887 resultados para Global Positioning System (gps)


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Synchronization of data coming from different sources is of high importance in biomechanics to ensure reliable analyses. This synchronization can either be performed through hardware to obtain perfect matching of data, or post-processed digitally. Hardware synchronization can be achieved using trigger cables connecting different devices in many situations; however, this is often impractical, and sometimes impossible in outdoors situations. The aim of this paper is to describe a wireless system for outdoor use, allowing synchronization of different types of - potentially embedded and moving - devices. In this system, each synchronization device is composed of: (i) a GPS receiver (used as time reference), (ii) a radio transmitter, and (iii) a microcontroller. These components are used to provide synchronized trigger signals at the desired frequency to the measurement device connected. The synchronization devices communicate wirelessly, are very lightweight, battery-operated and thus very easy to set up. They are adaptable to every measurement device equipped with either trigger input or recording channel. The accuracy of the system was validated using an oscilloscope. The mean synchronization error was found to be 0.39 μs and pulses are generated with an accuracy of <2 μs. The system provides synchronization accuracy about two orders of magnitude better than commonly used post-processing methods, and does not suffer from any drift in trigger generation.

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ACCURATE sensing of vehicle position and attitude is still a very challenging problem in many mobile robot applications. The mobile robot vehicle applications must have some means of estimating where they are and in which direction they are heading. Many existing indoor positioning systems are limited in workspace and robustness because they require clear lines-of-sight or do not provide absolute, driftfree measurements.The research work presented in this dissertation provides a new approach to position and attitude sensing system designed specifically to meet the challenges of operation in a realistic, cluttered indoor environment, such as that of an office building, hospital, industrial or warehouse. This is accomplished by an innovative assembly of infrared LED source that restricts the spreading of the light intensity distribution confined to a sheet of light and is encoded with localization and traffic information. This Digital Infrared Sheet of Light Beacon (DISLiB) developed for mobile robot is a high resolution absolute localization system which is simple, fast, accurate and robust, without much of computational burden or significant processing. Most of the available beacon's performance in corridors and narrow passages are not satisfactory, whereas the performance of DISLiB is very encouraging in such situations. This research overcomes most of the inherent limitations of existing systems.The work further examines the odometric localization errors caused by over count readings of an optical encoder based odometric system in a mobile robot due to wheel-slippage and terrain irregularities. A simple and efficient method is investigated and realized using an FPGA for reducing the errors. The detection and correction is based on redundant encoder measurements. The method suggested relies on the fact that the wheel slippage or terrain irregularities cause more count readings from the encoder than what corresponds to the actual distance travelled by the vehicle.The application of encoded Digital Infrared Sheet of Light Beacon (DISLiB) system can be extended to intelligent control of the public transportation system. The system is capable of receiving traffic status input through a GSM (Global System Mobile) modem. The vehicles have infrared receivers and processors capable of decoding the information, and generating the audio and video messages to assist the driver. The thesis further examines the usefulness of the technique to assist the movement of differently-able (blind) persons in indoor or outdoor premises of his residence.The work addressed in this thesis suggests a new way forward in the development of autonomous robotics and guidance systems. However, this work can be easily extended to many other challenging domains, as well.

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Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

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The impact of selected observing systems on the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA40) is explored by mimicking observational networks of the past. This is accomplished by systematically removing observations from the present observational data base used by ERA40. The observing systems considered are a surface-based system typical of the period prior to 1945/50, obtained by only retaining the surface observations, a terrestrial-based system typical of the period 1950-1979, obtained by removing all space-based observations, and finally a space-based system, obtained by removing all terrestrial observations except those for surface pressure. Experiments using these different observing systems have been limited to seasonal periods selected from the last 10 yr of ERA40. The results show that the surface-based system has severe limitations in reconstructing the atmospheric state of the upper troposphere and stratosphere. The terrestrial system has major limitations in generating the circulation of the Southern Hemisphere with considerable errors in the position and intensity of individual weather systems. The space-based system is able to analyse the larger-scale aspects of the global atmosphere almost as well as the present observing system but performs less well in analysing the smaller-scale aspects as represented by the vorticity field. Here, terrestrial data such as radiosondes and aircraft observations are of paramount importance. The terrestrial system in the form of a limited number of radiosondes in the tropics is also required to analyse the quasi-biennial oscillation phenomenon in a proper way. The results also show the dominance of the satellite observing system in the Southern Hemisphere. These results all indicate that care is required in using current reanalyses in climate studies due to the large inhomogeneity of the available observations, in particular in time.

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This paper reviews the impact of the global financial crisis on financial system reform in China. Scholars and practitioners have critically questioned the efficiencies of the Anglo- American principal-agent model of corporate governance which promotes shareholder-value maximisation. Should China continue to follow the U.K.-U.S. path in relation to financial reform? This conceptual paper provides an insightful review of the corporate governance literature, regulatory reports and news articles from the financial press. After examining the fundamental limitations of the laissez-faire philosophy that underpins the neo-liberal model of capitalism, the paper considers the risks in opening up China’s financial markets and relaxing monetary and fiscal policies. The paper outlines a critique of shareholder-capitalism in relation to the German team-production model of corporate governance, promoting a “social market economy” styled capitalism. Through such analysis, the paper explores numerous implications for China to consider in terms of developing a new and sustainable corporate governance model. China needs to follow its own financial reform through understanding its particular economy. The global financial crisis might help China rethink the nature of corporate governance, identify its weakness and assess the current reform agenda.

