Robert Kudelić

Monte-Carlo randomized algorithm: Empirical analysis on real-world information systems

New national and regional bryophyte records, 31 L T Ellis, A Alegro, H Bednarek-Ochyra, R Ochyra, A Bergamini, A Cogoni, P Erzberger, P Górski, N Gremmen, H Hespanhol, C Vieira, L E Kurbatova, M Lebouvier, A Martinčič, A K Asthana, R Gupta, V Nath, R Natcheva, A Ganeva, T Özdemir, N Batan, V Plášek, R D Porley, M Randić, J Sawicki, W Schroder, C Sérgio, V R Smith, P Sollman, S Ştefănuţ, C R Stevenson, G M Suárez, B Surina, G Uyar, Z Modrič Surina The Natural History Museum, UK, University of Zagreb, Croatia, Polish Academy of Sciences, Poland, Swiss Federal Research Institute WSL, Switzerland, Università degli Studi di Cagliari, Italy, Berlin, Germany, Poznań University of Life Sciences, Poland, Diever, The Netherlands, Universidade do Porto, Portugal, Russian Academy of Sciences, Russia, Université de Rennes 1, France, 12 Ljubljana, Slovenia, CSIR-National Botanical Research Institute, India, Bulgarian Academy of Sciences, Bulgaria, Karadeniz Technical University, Turkey, University of Ostrava, Czech Republic, Cerca dos Pomares, Portugal, Public Institution, Croatia, University of Warmia and Mazury in Olsztyn, Poland, Ludwigsstadt, Germany, Universidade de Lisboa, Portugal, University of Stellenbosch, South Africa, St Anna Parochie, The Netherlands, Institute of Biology Bucharest of Romanian Academy, Romania, Norfolk, UK, Facultad de Ciencias Naturales, Argentina, University of Primorska, Slovenia, Zonguldak Karaelmas University, Turkey, Natural History Museum Rijeka, CroatiaDetermination of development priority of information system subsystems is a problem that warrants resolution during information system development. It has been proven, previously, that this problem of information system development order is in fact NP-complete, NP-hard, and APX-hard. To solve this problem on a general case we have previously developed Monte-Carlo randomized algorithm, calculated complexity of this algorithm, and so on. After previous research we were able to come into possession of digraphs that represent real-world information systems. Therefore, in this paper we will empirically analyze Monte-Carlo algorithm to determine how the algorithm works on real-world examples. Also, we will critically review the results and give some possible areas of future research as well.

Monte-Carlo randomized algorithm for minimal feedback arc set problem

Graphical abstractDisplay Omitted HighlightsTo solve the problem of Information System Subsystem Development Order we are proposing a solution which takes sum of weights of feedback arcs as a criteria for determining development order rather than some other criteria which has not come directly from information system description.We have proven that this problem is NP-hard, NP-complete and APX-hard.For the purpose of solving this problem efficiently we have developed, analyzed and tested Monte Carlo randomized algorithm. When we are developing information system we must, in some way, determine the development order of its subsystems. Currently, this problem is not formally solved. Therefore, to rectify this we are proposing a solution which takes the sum of weights of feedback arcs as a criteria for determining the development order, rather than some other criteria that has not come directly from information system description. For the purpose of solving this problem we have developed, analyzed, and tested, Branch and Bound algorithm and Monte-Carlo randomized algorithm which solves the problem of Information System Subsystems Development Order in polynomial time with arbitrary probability. Also, we have determined an approximation error for developed Monte-Carlo randomized algorithm. Lastly, we have proven that the problem of Information System Subsystems Development Order is NP-hard, NP-complete, and APX-hard.

GUIDL IA: An intelligent assistant for aiding visually impaired in using GUIDL

GUIDL (Graphical User Interface Description Language) system has been proposed as an effective aiding technology that enables inclusion of visually impaired computer users into activities of graphical user interface design. GUIDL system implements many aiding concepts that make creation of graphical user interfaces suitable for visually impaired. In order to make GUIDL system even more accessible to visually impaired a GUIDL IA (Intelligent Assistant) is proposed as a mean of providing a more suitable and simpler way of getting help about various parts of GUIDL system. GUIDL IA enables visually impaired to ask questions in the form of natural language compared to browsing through instruction manual which makes getting the right information easier and quicker. GUIDL IA also enables visually impaired to hear the answer through integrated text-to-speech synthesizer that enables more natural pronunciation of given answers. In this paper GUIDL IA is presented and discussed along with the results about its effectives.

Mind map generator software

In our previous research we have made literature analysis and discovered possible mind map application areas. We have pointed out why currently developed software and methods are not adequate and why we are developing a new one. We have defined system architecture and functionality that our software would have. After that, we proceeded with text-mining algorithm development and testing after which we have concluded with our plans for further research. In this paper we will give basic notions about previously published article and present our custom developed software for automatic mind map generation. This software will be tested. Generated mind maps will be critically analyzed. The paper will be concluded with research summary and possible further research and software improvement.

More general minimum feedback arc set: Statistically defining information system digraph

When information system is being designed we have to determine, in some way, a sequence/priority of development of its subsystems. There are many algorithms that can be immediately applied or modified to solve previously mentioned problem. Nevertheless, they have all been tested on randomly generated graphs which in certain cases may or may not represent real information systems that can be found in practical situations. Therefore, in this paper we have statistically defined general digraph that represents real-world information systems. This definition can potentially lead to finding better algorithms for automatic or semiautomatic development and design of information systems.