861 resultados para Demand scenarios
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We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., the third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source — even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland’13), ADSNARK achieves up to 25× improvement in proof-computation time and a 20× reduction in prover storage space.
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The environmental and socio-economic importance of coastal areas is widely recognized, but at present these areas face severe weaknesses and high-risk situations. The increased demand and growing human occupation of coastal zones have greatly contributed to exacerbating such weaknesses. Today, throughout the world, in all countries with coastal regions, episodes of waves overtopping and coastal flooding are frequent. These episodes are usually responsible for property losses and often put human lives at risk. The floods are caused by coastal storms primarily due to the action of very strong winds. The propagation of these storms towards the coast induces high water levels. It is expected that climate change phenomena will contribute to the intensification of coastal storms. In this context, an estimation of coastal flooding hazards is of paramount importance for the planning and management of coastal zones. Consequently, carrying out a series of storm scenarios and analyzing their impacts through numerical modeling is of prime interest to coastal decision-makers. Firstly, throughout this work, historical storm tracks and intensities are characterized for the northeastern region of United States coast, in terms of probability of occurrence. Secondly, several storm events with high potential of occurrence are generated using a specific tool of DelftDashboard interface for Delft3D software. Hydrodynamic models are then used to generate ensemble simulations to assess storms' effects on coastal water levels. For the United States’ northeastern coast, a highly refined regional domain is considered surrounding the area of The Battery, New York, situated in New York Harbor. Based on statistical data of numerical modeling results, a review of the impact of coastal storms to different locations within the study area is performed.
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Dissertação de Mestrado em Estratégia
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El problema: En todo momento y sobre todo cuando estamos en presencia de escenarios económicos turbulentos resulta imprescindible utilizar herramientas que permitan realizar análisis de sensitividad sobre las distintas situaciones que podrían plantearse. La elaboración de modelos matemáticos deterministas desde las aplicaciones realizadas por Richard Mattessich han constituido un instrumento idóneo para el caso de empresas comerciales o industriales. Los modelos informáticos utilizados para las empresas agropecuarias han abordado fundamentalmente la temática relacionada con la producción, no así las otras variables económicas y financieras. Por lo tanto, entendemos que se hace necesario trabajar con modelos agropecuarios que comprendan todas las variables económicas y financieras, de manera de observar otro tipo de cuestiones, tales como: el modo de financiarse, los costos financieros, necesidades de capital de trabajo. Hipótesis: Es posible, a través de la utilización de la información contable en sentido prospectivo, interpretar adecuadamente los escenarios futuros de las organizaciones agropecuarias, cuantificando los impactos que generan tanto las estrategias y políticas aplicables, como las distorsiones del contexto. Objetivo general: determinar la incidencia de las decisiones internas y las que provengan del funcionamiento del sistema económico, a través de la información contable prospectiva. Objetivos específicos: a. Describir los impactos que se producen en la estructura patrimonial, financiera y en los resultados, como consecuencia de los cambios en las estrategias y políticas de la empresa agropecuaria, así como los efectos macroeconómicos en la estructura de la empresa que pudieran estar conmoviendo la gestión económico-financiera. b. Identificar mecanismos y proponer criterios para la elaboración de modelos que permitan visualizar los impactos en los escenarios futuros y las adecuaciones necesarias en la estructura que permitan soportar las modificaciones. Metodología: será un estudio a nivel teórico, donde una vez identificadas las variables y planteados los modelos, se propondrán distintas situaciones y se testearán las respuestas. Resultados esperados: lograr un avance en la evaluación económico-financiera prospectiva de empresas agropecuarias y constituir un avance para futuras investigaciones. Importancia del proyecto: La producción agropecuaria es vital tanto para el desarrollo económico de Argentina, como en particular para la provincia de Córdoba. Elaborar herramientas que eficientizen la administración de este tipo de empresas, redundará en beneficio colectivo. Pertinencia: El producto verificable será la construcción de un modelo distinto a los actuales, tanto en su desarrollo, objetivo al que está destinado y sencillez de su aplicación, posibilitando la inserción del productor en el proceso de planificación, reduciendo el riesgo en la toma de decisiones. Esperando generar un avance sobre los modelos preexistente.
