924 resultados para Lincoln Electric Light and Power Company
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How companies can sell their surplus production capacity of electric power in Brazil? This work was developed from the question presented and focusing on clarification of procedures to enter the Brazilian electricity market by providing basic guidelines based on resolutions by National Agency of Electric Energy, National System Operator procedures and rules of the Assembly of Electric Energy Commercialization. It features subsidy to companies that fit this profile to evaluate the possibility to sell their surplus electricity. The general aim was to analyze the procedures and the necessary steps to make this sale happen. Was developed through a literature review where an overview of the Brazilian electric sector and a case study of a company that has excess capacity of electricity, but doesn’t make its marketing. Resulted in the expected clarification as well as the incentive for companies through the information presented, the entry in this trade since power is still crucial to the country's economic growth and ensure its availability in quantity demanded is a challenge of the utmost importance for satisfactory results are achieved economic development contributing to the progress of our society
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Pós-graduação em Serviço Social - FCHS
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The present study aimed to assess the influence of curing distance on the loss of irradiance and power density of four curing light devices. The behavior in terms of power density of four different dental curing devices was analyzed (Valo, Elipar 2, Radii-Cal, and Optilux-401) using three different distances of photopolymerization (0 mm, 4 mm, and 8 mm). All devices had their power density measured using a MARC simulator. Ten measurements were made per device at each distance. The total amount of energy delivered and the required curing time to achieve 16 J/cm2 of energy was also calculated. Data were statistically analyzed with one-way analysis of variance and Tukey’s tests (p < 0.05). The curing distance significantly interfered with the loss of power density for all curing light devices, with the farthest distance generating the lowest power density and consequently the longer time to achieve an energy density of 16 J/cm2 (p < 0.01). Comparison of devices showed that Valo, in extra power mode, showed the best results at all distances, followed by Valo in high power mode, Valo in standard mode, Elipar 2, Radii-Cal, and Optilux-401 halogen lamp (p < 0.01). These findings indicate that all curing lights induced a significant loss of irradiance and total energy when the light was emitted farther from the probe. The Valo device in extra power mode showed the highest power density and the shortest time to achieve an energy density of 16 J/cm2 at all curing distances.
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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 paper shows how the detailed examination of active and nonactive power components may produce new information for modern smart meters. For this purpose, a prototype of electronic power meter has been implemented and applied to the evaluation of the Conservative Power Theory (CPT). Considering five sorts of loads, under four different operating conditions, the experimental results indicate that the CPT is able to provide a good methodology for load characterization, which could possibly benefits consumers and power utilities in several different ways. The results also show that depending on the situation, the analysis of nonactive power terms may be more important than the observation of traditional power quality indices, such as total harmonic distortion, unbalance factors or the fundamental positive sequence power factor.
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A new mixed-integer linear programming (MILP) model is proposed to represent the plug-in electric vehicles (PEVs) charging coordination problem in electrical distribution systems. The proposed model defines the optimal charging schedule for each division of the considered period of time that minimizes the total energy costs. Moreover, priority charging criteria is taken into account. The steady-state operation of the electrical distribution system, as well as the PEV batteries charging is mathematically represented; furthermore, constraints related to limits of voltage, current and power generation are included. The proposed mathematical model was applied in an electrical distribution system used in the specialized literature and the results show that the model can be used in the solution of the PEVs charging problem.
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A CMOS/SOI circuit to decode PWM signals is presented as part of a body-implanted neurostimulator for visual prosthesis. Since encoded data is the sole input to the circuit, the decoding technique is based on a double-integration concept and does not require dc filtering. Nonoverlapping control phases are internally derived from the incoming pulses and a fast-settling comparator ensures good discrimination accuracy in the megahertz range. The circuit was integrated on a 2 mu m single-metal SOI fabrication process and has an effective area of 2mm(2) Typically, the measured resolution of encoding parameter a was better than 10% at 6MHz and V-DD=3.3V. Stand-by consumption is around 340 mu W. Pulses with frequencies up to 15MHz and alpha = 10% can be discriminated for V-DD spanning from 2.3V to 3.3V. Such an excellent immunity to V-DD deviations meets a design specification with respect to inherent coupling losses on transmitting data and power by means of a transcutaneous link.
