935 resultados para Simulation tool
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PURPOSE: This pilot project’s aim was to trial a tool and process for developing students’ ability to engage in self-assessment using reflection on their clinical experiences, including feedback from workplace learning, in order to aid them in linking theory to practice and develop strategies to improve performance. BACKGROUND: In nursing education, students can experience a mismatch in performance compared to theoretical learning, this is referred to as the ‘theory practice gap’ (Scully 2011, Chan Chan & Liu 2011). One specific contributing factor seems to be students’ inability to engage in meaningful reflection and self-correcting behaviours. A self-assessment strategy was implemented within a third year clinical unit to ameliorate this mismatch with encouraging results, as students developed self-direction in addressing learning needs. In this pilot project the above strategy was adapted for implementation between different clinical units, to create a whole of course approach to integrating workplace learning. METHOD: The methodology underpinning this project is a scaffolded, supported reflective practice process. Improved self-assessment skills is achieved by students reflecting on and engaging with feedback, then mapping this to learning outcomes to identify where performance can be improved. Evaluation of this project includes: collation of student feedback identifying successful strategies along with barriers encountered in implementation; feedback from students and teachers via above processes and tools; and comparison of the number of learning contracts issued in clinical nursing units with similar cohorts. RESULTS: Results will be complete by May 2012 and include analysis of the data collected via the above evaluation methods. Other outcomes will include the refined process and tool, plus resources that should improve cost effectiveness without reducing student support. CONCLUSION: Implementing these tools and processes over the entire student’s learning package, will assist them to demonstrate progressive development through the course. Students will have learnt to understand feedback and integrate these skills for life-long learning.
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Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.
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In this work we discuss the effects of white and coloured noise perturbations on the parameters of a mathematical model of bacteriophage infection introduced by Beretta and Kuang in [Math. Biosc. 149 (1998) 57]. We numerically simulate the strong solutions of the resulting systems of stochastic ordinary differential equations (SDEs), with respect to the global error, by means of numerical methods of both Euler-Taylor expansion and stochastic Runge-Kutta type.
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For the evaluation, design, and planning of traffic facilities and measures, traffic simulation packages are the de facto tools for consultants, policy makers, and researchers. However, the available commercial simulation packages do not always offer the desired work flow and flexibility for academic research. In many cases, researchers resort to designing and building their own dedicated models, without an intrinsic incentive (or the practical means) to make the results available in the public domain. To make matters worse, a substantial part of these efforts pertains to rebuilding basic functionality and, in many respects, reinventing the wheel. This problem not only affects the research community but adversely affects the entire traffic simulation community and frustrates the development of traffic simulation in general. For this problem to be addressed, this paper describes an open source approach, OpenTraffic, which is being developed as a collaborative effort between the Queensland University of Technology, Australia; the National Institute of Informatics, Tokyo; and the Technical University of Delft, the Netherlands. The OpenTraffic simulation framework enables academies from geographic areas and disciplines within the traffic domain to work together and contribute to a specific topic of interest, ranging from travel choice behavior to car following, and from response to intelligent transportation systems to activity planning. The modular approach enables users of the software to focus on their area of interest, whereas other functional modules can be regarded as black boxes. Specific attention is paid to a standardization of data inputs and outputs for traffic simulations. Such standardization will allow the sharing of data with many existing commercial simulation packages.
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Effective flocculation and dewatering of mineral processing streams containing clays are microstructure dependent in clay-water systems. Initial clay flocculation is crucial in the design and for the development of a new methodology of gas exploitation. Microstructural engineering of clay aggregates using covalent cations and Keggin macromolecules have been monitored using the new state of the art Transmission X-ray Microscope (TXM) with 60 nm tomography resolution installed in a Taiwanese synchrotron. The 3-D reconstructions from TXM images show complex aggregation structures in montmorillonite aqueous suspensions after treatment with Na+, Ca2+ and Al13 Keggin macromolecules. Na-montmorillonite displays elongated, parallel, well-orientated and closed-void cellular networks, 0.5–3 μm in diameter. After treatment by covalent cations, the coagulated structure displays much smaller, randomly orientated and openly connected cells, 300–600 nm in diameter. The average distances measured between montmorillonite sheets was around 450 nm, which is less than half of the cell dimension measured in Na-montmorillonite. The most dramatic structural changes were observed after treatment by Al13 Keggin; aggregates then became arranged in compacted domains of a 300 nm average diameter composed of thick face-to-face oriented sheets, which forms porous aggregates with larger intra-aggregate open and connected voids.
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Internet chatrooms are common means of interaction and communications, and they carry valuable information about formal or ad-hoc formation of groups with diverse objectives. This work presents a fully automated surveillance system for data collection and analysis in Internet chatrooms. The system has two components: First, it has an eavesdropping tool which collects statistics on individual (chatter) and chatroom behavior. This data can be used to profile a chatroom and its chatters. Second, it has a computational discovery algorithm based on Singular Value Decomposition (SVD) to locate hidden communities and communication patterns within a chatroom. The eavesdropping tool is used for fine tuning the SVD-based discovery algorithm which can be deployed in real-time and requires no semantic information processing. The evaluation of the system on real data shows that (i) statistical properties of different chatrooms vary significantly, thus profiling is possible, (ii) SVD-based algorithm has up to 70-80% accuracy to discover groups of chatters.