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Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2012
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Magdeburg, Univ., Fak. für Informatik, Diss., 2013
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Magdeburg, Univ., Fak. für Informatik, Diss., 2015
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Despite the huge increase in processor and interprocessor network performace, many computational problems remain unsolved due to lack of some critical resources such as floating point sustained performance, memory bandwidth, etc... Examples of these problems are found in areas of climate research, biology, astrophysics, high energy physics (montecarlo simulations) and artificial intelligence, among others. For some of these problems, computing resources of a single supercomputing facility can be 1 or 2 orders of magnitude apart from the resources needed to solve some them. Supercomputer centers have to face an increasing demand on processing performance, with the direct consequence of an increasing number of processors and systems, resulting in a more difficult administration of HPC resources and the need for more physical space, higher electrical power consumption and improved air conditioning, among other problems. Some of the previous problems can´t be easily solved, so grid computing, intended as a technology enabling the addition and consolidation of computing power, can help in solving large scale supercomputing problems. In this document, we describe how 2 supercomputing facilities in Spain joined their resources to solve a problem of this kind. The objectives of this experience were, among others, to demonstrate that such a cooperation can enable the solution of bigger dimension problems and to measure the efficiency that could be achieved. In this document we show some preliminary results of this experience and to what extend these objectives were achieved.
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This paper studies the impact of instrumental voting on information demand and mass media behaviour during electoral campaigns. If voters act instrumentally then information demand should increase with the closeness of an election. Mass media are modeled as profit-maximizing firms that take into account information demand, the value of customers to advertisers and the marginal cost of customers. Information supply should be larger in electoral constituencies where the contest is expected to be closer, there is a higher population density, and customers are on average more profitable for advertisers. The impact of electorate size is theoretically undetermined. These conclusions are then tested with comfortable results on data from the 1997 general election in Britain.
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We study whether people's behavior in unbalanced gift exchange markets with repeated interaction are affected by whether they are on the excess supply side or the excess demand side of the market. Our analysis is based on the comparison of behavior between two types of experimental gift exchange markets, which vary only with respect to whether first or second movers are on the long side of the market. The direction of market imbalance could influence subjects' behavior, as second movers (workers) might react differently to favorable actions by first movers (firms) in the two cases. While our data show strong deviations from the standard game-theoretic prediction, we find mainly secondary treatment effects. Wage offers are not higher when there is an excess supply of firms, and workers do not respond more favorably to a given wage when there is an excess supply of labor. The state of competition does not appear to have strong effects in our data. We also present data from single-period sessions that show substantial gift exchange even without repeated interactions.
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We study the outcomes of experimental multi-unit uniform and discriminatory auctions with demand uncertainty. Our study is motivated by the ongoing debate about market design in the electricity industry. Our main aim is to compare the effect of asymmetric demand-information between sellers on the performance of the two auction institutions. In our baseline conditions all sellers have the same information, whereas in our treatment conditions some sellers have better information than others. In both information conditions we find that average transaction prices and price volatility are not significantly different under the two auction institutions. However, when there is asymmetric information among sellers the discriminatory auction is significantly less efficient. These results are not in line with the typical arguments made in favor of discriminatory pricing in electricity industries; namely, lower consumer prices and less price volatility. Moreover, our results provide some indication that discriminatory auctions reduce technical efficiency relative to uniform auctions.
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The Hausman (1978) test is based on the vector of differences of two estimators. It is usually assumed that one of the estimators is fully efficient, since this simplifies calculation of the test statistic. However, this assumption limits the applicability of the test, since widely used estimators such as the generalized method of moments (GMM) or quasi maximum likelihood (QML) are often not fully efficient. This paper shows that the test may easily be implemented, using well-known methods, when neither estimator is efficient. To illustrate, we present both simulation results as well as empirical results for utilization of health care services.
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We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.
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This paper analyses the elasticities of demand in tolled motorways in Spain with respect to the main variables influencing it. The demand equation is estimated using a panel data set where the cross-section observations correspond to the different Spanish tolled motorways sections, and the temporal dimension ranges from the beginning of the eighties until the end of the nineties. The results show a high elasticity with respect to the economic activity level. The average elasticity with respect to petrol price falls around -0.3, while toll elasticities clearly vary across motorway sections. These motorway sections are classified into four groups according to the estimated toll elasticity with values that range from -0.21 for the most inelastic to -0.83 for the most elastic. The main factors that explain such differences are the quality of the alternative road and the length of the section. The long-term effect is about 50 per cent higher than the short term one; however, the period of adjustment is relatively short.