DISPRO datasets for validation of coastal hydrodynamic models

Appropriate field data are required to check the reliability of hydrodynamic models simulating the dispersion of soluble substances in the marine environment. This study deals with the collection of physical measurements and soluble tracer data intended specifically for this kind of validation. The intensity of currents as well as the complexity of topography and tides around the Cap de La Hague in the center of the English Channel makes it one of the most difficult areas to represent in terms of hydrodynamics and dispersion. Controlled releases of tritium - in the form of HTO - are carried out in this area by the AREVA-NC plant, providing an excellent soluble tracer. A total of 14 493 measurements were acquired to track dispersion in the hours and days following a release. These data, supplementing previously gathered data and physical measurements (bathymetry, water-surface levels, Eulerian and Lagrangian current studies) allow us to test dispersion models from the hour following release to periods of several years which are not accessible with dye experiments. The dispersion characteristics are described and methods are proposed for comparing models against measurements. An application is proposed for a 2 dimensions high-resolution numerical model. It shows how an extensive dataset can be used to build, calibrate and validate several aspects of the model in a highly dynamic and macrotidal area: tidal cycle timing, tidal amplitude, fixed-point current data, hodographs. This study presents results concerning the model's ability to reproduce residual Lagrangian currents, along with a comparison between simulation and high-frequency measurements of tracer dispersion. Physical and tracer data are available from the SISMER database of IFREMER (www.ifremer.fr/sismer/catal). This tool for validation of models in macro-tidal seas is intended to be an open and evolving resource, which could provide a benchmark for dispersion model validation.

Financial Policies and Dynamic Game Simulation in Poland and Hungary

Recently, steady economic growth rates have been kept in Poland and Hungary. Money supplies are growing rather rapidly in these economies. In large, exchange rates have trends of depreciation. Then, exports and prices show the steady growth rates. It can be thought that per capita GDPs are in the same level and development stages are similar in these two countries. It is assumed that these two economies have the same export market and export goods are competing in it. If one country has an expansion of monetary policy, price increase and interest rate decrease. Then, exchange rate decrease. Exports and GDP will increase through this phenomenon. At the same time, this expanded monetary policy affects another country through the trade. This mutual relationship between two countries can be expressed by the Nash-equilibrium in the Game theory. In this paper, macro-econometric models of Polish and Hungarian economies are built and the Nash- equilibrium is introduced into them.

Spillover effects of TTIP on BRICS economies : a dynamic GVC-based CGE model

This paper uses a GVC (Global Value Chain)-based CGE model to assess the impact of TTIP between the U.S. and the EU on their main trading partners who are mainly engaged at the low end in the division system of global value chains, such as BRICS countries. The simulation results indicate that in general the TTIP would positively impact global trade and economies due to the reduction of both tariff and non-tariff barriers. With great increases in the US–EU bilateral trade, significant economic gains for the U.S. and the EU can be expected. For most BRICS countries, the aggregate exports and GDP suffer small negative impacts from the TTIP, except Brazil, but the inter-country trade within BRICS economies increases due to the substitution effect between the US–EU trade and the imports from BRICS countries when the TTIP commences.

Spatial spillover effects in determining China's regional CO2 emission growth : 2007-2010

This paper proposes an alternative input-output based spatial-structural decomposition analysis to elucidate the role of domestic-regional heterogeneity and interregional spillover effects in determining China's regional CO2 emission growth. Our empirical results based on the 2007 and 2010 Chinese interregional input-output tables show that the changes in most regions' final demand scale, final expenditure structure and export scale give positive spatial spillover effects on other regions' CO2 emission growth, the changes in most regions' consumption and export preference help the reduction of other regions' CO2 emissions, the changes in production technology, and investment preference may give positive or negative impacts on other region's CO2 emission growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emission growth. All these facts can significantly help better and deeper understanding on the driving forces of China's regional CO2 emission growth, thus can enrich the policy implication concerning a narrow definition of "carbon leakage" through domestic-interregional trade, and relevant political consensus about the responsibility sharing between developed and developing regions inside China.

