Integration of multisensor hybrid reasoners to support personal autonomy in the smart home.

The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment¿s reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy.

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.

Cognitive Surveillance Architecture for Scenario Understanding

Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.

Knowledge pipeline in freight pipeline industry: competence- based model for open innovation

There is growing concern over the challenges for innovation in Freight Pipeline industry. Since the early works of Chesbrough a decade ago, we have learned a lot about the content, context and process of open innovation. However, much more research is needed in Freight Pipeline Industry. The reality is that few corporations have institutionalized open innovation practices in ways that have enabled substantial growth or industry leadership. Based on this, we pursue the following question: How does a firm’s integration into knowledge networks depend on its ability to manage knowledge? A competence-based model for freight pipeline organizations is analysed, this model should be understood by any organization in order to be successful in motivating professionals who carry out innovations and play a main role in collaborative knowledge creation processes. This paper aims to explain how can open innovation achieve its potential in most Freight Pipeline Industries.

A New End-User Composition Model to Empower Knowledge Workers to Develop Rich Internet Applications

Enabling real end-user programming development is the next logical stage in the evolution of Internetwide service-based applications. Even so, the vision of end users programming their own web-based solutions has not yet materialized. This will continue to be so unless both industry and the research community rise to the ambitious challenge of devising an end-to-end compositional model for developing a new age of end-user web application development tools. This paper describes a new composition model designed to empower programming-illiterate end users to create and share their own off-the-shelf rich Internet applications in a fully visual fashion. This paper presents the main insights and outcomes of our research and development efforts as part of a number of successful European Union research projects. A framework implementing this model was developed as part of the European Seventh Framework Programme FAST Project and the Spanish EzWeb Project and allowed us to validate the rationale behind our approach.

Knowledge Management and Information Systems based on Workflow Technology

Knowledge management is critical for the success of virtual communities, especially in the case of distributed working groups. A representative example of this scenario is the distributed software development, where it is necessary an optimal coordination to avoid common problems such as duplicated work. In this paper the feasibility of using the workflow technology as a knowledge management system is discussed, and a practical use case is presented. This use case is an information system that has been deployed within a banking environment. It combines common workflow technology with a new conception of the interaction among participants through the extension of existing definition languages.

Vision-based vehicle detection and tracking with a mobile camera using a statistical framework

En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

Desintegración vertical en la industria del automóvil en España: un caso de estudio = Vertical disintegration in the automotive industry in Spain: a case study

