959 resultados para CMF, molecular cloud, extraction algorithm


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Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

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Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

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We present observations of total cloud cover and cloud type classification results from a sky camera network comprising four stations in Switzerland. In a comprehensive intercomparison study, records of total cloud cover from the sky camera, long-wave radiation observations, Meteosat, ceilometer, and visual observations were compared. Total cloud cover from the sky camera was in 65–85% of cases within ±1 okta with respect to the other methods. The sky camera overestimates cloudiness with respect to the other automatic techniques on average by up to 1.1 ± 2.8 oktas but underestimates it by 0.8 ± 1.9 oktas compared to the human observer. However, the bias depends on the cloudiness and therefore needs to be considered when records from various observational techniques are being homogenized. Cloud type classification was conducted using the k-Nearest Neighbor classifier in combination with a set of color and textural features. In addition, a radiative feature was introduced which improved the discrimination by up to 10%. The performance of the algorithm mainly depends on the atmospheric conditions, site-specific characteristics, the randomness of the selected images, and possible visual misclassifications: The mean success rate was 80–90% when the image only contained a single cloud class but dropped to 50–70% if the test images were completely randomly selected and multiple cloud classes occurred in the images.

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The purpose of the work performed in this dissertation was to examine some of the possible regulatory mechanisms involved in the initiation of muscular atrophy during periods of decreased muscle utilization resulting from hindlimb immobilization in the rat. A 37% decrease in the rate of total muscle protein synthesis which has been observed to occur in the first 6 h of immobilization contributes significantly to the observed loss of protein during immobilization.^ The rates of cytochrome c and actin synthesis were determined in adult rat red vastus lateralis and gastrocnemius muscles, respectively, by the constant infusion and incorporation of ('3)H-tyrosine into protein. The fractional synthesis rates of both actin and cytochrome c were significantly decreased (P < 0.05) in the 6th h of hindlimb immobilization.^ RHA was extracted from adult rat gastrocnemius muscle by modification of the phenol: chloroform: SDS extraction procedures commonly used for preparation of RNA for hybridization analysis from other mammalian tissues. RNA content of rat gastrocnemius muscle, as determined by this method of extraction and its subsequent quantification by UV absorbance and orcinol assay, was significantly greater than the RNA content previously determined for adult rat gastrocnemius by other commonly employed methods.^ RNA extracted by this method from gastrocnemius muscles of control and 6h immobilized rats was subjected to "dot blot" hybridization to ('32)P-labelled probe from plasmid p749, containing a cDNA sequence complementary to (alpha)-actin mRNA and from rat skeletal muscle. (alpha)-Actin specific mRNA content as estimated by this procedure is not significantly decreased in rat gastrocnemius following 6h or hindlimb immobilization. However, (alpha)-actin specific mRNA content is significantly decreased (P < 0.05) in adult rat gastrocnemius (alpha)-actin specific mRNA is not decreased in adult rat gastrocnemius muscle following 6h of immobilization, a time when actin synthesis is significantly decreased, it is concluded that a change in (alpha)-actin specific mRNA content is not the initiating event responsible for the early decrease in actin synthesis observed in the 6th h of immobilization. ^

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The histology of healing in a tooth extraction socket has been described in many studies. The focus of research in bone biology and healing is now centered on molecular events that regulate repair of injured tissue. Rapid progress in cellular and molecular biology has resulted in identification of many signaling molecules (growth factors and cytokines) associated with formation and repair of skeletal tissues. Some of these include members of the transforming growth factor-β superfamily (including the bone morphogenetic proteins), fibroblast growth factors, platelet derived growth factors and insulin like growth factors. ^ Healing of a tooth extraction socket is a complex process involving tissue repair and regeneration. It involves chemotaxis of appropriate cells into the wound, transformation of undifferentiated mesenchymal cells to osteoprogenitor cells, proliferation and differentiation of committed bone forming cells, extracellular matrix synthesis, mineralization of osteoid, maturation and remodeling of bone. Current data suggests that these cellular events are precisely controlled and regulated by specific signaling molecules. A plethora of cytokines; have been identified and studied in the past two decades. Some of these like transforming growth factor beta (TGF-β), vascular endothelial growth factor (VEGF), platelet derived growth factor (PDGF) and fibroblast growth factors (FGFs) are well conserved proteins involved in the initial response to injury and repair in soft and hard tissue. ^ The purpose of this study was to characterize the spatial and temporal localization of TGF-βl, VEGF, PDGF-A, FGF-2 and BMP-2, and secretory IgA in a tooth extraction socket model, and evaluate correlation of spatial and temporal changes of these growth factors to histological events. The results of this study showed positive correlation of histological events to spatial and temporal localization of TGF-β1, BMP-2, FGF-2, PDGF-A, and VEGF in a rabbit tooth extraction model. ^