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We present a virtual test bed for network security evaluation in mid-scale telecommunication networks. Migration from simulation scenarios towards the test bed is supported and enables researchers to evaluate experiments in a more realistic environment. We provide a comprehensive interface to manage, run and evaluate experiments. On basis of a concrete example we show how the proposed test bed can be utilized.
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The evolution of classic power grids to smart grids creates chances for most participants in the energy sector. Customers can save money by reducing energy consumption, energy providers can better predict energy demand and environment benefits since lower energy consumption implies lower energy production including a decrease of emissions from plants. But information and communication systems supporting smart grids can also be subject to classical or new network attacks. Attacks can result in serious damage such as harming privacy of customers, creating economical loss and even disturb the power supply/demand balance of large regions and countries. In this paper, we give an overview about the German smart measuring architecture, protocols and security. Afterwards, we present a simulation framework which enables researchers to analyze security aspects of smart measuring scenarios.
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Theme Paper for Curriculum innovation and enhancement theme AIM: This paper reports on a research project that trialled an educational strategy implemented in an undergraduate nursing curriculum. The project aimed to explore the effectiveness of ‘think aloud’ as a strategy for improving clinical reasoning for students in simulated clinical settings. BACKGROUND: Nurses are required to apply and utilise critical thinking skills to enable clinical reasoning and problem solving in the clinical setting (Lasater, 2007). Nursing students are expected to develop and display clinical reasoning skills in practice, but may struggle articulating reasons behind decisions about patient care. The ‘think aloud’ approach is an innovative learning/teaching method which can create an environment suitable for developing clinical reasoning skills in students (Banning, 2008, Lee and Ryan-Wenger, 1997). This project used the ‘think aloud’ strategy within a simulation context to provide a safe learning environment in which third year students were assisted to uncover cognitive approaches to assist in making effective patient care decisions, and improve their confidence, clinical reasoning and active critical reflection about their practice. MEHODS: In semester 2 2011 at QUT, third year nursing students undertook high fidelity simulation (some for the first time), commencing in September of 2011. There were two cohorts for strategy implementation (group 1= used think aloud as a strategy within the simulation, group 2= no specific strategy outside of nursing assessment frameworks used by all students) in relation to problem solving patient needs. The think aloud strategy was described to students in their pre-simulation briefing and allowed time for clarification of this strategy. All other aspects of the simulations remained the same, (resources, suggested nursing assessment frameworks, simulation session duration, size of simulation teams, preparatory materials). Ethics approval has been obtained for this project. RESULTS: Results of a qualitative analysis (in progress- will be completed by March 2012) of student and facilitator reports on students’ ability to meet the learning objectives of solving patient problems using clinical reasoning and experience with the ‘think aloud’ method will be presented. A comparison of clinical reasoning learning outcomes between the two groups will determine the effect on clinical reasoning for students responding to patient problems. CONCLUSIONS: In an environment of increasingly constrained clinical placement opportunities, exploration of alternate strategies to improve critical thinking skills and develop clinical reasoning and problem solving for nursing students is imperative in preparing nurses to respond to changing patient needs.
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Three dimensional conjugate heat transfer simulation of a standard parabolic trough thermal collector receiver is performed numerically in order to visualize and analyze the surface thermal characteristics. The computational model is developed in Ansys Fluent environment based on some simplified assumptions. Three test conditions are selected from the existing literature to verify the numerical model directly, and reasonably good agreement between the model and the test results confirms the reliability of the simulation. Solar radiation flux profile around the tube is also approximated from the literature. An in house macro is written to read the input solar flux as a heat flux wall boundary condition for the tube wall. The numerical results show that there is an abrupt variation in the resultant heat flux along the circumference of the receiver. Consequently, the temperature varies throughout the tube surface. The lower half of the horizontal receiver enjoys the maximum solar flux, and therefore, experiences the maximum temperature rise compared to the upper part with almost leveled temperature. Reasonable attributions and suggestions are made on this particular type of conjugate thermal system. The knowledge that gained so far from this study will be used to further the analysis and to design an efficient concentrator photovoltaic collector in near future.
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Parabolic Trough Concentrators (PTC) are the most proven solar collectors for solar thermal power plants, and are suitable for concentrating photovoltaic (CPV) applications. PV cells are sensitive to spatial uniformity of incident light and the cell operating temperature. This requires the design of CPV-PTCs to be optimised both optically and thermally. Optical modelling can be performed using Monte Carlo Ray Tracing (MCRT), with conjugate heat transfer (CHT) modelling using the computational fluid dynamics (CFD) to analyse the overall designs. This paper develops and evaluates a CHT simulation for a concentrating solar thermal PTC collector. It uses the ray tracing work by Cheng et al. (2010) and thermal performance data for LS-2 parabolic trough used in the SEGS III-VII plants from Dudley et al. (1994). This is a preliminary step to developing models to compare heat transfer performances of faceted absorbers for concentrating photovoltaic (CPV) applications. Reasonable agreement between the simulation results and the experimental data confirms the reliability of the numerical model. The model explores different physical issues as well as computational issues for this particular kind of system modeling. The physical issues include the resultant non-uniformity of the boundary heat flux profile and the temperature profile around the tube, and uneven heating of the HTF. The numerical issues include, most importantly, the design of the computational domain/s, and the solution techniques of the turbulence quantities and the near-wall physics. This simulation confirmed that optical simulation and the computational CHT simulation of the collector can be accomplished independently.
