24 resultados para Entity-Relationship Model

em Universidad Politécnica de Madrid


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En un mundo donde el cambio es constante y cada vez más vertiginoso, la innovación es el combustible que utilizan las empresas que permite su renovación constante y, como consecuencia, su supervivencia en el largo plazo. La innovación es sin dudas un elemento fundamental para determinar la capacidad de las empresas en crear valor a lo largo del tiempo, y por ello, las empresas suelen dedicar esfuerzos considerables y recursos de todo tipo para identificar nuevas alternativas de innovación que se adapten a su estrategia, cultura, objetivos y ambiciones corporativas. Una forma específica para llevar a cabo la innovación es la innovación abierta. Esta se entiende como la innovación que se realiza de manera conjunta con otras empresas o participantes del ecosistema. Cabe la aclaración que en este documento se toma la definición de ecosistema referida al conjunto de clientes, proveedores, competidores y otros participantes que interactúan en un mismo entorno donde existen posiciones de liderazgo que pueden cambiar a lo largo del tiempo (Moore 1996). El termino de innovación abierta fue acuñado por Henry Chesbrough hace algo mas de una década para referirse a esta forma particular de organizar la innovación corporativa. Como se observa en el presente trabajo la innovación abierta es un nuevo paradigma que ha capturado el interés académico y empresarial desde algo más de una década. Se verán varios casos de innovación abierta que se están llevando a cabo en diversos países y sectores de la economía. El objetivo principal de este trabajo de investigación es el de desarrollar y explicar un modelo de relación entre la innovación abierta y la creación de valor en las empresas. Para ello, y como objetivos secundarios, se ha investigado los elementos de un Programa de Innovación Abierta, los impulsores 1 de creación de valor, el proceso de creación de valor y, finalmente, la interacción entre estos tres elementos. Como producto final de la investigación se ha desarrollado un marco teórico general para establecer la conexión entre la innovación abierta y la creación de valor que facilita la explicación de la interacción entre ambos elementos. Se observa a partir de los casos de estudio que la innovación abierta puede abarcar todos los sectores de la economía, múltiples geografías y empresas de distintos tamaños (grandes empresas, pequeñas y medianas empresas, incluso empresas de reciente creación) cada una de ellas con distinta relevancia dentro del ecosistema en el que participan. Elementos de un Programa de Innovación Abierta La presente investigación comienza con la enumeración de los distintos elementos que se encuentran presentes en los Programas de Innovación Abierta. De esta manera, se describen los diversos elementos que se han identificado a través de la revisión de la literatura académica que se ha llevado a cabo. En función de una serie de características comunes, los distintos elementos se agrupan en cuatro niveles diferentes para lograr un mejor entendimiento de los Programas de Innovación Abierta. A continuación se detallan estos elementos § Organización del Programa. En primer lugar se menciona la existencia de una estructura organizativa capaz de cumplir una serie de objetivos establecidos previamente. Por su naturaleza de innovación abierta deberá existir cierto grado de interacción entre los distintos miembros que participen en el proceso de innovación. § Talento Interno. El talento interno asociado a los programas de innovación abierta juega un rol fundamental en la ejecución y éxito del programa. Bajo este nivel se asocian elementos como la cultura de innovación abierta y el liderazgo como mecanismo para entender uno de los elementos que explica el grado de adopción de innovación en una empresa. Estrechamente ligados al liderazgo se encuentran los comportamientos organizacionales como elementos diferenciadores para aumentar las posibilidades de creación de innovación abierta. § Infraestructura. En este nivel se agrupan los elementos relacionados con la infraestructura tecnológica necesaria para llevar a cabo el programa incluyendo los procesos productivos y las herramientas necesarias para la gestión cotidiana. § Instrumentos. Por último, se mencionan los instrumentos o vehículos que se utilizan en el entorno corporativo para implementar innovación abierta. Hay varios instrumentos disponibles como las incubadoras corporativas, los acuerdos de licenciamiento o las áreas de capital de riesgo corporativo. Para este último caso se hará una mención especial por el creciente y renovado interés que ha despertado tanto en el entorno académico como empresarial. Se ha identificado al capital de riesgo corporativo como un de los elementos diferenciales en el desarrollo de la estrategia de innovación abierta de las empresas ya que suele aportar credibilidad, capacidad y soporte tecnológico. Estos cuatro elementos, interactuando de manera conjunta y coordinada, tienen la capacidad de crear, potenciar e incluso desarrollar impulsores de creación de valor que impactan en la estrategia y organización de la empresa y partir de aquí en su desempeño financiero a lo largo del tiempo. Los Impulsores de Creación de Valor Luego de identificar, ordenar y describir los distintos elementos presentes en un Programa de Innovación Abierta se ha avanzado en la investigación con los impulsores de creación de valor. Estos pueden definirse como elementos que potencian o determinan la capacidad de crear valor dentro del entorno empresarial. Como se puede observar, se detallan estos impulsores como punto de interacción entre los elementos del programa y el proceso de creación de valor corporativo. A lo largo de la presente investigación se han identificado 6 impulsores de creación de valor presentes en un Programa de Innovación Abierta. § Nuevos Productos y Servicios. El impulsor de creación de valor más directo y evidente en un Programa de Innovación Abierta es la capacidad de crear nuevos productos y servicios dado que se relacionan directamente con el proceso de innovación de la empresa § Acceso a Mercados Adyacentes. El proceso de innovación también puede ser una fuente de valor al permitir que la empresa acceda a mercados cercanos a su negocio tradicional, es decir satisfaciendo nuevas necesidades de sus clientes existentes o de nuevos clientes en otro mercado. § Disponibilidad de Tecnologías. La disponibilidad de tecnologías es un impulsor en si mismo de la creación de valor. Estas pueden ser tanto complementarias como de apalancamiento de tecnologías ya existentes dentro de la empresa y que tengan la función de transformar parte de los componentes de la estrategia de la empresa. § Atracción del Talento Externo. La introducción de un Programa de Innovación Abierta en una empresa ofrece la oportunidad de interactuar con otras organizaciones del ecosistema y, por tanto, de atraer el talento externo. La movilidad del talento es una característica singular de la innovación abierta. § Participación en un Ecosistema Virtuoso. Se ha observado que las acciones realizadas en el entorno por cualquiera de los participantes también tendrán un claro impacto en la creación de valor para el resto de participantes por lo tanto la participación en un ecosistema virtuoso es un impulsor de creación de valor presente en la innovación abierta. § Tecnología “Dentro--‐Fuera”. Como último impulsor de valor es necesario comentar que la dirección que puede seguir la tecnología puede ser desde la empresa hacia el resto del ecosistema generando valor a partir de disponibilizar tecnologías que no son de utilidad interna para la empresa. Estos seis impulsores de creación de valor, presentes en los procesos de innovación corporativos, tienen la capacidad de influir en la estrategia y organización de la empresa aumentando su habilidad de crear valor. El Proceso de Creación de Valor en las Empresas Luego se ha investigado la práctica de la gestión basada en valor que sostiene la necesidad de alinear la estrategia corporativa y el diseño de la organización con el fin de obtener retornos financieros superiores al resto de los competidores de manera sostenida, y finalmente crear valor a lo largo del tiempo. Se describe como los impulsores de creación de valor influyen en la creación y fortalecimiento de las ventajas competitivas de la empresa impactando y alineando su estrategia y organización. Durante la investigación se ha identificado que las opciones reales pueden utilizarse como una herramienta para gestionar entornos de innovación abierta que, por definición, tienen altos niveles de incertidumbre. Las opciones reales aportan una capacidad para la toma de decisiones de forma modular y flexible que pueden aplicarse al entorno corporativo. Las opciones reales han sido particularmente diseñadas para entender, estructurar y gestionar entornos de múltiples incertidumbres y por ello tienen una amplia aplicación en los entornos de innovación. Se analizan los usos potenciales de las opciones reales como complemento a los distintos instrumentos identificados en los Programas de Innovación Abierta. La Interacción Entre los Programas de Innovación Abierta, los Impulsores de Creación de Valor y el Proceso de Creación de Valor A modo de conclusión del presente trabajo se puede mencionar que se ha desarrollado un marco general de