944 resultados para horizons roulants
Resumo:
A study has been made on the influence of the open trailing edge in airfoils used in different devices relating their aerodynamic performances. Wind tunnel tests have been made at different Reynolds numbers and angles of attack in order to show this effect. Besides, a quantitative study of the aerodynamic properties has been made based on the different trailing edge thickness
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New actuation technology in functional or "smart" materials has opened new horizons in robotics actuation systems. Materials such as piezo-electric fiber composites, electro-active polymers and shape memory alloys (SMA) are being investigated as promising alternatives to standard servomotor technology [52]. This paper focuses on the use of SMAs for building muscle-like actuators. SMAs are extremely cheap, easily available commercially and have the advantage of working at low voltages. The use of SMA provides a very interesting alternative to the mechanisms used by conventional actuators. SMAs allow to drastically reduce the size, weight and complexity of robotic systems. In fact, their large force-weight ratio, large life cycles, negligible volume, sensing capability and noise-free operation make possible the use of this technology for building a new class of actuation devices. Nonetheless, high power consumption and low bandwidth limit this technology for certain kind of applications. This presents a challenge that must be addressed from both materials and control perspectives in order to overcome these drawbacks. Here, the latter is tackled. It has been demonstrated that suitable control strategies and proper mechanical arrangements can dramatically improve on SMA performance, mostly in terms of actuation speed and limit cycles.
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The important developments in technology in all areas of human life have generated high expectations and hopes with regard to the health sector. Science and technology have favored the development of incredible therapeutic treatments to help resolve numerous problems relating to illness and disability. Nonetheless, many developments in the therapeutic realm have given rise to discussions over the possibility of whether this same scientific and technological progress could be beneficial even for those who may not be sick. One may ask: why not apply the same knowledge and technology used for treatment of illness for conditions where therapy is not necessary, but there is a desire to care for, improve and enhance human person? These new horizons offered by biomedical technologies undoubtedly express a deep desire of every person for health, happiness, and a long life. In order to offer a response to these questions, current biomedical technologies and those in development offer a wide range of possibilities. Therefore, in this investigation we attempt to identify and define four areas of non-therapeutic treatment: illness prevention, health promotion, improving human nature, and human enhancement. These four areas, which do not directly regard illness, give rise to a series of questions, which range from those regarding the meaning of health and illness to those concerning anthropological questions, such as situations and conditions that must be taken into account so human dignity is respected. The treatment, improvement and enhancement of the human being imply clarifying in scientific and technological terms the truth and meaning of the human person as such. This research identifies and looks at the relationship between the four anthropological cornerstones which non-therapeutic biomedical technologies should be based upon so as not to impact or violate the dignity of the human person. This research presents the anthropological boundaries which non-therapeutic biomedical technologies should take into consideration so as not to alter or violate the dignity of the human person. At the same time, the research proposes an anthropological foundation on which to build a code of ethics for non-therapeutic biomedical technologies. El gran desarrollo de las tecnologías en todos los ámbitos de la vida del hombre ha generado una gran expectativa y esperanza en lo que se refiere a la salud. Ciencia y técnica están aportando grandes beneficios en materia terapéutica, ayudando a resolver muchos problemas concernientes a la enfermedad y a la discapacidad. Pero este desarrollo que se ha producido en el ámbito terapéutico nos conduce a la formulación de preguntas sobre las posibilidades que esos avances técnico-científicos pueden aportar en beneficio del hombre, cuando no se encuentra enfermo: ¿por qué no pueden aplicarse los conocimientos y tecnologías usados en terapia a un ámbito diferente, no terapéutico, con el fin de mantener, mejorar o incluso potenciar al hombre? Ciertamente los nuevos horizontes que abren las Tecnologías Biomédicas encuentran repercusión en el deseo de bienestar, de felicidad e incluso de prolongación de la vida presente en todos los hombres. Para responder a esta pregunta las Tecnologías Biomédicas han desarrollado y están desarrollando una gama muy amplia de posibilidades. En este trabajo intentamos organizar en cuatro áreas los conceptos de los tratamientos no-terapéuticos: prevención de la enfermedad, promoción de la salud, mejoramiento de la naturaleza humana y potenciación del hombre. Estas cuatro áreas, que no se refieren directamente a la enfermedad, generan una serie de interrogantes que van desde las preguntas sobre el significado de salud y enfermedad, hasta las cuestiones antropológicas relativas a la posibilidad y las condiciones que se han de dar para que tales acciones respeten la dignidad humana. Cuidar, mejorar y potenciar al hombre implica que los objetivos de la ciencia y de la técnica mantengan siempre claros los valores y la realidad del hombre en cuanto tal. ... Este Trabajo de Investigación presenta los límites antropológicos dentro de los cuales deben moverse las Tecnologías Biomédicas no-terapéuticas para no alterar el ser ni menoscabar la dignidad del hombre. Y ofrece los fundamentos antropológicos sobre los cuales se pueda construir un código ético y deontológico para las Tecnologías Biomédicas no-terapéuticas.
