908 resultados para Safety Culture, Safety Leadership, Safety Critical Tasks


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The concept of ontological security has a remarkable echo in the current sociology to describe emotional status of men of late modernity. However, the concept created by Giddens in the eighties has been little used in empirical research covering various sources of risk or uncertainty. In this paper, a scale for ontological security is proposed. To do this, we start from the results of a research focused on the relationship between risk, uncertainty and vulnerability in the context of the economic crisis in Spain. These results were produced through nine focus groups and a telephone survey with standardized questionnaire applied to a national sample of 2,408 individuals over 18 years. This work is divided into three main sections. In the fi rst, a scale has been built from the results of the application of different items present in the questionnaire used. The second part explores the relationships of the scale obtained with the variables further approximate the emotional dimensions of individuals. The third part observes the variables that contribute to changes in the scale: These variables show the structural feature of the ontological security.

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En esta tesis se presenta la influencia que tiene la Cultura Nacional en el desempeño Logístico de una Nación, en especial de los 123 primeros países evaluados por el Índice de Desempeño Logístico (LPI) realizado por el Banco Mundial. Este estudio se realiza a partir de los seis ítems evaluados en el LPI y de las seis Dimensiones Culturales de Hofstede, para relacionar estas calificaciones se empleará el programa estadístico SPSS Statistical Package for the Social Sciences obteniendo como resultado posibles correlaciones para probar la hipótesis del efecto de la cultura en el desempeño logístico y establecer patrones de comportamiento en los mejores países de cada correlación. De acuerdo a los resultados obtenidos de estas correlaciones, se encontró que si existe una relación entre la cultura nacional y el desempeño logístico de un país, al igual que las dimensiones culturales más influyentes para obtener dichos resultados y se identificaron los países que cuentan con condiciones sobresalientes que facilitan tener altas posiciones en el LPI.

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Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

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Modern applications comprise multiple components, such as browser plug-ins, often of unknown provenance and quality. Statistics show that failure of such components accounts for a high percentage of software faults. Enabling isolation of such fine-grained components is therefore necessary to increase the robustness and resilience of security-critical and safety-critical computer systems. In this paper, we evaluate whether such fine-grained components can be sandboxed through the use of the hardware virtualization support available in modern Intel and AMD processors. We compare the performance and functionality of such an approach to two previous software based approaches. The results demonstrate that hardware isolation minimizes the difficulties encountered with software based approaches, while also reducing the size of the trusted computing base, thus increasing confidence in the solution's correctness. We also show that our relatively simple implementation has equivalent run-time performance, with overheads of less than 34%, does not require custom tool chains and provides enhanced functionality over software-only approaches, confirming that hardware virtualization technology is a viable mechanism for fine-grained component isolation.

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Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

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Railroad corridors contain large number of Insulated Rail Joints (IRJs) that act as safety critical elements in the circuitries of the signaling and broken rail identification systems. IRJs are regarded as sources of excitation for the passage of loaded wheels leading to high impact forces; these forces in turn cause dips, cross levels and twists to the railroad geometry in close proximity to the sections containing the IRJs in addition to the local damages to the railhead of the IRJs. Therefore, a systematic monitoring of the IRJs in railroad is prudent to mitigate potential risk of their sudden failure (e.g., broken tie plates) under the traffic. This paper presents a simple method of periodic recording of images using time-lapse photography and total station surveying measurements to understand the ongoing deterioration of the IRJs and their surroundings. Over a 500 day period, data were collected to examine the trends in narrowing of the joint gap due to plastic deformation the railhead edges and the dips, cross levels and twists caused to the railroad geometry due to the settlement of ties (sleepers) around the IRJs. The results reflect that the average progressive settlement beneath the IRJs is larger than that under the continuously welded rail, which leads to excessive deviation of railroad profile, cross levels and twists.

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Crash statistics that include the blood alcohol concentration (BAC) of vehicle operators reveal that crash involved motorcyclists are over represented at low BACs (e.g., ≤0.05%). This riding simulator study compared riding performance and hazard response under three low dose alcohol conditions (sober, 0.02% BAC, 0.05% BAC). Forty participants (20 novice, 20 experienced) completed simulated rides in urban and rural scenarios while responding to a safety-critical peripheral detection task (PDT). Results showed a significant increase in the standard deviation of lateral position in the urban scenario and PDT reaction time in the rural scenario under 0.05% BAC compared with zero alcohol. Participants were most likely to collide with an unexpected pedestrian in the urban scenario at 0.02% BAC, with novice participants at a greater relative risk than experienced riders. Novices chose to ride faster than experienced participants in the rural scenario regardless of BAC. Not all results were significant, emphasising the complex situation of the effects of low dose BAC on riding performance, which needs further research. The results of this simulator study provide some support for a legal BAC for motorcyclists below 0.05%.

