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.

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.

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.

Comparison of dynamic effects of high-speed traffic load on ballasted track using a simplified two-dimensional and full three-dimensional model.

The vertical dynamic actions transmitted by railway vehicles to the ballasted track infrastructure is evaluated taking into account models with different degree of detail. In particular, we have studied this matter from a two-dimensional (2D) finite element model to a fully coupled three-dimensional (3D) multi-body finite element model. The vehicle and track are coupled via a non-linear Hertz contact mechanism. The method of Lagrange multipliers is used for the contact constraint enforcement between wheel and rail. Distributed elevation irregularities are generated based on power spectral density (PSD) distributions which are taken into account for the interaction. The numerical simulations are performed in the time domain, using a direct integration method for solving the transient problem due to the contact nonlinearities. The results obtained include contact forces, forces transmitted to the infrastructure (sleeper) by railpads and envelopes of relevant results for several track irregularities and speed ranges. The main contribution of this work is to identify and discuss coincidences and differences between discrete 2D models and continuum 3D models, as wheel as assessing the validity of evaluating the dynamic loading on the track with simplified 2D models

Simulation tools for statistical model comparison: an application to unobserved componenet models versus dynamic regression models

Aplicación de simulación de Monte Carlo y técnicas de Análisis de la Varianza (ANOVA) a la comparación de modelos estocásticos dinámicos para accidentes de tráfico.

Localization and Tracking in Energy-Constrained Networks with Dynamic Connectivity

Systems used for target localization, such as goods, individuals, or animals, commonly rely on operational means to meet the final application demands. However, what would happen if some means were powered up randomly by harvesting systems? And what if those devices not randomly powered had their duty cycles restricted? Under what conditions would such an operation be tolerable in localization services? What if the references provided by nodes in a tracking problem were distorted? Moreover, there is an underlying topic common to the previous questions regarding the transfer of conceptual models to reality in field tests: what challenges are faced upon deploying a localization network that integrates energy harvesting modules? The application scenario of the system studied is a traditional herding environment of semi domesticated reindeer (Rangifer tarandus tarandus) in northern Scandinavia. In these conditions, information on approximate locations of reindeer is as important as environmental preservation. Herders also need cost-effective devices capable of operating unattended in, sometimes, extreme weather conditions. The analyses developed are worthy not only for the specific application environment presented, but also because they may serve as an approach to performance of navigation systems in absence of reasonably accurate references like the ones of the Global Positioning System (GPS). A number of energy-harvesting solutions, like thermal and radio-frequency harvesting, do not commonly provide power beyond one milliwatt. When they do, battery buffers may be needed (as it happens with solar energy) which may raise costs and make systems more dependent on environmental temperatures. In general, given our problem, a harvesting system is needed that be capable of providing energy bursts of, at least, some milliwatts. Many works on localization problems assume that devices have certain capabilities to determine unknown locations based on range-based techniques or fingerprinting which cannot be assumed in the approach considered herein. The system presented is akin to range-free techniques, but goes to the extent of considering very low node densities: most range-free techniques are, therefore, not applicable. Animal localization, in particular, uses to be supported by accurate devices such as GPS collars which deplete batteries in, maximum, a few days. Such short-life solutions are not particularly desirable in the framework considered. In tracking, the challenge may times addressed aims at attaining high precision levels from complex reliable hardware and thorough processing techniques. One of the challenges in this Thesis is the use of equipment with just part of its facilities in permanent operation, which may yield high input noise levels in the form of distorted reference points. The solution presented integrates a kinetic harvesting module in some nodes which are expected to be a majority in the network. These modules are capable of providing power bursts of some milliwatts which suffice to meet node energy demands. The usage of harvesting modules in the aforementioned conditions makes the system less dependent on environmental temperatures as no batteries are used in nodes with harvesters--it may be also an advantage in economic terms. There is a second kind of nodes. They are battery powered (without kinetic energy harvesters), and are, therefore, dependent on temperature and battery replacements. In addition, their operation is constrained by duty cycles in order to extend node lifetime and, consequently, their autonomy. There is, in turn, a third type of nodes (hotspots) which can be static or mobile. They are also battery-powered, and are used to retrieve information from the network so that it is presented to users. The system operational chain starts at the kinetic-powered nodes broadcasting their own identifier. If an identifier is received at a battery-powered node, the latter stores it for its records. Later, as the recording node meets a hotspot, its full record of detections is transferred to the hotspot. Every detection registry comprises, at least, a node identifier and the position read from its GPS module by the battery-operated node previously to detection. The characteristics of the system presented make the aforementioned operation own certain particularities which are also studied. First, identifier transmissions are random as they depend on movements at kinetic modules--reindeer movements in our application. Not every movement suffices since it must overcome a certain energy threshold. Second, identifier transmissions may not be heard unless there is a battery-powered node in the surroundings. Third, battery-powered nodes do not poll continuously their GPS module, hence localization errors rise even more. Let's recall at this point that such behavior is tight to the aforementioned power saving policies to extend node lifetime. Last, some time is elapsed between the instant an identifier random transmission is detected and the moment the user is aware of such a detection: it takes some time to find a hotspot. Tracking is posed as a problem of a single kinetically-powered target and a population of battery-operated nodes with higher densities than before in localization. Since the latter provide their approximate positions as reference locations, the study is again focused on assessing the impact of such distorted references on performance. Unlike in localization, distance-estimation capabilities based on signal parameters are assumed in this problem. Three variants of the Kalman filter family are applied in this context: the regular Kalman filter, the alpha-beta filter, and the unscented Kalman filter. The study enclosed hereafter comprises both field tests and simulations. Field tests were used mainly to assess the challenges related to power supply and operation in extreme conditions as well as to model nodes and some aspects of their operation in the application scenario. These models are the basics of the simulations developed later. The overall system performance is analyzed according to three metrics: number of detections per kinetic node, accuracy, and latency. The links between these metrics and the operational conditions are also discussed and characterized statistically. Subsequently, such statistical characterization is used to forecast performance figures given specific operational parameters. In tracking, also studied via simulations, nonlinear relationships are found between accuracy and duty cycles and cluster sizes of battery-operated nodes. The solution presented may be more complex in terms of network structure than existing solutions based on GPS collars. However, its main gain lies on taking advantage of users' error tolerance to reduce costs and become more environmentally friendly by diminishing the potential amount of batteries that can be lost. Whether it is applicable or not depends ultimately on the conditions and requirements imposed by users' needs and operational environments, which is, as it has been explained, one of the topics of this Thesis.