Determinants of inbound tourists in Cambodia : a dynamic panel data approach

Understanding the determinants of tourism demand is crucial for the tourism sector. This paper develops a dynamic panel model to examine the determinants of inbound tourists to Siem Reap airport, Phnom Penh airport, and land and waterway borders in Cambodia. Consistent with the consumer theory of tourism consumption, a 10% increase in the origin country GDP per capita is predicted to increase the number of tourist visits to Siem Reap airport by 5.8%. A 10% increase in the real exchange rate between the origin country and Cambodia is predicted to decrease the number of tourist visits by 0.89%. In contrast, the number of foreign tourists in a previous period has little effect on the number of foreign tourists in the current period. Additionally, the determinants are different by the mode of entry to Cambodia.

Dynamic Model-based Management of Service-Oriented Infrastructure.

Models are an effective tool for systems and software design. They allow software architects to abstract from the non-relevant details. Those qualities are also useful for the technical management of networks, systems and software, such as those that compose service oriented architectures. Models can provide a set of well-defined abstractions over the distributed heterogeneous service infrastructure that enable its automated management. We propose to use the managed system as a source of dynamically generated runtime models, and decompose management processes into a composition of model transformations. We have created an autonomic service deployment and configuration architecture that obtains, analyzes, and transforms system models to apply the required actions, while being oblivious to the low-level details. An instrumentation layer automatically builds these models and interprets the planned management actions to the system. We illustrate these concepts with a distributed service update operation.

Next Generation of Energy Residential Gateways for Demand Response and Dynamic Pricing

Predictions about electric energy needs, based on current electric energy models, forecast that the global energy consumption on Earth for 2050 will double present rates. Using distributed procedures for control and integration, the expected needs can be halved. Therefore implementation of Smart Grids is necessary. Interaction between final consumers and utilities is a key factor of future Smart Grids. This interaction is aimed to reach efficient and responsible energy consumption. Energy Residential Gateways (ERG) are new in-building devices that will govern the communication between user and utility and will control electric loads. Utilities will offer new services empowering residential customers to lower their electric bill. Some of these services are Smart Metering, Demand Response and Dynamic Pricing. This paper presents a practical development of an ERG for residential buildings.

Dynamic Response of Wind Turbines to Theoretical 3D Seismic Motions Taking into Account the Rotational Component

We study the dynamic response of a wind turbine structure subjected to theoretical seismic motions, taking into account the rotational component of ground shaking. Models are generated for a shallow moderate crustal earthquake in the Madrid Region (Spain). Synthetic translational and rotational time histories are computed using the Discrete Wavenumber Method, assuming a point source and a horizontal layered earth structure. These are used to analyze the dynamic response of a wind turbine, represented by a simple finite element model. Von Mises stress values at different heights of the tower are used to study the dynamical structural response to a set of synthetic ground motion time histories

Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.

Dynamic effect of high speed railway traffic loads on the ballast track settlement

The traditional ballast track structures are still being used in high speed railways lines with success, however technical problems or performance features have led to non-ballast track solution in some cases. A considerable maintenance work is needed for ballasted tracks due to the track deterioration. Therefore it is very important to understand the mechanism of track deterioration and to predict the track settlement or track irregularity growth rate in order to reduce track maintenance costs and enable new track structures to be designed. The objective of this work is to develop the most adequate and efficient models for calculation of dynamic traffic load effects on railways track infrastructure, and then evaluate the dynamic effect on the ballast track settlement, using a ballast track settlement prediction model, which consists of the vehicle/track dynamic model previously selected and a track settlement law. The calculations are based on dynamic finite element models with direct time integration, contact between wheel and rail and interaction with railway cars. A initial irregularity profile is used in the prediction model. The track settlement law is considered to be a function of number of loading cycles and the magnitude of the loading, which represents the long-term behavior of ballast settlement. The results obtained include the track irregularity growth and the contact force in the final interaction of numerical simulation

