Multiplant strategy under core-periphery structure

A typical implicit assumption on monopolistic competition models for trade and economic geography is that firms can produce and sell only at one place. This paper fallows endogenous determination of the number of plants in a new economic geography model and examine the stable outcomes of organization choice between single-plant and multi-plant in two regions. We explicitly consider the firms' trade-off between larger economies of scale under single plant configuration and the saving in interregional transport costs under multi-plant configuration. We show that organization change arises under decreasing transportation costs and observe several organization configurations under a generalized cost function.

Design and Optimization of Power Delivery and Distribution Systems Using Evolutionary Computation Techniques

Nowadays computing platforms consist of a very large number of components that require to be supplied with diferent voltage levels and power requirements. Even a very small platform, like a handheld computer, may contain more than twenty diferent loads and voltage regulators. The power delivery designers of these systems are required to provide, in a very short time, the right power architecture that optimizes the performance, meets electrical specifications plus cost and size targets. The appropriate selection of the architecture and converters directly defines the performance of a given solution. Therefore, the designer needs to be able to evaluate a significant number of options in order to know with good certainty whether the selected solutions meet the size, energy eficiency and cost targets. The design dificulties of selecting the right solution arise due to the wide range of power conversion products provided by diferent manufacturers. These products range from discrete components (to build converters) to complete power conversion modules that employ diferent manufacturing technologies. Consequently, in most cases it is not possible to analyze all the alternatives (combinations of power architectures and converters) that can be built. The designer has to select a limited number of converters in order to simplify the analysis. In this thesis, in order to overcome the mentioned dificulties, a new design methodology for power supply systems is proposed. This methodology integrates evolutionary computation techniques in order to make possible analyzing a large number of possibilities. This exhaustive analysis helps the designer to quickly define a set of feasible solutions and select the best trade-off in performance according to each application. The proposed approach consists of two key steps, one for the automatic generation of architectures and other for the optimized selection of components. In this thesis are detailed the implementation of these two steps. The usefulness of the methodology is corroborated by contrasting the results using real problems and experiments designed to test the limits of the algorithms.

Intrusion-Resilient Integrity in Data-Centric Unattended WSNs

Unattended Wireless Sensor Networks (UWSNs) operate in autonomous or disconnected mode: sensed data is collected periodically by an itinerant sink. Between successive sink visits, sensor-collected data is subject to some unique vulnerabilities. In particular, while the network is unattended, a mobile adversary (capable of subverting up to a fraction of sensors at a time) can migrate between compromised sets of sensors and inject fraudulent data. In this paper, we provide two collaborative authentication techniques that allow an UWSN to maintain integrity and authenticity of sensor data-in the presence of a mobile adversary-until the next sink visit. Proposed schemes use simple, standard, and inexpensive symmetric cryptographic primitives, coupled with key evolution and few message exchanges. We study their security and effectiveness, both analytically and via simulations. We also assess their robustness and show how to achieve the desired trade-off between performance and security.

A low power routing algorithm for localization in IEEE 802.15.4 networks

Many context-aware applications rely on the knowledge of the position of the user and the surrounding objects to provide advanced, personalized and real-time services. In wide-area deployments, a routing protocol is needed to collect the location information from distant nodes. In this paper, we propose a new source-initiated (on demand) routing protocol for location-aware applications in IEEE 802.15.4 wireless sensor networks. This protocol uses a low power MAC layer to maximize the lifetime of the network while maintaining the communication delay to a low value. Its performance is assessed through experimental tests that show a good trade-off between power consumption and time delay in the localization of a mobile device.

Improving target localization accuracy of wireless visual sensor networks

This paper discusses the target localization problem of wireless visual sensor networks. Specifically, each node with a low-resolution camera extracts multiple feature points to represent the target at the sensor node level. A statistical method of merging the position information of different sensor nodes to select the most correlated feature point pair at the base station is presented. This method releases the influence of the accuracy of target extraction on the accuracy of target localization in universal coordinate system. Simulations show that, compared with other relative approach, our proposed method can generate more desirable target localization's accuracy, and it has a better trade-off between camera node usage and localization accuracy.

Design methodology in multiphase buck converter based on minimum time control for high efficiency RF amplifiers

This paper proposes an interleaved multiphase buck converter with minimum time control strategy for envelope amplifiers in high efficiency RF power amplifiers. The solution of the envelope amplifier is to combine the proposed converter with a linear regulator in series. High system efficiency can be obtained through modulating the supply voltage of the envelope amplifier with the fast output voltage variation of the converter working with several particular duty cycles that achieve total ripple cancellation. The transient model for minimum time control is explained, and the calculation of transient times that are pre-calculated and inserted into a look-up table is presented. The filter design trade-off that limits capability of envelope modulation is also discussed. The experimental results verify the fast voltage transient obtained with a 4-phase buck prototype.