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Dissolved organic matter (DOM) in the oceans constitutes a major carbon pool involved in global biogeochemical cycles. More than 96% of the marine DOM resists microbial degradation for thousands of years. The composition of this refractory DOM (RDOM) exhibits a molecular signature which is ubiquitously detected in the deep oceans. Surprisingly efficient microbial transformation of labile into RDOM was shown experimentally, implying that microorganisms produce far more RDOM than needed to sustain the global pool. By assessing the microbial formation and transformation of DOM in unprecedented molecular detail for 3 years, we show that most of the newly formed RDOM is molecularly different from deep sea RDOM. Only <0.4% of the net community production was channeled into RDOM molecularly undistinguishable from deep sea DOM. Our study provides novel experimentally derived molecular evidence and data for global models on the production, turnover and accumulation of marine DOM.

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Authigenic phosphatic laminites enclosed in phosphorite crusts from the shelf off Peru (10°01' S and 10°24' S) consist of carbonate fluorapatite layers, which contain abundant sulfide minerals including pyrite (FeS2) and sphalerite (ZnS). Low d34Spyrite values (average -28.8 per mill) agree with bacterial sulfate reduction and subsequent pyrite formation. Stable sulfur isotopic compositions of sulfate bound in carbonate fluorapatite are lower than that of sulfate from ambient sea water, suggesting bacterial reoxidation of sulfide by sulfide-oxidizing bacteria. The release of phosphorus and subsequent formation of the autochthonous phosphatic laminites are apparently caused by the activity of sulfate-reducing bacteria and associated sulfide-oxidizing bacteria. Following an extraction-phosphorite dissolution-extraction procedure, molecular fossils of sulfate-reducing bacteria (mono-O-alkyl glycerol ethers, di-O-alkyl glycerol ethers, as well as the short-chain branched fatty acids i/ai-C15:0, i/ai-C17:0 and 10MeC16:0) are found to be among the most abundant compounds. The fact that these molecular fossils of sulfate-reducing bacteria are distinctly more abundant after dissolution of the phosphatic laminite reveals that the lipids are tightly bound to the mineral lattice of carbonate fluorapatite. Moreover, compared with the autochthonous laminite, molecular fossils of sulfate-reducing bacteria are: (1) significantly less abundant and (2) not as tightly bound to the mineral lattice in the other, allochthonous facies of the Peruvian crusts consisting of phosphatic coated grains. These observations confirm the importance of sulfate-reducing bacteria in the formation of the phosphatic laminite. Model calculations highlight that organic matter degradation by sulfate-reducing bacteria has the potential to liberate sufficient phosphorus for phosphogenesis.

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Although sulfur is an essential element for marine primary production and critical for climate processes, little is known about the oceanic pool of non-volatile dissolved organic sulfur (DOS). We present a basin-scale distribution of solid phase extractable DOS in the East Atlantic Ocean and the Atlantic sector of the Southern Ocean. While molar DOS versus dissolved organic nitrogen (DON) ratios of 0.11 ± 0.024 in Atlantic surface water resembled phytoplankton stoichiometry (S/N ~ 0.08), increasing dissolved organic carbon (DOC) versus DOS ratios and decreasing methionine-S yield demonstrated selective DOS removal and active involvement in marine biogeochemical cycles. Based on stoichiometric estimates, the minimum global inventory of marine DOS is 6.7 Pg S, exceeding all other marine organic sulfur reservoirs by an order of magnitude.

