993 resultados para Real-time Control


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Staphylococcus aureus is a common pathogen that causes a variety of infections including soft tissue infections, impetigo, septicemia toxic shock and scalded skin syndrome. Traditionally, Methicillin-Resistant Staphylococcus aureus (MRSA) was considered a Hospital-Acquired (HA) infection. It is now recognised that the frequency of infections with MRSA is increasing in the community, and that these infections are not originating from hospital environments. A 2007 report by the Centers for Disease Control and Prevention (CDC) stated that Staphylococcus aureus is the most important cause of serious and fatal infections in the USA. Community-Acquired MRSA (CA-MRSA) are genetically diverse and distinct, meaning they are able to be identified and tracked by way of genotyping. Genotyping of MRSA using Single nucleotide polymorphisms (SNPs) is a rapid and robust method for monitoring MRSA, specifically ST93 (Queensland Clone) dissemination in the community. It has been shown that a large proportion of CA-MRSA infections in Queensland and New South Wales are caused by ST93. The rationale for this project was that SNP analysis of MLST genes is a rapid and cost-effective method for genotyping and monitoring MRSA dissemination in the community. In this study, 16 different sequence types (ST) were identified with 41% of isolates identified as ST93 making it the predominate clone. Males and Females were infected equally with an average patient age of 45yrs. Phenotypically, all of the ST93 had an identical antimicrobial resistance pattern. They were resistant to the β-lactams – Penicillin, Flu(di)cloxacillin and Cephalothin but sensitive to all other antibiotics tested. Virulence factors play an important role in allowing S. aureus to cause disease by way of colonising, replication and damage to the host. One virulence factor of particular interest is the toxin Panton-Valentine leukocidin (PVL), which is composed of two separate proteins encoded by two adjacent genes. PVL positive CA-MRSA are shown to cause recurrent, chronic or severe skin and soft tissue infections. As a result, it is important that PVL positive CA-MRSA is genotyped and tracked. Especially now that CA-MRSA infections are more prevalent than HA-MRSA infections and are now deemed endemic in Australia. 98% of all isolates in this study tested positive for the PVL toxin gene. This study showed that PVL is present in many different community based ST, not just ST93, which were all PVL positive. With this toxin becoming entrenched in CA-MRSA, genotyping would provide more accurate data and a way of tracking the dissemination. PVL gene can be sub-typed using an allele-specific Real-Time PCR (RT-PCR) followed by High resolution meltanalysis. This allows the identification of PVL subtypes within the CA-MRSA population and allow the tracking of these clones in the community.

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Dwell times at stations and inter-station run times are the two major operational parameters to maintain train schedule in railway service. Current practices on dwell-time and run-time control are that they are only optimal with respect to certain nominal traffic conditions, but not necessarily the current service demand. The advantages of dwell-time and run-time control on trains are therefore not fully considered. The application of a dynamic programming approach, with the aid of an event-based model, to devise an optimal set of dwell times and run times for trains under given operational constraints over a regional level is presented. Since train operation is interactive and of multi-attributes, dwell-time and run-time coordination among trains is a multi-dimensional problem. The computational demand on devising trains' instructions, a prime concern in real-time applications, is excessively high. To properly reduce the computational demand in the provision of appropriate dwell times and run times for trains, a DC railway line is divided into a number of regions and each region is controlled by a dwell- time and run-time controller. The performance and feasibility of the controller in formulating the dwell-time and run-time solutions for real-time applications are demonstrated through simulations.

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This paper discusses a new paradigm of real-time simulation of power systems in which equipment can be interfaced with a real-time digital simulator. In this scheme, one part of a power system can be simulated by using a real-time simulator; while the other part is implemeneted as a physical system. The only interface of the physical system with the computer-based simulator is through data-acquisition system. The physical system is driven by a voltage-source converter (VSC)that mimics the power system simulated in the real-time simulator. In this papar, the VSC operates in a voltage-control mode to track the point of common coupling voltage signal supplied by the digital simulator. This type of splitting a network in two parts and running a real-time simulation with a physical system in parallel is called a power network in loop here. this opens up the possibility of study of interconnection o f one or several distributed generators to a complex power network. The proposed implementation is verified through simulation studies using PSCAD/EMTDC and through hardware implementation on a TMS320G2812 DSP.

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Abstract Computer simulation is a versatile and commonly used tool for the design and evaluation of systems with different degrees of complexity. Power distribution systems and electric railway network are areas for which computer simulations are being heavily applied. A dominant factor in evaluating the performance of a software simulator is its processing time, especially in the cases of real-time simulation. Parallel processing provides a viable mean to reduce the computing time and is therefore suitable for building real-time simulators. In this paper, we present different issues related to solving the power distribution system with parallel computing based on a multiple-CPU server and we will concentrate, in particular, on the speedup performance of such an approach.

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A number of advanced driver assistance systems (ADAS) are currently being released on the market, providing safety functions to the drivers such as collision avoidance, adaptive cruise control or enhanced night-vision. These systems however are inherently limited by their sensory range: they cannot gather information from outside this range, also called their “perceptive horizon”. Cooperative systems are a developing research avenue that aims at providing extended safety and comfort functionalities by introducing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications to the road actors. This paper presents the problematic of cooperative systems, their advantages and contributions to road safety and exposes some limitations related to market penetration, sensors accuracy and communications scalability. It explains the issues of how to implement extended perception, a central contribution of cooperative systems. The initial steps of an evaluation of data fusion architectures for extended perception are exposed.

