An Internet of Things approach for managing smart services provided by wearable devices.

The Internet of Things (IoT) is growing at a fast pace with new devices getting connected all the time. A new emerging group of these devices are the wearable devices, and Wireless Sensor Networks are a good way to integrate them in the IoT concept and bring new experiences to the daily life activities. In this paper we present an everyday life application involving a WSN as the base of a novel context-awareness sports scenario where physiological parameters are measured and sent to the WSN by wearable devices. Applications with several hardware components introduce the problem of heterogeneity in the network. In order to integrate different hardware platforms and to introduce a service-oriented semantic middleware solution into a single application, we propose the use of an Enterprise Service Bus (ESB) as a bridge for guaranteeing interoperability and integration of the different environments, thus introducing a semantic added value needed in the world of IoT-based systems. This approach places all the data acquired (e.g., via Internet data access) at application developers disposal, opening the system to new user applications. The user can then access the data through a wide variety of devices (smartphones, tablets, computers) and Operating Systems (Android, iOS, Windows, Linux, etc.).

Collective Organization of Complex Networks: Emergent Scales, Vulnerability, and Targeting of Desired Dynamics

Cuando una colectividad de sistemas dinámicos acoplados mediante una estructura irregular de interacciones evoluciona, se observan dinámicas de gran complejidad y fenómenos emergentes imposibles de predecir a partir de las propiedades de los sistemas individuales. El objetivo principal de esta tesis es precisamente avanzar en nuestra comprensión de la relación existente entre la topología de interacciones y las dinámicas colectivas que una red compleja es capaz de mantener. Siendo este un tema amplio que se puede abordar desde distintos puntos de vista, en esta tesis se han estudiado tres problemas importantes dentro del mismo que están relacionados entre sí. Por un lado, en numerosos sistemas naturales y artificiales que se pueden describir mediante una red compleja la topología no es estática, sino que depende de la dinámica que se desarrolla en la red: un ejemplo son las redes de neuronas del cerebro. En estas redes adaptativas la propia topología emerge como consecuencia de una autoorganización del sistema. Para conocer mejor cómo pueden emerger espontáneamente las propiedades comúnmente observadas en redes reales, hemos estudiado el comportamiento de sistemas que evolucionan según reglas adaptativas locales con base empírica. Nuestros resultados numéricos y analíticos muestran que la autoorganización del sistema da lugar a dos de las propiedades más universales de las redes complejas: a escala mesoscópica, la aparición de una estructura de comunidades, y, a escala macroscópica, la existencia de una ley de potencias en la distribución de las interacciones en la red. El hecho de que estas propiedades aparecen en dos modelos con leyes de evolución cuantitativamente distintas que siguen unos mismos principios adaptativos sugiere que estamos ante un fenómeno que puede ser muy general, y estar en el origen de estas propiedades en sistemas reales. En segundo lugar, proponemos una medida que permite clasificar los elementos de una red compleja en función de su relevancia para el mantenimiento de dinámicas colectivas. En concreto, estudiamos la vulnerabilidad de los distintos elementos de una red frente a perturbaciones o grandes fluctuaciones, entendida como una medida del impacto que estos acontecimientos externos tienen en la interrupción de una dinámica colectiva. Los resultados que se obtienen indican que la vulnerabilidad dinámica es sobre todo dependiente de propiedades locales, por tanto nuestras conclusiones abarcan diferentes topologías, y muestran la existencia de una dependencia no trivial entre la vulnerabilidad y la conectividad de los elementos de una red. Finalmente, proponemos una estrategia de imposición de una dinámica objetivo genérica en una red dada e investigamos su validez en redes con diversas topologías que mantienen regímenes dinámicos turbulentos. Se obtiene como resultado que las redes heterogéneas (y la amplia mayora de las redes reales estudiadas lo son) son las más adecuadas para nuestra estrategia de targeting de dinámicas deseadas, siendo la estrategia muy efectiva incluso en caso de disponer de un conocimiento muy imperfecto de la topología de la red. Aparte de la relevancia teórica para la comprensión de fenómenos colectivos en sistemas complejos, los métodos y resultados propuestos podrán dar lugar a aplicaciones en sistemas experimentales y tecnológicos, como por ejemplo los sistemas neuronales in vitro, el sistema nervioso central (en el estudio de actividades síncronas de carácter patológico), las redes eléctricas o los sistemas de comunicaciones. ABSTRACT The time evolution of an ensemble of dynamical systems coupled through an irregular interaction scheme