This work addresses the problem of detecting devices which are stealthily attached to the computer for logging keystrokes from keyboards. These devices are known as hardware keyloggers (HKL). When an HKL is attached to the keyboard, certain electrical characteristics of the keyboard signal are altered. Based on these characteristics (features), differences have been identified in an accurate assertion was made about the presence of HKL. The characteristics from which the differences were obtained were used to make distributions and compared with distance-measuring methods. An experiment was done to collect data from a number of keyboards and form two distributions (training and test) to perform the comparison. It was possible to detect the presence of HKL in the keyboard with a minimum of 4 to 100 keystrokes. For justifying the stability of the features, the temperature of the surroundings was obtained and the dependence of the features on temperature was obtained. Also, an experiment was done to see whether the keyboards were uniquely affected by the HKLs. This was done without using any training data, i.e., the distribution of features which was used did not come from a known state of the system (either with HKL or not with HKL).

This work is focused on detection of loss in nerve fibre layer on colour pictures of retina, witch are makes by fundus camera. It describe every simple objects of retina, optic nerve head, macula lutea and vascular bed. It detect optic nerve head and his near area, witch is general for detection of breakdownds. It use several metodes of picture adjusting for picture elaboration and objects detection (segmentation, thresholding, enhancement, hough transformation ). The detection of loss in nerve fibre layer is based on comparing of statistic parameters ( average, standart deviation, skewness coefficient and kurtosis coefficient histogram, entropy ) in choosed areas with and withou destruction of nerve layers. Vascular bed have badwatsh on results, cause of this we using hand choosing of essay.

According to a 1999 Federal Highway Administration statistic, the U.S. has around 8.2 million lane-miles of roadways that need to be maintained and rehabilitated periodically. Therefore, in order to reduce rehabilitation costs, pavement engineers need to optimize the rehabilitation procedure, which is achieved by accurately knowing the existing pavement layer thicknesses and localization of subsurface defects. Currently, the majority of departments of transportation (DOTs) rely on coring as a means to estimate pavement thicknesses, instead of using other nondestructive techniques, such as Ground Penetrating Radar (GPR). The use of GPR as a nondestructive pavement assessment tool is limited mainly due to the difficulty of GPR data interpretation, which requires experienced operators. Therefore, GPR results are usually subjective and inaccurate. Moreover, GPR data interpretation is very time-consuming because of the huge amount of data collected during a survey and the lack of reliable GPR data-interpretation software. This research effort attempts to overcome these problems by developing new GPR data analysis techniques that allow thickness estimation and subsurface defect detection from GPR data without operator intervention. The data analysis techniques are based on an accurate modeling of the propagation of the GPR electromagnetic waves through the pavement dielectric materials while traveling from the GPR transmitter to the receiver. Image-processing techniques are also applied to detect layer boundaries and subsurface defects. The developed data analysis techniques were validated utilizing data collected from an experimental pavement system: the Virginia Smart Road. The layer thickness error achieved by the developed system was around 3%. The conditions needed to achieve reliable and accurate results from GPR testing were also established. / Ph. D.

This thesis is deals with the nerve fibre layer in the colour ophthalmology images of retina. The thesis describes how can we use finding of nerve fibre layer and how was it solved in the past. In the thesis are proposed the methods that are based on processing and scoring frequency spectrums of individual sample of retina. At first here are described the methods of detection on the artificial generated samples that just simulate the nerve fibre layer. Then the thesis concentrates on processing of real images of retina. Because of the bloodstream, that depreciates processing at real images, are all surveyed samples are chosen manually. Except detection the nerve fibre layer itself, the thesis also deals with determination of direction their dissemination.