900 resultados para constraint based design
Resumo:
The work done is about the seismic analysis of an existing reinforced concrete structure that is equipped with a special bracing device. The main objective of the research is to provide a simple procedure that can be followed in order to design the lateral bracing system in such a way that the actual behavior of the structure matches the desired pre-defined objective curve. a great attention is devoted to the internal actions in the structural elements produced by the braces. The device used is called: Crescent shaped braces. This device is a special type of bracing because it has a banana-like geometry that allows the designer to have more control over the stiffness of the structure, especially under cyclic behavior, Unlike the conventional bracing that resists only through its axial stiffness. This device has been installed in a hospital in Italy. However, it has not been exposed to any ground motion so far. Different analysis methods, such as static pushover and dynamic time-history have been used in the analysis of the structure.
Resumo:
Using latent class analysis (LCA), a previous study on patients attending primary care identified four courses of low back pain (LBP) over the subsequent 6 months. To date, no studies have used longitudinal pain recordings to examine the "natural" course of recurrent and chronic LBP in a population-based sample of individuals. This study examines the course of LBP in the general population and elaborates on the stability and criterion-related validity of the clusters derived. A random sample of 400 individuals reporting LBP in a population-based study was asked to complete a comprehensive questionnaire at the start and end of the year's survey, and 52 weekly pain diaries in between. The latter were analyzed using LCA. 305 individuals returned more than 50% of the diaries. Four clusters were identified (severe persistent, moderate persistent, mild persistent, and fluctuating). The clusters differed significantly with regards to pain and disability. Assessment of cluster stability showed that a considerable proportion of patients in the "fluctuating" group changed their classification over time. Three of the four clusters describing the typical course of pain matched the clusters described previously for patients in primary care. Due to the population-based design, this study achieves, for the first time, a close insight into the "natural" course of chronic and recurrent low back pain, including individuals that did not necessarily visit the general practitioner. The findings will help to understand better the nature of this pain in the general population.
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This report presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. Knock Signal Simulator (KSS) was developed as the plant model for the engine. The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies. The SKD method is implemented in Knock Detection Module (KDM) which processes the knock intensities generated by KSS with a stochastic distribution estimation algorithm and outputs estimates of high and low knock intensity levels which characterize knock and reference level respectively. These estimates are then used to determine a knock factor which provides quantitative measure of knock level and can be used as a feedback signal to control engine knock. The knock factor is analyzed and compared with a traditional knock detection method to detect engine knock under various engine operating conditions. To verify the effectiveness of the SKD method, a knock controller was also developed and tested in a model-in-loop (MIL) system. The objective of the knock controller is to allow the engine to operate as close as possible to its border-line spark-timing without significant engine knock. The controller parameters were tuned to minimize the cycle-to-cycle variation in spark timing and the settling time of the controller in responding to step increase in spark advance resulting in the onset of engine knock. The simulation results showed that the combined system can be used adequately to model engine knock and evaluated knock control strategies for a wide range of engine operating conditions.
Resumo:
Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.
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Ureides are compounds, which essentially incorporate urea as a substructural component either in open or cyclic form. Ureido derivatives are one of the oldest classes of bioactives, widely used as antiinfective agents. Several of these compounds, including aminoquinuride, aminocarbalide, imidurea, cloflucarban, nitrofurazone, urosulfan, viomycin are used in clinical situations. One of the ureides, the triclocarban is compulsorily used as antibacterial agent in cleansing and disinfecting solutions in hospital, household, cosmetics, toys, textile and plastics. It disables the activity of ENR, an enzyme vital for building the cell wall of the bacteria and fungus. Besides, the ureido-penicillins in clinical use there have been several ureido-lactam derivatives which have been reported to exhibit significant antibacterial activity. A urea containing dipeptide TAN-1057A isolated from Flexibacter spp. has potent bioactivity against MRSA. The metal complexes of sulphonyl ureido derivatives are effective antifungal agents by inhibiting the activity of phosphomannose isomerase, a key enzyme in the biosynthesis of yeast cell walls. There have been number of ureides including the cyclic ureas which are potent HIV protease inhibitors and display significant anti-HIV activity. The urea derivative, merimepodip that has been derived using structure based design, is potent inhibitor of IMPDH and is active against Hepatitis-C infection. This review will primarily focus on the significant work reported for this class of compounds including design, synthesis and biological activity.
