The utility of flow sorting to identify chromosomes carrying a single copy transgene in wheat

Additional file 1: Figure S1. Flow karyotypes (histograms of fluorescence intensity) obtained after the analysis of DAPI-stained chromosomes isolated from three transgenic lines and cv. Chinese Spring of common wheat. Flow karyotypes of the transgenic lines are indistinguishable from each other, and slightly differ in profiles of the major composite peaks from those of Chinese Spring

Prospects of Youngle People on the Labour Market

Family and reproductive behaviour shapes the outline of Czech Republic. Regime changes after 1989 certainly influenced the whole society. Critical changes in demographic behaviour need to be viewed in context of economic, social and cumtural changes in society. The purpose of this thesis is to explore perspectives of young adults, with an emphasis on exploring links between demographic behavious and on job market between 1989 and 2015. Thus this thesis should provide an answer to a question on how signifikance of influence of e.g. parenthood on career paths of youg people. To achieve this target, we used mainly publicly available data provided by Czech Statistical Bureau, interchangeably with data from Eurostat and basic statistical analysis

Demographic analysis unemployment above 50 years in the period of 1999-2013

The subject of the bachelor thesis are unemployed persons in higher age groups. The objective is to analyse and describe the development on the labour market of unemployed persons older than 50 years, and simultaneously describe the development on the labour market of entire population of unemployed persons. Data are analysed through economic indicators in the period of 1999-2013 base on publicly available statistics from the Ministry of Labour and Social Affairs. The result of the analysis is the outcome that absolute number of unemployed persons is increasing, primarily in higher age group. Gender ratio among the unemployed has recorded development thanks to legislative changes, mainly in the group of people above 50 years. Gradual aligning of ratio between males and females has happened in the analysed period, in all age groups with the exception of persons above 60 year

Comparison of modern clustering algorithms for twodimensional data

Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is the main task of exploratory data mining and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics.The topic of this paper is modern methods of clustering. The paper describes the theory needed to understand the principle of clustering and descriptions of algorithms used with clustering, followed by a comparison of the chosen methods. Proceedings 28th European Conference on Modelling and Simulation © ECMS Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani (Editors)

Elliott waves classification via softcomputing

This article presents a comparative study of the classification of Elliott waves in the chart. Regarding the methods of classification, the paper deals with backpropagation neural networks. Forms of activation functions of neurons in the hidden and output layers have been proposed by analytical programming with the differential evolution. The adaptation of the proposed neural network was performed by a standard backpropagation rule and Levenberg- Marquardt adaptation from Neural Network Toolbox in the Wolfram Mathematica environment. In conclusion, all results of this experimental study were evaluated and compared with each other

Elliott waves classification by means of neural and pseudo neural networks

This article presents a comparative study of the classification of Elliott waves in data. Regarding the methods of classification, the paper deals with three approaches. The first one is a multilayer artificial neural network (ANN) with sigmoid activation function and backpropagation and Levenberg–Marquardt training algorithm. Second approach uses training algorithms of ANN but forms of activation functions of hidden nodes and nodes in output layers have been proposed by analytical programming with the differential evolution. The last approach offers results performed by synthesized pseudo neural networks where the symbolic regression is used for synthesis of a whole structure of the classifier, i.e., the relation between inputs and output(s) similar to ANN. In this case, meta-evolution version of analytic programming with differential evolution is used. In conclusion, all results of this experimental study were evaluated and compared mutually. © 2016, Springer-Verlag Berlin Heidelberg.University of Ostrava [SGS17/PrF/2015]; Grant Agency of the Czech Republic-GACR [P103/15/06700S]; Ministry of Education of the Czech Republic [MSMT-7778/2014]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089

Soft computing-based information security

This chapter deals with using soft computing methods in information security. It is engaged in two big areas: (1) information security and spam detection and (2) cryptography. The latter field is covered by a proposal of an artificial neural network application, which represents a way of further development in this area. Such a neural network can be practically used in the area of cryptography. It is a new approach, which presents a development of automatic neural networks design. The approach is based on evolutionary algorithms, which allow evolution of architecture and weights simultaneously. A spam filter is an automated tool to recognize spam so as to prevent its delivery. The chapter contains a survey of current and proposed spam filtering techniques with particular emphasis on how well they work. The primary focus is spam filtering in email, but the role of the spam filter is only one component of a large and complex information universe. The chapter also includes experimental demonstrations. © 2014 by IGI Global. All rights reserved

Soft Computing-Based Information Security

This chapter deals with using soft computing methods in information security. It is engaged in two big areas: (1) information security and spam detection and (2) cryptography. The latter field is covered by a proposal of an artificial neural network application, which represents a way of further development in this area. Such a neural network can be practically used in the area of cryptography. It is a new approach, which presents a development of automatic neural networks design. The approach is based on evolutionary algorithms, which allow evolution of architecture and weights simultaneously. A spam filter is an automated tool to recognize spam so as to prevent its delivery. The chapter contains a survey of current and proposed spam filtering techniques with particular emphasis on how well they work. The primary focus is spam filtering in email, but the role of the spam filter is only one component of a large and complex information universe. The chapter also includes experimental demonstrations.P(ED2.1.00/03.0089),