992 resultados para Real-time data processing
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Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.
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Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.
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This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.
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Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.
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An array of Bio-Argo floats equipped with radiometric sensors has been recently deployed in various open ocean areas representative of the diversity of trophic and bio-optical conditions prevailing in the so-called Case 1 waters. Around solar noon and almost everyday, each float acquires 0-250 m vertical profiles of Photosynthetically Available Radiation and downward irradiance at three wavelengths (380, 412 and 490 nm). Up until now, more than 6500 profiles for each radiometric channel have been acquired. As these radiometric data are collected out of operator’s control and regardless of meteorological conditions, specific and automatic data processing protocols have to be developed. Here, we present a data quality-control procedure aimed at verifying profile shapes and providing near real-time data distribution. This procedure is specifically developed to: 1) identify main issues of measurements (i.e. dark signal, atmospheric clouds, spikes and wave-focusing occurrences); 2) validate the final data with a hierarchy of tests to ensure a scientific utilization. The procedure, adapted to each of the four radiometric channels, is designed to flag each profile in a way compliant with the data management procedure used by the Argo program. Main perturbations in the light field are identified by the new protocols with good performances over the whole dataset. This highlights its potential applicability at the global scale. Finally, the comparison with modeled surface irradiances allows assessing the accuracy of quality-controlled measured irradiance values and identifying any possible evolution over the float lifetime due to biofouling and instrumental drift.
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An array of Bio-Argo floats equipped with radiometric sensors has been recently deployed in various open ocean areas representative of the diversity of trophic and bio-optical conditions prevailing in the so-called Case 1 waters. Around solar noon and almost everyday, each float acquires 0-250 m vertical profiles of Photosynthetically Available Radiation and downward irradiance at three wavelengths (380, 412 and 490 nm). Up until now, more than 6500 profiles for each radiometric channel have been acquired. As these radiometric data are collected out of operator’s control and regardless of meteorological conditions, specific and automatic data processing protocols have to be developed. Here, we present a data quality-control procedure aimed at verifying profile shapes and providing near real-time data distribution. This procedure is specifically developed to: 1) identify main issues of measurements (i.e. dark signal, atmospheric clouds, spikes and wave-focusing occurrences); 2) validate the final data with a hierarchy of tests to ensure a scientific utilization. The procedure, adapted to each of the four radiometric channels, is designed to flag each profile in a way compliant with the data management procedure used by the Argo program. Main perturbations in the light field are identified by the new protocols with good performances over the whole dataset. This highlights its potential applicability at the global scale. Finally, the comparison with modeled surface irradiances allows assessing the accuracy of quality-controlled measured irradiance values and identifying any possible evolution over the float lifetime due to biofouling and instrumental drift.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.
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The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.
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Objective: Aspergillus species are the main pathogens causing invasive fungal infections but the prevalence of other mould species is rising. Resistance to antifungals among these new emerging pathogens presents a challenge for managing of infections. Conventional susceptibility testing of non-Aspergillus species is laborious and often difficult to interpret. We evaluated a new method for real-time susceptibility testing of moulds based on their of growth-related heat production.Methods: Laboratory and clinical strains of Mucor spp. (n = 4), Scedoporium spp. (n = 4) and Fusarium spp. (n = 5) were used. Conventional MIC was determined by microbroth dilution. Isothermal microcalorimetry was performed at 37 C using Sabouraud dextrose broth (SDB) inoculated with 104 spores/ml (determined by microscopical enumeration). SDB without antifungals was used for evaluation of growth characteristics. Detection time was defined as heat flow exceeding 10 lW. For susceptibility testing serial dilutions of amphotericin B, voriconazole, posaconazole and caspofungin were used. The minimal heat inhibitory concentration (MHIC) was defined as the lowest antifungal concentration, inhbiting 50% of the heat produced by the growth control at 48 h or at 24 h for Mucor spp. Susceptibility tests were performed in duplicate.Results: Tested mould genera had distinctive heat flow profiles with a median detection time (range) of 3.4 h (1.9-4.1 h) for Mucor spp, 11.0 h (7.1-13.7 h) for Fusarium spp and 29.3 h (27.4-33.0 h) for Scedosporium spp. Graph shows heat flow (in duplicate) of one representative strain from each genus (dashed line marks detection limit). Species belonging to the same genus showed similar heat production profiles. Table shows MHIC and MIC ranges for tested moulds and antifungals.Conclusions: Microcalorimetry allowed rapid detection of growth of slow-growing species, such as Fusarium spp. and Scedosporium spp. Moreover, microcalorimetry offers a new approach for antifungal susceptibility testing of moulds, correlating with conventional MIC values. Interpretation of calorimetric susceptibility data is easy and real-time data on the effect of different antifungals on the growth of the moulds is additionally obtained. This method may be used for investigation of different mechanisms of action of antifungals, new substances and drug-drug combinations.
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L’objectiu d’aquest PFC és desenvolupar un sistema de pluja per a videojocs i aplicacions de realitat virtual que sigui acurat, tant en el sentit del realisme visual com del seu comportament. El projecte permetrà al desenvolupador de videojocs incorporar a les seves aplicacions, zones de pluja amb diferents intensitats utilitzant el hardware gràfic més modern, per així evitar que aquesta pluja sigui processada per la CPU i per tant pugui alentir el videojoc que està creant. S’han desenvolupat dos sistemes, el sistema d’edició de pluja i el de visualització en temps real
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The real time hardware architecture of a deterministic video echo canceller (deghoster) system is presented. The deghoster is capable of calculating all the multipath channel distortion characteristics from terrestrial and cable television in one single pass while performing real time video in-line ghost cancellation. The results from the actual system are also presented in this paper.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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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.