Resumo:
The past few years, multimodal interaction has been gaining importance in virtual environments. Although multimodality renders interacting with an environment more natural and intuitive, the development cycle of such an application is often long and expensive. In our overall field of research, we investigate how modelbased design can facilitate the development process by designing environments through the use of highlevel diagrams. In this scope, we present ‘NiMMiT’, a graphical notation for expressing and evaluating multimodal user interaction; we elaborate on the NiMMiT primitives and demonstrate its use by means of a comprehensive example.
Resumo:
Hoy en día, con la evolución continua y rápida de las tecnologías de la información y los dispositivos de computación, se recogen y almacenan continuamente grandes volúmenes de datos en distintos dominios y a través de diversas aplicaciones del mundo real. La extracción de conocimiento útil de una cantidad tan enorme de datos no se puede realizar habitualmente de forma manual, y requiere el uso de técnicas adecuadas de aprendizaje automático y de minería de datos. La clasificación es una de las técnicas más importantes que ha sido aplicada con éxito a varias áreas. En general, la clasificación se compone de dos pasos principales: en primer lugar, aprender un modelo de clasificación o clasificador a partir de un conjunto de datos de entrenamiento, y en segundo lugar, clasificar las nuevas instancias de datos utilizando el clasificador aprendido. La clasificación es supervisada cuando todas las etiquetas están presentes en los datos de entrenamiento (es decir, datos completamente etiquetados), semi-supervisada cuando sólo algunas etiquetas son conocidas (es decir, datos parcialmente etiquetados), y no supervisada cuando todas las etiquetas están ausentes en los datos de entrenamiento (es decir, datos no etiquetados). Además, aparte de esta taxonomía, el problema de clasificación se puede categorizar en unidimensional o multidimensional en función del número de variables clase, una o más, respectivamente; o también puede ser categorizado en estacionario o cambiante con el tiempo en función de las características de los datos y de la tasa de cambio subyacente. A lo largo de esta tesis, tratamos el problema de clasificación desde tres perspectivas diferentes, a saber, clasificación supervisada multidimensional estacionaria, clasificación semisupervisada unidimensional cambiante con el tiempo, y clasificación supervisada multidimensional cambiante con el tiempo. Para llevar a cabo esta tarea, hemos usado básicamente los clasificadores Bayesianos como modelos. La primera contribución, dirigiéndose al problema de clasificación supervisada multidimensional estacionaria, se compone de dos nuevos métodos de aprendizaje de clasificadores Bayesianos multidimensionales a partir de datos estacionarios. Los métodos se proponen desde dos puntos de vista diferentes. El primer método, denominado CB-MBC, se basa en una estrategia de envoltura de selección de variables que es voraz y hacia delante, mientras que el segundo, denominado MB-MBC, es una estrategia de filtrado de variables con una aproximación basada en restricciones y en el manto de Markov. Ambos métodos han sido aplicados a dos problemas reales importantes, a saber, la predicción de los inhibidores de la transcriptasa inversa y de la proteasa para el problema de infección por el virus de la inmunodeficiencia humana tipo 1 (HIV-1), y la predicción del European Quality of Life-5 Dimensions (EQ-5D) a partir de los cuestionarios de la enfermedad de Parkinson con 39 ítems (PDQ-39). El estudio experimental incluye comparaciones de CB-MBC y MB-MBC con los métodos del estado del arte de la clasificación multidimensional, así como con métodos comúnmente utilizados para resolver el problema de predicción de la enfermedad de Parkinson, a saber, la regresión logística multinomial, mínimos cuadrados ordinarios, y mínimas desviaciones absolutas censuradas. En ambas aplicaciones, los resultados han sido prometedores con respecto a la precisión de la clasificación, así como en relación al análisis de las estructuras gráficas que identifican interacciones conocidas y novedosas entre las variables. La segunda contribución, referida al problema de clasificación semi-supervisada unidimensional cambiante con el tiempo, consiste en un método nuevo (CPL-DS) para clasificar flujos de datos parcialmente etiquetados. Los flujos de datos difieren de los conjuntos de datos estacionarios en su proceso de generación muy rápido y en su aspecto de cambio de concepto. Es decir, los conceptos aprendidos y/o la distribución subyacente están probablemente cambiando y evolucionando en el tiempo, lo que hace que el modelo de clasificación actual sea obsoleto y deba ser actualizado. CPL-DS utiliza la divergencia de Kullback-Leibler y el método de bootstrapping para cuantificar y detectar tres tipos posibles de cambio: en las predictoras, en la a posteriori de la clase o en ambas. Después, si se detecta cualquier cambio, un nuevo modelo de clasificación se aprende usando el algoritmo EM; si no, el modelo de clasificación actual se mantiene sin modificaciones. CPL-DS es general, ya que puede ser aplicado a varios modelos de clasificación. Usando dos modelos diferentes, el clasificador naive Bayes y la regresión logística, CPL-DS se ha probado con flujos de datos sintéticos y también se ha aplicado al problema real de la detección de código malware, en el cual los nuevos ficheros recibidos deben ser continuamente clasificados en malware o goodware. Los resultados experimentales muestran que nuestro método es efectivo para la detección de diferentes tipos de cambio a partir de los flujos de datos parcialmente etiquetados y también tiene una buena precisión de la