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Pb17Li is today a reference breeder material in diverse fusion R&D programs worldwide. One of the main issues in these programs is the problem of liquid metals breeder blanket behavior. Structural material of the blanket should meet high requirements because of extreme operating conditions. Therefore the knowledge of eutectic properties like optimal composition, physical and thermodynamic behavior or diffusion coefficients of Tritium are extremely necessary for current designs. In particular, the knowledge of the function linking the tritium concentration dissolved in liquid materials with the tritium partial pressure at a liquid/gas interface in equilibrium, CT=f(PT), is of basic importance because it directly impacts all functional properties of a blanket determining: tritium inventory, tritium permeation rate and tritium extraction efficiency. Nowadays, understanding the structure and behavior of this compound is a real goal in fusion engineering and materials science. Simulations of liquids can provide much information to the community; not only supplementing experimental data, but providing new tests of theories and ideas, making specific predictions that require experimental tests, and ultimately helping to lead to the deeper understanding and better predictive behavior.

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We present and discuss an algorithm to identify and characterize the long icosahedral structures (staggered pentagonal nanowires with 1-5-1-5 atomic structure) that appear in Molecular Dynamics simulations of metallic nanowires of different species subjected to stretching. The use of this algorithm allows the identification of pentagonal rings forming the icosahedral structure as well as the determination of its number np , and the maximum length of the pentagonal nanowire Lpm. The algorithm is tested with some ideal structures to show its ability to discriminate between pentagonal rings and other ring structures. We applied the algorithm to Ni nanowires with temperatures ranging between 4K and 865K, stretched along the [111], [100] and [110] directions. We studied statistically the formation of pentagonal nanowires obtaining the distributions of length Lpm and number of rings np as function of the temperature. The Lpm distribution presents a peaked shape, with peaks located at fixed distances whose separation corresponds to the distance between two consecutive pentagonal rings.