creación de valor en el entorno de los Programas de Innovación Abierta. Este marco general incluye tres elementos fundamentales. En primer lugar describe los elementos que se encuentran presentes en los Programas de Innovación Abierta, en segundo lugar como estos programas colaboran en la creación de los seis impulsores de creación de valor que se han identificado y finalmente en tercer lugar como estos impulsores impactan sobre la estrategia y la organización de la empresa para dar lugar a la creación de valor de forma sostenida. A través de un Programa de Innovación Abierta, se pueden desarrollar los impulsores de valor para fortalecer la posición estratégica de la empresa y su capacidad de crear de valor. Es lo que denominamos el marco de referencia para la creación de valor en un Programa de Innovación Abierta. Se presentará la idea que los impulsores de creación de valor pueden colaborar en generar una estrategia óptima que permita alcanzar un desempeño financiero superior y lograr creación de valor de la empresa. En resumen, se ha desarrollado un modelo de relación que describe el proceso de creación de valor en la empresa a partir de los Programas de Innovación Abierta. Para ello, se han identificado los impulsores de creación de valor y se ha descripto la interacción entre los distintos elementos del modelo. ABSTRACT In a world of constant, accelerating change innovation is fuel for business. Year after year, innovation allows firms to renew and, therefore, advance their long--‐term survival. Undoubtedly, innovation is a key element for the firms’ ability to create value over time. Companies often devote considerable effort and diverse resources to identify innovation alternatives that could fit into their strategy, culture, corporate goals and ambitions. Open innovation refers to a specific approach to innovate by collaborating with other firms operating within the same business ecosystem.2 The term open innovation was pioneered by Henry Chesbrough more than a decade ago to refer to this particular mode of driving corporate innovation. Open innovation is a new paradigm that has attracted academic and business interest for over a decade. Several cases of open innovation from different countries and from different economic sectors are included and reviewed in this document. The main objective of this study is to explain and develop a relationship model between open innovation and value creation. To this end, and as secondary objectives, we have explored the elements of an Open Innovation Program, the drivers of value creation, the process of value creation and, finally, the interaction between these three elements. As a final product of the research we have developed a general theoretical framework for establishing the connection between open innovation and value creation that facilitates the explanation of the interaction between the two. From the case studies we see that open innovation can encompass all sectors of the economy, multiple geographies and varying businesses – large companies, SMEs, including (even) start--‐ups – each with a different relevance within the ecosystem in which they participate. Elements of an Open Innovation Program We begin by listing and describing below the items that can be found in an Open Innovation Program. Many of such items have been identified through the review of relevant academic literature. Furthermore, in order to achieve a better understanding of Open Innovation, we have classified those aspects into four different categories according to the features they share. § Program Organization. An organizational structure must exist with a degree of interaction between the different members involved in the innovation process. This structure must be able to meet a number of previously established objectives. § Internal Talent. Internal talent plays a key role in the implementation and success of any Open Innovation program. An open innovation culture and leadership skills are essential for adopting either radical or incremental innovation. In fact, leadership is closely linked to organizational behavior and it is essential to promote open innovation. § Infrastructure. This category groups the elements related to the technological infrastructure required to carry out the program, including production processes and daily management tools. § Instruments. Finally, we list the instruments or vehicles used in the corporate environment to implement open innovation. Several instruments are available, such as corporate incubators, licensing agreements or venture capital. There has been a growing and renewed interest in the latter, both in academia and business circles. The use of corporate venture capital to sustain the development of the open innovation strategy brings ability, credibility, and technological support to the process. The combination of elements from these four categories, interacting in a coordinated way, makes it possible to create, enhance and develop value creation drivers that may impact the company’s strategy and organization and affect its financial performance over time. The Drivers of Value Creation After identifying describing and categorizing the different elements present in an Open Innovation Program our research examines the drivers of value creation. These can be defined as elements that enhance or determine the ability to create value in the business environment. As can be seen, these drivers can act as interacting points between the elements of the program and the process of value creation. The study identifies six drivers of value creation that might be found in an Open Innovation Program. § New Products and Services. The more direct and obvious driver of value creation in any Open Innovation Program is the ability to create new products and services. This is directly related to the company’s innovation process. § Access to Adjacent Markets. The innovation process can also serve as a source of value by granting access to adjacent markets through satisfying new needs for existing customers or attracting new customers from other markets. § Availability of Technologies. The availability of technology is in itself a driver for value creation. New technologies can either be complementary and/or can leverage existing technologies within the firm. They can partly transform certain elements of the company’s strategy. § External Talent Strategy. Incorporating an Open Innovation Program offers the opportunity to interact with other organizations operating in the same ecosystem and can therefore attract external skilled resources. Talent mobility is a unique feature of open innovation. § Becoming Part of a Virtuous Circle. The actions carried out in the environment by any of its members will also have a clear impact on value creation for the other participants. Participation in a virtuous ecosystem is thus a driver for value creation in an open innovation strategy. § Inside--‐out Technology. Value creation may also evolve by allowing other firms in the ecosystem to incorporate internally developed under--‐utilized technologies into their own innovation processes. These six drivers that are present in the innovation process can influence the strategy and the organization of the company, increasing its ability to create value. The Value Creation Process Value--‐based management is the management approach that requires aligning the corporate strategy and the organizational design to create value and obtain sustained financial returns (at least, higher returns than its competitors). We describe how the drivers of value creation can enhance corporate advantages by aligning its strategy and organization. During this study, we were able to determine that real options can be used as managing tools in open innovation environments which, by definition, have high uncertainty levels. Real options provide capability for flexible and modular decision--‐making in the business environment. In particular, real options have been designed for uncertainty management and, therefore, they may be widely applied in innovation environments. We analyze potential uses of real options to supplement the various instruments identified in the Open Innovation programs. The Interaction Between Open Innovation Programs, Value Creation drivers and Value Creation Process As a result of this study, we have developed a general framework for value creation in Open Innovation Programs. This framework includes three key elements. We first described the elements that are present in Open Innovation Programs. Next, we showed how these programs can boost six drivers of value creation that have been identified. Finally, we analyzed how the drivers impact on the strategy and organization of the company in order to lead to the creation of sustainable value. Through an Open Innovation Program, value drivers can be developed to strengthen a company’s strategic position and its ability to create value. That is what we call the framework for value creation in the Open Innovation Program. Value drivers can collaborate in generating an optimal strategy that helps foster a superior financial performance and a sustained value creation process. In sum, we have developed a relationship model that describes the process of creating value in a firm with an Open Innovation Program. We have identified the drivers of value creation and described how the different elements of the model interact with each other.