clasificación. Finalmente, la tercera contribución, sobre el problema de clasificación supervisada multidimensional cambiante con el tiempo, consiste en dos métodos adaptativos, a saber, Locally Adpative-MB-MBC (LA-MB-MBC) y Globally Adpative-MB-MBC (GA-MB-MBC). Ambos métodos monitorizan el cambio de concepto a lo largo del tiempo utilizando la log-verosimilitud media como métrica y el test de Page-Hinkley. Luego, si se detecta un cambio de concepto, LA-MB-MBC adapta el actual clasificador Bayesiano multidimensional localmente alrededor de cada nodo cambiado, mientras que GA-MB-MBC aprende un nuevo clasificador Bayesiano multidimensional. El estudio experimental realizado usando flujos de datos sintéticos multidimensionales indica los méritos de los métodos adaptativos propuestos. ABSTRACT Nowadays, with the ongoing and rapid evolution of information technology and computing devices, large volumes of data are continuously collected and stored in different domains and through various real-world applications. Extracting useful knowledge from such a huge amount of data usually cannot be performed manually, and requires the use of adequate machine learning and data mining techniques. Classification is one of the most important techniques that has been successfully applied to several areas. Roughly speaking, classification consists of two main steps: first, learn a classification model or classifier from an available training data, and secondly, classify the new incoming unseen data instances using the learned classifier. Classification is supervised when the whole class values are present in the training data (i.e., fully labeled data), semi-supervised when only some class values are known (i.e., partially labeled data), and unsupervised when the whole class values are missing in the training data (i.e., unlabeled data). In addition, besides this taxonomy, the classification problem can be categorized into uni-dimensional or multi-dimensional depending on the number of class variables, one or more, respectively; or can be also categorized into stationary or streaming depending on the characteristics of the data and the rate of change underlying it. Through this thesis, we deal with the classification problem under three different settings, namely, supervised multi-dimensional stationary classification, semi-supervised unidimensional streaming classification, and supervised multi-dimensional streaming classification. To accomplish this task, we basically used Bayesian network classifiers as models. The first contribution, addressing the supervised multi-dimensional stationary classification problem, consists of two new methods for learning multi-dimensional Bayesian network classifiers from stationary data. They are proposed from two different points of view. The first method, named CB-MBC, is based on a wrapper greedy forward selection approach, while the second one, named MB-MBC, is a filter constraint-based approach based on Markov blankets. Both methods are applied to two important real-world problems, namely, the prediction of the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors, and the prediction of the European Quality of Life-5 Dimensions (EQ-5D) from 39-item Parkinson’s Disease Questionnaire (PDQ-39). The experimental study includes comparisons of CB-MBC and MB-MBC against state-of-the-art multi-dimensional classification methods, as well as against commonly used methods for solving the Parkinson’s disease prediction problem, namely, multinomial logistic regression, ordinary least squares, and censored least absolute deviations. For both considered case studies, results are promising in terms of classification accuracy as well as regarding the analysis of the learned MBC graphical structures identifying known and novel interactions among variables. The second contribution, addressing the semi-supervised uni-dimensional streaming classification problem, consists of a novel method (CPL-DS) for classifying partially labeled data streams. Data streams differ from the stationary data sets by their highly rapid generation process and their concept-drifting aspect. That is, the learned concepts and/or the underlying distribution are likely changing and evolving over time, which makes the current classification model out-of-date requiring to be updated. CPL-DS uses the Kullback-Leibler divergence and bootstrapping method to quantify and detect three possible kinds of drift: feature, conditional or dual. Then, if any occurs, a new classification model is learned using the expectation-maximization algorithm; otherwise, the current classification model is kept unchanged. CPL-DS is general as it can be applied to several classification models. Using two different models, namely, naive Bayes classifier and logistic regression, CPL-DS is tested with synthetic data streams and applied to the real-world problem of malware detection, where the new received files should be continuously classified into malware or goodware. Experimental results show that our approach is effective for detecting different kinds of drift from partially labeled data streams, as well as having a good classification performance. Finally, the third contribution, addressing the supervised multi-dimensional streaming classification problem, consists of two adaptive methods, namely, Locally Adaptive-MB-MBC (LA-MB-MBC) and Globally Adaptive-MB-MBC (GA-MB-MBC). Both methods monitor the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a drift is detected, LA-MB-MBC adapts the current multi-dimensional Bayesian network classifier locally around each changed node, whereas GA-MB-MBC learns a new multi-dimensional Bayesian network classifier from scratch. Experimental study carried out using synthetic multi-dimensional data streams shows the merits of both proposed adaptive methods.
