73 resultados para “Hybrid” implementation model
em Universidad Politécnica de Madrid
Resumo:
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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This work presents a behavioral-analytical hybrid loss model for a buck converter. The model has been designed for a wide operating frequency range up to 4MHz and a low power range (below 20W). It is focused on the switching losses obtained in the power MOSFETs. Main advantages of the model are the fast calculation time (below 8.5 seconds) and a good accuracy, which makes this model suitable for the optimization process of the losses in the design of a converter. It has been validated by simulation and experimentally with one GaN power transistor and three Si MOSFETs. Results show good agreement between measurements and the model
Resumo:
This work presents a behavioral-analytical hybrid loss model for a buck converter. The model has been designed for a wide operating frequency range up to 4MHz and a low power range (below 20W). It is focused on the switching losses obtained in the power MOSFETs. Main advantages of the model are the fast calculation time and a good accuracy. It has been validated by simulation and experimentally with one Ga, power transistor and two Si MOSFETs. Results show good agreement between measurements and the model.
Resumo:
There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.
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La Responsabilidad Social Corporativa (RSC) sigue constituyendo en la actualidad un área de estudio de elevado interés tanto para la comunidad académica como para los negocios en general. A pesar del gran número de investigaciones realizadas en las pasadas décadas sobre los distintos aspectos que la caracterizan, y la definición generalizada de políticas relacionadas en las compañías más importantes, existen todavía algunos asuntos clave sobre los que se plantean interrogantes fundamentales. La complejidad asociada al constructo RSC y su carácter intrínsecamente dinámico explican en parte esta afirmación. En su aplicación práctica, las dudas sobre la RSC se enfocan hoy en día hacia su implantación con carácter permanente en el día a día de las organizaciones, la relevancia estratégica de las principales iniciativas, o la posibilidad de obtención de beneficios a medio y largo plazo. Se observa de esta forma la traslación de los debates principales hacia las consecuencias más estratégicas de dichas políticas, influenciados por prestigiosos estudios académicos en los que se caracteriza la denominada RSC Estratégica (RSCE), y por las principales organizaciones de certificación de memorias anuales de RSC y sostenibilidad. En este contexto se sitúa el objeto principal de esta investigación, consistente en el diseño de un modelo de implantación de RSCE que permita no sólo identificar los factores más importantes a tener en consideración para su éxito, sino para caracterizar las potenciales formas de creación de valor que pueden surgir de la aplicación del mismo. Se argumenta la elección del tema por considerarse que los asuntos asociados a la RSC no están lo suficientemente explorados desde la visión estratégica más actual, y por constituir la creación de valor el objetivo más crítico dentro de los procesos directivos de planificación estratégica. De esta forma, se utilizan dos metodologías para destacar qué factores son esenciales en la implantación de la RSCE, con qué fines las compañías aplican esas políticas, y qué resultados obtienen como consecuencia: análisis comparativo de casos de estudio y análisis estadístico cuantitativo. Los casos de estudio analizan en profundidad políticas globales de RSCE bajo diferentes puntos de vista, para derivar conclusiones sobre los factores que facilitan u obstaculizan su implantación permanente en las organizaciones. Su desarrollo se estructura en torno a un marco conceptual de referencia obtenido a través de la revisión bibliográfica específica, y se complementa con la información primaria y secundaria de investigación. Por su parte, el análisis cuantitativo se desarrolla mediante tres técnicas exploratorias: estadística descriptiva, regresión múltiple y análisis de componentes principales. Su aplicación combinada va a posibilitar el contraste de aspectos destacados en los análisis de casos, así como la configuración final del modelo de implantación, y la expresión numérica de la creación de valor a través de la RSCE en función de las dimensiones estratégicas consideradas. En consecuencia, los resultados de la tesis se estructuran alrededor de tres preguntas de investigación: ¿cómo se están produciendo y qué caracterización presentan los beneficios que resultan como consecuencia de la implantación de la RSCE en los procesos de planificación estratégica de las compañías?, ¿qué factores esenciales y característicos de la RSCE pueden resultar críticos en los procesos de implantación y futuro desarrollo?, y ¿qué importancia puede tener en el medio y largo plazo el poder de decisión de compra de los consumidores y usuarios finales en la implantación y desarrollo de políticas de RSCE? ABSTRACT Corporate Social Responsibility (CSR) remains a study area of high interest today to both the academic community and businesses in general. Despite the large number of investigations of various aspects of CSR in past decades, and its generalized consideration by the world’s most important companies, there are still some key issues and fundamental