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The objective of this dissertation is to analyze, design, and implement an activity module for a larger educational platform with the use of gamification techniques with the purpose to improve learning, pass rates, and feedback. The project investigates how to better incentivize student learning. A software requirement specification was delineated to establish the system guidelines and behavior. Following, a definition of the activities in the module was created. This definition encompassed a detailed description of each activity, together with elements that compose it, available customizations and the involved formulas. The activity high-level design process includes the design of the defined activities by use of the software methodology UWE (UML-based Web Engineering) for their future implementation, modeling requirements, content, navigation and presentation. The low-level design is composed of the database schema and types and the relating EER (Enhanced Entity-Relationship) diagram. After this, the implementation of the designed module began, together with testing in the later stages. We expect that by using the implemented activity module, students will become more interested in learning, as well as more engaged in the process, resulting in a continuous progress during the course.---RESUMEN---El objetivo de este trabajo es analizar, diseñar e implementar un módulo de actividades didácticas que formará parte de una plataforma educativa, haciendo uso de técnicas de gamificación con la finalidad de mejorar el aprendizaje, ratio de aprobados y retroalimentación para los alumnos. El proyecto investiga como incentivar mejor el aprendizaje estudiantil. Se trazó una especificación de requisitos de software para establecer las pautas del sistema y su comportamiento. A continuación, se definieron las actividades del módulo. Esta definición abarca una descripción detallada de cada actividad, junto a los elementos que la componen, las configuraciones disponibles y las formulas involucradas. El proceso de diseño de alto nivel incluye el diseño de las actividades definidas usando la metodología de software UWE (UML-based Web Engineering) para su futura implementación, requisitos de modelaje, contenido, navegación y presentación. El diseño de bajo nivel está compuesto por el esquema y tipos de la base de datos y el diagrama de entidad-relación correspondiente. Tras esto se realizó la implementación y pruebas de parte del sistema. Se espera que usando el módulo de actividades implementado, los estudiantes muestren un mayor interés por aprender, así como estar más involucrados en el proceso, resultando en un progreso más continuo durante el curso.

