994 resultados para War of 1812 -- War losses


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Mode of access: Internet.

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Full Title: Medical sketches of the campaigns of 1812, 13, 14 : to which are added, surgical cases, observations on military hospitals, and flying hospitals attached to a moving army : also, an appendix comprising a dissertation on dysentery which obtained the Boylstonian prize medal for the year 1806 and observations on the winter epidemic of 1815-16, denominated peripneumonia notha, as it appeared at Sharon and Rochester, state of Massachusetts

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An account of Jonathon Phillips, a settler in the Bay of Quinte region and a War of 1812 veteran. Printed at the Chronicle Office, Belleville

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The electricity demand in Brazil has been growing. Some studies estimate that through 2035 the energy consumption (the power consumption) should increase 78%. Two distinct actions are necessary to meet this growth: the construction of new generating plants and to reduce electrical losses in the country. As the construction of power plants have a high price, coupled with the growth of (current) environmental concern, electric utilities are investing in reducing losses, both technical and non-technical. In this context, this paper aims to present an overview of nontechnical losses in Brazil and to raise a discussion on the reasons that contribute to energy fraud.

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The electric utilities have large revenue losses annually due to commercial losses, which are caused mainly by fraud on the part of consumers and faulty meters. Automatic detection of such losses where there is a complex problem, given the large number of consumers and the high cost of each inspection, not to mention the wear of the relationship between company and consumer. Given the above, this paper aims to briefly present some methodologies applied by utilities to identify consumer frauds.

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The article provides a method for long-term forecast of frame alignment losses based on the bit-error rate monitoring for structure-agnostic circuit emulation service over Ethernet in a mobile backhaul network. The developed method with corresponding algorithm allows to detect instants of probable frame alignment losses in a long term perspective in order to give engineering personnel extra time to take some measures aimed at losses prevention. Moreover, long-term forecast of frame alignment losses allows to make a decision about the volume of TDM data encapsulated into a circuit emulation frame in order to increase utilization of the emulated circuit. The developed long-term forecast method formalized with the corresponding algorithm is recognized as cognitive and can act as a part of network predictive monitoring system.

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The dynamics of N losses in fertilizer by ammonia volatilization is affected by several factors, making investigation of these dynamics more complex. Moreover, some features of the behavior of the variable can lead to deviation from normal distribution, making the main commonly adopted statistical strategies inadequate for data analysis. Thus, the purpose of this study was to evaluate the patterns of cumulative N losses from urea through ammonia volatilization in order to find a more adequate and detailed way of assessing the behavior of the variable. For that reason, changes in patterns of ammonia volatilization losses as a result of applying different combinations of two soil classes [Planossolo and Chernossolo (Typic Albaqualf and Vertic Argiaquolls)] and different rates of urea (50, 100 and 150 kg ha-1 N), in the presence or absence of a urease inhibitor, were evaluated, adopting a 2 × 3 × 2 factorial design with four replications. Univariate and multivariate analysis of variance were performed using the adjusted parameter values of a logistic function as a response variable. The results obtained from multivariate analysis indicated a prominent effect of the soil class factor on the set of parameters, indicating greater relevance of soil adsorption potential on ammonia volatilization losses. Univariate analysis showed that the parameters related to total N losses and rate of volatilization were more affected by soil class and the rate of urea applied. The urease inhibitor affected only the rate and inflection point parameters, decreasing the rate of losses and delaying the beginning of the process, but had no effect on total ammonia losses. Patterns of ammonia volatilization losses provide details on behavior of the variable, details which can be used to develop and adopt more accurate techniques for more efficient use of urea.

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A common problem when planning large free field PV-plants is optimizing the ground occupation ratio while maintaining low shading losses. Due to the complexity of this task, several PV-plants have been built using various configurations. In order to compare the shading losses of different PV technologies and array designs, empirical performance data of five free field PV-plants operating in Germany was analyzed. The data collected comprised 140 winter days from October 2011 until March 2012. The relative shading losses were estimated by comparing the energy output of selected arrays in the front rows (shading-free) against that of shaded arrays in the back rows of the same plant. The results showed that landscape mounting with mc-Si PV-modules yielded significantly better results than portrait one. With CIGS modules, making cross-table strings using the lower modules was not beneficial as expected and had more losses than a one-string-per-table layout. Parallel substrings with CdTe showed relatively low losses. Among the two CdTe products analyzed, none showed a significantly better performance.

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Tillage stimulates soil carbon (C) losses by increasing aeration, changing temperature and moisture conditions, and thus favoring microbial decomposition. In addition, soil aggregate disruption by tillage exposes once protected organic matter to decomposition. We propose a model to explain carbon dioxide (CO2) emission after tillage as a function of the no-till emission plus a correction due to the tillage disturbance. The model assumes that C in the readily decomposable organic matter follows a first-order reaction kinetics equation as: dC(sail)(t)/dt = -kC(soil)(t) and that soil C-CO2 emission is proportional to the C decay rate in soil, where C-soil(t) is the available labile soil C (g m(-2)) at any time (t). Emissions are modeled in terms soil C available to decomposition in the tilled and non-tilled plots, and a relationship is derived between no-till (F-NT) and tilled (F-Gamma) fluxes, which is: F-T = a1F(NT)e(-a2t), where t is time after tillage. Predicted and observed fluxes showed good agreement based on determination coefficient (R-2), index of agreement and model efficiency, with R-2 as high as 0.97. The two parameters included in the model are related to the difference between the decay constant (k factor) of tilled and no-till plots (a(2)) and also to the amount of labile carbon added to the readily decomposable soil organic matter due to tillage (a,). These two parameters were estimated in the model ranging from 1.27 and 2.60 (a(1)) and - 1.52 x 10(-2) and 2.2 x 10(-2) day(-1) (a(2)). The advantage is that temporal variability of tillage-induced emissions can be described by only one analytical function that includes the no-till emission plus an exponential term modulated by tillage and environmentally dependent parameters. (C) 2008 Elsevier B.V. All rights reserved.

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This work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids. © 2012 IEEE.