The paper addresses the problem of the automatic distortion removal from images acquired with non-metric SLR camera equipped with prime lenses. From the photogrammetric point of view the following question arises: is the accuracy of distortion control data provided by the manufacturer for a certain lens model (not item) sufficient in order to achieve demanded accuracy? In order to obtain the reliable answer to the aforementioned problem the two kinds of tests were carried out for three lens models. Firstly the multi-variant camera calibration was conducted using the software providing full accuracy analysis. Secondly the accuracy analysis using check points took place. The check points were measured in the images resampled based on estimated distortion model or in distortion-free images simply acquired in the automatic distortion removal mode. The extensive conclusions regarding application of each calibration approach in practice are given. Finally the rules of applying automatic distortion removal in photogrammetric measurements are suggested

Both the growing number of dispersed generation plants and storage systems

and the new roles and functions on the demand side (e.g. demand side management) are

making the operation (monitoring and control) of electrical grids more complex, especially

in distribution. This paper demonstrates how to integrate phasor measurements so that

state estimation in a distribution grid profits optimally from the high accuracy of PMUs.

Different measurement configurations consisting of conventional and synchronous mea-

surement units, each with different fault tolerances for the quality of the calculated system

state achieved, are analyzed and compared. Weighted least squares (WLS) algorithms for

conventional, linear and hybrid state estimation provide the mathematical method used in

this paper. A case study of an 18-bus test grid with real measured PMU data from a 110 kV

distribution grid demonstrates the improving of the system’s state variable’s quality by

using synchrophasors. The increased requirements, which are the prerequisite for the use

of PMUs in the distribution grid, are identified by extensively analyzing the inaccuracy of

measurement and subsequently employed to weight the measured quantities.

Driver assistance systems have started becoming a key differentiator in automotive space and all major automotive manufacturers have such systems with various capabilities and stages of implementation. The main building blocks of such systems are similar in nature and one of the major building blocks is road lane detection. Even though lane detection technology has been around for decades, it is still an ongoing area of research and there are still several improvements and optimizations that are possible. This paper offers an Optimized Dynamic Origin Technique (Optimized DOT) for lane detection. The proposed optimization algorithm of optimized DOT gives better results in performance and accuracy compared to other methods of lane detection. Analysis of proposed optimized DOT with various edge detection techniques, various threshold levels, various sample dataset and various lane detection methods were done and the results are discussed in this paper. The proposed optimized DOT lane detection average processing time increases by 9.21 % when compared to previous Dynamic Origin Technique (DOT) and 59.09 % compared to traditional hough transform.