929 resultados para Based structure model
Linear global instability of non-orthogonal incompressible swept attachment-line boundary layer flow
Resumo:
Instability of the orthogonal swept attachment line boundary layer has received attention by local1, 2 and global3–5 analysis methods over several decades, owing to the significance of this model to transition to turbulence on the surface of swept wings. However, substantially less attention has been paid to the problem of laminar flow instability in the non-orthogonal swept attachment-line boundary layer; only a local analysis framework has been employed to-date.6 The present contribution addresses this issue from a linear global (BiGlobal) instability analysis point of view in the incompressible regime. Direct numerical simulations have also been performed in order to verify the analysis results and unravel the limits of validity of the Dorrepaal basic flow7 model analyzed. Cross-validated results document the effect of the angle _ on the critical conditions identified by Hall et al.1 and show linear destabilization of the flow with decreasing AoA, up to a limit at which the assumptions of the Dorrepaal model become questionable. Finally, a simple extension of the extended G¨ortler-H¨ammerlin ODE-based polynomial model proposed by Theofilis et al.4 is presented for the non-orthogonal flow. In this model, the symmetries of the three-dimensional disturbances are broken by the non-orthogonal flow conditions. Temporal and spatial one-dimensional linear eigenvalue codes were developed, obtaining consistent results with BiGlobal stability analysis and DNS. Beyond the computational advantages presented by the ODE-based model, it allows us to understand the functional dependence of the three-dimensional disturbances in the non-orthogonal case as well as their connections with the disturbances of the orthogonal stability problem.
Resumo:
This paper presents the results obtained with a new agent-based computer model that can simulate the evacuation of narrow-body transport airplanes in the conditions prescribed by the airworthiness regulations for certification. The model, described in detail in a former paper, has been verified with real data of narrow-body certification demonstrations. Numerical simulations of around 20 narrow-body aircraft, representative of current designs in various market segments, show the capabilities of the model and provide relevant information on the relationship between cabin features and emergency evacuation. The longitudinal location of emergency exits seems to be even more important than their size or the overall margin with respect to the prescribed number and type of exits indicated by the airworthiness requirements
Resumo:
How to create or integrate large Smart Spaces (considered as mash-ups of sensors and actuators) into the paradigm of ?Web of Things? has been the motivation of many recent works. A cutting-edge approach deals with developing and deploying web-enabled embedded devices with two major objectives: 1) to integrate sensor and actuator technologies into everyday objects, and 2) to allow a diversity of devices to plug to Internet. Currently, developers who want to use this Internet-oriented approach need have solid understanding about sensorial platforms and semantic technologies. In this paper we propose a Resource-Oriented and Ontology-Driven Development (ROOD) methodology, based on Model Driven Architecture (MDA), to facilitate to any developer the development and deployment of Smart Spaces. Early evaluations of the ROOD methodology have been successfully accomplished through a partial deployment of a Smart Hotel.
Resumo:
This work describes an acoustic system that allows the automatic detection and location of mechanical impacts on metallic based structures, which is suitable in robotics and industrial applications. The system is based on the time delays of propagation of the acoustic waves along the metallic based structure and it determines the instant and the position when and were the impact has been produced by piezoelectric sensors and an electronic-computerized system. We have obtained that for distance impact of 40 cm and 50 cm the time delay is 2 s and 72 s respectively.
