930 resultados para Electronics in navigation.
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Low-frequency noise in an electrolyte-insulator- semiconductor (EIS) structure functionalized with multilayers of polyamidoamine (PAMAM) dendrimer and single-walled carbon nanotubes (SWNT) is studied. The noise spectral density exhibits 1/f(gamma) dependence with the power factor of gamma approximate to 0.8 and gamma = 0.8-1.8 for the bare and functionalized EIS sensor, respectively. The gate-voltage noise spectral density is practically independent of the pH value of the solution and increases with increasing gate voltage or gate-leakage current. It has been revealed that functionalization of an EIS structure with a PAMAM/SWNTs multilayer leads to an essential reduction of the 1/f noise. To interpret the noise behavior in bare and functionalized EIS devices, a gate-current noise model for capacitive EIS structures based on an equivalent flatband-voltage fluctuation concept has been developed.
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Spin polarization is a key characteristic in developing spintronic devices. Diluted magnetic heterostructures (DMH), where subsequent layers of conventional and diluted magnetic semiconductors (DMS) are alternate, are one of the possible ways to obtain it. Si being the basis of modern electronics, Si or other group-IV DMH can be used to build spintronic devices directly integrated with conventional ones. In this work we study the physical properties and the spin-polarization effects of p-type DMH based in group-IV semiconductors (Si, Ge, SiGe, and SiC), by performing self-consistent (k) over right arrow . (p) over right arrow calculations in the local spin density approximation. We show that high spin polarization can be maintained in these structures below certain values of the carrier concentrations. Full spin polarization is attained in the low carrier concentration regime for carrier concentrations in the DMS layer up to similar to 2.0 x 10(19) cm(-3) for Si and up to similar to 6.0 x 10(19) cm(-3) for SiC. Partial, but still important spin polarization can be achieved for all studied group-IV DMH, with the exception of Ge for carrier concentrations up to 6.0 x 10(19) cm(-3). The role played by the effective masses and the energy splitting of the spin-orbit split-off hole bands is also discussed throughout the paper.
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The work presented here demonstrates the feasibility of using the single-mode fibers of an optical Internet network to deliver visible light between separate laboratories as a way to perform remote spectroscopy in the visible for teaching purposes. The coupling of a broadband light source into the single-mode fiber (SMF) and the characterization of optical losses as a function of the wavelength are discussed. Sample spectra were measured with a portable spectrometer controlled by an acquisition program developed with the LabVIEW software that allows the data to be collected and analyzed.
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Surface roughness is an important geomorphological variable which has been used in the Earth and planetary sciences to infer material properties, current/past processes, and the time elapsed since formation. No single definition exists; however, within the context of geomorphometry, we use surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter`s behavior at different spatial scales and data-set resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenization of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography highlighted local features and did not detect regional relief. Standard deviation of elevation correctly identified breaks of slope and was good at detecting regional relief. Standard deviation of slope (SD(slope)) also correctly identified smooth sloping areas and breaks of slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks of slope, although not as strongly as SD(slope), and it is sensitive to noise and spurious data. In general, SD(slope) offered good performance at a variety of scales, while the simplicity of calculation is perhaps its single greatest benefit.
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Relevant results for (sub-)distribution functions related to parallel systems are discussed. The reverse hazard rate is defined using the product integral. Consequently, the restriction of absolute continuity for the involved distributions can be relaxed. The only restriction is that the sets of discontinuity points of the parallel distributions have to be disjointed. Nonparametric Bayesian estimators of all survival (sub-)distribution functions are derived. Dual to the series systems that use minimum life times as observations, the parallel systems record the maximum life times. Dirichlet multivariate processes forming a class of prior distributions are considered for the nonparametric Bayesian estimation of the component distribution functions, and the system reliability. For illustration, two striking numerical examples are presented.
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We describe the optical and electrical characterization of a poly(p-phenylenevinylene) derivative: poly(2-dodecanoylsulfanyl-p-phenylenevinylene) (12COS-PPV). The electrical characterization was carried out on devices with the FTO\PEDOT:PSS\12COS-PPV/Al structure. Positive charge carrier mobility mu(h) of similar to 1.0 x 10(-6) cm(2) V(-1) s(-1) and barrier height phi of similar to 0.1 eV for positive charge carrier injection at the PEDOT:PSS/12COS-PPV interface were obtained using a thermionic injection model. FTO\PEDOT:P55\12COS-PPV/Ca devices exhibited green-yellow electroluminescence with maximum emission at lambda = 540 nm.