Design of envelope amplifier based on interleaved multiphase buck converter with minimum time control for RF application

In this paper, an interleaved multiphase buck converter with minimum time control strategy for envelope amplifiers in high efficiency RF power amplifiers is proposed. The solution for the envelope amplifier is to combine the proposed converter with a linear regulator in series. High efficiency of envelope amplifier can be obtained through modulating the supply voltage of the linear regulator. Instead of tracking the envelope, the buck converter has discrete output voltage that corresponding to particular duty cycles which achieve total ripple cancellation. The transient model for minimum time control is explained, and the calculation of transient times that are pre-calculated and inserted into a lookup table is presented. The filter design trade-off that limits capability of envelope modulation is also discussed. The experimental results verify the fast voltage transient obtained with a 4-phase buck prototype.

High efficiency envelope tracking buck converter for RFPA using GaN HEMTs

—In this paper, application of a new technological solution for power switches based on Gallium Nitride and a filter design methodology for high efficiency Envelope Amplifier in RF transmitters are proposed. Comparing to Si MOSFETs, GaN HEMTs can provide higher efficiency of the Envelope Amplifier, due to better Figure Of Merit (lower product of on- resistance and gate charge). Benefits of their application were verified through the experimental results. The goal of the filter design is to generate the envelope reference with the minimum possible distortion and to improve the efficiency of the Amplifier, obtaining the optimum trade-off between conduction and switching losses.

Optimum Design of an Envelope Tracking Buck Converter for RF PA using GaN HEMTs

In this paper, filter design methodology and application of GaN HEMTs for high efficiency Envelope Amplifier in RF transmitters are proposed. The main objectives of the filter design are generation of the envelope reference with the minimum possible distortion and high efficiency of the amplifier obtained by the optimum trade-off between conduction and switching losses. This optimum point was determined using power losses model for synchronous buck with sinusoidal output voltage and experimental results showed good correspondence with the model and verified the proposed methodology. On the other hand, comparing to Si MOSFETs, GaN HEMTs can provide higher efficiency of the envelope amplifier, due to superior conductivity and switching characteristics. Experimental results verified benefits of GaN devices comparing to the appliance of Si switching devices with very good Figure Of Merit, for this particular application

Desarrollo de un modelo para la caracterización termoeconómica de ciclos combinados de turbinas de gas y de vapor en condiciones de carga variable

En la actualidad, el interés por las plantas de potencia de ciclo combinado de gas y vapor ha experimentado un notable aumento debido a su alto rendimiento, bajo coste de generación y rápida construcción. El objetivo fundamental de la tesis es profundizar en el conocimiento de esta tecnología, insuficientemente conocida hasta el momento debido al gran número de grados de libertad que existen en el diseño de este tipo de instalaciones. El estudio se realizó en varias fases. La primera consistió en analizar y estudiar las distintas tecnologías que se pueden emplear en este tipo de centrales, algunas muy recientes o en fase de investigación, como las turbinas de gas de geometría variable, las turbinas de gas refrigeradas con agua o vapor del ciclo de vapor o las calderas de paso único que trabajan con agua en condiciones supercríticas. Posteriormente se elaboraron los modelos matemáticos que permiten la simulación termodinámica de cada uno de los componentes que integran las plantas, tanto en el punto de diseño como a cargas parciales. Al mismo tiempo, se desarrolló una metodología novedosa que permite resolver el sistema de ecuaciones que resulta de la simulación de cualquier configuración posible de ciclo combinado. De esa forma se puede conocer el comportamiento de cualquier planta en cualquier punto de funcionamiento. Por último se desarrolló un modelo de atribución de costes para este tipo de centrales. Con dicho modelo, los estudios se pueden realizar no sólo desde un punto de vista termodinámico sino también termoeconómico, con lo que se pueden encontrar soluciones de compromiso entre rendimiento y coste, asignar costes de producción, determinar curvas de oferta, beneficios económicos de la planta y delimitar el rango de potencias donde la planta es rentable. El programa informático, desarrollado en paralelo con los modelos de simulación, se ha empleado para obtener resultados de forma intensiva. El estudio de los resultados permite profundizar ampliamente en el conocimiento de la tecnología y, así, desarrollar una metodología de diseño de este tipo de plantas bajo un criterio termoeconómico. ABSTRACT The growing energy demand and the need of shrinking costs have led to the design of high efficiency and quick installation power plants. The success of combined cycle gas turbine power plants lies on their high efficiency, low cost and short construction lead time. The main objective of the work is to study in detail this technology, which is not thoroughly known owing to the great number of degrees of freedom that exist in the design of this kind of power plants. The study is divided into three parts. Firstly, the different technologies and components that could be used in any configuration of a combined cycle gas turbine power plant are studied. Some of them could be of recent technology, such as the variable inlet guide vane compressors, the H-technology for gas turbine cooling or the once-through heat recovery steam generators, used with water at supercritical conditions. Secondly, a mathematical model has been developed to simulate at full and part load the components of the power plant. At the same time, a new methodology is proposed in order to solve the equation system resulting for any possible power plant configuration. Therefore, any combined cycle gas turbine could be simulated at any part load condition. Finally a themoeconomic model is proposed. This model allows studying the power plant not only from a thermodynamic point of view but also from a thermoeconomic one. Likewise, it allows determining the generating costs or the cash flow, thus achieving a trade off between efficiency and cost. Likewise, the model calculates the part load range where the power plant is profitable. Once the thermodynamic and thermoeconomic models are developed, they are intensively used in order to gain knowledge in the combined cycle gas turbine technology and, in this way, to propose a methodology aimed at the design of this kind of power plants from a thermoeconomic point of view.