questions to resolve. The complexity associated with the CSR construct and its inherently dynamic character, partly explains this statement. In its practical application, doubts about CSR arise today about its permanent implementation in normal business activities, the strategic relevance of related policies, and the possibility of making profits in the medium and long term. It is observed in this way the translation of the main debates towards the more strategic consequences of these policies, influenced by prestigious academic studies that characterize the so-called Strategic CSR (SCSR), and by leading certification agencies of CSR and sustainability reports. In this context, the main purpose of this investigation is to design a model of SCSR for implementation that allows one to not only identify the most important factors to consider for SCSR success, but also to characterize potential forms of value creation that can arise from its application. The selection of this research approach is justified because it is believed that important issues that are associated with CSR have not been sufficiently explored from the aspect of the strategic vision in the current context, and because value creation constitutes the most critical objective within the strategic planning steering processes. Thus, two methods are used to highlight which factors are essential in SCSR implementation processes, the end to which companies apply these policies, and the kind of results that they expect. These methods are: comparative analysis of case studies and quantitative statistical analysis. The case studies discuss in depth SCSR global policies under different perspectives to draw conclusions about the factors that facilitate or hinder permanent implantation in organizations. Their development is structured around a conceptual framework that is obtained by review of specific literature, and is complemented by primary and secondary research information. On the other hand, quantitative analysis is developed by means of three exploratory techniques: descriptive statistics, multiple regression and principal component analysis. Their combined application facilitates a contrast of highlighted aspects in analyzing cases, the final configuration of the implementation model, and the numerical expression of value creation by SCSR as a consequence of the strategic dimensions considered by companies. Finally, the results of the thesis are structured around three research questions: what are the benefits that result from the implementation of SCSR policies in companies’ strategic planning processes?, which essential SCSR factors are potentially critical in the implementation and future development of companies’ processes?, and how decisive in the medium and long term will be the purchase decision power of consumers to the success of SCSR policies?
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This paper discusses a novel hybrid approach for text categorization that combines a machine learning algorithm, which provides a base model trained with a labeled corpus, with a rule-based expert system, which is used to improve the results provided by the previous classifier, by filtering false positives and dealing with false negatives. The main advantage is that the system can be easily fine-tuned by adding specific rules for those noisy or conflicting categories that have not been successfully trained. We also describe an implementation based on k-Nearest Neighbor and a simple rule language to express lists of positive, negative and relevant (multiword) terms appearing in the input text. The system is evaluated in several scenarios, including the popular Reuters-21578 news corpus for comparison to other approaches, and categorization using IPTC metadata, EUROVOC thesaurus and others. Results show that this approach achieves a precision that is comparable to top ranked methods, with the added value that it does not require a demanding human expert workload to train
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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
Resumo:
The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs.
Transformation�based implementation and optimization of programs exploiting the basic Andorra model.
Resumo:
The characteristics of CC and CLP systems are in principle very dierent However a recent trend towards convergence in the implementation techniques for these systems can be observed While CLP and Prolog systems have been incorporating capabilities to deal with userdened suspension and coroutining CC compilers have been trying to coalesce negrained tasks into coarsergrained sequential threads This convergence of techniques opens up the possibility of having a general purpose kernel language and abstract machine to serve as a compilation target for a variety of userlevel languages We propose a transformation technique directed towards such an objective In particular we report on techniques to support the Andorra computational model essentially emulating the AndorraI system via program transformation into a sequential language with delay primitives The system is automatic comprising an optional program analyzer and a basic transformer to the kernel language It turns out that a simple parallel CLP or Prolog system with dynamic scheduling is sucient as a kernel language for this purpose The preliminary results are quite encouraging performance of the resulting system is comparable to the current AndorraI implementation.