En los años recientes se ha producido un rápido crecimiento del comercio internacional en productos semielaborados que son diseñados, producidos y ensamblados en diferentes localizaciones a lo largo de diferentes países, debido principalmente a los siguientes motivos: el desarrollo de las tecnologías de la información, la reducción de los costes de transporte, la liberalización de los mercados de capitales, la armonización de factores institucionales, la integración económica regional que implica la reducción y la eliminación de las barreras al comercio, el desarrollo económico de los países emergentes, el uso de economías de escala, así como una desregulación del comercio internacional. Todo ello ha incrementado la competencia a nivel mundial en los mercados y ha posibilitado a las compañías tener más facilidad de acceso a potenciales mercados, así como a la adquisición de capacidades y conocimientos en otros países y a la realización de alianzas estratégicas internacionales con terceros, creando un entorno con mayor incertidumbre y más exigente para las compañías que componen una industria, y que tiene consecuencias directas en las operaciones de las compañías y en la organización de su producción. Las compañías, para adaptarse, ser competitivas y beneficiarse de este nuevo escenario globalizado y más competitivo, han externalizado partes del proceso productivo hacia proveedores especializados, creando un nuevo mercado intermedio que divide el proceso productivo, anteriormente integrado en las compañías que conforman una industria, entre dos conjuntos de empresas especializadas en esa industria. Dicho proceso suele ocurrir conservando la industria en que tiene lugar, los mismos servicios y productos, la tecnología empleada y las compañías originales que la conformaban previamente a la desintegración vertical. Todo ello es así debido a que es beneficioso tanto para las compañías originales de la industria como para las nuevas compañías de este mercado intermedio por diversos motivos. La desintegración vertical en una industria tiene unas consecuencias que la transforman completamente, así como la forma de operar de las compañías que la integran, incluso para aquellas que permanecen verticalmente integradas. Una de las características más importantes de esta desintegración vertical en una industria es la posibilidad que tiene una compañía de adquirir a una tercera la primera parte del proceso productivo o un bien semielaborado, que posteriormente será finalizado por la compañía adquiriente con la práctica del outsourcing; así mismo, una compañía puede realizar la primera parte del proceso productivo o un bien semielaborado, que posteriormente será finalizado por una tercera compañía con la práctica de la fragmentación. El principal objetivo de la presente investigación es el estudio de los motivos, los facilitadores, los efectos, las consecuencias y los principales factores significativos, microeconómicos y macroeconómicos, que desencadenan o incrementan la práctica de la desintegración vertical en una industria; para ello, la investigación se divide en dos líneas completamente diferenciadas: el estudio de la práctica del outsourcing y, por otro lado, el estudio de la fragmentación por parte de las compañías que componen la industria del automóvil en España, puesto que se trata de una de las industrias más desintegradas verticalmente y fragmentadas, y este sector posee una gran importancia en la economía del país. En primer lugar, se hace una revisión de la literatura existente relativa a los siguientes aspectos: desintegración vertical, outsourcing, fragmentación, teoría del comercio internacional, historia de la industria del automóvil en España y el uso de las aglomeraciones geográficas y las tecnologías de la información en el sector del automóvil. La metodología empleada en cada uno de ellos ha sido diferente en función de la disponibilidad de los datos y del enfoque de investigación: los factores microeconómicos, utilizando el outsourcing, y los factores macroeconómicos, empleando la fragmentación. En el estudio del outsourcing, se usa un índice basado en las compras externas sobre el valor total de la producción. Así mismo, se estudia su correlación y significación con las variables económicas más importantes que definen a una compañía del sector del automóvil, utilizando la técnica estadística de regresión lineal. Aquellas variables relacionadas con la competencia en el mercado, la externalización de las actividades de menor valor añadido y el incremento de la modularización de las actividades de la cadena de valor, han resultado significativas con la práctica del outsourcing. En el estudio de la fragmentación se seleccionan un conjunto de factores macroeconómicos, comúnmente usados en este tipo de investigaciones, relacionados con las principales magnitudes económicas de un país, y un conjunto de factores macroeconómicos, no comúnmente usados en este tipo de investigaciones, relacionados con la libertad económica y el comercio internacional de un país. Se emplea un modelo de regresión logística para identificar qué factores son significativos en la práctica de la fragmentación. De entre todos los factores usados en el modelo, los relacionados con las economías de escala y los costes de servicio han resultado significativos. Los resultados obtenidos de los test estadísticos realizados en el modelo de regresión logística han resultado satisfactorios; por ello, el modelo propuesto de regresión logística puede ser considerado sólido, fiable y versátil; además, acorde con la realidad. De los resultados obtenidos en el estudio del outsourcing y de la fragmentación, combinados conjuntamente con el estado del arte, se concluye que el principal factor que desencadena la desintegración vertical en la industria del automóvil es la competencia en el mercado de vehículos. Cuanto mayor es la demanda de vehículos, más se reducen los beneficios y la rentabilidad para sus fabricantes. Estos, para ser competitivos, diferencian sus productos de la competencia centrándose en las actividades que mayor valor añadido aportan al producto final, externalizando las actividades de menor valor añadido a proveedores especializados, e incrementando la modularidad de las actividades de la cadena de valor. Las compañías de la industria del automóvil se especializan en alguna o varias de estas actividades modularizadas que, combinadas con el uso de factores facilitadores como las economías de escala, las tecnologías de la información, las ventajas de la globalización económica y la aglomeración geográfica de una industria, incrementan y motivan la desintegración vertical en la industria del automóvil, desencadenando la coespecialización en dos sectores claramente diferenciados: el sector de fabricantes de vehículos y el sector de proveedores especializados. Cada uno de ellos se especializa en unas actividades y en unos productos o servicios específicos de la cadena de valor, lo cual genera las siguientes consecuencias en la industria del automóvil: se reducen los costes de transacción en los productos o servicios intercambiados; se incrementan la relación de dependencia entre fabricantes de vehículos y proveedores especializados, provocando un aumento en la cooperación y la coordinación, acelerando el proceso de aprendizaje, posibilitando a ambos adquirir nuevas capacidades, conocimientos y recursos, y creando nuevas ventajas competitivas para ambos; por último, las barreras de entrada a la industria del automóvil y el número de compañías se ven alteradas cambiando su estructura. Como futura línea de investigación, los fabricantes de vehículos tenderán a centrarse en investigar, diseñar y comercializar el producto o servicio, delegando el ensamblaje en manos de nuevos especialistas en la materia, el contract manufacturer; por ello, sería conveniente investigar qué factores motivantes o facilitadores existen y qué consecuencias tendría la implantación de los contract manufacturer en la industria del automóvil. 