876 resultados para Sensor of electric measures
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The electrical measures of the soil have been used as variables that correlate with its characteristics. This study aimed at developing an electrical capacitance sensor of low cost, to evaluate its performance on the field and verify the correlation between the measurements of electrical capacitance with physical properties (sand, silt and clay) and chemical properties of soil (pH, MO, P resin, H + Al, K, Ca, Mg, SB, CTC and V%) and the moisture content. The data sampling was performed at the farm named "Capão da Onça" which belongs to the State University of Ponta Grossa. The samples collection was conducted in an area of approximately 13 hectares, totalizing 81 samples. In each sampling the electrical capacitance of the soil was measured. After the sensor withdrawal, soil samples were collected and sent to be analysed in the laboratory of the College of Agronomics Science of the Paulista State University. The measuring instrument used to collect data on electric capacitance of the soil a digital multimeter was used. The data were submitted to the analysis of correlation and regression. The developed system presented a low cost and it was capable to measuring variation of the electrical capacitance of the soil. The obtained measures satisfactorily correlated with the levels of clay and sand, and weakly with the moisture content. This had demonstrated the possibility to use a sensor to verify the soil texture in not homogeneous areas. The measures of the electrical capacitance of the soil obtained by the sensor had significantly correlated with the soil attributes: calcium, magnesium, pH, SB and CTC. These results had demonstrated the possibility to use a sensor for soil fertility control.
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The paper presents the main elements of a project entitled ICT-Emissions that aims at developing a novel methodology to evaluate the impact of ICT-related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures. The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. A number of sources are available to the consortium to obtain the necessary input data. Also, experimental campaigns are offered to fill in gaps of information in traffic and emission patterns. The application of the methodology will be demonstrated using commercially available software. However, the methodology is developed in such a way as to enable its implementation by a variety of emission and traffic models. Particular emphasis is given to (a) the correct estimation of driver behaviour, as a result of traffic-related ICT measures, (b) the coverage of a large number of current vehicle technologies, including ICT systems, and (c) near future technologies such as hybrid, plug-in hybrids, and electric vehicles. The innovative combination of traffic, driver, and emission models produces a versatile toolbox that can simulate the impact on energy and CO2 of infrastructure measures (traffic management, dynamic traffic signs, etc.), driver assistance systems and ecosolutions (speed/cruise control, start/stop systems, etc.) or a combination of measures (cooperative systems).The methodology is validated by application in the Turin area and its capacity is further demonstrated by application in real world conditions in Madrid and Rome.
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International audience
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This thesis presents a system for visually analyzing the electromagnetic fields of the electrical machines in the energy conversion laboratory. The system basically utilizes the finite element method to achieve a real-time effect in the analysis of electrical machines during hands-on experimentation. The system developed is a tool to support the student's understanding of the electromagnetic field by calculating performance measures and operational concepts pertaining to the practical study of electrical machines. Energy conversion courses are fundamental in electrical engineering. The laboratory is conducted oriented to facilitate the practical application of the theory presented in class, enabling the student to use electromagnetic field solutions obtained numerically to calculate performance measures and operating characteristics. Laboratory experiments are utilized to help the students understand the electromagnetic concepts by the use of this visual and interactive analysis system. In this system, this understanding is accomplished while hands-on experimentation takes place in real-time.
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An algorithm inspired on ant behavior is developed in order to find out the topology of an electric energy distribution network with minimum power loss. The algorithm performance is investigated in hypothetical and actual circuits. When applied in an actual distribution system of a region of the State of Sao Paulo (Brazil), the solution found by the algorithm presents loss lower than the topology built by the concessionary company.
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Electric arc furnace (EAF) dust is a waste generated in the EAF during the steel production process. Among different wastes, EAF dust represents one of the most hazardous, since it contains heavy metals such as Zn, Fe, Cr, Cd and Pb. The goal of the present work is to characterise the waste through chemical analysis, particle size distribution, X-ray diffraction (XRD), scanning electron microscopy coupled with energy dispersive spectroscopy detection and thermal analysis. The waste sample is composed essentially of spherical particles and has a very small particle size and the majority of the identified elements were Fe, Zn, Ca, Cr, Mn, K and Si. The XRD has presented compounds such as ZnO, ZnFe2O4, Fe2O3, MnO, SiO2, FeFe2O4 and MnAl2O4. According to the thermal analysis results, up to 1000 degrees C the total weight loss was similar to 5%. The results of waste characterisation are very important to these further investigations.
