870 resultados para Scale factor


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This paper reports a high-resolution frequency-output MEMS tilt sensor based on resonant sensing principles. The tilt sensor measures orientation by sensing the component of gravitational acceleration along a specified input axis. A combination of design enhancements enables significantly higher sensitivity for this device as compared to previously reported prototype sensors. The MEMS tilt sensor is calibrated on a manual tilt table over tilt angles ranging over 0-90 degrees with a relatively linear response measured in the range of ±20°(linearity error <2.3%) with a scale factor of approximately 50.06 Hz/degree. The noise-limited resolution of the sensor is found to be approximately 250 nano-radians for an integration time of 0.8 s, which is over an order of magnitude better than previously reported results [1]. © 2013 IEEE.

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A mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture of Gaussian classifier. The system was tested in recognizing various dynamic human outdoor activities; e.g., running, walking, roller blading, and cycling. Experiments with synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

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A combined 2D, 3D approach is presented that allows for robust tracking of moving people and recognition of actions. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object that are then used as input to action recognition modules. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture-of-Gaussians classifier. The system was tested in recognizing various dynamic human outdoor activities: running, walking, roller blading, and cycling. Experiments with real and synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

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A novel application-specific instruction set processor (ASIP) for use in the construction of modern signal processing systems is presented. This is a flexible device that can be used in the construction of array processor systems for the real-time implementation of functions such as singular-value decomposition (SVD) and QR decomposition (QRD), as well as other important matrix computations. It uses a coordinate rotation digital computer (CORDIC) module to perform arithmetic operations and several approaches are adopted to achieve high performance including pipelining of the micro-rotations, the use of parallel instructions and a dual-bus architecture. In addition, a novel method for scale factor correction is presented which only needs to be applied once at the end of the computation. This also reduces computation time and enhances performance. Methods are described which allow this processor to be used in reduced dimension (i.e., folded) array processor structures that allow tradeoffs between hardware and performance. The net result is a flexible matrix computational processing element (PE) whose functionality can be changed under program control for use in a wider range of scenarios than previous work. Details are presented of the results of a design study, which considers the application of this decomposition PE architecture in a combined SVD/QRD system and demonstrates that a combination of high performance and efficient silicon implementation are achievable. © 2005 IEEE.

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A novel most significant digit first CORDIC architecture is presented that is suitable for the VLSI design of systolic array processor cells for performing QR decomposition. This is based on an on-line CORDIC algorithm with a constant scale factor and a latency independent of the wordlength. This has been derived through the extension of previously published CORDIC algorithms. It is shown that simplifying the calculation of convergence bounds also greatly simplifies the derivation of suitable VLSI architectures. Design studies, based on a 0.35-µ CMOS standard cell process, indicate that 20 such QR processor cells operating at rates suitable for radar beamfoming can be readily accommodated on a single chip.

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An SVD processor system is presented in which each processing element is implemented using a simple CORDIC unit. The internal recursive loop within the CORDIC module is exploited, with pipelining being used to multiplex the two independent micro-rotations onto a single CORDIC processor. This leads to a high performance and efficient hardware architecture. In addition, a novel method for scale factor correction is presented which only need be applied once at the end of the computation. This also reduces the computation time. The net result is an SVD architecture based on a conventional CORDIC approach, which combines high performance with high silicon area efficiency.

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The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

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Financial integration has been pursued aggressively across the globe in the last fifty years; however, there is no conclusive evidence on the diversification gains (or losses) of such efforts. These gains (or losses) are related to the degree of comovements and synchronization among increasingly integrated global markets. We quantify the degree of comovements within the integrated Latin American market (MILA). We use dynamic correlation models to quantify comovements across securities as well as a direct integration measure. Our results show an increase in comovements when we look at the country indexes, however, the increase in the trend of correlation is previous to the institutional efforts to establish an integrated market in the region. On the other hand, when we look at sector indexes and an integration measure, we find a decreased in comovements among a representative sample of securities form the integrated market.

