The article discusses text recognition techniques related to mobile technologies. Android application was developed for comparison of applying separate and joining of filtering methods. Three metrics based on classification of text were proposed and compared and the recognition time was analyzed.
Designing machine tools is an extremely complicated process, requiring thorough knowledge from the constructors in terms of statics, dynamics, contact mechanics, etc. Therefore, it is necessary to support this process by analyzing their models. However, only on the basis of experimentally identified models, reliable information about the object can be obtained. Presented paper contains numerical studies of the efficiency of optimization algorithms to identify parameters of FEM models. Numerical studies were carried out for the FEM model of the hybrid machine tool body structural component, consisting of steel and polymer concrete. In order to identify the parameters of the model, an interface was developed to enable data exchange between the FEM preprocessor of the Nastran FX and Matlab to cooperate. Numerical studies were then conducted using a developed identification algorithm based on accelerance functions, developed on the basis of reduced order FEM model and introduced correction parameters.
Information technology is one of the fastest developing business sector and research area. People use IT solutions based on computer science both for entertainment, education and work. Modern organizations cannot operate effectively without application of IT tools for data acquisition, storage, communication, visualization, but also for linking digital world with the real life or the real business processes. Works in the field of computer science are the foundation of fast and balanced development of IT sector. They are the accelerators of transformation from traditional, real economy into digital business and digital society. The main aim of the article is to explore what nations, people and works played the most significant role in development of information technology during the previous decades. Also what works are crucial today to ensure stability of present digital natives. The author analyzes the five prestigious awards in computer science to find out what works were honored for the past hundred years. In the first part of the article the characteristics of the explored awards is presented. The second part of the paper contains quantitative analysis of award recipients (n = 224) and prizes comparison. The performed literature review and the analysis of the awarded works allow to conclude that during the last decades the main drivers for IT development, noticed by awards committees were related both to the theory, hardware, software development and application areas. The vast majority of laureates came from (was born in) United States (62%), United Kingdom (8,5%) and Japan (4,9%). At the beginning of twenty first century huge amounts of data are generated not only by people but also autonomous objects, so the most crucial in computer science was to prepare systems and networks for secure processing (transferring) huge amounts of data in real time and find methods to assess the accuracy and quality of the information. Therefore, new awards like IEEE Internet Award were established to honor the works closely related to the development of the Internet and computer networks.
Groups of interacting agents are able to solve complex tasks in a dynamic environment. Robots in a group can have a simpler device than single stand-alone robots. Each agent in the group has the ability to accumulate interaction experience with the environment and share it with other members of the group. In many cases, the group behavior is not deduced from any properties of its parts. The paper proposes an approach to modeling the mobile agent group behavior that is busy with a common goal. The main purpose of the agents is to study the greatest territory at minimal time. The agents interact with the environment. A control of each agent is carried out by a modified neural network with restrictions imposed on it. Weights of the neural network are chosen by a genetic evolution method. The agents compete among themselves for obtaining the greatest reward from the environment. An efficiency of the proposed model is confirmed by some convergence speed tests by computer simulation. The proposed model can be applied to a group of robots that perform search tasks in a real physical space.
In this paper Mercer kernels with certain invariance properties are briefly introduced and an apparently not well-known construction using certain cohomology groups is described. As a consequence some kernels arising from this are given. Hence a kernel version of an iterative k-means algorithm due to Duda et al. is exhibited. It resembles the usual k-means algorithm but relies on a different update procedure and allows an elegant computation of the target function.
