930 resultados para remote CUDA


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CO2 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic CO2 into the atmosphere. CCS technologies are expected to account for the 20% of the CO2 reduction by 2050. Geophysical, ground deformation and geochemical monitoring have been carried out to detect potential leakage, and, in the event that this occurs, identify and quantify it. This monitoring needs to be developed prior, during and after the injection stage. For a correct interpretation and quantification of the leakage, it is essential to establish a pre-injection characterization (baseline) of the area affected by the CO2 storage at reservoir level as well as at shallow depth, surface and atmosphere, via soil gas measurements. Therefore, the methodological approach is important because it can affect the spatial and temporal variability of this flux and even jeopardize the total value of CO2 in a given area. In this sense, measurements of CO2 flux were done using portable infrared analyzers (i.e., accumulation chambers) adapted to monitoring the geological storage of CO2, and other measurements of trace gases, e.g. radon isotopes and remote sensing imagery were tested in the natural analogue of Campo de Calatrava (Ciudad Real, Spain) with the aim to apply in CO2 leakage detection; thus, observing a high correlation between CO2 and radon (r=0,858) and detecting some vegetation indices that may be successfully applied for the leakage detection.

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En el presente documento se hablará acerca del desarrollo de un proyecto para la mejora de un programa de análisis de señales; con ese fin, se hará uso de técnicas de optimización del software y de tecnologías de aceleración, mediante el aprovechamiento del paralelismo del programa. Además se hará un análisis de acerca del uso de dos tecnologías basadas en diferentes paradigmas de programación paralela; una mediante múltiples hilos con memoria compartida y la otra mediante el uso de GPUs como dispositivos de coprocesamiento. This paper will talk about the development of a Project to improve a program that does signals analysis; to that end, it will make use of software optimization techniques and acceleration technologies by exploiting parallelism in the program. In Addition will be done an analysis on the use of two technologies based on two different paradigms; one using multiple threads with shared memory and the other using GPU as co-processing devices.

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Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI and their interpretation as a drought index. During 2012 three locations (at Salamanca, Granada and Córdoba) were selected and a periodic pasture monitoring and botanic composition were achieved. Daily precipitation, temperature and monthly soil water content were measurement as well as fresh and dry pasture weight. At the same time, remote sensing images were capture by DEIMOS-1 and MODIS of the chosen places. DEIMOS-1 is based on the concept Microsat-100 from Surrey. It is conceived for obtaining Earth images with a good enough resolution to study the terrestrial vegetation cover (20x20 m), although with a great range of visual field (600 km) in order to obtain those images with high temporal resolution and at a reduced cost. By contranst, MODIS images present a much lower spatial resolution (500x500 m). The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Acknowledgements. This work was partially supported by ENESA under project P10 0220C-823. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. MTM2009-14621 and i-MATH No. CSD2006-00032 is greatly appreciated.

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This study was motivated by the need to improve densification of Global Horizontal Irradiance (GHI) observations, increasing the number of surface weather stations that observe it, using sensors with a sub-hour periodicity and examining the methods of spatial GHI estimation (by interpolation) with that periodicity in other locations. The aim of the present research project is to analyze the goodness of 15-minute GHI spatial estimations for five methods in the territory of Spain (three geo-statistical interpolation methods, one deterministic method and the HelioSat2 method, which is based on satellite images). The research concludes that, when the work area has adequate station density, the best method for estimating GHI every 15 min is Regression Kriging interpolation using GHI estimated from satellite images as one of the input variables. On the contrary, when station density is low, the best method is estimating GHI directly from satellite images. A comparison between the GHI observed by volunteer stations and the estimation model applied concludes that 67% of the volunteer stations analyzed present values within the margin of error (average of +-2 standard deviations).

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In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 1 m. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss future lines of research to improve their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters or the processing time that it takes to retrieve ocean wave measurements from the stereo videos, which are very large datasets that need to be processed efficiently to be of practical usage. Multiresolution and short-time approaches would improve efficiency and scalability of the techniques so that wave displacements are obtained in feasible times.

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Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

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The identification of malnourished children living under extreme poverty conditions in isolated areas is crucial to trigger urgent interventions like supplementary or therapeutic feeding. This work aims to strengthen the task of following-up malnourished maternal-child population in rural areas of developing countries like Nicaragua. The solution facilitates low-cost health nutritional remote monitoring to support rural communities at the point of care. Thus, the system allows medical staff to communicate with brigades, who transmit anthropometric measurements, such as weight and height of the children, from communities which are sited about 12 km. far away. A hybrid WiMAX/WiFi architecture was deployed to provide affordable communications between the isolated communities and the health center. Furthermore, a free PBX software and an open information system, installed at the health center, support WiFi based mobile communications and information management to support the care needs of maternal-child population at risk.