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As we move through the world, our eyes acquire a sequence of images. The information from this sequence is sufficient to determine the structure of a three-dimensional scene, up to a scale factor determined by the distance that the eyes have moved [1, 2]. Previous evidence shows that the human visual system accounts for the distance the observer has walked [3,4] and the separation of the eyes [5-8] when judging the scale, shape, and distance of objects. However, in an immersive virtual-reality environment, observers failed to notice when a scene expanded or contracted, despite having consistent information about scale from both distance walked and binocular vision. This failure led to large errors in judging the size of objects. The pattern of errors cannot be explained by assuming a visual reconstruction of the scene with an incorrect estimate of interocular separation or distance walked. Instead, it is consistent with a Bayesian model of cue integration in which the efficacy of motion and disparity cues is greater at near viewing distances. Our results imply that observers are more willing to adjust their estimate of interocular separation or distance walked than to accept that the scene has changed in size.

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The usefulness of any simulation of atmospheric tracers using low-resolution winds relies on both the dominance of large spatial scales in the strain and time dependence that results in a cascade in tracer scales. Here, a quantitative study on the accuracy of such tracer studies is made using the contour advection technique. It is shown that, although contour stretching rates are very insensitive to the spatial truncation of the wind field, the displacement errors in filament position are sensitive. A knowledge of displacement characteristics is essential if Lagrangian simulations are to be used for the inference of airmass origin. A quantitative lower estimate is obtained for the tracer scale factor (TSF): the ratio of the smallest resolved scale in the advecting wind field to the smallest “trustworthy” scale in the tracer field. For a baroclinic wave life cycle the TSF = 6.1 ± 0.3 while for the Northern Hemisphere wintertime lower stratosphere the TSF = 5.5 ± 0.5, when using the most stringent definition of the trustworthy scale. The similarity in the TSF for the two flows is striking and an explanation is discussed in terms of the activity of potential vorticity (PV) filaments. Uncertainty in contour initialization is investigated for the stratospheric case. The effect of smoothing initial contours is to introduce a spinup time, after which wind field truncation errors take over from initialization errors (2–3 days). It is also shown that false detail from the proliferation of finescale filaments limits the useful lifetime of such contour advection simulations to 3σ−1 days, where σ is the filament thinning rate, unless filaments narrower than the trustworthy scale are removed by contour surgery. In addition, PV analysis error and diabatic effects are so strong that only PV filaments wider than 50 km are at all believable, even for very high-resolution winds. The minimum wind field resolution required to accurately simulate filaments down to the erosion scale in the stratosphere (given an initial contour) is estimated and the implications for the modeling of atmospheric chemistry are briefly discussed.

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A new accelerating cosmology driven only by baryons plus cold dark matter (CDM) is proposed in the framework of general relativity. In this scenario the present accelerating stage of the Universe is powered by the negative pressure describing the gravitationally-induced particle production of cold dark matter particles. This kind of scenario has only one free parameter and the differential equation governing the evolution of the scale factor is exactly the same of the Lambda CDM model. For a spatially flat Universe, as predicted by inflation (Omega(dm) + Omega(baryon) = 1), it is found that the effectively observed matter density parameter is Omega(meff) = 1 - alpha, where alpha is the constant parameter specifying the CDM particle creation rate. The supernovae test based on the Union data (2008) requires alpha similar to 0.71 so that Omega(meff) similar to 0.29 as independently derived from weak gravitational lensing, the large scale structure and other complementary observations.

