483 resultados para operating systems


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Emission spectroscopy was used to investigate ignition and combustion characteristics of supersonic combustion ramjet engines. Two-dimensional scramjet models with inlet injection, fuelled with hydrogen gas, were used in the study. The scramjet engines were configured to operate in radical farming mode, where combustion radicals are formed behind shock waves reflected at the walls. The chemiluminescence emission signals were recorded in a two-dimensional, time-integrated fashion to give information on the location and distribution of the radical farms in the combustors. High signal levels were detected in localised regions immediately downstream of shock reflections, an indication of localised hydroxyl formation supporting the concept of radical farming. Results are presented for a symmetric as well as an asymmetric scramjet geometry. These data represent the first successful visualisation of radical farms in the hot pockets of a supersonic combustor. Spectrally resolved measurements have been obtained in the ultraviolet wavelength range between 300 and 400 nm. This data shows that the OH! chemiluminescence signal around 306nm is not the most dominant source of radiation observed in the radical farms.

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This paper sets out to contribute to the literature on the design and the implementation of management control systems. To this end, we question what is discussed when a management control system is to be chosen and on what decision-making eventually rests. This study rests upon an ethnomethodology of the Salvation Army’s French branch. Operating in the dual capacity of a researcher and a counsellor to management, between 2000 and 2007, we have unrestricted access to internal data revealing the backstage of management control: discussions and interactions surrounding the choosing of control devices. We contribute to understanding the arising of a need for control, the steps and process followed to decide upon a management control system, and controls in nonprofits. [Cet article vise à contribuer à la littérature sur la mise en place des systèmes de contrôle de gestion. À cette fin, nous questionnons ce qui est discuté lors du choix d’un système de contrôle et sur quoi repose in fine la décision. Cet article est fondé sur une approche ethnométhodologique de l’Armée du Salut en France permise par notre double qualité de chercheurs mais également de conseiller auprès de la direction de l’organisation entre 2000 et 2007. Un accès illimité à des données internes nous permet ainsi de mettre en lumière les aspects méconnus et invisibles du contrôle de gestion : les discussions et interactions entourant le choix d’outils. Nous contribuons à la compréhension de l’émergence du besoin de contrôle, des étapes et du processus de choix d’outils et enfin du contrôle de gestion dans une organisation à but non lucratif.]

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Intelligent Transport System (ITS) technology is seen as a cost-effective way to increase the conspicuity of approaching trains and the effectiveness of train warnings at level crossings by providing an in-vehicle warning of an approaching train. The technology is often seen as a potential low-cost alternative to upgrading passive level crossings with traditional active warning systems (flashing lights and boom barriers). ITS platforms provide sensor, localization and dedicated short-range communication (DSRC) technologies to support cooperative applications such as collision avoidance for road vehicles. In recent years, in-vehicle warning systems based on ITS technology have been trialed at numerous locations around Australia, at level crossing sites with active and passive controls. While significant research has been conducted on the benefits of the technology in nominal operating modes, little research has focused on the effects of the failure modes, the human factors implications of unreliable warnings and the technology adoption process from the railway industry’s perspective. Many ITS technology suppliers originate from the road industry and often have limited awareness of the safety assurance requirements, operational requirements and legal obligations of railway operators. This paper aims to raise awareness of these issues and start a discussion on how such technology could be adopted. This paper will describe several ITS implementation cenarios and discuss failure modes, human factors considerations and the impact these scenarios are likely to have in terms of safety, railway safety assurance requirements and the practicability of meeting these requirements. The paper will identify the key obstacles impeding the adoption of ITS systems for the different implementation scenarios and a possible path forward towards the adoption of ITS technology.

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The results of large-scale (∼109 atoms) numerical simulations of the growth of different-diameter vertically-aligned single-walled carbon nanotubes in plasma systems with different sheath widths and in neutral gases with the same operating parameters are reported. It is shown that the nanotube lengths and growth rates can be effectively controlled by varying the process conditions. The SWCNT growth rates in the plasma can be up to two orders of magnitude higher than in the equivalent neutral gas systems. Under specific process conditions, thin SWCNTs can grow much faster than their thicker counterparts despite the higher energies required for catalyst activation and nanotube nucleation. This selective growth of thin SWCNTs opens new avenues for the solution of the currently intractable problem of simultaneous control of the nanotube chirality and length during the growth stage.