gives rise to dynamics of great of complexity and emergent phenomena that cannot be predicted from the properties of the individual systems. The main objective of this thesis is precisely to increase our understanding of the interplay between the interaction topology and the collective dynamics that a complex network can support. This is a very broad subject, so in this thesis we will limit ourselves to the study of three relevant problems that have strong connections among them. First, it is a well-known fact that in many natural and manmade systems that can be represented as complex networks the topology is not static; rather, it depends on the dynamics taking place on the network (as it happens, for instance, in the neuronal networks in the brain). In these adaptive networks the topology itself emerges from the self-organization in the system. To better understand how the properties that are commonly observed in real networks spontaneously emerge, we have studied the behavior of systems that evolve according to local adaptive rules that are empirically motivated. Our numerical and analytical results show that self-organization brings about two of the most universally found properties in complex networks: at the mesoscopic scale, the appearance of a community structure, and, at the macroscopic scale, the existence of a power law in the weight distribution of the network interactions. The fact that these properties show up in two models with quantitatively different mechanisms that follow the same general adaptive principles suggests that our results may be generalized to other systems as well, and they may be behind the origin of these properties in some real systems. We also propose a new measure that provides a ranking of the elements in a network in terms of their relevance for the maintenance of collective dynamics. Specifically, we study the vulnerability of the elements under perturbations or large fluctuations, interpreted as a measure of the impact these external events have on the disruption of collective motion. Our results suggest that the dynamic vulnerability measure depends largely on local properties (our conclusions thus being valid for different topologies) and they show a non-trivial dependence of the vulnerability on the connectivity of the network elements. Finally, we propose a strategy for the imposition of generic goal dynamics on a given network, and we explore its performance in networks with different topologies that support turbulent dynamical regimes. It turns out that heterogeneous networks (and most real networks that have been studied belong in this category) are the most suitable for our strategy for the targeting of desired dynamics, the strategy being very effective even when the knowledge on the network topology is far from accurate. Aside from their theoretical relevance for the understanding of collective phenomena in complex systems, the methods and results here discussed might lead to applications in experimental and technological systems, such as in vitro neuronal systems, the central nervous system (where pathological synchronous activity sometimes occurs), communication systems or power grids.

Providing a consensus definition for the term "Smart Product"

The term "Smart Product" has become commonly used in recent years. This is because there has been an increasing interest in these kinds of products as part of the consumer goods industry, impacting everyday life and industry. Nevertheless, the term "Smart Product" is used with different meanings in different contexts and application domains. The use of the term "Smart Product" with different meanings and underlying semantics can create important misunderstandings and dissent. The aim of this paper is to analyze the different definitions of Smart Product available in the literature, and to explore and analyze their commonalities and differences, in order to provide a consensus definition that satisfies, and can therefore be used by, all parties. To embrace the identified definitions, the concept of "Smart Thing" is introduced. The methodology used was a systematic literature review. The definition is expressed as an ontology.

A new dominance intensity method to deal with ordinal information about a DM's preferences within MAVT

Dominance measuring methods are a new approach to deal with complex decision-making problems with imprecise information. These methods are based on the computation of pairwise dominance values and exploit the information in the dominance matrix in dirent ways to derive measures of dominance intensity and rank the alternatives under consideration. In this paper we propose a new dominance measuring method to deal with ordinal information about decision-maker preferences in both weights and component utilities. It takes advantage of the centroid of the polytope delimited by ordinal information and builds triangular fuzzy numbers whose distances to the crisp value 0 constitute the basis for the de?nition of a dominance intensity measure. Monte Carlo simulation techniques have been used to compare the performance of this method with other existing approaches.

Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics

In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.

Multi-argument fuzzy measures on lattices of fuzzy sets

In this paper, we axiomatically introduce fuzzy multi-measures on bounded lattices. In particular, we make a distinction between four different types of fuzzy set multi-measures on a universe X, considering both the usual or inverse real number ordering of this lattice and increasing or decreasing monotonicity with respect to the number of arguments. We provide results from which we can derive families of measures that hold for the applicable conditions in each case.

Gramáticas lógicas: resolución de problemas en lenguaje natural

Esta tesis tiene por objeto estudiar las posibilidades de realizar en castellano tareas relativas a la resolución de problemas con sistemas basados en el conocimiento. En los dos primeros capítulos se plantea un análisis de la trayectoria seguida por las técnicas de tratamiento del lenguaje natural, prestando especial interés a los formalismos lógicos para la comprensión del lenguaje. Seguidamente, se plantea una valoración de la situación actual de los sistemas de tratamiento del lenguaje natural. Finalmente, se presenta lo que constituye el núcleo de este trabajo, un sistema llamado Sirena, que permite realizar tareas de adquisición, comprensión, recuperación y explicación de conocimiento en castellano con sistemas basados en el conocimiento. Este sistema contiene un subconjunto del castellano amplio pero simple formalizado con una gramática lógica. El significado del conocimiento se basa en la lógica y ha sido implementado en el lenguaje de programación lógica Prolog II vS. Palabras clave: Programación Lógica, Comprensión del Lenguaje Natural, Resolución de Problemas, Gramáticas Lógicas, Lingüistica Computacional, Inteligencia Artificial.---ABSTRACT---The purpose of this thesis is to study the possibi1 ities of performing in Spanish problem solving tasks with knowledge based systems. Ule study the development of the techniques for natural language processing with a particular interest in the logical formalisms that have been used to understand natural languages. Then, we present an evaluation of the current state of art in the field of natural language processing systems. Finally, we introduce the main contribution of our work, Sirena a system that allows the adquisition, understanding, retrieval and explanation of knowledge in Spanish with knowledge based systems. Sirena can deal with a large, although simple» subset of Spanish. This subset has been formalised by means of a logic grammar and the meaning of knowledge is based on logic. Sirena has been implemented in the programming language Prolog II v2. Keywords: Logic Programming, Understanding Natural Language, Problem Solving, Logic Grammars, Cumputational Linguistic, Artificial Intelligence.

Methodology for developing an advanced communications system for the Deaf in a new domain

A methodology for developing an advanced communications system for the Deaf in a new domain is presented in this paper. This methodology is a user-centred design approach consisting of four main steps: requirement analysis, parallel corpus generation, technology adaptation to the new domain, and finally, system evaluation. During the requirement analysis, both the user and technical requirements are evaluated and defined. For generating the parallel corpus, it is necessary to collect Spanish sentences in the new domain and translate them into LSE (Lengua de Signos Española: Spanish Sign Language). LSE is represented by glosses and using video recordings. This corpus is used for training the two main modules of the advanced communications system to the new domain: the spoken Spanish into the LSE translation module and the Spanish generation from the LSE module. The main aspects to be generated are the vocabularies for both languages (Spanish words and signs), and the knowledge for translating in both directions. Finally, the field evaluation is carried out with deaf people using the advanced communications system to interact with hearing people in several scenarios. In this evaluation, the paper proposes several objective and subjective measurements for evaluating the performance. In this paper, the new considered domain is about dialogues in a hotel reception. Using this methodology, the system was developed in several months, obtaining very good performance: good translation rates (10% Sign Error Rate) with small processing times, allowing face-to-face dialogues.