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Este proyecto está centrado en investigar la utilización de los frameworks de Java Spring,Hibernate y JSF en el desarrollo de aplicaciones web. Para poder analizar sus ventajas e inconvenientes, he realizado un caso práctico, una aplicación web llamada “Votación de Product Box”. Las primeras dos secciones de este proyecto son este resumen del proyecto y un abstract, es decir, este mismo resumen, en inglés. En la introducción (sección tercera), definiré los objetivos del proyecto, luego en la cuarta sección explicaré las características principales de cada framework, destacando sus ventajas. Una vez presentados los frameworks, paso a explicar el caso práctico, definiendo los requisitos de la aplicación Web y sus casos de uso en la quinta sección. Describo el entorno de desarrollo, las herramientas utilizadas y la razón por las cuales las he elegido en la sexta sección. Ahora explico cómo he realizado la integración de los tres frameworks en la aplicación (sección séptima) y la relaciono por medio de diagramas de clase y de entidad-relación (sección octava). Por último he realizado un tutorial de uso de la aplicación Web (sección novena), he sacado las conclusiones de haber trabajado con estos frameworks, qué ventajas e inconvenientes he encontrado y qué he aprendido a lo largo de este proyecto (sección décima),y he referenciado una bibliografía por si se quiere profundizar en el estudio de estos frameworks (sección undécima). ABSTRACT This project focuses on investigating the use of Java frameworks Spring, JSF and Hibernate on the development of Web applications. To analyze their advantages and disadvantages, I have made a practical example, a website called “Votación de Product Box”. The first two sections of this project are the project summary and abstract (the same summary in English). In the introduction (section three), I define the project goals, and then, in the fourth section, I explain the main features of each framework, emphasizing on its advantages. After introducing the frameworks, I explain the study case, I gather requirements and I make use cases in the fifth section. I describe the development environment, the tools used and the reason why I have chosen them in the sixth section. So I can explain how I made the integration of the three frameworks in the application (section seventh) and relate through class diagrams and entity relationship (section eight). Finally I make a tutorial to use the Web application (Section ninth), I draw to the conclusions of working with these frameworks, which advantages and disadvantages I have found, and I what things I learned through this project (tenth section) and I have a referenced bibliography just in case you want to find out some more about these frameworks (section eleven).