1.1. ABSTRACT In recent years there has been a rapid growth of international trade in semi-finished products designed, produced and assembled in different locations across different countries, mainly due to the following reasons: development of information technologies, reduction of transportation costs, liberalisation of capital markets, harmonisation of institutional factors, regional economic integration, which involves the reduction and elimination of trade barriers, economic development of emerging countries, use of economies of scale and deregulation of international trade. All these factors have increased competition in markets at a global level and have allowed companies to gain easier access to potential markets and to the acquisition of skills and knowledge in other countries, as well as to the completion of international strategic alliances with third parties, thus creating a more demanding and uncertain environment for these companies constituting an industry, which has a direct impact on the companies' operations and the organization of their production. In order to adapt, be competitive and benefit from this new and more competitive global scenario, companies have outsourced some parts of their production process to specialist suppliers, generating a new intermediate market which divides the production process, previously integrated in the companies that made up the industry, into two sets of companies specialized in that industry. This process often occurs while preserving the industry where it takes place, its same services and products, the technology used and the original companies that formed it prior to vertical disintegration. This is because it is beneficial for both the industry's original companies and the companies belonging to this new intermediate market, for various reasons. Vertical disintegration has consequences which completely transform the industry where it takes place as well as the modus operandi of the companies that are part of it, even of those who remain vertically integrated. One of the most important features of vertical disintegration of an industry is the possibility for a company to acquire from a third one the first part of the production process or a semi-finished product, which will then be finished by the acquiring company through the practice of outsourcing; also, a company can perform the first part of the production process or a semi-finish product, which will then be completed by a third company through the practice of fragmentation. The main objective of this research is to study the motives, facilitators, effects, consequences and major significant microeconomic and macroeconomic factors that trigger or increase the practice of vertical disintegration in a certain industry; in order to do so, research is divided into two completely differentiated lines: on the one hand, the study of the practise of outsourcing and, on the other, the study of fragmentation by companies constituting the automotive industry in Spain, since this is one of the most vertically disintegrated and fragmented industries and this particular sector is of major significance in this country's economy. First, a review is made of the existing literature, on the following aspects: vertical disintegration, outsourcing, fragmentation, international trade theory, history of the automobile industry in Spain and the use of geographical agglomeration and information technologies in the automotive sector. The methodology used for each of these aspects has been different depending on the availability of data and the research approach: the microeconomic factors, using outsourcing, and the macroeconomic factors, using fragmentation. In the study on outsourcing, an index is used based on external purchases in relation to the total value of production. Likewise, their significance and correlation with the major economic variables that define an automotive company are studied, using the statistical technique of linear regression. Variables related to market competition, outsourcing of lowest value-added activities and increased modularisation of the activities of the value chain have turned out to be significant with the practice of outsourcing. In the study of fragmentation, a set of macroeconomic factors commonly used for this type of research, is selected, related to the main economic indicators of a country, as well as a set of macroeconomic factors, not commonly used for this type of research, which are related to economic freedom and the international trade of a certain country. A logistic regression model is used to identify which factors are significant in the practice of fragmentation. Amongst all factors used in the model, those related to economies of scale and service costs have turned out to be significant. The results obtained from the statistical tests performed on the logistic regression model have been successful; hence, the suggested logistic regression model can be considered to be solid, reliable and versatile; likewise, it is in line with reality. From the results obtained in the study of outsourcing and fragmentation, combined with the state of the art, it is concluded that the main factor that triggers vertical disintegration in the automotive industry is competition within the vehicle market. The greater the vehicle demand, the lower the earnings and profitability for manufacturers. These, in order to be competitive, differentiate their products from the competition by focusing on those activities that contribute with the highest added value to the final product, outsourcing the lower valueadded activities to specialist suppliers, and increasing the modularity of the activities of the value chain. Companies in the automotive industry specialize in one or more of these modularised activities which, combined with the use of enabling factors such as economies of scale, information technologies, the advantages of economic globalisation and the geographical agglomeration of an industry, increase and encourage vertical disintegration in the automotive industry, triggering co-specialization in two clearly distinct sectors: the sector of vehicle manufacturers and the specialist suppliers sector. Each of them specializes in certain activities and specific products or services of the value chain, generating the following consequences in the automotive industry: reduction of transaction costs of the goods or services exchanged; growth of the relationship of dependency between vehicle manufacturers and specialist suppliers, which causes an increase in cooperation and coordination, accelerates the learning process, enables both to acquire new skills, knowledge and resources, and creates new competitive advantages for both; finally, barriers to entry the automotive industry and the number of companies are altered, changing their structure. As a future line of research, vehicle manufacturers will tend to focus on researching, designing and marketing the product or service, delegating the assembly in the hands of new specialists in the field, the contract manufacturer; for this reason, it would be useful to investigate what motivating or facilitating factors exist in this respect and what consequences would the implementation of contract manufacturers have in the automotive industry.