Contribución a la localización en interiores basada en comunicaciones inalámbricas

Determinar con buena precisión la posición en la que se encuentra un terminal móvil, cuando éste se halla inmerso en un entorno de interior (centros comerciales, edificios de oficinas, aeropuertos, estaciones, túneles, etc), es el pilar básico sobre el que se sustentan un gran número de aplicaciones y servicios. Muchos de esos servicios se encuentran ya disponibles en entornos de exterior, aunque los entornos de interior se prestan a otros servicios específicos para ellos. Ese número, sin embargo, podría ser significativamente mayor de lo que actualmente es, si no fuera necesaria una costosa infraestructura para llevar a cabo el posicionamiento con la precisión adecuada a cada uno de los hipotéticos servicios. O, igualmente, si la citada infraestructura pudiera tener otros usos distintos, además del relacionado con el posicionamiento. La usabilidad de la misma infraestructura para otros fines distintos ofrecería la oportunidad de que la misma estuviera ya presente en las diferentes localizaciones, porque ha sido previamente desplegada para esos otros usos; o bien facilitaría su despliegue, porque el coste de esa operación ofreciera un mayor retorno de usabilidad para quien lo realiza. Las tecnologías inalámbricas de comunicaciones basadas en radiofrecuencia, ya en uso para las comunicaciones de voz y datos (móviles, WLAN, etc), cumplen el requisito anteriormente indicado y, por tanto, facilitarían el crecimiento de las aplicaciones y servicios basados en el posicionamiento, en el caso de poderse emplear para ello. Sin embargo, determinar la posición con el nivel de precisión adecuado mediante el uso de estas tecnologías, es un importante reto hoy en día. El presente trabajo pretende aportar avances significativos en este campo. A lo largo del mismo se llevará a cabo, en primer lugar, un estudio de los principales algoritmos y técnicas auxiliares de posicionamiento aplicables en entornos de interior. La revisión se centrará en aquellos que sean aptos tanto para tecnologías móviles de última generación como para entornos WLAN. Con ello, se pretende poner de relieve las ventajas e inconvenientes de cada uno de estos algoritmos, teniendo como motivación final su aplicabilidad tanto al mundo de las redes móviles 3G y 4G (en especial a las femtoceldas y small-cells LTE) como al indicado entorno WLAN; y teniendo siempre presente que el objetivo último es que vayan a ser usados en interiores. La principal conclusión de esa revisión es que las técnicas de triangulación, comúnmente empleadas para realizar la localización en entornos de exterior, se muestran inútiles en los entornos de interior, debido a efectos adversos propios de este tipo de entornos como la pérdida de visión directa o los caminos múltiples en el recorrido de la señal. Los métodos de huella radioeléctrica, más conocidos bajo el término inglés “fingerprinting”, que se basan en la comparación de los valores de potencia de señal que se están recibiendo en el momento de llevar a cabo el posicionamiento por un terminal móvil, frente a los valores registrados en un mapa radio de potencias, elaborado durante una fase inicial de calibración, aparecen como los mejores de entre los posibles para los escenarios de interior. Sin embargo, estos sistemas se ven también afectados por otros problemas, como por ejemplo los importantes trabajos a realizar para ponerlos en marcha, y la variabilidad del canal. Frente a ellos, en el presente trabajo se presentan dos contribuciones originales para mejorar los sistemas basados en los métodos fingerprinting. La primera de esas contribuciones describe un método para determinar, de manera sencilla, las características básicas del sistema a nivel del número de muestras necesarias para crear el mapa radio de la huella radioeléctrica de referencia, junto al número mínimo de emisores de radiofrecuencia que habrá que desplegar; todo ello, a partir de unos requerimientos iniciales relacionados con el error y la precisión buscados en el posicionamiento a realizar, a los que uniremos los datos correspondientes a las dimensiones y realidad física del entorno. De esa forma, se establecen unas pautas iniciales a la hora de dimensionar el sistema, y se combaten los efectos negativos que, sobre el coste o el rendimiento del sistema en su conjunto, son debidos a un despliegue ineficiente de los emisores de radiofrecuencia y de los puntos de captura de su huella. La segunda contribución incrementa la precisión resultante del sistema en tiempo real, gracias a una técnica de recalibración automática del mapa radio de potencias. Esta técnica tiene en cuenta las medidas reportadas continuamente por unos pocos puntos de referencia estáticos, estratégicamente distribuidos en el entorno, para recalcular y actualizar las potencias registradas en el mapa radio. Un beneficio adicional a nivel operativo de la citada técnica, es la prolongación del tiempo de usabilidad fiable del sistema, bajando la frecuencia en la que se requiere volver a capturar el mapa radio de potencias completo. Las mejoras anteriormente citadas serán de aplicación directa en la mejora de los mecanismos de posicionamiento en interiores basados en la infraestructura inalámbrica de comunicaciones de voz y datos. A partir de ahí, esa mejora será extensible y de aplicabilidad