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A research has been carried out in two-lanehighways in the Madrid Region to propose an alternativemodel for the speed-flowrelationship using regular loop data. The model is different in shape and, in some cases, slopes with respect to the contents of Highway Capacity Manual (HCM). A model is proposed for a mountainous area road, something for which the HCM does not provide explicitly a solution. The problem of a mountain road with high flows to access a popular recreational area is discussed, and some solutions are proposed. Up to 7 one-way sections of two-lanehighways have been selected, aiming at covering a significant number of different characteristics, to verify the proposed method the different classes of highways on which the Manual classifies them. In order to enunciate the model and to verify the basic variables of these types of roads a high number of data have been used. The counts were collected in the same way that the Madrid Region Highway Agency performs their counts. A total of 1.471 hours have been collected, in periods of 5 minutes. The models have been verified by means of specific statistical test (R2, T-Student, Durbin-Watson, ANOVA, etc.) and with the diagnostics of the contrast of assumptions (normality, linearity, homoscedasticity and independence). The model proposed for this type of highways with base conditions, can explain the different behaviors as traffic volumes increase, and follows a polynomial multiple regression model of order 3, S shaped. As secondary results of this research, the levels of service and the capacities of this road have been measured with the 2000 HCM methodology, and the results discussed. © 2011 Published by Elsevier Ltd.

