Jaroslav Marek

How the design of an experiment influences the nonsensitiveness regions in models with variance components

Nonsensitiveness regions for estimators of linear functions, for confidence ellipsoids, for the level of a test of a linear hypothesis on parameters and for the value of the power function are investigated in a linear model with variance components.The influence of the design of an experiment on the nonsensitiveness regions mentioned is numerically demonstrated and discussed on an example.

Analysis of wind speed and power time series preceding wind ramp events

Wind energy has become one of the fastest growing renewable sources during last few decades. Sudden changes in wind power output, called wind ramps, recently attracted great research interest in wind power forecasting community. Conventional ramp prediction methods derive future ramp estimates from power forecast series. We suggest to analyze real wind power series or other weather parameters, searching for specific patterns and dependencies indicating forthcoming wind ramp events.This paper presents a methodology for parametric analysis of time series preceding wind ramp events. The presented methodology is based on probabilistic data analysis. Sensitivity of the developed algorithm can be adjusted through the size of the time window defined before a ramp event. Power production and other weather data are standardized, averaged and then searched for specific patterns in the form of trend lines. The resulting methodology does not require the use of a numerical weather prediction (NWP) model; this is a significant simplification compared to most conventional methods. The proposed methodology is tested using power production and wind speed data collected between August 2011 and July 2012 at a wind farm located in a wind-rich region of southern Alberta, Canada.

Expectation-maximization algorithm for evaluation of wind direction characteristics

Directional statistical distributions can be used to model a wide range of industrial and phenomena. Finite mixtures of circular normal von Mises (MvM) distributions have been used to represent directional data from various domains including energy industry, medical science, and information retrieval. This paper presents the probabilisticmodeling of the prevailing wind directions. Expectation-maximization algorithm (EM algorithm) is employed to evaluate unknown parameters of MvM distribution. The evaluation is carried out using real-world data sets describing annual wind direction at St. Johns airport in Newfoundland, Canada. Experimental results show that EM algorithm is able to find good model parameters corresponding to input data. However, because the termination criterion χ2-function converges to 335, the resulting distribution cannot pass Pearsons test of goodness of fit.

Principal Component Analysis for Evaluation of Wind Ramp Event Probability

During last few decades wind energy has become one of the fastest growing renewable sources. Recent research interest in wind power forecasting community is focused on wind ramps, sudden changes in wind power output. Conventional ramp prediction methods derive future ramp estimates from power forecast series. We suggest to analyze real wind power series or other weather parameters searching for specific patterns and dependencies signalizing forthcoming wind ramp event. In this paper, principal component analysis of wind speed time series is presented. Analyzed power production and wind speed data were collected from August 2011 to July 2012 on sample wind farm located close to Let bridge, AB Canada. Sensitivity of analysis is defined by length of selected time frame. Frequency tables for first three principal components are used to evaluate conditional probability of forthcoming wind ramp event. Advantage of proposed methodology compared to conventional methods is that numerical weather prediction (NWP) model producing wind forecasts is not required.

Estimation of Angles Yaw, Pitch and Roll in a Special Transformation Problem

The aim of this contribution is to present a possible approach how to estimate the unknown parameters yaw, pitch and roll by regression models in transformation from the G-sensor coordinate system to the vehicle system. The unknown angles can be determine from acceleration vector measurement in coordinate system of sensor when vehicle is parked and when it is accelerating in a forward direction. Estimation of rotation matrix based on a long-time measurement looks like a simple task. But even small change of one acceleration component or one measurement that does not meet the prerequisites (acceleration only and only in a forward direction, plane ride) could mean significant shift in estimators of unknown angles. Nonlinear regression model and its linearization can help to improve uncertainty of estimated parameters. Feasible solution could be provided as well by utilization of some heuristic algorithms.

New Year’s Day Speeches of Czech Presidents: Phonetic Analysis and Text Analysis

The aim of our study is verification of programmed algorithms of phonetic analysis using concrete data, and reassurance that it works as also sought after. For our testing, the appropriate recordings of New Year’s Day speeches of Czech and Czechoslovak presidents are available. The very first available recording of presidential speech comes from 1935. All transcripts and recordings of the last 87 speeches are located on the web page www.rozhlas.cz. The primary goal of this paper is to analyze voice characteristics of the speaker (log energy, speech velocity and Zero crossing rate). Especially words “with greatest energy” will be found. There will be a list of words having the highest energy values. The most interesting results will be presented by graphical tools. Using a software, capable of text analysis, transcript characteristics such as most frequent words, length of words, total number of words and different words will be computed. The most frequent words will be presented. Political speeches often become the subject of various analyses. Our calculation allows a new perspective on speeches. It is interesting to compare the most frequent semantic words and words with the greatest energy. The results can be historically important. It allows an extraction of new information from available data and scientifically different approach.

Pioneering works in the application of random numbers to digital art and linear programs of Zdeněk Sýkora

The aim of the paper is to present the history of using random processes in art. A computer and algorithm can not work in isolation without a painter --- throughout the whole art process. At the beginning of the work is an ideological concept, idea or principle of creation. The painter gets a tool for creating works of art only by connecting computers with an idea. In this article principles of creation of selected digital paintings are described. Special attention is given to the Czech painter Zdeněk Sýkora. In detail the problem of construction of Sýkoras Lines is studied.

Software for determining the quality of an exam test

Theory of reliability and mathematical statistics provides us tools for monitoring the quality of a test. Using methodologies often covers estimation of validity, reliability and transparency. Of course quality tests depend on quality learning objectives and difficulty of questions. Such a study adds another dimension to perception of the causes of poor test results. Even though many authors warn about these criteria, these tools can provide useful information to the teacher. This paper presents the developed software for quality of test evaluation. The evaluation is carried out using real data sets describing test evaluation of the course Probability and Statistics at the Faculty of electrical engineering and informatics, University of Pardubice.

Fingers segmentation and its approximation

Aim of the paper is to find an algorithm for detecting fingers knuckle in the binary image with high precision and accuracy. At our disposal are measured coordinates of points on the finger, which are obtained from Microsoft Kinect. We form a suitable model for fingers characterization. It is based on the transformation of coordinates and regression models. A regression model gives a non-smooth function with change point. The main goal is to find the change point of the approximation function corresponding to the knuckle.

Transformation Problem with Different Accuracy of Measured Data

Abstract Let us have a group of points in 2D given by their coordinates in a system I. The points are located among other points with coordinates given in system II. The coordinates in the system I are much more accurate than the coordinates in the system II. The problem is to find the coordinates in the system II of the points of the given group however in such a way that the Euclidean distance between any two points are of the same accuracy as in the system I.