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The insulated rail joint (IRJ) is an essential component in a track circuit that controls the signaling system. Failure of IRJs leads to improper functioning of the signals,with potential for catastrophic results. Therefore, IRJs are regarded as safety-critical sections of rail network; hence, all of their components must be maintained in pristine design condition.

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Level crossing risk continues to be a significant safety concern for the security of rail operations around the world. Over the last decade or so, a third of railway related fatalities occurred as a direct result of collisions between road and rail vehicles in Australia. Importantly, nearly half of these collisions occurred at railway level crossings with no active protection, such as flashing lights or boom barriers. Current practice is to upgrade level crossings that have no active protection. However, the total number of level crossings found across Australia exceed 23,500, and targeting the proportion of these that are considered high risk (e.g. public crossings with passive controls) would cost in excess of AU$3.25 billion based on equipment, installation and commissioning costs of warning devices that are currently type approved. Level crossing warning devices that are low-cost provide a potentially effective control for reducing risk; however, over the last decade, there have been significant barriers and legal issues in both Australia and the US that have foreshadowed their adoption. These devices are designed to have significantly lower lifecycle costs compared with traditional warning devices. They often make use of use of alternative technologies for train detection, wireless connectivity and solar energy supply. This paper describes the barriers that have been encountered for the adoption of these devices in Australia, including the challenges associated with: (1) determining requisite safety levels for such devices; (2) legal issues relating to duty of care obligations of railway operators; and (3) issues of Tort liability around the use of less than fail-safe equipment. This paper provides an overview of a comprehensive safety justification that was developed as part of a project funded by a collaborative rail research initiative established by the Australian government, and describes the conceptual framework and processes being used to justify its adoption. The paper provides a summary of key points from peer review and discusses prospective barriers that may need to be overcome for future adoption. A successful outcome from this process would result in the development of a guideline for decision-making, providing a precedence for adopting low-cost level crossing warning devices in other parts of the world. The framework described in this paper also provides relevance to the review and adoption of analogous technologies in rail and other safety critical industries.

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While the exact rate of incidence is unknown (due to the paucity of exposure data), it is acknowledged that safety compromising accidents and incidents occur in the led outdoor activity domain, and that they represent an important issue. Despite this, compared to other safety critical domains, very little is currently known about the key causal factors involved in such accidents and incidents. This report presents the findings derived from a review of the literature, the aim of which was to identify the Human Factors-related issues involved in accidents and incidents occurring in this area. In addition, to demonstrate the utility of systems-based, theoretically underpinned accident analysis methodologies for identifying the systemic and human contribution to accidents and incidents occurring in the led outdoor activity domain, three case-study accidents were analysed using two such approaches. In conclusion, the review identified a range of causal factors cited in the literature; however, it was noted that the majority of the research undertaken to date lacks theoretical underpinning and focuses mainly on instructor or activity leader causal factors, as opposed to the wider system failures involved. The accident analysis presented highlighted the utility of systems-based, theoretically underpinned accident analysis methodologies for analysing and learning from accidents and incidents in the led outdoor activity sector. In closing, the need for further research in the area is articulated, in particular focussing on the development of standardised and universally accepted accident and incident reporting systems and databases, the development of data driven, theoretically underpinned causal factor taxonomies, and the development and application of systems-based accident analysis methodologies.