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We introduced a spectral clustering algorithm based on the bipartite graph model for the Manufacturing Cell Formation problem in [Oliveira S, Ribeiro JFF, Seok SC. A spectral clustering algorithm for manufacturing cell formation. Computers and Industrial Engineering. 2007 [submitted for publication]]. It constructs two similarity matrices; one for parts and one for machines. The algorithm executes a spectral clustering algorithm on each separately to find families of parts and cells of machines. The similarity measure in the approach utilized limited information between parts and between machines. This paper reviews several well-known similarity measures which have been used for Group Technology. Computational clustering results are compared by various performance measures. (C) 2008 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
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In modern magnetic resonance imaging (MRI), patients are exposed to strong, nonuniform static magnetic fields outside the central imaging region, in which the movement of the body may be able to induce electric currents in tissues which could be possibly harmful. This paper presents theoretical investigations into the spatial distribution of induced electric fields and currents in the patient when moving into the MRI scanner and also for head motion at various positions in the magnet. The numerical calculations are based on an efficient, quasi-static, finite-difference scheme and an anatomically realistic, full-body, male model. 3D field profiles from an actively shielded 4T magnet system are used and the body model projected through the field profile with a range of velocities. The simulation shows that it possible to induce electric fields/currents near the level of physiological significance under some circumstances and provides insight into the spatial characteristics of the induced fields. The results are extrapolated to very high field strengths and tabulated data shows the expected induced currents and fields with both movement velocity and field strength. (C) 2003 Elsevier Science (USA). All rights reserved.
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Background. The purpose of this study was to examine the reliability of stage of change (SOC) measures for moderate-intensity and vigorous physical activity in two separate samples of young adults. Staging measures have focused on vigorous exercise, but current public health guidelines emphasize moderate-intensity activity. Method. For college students in the USA (n = 105) and in Australia (n = 123), SOC was assessed separately on two occasions for moderate-intensity activity and for vigorous activity. Test-retest repeatability was determined, using Cohen's kappa coefficient. Results. In both samples, the reliability scores for the moderate-intensity physical activity staging measure were lower than the scores for the vigorous exercise staging measure. Weighted kappa values for the moderate-intensity staging measure were in the fair to good range for both studies (0.50 and 0.45); for the vigorous staging measure kappa values were excellent and fair to good (0.76 and 0.72). Conclusions. There is a need to standardize and improve methods for staging moderate-intensity activity, given that such measures are used in public health interventions targeting HEPA (health-enhancing physical activity). (C) 2003 American Health Foundation and Elsevier Science (USA). All rights reserved.
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The participation of citizens in public policies is an opportunity not only to educate them, but also to increase their empowerment. However, the best way for deploying participatory policies, defining their scope and approach, still remains an open and continuous debate. Using as a case study the Brazilian National Agency of Electric Energy (Aneel), with its public hearings about tariff review, this paper aims at analyzing the democratic aspects of these hearings and challenges the hypothesis of many scholars about the social participation bias in this kind of procedure. This study points out a majority participation of experts, contrasting with the political content of discussions. And, this way, it contributes to a critical analysis of the public hearings as a participatory tool, indicating their strengths and their aspects which deserve a special attention.
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In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.
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Background: Poor nutritional status and worse health-related quality of life (QoL) have been reported in haemodialysis (HD) patients. The utilization of generic and disease specific QoL questionnaires in the same population may provide a better understanding of the significance of nutrition in QoL dimensions. Objective: To assess nutritional status by easy to use parameters and to evaluate the potential relationship with QoL measured by generic and disease specific questionnaires. Methods: Nutritional status was assessed by subjective global assessment adapted to renal patients (SGA), body mass index (BMI), nutritional intake and appetite. QoL was assessed by the generic EuroQoL and disease specific Kidney Disease Quality of Life-Short Form (KDQoL-SF) questionnaires. Results: The study comprised 130 patients of both genders, mean age 62.7 ± 14.7 years. The prevalence of undernutrition ranged from 3.1% by BMI ≤ 18.5 kg/m2 to 75.4% for patients below energy and protein intake recommendations. With the exception of BMI classification, undernourished patients had worse scores in nearly all QoL dimensions (EuroQoL and KDQoL-SF), a pattern which was dominantly maintained when adjusted for demographics and disease-related variables. Overweight/obese patients (BMI ≥ 25) also had worse scores in some QoL dimensions, but after adjustment the pattern was maintained only in the symptoms and problems dimension of KDQoL-SF (p = 0.011). Conclusion: Our study reveals that even in mildly undernourished HD patients, nutritional status has a significant impact in several QoL dimensions. The questionnaires used provided different, almost complementary perspectives, yet for daily practice EuroQoL is simpler. Assuring a good nutritional status, may positively influence QoL.