Resumo:
Las pruebas de software (Testing) son en la actualidad la técnica más utilizada para la validación y la evaluación de la calidad de un programa. El testing está integrado en todas las metodologías prácticas de desarrollo de software y juega un papel crucial en el éxito de cualquier proyecto de software. Desde las unidades de código más pequeñas a los componentes más complejos, su integración en un sistema de software y su despliegue a producción, todas las piezas de un producto de software deben ser probadas a fondo antes de que el producto de software pueda ser liberado a un entorno de producción. La mayor limitación del testing de software es que continúa siendo un conjunto de tareas manuales, representando una buena parte del coste total de desarrollo. En este escenario, la automatización resulta fundamental para aliviar estos altos costes. La generación automática de casos de pruebas (TCG, del inglés test case generation) es el proceso de generar automáticamente casos de prueba que logren un alto recubrimiento del programa. Entre la gran variedad de enfoques hacia la TCG, esta tesis se centra en un enfoque estructural de caja blanca, y más concretamente en una de las técnicas más utilizadas actualmente, la ejecución simbólica. En ejecución simbólica, el programa bajo pruebas es ejecutado con expresiones simbólicas como argumentos de entrada en lugar de valores concretos. Esta tesis se basa en un marco general para la generación automática de casos de prueba dirigido a programas imperativos orientados a objetos (Java, por ejemplo) y basado en programación lógica con restricciones (CLP, del inglés constraint logic programming). En este marco general, el programa imperativo bajo pruebas es primeramente traducido a un programa CLP equivalente, y luego dicho programa CLP es ejecutado simbólicamente utilizando los mecanismos de evaluación estándar de CLP, extendidos con operaciones especiales para el tratamiento de estructuras de datos dinámicas. Mejorar la escalabilidad y la eficiencia de la ejecución simbólica constituye un reto muy importante. Es bien sabido que la ejecución simbólica resulta impracticable debido al gran número de caminos de ejecución que deben ser explorados y a tamaño de las restricciones que se deben manipular. Además, la generación de casos de prueba mediante ejecución simbólica tiende a producir un número innecesariamente grande de casos de prueba cuando es aplicada a programas de tamaño medio o grande. Las contribuciones de esta tesis pueden ser resumidas como sigue. (1) Se desarrolla un enfoque composicional basado en CLP para la generación de casos de prueba, el cual busca aliviar el problema de la explosión de caminos interprocedimiento analizando de forma separada cada componente (p.ej. método) del programa bajo pruebas, almacenando los resultados y reutilizándolos incrementalmente hasta obtener resultados para el programa completo. También se ha desarrollado un enfoque composicional basado en especialización de programas (evaluación parcial) para la herramienta de ejecución simbólica Symbolic PathFinder (SPF). (2) Se propone una metodología para usar información del consumo de recursos del programa bajo pruebas para guiar la ejecución simbólica hacia aquellas partes del programa que satisfacen una determinada política de recursos, evitando la exploración de aquellas partes del programa que violan dicha política. (3) Se propone una metodología genérica para guiar la ejecución simbólica hacia las partes más interesantes del programa, la cual utiliza abstracciones como generadores de trazas para guiar la ejecución de acuerdo a criterios de selección estructurales. (4) Se propone un nuevo resolutor de restricciones, el cual maneja eficientemente restricciones sobre el uso de la memoria dinámica global (heap) durante ejecución simbólica, el cual mejora considerablemente el rendimiento de la técnica estándar utilizada para este propósito, la \lazy initialization". (5) Todas las técnicas propuestas han sido implementadas en el sistema PET (el enfoque composicional ha sido también implementado en la herramienta SPF). Mediante evaluación experimental se ha confirmado que todas ellas mejoran considerablemente la escalabilidad y eficiencia de la ejecución simbólica y la generación de casos de prueba. ABSTRACT Testing is nowadays the most used technique to validate software and assess its quality. It is integrated into all practical software development methodologies and plays a crucial role towards the success of any software project. From the smallest units of code to the most complex components and their integration into a software system and later deployment; all pieces of a software product must be tested thoroughly before a software product can be released. The main limitation of software testing is that it remains a mostly manual task, representing a large fraction of the total development cost. In this scenario, test automation is paramount to alleviate such high costs. Test case generation (TCG) is the process of automatically generating test inputs that achieve