sobre los servicios de localización (conocimiento personal del lugar donde uno mismo se encuentra), monitorización (conocimiento por terceros del citado lugar) y seguimiento (monitorización prolongada en el tiempo), ya que todos ellas toman como base un correcto posicionamiento para un adecuado desempeño. ABSTRACT To find the position where a mobile is located with good accuracy, when it is immersed in an indoor environment (shopping centers, office buildings, airports, stations, tunnels, etc.), is the cornerstone on which a large number of applications and services are supported. Many of these services are already available in outdoor environments, although the indoor environments are suitable for other services that are specific for it. That number, however, could be significantly higher than now, if an expensive infrastructure were not required to perform the positioning service with adequate precision, for each one of the hypothetical services. Or, equally, whether that infrastructure may have other different uses beyond the ones associated with positioning. The usability of the same infrastructure for purposes other than positioning could give the opportunity of having it already available in the different locations, because it was previously deployed for these other uses; or facilitate its deployment, because the cost of that operation would offer a higher return on usability for the deployer. Wireless technologies based on radio communications, already in use for voice and data communications (mobile, WLAN, etc), meet the requirement of additional usability and, therefore, could facilitate the growth of applications and services based on positioning, in the case of being able to use it. However, determining the position with the appropriate degree of accuracy using these technologies is a major challenge today. This paper provides significant advances in this field. Along this work, a study about the main algorithms and auxiliar techniques related with indoor positioning will be initially carried out. The review will be focused in those that are suitable to be used with both last generation mobile technologies and WLAN environments. By doing this, it is tried to highlight the advantages and disadvantages of each one of these algorithms, having as final motivation their applicability both in the world of 3G and 4G mobile networks (especially in femtocells and small-cells of LTE) and in the WLAN world; and having always in mind that the final aim is to use it in indoor environments. The main conclusion of that review is that triangulation techniques, commonly used for localization in outdoor environments, are useless in indoor environments due to adverse effects of such environments as loss of sight or multipaths. Triangulation techniques used for external locations are useless due to adverse effects like the lack of line of sight or multipath. Fingerprinting methods, based on the comparison of Received Signal Strength values measured by the mobile phone with a radio map of RSSI Recorded during the calibration phase, arise as the best methods for indoor scenarios. However, these systems are also affected by other problems, for example the important load of tasks to be done to have the system ready to work, and the variability of the channel. In front of them, in this paper we present two original contributions to improve the fingerprinting methods based systems. The first one of these contributions describes a method for find, in a simple way, the basic characteristics of the system at the level of the number of samples needed to create the radio map inside the referenced fingerprint, and also by the minimum number of radio frequency emitters that are needed to be deployed; and both of them coming from some initial requirements for the system related to the error and accuracy in positioning wanted to have, which it will be joined the data corresponding to the dimensions and physical reality of the environment. Thus, some initial guidelines when dimensioning the system will be in place, and the negative effects into the cost or into the performance of the whole system, due to an inefficient deployment of the radio frequency emitters and of the radio map capture points, will be minimized. The second contribution increases the resulting accuracy of the system when working in real time, thanks to a technique of automatic recalibration of the power measurements stored in the radio map. This technique takes into account the continuous measures reported by a few static reference points, strategically distributed in the environment, to recalculate and update the measurements stored into the map radio. An additional benefit at operational level of such technique, is the extension of the reliable time of the system, decreasing the periodicity required to recapture the radio map within full measurements. The above mentioned improvements are directly applicable to improve indoor positioning mechanisms based on voice and data wireless communications infrastructure. From there, that improvement will be also extensible and applicable to location services (personal knowledge of the location where oneself is), monitoring (knowledge by other people of your location) and monitoring (prolonged monitoring over time) as all of them are based in a correct positioning for proper performance.