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Stonemasonry of the Gothic vault in its totality is based upon geometry of the line, whereas classic stereotomy relies on the comprehensive knowledge of the surface and the highly sophisticated sides of the voussoirs necessary for its vaults. It is obvious that this leap in the art of construction was paralleled and accompanied by an extension of the horizons of geometry. In Spain, it was made possible thanks to the centuries-old tradition of stone building begun in the most remote medieval times and to the presence of outstanding architects or stonemasons such as Juan de Álava, whose professional work surpassed the established limits and provided the art of building with new instruments.
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Patent and trademark offices which run according to principles of new management have an inherent need for dependable forecasting data in planning capacity and service levels. The ability of the Spanish Office of Patents and Trademarks to carry out efficient planning of its resource needs requires the use of methods which allow it to predict the changes in the number of patent and trademark applications at different time horizons. The approach for the prediction of time series of Spanish patents and trademarks applications (1979e2009) was based on the use of different techniques of time series prediction in a short-term horizon. The methods used can be grouped into two specifics areas: regression models of trends and time series models. The results of this study show that it is possible to model the series of patents and trademarks applications with different models, especially ARIMA, with satisfactory model adjustment and relatively low error.
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Immersion and interaction have been identified as key factors influencing the quality of experience in stereoscopic video systems. The work presented here aims to create a new paradigm for 3D Multimedia consumption exploiting these factors in order to increase user involvement. We use a 5-sided CAVETM environment to support 3D panoramic video reproduction, real-time insertion of synthetic objects into the three-dimensional scene and real-time user interaction with the inserted elements. In this paper we describe our system requirements, functionalities, conceptual design and preliminary implementation results emphasizing the most relevant challenges accomplished. The focus is on three main issues: the generation of stereoscopic video panoramas; the synchronous reproduction of immersive 3D video across multiple screens; and, the real-time insertion algorithm implemented for the integration of synthetic objects into the stereoscopic video. These results have been successfully integrated into the graphic engine managing the operation of the CAVETM infrastructure.
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First, this paper describes a future layered Air Traffic Management (ATM) system centred in the execution phase of flights. The layered ATM model is based on the work currently performed by SESAR [1] and takes into account the availability of accurate and updated flight information ?seen by all? across the European airspace. This shared information of each flight will be referred as Reference Business Trajectory (RBT). In the layered ATM system, exchanges of information will involve several actors (human or automatic), which will have varying time horizons, areas of responsibility and tasks. Second, the paper will identify the need to define the negotiation processes required to agree revisions to the RBT in the layered ATM system. Third, the final objective of the paper is to bring to the attention of researchers and engineers the communalities between multi-player games and Collaborative Decision Making processes (CDM) in a layered ATM system
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The study of three soil profiles in the aridic-xeric zone of Las Palmas island showed that: petrocalcic horizons are formed in pyroclastic episodes; these horizons are generally thick; the xeric zone frequently have polycyclic profiles and their carbonates have complex mineralogy; underlain basaltic rocks are scantly altered, and their joints are frequently filled by carbonates. These facts suggest that the development of these profiles is mostly Pleistocene, and the diffuse carbonates accumulation in depth obstructs the assessment of carbonatation processes.
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La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.
Resumo:
Bruise damage is a major cause of quality loss for apples. It would be very useful to establish a method of characterizing bruise susceptibility in order to improve fruit handling, sometimes Magness-Taylor firmness is used as an indirect guide to handling requirements. The objective of the present work was to achieve a better bruise susceptibility prediction.
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Nondestructive techniques are extensively researched for the measurement of physical properties of fruits related to quality. Optical properties can be applied mainly in the detection of those quality features which are related to the chemical composition of the fruit, color (in the VIS region) or chemical constituents (sugar, in the MR region) being the most important. The most relevant mechanical property of fruits is consistency, generally called firmness, and to date only techniques which are able to measure the mechanical properties of the fruit bulk tissue are used for its prediction. Fruits can be modelled as elastic bodies, or at least as partially elastic. Therefore, the measurement of some elastic constants of the fruit can be used for the evaluation of its firmness. The differences in the response to loading are relevant in studying a) fruit firmness and b) bruising susceptibility. Both have been modelled for selected fruit species and varieties.
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One of the fundamental aspects in the adaptation of the teaching to the European higher education is changing based models of teacher education to models based on student learning. In this work we present an educational experience developed with the teaching method based on the case method, with a clearly multidisciplinary. The experience has been developed in the teaching of analysis and verification of safety rails. This is a multidisciplinary field that presents great difficulties during their teaching. The use of the case method has given good results in the competences achieved by students
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The technique of reinforcement of wooden floors is a matter clearly multidisciplinary. The teaching of the subject using the "traditional" method, explaining the theory first and then proposing and solving problems has not been successful. This paper discusses the results of a teaching experiencie. It has been the teaching of the subject by the case method. The results are clearly superior to those obtained with the traditional methodology.