A visual framework to accelerate knowledge discovery based on dimensionality reduction minimizing degradation of quality

Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

Using Knowledge Modelling Tools for Agent-Based Systems: The Experience of KSM

The aim of this chapter is to discuss the applicability of recently proposed knowledge modelling tools to the development of agent-based systems. The discussion is derived from the real world experience of a particular software tool called KSM (Knowledge Structure Manager). The chapter provides details about this tool and then proceeds to show in which forms the software may be used to support the development of agent-based systems. Two multiagent systems, one in the field of telecommunications management and the other one in the field of flood control, are described. Conclusions about these studies are presented, summarizing the main contributions that knowledge modelling tools can bring to the development of agent-based systems.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

KATS: A Knowledge Acquisition Tool Based on Electronic Document Processing

This paper describes a particular knowledge acquisition tool for the construction and maintenance of the knowledge model of an intelligent system for emergency management in the field of hydrology. This tool has been developed following an innovative approach directed to end-users non familiarized in computer oriented terminology. According to this approach, the tool is conceived as a document processor specialized in a particular domain (hydrology) in such a way that the whole knowledge model is viewed by the user as an electronic document. The paper first describes the characteristics of the knowledge model of the intelligent system and summarizes the problems that we found during the development and maintenance of such type of model. Then, the paper describes the KATS tool, a software application that we have designed to help in this task to be used by users who are not experts in computer programming. Finally, the paper shows a comparison between KATS and other approaches for knowledge acquisition.

