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    Wyświetlanie 1-4 z 4
    Tytuł:
    Cross modeling of embedded systems using SysML and Petri Nets
    Autorzy:
    Szmuc, Wojciech
    Szmuc, Tomasz
    Powiązania:
    https://bibliotekanauki.pl/articles/397841.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Łódzka. Wydział Mikroelektroniki i Informatyki
    Tematy:
    embedded systems
    cross modeling
    formal verification
    systemy wbudowane
    modelowanie krzyżowe
    formalna weryfikacja
    Opis:
    Cross modeling in embedded systems development is proposed in the paper. The main idea consists in a translation of SysML artifacts into the related Coloured Petri Net (CPN) models, which may be verified directly or using other tools, e.g. Temporal Logic Provers. The paper is an extension of [20] mainly by insertion of sequence diagrams (SysML) and presentation of their mapping into CPN models. The additional part describes communication features and completes the cross modeling approach.
    Źródło:
    International Journal of Microelectronics and Computer Science; 2018, 9, 2; 60-65
    2080-8755
    2353-9607
    Pojawia się w:
    International Journal of Microelectronics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Applications of rough sets in big data analysis: An overview
    Autorzy:
    Pięta, Piotr
    Szmuc, Tomasz
    Powiązania:
    https://bibliotekanauki.pl/articles/2055175.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    rough sets theory
    big data analysis
    deep learning
    data mining
    teoria zbiorów przybliżonych
    duży zbiór danych
    uczenie głębokie
    eksploracja danych
    Opis:
    Big data, artificial intelligence and the Internet of things (IoT) are still very popular areas in current research and industrial applications. Processing massive amounts of data generated by the IoT and stored in distributed space is not a straightforward task and may cause many problems. During the last few decades, scientists have proposed many interesting approaches to extract information and discover knowledge from data collected in database systems or other sources. We observe a permanent development of machine learning algorithms that support each phase of the data mining process, ensuring achievement of better results than before. Rough set theory (RST) delivers a formal insight into information, knowledge, data reduction, uncertainty, and missing values. This formalism, formulated in the 1980s and developed by several researches, can serve as a theoretical basis and practical background for dealing with ambiguities, data reduction, building ontologies, etc. Moreover, as a mature theory, it has evolved into numerous extensions and has been transformed through various incarnations, which have enriched expressiveness and applicability of the related tools. The main aim of this article is to present an overview of selected applications of RST in big data analysis and processing. Thousands of publications on rough sets have been contributed; therefore, we focus on papers published in the last few years. The applications of RST are considered from two main perspectives: direct use of the RST concepts and tools, and jointly with other approaches, i.e., fuzzy sets, probabilistic concepts, and deep learning. The latter hybrid idea seems to be very promising for developing new methods and related tools as well as extensions of the application area.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2021, 31, 4; 659--683
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A novel method for fast generation of 3D objects from multiple depth sensors
    Autorzy:
    Szmuc, Tomasz
    Mrówka, Rafał
    Brańka, Marek
    Ficoń, Jakub
    Pięta, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/2201328.pdf
    Data publikacji:
    2023
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    3D scan
    LiDAR
    point cloud
    mesh
    registration
    Opis:
    Scanning real 3D objects face many technical challenges. Stationary solutions allow for accurate scanning. However, they usually require special and expensive equipment. Competitive mobile solutions (handheld scanners, LiDARs on vehicles, etc.) do not allow for an accurate and fast mapping of the surface of the scanned object. The article proposes an end-to-end automated solution that enables the use of widely available mobile and stationary scanners. The related system generates a full 3D model of the object based on multiple depth sensors. For this purpose, the scanned object is marked with markers. Markers type and positions are automatically detected and mapped to a template mesh. The reference template is automatically selected for the scanned object, which is then transformed according to the data from the scanners with non-rigid transformation. The solution allows for the fast scanning of complex and varied size objects, constituting a set of training data for segmentation and classification systems of 3D scenes. The main advantage of the proposed solution is its efficiency, which enables real-time scanning and the ability to generate a mesh with a regular structure. It is critical for training data for machine learning algorithms. The source code is available at https://github.com/SATOffice/improved_scanner3D.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 2; 95--105
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Inulin as an effectiveness and safe ingredient in cosmetics
    Autorzy:
    Nizioł-Łukaszewska, Zofia
    Bujak, Tomasz
    Wasilewski, Tomasz
    Szmuc, Edyta
    Powiązania:
    https://bibliotekanauki.pl/articles/779488.pdf
    Data publikacji:
    2019
    Wydawca:
    Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
    Tematy:
    Inulin
    Jerusalem artichoke
    Helianthus tuberosus
    chicory
    Cichorium intybus
    Opis:
    Jerusalem artichoke (Helianthus tuberosus) and chicory (Cichorium intybus) are valuable pharmaceutical raw materials on account of their high content of inulin, a natural prebiotic. Inulin-rich plants are also increasingly employed in the formulation of cosmetic products. The paper presents the biological properties of aqueous and aqueous-ethanolic extracts of Jerusalem artichoke and chicory. The extracts have been found to have a high free radical scavenging ability, with the most beneficial antioxidant properties being observed for the aqueous-ethanolic extract of Jerusalem artichoke. Inulin isolated from both plant types is a safe and non-toxic raw material. Inulin added to model body wash gel formulations markedly reduces their potential to cause skin irritation and sensitization.
    Źródło:
    Polish Journal of Chemical Technology; 2019, 21, 1; 44-49
    1509-8117
    1899-4741
    Pojawia się w:
    Polish Journal of Chemical Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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