Advanced Control Strategies for a 6 DoF Hydraulic Parallel Robot Based on the Dynamic Model

Nowadays robots have made their way into real applications that were prohibitive and unthinkable thirty years ago. This is mainly due to the increase in power computations and the evolution in the theoretical field of robotics and control. Even though there is plenty of information in the current literature on this topics, it is not easy to find clear concepts of how to proceed in order to design and implement a controller for a robot. In general, the design of a controller requires of a complete understanding and knowledge of the system to be controlled. Therefore, for advanced control techniques the systems must be first identified. Once again this particular objective is cumbersome and is never straight forward requiring of great expertise and some criteria must be adopted. On the other hand, the particular problem of designing a controller is even more complex when dealing with Parallel Manipulators (PM), since their closed-loop structures give rise to a highly nonlinear system. Under this basis the current work is developed, which intends to resume and gather all the concepts and experiences involve for the control of an Hydraulic Parallel Manipulator. The main objective of this thesis is to provide a guide remarking all the steps involve in the designing of advanced control technique for PMs. The analysis of the PM under study is minced up to the core of the mechanism: the hydraulic actuators. The actuators are modeled and experimental identified. Additionally, some consideration regarding traditional PID controllers are presented and an adaptive controller is finally implemented. From a macro perspective the kinematic and dynamic model of the PM are presented. Based on the model of the system and extending the adaptive controller of the actuator, a control strategy for the PM is developed and its performance is analyzed with simulation.

Towards a dynamic model for the Urban Heat Island of Madrid

Present research is framed within the project MODIFICA (MODelo predictivo - edIFIcios - Isla de Calor urbanA) aimed at developing a predictive model for dwelling energy performance under the urban heat island effect in order to implement it in the evaluation of real energy demand and consumption of dwellings as well as in the selection of energy retrofitting strategies. It is funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. Despite great advances on building energy performance have been achieved during the last years, available climate data is derived from weather stations placed in the outskirts of the city. Hence, urban heat island effect is not considered in energy simulations, which implies an important lack of accuracy. Since 1980's several international studies have been conducted on the urban heat island (UHI) phenomena, which modifies the atmospheric conditions of the urban centres due to urban agglomeration [1][2][3][4]. In the particular case of Madrid, multiple maps haven been generated using different methodologies during the last two decades [5][6][7]. These maps allow us to study the UHI phenomena from a wide perspective, offering however an static representation of it. Consequently a dynamic model for Madrid UHI is proposed, in order to evaluate it in a continuous way, and to be able to integrate it in building energy simulations.

