887 resultados para Data acquisition system


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The State of Paraíba is one of the most dynamic states of Brazil, strategically located in the northeast, is notable for the excellent potential for integration of different transportation modes forming the states of Rio Grande do Norte, Pernambuco and Alagoas. The dynamic that occurs with port activity causes changes in the space where it is installed. And the elements of this space are always more than suffering direct or indirect influences as the flow in the port is expanded. Therefore, this region became subject to the accidental spillage of oil, because it presents a heavy traffic of ships of various sizes that can run aground or collide with oil causing accidental events. The study of geomorphological and sedimentological compositions of seafloor becomes important as more is known about the relationships between these parameters and associated fauna, and can identify their preferred habitats. The database background, acoustically collected along the proposed study area, is a wealth of information, which were duly examined, cataloged and made available. Such information can serve as an important tool, providing a geomorphological survey of the sedimentary area studied, and come to subsidize, in a flexible, future decision making. With the study area Port of Cabedelo, Paraíba - Brazil, this research aimed to evaluate the influence of the tidal surface and background in modeling the seabed, including the acquisition of information about the location of submerged rocky bodies and the depth of these bodies may turn out to be natural traps for the trapping of oil in case of leaks, and obtain the relationship between types of bed and the hydrodynamic conditions present in the region. In this context, for this study were collected bathymetric data (depth) and physical oceanographic (height of water column, water temperature, intensity and direction of currents, waves and turbidity), meteorological (rainfall, air temperature, humidity, winds and barometric pressure) of the access channel to the Port of Cabedelo / PB and its basin evolution (where the cruise ships dock), and includes tools of remote sensing (Landsat 7 ETM +, 2001), so that images and the results are integrated into Geographic Information Systems and used in the elaboration of measures aimed at environmental protection areas under the influence of this scale facilities, serving as a grant to prepare a contingency plan in case of oil spills in the region. The main findings highlight the techniques of using hydroacoustic data acquisition together bathymetric surveys of high and low frequency. From there, five were prepared in bathymetric pattern of Directorate of Hydrography and Navigation - DHN, with the depth in meters, on a scale of 1:2500 (Channel and Basin Evolution of Access to Port of Cabedelo), where there is a large extent possible beachrocks that hinder the movement of vessels in the port area, which can cause collisions, running aground and leaking oil. From the scatter diagram of the vectors of currents, it can be seen as the tidal stream and undergoes a channeling effect caused by the bidirectional effect of the tide (ebb and flood) in the basin of the Port of Cabedelo evolution in NW-direction SE and the highest speed of the currents occurs at low tide. The characterization weather for the period from 28/02 to 04/07/2010 values was within the expected average for the region of study. The multidisciplinary integration of products (digital maps and remote sensing images), proved to be efficient for the characterization of underwater geomorphological study area, reaching the aim to discriminate and enhance submerged structures, previously not visible in the images

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Due to the current need of the industry to integrate data of the beginning of production originating from of several sources and of transforming them in useful information for sockets of decisions, a search exists every time larger for systems of visualization of information that come to collaborate with that functionality. On the other hand, a common practice nowadays, due to the high competitiveness of the market, it is the development of industrial systems that possess characteristics of modularity, distribution, flexibility, scalability, adaptation, interoperability, reusability and access through web. Those characteristics provide an extra agility and a larger easiness in adapting to the frequent changes of demand of the market. Based on the arguments exposed above, this work consists of specifying a component-based architecture, with the respective development of a system based on that architecture, for the visualization of industrial data. The system was conceived to be capable to supply on-line information and, optionally, historical information of variables originating from of the beginning of production. In this work it is shown that the component-based architecture developed possesses the necessary requirements for the obtaining of a system robust, reliable and of easy maintenance, being, like this, in agreement with the industrial needs. The use of that architecture allows although components can be added, removed or updated in time of execution, through a manager of components through web, still activating more the adaptation process and updating of the system

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Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

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This work presents simulation results of an identification platform compatible with the INPE Brazilian Data Collection System, modeled with SystemC-AMS. SystemC-AMS that is a library of C++ classes dedicated to the simulation of heterogeneous systems, offering a powerful resource to describe models in digital, analog and RF domains, as well as mechanical and optic. The designed model was divided in four parts. The first block takes into account the satellite s orbit, necessary to correctly model the propagation channel, including Doppler effect, attenuation and thermal noise. The identification block detects the satellite presence. It is composed by low noise amplifier, band pass filter, power detector and logic comparator. The controller block is responsible for enabling the RF transmitter when the presence of the satellite is detected. The controller was modeled as a Petri net, due to the asynchronous nature of the system. The fourth block is the RF transmitter unit, which performs the modulation of the information in BPSK ±60o. This block is composed by oscillator, mixer, adder and amplifier. The whole system was simulated simultaneously. The results are being used to specify system components and to elaborate testbenchs for design verification

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This work shows a theoretical analysis together with numerical and experimental results of transmission characteristics from the microstrip bandpass filters with different geometries. These filters are built over isotropic dielectric substrates. The numerical analysis is made by specifical commercial softwares, like Ansoft Designer and Agilent Advanced Design System (ADS). In addition to these tools, a Matlab Script was built to analyze the filters through the Finite-Difference Time-Domain (FDTD) method. The filters project focused the development of the first stage of filtering in the ITASAT s Transponder receptor, and its integration with the others systems. Some microstrip filters architectures have been studied, aiming the viability of implementation and suitable practical application for the purposes of the ITASAT Project due to its lowspace occupation in the lower UHF frequencies. The ITASAT project is a Universityexperimental project which will build a satellite to integrate the Brazilian Data Collect System s satellite constellation, with efforts of many Brazilian institutes, like for example AEB (Brazilian Spatial Agency), ITA (Technological Institute of Aeronautics), INPE/CRN (National Institute of Spatial Researches/Northeastern Regional Center) and UFRN (Federal University of Rio Grande do Norte). Comparisons were made between numerical and experimental results of all filters, where good agreements could be noticed, reaching the most of the objectives. Also, post-work improvements were suggested.