high coverage of the system under test. Among a wide variety of approaches to TCG, this thesis focuses on structural (white-box) TCG, where one of the most successful enabling techniques is symbolic execution. In symbolic execution, the program under test is executed with its input arguments being symbolic expressions rather than concrete values. This thesis relies on a previously developed constraint-based TCG framework for imperative object-oriented programs (e.g., Java), in which the imperative program under test is first translated into an equivalent constraint logic program, and then such translated program is symbolically executed by relying on standard evaluation mechanisms of Constraint Logic Programming (CLP), extended with special treatment for dynamically allocated data structures. Improving the scalability and efficiency of symbolic execution constitutes a major challenge. It is well known that symbolic execution quickly becomes impractical due to the large number of paths that must be explored and the size of the constraints that must be handled. Moreover, symbolic execution-based TCG tends to produce an unnecessarily large number of test cases when applied to medium or large programs. The contributions of this dissertation can be summarized as follows. (1) A compositional approach to CLP-based TCG is developed which overcomes the inter-procedural path explosion by separately analyzing each component (method) in a program under test, stowing the results as method summaries and incrementally reusing them to obtain whole-program results. A similar compositional strategy that relies on program specialization is also developed for the state-of-the-art symbolic execution tool Symbolic PathFinder (SPF). (2) Resource-driven TCG is proposed as a methodology to use resource consumption information to drive symbolic execution towards those parts of the program under test that comply with a user-provided resource policy, avoiding the exploration of those parts of the program that violate such policy. (3) A generic methodology to guide symbolic execution towards the most interesting parts of a program is proposed, which uses abstractions as oracles to steer symbolic execution through those parts of the program under test that interest the programmer/tester most. (4) A new heap-constraint solver is proposed, which efficiently handles heap-related constraints and aliasing of references during symbolic execution and greatly outperforms the state-of-the-art standard technique known as lazy initialization. (5) All techniques above have been implemented in the PET system (and some of them in the SPF tool). Experimental evaluation has confirmed that they considerably help towards a more scalable and efficient symbolic execution and TCG.
Resumo:
La acción del dibujar intenta presentarse en este texto como lenguaje mudo, práctica común general y práctica común en el campo arquitectónico en concreto; y también como acción, apertura, exploración (no representación) en el estado naciente del proyecto. La tesis se presenta como un estudio basado en la experiencia directa, la observación in situ (Practice Based Design Doctórate) intentando reflexionar no desde sus productos alcanzados al dibujar, sino desde la propia acción, enfatizando la dinamicidad del cuerpo como productor de gestos dinámicos. El trabajo busca describir la acción del trazar como apertura, exploración (no representación) en el estado naciente del proyecto. Es el cruce entre la acción experienciada y el pensamiento crítico respecto al hacer con aproximaciones a la artesanía (Sennett, 2010), al placer del dibujar (Nancy, 2013) y la aventura de conformar (Badiou, 2006). La experiencia en el dibujar que este estudio recoge es la desarrollada por la autora en el contexto pedagógico del D.I.G.A. de la E.T.S.A. de Madrid en concreto en las asignaturas “Dibujo Avanzado e Interpretación Gráfica (DAII) I y II” y “Dibujo del Natural” ambas impartidas por el profesor Antonio Verd Herrero y en la participación en los trabajos del Grupo de Investigación y de Innovación Educativa denominado: “Hypermedia” dirigidos por el profesor Javier Seguí, en el periodo que va del año 2007 a la actualidad. La colección de acontecimientos que surgió de esta experiencia y se formó de aproximaciones sucesivas presenta algunos rasgos característicos de la acción del dibujar. Los acontecimientos abordan la acción del dibujar desde una experiencia muda, un tipo de lenguaje, escritura y comunicación común, intercultural pero a la vez impersonal, desde su relación con la escritura, la palabra, el movimiento, el gesto y su imagen. El dibujar se presenta como modo de exploración en la investigación proyectual basada en la arbitrariedad que requiere voluntad, compromiso, ir en contra para participar en cualquier transformación de los límites (físicos, nacionales, sociales, de género, religión, sentido). El dibujar no representativo se presenta como técnica imaginaria radical, “terapia” configural con capacidad para la experimentación con uno mismo (Sloderdijk, 2003), un modo