The folded plate model in structural analysis. Elastic, plastic and dynamic formulations for nonprismatic structures

A specific numerical procedure for the analysis of arbitrary nonprismatic folded plate structures is presented. An elastic model is studied and compared with a harmonic solution for a prismatic structure. An extension to the plastic analysis is developed, and the influence of the structural geometry and loading pattern is analyzed. Nonprismatic practical cases, with arbitrary geometry and loading are shown, as well in the elastic range as in the plastic one. Finally, a dynamic formulation is outlined

Hacia un modelo dinámico para la isla de calor urbana de Madrid = Towards a Dynamic Model for the Urban Heat Island of Madrid

Esta investigación se enmarca dentro del proyecto MODIFICA (modelo predictivo - Edificios - Isla de Calor Urbano), financiado por el Programa de I + D + i Orientada a los Retos de la sociedad 'Retos Investigación' de 2013. Está dirigido a desarrollar un modelo predictivo de eficiencia energética para viviendas, bajo el efecto de isla de calor urbano (AUS) con el fin de ponerla en práctica en la evaluación de la demanda de energía real y el consumo en las viviendas. A pesar de los grandes avances que se han logrado durante los últimos años en el rendimiento energético de edificios, los archivos de tiempo utilizados en la construcción de simulaciones de energía se derivan generalmente de estaciones meteorológicas situadas en las afueras de la ciudad. Por lo tanto, el efecto de la Isla de Calor Urbano (ICU) no se considera en estos cálculos, lo que implica una importante falta de precisión. Centrado en explorar cómo incluir los fenómenos ICU, el presente trabajo recopila y analiza la dinámica por hora de la temperatura en diferentes lugares dentro de la ciudad de Madrid. Abstract This research is framed within the project MODIFICA (Predictive model - Buildings - Urban Heat Island), funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. It is aimed at developing a predictive model for dwelling energy performance under the Urban Heat Island (UHI) effect in order to implement it in the evaluation of real energy demand and consumption in dwellings. Despite great advances on building energy performance have been achieved during the last years, weather files used in building energy simulations are usually derived from weather stations placed in the outskirts of the city. Hence, Urban Heat Island (UHI) effect is not considered in this calculations, which implies an important lack of accuracy. Focused on exploring how to include the UHI phenomena, the present paper compiles and analyses the hourly dynamics of temperature in different locations within the city of Madrid.

Particle swarm optimization with sequential niche technique for dynamic finite element model updating

Peer reviewed

The kinesin walk: a dynamic model with elastically coupled heads.

Recently individual two-headed kinesin molecules have been studied in in vitro motility assays revealing a number of their peculiar transport properties. In this paper we propose a simple and robust model for the kinesin stepping process with elastically coupled Brownian heads that show all of these properties. The analytic and numerical treatment of our model results in a very good fit to the experimental data and practically has no free parameters. Changing the values of the parameters in the restricted range allowed by the related experimental estimates has almost no effect on the shape of the curves and results mainly in a variation of the zero load velocity that can be directly fitted to the measured data. In addition, the model is consistent with the measured pathway of the kinesin ATPase.

Nonuniformity of the constitutive law parameters for shear rupture and quasistatic nucleation to dynamic rupture: a physical model of earthquake generation processes.

Based on the recent high-resolution laboratory experiments on propagating shear rupture, the constitutive law that governs shear rupture processes is discussed in view of the physical principles and constraints, and a specific constitutive law is proposed for shear rupture. It is demonstrated that nonuniform distributions of the constitutive law parameters on the fault are necessary for creating the nucleation process, which consists of two phases: (i) a stable, quasistatic phase, and (ii) the subsequent accelerating phase. Physical models of the breakdown zone and the nucleation zone are presented for shear rupture in the brittle regime. The constitutive law for shear rupture explicitly includes a scaling parameter Dc that enables one to give a common interpretation to both small scale rupture in the laboratory and large scale rupture as earthquake source in the Earth. Both the breakdown zone size Xc and the nucleation zone size L are prescribed and scaled by Dc, which in turn is prescribed by a characteristic length lambda c representing geometrical irregularities of the fault. The models presented here make it possible to understand the earthquake generation process from nucleation to unstable, dynamic rupture propagation in terms of physics. Since the nucleation process itself is an immediate earthquake precursor, deep understanding of the nucleation process in terms of physics is crucial for the short-term (or immediate) earthquake prediction.

A Belief System's Organization Based on a Computational Model of the Dynamic Context: First Approximation

In this article we present a model of organization of a belief system based on a set of binary recursive functions that characterize the dynamic context that modifies the beliefs. The initial beliefs are modeled by a set of two-bit words that grow, update, and generate other beliefs as the different experiences of the dynamic context appear. Reason is presented as an emergent effect of the experience on the beliefs. The system presents a layered structure that allows a functional organization of the belief system. Our approach seems suitable to model different ways of thinking and to apply to different realistic scenarios such as ideologies.

Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.