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Insulated Rail Joints (IRJs) are safety critical component of the automatic block signalling and broken rail detection systems. IRJs exhibit several failure modes due to complex interaction between the railhead ends and the wheel tread near the gap. These localised zones could not be monitored using automatic sensing devices and hence are resorted to visual inspection only, which is error prone and expensive. In Australia alone currently there are 50,000 IRJs across 80,000 km of rail track. The significance of the problem around the world could thus be realised as there exists one IRJ for each 1.6 km track length. IRJs exhibit extremely low and variable service life; further the track substructure underneath IRJs degrade faster. Thus presence of the IRJs incur significant costs to track maintenance. IRJ failures have also contributed to some train derailments and various traffic disruptions in rail lines. This paper reports a systematic research carried out over seven years on the mechanical behaviour of IRJs for practically relevant outcomes. The research has scientifically established that stiffening the track bed for reduction in impact force is an ill-conceived concept and the most effective method is to reduce the gap size. Further it is established that hardening the railhead ends through laser coating (or other) cannot adequately address the metal flow problem in the long run; modification of the railhead profile is the only appropriate technique to completely eliminate the problem. Part of these outcomes has been adopted by the rail infrastructure owners in Australia.

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Objective: The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Background: Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. Method: A multilevel workload model was developed in Study 1 with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters. The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Results: Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. Conclusion: The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Application: Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs. Tactical uses include the dynamic reallocation of resources to meet changes in demand.

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Cooperative Intelligent Transportation Systems (C-ITS) allow in-vehicle systems, and ultimately the driver, to enhance their awareness of their surroundings by enabling communication between vehicles and road infrastructure. C-ITS are widely considered as the next major step in driving assistance systems, aiming at increasing safety, comfort and mobility for drivers. However, any communicating systems are subjected to security threats. A key component for providing secure communications at a large scale is a Public Key Infrastructure (PKI). Due to the safety-critical nature of Vehicle-to-Vehicle (V2V) communications, a C-ITS PKI has functional, performance and scalability requirements that differ from traditional non-automotive environments. This paper identifies and defines the key functional and security requirements for C-ITS PKI systems and analyses proposed C-ITS PKI standards against these requirements. In particular, the proposed US and European C-ITS PKI systems are identified as being too complex and not scalable. The paper also highlights various privacy, security and scalability concerns that should be considered for a secure C-ITS PKI solution in the Australian transport landscape.

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The Australian Naturalistic Driving Study (ANDS), a ground-breaking study of Australian driver behaviour and performance, was officially launched on April 21st, 2015 at UNSW. The ANDS project will provide a realistic perspective on the causes of vehicle crashes and near miss crash events, along with the roles speeding, distraction and other factors have on such events. A total of 360 volunteer drivers across NSW and Victoria - 180 in NSW and 180 in Victoria - will be monitored by a Data Acquisition System (DAS) recording continuously for 4 months their driving behaviour using a suite of cameras and sensors. Participants’ driving behaviour (e.g. gaze), the behaviour of their vehicle (e.g. speed, lane position) and the behaviour of other road users with whom they interact in normal and safety-critical situations will be recorded. Planning of the ANDS commenced over two years ago in June 2013 when the Multi-Institutional Agreement for a grant supporting the equipment purchase and assembly phase was signed by parties involved in this large scale $4 million study (5 university accident research centres, 3 government regulators, 2 third party insurers and 2 industry partners). The program’s second development phase commenced a year later in June 2014 after a second grant was awarded. This paper presents an insider's view into that two year process leading up to the launch, and outlines issues that arose in the set-up phase of the study and how these were addressed. This information will be useful to other organisations considering setting up an NDS.

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Many real-time database applications arise in electronic financial services, safety-critical installations and military systems where enforcing security is crucial to the success of the enterprise. For real-time database systems supporting applications with firm deadlines, we investigate here the performance implications, in terms of killed transactions, of guaranteeing multilevel secrecy. In particular, we focus on the concurrency control (CC) aspects of this issue. Our main contributions are the following: First, we identify which among the previously proposed real-time CC protocols are capable of providing covert-channel-free security. Second, using a detailed simulation model, we profile the real-time performance of a representative set of these secure CC protocols for a variety of security-classified workloads and system configurations. Our experiments show that a prioritized optimistic CC protocol, OPT-WAIT, provides the best overall performance. Third, we propose and evaluate a novel "dual-CC" approach that allows the real-time database system to simultaneously use different CC mechanisms for guaranteeing security and for improving real-time performance. By appropriately choosing these different mechanisms, concurrency control protocols that provide even better performance than OPT-WAIT are designed. Finally, we propose and evaluate GUARD, an adaptive admission-control policy designed to provide fairness with respect to the distribution of killed transactions across security levels. Our experiments show that GUARD efficiently provides close to ideal fairness for real-time applications that can tolerate covert channel bandwidths of upto one bit per second.