de comunicación intercultural que, sin embargo, siempre recurre al lenguaje verbal, leída e interpretada para cobrar sentido. ABSTRACT The action of drawing is intended to be presented in this text as a mute language, a common practice in general and a common practice in the field of architecture specifically; and also as an action, opening, exploration (not representation) at the birth stage of a project. The thesis forms a study based on a direct observation in an in situ experience (Practice Based Design Doctórate), which intends to reflect not on the products produced by drawing, but on the action itself, emphasizing on the dynamics of the body as a generator of dynamic gestures. The work is the intersection of experienced action and critical thinking related with the making with an approach to a path on craftsmanship (Sennett, 2010), the pleasure in drawing (Nancy, 2013) and the adventure of compromise/ conciliation (Badiou, 2006). The experience in drawing was collected and developed for this study by the author in the context of D.I.G.A. at the E.T.S.A. of Madrid and in particular at the courses of “Advanced Drawing and Graphic Interpretation” (DAII) I y II” and “Life drawing”, together with the active participation and the work of the investigation and Innovation Educational Group “Hypermedia”, coordinated by professor Javier Seguí, during the period starting the year 2007 until the present (2013). The collection of the events derives from a process of successive attempts to approach some characteristic aspects of the action of drawing. The events approach the action of drawing as a mute experience, a kind of language, common communication, writing, gesture and image. Drawing is presented as a way of exploration for a project's investigation, based on arbitrarily and on the asking “what if”. At the same time this process requires will, compromise, opposition in order to participate in a transformation of any kind of limits (physical, national, social, genre, religion, sense). This thesis aims to present non-representative drawing as a radical imaginary technique, a configurational ‘therapy’ with the capacity to experiment with oneself (Sloderdijk, 2003). It can also be considered as a way of intercultural communication which always uses the verbal, readable and interpreted language in order to charge sense.
Resumo:
In the SESAR Step 2 concept of operations a RBT is available and seen by all making it possible to conceive a different operating method than the current ATM system based on Collaborative Decisions Making processes. Currently there is a need to describe in more detail the mechanisms by which actors (ATC, Network Management, Flight Crew, airports and Airline Operation Centre) will negotiate revisions to the RBT. This paper introduces a negotiation model, which uses constraint based programing applied to a mediator to facilitate negotiation process in a SWIM enabled environment. Three processes for modelling the negotiation process are explained as well a preliminary reasoning agent algorithm modelled with constraint satisfaction problem is presented. Computational capability of the model is evaluated in the conclusion.
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This paper analyzes issues which appear when supporting pruning operators in tabled LP. A version of the once/1 control predicate tailored for tabled predicates is presented, and an implementation analyzed and evaluated. Using once/1 with answer-on-demand strategies makes it possible to avoid computing unneeded solutions for problems which can benefit from tabled LP but in which only a single solution is needed, such as model checking and planning. The proposed version of once/1 is also directly applicable to the efficient implementation of other optimizations, such as early completion, cut-fail loops (to, e.g., prune at the top level), if-then-else, and constraint-based branch-and-bound optimization. Although once/1 still presents open issues such as dependencies of tabled solutions on program history, our experimental evaluation confirms that it provides an arbitrarily large efficiency improvement in several application areas.
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Modern sensor technologies and simulators applied to large and complex dynamic systems (such as road traffic networks, sets of river channels, etc.) produce large amounts of behavior data that are difficult for users to interpret and analyze. Software tools that generate presentations combining text and graphics can help users understand this data. In this paper we describe the results of our research on automatic multimedia presentation generation (including text, graphics, maps, images, etc.) for interactive exploration of behavior datasets. We designed a novel user interface that combines automatically generated text and graphical resources. We describe the general knowledge-based design of our presentation generation tool. We also present applications that we developed to validate the method, and a comparison with related work.