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The satellite remote sensing missions are essential for long-term research around the condition of the earth resources and environment. On the other hand, in recent years the application of microsatellites is of interest in many space programs for their less cost and response time. In microsatellite remote sensing missions there are tight interrelations between different requirements such as orbital altitude, revisit time, mission life and spatial resolution. Also, all of these requirements can affect the whole system level design characteristics. In this work, the remote sensing microsatellite sizing process is divided into three major design disciplines; a) orbit design, b) payload sizing and c) bus sizing. Finally, some specific design cases are investigated inside the design space for evaluating the effect of different design variables on the satellite total mass. Considering the results of the work, it is concluded that applying a systematic approach at the initial design phase of such projects provides a good insight to the not clearly seen interactions inside their highly extended design space

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C0 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic co2 into the atmosphere. CCS technologies are expected to account for the 20% of the C0 reduction by 2050.The results of this paper are referred to the OXYCFB300 Compostilla Project (European Energy Program for Recover). Since the detection and control of potential leakage from storage formation is mandatory in a project of capture and geological storage of C02 (CCS), geophysical , ground deformation and geochemical monitoring have been carried out to detect potentialleakage, and, in the event that this occurs, identify and quantify it. This monitoring needs to be developed prior, during and after the injection stage. For a correct interpretation and quantification of the leakage, it is essential to establish a pre-injection characterization (baseline)of the area affected by the C02 storage at reservoir level as well as at shallow depth, surface and atmosphere, via soil gas measurements.

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Ubiquitous computing (one person, many computers) is the third era in the history of computing. It follows the mainframe era (many people, one computer) and the PC era (one person, one computer). Ubiquitous computing empowers people to communicate with services by interacting with their surroundings. Most of these so called smart environments contain sensors sensing users’ actions and try to predict the users’ intentions and necessities based on sensor data. The main drawback of this approach is that the system might perform unexpected or unwanted actions, making the user feel out of control. In this master thesis we propose a different procedure based on Interactive Spaces: instead of predicting users’ intentions based on sensor data, the system reacts to users’ explicit predefined actions. To that end, we present REACHeS, a server platform which enables communication among services, resources and users located in the same environment. With REACHeS, a user controls services and resources by interacting with everyday life objects and using a mobile phone as a mediator between himself/herself, the system and the environment. REACHeS’ interfaces with a user are built upon NFC (Near Field Communication) technology. NFC tags are attached to objects in the environment. A tag stores commands that are sent to services when a user touches the tag with his/her NFC enabled device. The prototypes and usability tests presented in this thesis show the great potential of NFC to build such user interfaces.

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A spatial-color-based non-parametric background-foreground modeling strategy in a GPGPU by using CUDA is proposed. This strategy is suitable for augmented-reality applications, providing real-time high-quality results in a great variety of scenarios.

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This paper summarizes the experience and the lessons learned from the European project PERFORM (A sophisticated multi-parametric system FOR the continuous effective assessment and monitoring of motor status in Parkinson's disease and other neurodegenerative diseases). PERFORM is aimed to provide a telehealth system for the remote monitoring of Parkinson's disease patients (PD) at their homes. This paper explains the global experience with PERFORM. It summarizes the technical performance of the system and the feedback received from the patients in terms of usability and wearability.

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This paper summarizes the experience and the lessons learned from the European project PERFORM (A sophisticated multi-parametric system FOR the continuous effective assessment and monitoring of motor status in Parkinson s disease and other neurodegenerative diseases). PERFORM is aimed to provide a telehealth system for the remote monitoring of Parkinson s disease patients (PD) at their homes. This paper explains the global experience with PERFORM. It summarizes the technical performance of the system and the feedback received from the patients in terms of usability and wearability.

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The aim of this work is an approach using multisensor remote sensing techniques to recognize the potential remains and recreate the original landscape of three archaeological sites. We investigate the spectral characteristics of the reflectance parameter and emissivity in the pattern recognition of archaeological materials in several hyperspectral scenes of the prehispanic site in Palmar Sur (Costa Rica), the Jarama Valley site and the celtiberian city of Segeda in Spain. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of HyMAP, AHS, MASTER and ATM have been used. Several experiments on natural scenarios of Costa Rica and Spain of different complexity, have been designed. Spectral patterns and thermal anomalies have been calculated as evidences of buried remains and change detection. First results, land cover change analyses and their consequences in the digital heritage registration are discussed.

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The present study shows a first approach to the simulation of the remote handling oper- ation which takes into account the thermal and flexible behavior of the blanket segments and its implications on the remote handling equipment, in order to validate and improve its design.