954 resultados para Critical Incident Technique
Resumo:
In response to the rail industry lacking a consistently accepted standard of minimal training to perform incident investigations, the Australasian rail industry requested the development of a unified approach to investigator training. This paper details how the findings from a training needs analysis were applied to inform the development of a standardised training package for rail incident investigators. Data from job descriptions, training documents and subject matter experts sourced from 17 Australasian organisations were analysed and refined to yield a draft set of 10 critical competencies. Finally the draft of critical competencies was reviewed by industry experts to verify the accuracy and completeness of the competency list and to consider the most appropriate level of qualification for training development. The competencies identified and the processes described to translate research into an applied training framework in this paper, can be generalised to assist practitioners and researchers in developing industry approved standardised training packages.
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Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applications have been increasing since its introduction in the 1980s. This paper provides a critical review of 84 articles involving the use of SEM to address construction related problems over the period 1998–2012 including, but not limited to, seven top construction research journals. After conducting a yearly publication trend analysis, it is found that SEM applications have been accelerating over time. However, there are inconsistencies in the various recorded applications and several recurring problems exist. The important issues that need to be considered are examined in research design, model development and model evaluation and are discussed in detail with reference to current applications. A particularly important issue concerns the construct validity. Relevant topics for efficient research design also include longitudinal or cross-sectional studies, mediation and moderation effects, sample size issues and software selection. A guideline framework is provided to help future researchers in construction SEM applications.
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The estimation of the critical gap has been an issue since the 1970s, when gap acceptance was introduced to evaluate the capacity of unsignalized intersections. The critical gap is the shortest gap that a driver is assumed to accept. A driver’s critical gap cannot be measured directly and a number of techniques have been developed to estimate the mean critical gaps of a sample of drivers. This paper reviews the ability of the Maximum Likelihood technique and the Probability Equilibrium Method to predict the mean and standard deviation of the critical gap with a simulation of 100 drivers, repeated 100 times for each flow condition. The Maximum Likelihood method gave consistent and unbiased estimates of the mean critical gap. Whereas the probability equilibrium method had a significant bias that was dependent on the flow in the priority stream. Both methods were reasonably consistent, although the Maximum Likelihood Method was slightly better. If drivers are inconsistent, then again the Maximum Likelihood method is superior. A criticism levelled at the Maximum Likelihood method is that a distribution of the critical gap has to be assumed. It was shown that this does not significantly affect its ability to predict the mean and standard deviation of the critical gaps. Finally, the Maximum Likelihood method can predict reasonable estimates with observations for 25 to 30 drivers. A spreadsheet procedure for using the Maximum Likelihood method is provided in this paper. The PEM can be improved if the maximum rejected gap is used.
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A major drawback to the immunological potency of conventional vaccines, resulting in reduced level of immune responses, tissue injury, shock and high cytotoxicity, thus making their applications contraindicated in immunodeficiency diseases, is the presence of high contaminant concentrations in vaccine titers. Vaccine contamination arises from the simultaneous occurrence of competitive pathways resulting in the formation of other bio-products during cellular metabolism aside the pathways necessary for the production of vaccine molecules. One of such vaccine contaminating molecules is endotoxins which are mainly lipopolysaccharides (LPS) complexes found in the membrane of bacterial cell wall. The structural dynamics of these molecules make their removal from vaccine titers problematic, thus making vaccine endotoxin removal a major research endeavour. This presentation will discuss a novel technique for reducing the endotoxin level of vaccines. The technique commences with the disentanglement of endotoxin-vaccine molecular bonding and then capturing the vaccine molecules on an affinity monolith to separate the vaccine molecules from the endotoxins.
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Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.
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A simple cconversence technique is applied to obtain accurate estimates of critical temperatures and critical it\ponmts of a few two- and threpdiniensional king models. When applied to the virial series for hard spheres and hard discs, this method predicts a divergence of the equation-of-state at the density of closest packing.
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Background Medication incident reporting (MIR) is a key safety critical care process in residential aged care facilities (RACFs). Retrospective studies of medication incident reports in aged care have identified the inability of existing MIR processes to generate information that can be used to enhance residents’ safety. However, there is little existing research that investigates the limitations of the existing information exchange process that underpins MIR, despite the considerable resources that RACFs’ devote to the MIR process. The aim of this study was to undertake an in-depth exploration of the information exchange process involved in MIR and identify factors that inhibit the collection of meaningful information in RACFs. Methods The study was undertaken in three RACFs (part of a large non-profit organisation) in NSW, Australia. A total of 23 semi-structured interviews and 62 hours of observation sessions were conducted between May to July 2011. The qualitative data was iteratively analysed using a grounded theory approach. Results The findings highlight significant gaps in the design of the MIR artefacts as well as information exchange issues in MIR process execution. Study results emphasized the need to: a) design MIR artefacts that facilitate identification of the root causes of medication incidents, b) integrate the MIR process within existing information systems to overcome key gaps in information exchange execution, and c) support exchange of information that can facilitate a multi-disciplinary approach to medication incident management in RACFs. Conclusions This study highlights the advantages of viewing MIR process holistically rather than as segregated tasks, as a means to identify gaps in information exchange that need to be addressed in practice to improve safety critical processes.
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The Distributed Network Protocol v3.0 (DNP3) is one of the most widely used protocols to control national infrastructure. The move from point-to-point serial connections to Ethernet-based network architectures, allowing for large and complex critical infrastructure networks. However, networks and con- figurations change, thus auditing tools are needed to aid in critical infrastructure network discovery. In this paper we present a series of intrusive techniques used for reconnaissance on DNP3 critical infrastructure. Our algorithms will discover DNP3 outstation slaves along with their DNP3 addresses, their corresponding master, and class object configurations. To validate our presented DNP3 reconnaissance algorithms and demonstrate it’s practicality, we present an implementation of a software tool using a DNP3 plug-in for Scapy. Our implementation validates the utility of our DNP3 reconnaissance technique. Our presented techniques will be useful for penetration testing, vulnerability assessments and DNP3 network discovery.