Resumo:
En esta Tesis Doctoral se emplean y desarrollan Métodos Bayesianos para su aplicación en análisis geotécnicos habituales, con un énfasis particular en (i) la valoración y selección de modelos geotécnicos basados en correlaciones empíricas; en (ii) el desarrollo de predicciones acerca de los resultados esperados en modelos geotécnicos complejos. Se llevan a cabo diferentes aplicaciones a problemas geotécnicos, como es el caso de: (1) En el caso de rocas intactas, se presenta un método Bayesiano para la evaluación de modelos que permiten estimar el módulo de Young a partir de la resistencia a compresión simple (UCS). La metodología desarrollada suministra estimaciones de las incertidumbres de los parámetros y predicciones y es capaz de diferenciar entre las diferentes fuentes de error. Se desarrollan modelos "específicos de roca" para los tipos de roca más comunes y se muestra cómo se pueden "actualizar" esos modelos "iniciales" para incorporar, cuando se encuentra disponible, la nueva información específica del proyecto, reduciendo las incertidumbres del modelo y mejorando sus capacidades predictivas. (2) Para macizos rocosos, se presenta una metodología, fundamentada en un criterio de selección de modelos, que permite determinar el modelo más apropiado, entre un conjunto de candidatos, para estimar el módulo de deformación de un macizo rocoso a partir de un conjunto de datos observados. Una vez que se ha seleccionado el modelo más apropiado, se emplea un método Bayesiano para obtener distribuciones predictivas de los módulos de deformación de macizos rocosos y para actualizarlos con la nueva información específica del proyecto. Este método Bayesiano de actualización puede reducir significativamente la incertidumbre asociada a la predicción, y por lo tanto, afectar las estimaciones que se hagan de la probabilidad de fallo, lo cual es de un interés significativo para los diseños de mecánica de rocas basados en fiabilidad. (3) En las primeras etapas de los diseños de mecánica de rocas, la información acerca de los parámetros geomecánicos y geométricos, las tensiones in-situ o los parámetros de sostenimiento, es, a menudo, escasa o incompleta. Esto plantea dificultades para aplicar las correlaciones empíricas tradicionales que no pueden trabajar con información incompleta para realizar predicciones. Por lo tanto, se propone la utilización de una Red Bayesiana para trabajar con información incompleta y, en particular, se desarrolla un clasificador Naïve Bayes para predecir la probabilidad de ocurrencia de grandes deformaciones (squeezing) en un túnel a partir de cinco parámetros de entrada habitualmente disponibles, al menos parcialmente, en la etapa de diseño. This dissertation employs and develops Bayesian methods to be used in typical geotechnical analyses, with a particular emphasis on (i) the assessment and selection of geotechnical models based on empirical correlations; on (ii) the development of probabilistic predictions of outcomes expected for complex geotechnical models. Examples of application to geotechnical problems are developed, as follows: (1) For intact rocks, we present a Bayesian framework for model assessment to estimate the Young’s moduli based on their UCS. Our approach provides uncertainty estimates of parameters and predictions, and can differentiate among the sources of error. We develop ‘rock-specific’ models for common rock types, and illustrate that such ‘initial’ models can be ‘updated’ to incorporate new project-specific information as it becomes available, reducing model uncertainties and improving their predictive capabilities. (2) For rock masses, we present an approach, based on model selection criteria to select the most appropriate model, among a set of candidate models, to estimate the deformation modulus of a rock mass, given a set of observed data. Once the most appropriate model is selected, a Bayesian framework is employed to develop predictive distributions of the deformation moduli of rock masses, and to update them with new project-specific data. Such Bayesian updating approach can significantly reduce the associated predictive uncertainty, and therefore, affect our computed estimates of probability of failure, which is of significant interest to reliability-based rock engineering design. (3) In the preliminary design stage of rock engineering, the information about geomechanical and geometrical parameters, in situ stress or support parameters is often scarce or incomplete. This poses difficulties in applying traditional empirical correlations that cannot deal with incomplete data to make predictions. Therefore, we propose the use of Bayesian Networks to deal with incomplete data and, in particular, a Naïve Bayes classifier is developed to predict the probability of occurrence of tunnel squeezing based on five input parameters that are commonly available, at least partially, at design stages.
