In this paper, the comparative analysis of dynamic routing protocols EIGRP and OSPF is presented. The objective of analysis was to determine which routing protocol is converging faster. For testing, three approaches were used, namely simulation using OPNET simulator, emulation using GNS3 emulator and testing using real devices. Network topology that was used for testing purpose provide three possible paths between source and destination device. Generating large amount of echo request messages and observing echo reply message before and after link failure provide time needed to achieve convergence in network. Comparing the results obtained using real devices and simulator / emulator showed some shortcomings of OPNET and GNS. From the test results, it can be said that the dynamic routing protocol EIGRP is converging faster. This protocol is therefore more suitable for implementation in production infrastructures.

In this paper the elimination of image distortion and subsequent estimation of intrinsic camera parameters, while extracting the real object dimensions from photographs is presented. Research analysis includes description of the basic concepts related to the camera calibration. Following the analysis, the most suitable calibration method has been chosen and implemented as a software solution. The output of the research is the software application, which enables estimation of intrinsic camera parameters and subsequent elimination of image distortion. The most valuable is the extraction of dimensional units of the real object in the photographs.

Artificial neural networks (ANN) are one of the dominant learning techniques used in the field of artificial intelligence and have significant assets as their properties imitate the behavior of neurons in human brain. In this paper is presented the research focused on ANN, specifically Multilayer perceptron (MPL) with the aim of detection of human face in the still image. This system was implemented in the Java programming language and its utilizing the software framework called Neuroph, which is primary used precisely for neural networks. Evaluation part presents complex testing procedures and introduces possibilities to modify and set the individual parameters that enhance the overall detection process. Novelty of this research is in the use of ANN for several reasons, one of these being the utilizing of software framework, testing of the parameters and detailed description and evaluation on what influences the detection process. However the principal strength lies in the utilization of ANN for detection of faces rather than for a recognition. Utilization of Neuroph framework is an alternative to the systems that are focused on the detection of faces in still images and are commonly implemented in different programming languages.

Presented paper deals with the IP Flow Information Export (IPFIX) Mediation. The IPFIX Mediation was elaborated by IPFIX Working Group. This paper summarizes the design and implementation of the IPFIX Mediation framework into the SLAmeter monitoring tool. The analytical part is devoted to the IPFIX Mediation problem. The core part of the paper is represented by the design and description of the implementation workflow of IPFIX Mediation framework. The main contribution of this work is to extend the application domains of the SLAmeter monitoring tool.