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The main objective of on-line dynamic security assessment is to take preventive action if required or decide remedial action if a contingency actually occurs. Stability limits are obtained for different contingencies. The mode of instability is one of the outputs of dynamic security analysis. When a power system becomes unstable, it splits initially into two groups of generators, and there is a unique cutset in the transmission network known as critical cutset across which the angles become unbounded. The knowledge of critical cutset is additional information obtained from dynamic security assessment, which can be used for initiating preventive control actions, deciding emergency control actions, and adaptive out-of-step relaying. In this article, an analytical technique for the fast prediction of the critical cutset by system simulation for a short duration is presented. Case studies on the New England ten-generator system are presented. The article also suggests the applications of the identification of critical cutsets.
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A new experimental technique is proposed to determine refractive indices of liquids and isotropic solids at different wavelengths. A Pellin-Broca hollow prism filled with a liquid sample produces the spectrum (of the liquid prism) on the photographic plate of the camera. A plane reflector, mounted at a small angle to the normal of the exit face of the prism, also forms a direct image of the collimator slit in the plane of the same photographic plate. All the necessary information for determining the refractive indices (for different wavelengths) is extracted directly from the spectrogram without using any goniometric system. Experiments are conducted with the liquid prisms of isopropyl alcohol, water, and benzene. The results of the experiments are compared with those obtained by a Pulfrich refractometer (critical angle method). The proposed new technique gives the refractive indices for visible and invisible spectral lines to an accuracy of 2x10(-5). (C) 1997 Society of Photo-Optical Instrumentation Engineers.
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Radially homogeneous bulk alloys of GaxIn1-xSb in the range 0.7 < x < 0.8, have been grown by vertical Bridgman technique. The factors affecting the interface shape during the growth were optimised to achieve zero convexity. From a series of experiments, a critical ratio of the temperature gradient (G) of the furnace at the melting point of the melt composition to the ampoule lowering speed (v) was deduced for attaining the planarity of the melt-solid interface. The studies carried out on directional solidification of Ga0.77In0.23Sb mixed crystals employing planar melt-solid interface exhibited superior quality than those with nonplanar interfaces. The solutions to certain problems encountered during the synthesis and growth of the compound were discussed. (C) 1999 Elsevier Science B.V. All rights reserved.
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A deep‐level transient spectroscopy (DLTS) technique is reported for determining the capture cross‐section activation energy directly. Conventionally, the capture activation energy is obtained from the temperature dependence of the capture cross section. Capture cross‐section measurement is often very doubtful due to many intrinsic errors and is more critical for nonexponential capture kinetics. The essence of this technique is to use an emission pulse to allow the defects to emit electrons and the transient signal from capture process due to a large capture barrier was analyzed, in contrast with the emission signal in conventional DLTS. This technique has been applied for determining the capture barrier for silicon‐related DX centers in AlxGa1−xAs for different AlAs mole fractions.
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Three algorithms for reactive power optimization are proposed in this paper with three different objective functions. The objectives in the proposed algorithm are to minimize the sum of the squares of the voltage deviations of the load buses, minimization of sum of squares of voltage stability L-indices of load buses (:3L2) algorithm, and also the objective of system real power loss (Ploss) minimization. The approach adopted is an iterative scheme with successive power flow analysis using decoupled technique and solution of the linear programming problem using upper bound optimization technique. Results obtained with all these objectives are compared. The analysis of these objective functions are presented to illustrate their advantages. It is observed comparing different objective functions it is possible to identify critical On Load Tap Changers (OLTCs) that should be made manual to avoid possible voltage instability due to their operation based on voltage improvement criteria under heavy load conditions. These algorithms have been tested under simulated conditions on few test systems. The results obtained on practical systems of 24-node equivalent EHV Indian power network, and for a 205 bus EHV system are presented for illustration purposes.
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This paper presents a method for placement of Phasor Measurement Units, ensuring the monitoring of vulnerable buses which are obtained based on transient stability analysis of the overall system. Real-time monitoring of phase angles across different nodes, which indicates the proximity to instability, the very purpose will be well defined if the PMUs are placed at buses which are more vulnerable. The issue is to identify the key buses where the PMUs should be placed when the transient stability prediction is taken into account considering various disturbances. Integer Linear Programming technique with equality and inequality constraints is used to find out the optimal placement set with key buses identified from transient stability analysis. Results on IEEE-14 bus system are presented to illustrate the proposed approach.
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This paper presents a macro-level seismic landslide hazard assessment for the entire state of Sikkim, India, based on the Newmark's methodology. The slope map of Sikkim was derived from ASTER Global Digital Elevation Model (GDEM). Seismic shaking in terms of peak horizontal acceleration (PHA) at bedrock level was estimated from deterministic seismic hazard analysis (DSHA), considering point source model. Peak horizontal acceleration at the surface level for the study area was estimated based on nonlinear site amplification technique, considering B-type NEHRP site class. The PHA at surface was considered to induce driving forces on slopes, thus causing landslides. Knowing the surface level PHA and slope angle, the seismic landslide hazard assessment for each grid point was carried out using Newmark's analysis. The critical static factor of safety required to resist landslide for the PHA (obtained from deterministic analysis) was evaluated and its spatial variation throughout the study area is presented. For any slope in the study area, if the in-situ (available) static factor of safety is greater than the static factor of safety required to resist landslide as predicted in the present study, that slope is considered to be safe.