rd signs

rd signs

Scar formation in the inner ear followig acoustical injury: sequence of changes from early signs of damage to healed lesion

This paper is a review of a study to investigate the effects of excessive noise exposure to the organ of Corti using chinchillas.

Signs of l-doubling constants in NF3

Computed infrared band contours are presented for the two degenerate fundamentals of the NF3 molecule, using the l-resonance band contour program described by Cartwright and Mills, with values of the vibration-rotation constants determined from the microwave spectrum by Morino and co-workers. Computed contours are presented for both possible signs of the l-doubling constant, and comparison with the observed band contours leads to the conclusion that q3 = −121.4 MHz and q4 = +51.4 MHz.

Shubnikov de Haas oscillations in double wells with opposite signs of the electronic g-factor

We report on the measurements of the Shubnikov de Haas oscillations (SdH) in symmetrically doped AlxGa1-xAs double wells with different Al compositions in wells, which lead to the opposite signs of the electronic g-factor in each layer. Surprisingly, the spin splitting appears and collapses several times with increase in the magnetic field, We attribute such behaviour to the oscillations of the exchange-correlation term with Landau filling factor. (C) 2007 Elsevier B.V. All rights reserved.

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

A Contour-based Separation of VerticallyAttached Traffic Signs

This report presents an algorithm for locating the cut points for and separatingvertically attached traffic signs in Sweden. This algorithm provides severaladvanced digital image processing features: binary image which representsvisual object and its complex rectangle background with number one and zerorespectively, improved cross correlation which shows the similarity of 2Dobjects and filters traffic sign candidates, simplified shape decompositionwhich smoothes contour of visual object iteratively in order to reduce whitenoises, flipping point detection which locates black noises candidates, chasmfilling algorithm which eliminates black noises, determines the final cut pointsand separates originally attached traffic signs into individual ones. At each step,the mediate results as well as the efficiency in practice would be presented toshow the advantages and disadvantages of the developed algorithm. Thisreport concentrates on contour-based recognition of Swedish traffic signs. Thegeneral shapes cover upward triangle, downward triangle, circle, rectangle andoctagon. At last, a demonstration program would be presented to show howthe algorithm works in real-time environment.