502 resultados para visual methods
Resumo:
The transmission of bacteria is more likely to occur from wet skin than from dry skin; therefore, the proper drying of hands after washing should be an integral part of the hand hygiene process in health care. This article systematically reviews the research on the hygienic efficacy of different hand-drying methods. A literature search was conducted in April 2011 using the electronic databases PubMed, Scopus, and Web of Science. Search terms used were hand dryer and hand drying. The search was limited to articles published in English from January 1970 through March 2011. Twelve studies were included in the review. Hand-drying effectiveness includes the speed of drying, degree of dryness, effective removal of bacteria, and prevention of cross-contamination. This review found little agreement regarding the relative effectiveness of electric air dryers. However, most studies suggest that paper towels can dry hands efficiently, remove bacteria effectively, and cause less contamination of the washroom environment. From a hygiene viewpoint, paper towels are superior to electric air dryers. Paper towels should be recommended in locations where hygiene is paramount, such as hospitals and clinics.
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The present study considered factors influencing teachers' reporting of child sexual abuse (CSA). Conducted in three Australian jurisdictions with different reporting laws and policies, the study focused on teachers' actual past and anticipated future reporting of CSA. A sample of 470 teachers within randomly selected rural and urban schools was surveyed, to identify training and experience; knowledge of reporting legislation and policy; attitudes; and reporting practices. Factors influencing actual past reporting and anticipated future reporting were identified using logistic regression modelling. This is the first study to simultaneously examine the effect of important influences in reporting practice using both retrospective and prospective approaches across jurisdictions with different reporting laws. Teachers who have actually reported CSA in the past are more likely have higher levels of policy knowledge, and hold more positive attitudes towards reporting CSA along three specific dimensions: commitment to the reporting role; confidence in the system's effective response to their reporting; and they are more likely to be able to override their concerns about the consequences of their reporting. Teachers indicating intention to report hypothetical scenarios are more likely to hold reasonable grounds for suspecting CSA, to recognise that significant harm has been caused to the child, to know that their school policy requires a report, and to be able to override their concerns about the consequences of their reporting.
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Most unsignalised intersection capacity calculation procedures are based on gap acceptance models. Accuracy of critical gap estimation affects accuracy of capacity and delay estimation. Several methods have been published to estimate drivers’ sample mean critical gap, the Maximum Likelihood Estimation (MLE) technique regarded as the most accurate. This study assesses three novel methods; Average Central Gap (ACG) method, Strength Weighted Central Gap method (SWCG), and Mode Central Gap method (MCG), against MLE for their fidelity in rendering true sample mean critical gaps. A Monte Carlo event based simulation model was used to draw the maximum rejected gap and accepted gap for each of a sample of 300 drivers across 32 simulation runs. Simulation mean critical gap is varied between 3s and 8s, while offered gap rate is varied between 0.05veh/s and 0.55veh/s. This study affirms that MLE provides a close to perfect fit to simulation mean critical gaps across a broad range of conditions. The MCG method also provides an almost perfect fit and has superior computational simplicity and efficiency to the MLE. The SWCG method performs robustly under high flows; however, poorly under low to moderate flows. Further research is recommended using field traffic data, under a variety of minor stream and major stream flow conditions for a variety of minor stream movement types, to compare critical gap estimates using MLE against MCG. Should the MCG method prove as robust as MLE, serious consideration should be given to its adoption to estimate critical gap parameters in guidelines.
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Visual sea-floor mapping is a rapidly growing application for Autonomous Underwater Vehicles (AUVs). AUVs are well-suited to the task as they remove humans from a potentially dangerous environment, can reach depths human divers cannot, and are capable of long-term operation in adverse conditions. The output of sea-floor maps generated by AUVs has a number of applications in scientific monitoring: from classifying coral in high biological value sites to surveying sea sponges to evaluate marine environment health.
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Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.
