1000 resultados para remote CUDA


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Recent advances in telecommunications technologies have transformed the modes of learning and teaching. One potentially vital component in the equation will be Remote Education or Remote Learning, the ability to compress time and space between teachers and students through the judicious application of technology. The purpose of this thesis is to develop a Remote Learning and Laboratory Center over the Internet and ISDN, which provide education and access to resources to those living in remote areas, children in hospitals and traveling families, with audio, video and data.^ Remote Learning and Laboratory Center (RLLC) is not restricted to merely traditional education processes such as universities or colleges, it can be very useful for companies to train their engineers, via networks. This capability will facilitate the best use of scarce, high quality educational resources and will bring equity of services to students as well as will be helpful to the Industries to train their engineers. The RLLC over the Internet and ISDN has been described in details and implemented successfully. For the Remote Laboratory, the experiment procedure has been demonstrated on reprogrammable CPLD design using ISR Kit. ^

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Tide propagation through coastal wetlands is a complex phenomenon affected by vegetation, channels, and tidal conditions. Generally, tidal flow is studied using stage (water level) observations, which provide good temporal resolution, but they are acquired in limited locations. Here, a remote-sensing technique, wetland InSAR (interferometric synthetic aperture radar), is used to detect tidal flow in vegetated coastal environments over broad spatial scales. The technique is applied to data sets acquired by three radar satellites over the western Everglades in south Florida. Interferometric analysis of the data shows that the greatest water-level changes occur along tidal channels, reflecting a high velocity gradient between fast horizontal flow in the channel and the slow flow propagation through the vegetation. The high-resolution observations indicate that the tidal flushing zone extends 2–3 km on both sides of tidal channels and can extend 3–4 km inland from the end of the channel. The InSAR observations can also serve as quantitative constraints for detailed coastal wetland flow models.

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Supervisory Control & Data Acquisition (SCADA) systems are used by many industries because of their ability to manage sensors and control external hardware. The problem with commercially available systems is that they are restricted to a local network of users that use proprietary software. There was no Internet development guide to give remote users out of the network, control and access to SCADA data and external hardware through simple user interfaces. To solve this problem a server/client paradigm was implemented to make SCADAs available via the Internet. Two methods were applied and studied: polling of a text file as a low-end technology solution and implementing a Transmission Control Protocol (TCP/IP) socket connection. Users were allowed to login to a website and control remotely a network of pumps and valves interfaced to a SCADA. This enabled them to sample the water quality of different reservoir wells. The results were based on real time performance, stability and ease of use of the remote interface and its programming. These indicated that the most feasible server to implement is the TCP/IP connection. For the user interface, Java applets and Active X controls provide the same real time access.

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This research analyzed the spatial relationship between a mega-scale fracture network and the occurrence of vegetation in an arid region. High-resolution aerial photographs of Arches National Park, Utah were used for digital image processing. Four sets of large-scale joints were digitized from the rectified color photograph in order to characterize the geospatial properties of the fracture network with the aid of a Geographic Information System. An unsupervised landcover classification was carried out to identify the spatial distribution of vegetation on the fractured outcrop. Results of this study confirm that the WNW-ESE alignment of vegetation is dominantly controlled by the spatial distribution of the systematic joint set, which in turn parallels the regional fold axis. This research provides insight into the spatial heterogeneity inherent to fracture networks, as well as the effects of jointing on the distribution of surface vegetation in desert environments.

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Use of remotely sensed data for environmental and ecological assessment has recently become more widespread in wetland research and management and advantages and limitations of this approach have been addresses (Ozesmi and Bauer 2002). Applications of remote sensing (RS) methods vary in spatial and temporal extent and resolution, in the types of data acquired, and in digital processing and pattern recognition algorithms used.