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The demand of new services, the emergence of new business models, insufficient innovation, underestimation of customer loyalty and reluctance to adopt new management are evidence of the deficiencies and the lack of research about the relations between patients and dental clinics. In this article we propose the structure of a model of Relationship Marketing (RM) in the dental clinic that integrates information from SERVQUAL, Customer Loyalty (CL) and activities of RM and combines the vision of dentist and patient. The first pilot study on dentists showed that: they recognize the value of maintaining better patients however they don't perform RM actions to retain them. They have databases of patients but not sophisticated enough as compared to RM tools. They perceive that the patients value "Assurance" and "Empathy" (two dimensions of service quality). Finally, they indicate that a loyal patient not necessarily pays more by the service. The proposed model will be validated using Fuzzy Logic simulation and the ultimate goal of this research line is contributing a new definition of CL.

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Heart valve prostheses are used to replace native heart valves which that are damaged because of congenital diseases or due to ageing. Biological prostheses made of bovine pericardium are similar to native valves and do not require any anticoagulation treatment, but are less durable than mechanical prostheses and usually fail by tearing. Researches are oriented in improving the resistance and durability of biological heart valve prostheses in order to increase their life expectancy. To understand the mechanical behaviour of bovine pericardium and relate it to its microstructure (mainly collagen fibres concentration and orientation) uniaxial tensile tests have been performed on a model material made of collagen fibres. Small Angle Light Scattering (SALS) has been also used to characterize the microstructure without damaging the material. Results with the model material allowed us to obtain the orientation of the fibres, relating the microstructure to mechanical performance

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OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).

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Abstract Idea Management Systems are web applications that implement the notion of open innovation though crowdsourcing. Typically, organizations use those kind of systems to connect to large communities in order to gather ideas for improvement of products or services. Originating from simple suggestion boxes, Idea Management Systems advanced beyond collecting ideas and aspire to be a knowledge management solution capable to select best ideas via collaborative as well as expert assessment methods. In practice, however, the contemporary systems still face a number of problems usually related to information overflow and recognizing questionable quality of submissions with reasonable time and effort allocation. This thesis focuses on idea assessment problem area and contributes a number of solutions that allow to filter, compare and evaluate ideas submitted into an Idea Management System. With respect to Idea Management System interoperability the thesis proposes theoretical model of Idea Life Cycle and formalizes it as the Gi2MO ontology which enables to go beyond the boundaries of a single system to compare and assess innovation in an organization wide or market wide context. Furthermore, based on the ontology, the thesis builds a number of solutions for improving idea assessment via: community opinion analysis (MARL), annotation of idea characteristics (Gi2MO Types) and study of idea relationships (Gi2MO Links). The main achievements of the thesis are: application of theoretical innovation models for practice of Idea Management to successfully recognize the differentiation between communities, opinion metrics and their recognition as a new tool for idea assessment, discovery of new relationship types between ideas and their impact on idea clustering. Finally, the thesis outcome is establishment of Gi2MO Project that serves as an incubator for Idea Management solutions and mature open-source software alternatives for the widely available commercial suites. From the academic point of view the project delivers resources to undertake experiments in the Idea Management Systems area and managed to become a forum that gathered a number of academic and industrial partners. Resumen Los Sistemas de Gestión de Ideas son aplicaciones Web que implementan el concepto de innovación abierta con técnicas de crowdsourcing. Típicamente, las organizaciones utilizan ese tipo de sistemas para conectar con comunidades grandes y así recoger ideas sobre cómo mejorar productos o servicios. Los Sistemas de Gestión de Ideas lian avanzado más allá de recoger simplemente ideas de buzones de sugerencias y ahora aspiran ser una solución de gestión de conocimiento capaz de seleccionar las mejores ideas por medio de técnicas colaborativas, así como métodos de evaluación llevados a cabo por expertos. Sin embargo, en la práctica, los sistemas contemporáneos todavía se enfrentan a una serie de problemas, que, por lo general, están relacionados con la sobrecarga de información y el reconocimiento de las ideas de dudosa calidad con la asignación de un tiempo y un esfuerzo razonables. Esta tesis se centra en el área de la evaluación de ideas y aporta una serie de soluciones que permiten filtrar, comparar y evaluar las ideas publicadas en un Sistema de Gestión de Ideas. Con respecto a la interoperabilidad de los Sistemas de Gestión de Ideas, la tesis propone un modelo teórico del Ciclo de Vida de la Idea y lo formaliza como la ontología Gi2MO que permite ir más allá de los límites de un sistema único para comparar y evaluar la innovación en un contexto amplio dentro de cualquier organización o mercado. Por otra parte, basado en la ontología, la tesis desarrolla una serie de soluciones para mejorar la evaluación de las ideas a través de: análisis de las opiniones de la comunidad (MARL), la anotación de las características de las ideas (Gi2MO Types) y el estudio de las relaciones de las ideas (Gi2MO Links). Los logros principales de la tesis son: la aplicación de los modelos teóricos de innovación para la práctica de Sistemas de Gestión de Ideas para reconocer las diferenciasentre comu¬nidades, métricas de opiniones de comunidad y su reconocimiento como una nueva herramienta para la evaluación de ideas, el descubrimiento de nuevos tipos de relaciones entre ideas y su impacto en la agrupación de estas. Por último, el resultado de tesis es el establecimiento de proyecto Gi2MO que sirve como incubadora de soluciones para Gestión de Ideas y herramientas de código abierto ya maduras como alternativas a otros sistemas comerciales. Desde el punto de vista académico, el proyecto ha provisto de recursos a ciertos experimentos en el área de Sistemas de Gestión de Ideas y logró convertirse en un foro que reunión para un número de socios tanto académicos como industriales.