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A class room full of electronics students are depicted hard at work. Note the rows of light bulbs in the ceiling. Black and white photograph.
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The advancement of GPS technology enables GPS devices not only to be used as orientation and navigation tools, but also to track travelled routes. GPS tracking data provides essential information for a broad range of urban planning applications such as transportation routing and planning, traffic management and environmental control. This paper describes on processing the data that was collected by tracking the cars of 316 volunteers over a seven-week period. The detailed information is extracted. The processed data is further connected to the underlying road network by means of maps. Geographical maps are applied to check how the car-movements match the road network. The maps capture the complexity of the car-movements in the urban area. The results show that 90% of the trips on the plane match the road network within a tolerance.
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Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.
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SOUZA, Rodrigo B. ; MEDEIROS, Adelardo A. D. ; NASCIMENTO, João Maria A. ; GOMES, Heitor P. ; MAITELLI, André L. A Proposal to the Supervision of Processes in an Industrial Environment with Heterogeneous Systems. In: INTERNATIONAL CONFERENCE OF THE IEEEOF THE INDUSTRUI ELECTRONICS SOCIETY,32., Paris, 2006, Paris. Anais... Paris: IECON, 2006
Resumo:
This work proposes a method to localize a simple humanoid robot, without embedded sensors, using images taken from an extern camera and image processing techniques. Once the robot is localized relative to the camera, supposing we know the position of the camera relative to the world, we can compute the position of the robot relative to the world. To make the camera move in the work space, we will use another mobile robot with wheels, which has a precise locating system, and will place the camera on it. Once the humanoid is localized in the work space, we can take the necessary actions to move it. Simultaneously, we will move the camera robot, so it will take good images of the humanoid. The mainly contributions of this work are: the idea of using another mobile robot to aid the navigation of a humanoid robot without and advanced embedded electronics; chosing of the intrinsic and extrinsic calibration methods appropriated to the task, especially in the real time part; and the collaborative algorithm of simultaneous navigation of the robots
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In the absence of the selective availability, which was turned off on May 1, 2000, the ionosphere can be the largest source of error in GPS positioning and navigation. Its effects on GPS observable cause a code delays and phase advances. The magnitude of this error is affected by the local time of the day, season, solar cycle, geographical location of the receiver and Earth's magnetic field. As it is well known, the ionosphere is the main drawback for high accuracy positioning, when using single frequency receivers, either for point positioning or relative positioning of medium and long baselines. The ionosphere effects were investigated in the determination of point positioning and relative positioning using single frequency data. A model represented by a Fourier series type was implemented and the parameters were estimated from data collected at the active stations of RBMC (Brazilian Network for Continuous Monitoring of GPS satellites). The data input were the pseudorange observables filtered by the carrier phase. Quality control was implemented in order to analyse the adjustment and to validate the significance of the estimated parameters. Experiments were carried out in the equatorial region, using data collected from dual frequency receivers. In order to validate the model, the estimated values were compared with ground truth. For point and relative positioning of baselines of approximately 100 km, the values of the discrepancies indicated an error reduction better than 80% and 50% respectively, compared to the processing without the ionospheric model. These results give an indication that more research has to be done in order to provide support to the L1 GPS users in the Equatorial region.
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Several positioning techniques have been developed to explore the GPS capability to provide precise coordinates in real time. However, a significant problem to all techniques is the ionosphere effect and the troposphere refraction. Recent researches in Brazil, at São Paulo State University (UNESP), have been trying to tackle these problems. In relation to the ionosphere effects it has been developed a model named Mod_Ion. Concerning tropospheric refraction, a model of Numerical Weather Prediction(NWP) has been used to compute the zenithal tropospheric delay (ZTD). These two models have been integrated with two positioning methods: DGPS (Differential GPS) and network RTK (Real Time Kinematic). These two positioning techniques are being investigated at São Paulo State University (UNESP), Brazil. The in-house DGPS software was already finalized and has provided very good results. The network RTK software is still under development. Therefore, only preliminary results from this method using the VRS (Virtual Reference Station) concept are presented.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)