Partial order and contextual net semantics for atomic and locally atomic CC programs

We present two concurrent semantics (i.e. semantics where concurrency is explicitely represented) for CC programs with atomic tells. One is based on simple partial orders of computation steps, while the other one is based on contextual nets and it is an extensión of a previous one for eventual CC programs. Both such semantics allow us to derive concurrency, dependency, and nondeterminism information for the considered languages. We prove some properties about the relation between the two semantics, and also about the relation between them and the operational semantics. Moreover, we discuss how to use the contextual net semantics in the context of CLP programs. More precisely, by interpreting concurrency as possible parallelism, our semantics can be useful for a safe parallelization of some CLP computation steps. Dually, the dependency information may also be interpreted as necessary sequentialization, thus possibly exploiting it for the task of scheduling CC programs. Moreover, our semantics is also suitable for CC programs with a new kind of atomic tell (called locally atomic tell), which checks for consistency only the constraints it depends on. Such a tell achieves a reasonable trade-off between efficiency and atomicity, since the checked constraints can be stored in a local memory and are thus easily accessible even in a distributed implementation.

Multi-objective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables

This paper proposes a new multi-objective estimation of distribution algorithm (EDA) based on joint modeling of objectives and variables. This EDA uses the multi-dimensional Bayesian network as its probabilistic model. In this way it can capture the dependencies between objectives, variables and objectives, as well as the dependencies learnt between variables in other Bayesian network-based EDAs. This model leads to a problem decomposition that helps the proposed algorithm to find better trade-off solutions to the multi-objective problem. In addition to Pareto set approximation, the algorithm is also able to estimate the structure of the multi-objective problem. To apply the algorithm to many-objective problems, the algorithm includes four different ranking methods proposed in the literature for this purpose. The algorithm is applied to the set of walking fish group (WFG) problems, and its optimization performance is compared with an evolutionary algorithm and another multi-objective EDA. The experimental results show that the proposed algorithm performs significantly better on many of the problems and for different objective space dimensions, and achieves comparable results on some compared with the other algorithms.

From eventual to atomic and locally atomic CC programs: A concurrent semantics

We present a concurrent semantics (i.e. a semantics where concurrency is explicitely represented) for CC programs with atomic tells. This allows to derive concurrency, dependency, and nondeterminism information for such languages. The ability to treat failure information puts CLP programs also in the range of applicability of our semantics: although such programs are not concurrent, the concurrency information derived in the semantics may be interpreted as possible parallelism, thus allowing to safely parallelize those computation steps which appear to be concurrent in the net. Dually, the dependency information may also be interpreted as necessary sequentialization, thus possibly exploiting it to schedule CC programs. The fact that the semantical structure contains dependency information suggests a new tell operation, which checks for consistency only the constraints it depends on, achieving a reasonable trade-off between efficiency and atomicity.

Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach.

This paper proposes the optimization relaxation approach based on the analogue Hopfield Neural Network (HNN) for cluster refinement of pre-classified Polarimetric Synthetic Aperture Radar (PolSAR) image data. We consider the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution, which is then supplied to the HNN optimization approach. The goal is to improve the classification results obtained by the Wishart approach. The classification improvement is verified by computing a cluster separability coefficient and a measure of homogeneity within the clusters. During the HNN optimization process, for each iteration and for each pixel, two consistency coefficients are computed, taking into account two types of relations between the pixel under consideration and its corresponding neighbors. Based on these coefficients and on the information coming from the pixel itself, the pixel under study is re-classified. Different experiments are carried out to verify that the proposed approach outperforms other strategies, achieving the best results in terms of separability and a trade-off with the homogeneity preserving relevant structures in the image. The performance is also measured in terms of computational central processing unit (CPU) times.

Tracking recurrent concepts using context

The problem of recurring concepts in data stream classification is a special case of concept drift where concepts may reappear. Although several existing methods are able to learn in the presence of concept drift, few consider contextual information when tracking recurring concepts. Nevertheless, in many real-world scenarios context information is available and can be exploited to improve existing approaches in the detection or even anticipation of recurring concepts. In this work, we propose the extension of existing approaches to deal with the problem of recurring concepts by reusing previously learned decision models in situations where concepts reappear. The different underlying concepts are identified using an existing drift detection method, based on the error-rate of the learning process. A method to associate context information and learned decision models is proposed to improve the adaptation to recurring concepts. The method also addresses the challenge of retrieving the most appropriate concept for a particular context. Finally, to deal with situations of memory scarcity, an intelligent strategy to discard models is proposed. The experiments conducted so far, using synthetic and real datasets, show promising results and make it possible to analyze the trade-off between the accuracy gains and the learned models storage cost.