980 resultados para real-time system


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As a highly urbanized and flood prone region, Flanders has experienced multiple floods causing significant damage in the past. In response to the floods of 1998 and 2002 the Flemish Environment Agency, responsible for managing 1 400 km of unnavigable rivers, started setting up a real time flood forecasting system in 2003. Currently the system covers almost 2 000 km of unnavigable rivers, for which flood forecasts are accessible online (www.waterinfo.be). The forecasting system comprises more than 1 000 hydrologic and 50 hydrodynamic models which are supplied with radar rainfall, rainfall forecasts and on-site observations. Forecasts for the next 2 days are generated hourly, while 10 day forecasts are generated twice a day. Additionally, twice daily simulations based on percentile rainfall forecasts (from EPS predictions) result in uncertainty bands for the latter. Subsequent flood forecasts use the most recent rainfall predictions and observed parameters at any time while uncertainty on the longer-term is taken into account. The flood forecasting system produces high resolution dynamic flood maps and graphs at about 200 river gauges and more than 3 000 forecast points. A customized emergency response system generates phone calls and text messages to a team of hydrologists initiating a pro-active response to prevent upcoming flood damage. The flood forecasting system of the Flemish Environment Agency is constantly evolving and has proven to be an indispensable tool in flood crisis management. This was clearly the case during the November 2010 floods, when the agency issued a press release 2 days in advance allowing water managers, emergency services and civilians to take measures.

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Sharing sensor data between multiple devices and users can be^challenging for naive users, and requires knowledge of programming and use of different communication channels and/or development tools, leading to non uniform solutions. This thesis proposes a system that allows users to access sensors, share sensor data and manage sensors. With this system we intent to manage devices, share sensor data, compare sensor data, and set policies to act based on rules. This thesis presents the design and implementation of the system, as well as three case studies of its use.

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Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

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Condition monitoring is used to increase machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient real time vibration measurement and analysis instruments is capable of providing warning and predicting faults at early stages. In this paper, a new methodology for the implementation of vibration measurement and analysis instruments in real time based on circuit architecture mapped from a MATLAB/Simulink model is presented. In this study, signal processing applications such as FIR filters and fast Fourier transform are treated as systems, which are implemented in hardware using a system generator toolbox, which translates a Simulink model in a hardware description language - HDL for FPGA implementations.

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Quartz Crystal Microbalance (QCM) was used to monitor the mass changes on a quartz crystal surface containing immobilized lectins that interacted with carbohydrates. The strategy for lectin immobilization was developed on the basis of a multilayer system composed of Au-cystamine-glutaraldehyde-lectin. Each step of the immobilization procedure was confirmed by FTIR analysis. The system was used to study the interactions of Concanavalin A (ConA) with maltose and Jacalin with Fetuin. The real-time binding of different concentrations of carbohydrate to the immobilized lectin was monitored by means of QCM measurements and the data obtained allowed for the construction of Langmuir isotherm curves. The association constants determined for the specific interactions analyzed here were (6.4 +/- 0.2) X 10(4) M-1 for Jacalin-Fetuin and (4.5 +/- 0.1) x 10(2) M-1 for ConA-maltose. These results indicate that the QCM constitutes a suitable method for the analysis of lectin-carbohydrate interactions, even when assaying low molecular mass ligands such as disaccharides. Published by Elsevier B.V.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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O objetivo deste trabalho foi validar, pela técnica de PCR quantitativo em tempo real (RT-qPCR) genes para serem utilizados como referência em estudos de expressão gênica em soja, em ensaios de estresse hídrico. Foram avaliados quatro genes comumente utilizados em soja: Gmβ-actin, GmGAPDH, GmLectin e GmRNAr18S. O RNA total foi extraído de seis amostras: três amostras de raízes em sistema de hidroponia com diferentes intensidades de déficit hídrico (0, 25, 50, 75 e 100 minutos de estresse hídrico), e três amostras de folhas de plantas cultivadas em areia com diferentes umidades do solo (15, 5 e 2,5% de umidade gravimétrica). Os dados brutos do intervalo cycle threshold (Ct) foram analisados, e a eficiência de cada iniciador foi calculada para uma analise da Ct entre as diferentes amostras. A aplicação do programa GeNorm foi utilizada para a avaliação dos melhores genes de referência, de acordo com a estabilidade. O GmGAPDH foi o gene menos estável, com o maior valor médio de estabilidade de expressão (M), e os genes mais estáveis, com menor valor de M, foram o Gmβ-actin e GmRNAr18S, tanto nas amostras de raízes como nas de folhas. Estes genes podem ser usados em RT-qPCR como gens de referência para análises de expressão gênica.