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There is a need for an accurate real-time quantitative system that would enhance decision-making in the treatment of osteoarthritis. To achieve this objective, significant research is required that will enable articular cartilage properties to be measured and categorized for health and functionality without the need for laboratory tests involving biopsies for pathological evaluation. Such a system would provide the capability of access to the internal condition of the cartilage matrix and thus extend the vision-based arthroscopy that is currently used beyond the subjective evaluation of surgeons. The system required must be able to non-destructively probe the entire thickness of the cartilage and its immediate subchondral bone layer. In this thesis, near infrared spectroscopy is investigated for the purpose mentioned above. The aim is to relate it to the structure and load bearing properties of the cartilage matrix to the near infrared absorption spectrum and establish functional relationships that will provide objective, quantitative and repeatable categorization of cartilage condition outside the area of visible degradation in a joint. Based on results from traditional mechanical testing, their innovative interpretation and relationship with spectroscopic data, new parameters were developed. These were then evaluated for their consistency in discriminating between healthy viable and degraded cartilage. The mechanical and physico-chemical properties were related to specific regions of the near infrared absorption spectrum that were identified as part of the research conducted for this thesis. The relationships between the tissue's near infrared spectral response and the new parameters were modeled using multivariate statistical techniques based on partial least squares regression (PLSR). With significantly high levels of statistical correlation, the modeled relationships were demonstrated to possess considerable potential in predicting the properties of unknown tissue samples in a quick and non-destructive manner. In order to adapt near infrared spectroscopy for clinical applications, a balance between probe diameter and the number of active transmit-receive optic fibres must be optimized. This was achieved in the course of this research, resulting in an optimal probe configuration that could be adapted for joint tissue evaluation. Furthermore, as a proof-of-concept, a protocol for obtaining the new parameters from the near infrared absorption spectra of cartilage was developed and implemented in a graphical user interface (GUI)-based software, and used to assess cartilage-on-bone samples in vitro. This conceptual implementation has been demonstrated, in part by the individual parametric relationship with the near infrared absorption spectrum, the capacity of the proposed system to facilitate real-time, non-destructive evaluation of cartilage matrix integrity. In summary, the potential of the optical near infrared spectroscopy for evaluating articular cartilage and bone laminate has been demonstrated in this thesis. The approach could have a spin-off for other soft tissues and organs of the body. It builds on the earlier work of the group at QUT, enhancing the near infrared component of the ongoing research on developing a tool for cartilage evaluation that goes beyond visual and subjective methods.
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Many substation applications require accurate time-stamping. The performance of systems such as Network Time Protocol (NTP), IRIG-B and one pulse per second (1-PPS) have been sufficient to date. However, new applications, including IEC 61850-9-2 process bus and phasor measurement, require accuracy of one microsecond or better. Furthermore, process bus applications are taking time synchronisation out into high voltage switchyards where cable lengths may have an impact on timing accuracy. IEEE Std 1588, Precision Time Protocol (PTP), is the means preferred by the smart grid standardisation roadmaps (from both the IEC and US National Institute of Standards and Technology) of achieving this higher level of performance, and integrates well into Ethernet based substation automation systems. Significant benefits of PTP include automatic path length compensation, support for redundant time sources and the cabling efficiency of a shared network. This paper benchmarks the performance of established IRIG-B and 1-PPS synchronisation methods over a range of path lengths representative of a transmission substation. The performance of PTP using the same distribution system is then evaluated and compared to the existing methods to determine if the performance justifies the additional complexity. Experimental results show that a PTP timing system maintains the synchronising performance of 1-PPS and IRIG-B timing systems, when using the same fibre optic cables, and further meets the needs of process buses in large substations.
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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.
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Plasma enhanced chemical vapour deposition silicon nitride thin films are widely used in microelectromechanical system devices as structural materials because the mechanical properties of those films can be tailored by adjusting deposition conditions. However, accurate measurement of the mechanical properties, such as hardness, of films with thicknesses at nanometric scale is challenging. In the present study, the hardness of the silicon nitride films deposited on silicon substrate under different deposit conditions was characterised using nanoindentation and nanoscratch deconvolution methods. The hardness values obtained from the two methods were compared. The effect of substrate on the measured results was discussed.