Resumo:
Low-cost systems that can obtain a high-quality foreground segmentation almostindependently of the existing illumination conditions for indoor environments are verydesirable, especially for security and surveillance applications. In this paper, a novelforeground segmentation algorithm that uses only a Kinect depth sensor is proposedto satisfy the aforementioned system characteristics. This is achieved by combininga mixture of Gaussians-based background subtraction algorithm with a new Bayesiannetwork that robustly predicts the foreground/background regions between consecutivetime steps. The Bayesian network explicitly exploits the intrinsic characteristics ofthe depth data by means of two dynamic models that estimate the spatial and depthevolution of the foreground/background regions. The most remarkable contribution is thedepth-based dynamic model that predicts the changes in the foreground depth distributionbetween consecutive time steps. This is a key difference with regard to visible imagery,where the color/gray distribution of the foreground is typically assumed to be constant.Experiments carried out on two different depth-based databases demonstrate that theproposed combination of algorithms is able to obtain a more accurate segmentation of theforeground/background than other state-of-the art approaches.
Resumo:
An innovative background modeling technique that is able to accurately segment foreground regions in RGB-D imagery (RGB plus depth) has been presented in this paper. The technique is based on a Bayesian framework that efficiently fuses different sources of information to segment the foreground. In particular, the final segmentation is obtained by considering a prediction of the foreground regions, carried out by a novel Bayesian Network with a depth-based dynamic model, and, by considering two independent depth and color-based mixture of Gaussians background models. The efficient Bayesian combination of all these data reduces the noise and uncertainties introduced by the color and depth features and the corresponding models. As a result, more compact segmentations, and refined foreground object silhouettes are obtained. Experimental results with different databases suggest that the proposed technique outperforms existing state-of-the-art algorithms.
Resumo:
Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.
Resumo:
We have investigated the role of 2′-OH groups in the specific interaction between the acceptor stem of Escherichia coli tRNACys and cysteine-tRNA synthetase. This interaction provides for the high aminoacylation specificity observed for cysteine-tRNA synthetase. A synthetic RNA microhelix that recapitulates the sequence of the acceptor stem was used as a substrate and variants containing systematic replacement of the 2′-OH by 2′-deoxy or 2′-O-methyl groups were tested. Except for position U73, all substitutions had little effect on aminoacylation. Interestingly, the deoxy substitution at position U73 had no effect on aminoacylation, but the 2′-O-methyl substitution decreased aminoacylation by 10-fold and addition of the even bulkier 2′-O-propyl group decreased aminoacylation by another 2-fold. The lack of an effect by the deoxy substitution suggests that the hydrogen bonding potential of the 2′-OH at position U73 is unimportant for aminoacylation. The decrease in activity upon alkyl substitution suggests that the 2′-OH group instead provides a monitor of the steric environment during the RNA–synthetase interaction. The steric role was confirmed in the context of a reconstituted tRNA and is consistent with the observation that the U73 base is the single most important determinant for aminoacylation and therefore is a site that is likely to be in close contact with cysteine-tRNA synthetase. A steric role is supported by an NMR-based structural model of the acceptor stem, together with biochemical studies of a closely related microhelix. This role suggests that the U73 binding site for cysteine-tRNA synthetase is sterically optimized to accommodate a 2′-OH group in the backbone, but that the hydroxyl group itself is not involved in specific hydrogen bonding interactions.
Resumo:
Biotinylated lactose permease from Escherichia coli containing a single-cysteine residue at position 330 (helix X) or at position 147, 148, or 149 (helix V) was purified by avidin-affinity chromatography and derivatized with 5-(alpha-bromoacetamido)-1,10-phenanthroline-copper [OP(Cu)]. Studies with purified, OP(Cu)-labeled Leu-330 --> Cys permease in dodecyl-beta-D-maltopyranoside demonstrate that after incubation in the presence of ascorbate, cleavage products of approximately 19 and 6-8 kDa are observed on immunoblots with anti-C-terminal antibody. Remarkably, the same cleavage products are observed with permease embedded in the native membrane. Comparison with the C-terminal half of the permease expressed independently as a standard indicates that the 19-kDa product results from cleavage near the cytoplasmic end of helix VII, whereas the 6- to 8-kDa fragment probably results from fragmentation near the cytoplasmic end of helix XI. Results are entirely consistent with a tertiary-structure model of the C-terminal half of the permease derived from earlier site-directed fluorescence and site-directed mutagenesis studies. Similar studies with OP(Cu)-labeled Cys-148 permease exhibit cleavage products at approximately 19 kDa and at 15-16 kDa. The larger fragment probably reflects cleavage at a site near the cytoplasmic end of helix VII, whereas the 15- to 16-kDa fragment is consistent with cleavage near the cytoplasmic end of helix VIII. When OP(Cu) is moved 100 degrees to position 149 (Val-149 --> Cys permease), a single product is observed at 19 kDa, suggesting fragmentation at the cytoplasmic end of helix VII. However, when the reagent is moved 100 degrees in the other direction to position 147 (Gly-147 --> Cys permease), cleavage is not observed. The results suggest that helix V is in close proximity to helices VII and VIII with position 148 in the interface between the helices, position 149 facing helix VII, and position 147 facing the lipid bilayer.