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Quantitative real time PCR was performed on genomic DNA from 40 primary oral carcinomas and the normal adjacent tissues. The target genes ECGFB, DIA1, BIK, and PDGFB and the microsatellite markers D22S274 and D22S277, mapped on 22q13, were selected according to our previous loss of heterozygosity findings in head and neck tumors. Quantitative PCR relies on the comparison of the amount of product generated from a target gene and that generated from a disomic reference gene (GAPDH-housekeeping gene). Reactions have been performed with normal control in triplicates, using the 7700 Sequence Detection System (PE Applied Biosystems). Losses in the sequences D22S274 (22q13.31) and in the DIA1 (22q13.2-13.31) gene were detected in 10 out of 40 cases (25%) each. Statistically significant correlations were observed for patients with relative copy number loss of the marker D22S274 and stages T3-T4 of disease (P=0.025), family history of cancer (P = 0.001), and death (P = 0.021). Relative copy number loss involving the DIA1 gene was correlated to family history of cancer (P<0.001), death (P=0.002), and consumption of alcohol (P=0.026). Log-rank test revealed a significant decrease in survival (P=0.0018) for patients with DIA1 gene loss. Relative copy number losses detected in these sequences may be related to disease progression and a worse prognosis in patients with oral cancer.

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This work analyses a real time orbit estimator using the raw navigation solution provided by GPS receivers. The estimation algorithm considers a Kalman filter with a rather simple orbit dynamic model and random walk modeling of the receiver clock bias and drift. Using the Topex/Poseidon satellite as test bed, characteristics of model truncation, sampling rates and degradation of the GPS receiver (Selective Availability) were analysed. Copyright © 2007 by ABCM.

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In the last decades there was a great development in the study of control systems to attenuate the harmful effect of natural events in great structures, as buildings and bridges. Magnetorheological fluid (MR), that is an intelligent material, has been considered in many proposals of project for these controllers. This work presents the controller design using feedback of states through LMI (Linear Matrix Inequalities) approach. The experimental test were carried out in a structure with two degrees of freedom with a connected shock absorber MR. Experimental tests were realized in order to specify the features of this semi-active controller. In this case, there exist states that are not measurable, so the feedback of the states involves the project of an estimator. The coupling of the MR damper causes a variation in dynamics properties, so an identification methods, based on experimental input/output signal was used to compare with the numerical application. The identification method of Prediction Error Methods - (PEM) was used to find the physical characteristics of the system through realization in modal space of states. This proposal allows the project of a semi-active control, where the main characteristic is the possibility of the variation of the damping coefficient.

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This work aims to demonstrate an application of telemetry for monitoring process variables. The authors developed the prototype of a dedicated device capable of multiplexing, encoding and transmitting real-time data signals via amplitude-shift keying modulation to remotely located device(s). The prototype development is described in details, enabling the reproduction of the proposed telemetry system for a three-phase motor as well as for other devices. Furthermore, the proposed device has an easy implementation by using of accessible components and low cost, also presenting a tutorial and educational purpose. © 2011 IEEE.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This study presents a new recombinant protein that acts as a powerful antiviral (rAVLO—recombinant Antiviral protein of Lonomia obliqua). It was able to reduce the replication by 106 fold for herpes virus and by 104 fold for rubella virus. RT-PCR of viral RNA rAVLO treated infected cells also showed similar rate of inhibition in replication. The analysis of this protein by bioinformatics suggests that this protein is globular, secreted with a signal peptide and has the ability to bind to MHC class I. It was found that there are several protein binding sites with various HLA and a prevalence of α-helices in the N-terminal region (overall classified as a α/β protein type). BLAST similarity sequence search for corresponding cDNA did not reveal a similar sequence in Genbank, suggesting that it is from a novel protein family. In this study we have observed that this recombinant protein and hemolymph has a potent antiviral action. This protein was produced in a baculovirus/Sf-9 system. Therefore, these analyses suggest that this novel polypeptide is a candidate as a broad spectrum antiviral.

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The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).