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El objetivo de la presente tesis doctoral es el desarrollo e implementación de un sistema para mejorar la metodología de extracción de la información geométrica necesaria asociada a los procesos de documentación de entidades de interés patrimonial, a partir de la información proporcionada por el empleo de sensores láser, tanto aéreos como terrestres. Para ello, inicialmente se realiza una presentación y justificación de los antecedentes y la problemática en el registro de información geométrica para el patrimonio, detallando todos aquellos sistemas de registro y análisis de la información geométrica utilizados en la actualidad. Este análisis permitirá realizar la comparación con los sistemas de registro basados en técnicas láser, aportando sugerencias de utilización para cada caso concreto. Posteriormente, se detallan los sistemas de registro basados en técnicas láser, comenzando por los sensores aerotransportados y concluyendo con el análisis pormenorizado de los sensores terrestres, tanto en su aplicación en modo estático como móvil. Se exponen las características técnicas y funcionamiento de cada uno de ellos, así como los ámbitos de aplicación y productos generados. Se analizan las fuentes de error que determinan la precisión que puede alcanzar el sistema. Tras la exposición de las características de los sistemas LiDAR, se detallan los procesos a realizar con los datos extraídos para poder generar la información necesaria para los diferentes tipos de objetos analizados. En esta exposición, se hace hincapié en los posibles riesgos que pueden ocurrir en algunas fases delicadas y se analizarán los diferentes algoritmos de filtrado y clasificación de los puntos, fundamentales en el procesamiento de la información LiDAR. Seguidamente, se propone una alternativa para optimizar los modelos de procesamiento existentes, basándose en el desarrollo de algoritmos nuevos y herramientas informáticas que mejoran el rendimiento en la gestión de la información LiDAR. En la implementación, se han tenido en cuenta características y necesidades particulares de la documentación de entidades de interés patrimonial, así como los diferentes ámbitos de utilización del LiDAR, tanto aéreo como terrestre. El resultado es un organigrama de las tareas a realizar desde la nube de puntos LiDAR hasta el cálculo de los modelos digitales del terreno y de superficies. Para llevar a cabo esta propuesta, se han desarrollado hasta 19 algoritmos diferentes que comprenden implementaciones para el modelado en 2.5D y 3D, visualización, edición, filtrado y clasificación de datos LiDAR, incorporación de información de sensores pasivos y cálculo de mapas derivados, tanto raster como vectoriales, como pueden ser mapas de curvas de nivel y ortofotos. Finalmente, para dar validez y consistencia a los desarrollos propuestos, se han realizado ensayos en diferentes escenarios posibles en un proceso de documentación del patrimonio y que abarcan desde proyectos con sensores aerotransportados, proyectos con sensores terrestres estáticos a media y corta distancia, así como un proyecto con un sensor terrestre móvil. Estos ensayos han permitido definir los diferentes parámetros necesarios para el adecuado funcionamiento de los algoritmos propuestos. Asimismo, se han realizado pruebas objetivas expuestas por la ISPRS para la evaluación y comparación del funcionamiento de algoritmos de clasificación LiDAR. Estas pruebas han permitido extraer datos de rendimiento y efectividad del algoritmo de clasificación presentado, permitiendo su comparación con otros algoritmos de prestigio existentes. Los resultados obtenidos han constatado el funcionamiento satisfactorio de la herramienta. Esta tesis está enmarcada dentro del proyecto Consolider-Ingenio 2010: “Programa de investigación en tecnologías para la valoración y conservación del patrimonio cultural” (ref. CSD2007-00058) realizado por el Consejo Superior de Investigaciones Científicas y la Universidad Politécnica de Madrid. ABSTRACT: The goal of this thesis is the design, development and implementation of a system to improve the extraction of useful geometric information in Heritage documentation processes. This system is based on information provided by laser sensors, both aerial and terrestrial. Firstly, a presentation of recording geometric information for Heritage processes is done. Then, a justification of the background and problems is done too. Here, current systems for recording and analyzing the geometric information are studied. This analysis will perform the comparison with the laser system techniques, providing suggestions of use for each specific case. Next, recording systems based on laser techniques are detailed. This study starts with airborne sensors and ends with terrestrial ones, both in static and mobile application. The technical characteristics and operation of each of them are described, as well as the areas of application and generated products. Error sources are also analyzed in order to know the precision this technology can achieve. Following the presentation of the LiDAR system characteristics, the processes to generate the required information for different types of scanned objects are described; the emphasis is on the potential risks that some steps can produce. Moreover different filtering and classification algorithms are analyzed, because of their main role in LiDAR processing. Then, an alternative to optimize existing processing models is proposed. It is based on the development of new algorithms and tools that improve the performance in LiDAR data management. In this implementation, characteristics and needs of the documentation of Heritage entities have been taken into account. Besides, different areas of use of LiDAR are considered, both air and terrestrial. The result is a flowchart of tasks from the LiDAR point cloud to the calculation of digital terrain models and digital surface models. Up to 19 different algorithms have been developed to implement this proposal. These algorithms include implementations for 2.5D and 3D modeling, viewing, editing, filtering and classification of LiDAR data, incorporating information from passive sensors and calculation of derived maps, both raster and vector, such as contour maps and orthophotos. Finally, in order to validate and give consistency to the proposed developments, tests in different cases have been executed. These tests have been selected to cover different possible scenarios in the Heritage documentation process. They include from projects with airborne sensors, static terrestrial sensors (medium and short distances) to mobile terrestrial sensor projects. These tests have helped to define the different parameters necessary for the appropriate functioning of the proposed algorithms. Furthermore, proposed tests from ISPRS have been tested. These tests have allowed evaluating the LiDAR classification algorithm performance and comparing it to others. Therefore, they have made feasible to obtain performance data and effectiveness of the developed classification algorithm. The results have confirmed the reliability of the tool. This investigation is framed within Consolider-Ingenio 2010 project titled “Programa de investigación en tecnologías para la valoración y conservación del patrimonio cultural” (ref. CSD2007-00058) by Consejo Superior de Investigaciones Científicas and Universidad Politécnica de Madrid.

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In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

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In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

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Vector reconstruction of objects from an unstructured point cloud obtained with a LiDAR-based system (light detection and ranging) is one of the most promising methods to build three dimensional models of orchards. The cylinder fitting method for woody structure reconstruction of leafless trees from point clouds obtained with a mobile terrestrial laser scanner (MTLS) has been analysed. The advantage of this method is that it performs reconstruction in a single step. The most time consuming part of the algorithm is generation of the cylinder direction, which must be recalculated at the inclusion of each point in the cylinder. The tree skeleton is obtained at the same time as the cluster of cylinders is formed. The method does not guarantee a unique convergence and the reconstruction parameter values must be carefully chosen. A balanced processing of clusters has also been defined which has proven to be very efficient in terms of processing time by following the hierarchy of branches, predecessors and successors. The algorithm was applied to simulated MTLS of virtual orchard models and to MTLS data of real orchards. The constraints applied in the method have been reviewed to ensure better convergence and simpler use of parameters. The results obtained show a correct reconstruction of the woody structure of the trees and the algorithm runs in linear logarithmic time