970 resultados para hard real-time system


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This paper presents a distribution feeder simulation using VHDL-AMS, considering the standard IEEE 13 node test feeder admitted as an example. In an electronic spreadsheet all calculations are performed in order to develop the modeling in VHDL-AMS. The simulation results are compared in relation to the results from the well knowing MatLab/Simulink environment, in order to verify the feasibility of the VHDL-AMS modeling for a standard electrical distribution feeder, using the software SystemVision™. This paper aims to present the first major developments for a future Real-Time Digital Simulator applied to Electrical Power Distribution Systems. © 2012 IEEE.

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Wireless LANs are growing rapidly and security has always been a concern. We have implemented a hybrid system, which will not only detect active attacks like identity theft causing denial of service attacks, but will also detect the usage of access point discovery tools. The system responds in real time by sending out an alert to the network administrator.

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Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

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The development of High-Integrity Real-Time Systems has a high footprint in terms of human, material and schedule costs. Factoring functional, reusable logic in the application favors incremental development and contains costs. Yet, achieving incrementality in the timing behavior is a much harder problem. Complex features at all levels of the execution stack, aimed to boost average-case performance, exhibit timing behavior highly dependent on execution history, which wrecks time composability and incrementaility with it. Our goal here is to restitute time composability to the execution stack, working bottom up across it. We first characterize time composability without making assumptions on the system architecture or the software deployment to it. Later, we focus on the role played by the real-time operating system in our pursuit. Initially we consider single-core processors and, becoming less permissive on the admissible hardware features, we devise solutions that restore a convincing degree of time composability. To show what can be done for real, we developed TiCOS, an ARINC-compliant kernel, and re-designed ORK+, a kernel for Ada Ravenscar runtimes. In that work, we added support for limited-preemption to ORK+, an absolute premiere in the landscape of real-word kernels. Our implementation allows resource sharing to co-exist with limited-preemptive scheduling, which extends state of the art. We then turn our attention to multicore architectures, first considering partitioned systems, for which we achieve results close to those obtained for single-core processors. Subsequently, we shy away from the over-provision of those systems and consider less restrictive uses of homogeneous multiprocessors, where the scheduling algorithm is key to high schedulable utilization. To that end we single out RUN, a promising baseline, and extend it to SPRINT, which supports sporadic task sets, hence matches real-world industrial needs better. To corroborate our results we present findings from real-world case studies from avionic industry.

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La tesi tratta lo studio del sistema QNX e dello sviluppo di un simulatore di task hard/soft real-time, tramite uso di un meta-scheduler. Al termine dello sviluppo vengono valutate le prestazioni del sistema operativo QNX Neutrino.

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An algorithm for the real-time registration of a retinal video sequence captured with a scanning digital ophthalmoscope (SDO) to a retinal composite image is presented. This method is designed for a computer-assisted retinal laser photocoagulation system to compensate for retinal motion and hence enhance the accuracy, speed, and patient safety of retinal laser treatments. The procedure combines intensity and feature-based registration techniques. For the registration of an individual frame, the translational frame-to-frame motion between preceding and current frame is detected by normalized cross correlation. Next, vessel points on the current video frame are identified and an initial transformation estimate is constructed from the calculated translation vector and the quadratic registration matrix of the previous frame. The vessel points are then iteratively matched to the segmented vessel centerline of the composite image to refine the initial transformation and register the video frame to the composite image. Criteria for image quality and algorithm convergence are introduced, which assess the exclusion of single frames from the registration process and enable a loss of tracking signal if necessary. The algorithm was successfully applied to ten different video sequences recorded from patients. It revealed an average accuracy of 2.47 ± 2.0 pixels (∼23.2 ± 18.8 μm) for 2764 evaluated video frames and demonstrated that it meets the clinical requirements.