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Coral reefs are biologically complex ecosystems that support a wide variety of marine organisms. These are fragile communities under enormous threat from natural and human-based influences. Properly assessing and measuring the growth and health of reefs is essential to understanding impacts of ocean acidification, coastal urbanisation and global warming. In this paper, we present an innovative 3-D reconstruction technique based on visual imagery as a non-intrusive, repeatable, in situ method for estimating physical parameters, such as surface area and volume for efficient assessment of long-term variability. The reconstruction algorithms are presented, and benchmarked using an existing data set. We validate the technique underwater, utilising a commercial-off-the-shelf camera and a piece of staghorn coral, Acropora cervicornis. The resulting reconstruction is compared with a laser scan of the coral piece for assessment and validation. The comparison shows that 77% of the pixels in the reconstruction are within 0.3 mm of the ground truth laser scan. Reconstruction results from an unknown video camera are also presented as a segue to future applications of this research.

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Embedded real-time programs rely on external interrupts to respond to events in their physical environment in a timely fashion. Formal program verification theories, such as the refinement calculus, are intended for development of sequential, block-structured code and do not allow for asynchronous control constructs such as interrupt service routines. In this article we extend the refinement calculus to support formal development of interrupt-dependent programs. To do this we: use a timed semantics, to support reasoning about the occurrence of interrupts within bounded time intervals; introduce a restricted form of concurrency, to model composition of interrupt service routines with the main program they may preempt; introduce a semantics for shared variables, to model contention for variables accessed by both interrupt service routines and the main program; and use real-time scheduling theory to discharge timing requirements on interruptible program code.

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In this paper a real-time vision based power line extraction solution is investigated for active UAV guidance. The line extraction algorithm starts from ridge points detected by steerable filters. A collinear line segments fitting algorithm is followed up by considering global and local information together with multiple collinear measurements. GPU boosted algorithm implementation is also investigated in the experiment. The experimental result shows that the proposed algorithm outperforms two baseline line detection algorithms and is able to fitting long collinear line segments. The low computational cost of the algorithm make suitable for real-time applications.

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This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.

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Widespread adoption by electricity utilities of Non-Conventional Instrument Transformers, such as optical or capacitive transducers, has been limited due to the lack of a standardised interface and multi-vendor interoperability. Low power analogue interfaces are being replaced by IEC 61850 9 2 and IEC 61869 9 digital interfaces that use Ethernet networks for communication. These ‘process bus’ connections achieve significant cost savings by simplifying connections between switchyard and control rooms; however the in-service performance when these standards are employed is largely unknown. The performance of real-time Ethernet networks and time synchronisation was assessed using a scale model of a substation automation system. The test bed was constructed from commercially available timing and protection equipment supplied by a range of vendors. Test protocols have been developed to thoroughly evaluate the performance of Ethernet networks and network based time synchronisation. The suitability of IEEE Std 1588 Precision Time Protocol (PTP) as a synchronising system for sampled values was tested in the steady state and under transient conditions. Similarly, the performance of hardened Ethernet switches designed for substation use was assessed under a range of network operating conditions. This paper presents test methods that use a precision Ethernet capture card to accurately measure PTP and network performance. These methods can be used for product selection and to assess ongoing system performance as substations age. Key findings on the behaviour of multi-function process bus networks are presented. System level tests were performed using a Real Time Digital Simulator and transformer protection relay with sampled value and Generic Object Oriented Substation Events (GOOSE) capability. These include the interactions between sampled values, PTP and GOOSE messages. Our research has demonstrated that several protocols can be used on a shared process bus, even with very high network loads. This should provide confidence that this technology is suitable for transmission substations.

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This project researched the performance of emerging digital technology for high voltage electricity substations that significantly improves safety for staff and reduces the potential impact on the environment of equipment failure. The experimental evaluation used a scale model of a substation control system that incorporated real substation control and networking equipment with real-time simulation of the power system. The outcomes confirm that it is possible to implement Ethernet networks in high voltage substations that meet the needs of utilities; however component-level testing of devices is necessary to achieve this. The assessment results have been used to further develop international standards for substation communication and precision timing.

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The existence of Macroscopic Fundamental Diagram (MFD), which relates space-mean density and flow, has been shown in urban networks under homogeneous traffic conditions. Since MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. One of the key requirements for well-defined MFD is the homogeneity of the area-wide traffic condition with links of similar properties, which is not universally expected in real world. For the practical application of the MFD concept, several researchers have identified the influencing factors for network homogeneity. However, they did not explicitly take the impact of drivers’ behaviour and information provision into account, which has a significant impact on simulation outputs. This research aims to demonstrate the effect of dynamic information provision on network performance by employing the MFD as a measurement. A microscopic simulation, AIMSUN, is chosen as an experiment platform. By changing the ratio of en-route informed drivers and pre-trip informed drivers different scenarios are simulated in order to investigate how drivers’ adaptation to the traffic congestion influences the network performance with respect to the MFD shape as well as other indicators, such as total travel time. This study confirmed the impact of information provision on the MFD shape, and addressed the usefulness of the MFD for measuring the dynamic information provision benefit.

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This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.