Dynamic Analysis of high Speed Railway Traffic Loads on Ballasted Track

This paper reports the studies carried out to develop and calibrate the optimal models for the objectives of this work. In particular, quarter bogie model for vehicle, rail-wheel contact with Lagrangian multiplier method, 2D spatial discretization were selected as the optimal decisions. Furthermore, the 3D model of coupled vehicle-track also has been developed to contrast the results obtained in the 2D model. The calculations were carried out in the time domain and envelopes of relevant results were obtained for several track profiles and speed ranges. Distributed elevation irregularities were generated based on power spectral density (PSD) distributions. The results obtained include the wheel-rail contact forces, forces transmitted to the bogie by primary suspension. The latter loads are relevant for the purpose of evaluating the performance of the infrastructure

Proposal of a dynamic performance index to analyze driving pattern effect on car emissions

The contributions of driver behaviour as well as surrounding infrastructure are decisive on pollutant emissions from vehicles in real traffic situations. This article deals with the preliminary study of the interaction between the dynamic variables recorded in a vehicle (driving pattern) and pollutant emissions produced over a given urban route. It has been established a “dynamic performance index”-DPI, which is calculated from some driving pattern parameters, which in turn depends on traffic congestion level and route characteristics, in order to determine whether the driving has been aggressive, normal or calm. Two passenger cars instrumented with a portable activity measurement system -to record dynamic variables- and on-board emission measurement equipment have been used. This study has shown that smooth driving patterns can reduce up to 80% NOX emissions and up to 20% of fuel in the same route

Generating multimedia presentations that summarize the behavior of dynamic systems using a model-based approach

This article describes a knowledge-based method for generating multimedia descriptions that summarize the behavior of dynamic systems. We designed this method for users who monitor the behavior of a dynamic system with the help of sensor networks and make decisions according to prefixed management goals. Our method generates presentations using different modes such as text in natural language, 2D graphics and 3D animations. The method uses a qualitative representation of the dynamic system based on hierarchies of components and causal influences. The method includes an abstraction generator that uses the system representation to find and aggregate relevant data at an appropriate level of abstraction. In addition, the method includes a hierarchical planner to generate a presentation using a model with dis- course patterns. Our method provides an efficient and flexible solution to generate concise and adapted multimedia presentations that summarize thousands of time series. It is general to be adapted to differ- ent dynamic systems with acceptable knowledge acquisition effort by reusing and adapting intuitive rep- resentations. We validated our method and evaluated its practical utility by developing several models for an application that worked in continuous real time operation for more than 1 year, summarizing sen- sor data of a national hydrologic information system in Spain.

Hydrologic models for emergency decision support using Bayesian networks

In the presence of a river flood, operators in charge of control must take decisions based on imperfect and incomplete sources of information (e.g., data provided by a limited number sensors) and partial knowledge about the structure and behavior of the river basin. This is a case of reasoning about a complex dynamic system with uncertainty and real-time constraints where bayesian networks can be used to provide an effective support. In this paper we describe a solution with spatio-temporal bayesian networks to be used in a context of emergencies produced by river floods. In the paper we describe first a set of types of causal relations for hydrologic processes with spatial and temporal references to represent the dynamics of the river basin. Then we describe how this was included in a computer system called SAIDA to provide assistance to operators in charge of control in a river basin. Finally the paper shows experimental results about the performance of the model.

Game Theory Models for Multi-Robot Patrolling of Infraestructures

Abstract This work is focused on the problem of performing multi‐robot patrolling for infrastructure security applications in order to protect a known environment at critical facilities. Thus, given a set of robots and a set of points of interest, the patrolling task consists of constantly visiting these points at irregular time intervals for security purposes. Current existing solutions for these types of applications are predictable and inflexible. Moreover, most of the previous centralized and deterministic solutions and only few efforts have been made to integrate dynamic methods. Therefore, the development of new dynamic and decentralized collaborative approaches in order to solve the aforementioned problem by implementing learning models from Game Theory. The model selected in this work that includes belief‐based and reinforcement models as special cases is called Experience‐Weighted Attraction. The problem has been defined using concepts of Graph Theory to represent the environment in order to work with such Game Theory techniques. Finally, the proposed methods have been evaluated experimentally by using a patrolling simulator. The results obtained have been compared with previous available