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Background: When experiencing sleep problems for the first time, consumers may often approach community pharmacists for advice as they are easily accessible health care professionals in the community. In Australian community pharmacies there are no specific tools available for use by pharmacists to assist with the assessment and handling of consumers with sleep enquiries. Objective: To assess the feasibility of improving the detection of sleep disorders within the community through the pilot of a newly developed Community Pharmacy Sleep Assessment Tool (COP-SAT). Method: The COP-SAT was designed to incorporate elements from a number of existing, standardized, and validated clinical screening measures. The COP-SAT was trialed in four Australian community pharmacies over a 4-week period. Key findings: A total of 241 community pharmacy consumers were assessed using the COP-SAT. A total of 74 (30.7%) were assessed as being at risk of insomnia, 26 (10.7%) were at risk of daytime sleepiness, 19 (7.9%) were at risk of obstructive sleep apnea, and 121 (50.2%) were regular snorers. A total of 116 (48.1%) participants indicated that they consume caffeine before bedtime, of which 55 (47%) had associated symptoms of sleep onset insomnia. Moreover, 85 (35%) consumed alcohol before bedtime, of which 50 (58%) experienced fragmented sleep, 50 (58%) were regular snorers, and nine (10.6%) had apnea symptoms. The COP-SAT was feasible in the community pharmacy setting. The prevalence of sleep disorders in the sampled population was high, but generally consistent with previous studies on the general population. Conclusion: A large proportion of participants reported sleep disorder symptoms, and a link was found between the consumption of alcohol and caffeine substances at bedtime and associated symptoms. While larger studies are needed to assess the clinical properties of the tool, the results of this feasibility study have demonstrated that the COP-SAT may be a practical tool for the identification of patients at risk of developing sleep disorders in the community.
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We introduce the Network Security Simulator (NeSSi2), an open source discrete event-based network simulator. It incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Compared to the predecessor NeSSi, it was extended with a three-tier plugin architecture and a generic network model to shift its focus towards simulation framework for critical infrastructures. We demonstrate the gained adaptability by different use cases
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Good daylighting design in buildings not only provides a comfortable luminous environment, but also delivers energy savings and comfortable and healthy environments for building occupants. Yet, there is still no consensus on how to assess what constitutes good daylighting design. Currently amongst building performance guidelines, Daylighting factors (DF) or minimum illuminance values are the standard; however, previous research has shown the shortcomings of these metrics. New computer software for daylighting analysis contains new more advanced metrics for daylighting (Climate Base Daylight Metrics-CBDM). Yet, these tools (new metrics or simulation tools) are not currently understood by architects and are not used within architectural firms in Australia. A survey of architectural firms in Brisbane showed the most relevant tools used by industry. The purpose of this paper is to assess and compare these computer simulation tools and new tools available architects and designers for daylighting. The tools are assessed in terms of their ease of use (e.g. previous knowledge required, complexity of geometry input, etc.), efficiency (e.g. speed, render capabilities, etc.) and outcomes (e.g. presentation of results, etc. The study shows tools that are most accessible for architects, are those that import a wide variety of files, or can be integrated into the current 3d modelling software or package. These software’s need to be able to calculate for point in times simulations, and annual analysis. There is a current need in these software solutions for an open source program able to read raw data (in the form of spreadsheets) and show that graphically within a 3D medium. Currently, development into plug-in based software’s are trying to solve this need through third party analysis, however some of these packages are heavily reliant and their host program. These programs however which allow dynamic daylighting simulation, which will make it easier to calculate accurate daylighting no matter which modelling platform the designer uses, while producing more tangible analysis today, without the need to process raw data.
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The power of testing for a population-wide association between a biallelic quantitative trait locus and a linked biallelic marker locus is predicted both empirically and deterministically for several tests. The tests were based on the analysis of variance (ANOVA) and on a number of transmission disequilibrium tests (TDT). Deterministic power predictions made use of family information, and were functions of population parameters including linkage disequilibrium, allele frequencies, and recombination rate. Deterministic power predictions were very close to the empirical power from simulations in all scenarios considered in this study. The different TDTs had very similar power, intermediate between one-way and nested ANOVAs. One-way ANOVA was the only test that was not robust against spurious disequilibrium. Our general framework for predicting power deterministically can be used to predict power in other association tests. Deterministic power calculations are a powerful tool for researchers to plan and evaluate experiments and obviate the need for elaborate simulation studies.