An Analysis Of The Recommended Knowledge For The Software Project Management Discipline

According to the PMBOK (Project Management Body of Knowledge), project management is “the application of knowledge, skills, tools, and techniques to project activities to meet the project requirements” [1]. Project Management has proven to be one of the most important disciplines at the moment of determining the success of any project [2][3][4]. Given that many of the activities covered by this discipline can be said that are “horizontal” for any kind of domain, the importance of acknowledge the concepts and practices becomes even more obvious. The specific case of the projects that fall in the domain of Software Engineering are not the exception about the great influence of Project Management for their success. The critical role that this discipline plays in the industry has come to numbers. A report by McKinsey & Co [4] shows that the establishment of programs for the teaching of critical skills of project management can improve the performance of the project in time and costs. As an example of the above, the reports exposes: “One defense organization used these programs to train several waves of project managers and leaders who together administered a portfolio of more than 1,000 capital projects ranging in Project management size from $100,000 to $500 million. Managers who successfully completed the training were able to cut costs on most projects by between 20 and 35 percent. Over time, the organization expects savings of about 15 percent of its entire baseline spending”. In a white paper by the PMI (Project Management Institute) about the value of project management [5], it is stated that: “Leading organizations across sectors and geographic borders have been steadily embracing project management as a way to control spending and improve project results”. According to the research made by the PMI for the paper, after the economical crisis “Executives discovered that adhering to project management methods and strategies reduced risks, cut costs and improved success rates—all vital to surviving the economic crisis”. In every elite company, a proper execution of the project management discipline has become a must. Several members of the software industry have putted effort into achieving ways of assuring high quality results from projects; many standards, best practices, methodologies and other resources have been produced by experts from different fields of expertise. In the industry and the academic community, there is a continuous research on how to teach better software engineering together with project management [4][6]. For the general practices of Project Management the PMI produced a guide of the required knowledge that any project manager should have in their toolbox to lead any kind of project, this guide is called the PMBOK. On the side of best practices 10 and required knowledge for the Software Engineering discipline, the IEEE (Institute of Electrical and Electronics Engineers) developed the SWEBOK (Software Engineering Body of Knowledge) in collaboration with software industry experts and academic researchers, introducing into the guide many of the needed knowledge for a 5-year expertise software engineer [7]. The SWEBOK also covers management from the perspective of a software project. This thesis is developed to provide guidance to practitioners and members of the academic community about project management applied to software engineering. The way used in this thesis to get useful information for practitioners is to take an industry-approved guide for software engineering professionals such as the SWEBOK, and compare the content to what is found in the PMBOK. After comparing the contents of the SWEBOK and the PMBOK, what is found missing in the SWEBOK is used to give recommendations on how to enrich project management skills for a software engineering professional. Recommendations for members of the academic community on the other hand, are given taking into account the GSwE2009 (Graduated Software Engineering 2009) standard [8]. GSwE2009 is often used as a main reference for software engineering master programs [9]. The standard is mostly based on the content of the SWEBOK, plus some contents that are considered to reinforce the education of software engineering. Given the similarities between the SWEBOK and the GSwE2009, the results of comparing SWEBOK and PMBOK are also considered valid to enrich what the GSwE2009 proposes. So in the end the recommendations for practitioners end up being also useful for the academic community and their strategies to teach project management in the context of software engineering.

Enhancing Evacuation Plans with a Situation Awareness System Based on End-User Knowledge Provision.

Recent disasters have shown that having clearly defined preventive procedures and decisions is a critical component that minimizes evacuation hazards and ensures a rapid and successful evolution of evacuation plans. In this context, we present our Situation-Aware System for enhancing Evacuation Plans (SASEP) system, which allows creating end-user business rules that technically support the specific events, conditions and actions related to evacuation plans. An experimental validation was carried out where 32 people faced a simulated emergency situation, 16 of them using SASEP and the other 16 using a legacy system based on static signs. From the results obtained, we compare both techniques and discuss in which situations SASEP offers a better evacuation route option, confirming that it is highly valuable when there is a threat in the evacuation route. In addition, a study about user satisfaction using both systems is presented showing in which cases the systems are assessed as satisfactory, relevant and not frustrating.