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Optical communications receivers using wavelet signals processing is proposed in this paper for dense wavelength-division multiplexed (DWDM) systems and modal-division multiplexed (MDM) transmissions. The optical signal-to-noise ratio (OSNR) required to demodulate polarization-division multiplexed quadrature phase shift keying (PDM-QPSK) modulation format is alleviated with the wavelet denoising process. This procedure improves the bit error rate (BER) performance and increasing the transmission distance in DWDM systems. Additionally, the wavelet-based design relies on signal decomposition using time-limited basis functions allowing to reduce the computational cost in Digital-Signal-Processing (DSP) module. Attending to MDM systems, a new scheme of encoding data bits based on wavelets is presented to minimize the mode coupling in few-mode (FWF) and multimode fibers (MMF). The Shifted Prolate Wave Spheroidal (SPWS) functions are proposed to reduce the modal interference.
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Passive energy dissipation devices are increasingly implemented in frame structures to improve their performance under seismic loading. Most guidelines for designing this type of system retain the requirements applicable to frames without dampers, and this hinders taking full advantage of the benefits of implementing dampers. Further, assessing the extent of damage suffered by the frame and by the dampers for different levels of seismic hazard is of paramount importance in the framework of performance-based design. This paper presents an experimental investigation whose objectives are to provide empirical data on the response of reinforced concrete (RC) frames equipped with hysteretic dampers (dynamic response and damage) and to evaluate the need for the frame to form a strong column-weak beam mechanism and dissipate large amounts of plastic strain energy. To this end, shake-table tests were conducted on a 2/5-scale RC frame with hysteretic dampers. The frame was designed only for gravitational loads. The dampers provided lateral strength and stiffness, respectively, three and 12 times greater than those of the frame. The test structure was subjected to a sequence of seismic simulations that represented different levels of seismic hazard. The RC frame showed a performance level of "immediate occupancy", with maximum rotation demands below 20% of the ultimate capacity. The dampers dissipated most of the energy input by the earthquake. It is shown that combining hysteretic dampers with flexible reinforced concrete frames leads to structures with improved seismic performance and that requirements of conventional RC frames (without dampers) can be relieved.
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El presente trabajo aborda el análisis de la idea de monumentalidad, así como el diseño y la construcción de monumentos concretos, a la finalización de la Segunda Guerra Mundial, prestando especial atención al intento del Movimiento Moderno de introducirse en un campo que hasta entonces le había sido ajeno. Entendiendo que el monumento es ante todo un artefacto para la memoria, y analizando las teorías de sociólogos como Émile Durkheim, Maurice Halbwachs, Jan Assmann o Iwona Irwin-Zarecka, la tesis se propone explicar el papel que juegan los monumentos en la creación de una memoria colectiva que, a diferencia de la historia, es una recopilación selectiva de acontecimientos del pasado cuyo fin es procurar y celebrar la permanencia del grupo social. También se propone analizar el papel del monumento como elemento de estabilidad en el paisaje urbano que genera de forma natural el apego de los ciudadanos, puesto que forma parte destacada del marco espacial en el que se han desarrollado sus vidas. Desde estas dos facetas se pretende justificar la necesidad de monumentos que experimenta cualquier grupo social, y por qué las guerras, que ponen en peligro la estructura, e incluso la propia vida del grupo, son acontecimientos que generan una tendencia especial a la construcción de monumentos que conjuren el peligro al que éste se ha visto sometido. Se explicarán las razones por las que la conmemoración de la Segunda Guerra Mundial se volvió especialmente problemática. Entre las principales, la desaparición de fronteras entre frente y retaguardia, entre objetivos militares y civiles; por otra parte la despersonalización de la acción bélica como consecuencia de la aplicación de la tecnología; en tercer lugar el papel de los medios de comunicación de masas, que por primera vez en la historia irrumpieron de forma masiva en una guerra, y ofrecían imágenes instantáneas, más impactantes y con un aura de realidad con la que el monumento convencional no era capaz de competir; en cuarto lugar el inicio de la era atómica, que enfrentaba por primera vez a la humanidad a la posibilidad de su destrucción total; y finalmente la experiencia del Holocausto, en cuanto que aniquilación carente de objetivo e ideología, que se servía del progreso de la ciencia para ganar en eficiencia, y que puso de manifiesto la manipulabilidad de la tecnología al servicio de unos intereses particulares. Como respuesta a esta dificultad para la conmemoración, se popularizaron dos fórmulas hasta entonces marginales que podemos considerar características del momento: una de ellas es el living memorial, que trataba de ofrecer una lectura constructiva de la guerra poniendo de relieve determinadas funciones