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A solar assisted heat pump is used for different applications, such as, water heating, drying and air conditioning. The unglazed evaporator-collector enables to absorb both solar energy and ambient energy due to low operating temperature. Three different systems are described: solar assisted heat pump system for hot water using an unglazed evaporator collector; solar assisted heat pump for hot water and drying, where evaporator collector and air collector are used; an integrated solar heat pump system making use of solar and ambient energy, and air-con waste heat. Unlike conventional collector, evaporator collector was found to have higher efficiency, 80% to 90%, and the coefficient of performance attained a value as high as 8.0. The integrated system leads to a reduction of global warming, as it uses solar energy, ambient energy and air-con waste heat.

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An opportunistic relay selection scheme improving cooperative diversity is devised using the concept of a virtual SIMO-MISO antenna array. By incorporating multiple users as a virtual distributed antenna, not only helps combat fading but also provides significant advantage in terms of energy consumption. The proposed efficient multiple relay selection uses the concept of the distributed Alamouti scheme in a time varying environment to realize cooperative networking in wireless relay networks and provides the platform for outage, Diversiy-Multiplexing Tradeoff (DMT) and Bit-Error-Rate (BER) analysis to conclude that it is capable of achieving promising diversity gains by operating at much lower SNR when compared with conventional relay selection methods. It also has the added advantage of conserving energy for the relays that are reachable but not selected for the cooperative communication.

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Partial shading and rapidly changing irradiance conditions significantly impact on the performance of photovoltaic (PV) systems. These impacts are particularly severe in tropical regions where the climatic conditions result in very large and rapid changes in irradiance. In this paper, a hybrid maximum power point (MPP) tracking (MPPT) technique for PV systems operating under partially shaded conditions witapid irradiance change is proposed. It combines a conventional MPPT and an artificial neural network (ANN)-based MPPT. A low cost method is proposed to predict the global MPP region when expensive irradiance sensors are not available or are not justifiable for cost reasons. It samples the operating point on the stairs of I–V curve and uses a combination of the measured current value at each stair to predict the global MPP region. The conventional MPPT is then used to search within the classified region to get the global MPP. The effectiveness of the proposed MPPT is demonstrated using both simulations and an experimental setup. Experimental comparisons with four existing MPPTs are performed. The results show that the proposed MPPT produces more energy than the other techniques and can effectively track the global MPP with a fast tracking speed under various shading patterns.

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We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

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This thesis presents a new vision-based decision and control strategy for automated aircraft collision avoidance that can be realistically applied to the See and Avoid problem. The effectiveness of the control strategy positions the research as a major contribution toward realising the simultaneous operation of manned and unmanned aircraft within civilian airspace. Key developments include novel classical and visual predictive control frameworks, and a performance evaluation technique aligned with existing aviation practise and applicable to autonomous systems. The overall approach is demonstrated through experimental results on a small multirotor unmanned aircraft, and through high fidelity probabilistic simulation studies.

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The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

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This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.

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With new national targets for patient flow in public hospitals designed to increase efficiencies in patient care and resource use, better knowledge of events affecting length of stay will support improved bed management and scheduling of procedures. This paper presents a case study involving the integration of material from each of three databases in operation at one tertiary hospital and demonstrates it is possible to follow patient journeys from admission to discharge. What is known about this topic? At present, patient data at one Queensland tertiary hospital are assembled in three information systems: (1) the Hospital Based Corporate Information System (HBCIS), which tracks patients from in-patient admission to discharge; (2) the Emergency Department Information System (EDIS) containing patient data from presentation to departure from the emergency department; and (3) Operation Room Management Information System (ORMIS), which records surgical operations. What does this paper add? This paper describes how a new enquiry tool may be used to link the three hospital information systems for studying the hospital journey through different wards and/or operating theatres for both individual and groups of patients. What are the implications for practitioners? An understanding of the patients’ journeys provides better insight into patient flow and provides the tool for research relating to access block, as well as optimising the use of physical and human resources.

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In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. In this paper, a novel job shop approach is proposed to create a more efficient integrated harvesting and sugarcane transport scheduling system to reduce the cost of sugarcane transport. There are several benefits that can be attained by treating the train scheduling problem as a job shop problem. Job shop is generic and suitable for all trains scheduling problems. Job shop technique prevents operating two trains on one section at the same time because it considers that the section or the machine is unique. This technique is more promising to find better solutions in reasonable computation times.