Analysing the complexity of the model-based decision making processes within the industrial management context

PURPOSE The decision-making process plays a key role in organizations. Every decision-making process produces a final choice that may or may not prompt action. Recurrently, decision makers find themselves in the dichotomous question of following a traditional sequence decision-making process where the output of a decision is used as the input of the next stage of the decision, or following a joint decision-making approach where several decisions are taken simultaneously. The implication of the decision-making process will impact different players of the organization. The choice of the decision- making approach becomes difficult to find, even with the current literature and practitioners’ knowledge. The pursuit of better ways for making decisions has been a common goal for academics and practitioners. Management scientists use different techniques and approaches to improve different types of decisions. The purpose of this decision is to use the available resources as well as possible (data and techniques) to achieve the objectives of the organization. The developing and applying of models and concepts may be helpful to solve managerial problems faced every day in different companies. As a result of this research different decision models are presented to contribute to the body of knowledge of management science. The first models are focused on the manufacturing industry and the second part of the models on the health care industry. Despite these models being case specific, they serve the purpose of exemplifying that different approaches to the problems and could provide interesting results. Unfortunately, there is no universal recipe that could be applied to all the problems. Furthermore, the same model could deliver good results with certain data and bad results for other data. A framework to analyse the data before selecting the model to be used is presented and tested in the models developed to exemplify the ideas. METHODOLOGY As the first step of the research a systematic literature review on the joint decision is presented, as are the different opinions and suggestions of different scholars. For the next stage of the thesis, the decision-making process of more than 50 companies was analysed in companies from different sectors in the production planning area at the Job Shop level. The data was obtained using surveys and face-to-face interviews. The following part of the research into the decision-making process was held in two application fields that are highly relevant for our society; manufacturing and health care. The first step was to study the interactions and develop a mathematical model for the replenishment of the car assembly where the problem of “Vehicle routing problem and Inventory” were combined. The next step was to add the scheduling or car production (car sequencing) decision and use some metaheuristics such as ant colony and genetic algorithms to measure if the behaviour is kept up with different case size problems. A similar approach is presented in a production of semiconductors and aviation parts, where a hoist has to change from one station to another to deal with the work, and a jobs schedule has to be done. However, for this problem simulation was used for experimentation. In parallel, the scheduling of operating rooms was studied. Surgeries were allocated to surgeons and the scheduling of operating rooms was analysed. The first part of the research was done in a Teaching hospital, and for the second part the interaction of uncertainty was added. Once the previous problem had been analysed a general framework to characterize the instance was built. In the final chapter a general conclusion is presented. FINDINGS AND PRACTICAL IMPLICATIONS The first part of the contributions is an update of the decision-making literature review. Also an analysis of the possible savings resulting from a change in the decision process is made. Then, the results of the survey, which present a lack of consistency between what the managers believe and the reality of the integration of their decisions. In the next stage of the thesis, a contribution to the body of knowledge of the operation research, with the joint solution of the replenishment, sequencing and inventory problem in the assembly line is made, together with a parallel work with the operating rooms scheduling where different solutions approaches are presented. In addition to the contribution of the solving methods, with the use of different techniques, the main contribution is the framework that is proposed to pre-evaluate the problem before thinking of the techniques to solve it. However, there is no straightforward answer as to whether it is better to have joint or sequential solutions. Following the proposed framework with the evaluation of factors such as the flexibility of the answer, the number of actors, and the tightness of the data, give us important hints as to the most suitable direction to take to tackle the problem. RESEARCH LIMITATIONS AND AVENUES FOR FUTURE RESEARCH In the first part of the work it was really complicated to calculate the possible savings of different projects, since in many papers these quantities are not reported or the impact is based on non-quantifiable benefits. The other issue is the confidentiality of many projects where the data cannot be presented. For the car assembly line problem more computational power would allow us to solve bigger instances. For the operation research problem there was a lack of historical data to perform a parallel analysis in the teaching hospital. In order to keep testing the decision framework it is necessary to keep applying more case studies in order to generalize the results and make them more evident and less ambiguous. The health care field offers great opportunities since despite the recent awareness of the need to improve the decision-making process there are many opportunities to improve. Another big difference with the automotive industry is that the last improvements are not spread among all the actors. Therefore, in the future this research will focus more on the collaboration between academia and the health care sector.