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The COSMIC-2 mission is a follow-on mission of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) with an upgraded payload for improved radio occultation (RO) applications. The objective of this paper is to develop a near-real-time (NRT) orbit determination system, called NRT National Chiao Tung University (NCTU) system, to support COSMIC-2 in atmospheric applications and verify the orbit product of COSMIC. The system is capable of automatic determinations of the NRT GPS clocks and LEO orbit and clock. To assess the NRT (NCTU) system, we use eight days of COSMIC data (March 24-31, 2011), which contain a total of 331 GPS observation sessions and 12 393 RO observable files. The parallel scheduling for independent GPS and LEO estimations and automatic time matching improves the computational efficiency by 64% compared to the sequential scheduling. Orbit difference analyses suggest a 10-cm accuracy for the COSMIC orbits from the NRT (NCTU) system, and it is consistent as the NRT University Corporation for Atmospheric Research (URCA) system. The mean velocity accuracy from the NRT orbits of COSMIC is 0.168 mm/s, corresponding to an error of about 0.051 μrad in the bending angle. The rms differences in the NRT COSMIC clock and in GPS clocks between the NRT (NCTU) and the postprocessing products are 3.742 and 1.427 ns. The GPS clocks determined from a partial ground GPS network [from NRT (NCTU)] and a full one [from NRT (UCAR)] result in mean rms frequency stabilities of 6.1E-12 and 2.7E-12, respectively, corresponding to range fluctuations of 5.5 and 2.4 cm and bending angle errors of 3.75 and 1.66 μrad .

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The previously described Nc5-specific PCR test for the diagnosis of Neospora caninum infections was used to develop a quantitative PCR assay which allows the determination of infection intensities within different experimental and diagnostic sample groups. The quantitative PCR was performed by using a dual fluorescent hybridization probe system and the LightCycler Instrument for online detection of amplified DNA. This assay was successfully applied for demonstrating the parasite proliferation kinetics in organotypic slice cultures of rat brain which were infected in vitro with N. caninum tachyzoites. This PCR-based method of parasite quantitation with organotypic brain tissue samples can be regarded as a novel ex vivo approach for exploring different aspects of cerebral N. caninum infection.

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PURPOSE To evaluate the accuracy, safety, and efficacy of cervical nerve root injection therapy using magnetic resonance guidance in an open 1.0 T MRI system. METHODS Between September 2009 and April 2012, a total of 21 patients (9 men, 12 women; mean age 47.1 ± 11.1 years) underwent MR-guided cervical periradicular injection for cervical radicular pain in an open 1.0 T system. An interactive proton density-weighted turbo spin echo (PDw TSE) sequence was used for real-time guidance of the MR-compatible 20-gauge injection needle. Clinical outcome was evaluated on a verbal numeric rating scale (VNRS) before injection therapy (baseline) and at 1 week and 1, 3, and 6 months during follow-up. RESULTS All procedures were technically successful and there were no major complications. The mean preinterventional VNRS score was 7.42 and exhibited a statistically significant decrease (P < 0.001) at all follow-up time points: 3.86 ± 1.53 at 1 week, 3.21 ± 2.19 at 1 month, 2.58 ± 2.54 at 3 months, and 2.76 ± 2.63 at 6 months. At 6 months, 14.3 % of the patients reported complete resolution of radicular pain and 38.1 % each had either significant (4-8 VNRS score points) or mild (1-3 VNRS score points) relief of pain; 9.5 % experienced no pain relief. CONCLUSION Magnetic resonance fluoroscopy-guided periradicular cervical spine injection is an accurate, safe, and efficacious treatment option for patients with cervical radicular pain. The technique may be a promising alternative to fluoroscopy- or CT-guided injections of the cervical spine, especially in young patients and in patients requiring repeat injections.

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In this paper we present an adaptive multi-camera system for real time object detection able to efficiently adjust the computational requirements of video processing blocks to the available processing power and the activity of the scene. The system is based on a two level adaptation strategy that works at local and at global level. Object detection is based on a Gaussian mixtures model background subtraction algorithm. Results show that the system can efficiently adapt the algorithm parameters without a significant loss in the detection accuracy.