Resumo:
Problems involving the solution of advection-diffusion-reaction equations on domains and subdomains whose growth affects and is affected by these equations, commonly arise in developmental biology. Here, a mathematical framework for these situations, together with methods for obtaining spatio-temporal solutions and steady states of models built from this framework, is presented. The framework and methods are applied to a recently published model of epidermal skin substitutes. Despite the use of Eulerian schemes, excellent agreement is obtained between the numerical spatio-temporal, numerical steady state, and analytical solutions of the model.
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Background: Gender differences in cycling are well-documented. However, most analyses of gender differences make broad comparisons, with few studies modeling male and female cycling patterns separately for recreational and transport cycling. This modeling is important, in order to improve our efforts to promote cycling to women and men in countries like Australia with low rates of transport cycling. The main aim of this study was to examine gender differences in cycling patterns and in motivators and constraints to cycling, separately for recreational and transport cycling. Methods: Adult members of a Queensland, Australia, community bicycling organization completed an online survey about their cycling patterns; cycling purposes; and personal, social and perceived environmental motivators and constraints (47% response rate). Closed and open-end questions were completed. Using the quantitative data, multivariable linear, logistic and ordinal regression models were used to examine associations between gender and cycling patterns, motivators and constraints. The qualitative data were thematically analysed to expand upon the quantitative findings. Results: In this sample of 1862 bicyclists, men were more likely than women to cycle for recreation and for transport, and they cycled for longer. Most transport cycling was for commuting, with men more likely than women to commute by bicycle. Men were more likely to cycle on-road, and women off-road. However, most men and women did not prefer to cycle on-road without designed bicycle lanes, and qualitative data indicated a strong preference by men and women for bicycle-only off-road paths. Both genders reported personal factors (health and enjoyment related) as motivators for cycling, although women were more likely to agree that other personal, social and environmental factors were also motivating. The main constraints for both genders and both cycling purposes were perceived environmental factors related to traffic conditions, motorist aggression and safety. Women, however, reported more constraints, and were more likely to report as constraints other environmental factors and personal factors. Conclusion: Differences found in men’s and women’s cycling patterns, motivators and constraints should be considered in efforts to promote cycling, particularly in efforts to increase cycling for transport.
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The Texas Department of Transportation (TxDOT) is concerned about the widening gap between pavement preservation needs and available funding. Thus, the TxDOT Austin District Pavement Engineer (DPE) has investigated methods to strategically allocate available pavement funding to potential projects that improve the overall performance of the District and Texas highway systems. The primary objective of the study presented in this paper is to develop a network-level project screening and ranking method that supports the Austin District 4-year pavement management plan development. The study developed candidate project selection and ranking algorithms that evaluated pavement conditions of each project candidate using data contained in the Pavement Management Information system (PMIS) database and incorporated insights from Austin District pavement experts; and implemented the developed method and supporting algorithm. This process previously required weeks to complete, but now requires about 10 minutes including data preparation and running the analysis algorithm, which enables the Austin DPE to devote more time and resources to conducting field visits, performing project-level evaluation and testing candidate projects. The case study results showed that the proposed method assisted the DPE in evaluating and prioritizing projects and allocating funds to the right projects at the right time.