Estudo e implementação de sinais de excitação aplicados em identificação de sistemas multivariáveis.
Resumo:
Devido à crescente implementação do Controle Preditivo baseado em Modelo (MPC) em outros processos além de refino e plantas petroquímicas, que geralmente possuem múltiplas entradas e saídas, tem-se um aumento na demanda de modelos gerados por identificação de sistemas. Identificar modelos que representem fielmente a dinâmica do processo depende em grande medida das características dos sinais de excitação dos processos. Assim, o foco deste trabalho é realizar um estudo dos sinais típicos usados em identificação de sistemas, PRBS e GBN, em uma abordagem multivariável. O estudo feito neste trabalho parte das características da geração dos sinais individualmente, depois é feita uma análise de correlação cruzada dos sinais de entrada, observando a influência desta sobre os resultados de identificação. Evitar uma alta correlação entre os sinais de entrada permite determinar o efeito de cada entrada sobre a saída no processo de identificação. Um ponto importante no projeto de sinais de identificação de sistemas multivariáveis é a frequência dos mesmos para conseguir excitar os processos nas regiões de frequência de operação normal e assim extrair a maior informação dinâmica possível do processo. As características estudadas são avaliadas por meio de testes em três plantas simuladas diferentes, categorizadas como mal, medianamente e bem condicionadas. Estas implementações foram feitas usando sinais GBN e PRBS de diferentes frequências. Expressões para a caracterização dos sinais de excitação foram avaliadas identificando os processos em malha aberta e malha fechada. Para as plantas mal condicionadas foram implementados sinais compostos por uma parte completamente correlacionada e uma parte não-correlacionada, conhecido como método de dois passos. Finalmente são realizados experimentos de identificação em uma aplicação em tempo real de uma planta piloto de neutralização de pH. Os testes realizados na planta foram feitos visando avaliar os estudos de frequência e correlação em uma aplicaficção real. Os resultados mostram que a condição de sinais completamente descorrelacionados n~ao deve ser cumprida para ter bons resultados nos modelos identificados. Isto permite ter mais exibilidade na geração do conjunto de sinais de excitação.
Resumo:
To examine population affinities in light of the ‘dual structure model’, frequencies of 21 nonmetric cranial traits were analyzed in 17 prehistoric to recent samples from Japan and five from continental northeast Asia. Eight bivariate plots, each representing a different bone or region of the skull, as well as cluster analysis of 21-trait mean measures of divergence using multidimensional scaling and additive tree techniques, revealed good discrimination between the Jomon-Ainu indigenous lineage and that of the immigrants who arrived from continental Asia after 300 BC. In Hokkaido, in agreement with historical records, Ainu villages of Hidaka province were least, and those close to the Japan Sea coast were most, hybridized with Wajin. In the central islands, clines were identified among Wajin skeletal samples whereby those from Kyushu most resembled continental northeast Asians, while those from the northernmost prefectures of Tohoku apparently retained the strongest indigenous heritage. In the more southerly prefectures of Tohoku, stronger traces of Jomon ancestry prevailed in the cohort born during the latest Edo period than in the one born after 1870. Thus, it seems that increased inter-regional mobility and gene flow following the Meiji Restoration initiated the most recent episode in the long process of demic diffusion that has helped to shape craniofacial change in Japan.
