Journal of Applied Computer Science

Stały URI zbioruhttp://hdl.handle.net/11652/3824

Journal of Applied Computer Science publishes original papers concerned with theory and practice of computer science and innovative computer technology as well as their application in engineering, biomedicine, ecology, socioeconomics and education.

Przeglądaj

Filtry

2017 - 20203

Ustawienia

Autorsearch.filters.applied.operator.equals: search.filters.author.Lipiński, Piotr

Wyniki wyszukiwania

Teraz wyświetlane 1 - 3 z 3
  • Pozycja
    Error Reduction for Static Localization
    (Wydawnictwo Politechniki Łódzkiej, 2020) Morawska, Barbara; Lichy, Krzysztof; Koch, Piotr; Niedźwiedzki, Jakub; Leplawy, Marcin; Lipiński, Piotr
    This article describes methods for reducing the position measure-ment error of ultra-wideband localization system - DecaWave TREK1000. The static localization accuracy of this system can achieve 10cm. The local-ization algorithm introduced in this paper can improve it up to 1 centimeter. We could achieve such good accuracy, thanks to experiments that were car-ried out in various environmental conditions. This allowed us to identify the nature of the measurement error and design the correct set of filters.
  • Pozycja
    The Use of Heuristic Algorithms: A Case Study of a Card Game
    (Wydawnictwo Politechniki Łódzkiej, 2018) Lichy, Krzysztof; Mazur, Marcin; Stolarek, Jan; Lipiński, Piotr
    In this paper we introduce the results of an experiment consisting in the creation of artificial intelligence using the heuristic algorithm Monte Carlo Tree Search and evaluation of its effectiveness in the card game Thousand.
  • Pozycja
    Generalized Structure of the Algorithm for Automated Detection of Non Relevant and Wrong Information on Web Resources
    (Wydawnictwo Politechniki Łódzkiej, 2017) Dyvak, Mykola; Kovbasistyi, Andrii; Stakhiv, Petro; Lipiński, Piotr
    In this article the algorithm for automated detection of non-relevant or wrong information on websites is introduced. The algorithm extracts the semantic information from the webpage using third party software and compares the semantic information with the reliable resources. Reliable information is identified by the means of majority voting or extracted from reliable databases.