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This paper presents two test procedures for evaluating the bond stress–slip and the slip–radial dilation relationships when the prestressing force is transmitted by releasing the steel (wire or strand) in precast prestressed elements. The bond stress–slip relationship is obtained with short length specimens, to guarantee uniform bond stress, for three depths of the wire indentation (shallow, medium and deep). An analytical model for bond stress–slip relationship is proposed and compared with the experimental results. The model is also compared with the experimental results of other researchers. Since numerical models for studying bond-splitting problems in prestressed concrete require experimental data about dilatancy angle (radial dilation), a test procedure is proposed to evaluate these parameters. The obtained values of the radial dilation are compared with the prior estimated by numerical modelling and good agreement is reached

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During the last years cities around the world have invested important quantities of money in measures for reducing congestion and car-trips. Investments which are nothing but potential solutions for the well-known urban sprawl phenomenon, also called the “development trap” that leads to further congestion and a higher proportion of our time spent in slow moving cars. Over the path of this searching for solutions, the complex relationship between urban environment and travel behaviour has been studied in a number of cases. The main question on discussion is, how to encourage multi-stop tours? Thus, the objective of this paper is to verify whether unobserved factors influence tour complexity. For this purpose, we use a data-base from a survey conducted in 2006-2007 in Madrid, a suitable case study for analyzing urban sprawl due to new urban developments and substantial changes in mobility patterns in the last years. A total of 943 individuals were interviewed from 3 selected neighbourhoods (CBD, urban and suburban). We study the effect of unobserved factors on trip frequency. This paper present the estimation of an hybrid model where the latent variable is called propensity to travel and the discrete choice model is composed by 5 alternatives of tour type. The results show that characteristics of the neighbourhoods in Madrid are important to explain trip frequency. The influence of land use variables on trip generation is clear and in particular the presence of commercial retails. Through estimation of elasticities and forecasting we determine to what extent land-use policy measures modify travel demand. Comparing aggregate elasticities with percentage variations, it can be seen that percentage variations could lead to inconsistent results. The result shows that hybrid models better explain travel behavior than traditional discrete choice models.

