8 resultados para Non-Archimedean Real Closed Fields

em Universidad de Alicante


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We have measured experimental adsorption isotherms of water in zeolite LTA4A, and studied the regeneration process by performing subsequent adsorption cycles after degassing at different temperatures. We observed incomplete desorption at low temperatures, and cation rearrangement at successive adsorption cycles. We also developed a new molecular simulation force field able to reproduce experimental adsorption isotherms in the range of temperatures between 273 K and 374 K. Small deviations observed at high pressures are attributed to the change in the water dipole moment at high loadings. The force field correctly describes the preferential adsorption sites of water at different pressures. We tested the influence of the zeolite structure, framework flexibility, and cation mobility when considering adsorption and diffusion of water. Finally, we performed checks on force field transferability between different hydrophilic zeolite types, concluding that classical, non-polarizable water force fields are not transferable.

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Análisis del impuesto español sobre bienes inmuebles de no residentes.

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Comunicación presentada en EVACES 2011, 4th International Conference on Experimental Vibration Analysis for Civil Engineering Structures, Varenna (Lecco), Italy, October 3-5, 2011.

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Let T be a given subset of ℝ n , whose elements are called sites, and let s∈T. The Voronoi cell of s with respect to T consists of all points closer to s than to any other site. In many real applications, the position of some elements of T is uncertain due to either random external causes or to measurement errors. In this paper we analyze the effect on the Voronoi cell of small changes in s or in a given non-empty set P⊂T\{s}. Two types of perturbations of P are considered, one of them not increasing the cardinality of T. More in detail, the paper provides conditions for the corresponding Voronoi cell mappings to be closed, lower and upper semicontinuous. All the involved conditions are expressed in terms of the data.

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Extensive application of vinasse, a subproduct from sugar cane plantations for bioethanol production, is currently taking place as a source of nutrients that forms part of agricultural management in different agroclimatic regions. Liquid vinasse composition is characterised by high variability of organic compounds and major ions, acid pH (4.7), high TDS concentration (117,416–599,400 mg L− 1) and elevated EC (14,350–64,099 μS cm− 1). A large-scale sugar cane field application is taking place in Valle del Cauca (Colombia), where monitoring of soil, unsaturated zone and the aquifer underneath has been made since 2006 to evaluate possible impacts on three experimental plots. For this assessment, monitoring wells and piezometers were installed to determine groundwater flow and water samples were collected for chemical analysis. In the unsaturated zone, tensiometers were installed at different depths to determine flow patterns, while suction lysimeters were used for water sample chemical determinations. The findings show that in the sandy loam plot (Hacienda Real), the unsaturated zone is characterised by low water retention, showing a high transport capacity, while the other two plots of silty composition presented temporal saturation due to La Niña event (2010–2011). The strong La Niña effect on aquifer recharge which would dilute the infiltrated water during the monitoring period and, on the other hand dissolution of possible precipitated salts bringing them back into solution may occur. A slight increase in the concentration of major ions was observed in groundwater (~ 5% of TDS), which can be attributed to a combination of factors: vinasse dilution produced by water input and hydrochemical processes along with nutrient removal produced by sugar cane uptake. This fact may make the aquifer vulnerable to contamination.

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Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

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Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.

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In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.