Resumo:
The crisis in Russia’s financial market, which started in mid-December 2014, has exposed the real scale of the economic problems that have been growing in Russia for several years. Over the course of the last year, Russia’s basic macroeconomic indicators deteriorated considerably, the confidence of its citizens in the state and in institutions in charge of economic stability declined, the government and business elites became increasingly dissatisfied with the policy direction adopted by the Kremlin, and fighting started over the shrinking resources. According to forecasts obtained from both governmental and expert communities, Russia will fall into recession in 2015. The present situation is the result of the simultaneous occurrence of three unfavourable trends: the fact that the Russian economy’s resource-based development model has reached the limits of its potential due to structural weaknesses, the dramatic decline in oil prices in the second half of 2014, and the impact of Western economic sanctions. Given the inefficiency of existing systemic mechanisms, in the coming years the Russian leadership will likely resort to ad hoc solutions such as switching to a more interventionist “manual override” mode in governing the state. In the short term, this will allow them to neutralise the most urgent problems, although an effective development policy will be impossible without a fundamental change of the political and economic system in Russia.
Resumo:
We estimate the 'fundamental' component of euro area sovereign bond yield spreads, i.e. the part of bond spreads that can be justified by country-specific economic factors, euro area economic fundamentals, and international influences. The yield spread decomposition is achieved using a multi-market, no-arbitrage affine term structure model with a unique pricing kernel. More specifically, we use the canonical representation proposed by Joslin, Singleton, and Zhu (2011) and introduce next to standard spanned factors a set of unspanned macro factors, as in Joslin, Priebsch, and Singleton (2013). The model is applied to yield curve data from Belgium, France, Germany, Italy, and Spain over the period 2005-2013. Overall, our results show that economic fundamentals are the dominant drivers behind sovereign bond spreads. Nevertheless, shocks unrelated to the fundamental component of the spread have played an important role in the dynamics of bond spreads since the intensification of the sovereign debt crisis in the summer of 2011
Resumo:
In the deep-sea, the Paleocene-Eocene Thermal Maximum (PETM) is often marked by clay-rich condensed intervals caused by dissolution of carbonate sediments, capped by a carbonate-rich interval. Constraining the duration of both the dissolution and subsequent cap-carbonate intervals is essential to computing marine carbon fluxes and thus testing hypotheses for the origin of this event. To this end, we provide new high-resolution helium isotope records spanning the Paleocene-Eocene boundary at ODP Site 1266 in the South Atlantic. The extraterrestrial 3He, 3HeET, concentrations replicate trends observed at ODP Site 690 by Farley and Eltgroth (2003, doi:10.1016/S0012-821X(03)00017-7). By assuming a constant flux of 3HeET we constrain relative changes in accumulation rates of sediment across the PETM and construct a new age model for the event. In this new chronology the zero carbonate layer represents 35 kyr, some of which reflects clay produced by dissolution of Paleocene (pre-PETM) sediments. Above this layer, carbonate concentrations increase for ~165 kyr and remain higher than in the latest Paleocene until 234 +48/-34 kyr above the base of the clay. The new chronology indicates that minimum d13C values persisted for a maximum of 134 +27/-19 kyr and the inflection point previously chosen to designate the end of the CIE recovery occurs at 217 +44/-31 kyr. This allocation of time differs from that of the cycle-based age model of Röhl et al. (2007, doi:10.1029/2007GC001784) in that it assigns more time to the clay layer followed by a more gradual recovery of carbonate-rich sedimentation. The new model also suggests a longer sustained d13C excursion followed by a more rapid recovery to pre-PETM d13C values. These differences have important implications for constraining the source(s) of carbon and mechanisms for its subsequent sequestration, favoring models that include a sustained release