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.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

RECLAMO: virtual and collaborative honeynets based on trust management and autonomous systems applied to intrusion management

Security intrusions in large systems is a problem due to its lack of scalability with the current IDS-based approaches. This paper describes the RECLAMO project, where an architecture for an Automated Intrusion Response System (AIRS) is being proposed. This system will infer the most appropriate response for a given attack, taking into account the attack type, context information, and the trust and reputation of the reporting IDSs. RECLAMO is proposing a novel approach: diverting the attack to a specific honeynet that has been dynamically built based on the attack information. Among all components forming the RECLAMO's architecture, this paper is mainly focused on defining a trust and reputation management model, essential to recognize if IDSs are exposing an honest behavior in order to accept their alerts as true. Experimental results confirm that our model helps to encourage or discourage the launch of the automatic reaction process.

Energy Storage Systems for Electric Vehicles: Performance Comparison based on a Simple Equivalent Circuit and Experimental Tests

The decision to select the most suitable type of energy storage system for an electric vehicle is always difficult, since many conditionings must be taken into account. Sometimes, this study can be made by means of complex mathematical models which represent the behavior of a battery, ultracapacitor or some other devices. However, these models are usually too dependent on parameters that are not easily available, which usually results in nonrealistic results. Besides, the more accurate the model, the more specific it needs to be, which becomes an issue when comparing systems of different nature. This paper proposes a practical methodology to compare different energy storage technologies. This is done by means of a linear approach of an equivalent circuit based on laboratory tests. Via these tests, the internal resistance and the self-discharge rate are evaluated, making it possible to compare different energy storage systems regardless their technology. Rather simple testing equipment is sufficient to give a comparative idea of the differences between each system, concerning issues such as efficiency, heating and self-discharge, when operating under a certain scenario. The proposed methodology is applied to four energy storage systems of different nature for the sake of illustration.

A Knowledge-based Approach for Automatic Generation of Summaries of Behavior

Effective automatic summarization usually requires simulating human reasoning such as abstraction or relevance reasoning. In this paper we describe a solution for this type of reasoning in the particular case of surveillance of the behavior of a dynamic system using sensor data. The paper first presents the approach describing the required type of knowledge with a possible representation. This includes knowledge about the system structure, behavior, interpretation and saliency. Then, the paper shows the inference algorithm to produce a summarization tree based on the exploitation of the physical characteristics of the system. The paper illustrates how the method is used in the context of automatic generation of summaries of behavior in an application for basin surveillance in the presence of river floods.

On the analytical approach for modeling photovoltaic systems behavior

The 1-diode/2-resistors electric circuit equivalent to a photovoltaic system is analyzed. The equations at particular points of the I–V curve are studied considering the maximum number of terms. The maximum power point as a boundary condition is given special attention. A new analytical method is developed based on a reduced amount of information, consisting in the normal manufacturer data. Results indicate that this new method is faster than numerical methods and has similar (or better) accuracy than other existing methods, numerical or analytical.