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In 2001, a weather and climate monitoring network was established along the temperature and aridity gradient between the sub-humid Moroccan High Atlas Mountains and the former end lake of the Middle Drâa in a pre-Saharan environment. The highest Automated Weather Stations (AWS) was installed just below the M'Goun summit at 3850 m, the lowest station Lac Iriki was at 450 m. This network of 13 AWS stations was funded and maintained by the German IMPETUS (BMBF Grant 01LW06001A, North Rhine-Westphalia Grant 313-21200200) project and since 2011 five stations were further maintained by the GERMAN DFG Fennec project (FI 786/3-1), this way some stations of the AWS network provided data for almost 12 years from 2001-2012. Standard meteorological variables such as temperature, humidity, and wind were measured at an altitude of 2 m above ground. Other meteorological variables comprise precipitation, station pressure, solar irradiance, soil temperature at different depths and for high mountain station snow water equivalent. The stations produced data summaries for 5-minute-precipitation-data, 10- or 15-minute-data and a daily summary of all other variables. This network is a unique resource of multi-year weather data in the remote semi-arid to arid mountain region of the Saharan flank of the Atlas Mountains. The network is described in Schulz et al. (2010) and its further continuation until 2012 is briefly discussed in Redl et al. (2015, doi:10.1175/MWR-D-15-0223.1) and Redl et al. (2016, doi:10.1002/2015JD024443).

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The northern Antarctic Peninsula is one of the fastest changing regions on Earth. The disintegration of the Larsen-A Ice Shelf in 1995 caused tributary glaciers to adjust by speeding up, surface lowering, and overall increased ice-mass discharge. In this study, we investigate the temporal variation of these changes at the Dinsmoor-Bombardier-Edgeworth glacier system by analyzing dense time series from various spaceborne and airborne Earth observation missions. Precollapse ice shelf conditions and subsequent adjustments through 2014 were covered. Our results show a response of the glacier system some months after the breakup, reaching maximum surface velocities at the glacier front of up to 8.8 m/d in 1999 and a subsequent decrease to ~1.5 m/d in 2014. Using a dense time series of interferometrically derived TanDEM-X digital elevation models and photogrammetric data, an exponential function was fitted for the decrease in surface elevation. Elevation changes in areas below 1000 m a.s.l. amounted to at least 130±15 m130±15 m between 1995 and 2014, with change rates of ~3.15 m/a between 2003 and 2008. Current change rates (2010-2014) are in the range of 1.7 m/a. Mass imbalances were computed with different scenarios of boundary conditions. The most plausible results amount to -40.7±3.9 Gt-40.7±3.9 Gt. The contribution to sea level rise was estimated to be 18.8±1.8 Gt18.8±1.8 Gt, corresponding to a 0.052±0.005 mm0.052±0.005 mm sea level equivalent, for the period 1995-2014. Our analysis and scenario considerations revealed that major uncertainties still exist due to insufficiently accurate ice-thickness information. The second largest uncertainty in the computations was the glacier surface mass balance, which is still poorly known. Our time series analysis facilitates an improved comparison with GRACE data and as input to modeling of glacio-isostatic uplift in this region. The study contributed to a better understanding of how glacier systems adjust to ice shelf disintegration.

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The marine ecosystem on the eastern shelf of the Antarctic Peninsula was surveyed 5 and 12 years after the climate-induced collapse of the Larsen A and B ice shelves. An impoverished benthic fauna was discovered, that included deep-sea species presumed to be remnants from ice-covered conditions. The current structure of various ecosystem components appears to result from extremely different response rates to the change from an oligotrophic sub-ice-shelf ecosystem to a productive shelf ecosystem. Meiobenthic communities remained impoverished only inside the embayments. On local scales, macro- and mega-epibenthic diversity was generally low, with pioneer species and typical Antarctic megabenthic shelf species interspersed. Antarctic Minke whales and seals utilised the Larsen A/B area to feed on presumably newly established krill and pelagic fish biomass. Ecosystem impacts also extended well beyond the zone of ice-shelf collapse, with areas of high benthic disturbance resulting from scour by icebergs discharged from the Larsen embayments.

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The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

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The research reported here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub [award reference: EP/G066051/1].