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In this thesis, a frequency selective surface (FSS) consists of a two-dimensional periodic structure mounted on a dielectric substrate, which is capable of selecting signals in one or more frequency bands of interest. In search of better performance, more compact dimensions, low cost manufacturing, among other characteristics, these periodic structures have been continually optimized over time. Due to its spectral characteristics, which are similar to band-stop or band-pass filters, the FSSs have been studied and used in several applications for more than four decades. The design of an FSS with a periodic structure composed by pre-fractal elements facilitates the tuning of these spatial filters and the adjustment of its electromagnetic parameters, enabling a compact design which generally has a stable frequency response and superior performance relative to its euclidean counterpart. The unique properties of geometric fractals have shown to be useful, mainly in the production of antennas and frequency selective surfaces, enabling innovative solutions and commercial applications in microwave range. In recent applications, the FSSs modify the indoor propagation environments (emerging concept called wireless building ). In this context, the use of pre-fractal elements has also shown promising results, allowing a more effective filtering of more than one frequency band with a single-layer structure. This thesis approaches the design of FSSs using pre-fractal elements based on Vicsek, Peano and teragons geometries, which act as band-stop spatial filters. The transmission properties of the periodic surfaces are analyzed to design compact and efficient devices with stable frequency responses, applicable to microwave frequency range and suitable for use in indoor communications. The results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as: fractal iteration number (or fractal level), scale factor, fractal dimension and periodicity of FSS, according the pre-fractal element applied on the surface. The analysis of the fractal dimension s influence on the resonant properties of a FSS is a new contribution in relation to researches about microwave devices that use fractal geometry. Due to its own characteristics and the geometric shape of the Peano pre-fractal elements, the reconfiguration possibility of these structures is also investigated and discussed. This thesis also approaches, the construction of efficient selective filters with new configurations of teragons pre-fractal patches, proposed to control the WLAN coverage in indoor environments by rejecting the signals in the bands of 2.4~2.5 GHz (IEEE 802.11 b) and 5.0~6.0 GHz (IEEE 802.11a). The FSSs are initially analyzed through simulations performed by commercial software s: Ansoft DesignerTM and HFSSTM. The fractal design methodology is validated by experimental characterization of the built prototypes, using alternatively, different measurement setups, with commercial horn antennas and microstrip monopoles fabricated for low cost measurements

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In this paper a methodology for automatic extraction of road segments from images with different resolutions (low, middle and high resolution) is presented. It is based on a generalized concept of lines in digital images, by which lines can be described by the centerlines of two parallel edges. In the specific case of low resolution images, where roads are manifested as entities of 1 or 2 pixels wide, the proposed methodology combines an automatic image enhancement operation with the following strategies: automatic selection of the hysteresis thresholds and the Gaussian scale factor; line length thresholding; and polygonization. In medium and high resolution images roads manifest as narrow and elongated ribbons and, consequently, the extraction goal becomes the road centerlines. In this case, it is not necessary to apply the previous enhancement step used to enhance roads in low resolution images. The results obtained in the experimental evaluation satisfied all criteria established for the efficient extraction of road segments from different resolution images, providing satisfactory results in a completely automatic way.

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In this work we obtain the cosmological solutions and investigate the thermodynamics of matter creation in two diferent contexts. In the first we propose a cosmological model with a time varying speed of light c. We consider two diferent time dependence of c for a at Friedmann-Robertson- Walker (FRW) universe. We write the energy conservation law arising from Einstein equations and study how particles are created as c decreases with cosmic epoch. The variation of c is coupled to a cosmological Λ term and both singular and non-singular solutions are possible. We calculate the "adiabatic" particle creation rate and the total number of particles as a function of time and find the constrains imposed by the second law of thermodynamics upon the models. In the second scenario, we study the nonlinearity of the electrodynamics as a source of matter creation in the cosmological models with at FRW geometry. We write the energy conservation law arising from Einstein field equations with cosmological term Λ, solve the field equations and study how particles are created as the magnetic field B changes with cosmic epoch. We obtain solutions for the adiabatic particle creation rate, the total number of particles and the scale factor as a function of time in three cases: Λ = 0, Λ = constant and Λ α H2 (cosmological term proportional to the Hubble parameter). In all cases, the second law of thermodynamics demands that the universe is not contracting (H ≥ 0). The first two solutions are non-singular and exhibit in ationary periods. The third case studied allows an always in ationary universe for a suficiently large cosmological term