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Flows of relevance to new generation aerospace vehicles exist, which are weakly dependent on the streamwise direction and strongly dependent on the other two spatial directions, such as the flow around the (flattened) nose of the vehicle and the associated elliptic cone model. Exploiting these characteristics, a parabolic integration of the Navier-Stokes equations is more appropriate than solution of the full equations, resulting in the so-called Parabolic Navier-Stokes (PNS). This approach not only is the best candidate, in terms of computational efficiency and accuracy, for the computation of steady base flows with the appointed properties, but also permits performing instability analysis and laminar-turbulent transition studies a-posteriori to the base flow computation. This is to be contrasted with the alternative approach of using order-of-magnitude more expensive spatial Direct Numerical Simulations (DNS) for the description of the transition process. The PNS equations used here have been formulated for an arbitrary coordinate transformation and the spatial discretization is performed using a novel stable high-order finite-difference-based numerical scheme, ensuring the recovery of highly accurate solutions using modest computing resources. For verification purposes, the boundary layer solution around a circular cone at zero angle of attack is compared in the incompressible limit with theoretical profiles. Also, the recovered shock wave angle at supersonic conditions is compared with theoretical predictions in the same circular-base cone geometry. Finally, the entire flow field, including shock position and compressible boundary layer around a 2:1 elliptic cone is recovered at Mach numbers 3 and 4
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En este proyecto se hace un análisis en profundidad de las técnicas de ataque a las redes de ordenadores conocidas como APTs (Advanced Persistent Threats), viendo cuál es el impacto que pueden llegar a tener en los equipos de una empresa y el posible robo de información y pérdida monetaria que puede llevar asociada. Para hacer esta introspección veremos qué técnicas utilizan los atacantes para introducir el malware en la red y también cómo dicho malware escala privilegios, obtiene información privilegiada y se mantiene oculto. Además, y cómo parte experimental de este proyecto se ha desarrollado una plataforma para la detección de malware de una red en base a las webs, URLs e IPs que visitan los nodos que la componen. Obtendremos esta visión gracias a la extracción de los logs y registros de DNS de consulta de la compañía, sobre los que realizaremos un análisis exhaustivo. Para poder inferir correctamente qué equipos están infectados o no se ha utilizado un algoritmo de desarrollo propio inspirado en la técnica Belief Propagation (“Propagación basada en creencia”) que ya ha sido usada antes por desarrolladores cómo los de los Álamos en Nuevo México (Estados Unidos) para fines similares a los que aquí se muestran. Además, para mejorar la velocidad de inferencia y el rendimiento del sistema se propone un algoritmo adaptado a la plataforma Hadoop de Apache, por lo que se modifica el paradigma de programación habitual y se busca un nuevo paradigma conocido como MapReduce que consiste en la división de la información en conceptos clave-valor. Por una parte, los algoritmos que existen basados en Belief Propagation para el descubrimiento de malware son propietarios y no han sido publicados completamente hasta la fecha, por otra parte, estos algoritmos aún no han sido adaptados a Hadoop ni a ningún modelo de programación distribuida aspecto que se abordará en este proyecto. No es propósito de este proyecto desarrollar una plataforma comercial o funcionalmente completa, sino estudiar el problema de las APTs y una implementación que demuestre que la plataforma mencionada es factible de implementar. Este proyecto abre, a su vez, un horizonte nuevo de investigación en el campo de la adaptación al modelo MapReduce de algoritmos del tipo Belief Propagation basados en la detección del malware mediante registros DNS. ABSTRACT. This project makes an in-depth investigation about problems related to APT in computer networks nowadays, seeing how much damage could they inflict on the hosts of a Company and how much monetary and information loss may they cause. In our investigation we will find what techniques are generally applied by attackers to inject malware into networks and how this malware escalates its privileges, extracts privileged information and stays hidden. As the main part of this Project, this paper shows how to develop and configure a platform that could detect malware from URLs and IPs visited by the hosts of the network. This information can be extracted from the logs and DNS query records of the Company, on which we will make an analysis in depth. A self-developed algorithm inspired on Belief Propagation technique has been used to infer which hosts are infected and which are not. This technique has been used before by developers of Los Alamos Lab (New Mexico, USA) for similar purposes. Moreover, this project proposes an algorithm adapted to Apache Hadoop Platform in order to improve the inference speed and system performance. This platform replaces the traditional coding paradigm by a new paradigm called MapReduce which splits and shares information among hosts and uses key-value tokens. On the one hand, existing algorithms based on Belief Propagation are part of owner software and they have not been published yet because they have been patented due to the huge economic benefits they could give. On the other hand these algorithms have neither been adapted to Hadoop nor to other distributed coding paradigms. This situation turn the challenge into a complicated problem and could lead to a dramatic increase of its installation difficulty on a client corporation. The purpose of this Project is to develop a complete and 100% functional brand platform. Herein, show a short summary of the APT problem will be presented and make an effort will be made to demonstrate the viability of an APT discovering platform. At the same time, this project opens up new horizons of investigation about adapting Belief Propagation algorithms to the MapReduce model and about malware detection with DNS records.