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Considering the growing use of digital cameras in Photogrammetric projects, especially in aerial survey, this paper presents tests and analyses of bundle block adjustment with additional parameters, using different mathematical models, and blocks of images acquired by the SAAPI digital acquisition system. Three blocks of images were processed by the LPS (Leica Photogrammetry Suite) software, in which five groups of additional parameters (AP) can be used: Bauer, Jacobsen, Ebner, Brown and Lens distortion. These AP's models were employed in the bundle block adjustment, and the results were analyzed based on the accuracy of the checking points and on the changes in these additional parameters. The obtained results showed that the Lens Distortion model allowed the best results.

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

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

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Nowadays, chemistry contents taught in high school continue to be presented in a fragmented and decontextualized manner by the teachers and the textbooks. Even though it is known that contextualization and interdisciplinary exchange play an important role in the process of Chemistry teaching/learning. Therefore, the present study aims at enlightening the importance of these methodological foundations in the learning of chemistry. The data acquisition about the subject Contextualization and Interdisciplinary Exchange involved in Chemistry Teaching was developed through bibliographical researches on chemistry textbooks, which focused on the analysis of the topics acid and base , since it is a theme studied throughout all three years of high school. The present study also developed questionnaires which were applied to analyze to what extent chemistry teachers are working in a contextualized and interdisciplinary manner throughout the process of Chemistry teaching/learning. The results obtained in the researches show that a contextualized and interdisciplinary teaching contributes to a more meaningful acquisition of chemistry knowledge, in a dynamic and interactive way, but there are still many roadblocks towards the achievement of this kind of Chemistry teaching/learning process

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This work aims to analyze socio-environmental vulnerability in the Zone of Environmental Preservation -9, located in the northern of the city of Natal / RN. This objective was outlined when we noted a large number of households (about 2000) located in an area considered relevant in terms of environmental and social conditions, notably because of the existence of lakes, sand dunes and rivers that contribute to groundwater recharge Dunas/Barreiras Furthermore, this area is widely used for agricultural activities. The methodology used during this research is accorded to the literature review about the concept of vulnerability, consultations in public agencies for data acquisition, field research and questionnaires. Data collected from each category of vulnerability (social and environmental) were tabulated, analyzed and presented as tables, maps and texts. According to theoretical concepts and methodology of Alves (2006), Cutter (1996), Torres (2000), Acselrad (2006) e Hogan e Marandola Junior (2005; 2006; 2007), the research is structured in the preparation of an environmental diagnosis of the neighborhoods of Blue Lagoon and Pajuçara and subsequent analysis of socio-environmental vulnerability in the Zone of Environmental Preservation -9, especially Area 1, 2 and 3.There was a variation in results between the social vulnerability and environmental vulnerability categories for each area of the Zone of Environmental Preservation -9. However, the crossing between the two categories above showed that Area 3 had the highest level of environmental vulnerability, followed by Area 1. On the other hand, the Area 2 was considered of minor environmental vulnerability. In this sense, this work presents relevant subsidies to the planning of public policies, to identify and characterize the critical areas with high socio-environmental vulnerability

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The DO experiment enjoyed a very successful data-collection run at the Fermilab Tevatron collider between 1992 and 1996. Since then, the detector has been upgraded to take advantage of improvements to the Tevatron and to enhance its physics capabilities. We describe the new elements of the detector, including the silicon microstrip tracker, central fiber tracker, solenoidal magnet, preshower detectors, forward muon detector, and forward proton detector. The uranium/liquid -argon calorimeters and central muon detector, remaining from Run 1, are discussed briefly. We also present the associated electronics, triggering, and data acquisition systems, along with the design and implementation of software specific to DO. (c) 2006 Elsevier B.V. All rights reserved.

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The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Background: Obstructive sleep apnea (OSA) is a respiratory disease characterized by the collapse of the extrathoracic airway and has important social implications related to accidents and cardiovascular risk. The main objective of the present study was to investigate whether the drop in expiratory flow and the volume expired in 0.2 s during the application of negative expiratory pressure (NEP) are associated with the presence and severity of OSA in a population of professional interstate bus drivers who travel medium and long distances.Methods/Design: An observational, analytic study will be carried out involving adult male subjects of an interstate bus company. Those who agree to participate will undergo a detailed patient history, physical examination involving determination of blood pressure, anthropometric data, circumference measurements (hips, waist and neck), tonsils and Mallampati index. Moreover, specific questionnaires addressing sleep apnea and excessive daytime sleepiness will be administered. Data acquisition will be completely anonymous. Following the medical examination, the participants will perform a spirometry, NEP test and standard overnight polysomnography. The NEP test is performed through the administration of negative pressure at the mouth during expiration. This is a practical test performed while awake and requires little cooperation from the subject. In the absence of expiratory flow limitation, the increase in the pressure gradient between the alveoli and open upper airway caused by NEP results in an increase in expiratory flow.Discussion: Despite the abundance of scientific evidence, OSA is still underdiagnosed in the general population. In addition, diagnostic procedures are expensive, and predictive criteria are still unsatisfactory. Because increased upper airway collapsibility is one of the main determinants of OSA, the response to the application of NEP could be a predictor of this disorder. With the enrollment of this study protocol, the expectation is to encounter predictive NEP values for different degrees of OSA in order to contribute toward an early diagnosis of this condition and reduce its impact and complications among commercial interstate bus drivers.

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Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.