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This thesis develops an understanding of how propaganda entered the realm of journalism and popular culture in the United States during World War I through an examination of materials created by the Committee on Public Information (CPI). The CPI was a US governmental propaganda organisation created during World War I to persuade the nation to mobilise for war. Three of its divisions were chosen for this study: the Division of News (DoN), the Division of Four Minute Men (FMM) and the Division of Pictorial Publicity (DPP). Chapter 1 provides a general context for the thesis, outlines the research questions and details previous research on the CPI. Chapter 2 outlines the methods of analysis for interpreting the case study chapters and provides contextual information. The case studies are presented in Chapters 3, 4 and 5. These chapters are structured in the order of context, medium and content, and contain historical contextual information about each particular division, medialogical aspects of its propagated form and thematic groupings created from close reading of CPI materials. A semiotic analysis in the Peircian tradition is also performed on visual forms of propaganda in Chapter 5. Chapter 6 discusses how the expectations of persuasion, truth and amusement relate to each other when mediated in culture, using Lotman’s concept of the semiosphere. This further develops an understanding of propaganda as a cultural system in relation to other cultural systems – in this case, journalism and popular culture. Chapter 7 provides conclusions about the study, outlines relative strengths and weaknesses regarding the selection and deployment of methods, makes recommendations for future research, and summarises the key contributions of the thesis.
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Background: Mesenchymal stromal cells (MSC) with similar properties to bone marrow derived mesenchymal stromal cells (BM-MSC) have recently been grown from the limbus of the human cornea. We presently contribute to this novel area of research by evaluating methods for culturing human limbal MSC (L-MSC). Methods: Four basic strategies are compared: serum-supplemented medium (10% foetal bovine serum; FBS), standard serum-free medium supplemented with B-27, epidermal growth factor, and fibroblast growth factor 2, or one of two commercial serum-free media including Defined Keratinocyte Serum Free Medium (Invitrogen), and MesenCult-XF (Stem Cell Technologies). The phenotype of resulting cultures was examined using photography, flow cytometry (for CD34, CD45, CD73, CD90, CD105, CD141, CD271), immunocytochemistry (α-sma), differentiation assays (osteogenesis, adipogenesis, chrondrogenesis), and co-culture experiments with human limbal epithelial (HLE) cells. Results: While all techniques supported to varying degrees establishment of cultures, sustained growth and serial propagation was only achieved in 10% FBS medium or MesenCult-XF medium. Cultures established in 10% FBS medium were 70-80% CD34-/CD45-/CD90+/CD73+/CD105+, approximately 25% α-sma+, and displayed multi-potency. Cultures established in MesenCult-XF were >95% CD34-/CD45-/CD90+/CD73+/CD105+, 40% CD141+, rarely expressed α-sma, and displayed multi-potency. L-MSC supported growth of HLE cells, with the largest epithelial islands being observed in the presence of MesenCult-XF-grown L-MSC. All HLE cultures supported by L-MSC widely expressed the progenitor cell marker ∆Np63, along with the corneal differentiation marker cytokeratin 3. Conclusions: We conclude that MesenCult-XF® is a superior culture system for L-MSC, but further studies are required to explore the significance of CD141 expression in these cells.
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This paper describes observational research and verbal protocols methods, how these methods are applied and integrated within different contexts, and how they complement each other. The first case study focuses on nurses’ interaction during bandaging of patients’ lower legs. To maintain research rigor a triangulation approach was applied that links observations of current procedures, ‘talk-aloud’ protocol during interaction and retrospective protocol. Maps of interactions demonstrated that some nurses bandage more intuitively than others. Nurses who bandage intuitively assemble long sequences of bandaging actions while nurses who bandage less intuitively ‘focus-shift’ in between bandaging actions. Thus different levels of expertise have been identified. The second case study consists of two laboratory experiments. It focuses on analysing and comparing software and product design teams and how they approached a design problem. It is based on the observational and verbal data analysis. The coding scheme applied evolved during the analysis of the activity of each team and is identical for all teams. The structure of knowledge captured from the analysis of the design team maps of interaction is identified. The significance of this work is within its methodological approach. The maps of interaction are instrumental for understanding the activities and interactions of the people observed. By examining the maps of interaction, it is possible to draw conclusions about interactions, structure of knowledge captured and level of expertise. This research approach is transferable to other design domains. Designers will be able to transfer the interaction maps outcomes to systems and services they design.