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Este Proyecto de Fin de Carrera presenta un prototipo de aplicación móvil híbrida multi-plataforma para Android y iOS. Las aplicaciones móviles híbridas son una combinación de aplicaciones web móviles y aplicaciones móviles nativas. Se desarrollan parcialmente con tecnologías web y pueden acceder a la capa nativa y sensores del teléfono. Para el usuario se presentan como aplicaciones nativas, ya que se pueden descargar de las tiendas de aplicaciones y son instaladas en el dispositivo. El prototipo consiste en la migración del módulo de noticias financieras de las aplicaciones actuales para móviles de una compañía bancaria reimplementándolo como aplicación híbrida utilizando uno de los entornos de desarrollo disponibles en el mercado para este propósito. El desarrollo de aplicaciones híbridas puede ahorrar tiempo y dinero cuando se pretende alcanzar más de una plataforma móvil. El objetivo es la evaluación de las ventajas e inconvenientes que ofrece el desarrollo de aplicaciones híbridas en términos de reducción de costes, tiempo de desarrollo y resultado final de la aplicación. El proyecto consta de varias fases. Durante la primera fase se realiza un estudio sobre las aplicaciones híbridas que podemos encontrar hoy en día en el mercado utilizando los ejemplos de linkedIn, Facebook y Financial times. Se hace hincapié en las tecnologías utilizadas, uso de la red móvil y problemas encontrados. Posteriormente se realiza una comparación de distintos entornos de desarrollo multi-plataforma para aplicaciones híbridas en términos de la estrategia utilizada, plataformas soportadas, lenguajes de programación, acceso a capacidades nativas de los dispositivos y licencias de uso. Esta primera fase da como resultado la elección del entorno de desarrollo más adecuado a las exigencias del proyecto, que es PhoneGap, y continua con un análisis más detallado de dicho entorno en cuanto a su arquitectura, características y componentes. La siguiente fase comienza con un estudio de las aplicaciones actuales de la compañía para extraer el código fuente necesario y adaptarlo a la arquitectura que tendrá la aplicación. Para la realización del prototipo se hace uso de la característica que ofrece PhoneGap para acceder a la capa nativa del dispositivo, esto es, el uso de plugins. Se diseña y desarrolla un plugin que permite acceder a la capa nativa para cada plataforma. Una vez desarrollado el prototipo para la plataforma Android, se migra y adapta para la plataforma iOS. Por último se hace una evaluación de los prototipos en cuanto a su facilidad y tiempo de desarrollo, rendimiento, funcionalidad y apariencia de la interfaz de usuario. ABSTRACT. This bachelor's thesis presents a prototype of a hybrid cross-platform mobile application for Android and iOS. Hybrid mobile applications are a combination of mobile web and mobile native applications. They are built partially with web technologies and they can also access native features and sensors of the device. For a user, they look like native applications as they are downloaded from the application stores and installed on the device. This prototype consists of the migration of the financial news module of current mobile applications from a financial bank reimplementing them as a hybrid application using one of the frameworks available in the market for that purpose. Development of applications on a hybrid way can help reducing costs and effort when targeting more than one platform. The target of the project is the evaluation of the advantages and disadvantages that hybrid development can offer in terms of reducing costs and efforts and the final result of the application. The project starts with an analysis of successfully released hybrid applications using the examples of linkedIn, Facebook and Financial Times, emphasizing the different used technologies, the transmitted network data and the encountered problems during the development. This analysis is followed by a comparison of most popular hybrid crossplatform development frameworks in terms of the different approaches, supported platforms, programming languages, access to native features and license. This first stage has the outcome of finding the development framework that best fits to the requirements of the project, that is PhoneGap, and continues with a deeper analysis of its architecture, features and components. Next stage analyzes current company's applications to extract the needed source code and adapt it to the architecture of the prototype. For the realization of the application, the feature that PhoneGap offers to access the native layer of the device is used. This feature is called plugin. A custom plugin is designed and developed to access the native layer of each targeted platform. Once the prototype is finished for Android, it is migrated and adapted to the iOS platform. As a final conclusion the prototypes are evaluated in terms of ease and time of development, performance, functionality and look and feel.