prácticas de carácter democrático, cultural, deportivo, etc. que se presentaban como los frutos por los que se había combatido en la guerra. En esta fórmula es donde el Movimiento Moderno encontró la posibilidad de abordar nuevos proyectos, en los que la función estaba presente pero no era el ingrediente determinante, lo que obligaría a un enriquecimiento del lenguaje con el que responder a la dimensión emotiva del monumento. Y si bien hay en esta época edificios modernos que podemos calificar justamente de monumentos, el desplazamiento del centro del debate teórico hacia cuestiones estilísticas y expresivas limitó considerablemente la claridad de los enunciados anteriores y la posibilidad de consenso. Dentro de los living memorials, las sedes de la Organización de Naciones Unidas y sus correspondientes agencias representaron la mayor esperanza del Movimiento Moderno por construir un auténtico monumento. Sin embargo, el sistema de trabajo en grupo, con su correspondiente conflicto de personalidades, la ausencia de proyección de los edificios sobre el espacio urbano anexo, y sobre todo el propio descrédito que comenzaron a sufrir las instituciones con el comienzo de la Guerra Fría, frustraron esta posibilidad. La segunda fórmula conmemorativa sería el monumento de advertencia o mahnmal, que renuncia a cualquier rasgo de heroísmo o romanticismo, y se concentra simplemente en advertir de los riesgos que implica la guerra. Dicha fórmula se aplicó fundamentalmente en los países vencidos, y generalmente no por iniciativa propia, sino como imposición de los vencedores, que de alguna forma aprovechaban la ocasión para hacer examen de conciencia lejos de la opinión pública de sus respectivos países. ABSTRACT This paper explores the idea of monumentality through the analysis of the design and construction of several monuments at the end ofWorldWar II. It pays particular attention to the attempt of the Modern Movement to enter a field that had been ignored until this moment. With the assumption that a monument is primarily a mnemonic device, this thesis focuses on the thinking of sociologists like Émile Durkheim, Maurice Halbwachs, Jan Assmann or Iwona Irwin-Zarecka, with the aim of explaining the role of monuments in the creation of a collective memory which, unlike history, consists of past events selected in order to secure and celebrate the permanence of a social group. It also considers the role of monuments as elements of stability in the urban landscape that naturally get assimilated by society, since they are prominent elements in the shared spaces of daily life. These two features explain the need felt by any society for monuments, and how wars, events that endanger the structure and even the existence of that same society, generate a special tendency to build monuments to conjure that inherent danger. The reasons why the memorializing of World War II became especially problematic will be explained. Primary among them is the blurring of boundaries between the front line and the domestic front, between military and civilian targets; moreover, the depersonalization of warfare as a result of advances in technology; thirdly, the role of mass media, which for the first time in history extensively covered a war, instantly broadcasting images of such power and with such an aura of reality that conventional monuments became obsolete; fourthly, the beginning of the atomic age, which meant that mankind faced the possibility of complete destruction; and finally the Holocaust, a racial annihilation devoid of purpose and ideology, which took advantage of scientific progress to gain efficiency, manipulating technology to serve particular interests. In response to this difficulty in commemorating wars, two formulas hitherto marginal gained such popularity as to become prototypes: one was the living memorial, offering a constructive reading of the war by hosting certain practical functions of democratic, cultural or sporting nature. Living memorials presented themselves as the image of the outcome for which the war had been fought. The Modern Movement found in this formula the opportunity for tackling new projects, in which function was present but not as the determining ingredient; in turn, they would require an enhancement of language in order to account for the emotional dimension of the monument. And while there are modern buildings at this time that we can justly describe as monuments, the displacement of the focus of the theoretical debate to stylistic and expressive issues considerably limited the clarity of previous statements and the possibility of consensus. Among all living memorials, the headquarters of the United Nations Organization and its satellite agencies represented the ultimate hope of the Modern Movement to build an authentic monument. However, the group-based design process, the fight of egos it caused, the lack of presence of these buildings over the adjacent urban space, and especially the very discredit that these institutions began to suffer with the onset of the Cold War, all thwarted this expectation. The second commemorative formula was the warning monument or Mahnmal, which rejects any trace of heroism or romanticism, and simply focuses on warning about the risks of war. This formula was mainly used in defeated countries, and generally not on their own initiative, but as an imposition of the victors, which seized the opportunity to do some soul-searching far away from the public opinion of their respective countries.