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Surface-based GPS measurements of zenith path delay (ZPD) can be used to derive vertically integrated water vapor (IWV) of the atmosphere. ZPD data are collected in a global network presently consisting of 160 stations as part of the International GPS Service. In the present study, ZPD data from this network are converted into IWV using observed surface pressure and mean atmospheric water vapor column temperature obtained from the European Centre for Medium-Range Weather Forecasts' (ECMWF) operational analyses (OA). For the 4 months of January/July 2000/2001, the GPS-derived IWV values are compared to the IWV from the ECMWF OA, with a special focus on the monthly averaged difference (bias) and the standard deviation of daily differences. This comparison shows that the GPS-derived IWV values are well suited for the validation of OA of IWV. For most GPS stations, the IWV data agree quite well with the analyzed data indicating that they are both correct at these locations. Larger differences for individual days are interpreted as errors in the analyses. A dry bias in the winter is found over central United States, Canada, and central Siberia, suggesting a systematic analysis error. Larger differences were mainly found in mountain areas. These were related to representation problems and interpolation difficulties between model height and station height. In addition, the IWV comparison can be used to identify errors or problems in the observations of ZPD. This includes errors in the data itself, e.g., erroneous outlier in the measured time series, as well as systematic errors that affect all IWV values at a specific station. Such stations were excluded from the intercomparison. Finally, long-term requirements for a GPS-based water vapor monitoring system are discussed.

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We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover, composition and 5 height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, 10 and are compared to scores based on the temporal or spatial mean value of the observations and a “random” model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), and the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global 15 vegetation models (DGVMs). SDBM reproduces observed CO2 seasonal cycles, but its simulation of independent measurements of net primary production (NPP) is too high. The two DGVMs show little difference for most benchmarks (including the interannual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified 20 several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change 25 impacts and feedbacks.

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A global river routing scheme coupled to the ECMWF land surface model is implemented and tested within the framework of the Global Soil Wetness Project II, to evaluate the feasibility of modelling global river runoff at a daily time scale. The exercise is designed to provide benchmark river runoff predictions needed to verify the land surface model. Ten years of daily runoff produced by the HTESSEL land surface scheme is input into the TRIP2 river routing scheme in order to generate daily river runoff. These are then compared to river runoff observations from the Global Runoff Data Centre (GRDC) in order to evaluate the potential and the limitations. A notable source of inaccuracy is bias between observed and modelled discharges which is not primarily due to the modelling system but instead of to the forcing and quality of observations and seems uncorrelated to the river catchment size. A global sensitivity analysis and Generalised Likelihood Uncertainty Estimation (GLUE) uncertainty analysis are applied to the global routing model. The ground water delay parameter is identified as being the most sensitive calibration parameter. Significant uncertainties are found in results, and those due to parameterisation of the routing model are quantified. The difficulty involved in parameterising global river discharge models is discussed. Detailed river runoff simulations are shown for the river Danube, which match well observed river runoff in upstream river transects. Results show that although there are errors in runoff predictions, model results are encouraging and certainly indicative of useful runoff predictions, particularly for the purpose of verifying the land surface scheme hydrologicly. Potential of this modelling system on future applications such as river runoff forecasting and climate impact studies is highlighted. Copyright © 2009 Royal Meteorological Society.

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We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover; composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). In general, the SDBM performs better than either of the DGVMs. It reproduces independent measurements of net primary production (NPP) but underestimates the amplitude of the observed CO2 seasonal cycle. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

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This paper introduces an ontology-based knowledge model for knowledge management. This model can facilitate knowledge discovery that provides users with insight for decision making. The users requiring the insight normally play different roles with different requirements in an organisation. To meet the requirements, insights are created by purposely aggregated transnational data. This involves a semantic data integration process. In this paper, we present a knowledge management system which is capable of representing knowledge requirements in a domain context and enabling the semantic data integration through ontology modeling. The knowledge domain context of United Bible Societies is used to illustrate the features of the knowledge management capabilities.

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This study examines the variability of the South America monsoon system (SAMS) over tropical South America (SA). The onset, end, and total rainfall during the summer monsoon are investigated using precipitation pentad estimates from the global precipitation climatology project (GPCP) 1979-2006. Likewise, the variability of SAMS characteristics is examined in ten Intergovernmental Panel on Climate Change (IPCC) global coupled climate models in the twentieth century (1981-2000) and in a future scenario of global change (A1B) (2081-2100). It is shown that most IPCC models misrepresent the intertropical convergence zone and therefore do not capture the actual annual cycle of precipitation over the Amazon and northwest SA. Most models can correctly represent the spatiotemporal variability of the annual cycle of precipitation in central and eastern Brazil such as the correct phase of dry and wet seasons, onset dates, duration of rainy season and total accumulated precipitation during the summer monsoon for the twentieth century runs. Nevertheless, poor representation of the total monsoonal precipitation over the Amazon and northeast Brazil is observed in a large majority of the models. Overall, MI-ROC3.2-hires, MIROC3.2-medres and MRI-CGCM3.2.3 show the most realistic representation of SAMS`s characteristics such as onset, duration, total monsoonal precipitation, and its interannual variability. On the other hand, ECHAM5, GFDL-CM2.0 and GFDL-CM2.1 have the least realistic representation of the same characteristics. For the A1B scenario the most coherent feature observed in the IPCC models is a reduction in precipitation over central-eastern Brazil during the summer monsoon, comparatively with the present climate. The IPCC models do not indicate statistically significant changes in SAMS onset and demise dates for the same scenario.