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This paper presents a novel single-phase high power factor PWM boost rectifier, featuring soft commutation of the active switches at zero-current (ZCS). It incorporates the most desirable properties of the conventional PWM and the soft-switching resonant techniques. The input current shaping is achieved with average current mode control, and continuous inductor current mode. This new PWM converter provides ZCS turn-on and turn-off of the active switches, and it is suitable for high power applications employing IGBTs. Principle of operation, theoretical analysis, a design example, and experimental results from a laboratory prototype rated at 1600 W with 400 Vdc output voltage are presented. The measured efficiency and power factor were 96.2% and 0.99 respectively, with an input current THD equal to 3.94%, for an input voltage THD equal to 3.8%, at rated load.
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The application of the Restricted Dynamics Approach in nuclear theory, based on the approximate solution of many-particle Schrödinger equation, which accounts for all conservation laws in many-nucleon system, is discussed. The Strictly Restricted Dynamics Model is used for the evaluation of binding energies, level schemes, E2 and Ml transition probabilities as well as the electric quadrupole and magnetic dipole momenta of light a-cluster type nuclei in the region 4 ≤ A ≤ 40. The parameters of effective nucleonnucleon interaction potential are evaluated from the ground state binding energies of doubly magic nuclei 4He, 16O and 40Ca.
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The objective of this work is to determine the membership functions for the construction of a fuzzy controller to evaluate the energy situation of the company with respect to load and power factors. The energy assessment of a company is performed by technicians and experts based on the indices of load and power factors, and analysis of the machines used in production processes. This assessment is conducted periodically to detect whether the procedures performed by employees in relation to how of use electricity energy are correct. With a fuzzy controller, this performed can be done by machines. The construction of a fuzzy controller is initially characterized by the definition of input and output variables, and their associated membership functions. We also need to define a method of inference and a processor output. Finally, you need the help of technicians and experts to build a rule base, consisting of answers that provide these professionals in function of characteristics of the input variables. The controller proposed in this paper has as input variables load and power factors, and output the company situation. Their membership functions representing fuzzy sets called by linguistic qualities, as “VERY BAD” and “GOOD”. With the method of inference Mandani and the processor to exit from the Center of Area chosen, the structure of a fuzzy controller is established, simply by the choice by technicians and experts of the field energy to determine a set of rules appropriate for the chosen company. Thus, the interpretation of load and power factors by software comes to meeting the need of creating a single index that indicates an overall basis (rational and efficient) as the energy is being used.
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In this paper, we investigate the problem of routing connections in all-optical networks while allowing for degradation of routed signals by different optical components. To overcome the complexity of the problem, we divide it into two parts. First, we solve the pure RWA problem using fixed routes for every connection. Second, power assignment is accomplished by either using the smallest-gain first (SGF) heuristic or using a genetic algorithm. Numerical examples on a wide variety of networks show that (a) the number of connections established without considering the signal attenuation was most of the time greater than that achievable considering attenuation and (b) the genetic solution quality was much better than that of SGF, especially when the conflict graph of the connections generated by the linear solver is denser.
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This study investigated the availability and use of audiovisual and electronic resources by distance learning students at the National Open University of Nigeria (NOUN). A questionnaire was administered tothe distance learning students selected across the various departments of the NOUN. The findings revealed that even though NOUN made provision for audiovisual and electronic resources for students' use, a majority of the audiovisual and electronic resources are available through personal provision by the students.The study also revealed regular use of audiovisual and electronic resources by the distance learning students. Constraints on use include poor power supply, poor infrastructure, lack of adequate skill, and high cost of access.
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Static analysis tools report software defects that may or may not be detected by other verification methods. Two challenges complicating the adoption of these tools are spurious false positive warnings and legitimate warnings that are not acted on. This paper reports automated support to help address these challenges using logistic regression models that predict the foregoing types of warnings from signals in the warnings and implicated code. Because examining many potential signaling factors in large software development settings can be expensive, we use a screening methodology to quickly discard factors with low predictive power and cost-effectively build predictive models. Our empirical evaluation indicates that these models can achieve high accuracy in predicting accurate and actionable static analysis warnings, and suggests that the models are competitive with alternative models built without screening.
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Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.