Resumo:
Accessibility is an essential concept widely used to evaluate the impact of land-use and transport strategies in transport and urban planning. Accessibility is typically evaluated by using a transport model or a land-use model independently or successively without a feedback loop, thus neglecting the interaction effects between the two systems and the induced competition effects among opportunities due to accessibility improvements. More than a mere methodological curiosity, failure to account for land- use/transport interactions and the competition effect may result in large underestimation of the policy effects. With the recent development of land-use and transport interaction (LUTI) models, there is a growing interest in using these models to adequately measure accessibility and evaluate its impact. The current study joins this research stream by embedding an accessibility measure in a LUTI model with two main aims. The first aim is to account for adaptive accessibility, namely the adjustment of the potential accessibility due to the effect of competition among opportunities (e.g., workplaces) as a result of improved accessibility. LUTI models are particularly suitable for assessing adaptive accessibility because the competition factor is a function of the number of jobs, which is related to land-use attractiveness and the number of workers which is related, among other factors, to the transport demand. The second aim is to identify the optimal implementation scenario of policy measures on the basis of the potential and adaptive accessibility and analyse the results in terms of social welfare and accessibility. The metropolitan area of Madrid is used as a case-study and two transport policy instruments, namely a cordon toll and bus frequency increase, have been chosen for the simulation study in order to present the usefulness of the approach to urban planners and policy makers. The MARS model (Metropolitan Activity Relocation Simulator) calibrated for Madrid was employed as the analysis tool. The impact of accessibility is embedded in the model through a social welfare function that includes not only costs and benefits to both road users and transport operators, but also costs and benefits for the government and society in general (external costs). An optimisation procedure is performed by the MARS model for maximizing the value of objective function in order to find the best (optimal) policy imp lementations intensity (i.e., price, frequency). Last, the two policy strategies are evaluated in terms of their accessibility. Results show that the accessibility with competition factor influences the optimal policy implementation level and also generates different results in terms of social welfare. In addition, mapping the difference between the potential and the adaptive accessibility indicators shows that the main changes occur in areas where there is a strong competition among land-use opportunities.
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Data from an attitudinal survey and stated preference ranking experiment conducted in two urban European interchanges (i.e. City-HUBs) in Madrid (Spain) and Thessaloniki (Greece) show that the importance that City-HUBs users attach to the intermodal infrastructure varies strongly as a function of their perceptions of time spent in the interchange (i.e.intermodal transfer and waiting time). A principal components analysis allocates respondents (i.e. city-HUB users) to two classes with substantially different perceptions of time saving when they make a transfer and of time using during their waiting time.
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In order to achieve to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. In the transport modelling literature there has been an increasing awareness that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users? social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced, but links between international and Spanish perspectives are rarely deal. In this paper, factorial and path analyses through a Multiple-Indicator Multiple-Cause (MIMIC) model are used to understand and describe the relationship between the different psychological and environmental constructs with social influence and socioeconomic variables. The MIMIC model generates Latent Variables (LVs) to be incorporated sequentially into Discrete Choice Models (DCM) where the levels of service and cost attributes of travel modes are also included directly to measure the effect of the transport policies that have been introduced in Madrid during the last three years in the context of the economic crisis. The data used for this paper are collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) of Madrid.
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In Chile, during the last three decades there has been a strong decentralization process whose main objective has been to improve the management of schools through the transfer of responsibilities and resources of education and thus improve the outcome of learning, reducing equity gaps between schools and territories. This is how, there has been an evolution of school principals¿ professional profile from an administrative to a management approach, in which principals have become project managers of educational projects. From a competence model for school leaders, based on IPMA guidelines, the present article presents an analysis of best practices for school management, allowing to generate a link between competencies and school management, from the perspective of project management. Results showed that the different competence elements, have relative weights according to the different practice fields, and that this analysis can be considered as a strategic element in educational project planning and development.
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Experimental characterization and implementation of an integrated autoregressive model to predict the thermal performance of vegetal façades