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Hoje em dia, a área de codificação de dados é transversal a diversos tipos de engenharias devido à sua grande importância. Com o aumento exponencial na criação de dados digitais, o campo da compressão de dados ganhou uma grande visibilidade nesta área. São constantemente desenvolvidos e melhorados algoritmos de compressão por forma a obter a maior compressão de dados possível seja com ou sem perda de dados, permitindo sustentar o rápido e constante crescimento dos mesmos. Um dos grandes problemas deste tipo de algoritmos deve-se ao grande poder computacional que por vezes é necessário para obter uma boa taxa de compressão mantendo a qualidade dos dados quando descompactados. Este documento descreve uma estratégia para tentar reduzir o impacto do poder computacional necessário à codificação de imagens utilizando uma implementação heterogénea. O objetivo é tentar efetuar a paralelização das secções que requerem elevado poder computacional reduzindo assim o tempo necessário à compressão de dados. Este documento baseia-se na implementação desta estratégia para o algoritmo de codificação de imagens MMP-Intra. Utilizando inicialmente uma análise teórica, demonstramos que é viável efetuar a paralelização do algoritmo, sendo possível obter elevados ganhos de desempenho. Por forma a provar que o algoritmo MMP-Intra era paralelizavel e identificar os ganhos reais foi desenvolvido um protótipo inicial, o qual obteve um desempenho muito inferiore ao do algoritmo original, necessitando de muito mais tempo para obter os mesmo resultados. Utilizando um processo de otimização iterativo o protótipo passou por várias etapas de refinação. O protótipo refinado final obteve resultados muito superiores ao algoritmo sequencial no qual o mesmo foi baseado chegando a obter desempenhos quatro vezes superior ao original.

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This study used Landsat 8 satellite imagery to identify environmental variables of households with malaria vector breeding sites in a malaria endemic rural district in Western Kenya. Understanding the influence of environmental variables on the distribution of malaria has been critical in the strengthening of malaria control programs. Using remote sensing and GIS technologies, this study performed a land classification, NDVI, Tasseled Cap Wetness Index, and derived land surface temperature values of the study area and examined the significance of each variable in predicting the probability of a household with a mosquito breeding site with and without larvae. The findings of this study revealed that households with any potential breeding sites were characterized by higher moisture, higher vegetation density (NDVI) and in urban areas or roads. The results of this study also confirmed that land surface temperature was significant in explaining the presence of active mosquito breeding sites (P< 0.000). The present study showed that freely available Landsat 8 imagery has limited use in deriving environmental characteristics of malaria vector habitats at the scale of the Bungoma East District in Western Kenya.

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Many studies have shown the considerable potential for the application of remote-sensing-based methods for deriving estimates of lake water quality. However, the reliable application of these methods across time and space is complicated by the diversity of lake types, sensor configuration, and the multitude of different algorithms proposed. This study tested one operational and 46 empirical algorithms sourced from the peer-reviewed literature that have individually shown potential for estimating lake water quality properties in the form of chlorophyll-a (algal biomass) and Secchi disc depth (SDD) (water transparency) in independent studies. Nearly half (19) of the algorithms were unsuitable for use with the remote-sensing data available for this study. The remaining 28 were assessed using the Terra/Aqua satellite archive to identify the best performing algorithms in terms of accuracy and transferability within the period 2001–2004 in four test lakes, namely Vänern, Vättern, Geneva, and Balaton. These lakes represent the broad continuum of large European lake types, varying in terms of eco-region (latitude/longitude and altitude), morphology, mixing regime, and trophic status. All algorithms were tested for each lake separately and combined to assess the degree of their applicability in ecologically different sites. None of the algorithms assessed in this study exhibited promise when all four lakes were combined into a single data set and most algorithms performed poorly even for specific lake types. A chlorophyll-a retrieval algorithm originally developed for eutrophic lakes showed the most promising results (R2 = 0.59) in oligotrophic lakes. Two SDD retrieval algorithms, one originally developed for turbid lakes and the other for lakes with various characteristics, exhibited promising results in relatively less turbid lakes (R2 = 0.62 and 0.76, respectively). The results presented here highlight the complexity associated with remotely sensed lake water quality estimates and the high degree of uncertainty due to various limitations, including the lake water optical properties and the choice of methods.