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To determine the contribution of polar auxin transport (PAT) to auxin accumulation and to adventitious root (AR) formation in the stem base of Petunia hybrida shoot tip cuttings, the level of indole-3-acetic acid (IAA) was monitored in non-treated cuttings and cuttings treated with the auxin transport blocker naphthylphthalamic acid (NPA) and was complemented with precise anatomical studies. The temporal course of carbohydrates, amino acids and activities of controlling enzymes was also investigated. Analysis of initial spatial IAA distribution in the cuttings revealed that approximately 40 and 10% of the total IAA pool was present in the leaves and the stem base as rooting zone, respectively. A negative correlation existed between leaf size and IAA concentration. After excision of cuttings, IAA showed an early increase in the stem base with two peaks at 2 and 24h post excision and, thereafter, a decline to low levels. This was mirrored by the expression pattern of the auxin-responsive GH3 gene. NPA treatment completely suppressed the 24-h peak of IAA and severely inhibited root formation. It also reduced activities of cell wall and vacuolar invertases in the early phase of AR formation and inhibited the rise of activities of glucose-6-phosphate dehydrogenase and phosphofructokinase during later stages. We propose a model in which spontaneous AR formation in Petunia cuttings is dependent on PAT and on the resulting 24-h peak of IAA in the rooting zone, where it induces early cellular events and also stimulates sink establishment. Subsequent root development stimulates glycolysis and the pentosephosphate pathway

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Assessing users’ benefit in a transport policy implementation has been studied by many researchers using theoretical or empirical measures. However, few of them measure users’ benefit in a different way from the consumer surplus. Therefore, this paper aims to assess a new measure of user benefits by weighting consumer surplus in order to include equity assessment for different transport policies simulated in a dynamic middle-term LUTI model adapted to the case study of Madrid. Three different transport policies, including road pricing, parking charge and public transport improvement have been simulated through the Metropolitan Activity Relocation Simulator, MARS, the LUTI calibrated model for Madrid). A social welfare function (WF) is defined using a cost benefit analysis function that includes mainly costs and benefits of users and operators of the transport system. Particularly, the part of welfare function concerning the users, (i.e. consumer surplus), is modified by a compensating weight (CW) which represents the inverse of household income level. Based on the modified social welfare function, the effects on the measure of users benefits are estimated and compared with the old WF ́s results as well. The result of the analysis shows that road pricing leads a negative effect on the users benefits specially on the low income users. Actually, the road pricing and parking charge implementation results like a regressive policy especially at long term. Public transport improvement scenario brings more positive effects on low income user benefits. The integrated (road pricing and increasing public services) policy scenario is the one which receive the most user benefits. The results of this research could be a key issue to understanding the relationship between transport systems policies and user benefits distribution in a metropolitan context.

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Office automation is one of the fields where the complexity related with technologies and working environments can be best shown. This is the starting point we have chosen to build up a theoretical model that shows us a scene quite different from the one traditionally considered. Through the development of the model, the levels of complexity associated with office automation and office environments have been identified, establishing a relationship between them. Thus, the model allows to state a general principle for sociotechnical design of office automation systems, comprising the ontological distinctions needed to properly evaluate each particular technology and its virtual contribution to office automation. From this fact comes the model's taxonomic ability to draw a global perspective of the state-of-art in office automation technologies.

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This research addressed the development of a consolidated model designed especially to cover the security and usability attributes of a software product. As a starting point, we built a new usability model on the basis of well-known quality standards and models. We then used an existing security model to analyse the relationship between these two approaches. This analysis consisted of a systematic mapping study of the relationship between security and usability as global quality factors. We identified five relationship types: inverse, direct, relative, one-way inverse, and no relationship. Most authors agree that there is an inverse relationship between security and usability. However, this is not a unanimous finding, and this study unveils a number of open questions, like application domain dependency and the need to explore lower-level relationships between attribute subcharacteristics. In order to clarify the questions raised during the research, we conducted a second systematic mapping to further analyse the finer-grained structure of these factors, such as authentication as a subset of security and user efficiency as a subset of usability. The most relevant finding is that efficiency does not depend on the security level during the authentication process. There are other subfactors that require analysis. Accordingly, this research is the first part of a larger project to develop a full-blown consolidated model for security and usability.

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This paper analyses the relationship between productive efficiency and online-social-networks (OSN) in Spanish telecommunications firms. A data-envelopment-analysis (DEA) is used and several indicators of business ?social Media? activities are incorporated. A super-efficiency analysis and bootstrapping techniques are performed to increase the model?s robustness and accuracy. Then, a logistic regression model is applied to characterise factors and drivers of good performance in OSN. Results reveal the company?s ability to absorb and utilise OSNs as a key factor in improving the productive efficiency. This paper presents a model for assessing the strategic performance of the presence and activity in OSN.