparous women were less likely to be positive than nulliparous women (OR 0.54; 95% CI: 0.30–0.99 and OR 0.46; 95% CI: 0.24–0.89, respectively). Conclusions The prevalence of CT infection in these Samoan women is very high. Further studies, including investigating the prevalence of CT infection in men, and strategies for sustainable control are needed.

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Higher education is becoming a major driver of economic competitiveness in an increasingly knowledge-driven global economy. Maintaining the competitive edge has seen an increase in public accountability of higher education institutions through the mechanism of ranking universities based on the quality of their teaching and learning outcomes. As a result, assessment processes are under scrutiny, creating tensions between standardisation and measurability and the development of creative and reflective learners. These tensions are further highlighted in the context of large undergraduate subjects, learner diversity and time-poor academics and students. Research suggests that high level and complex learning is best developed when assessment, combined with effective feedback practices, involves students as partners in these processes. This article reports on a four-phase, cross-institution and cross-discipline project designed to embed peer-review processes as part of the assessment in two large, undergraduate accounting classes. Using a social constructivist view of learning, which emphasises the role of both teacher and learner in the development of complex cognitive understandings, we undertook an iterative process of peer review. Successive phases built upon students’ feedback and achievements and input from language/learning and curriculum experts to improve the teaching and learning outcomes.

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Monitoring pedestrian and cyclists movement is an important area of research in transport, crowd safety, urban design and human behaviour assessment areas. Media Access Control (MAC) address data has been recently used as potential information for extracting features from people’s movement. MAC addresses are unique identifiers of WiFi and Bluetooth wireless technologies in smart electronics devices such as mobile phones, laptops and tablets. The unique number of each WiFi and Bluetooth MAC address can be captured and stored by MAC address scanners. MAC addresses data in fact allows for unannounced, non-participatory, and tracking of people. The use of MAC data for tracking people has been focused recently for applying in mass events, shopping centres, airports, train stations etc. In terms of travel time estimation, setting up a scanner with a big value of antenna’s gain is usually recommended for highways and main roads to track vehicle’s movements, whereas big gains can have some drawbacks in case of pedestrian and cyclists. Pedestrian and cyclists mainly move in built distinctions and city pathways where there is significant noises from other fixed WiFi and Bluetooth. Big antenna’s gains will cover wide areas that results in scanning more samples from pedestrians and cyclists’ MAC device. However, anomalies (such fixed devices) may be captured that increase the complexity and processing time of data analysis. On the other hand, small gain antennas will have lesser anomalies in the data but at the cost of lower overall sample size of pedestrian and cyclist’s data. This paper studies the effect of antenna characteristics on MAC address data in terms of travel-time estimation for pedestrians and cyclists. The results of the empirical case study compare the effects of small and big antenna gains in order to suggest optimal set up for increasing the accuracy of pedestrians and cyclists’ travel-time estimation.