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    Wyświetlanie 1-6 z 6
    Tytuł:
    Austempered Ductile Iron Manufacturing Data Acquisition Process with the Use of Semantic Techniques
    Autorzy:
    Wilk-Kołodziejczyk, D.
    Kluska-Nawarecka, A. S.
    Regulski, K.
    Adrian, W.
    Jaśkowiec, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/355169.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    austempered ductile iron
    thermal treatment
    properties
    process data
    data integration
    ontology
    Opis:
    The aim of this work was to propose a methodology supporting the task of collecting the comparative data on studies of the mechanical properties of ADI. Collecting of research data is an important step in the process of finding the optimum design solutions for newly made products - experimental data allow us properly calibrate the manufacturing process of ADI to let the final product achieve the required properties. Parameters of the ADI production process, i.e. the time and temperature of austenitising and austempering, as well as the alloying elements added to ductile iron affect the ADI properties. The design process can use research data collected, among others, from the Web. As stated in the article, the process of data acquisition can be supported by semantic technologies, including ontologies which are descriptive logic formalism.
    Źródło:
    Archives of Metallurgy and Materials; 2016, 61, 4; 2117-2122
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Formalization of Technological Knowledge in the Field of Metallurgy Using Document Classification Tools Supported with Semantic Techniques
    Autorzy:
    Regulski, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/353849.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    application of information technology to the foundry industry
    document classification
    semantic techniques
    knowledge formalization
    text mining
    Opis:
    The process of knowledge formalization is an essential part of decision support systems development. Creating a technological knowledge base in the field of metallurgy encountered problems in acquisition and codifying reusable computer artifacts based on text documents. The aim of the work was to adapt the algorithms for classification of documents and to develop a method of semantic integration of a created repository. Author used artificial intelligence tools: latent semantic indexing, rough sets, association rules learning and ontologies as a tool for integration. The developed methodology allowed for the creation of semantic knowledge base on the basis of documents in natural language in the field of metallurgy.
    Źródło:
    Archives of Metallurgy and Materials; 2017, 62, 2A; 715-720
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Semantic web techniques for clinical topic detection in health care
    Autorzy:
    Raman, R.
    Sahayaraj, Kishore Anthuvan
    Soni, Mukesh
    Nayak, Nihar Ranjan
    Govindarajan, Ramya
    Singh, Nikhil Kumar
    Powiązania:
    https://bibliotekanauki.pl/articles/38698068.pdf
    Data publikacji:
    2024
    Wydawca:
    Instytut Podstawowych Problemów Techniki PAN
    Tematy:
    clinical text
    frequent word set
    feature selection
    clustering
    topic detection
    time sequence
    semantics
    tekst kliniczny
    częsty zestaw słów
    wybór funkcji
    grupowanie
    wykrywanie tematu
    sekwencja czasu
    semantyka
    Opis:
    The scope of this paper is that it investigates and proposes a new clustering method thattakes into account the timing characteristics of frequently used feature words and thesemantic similarity of microblog short texts as well as designing and implementing mi-croblog topic detection and detection based on clustering results. The aim of the proposedresearch is to provide a new cluster overlap reduction method based on the divisions ofsemantic memberships to solve limited semantic expression and diversify short microblogcontents. First, by defining the time-series frequent word set of the microblog text, a fea-ture word selection method for hot topics is given; then, for the existence of initial clusters,according to the time-series recurring feature word set, to obtain the initial clustering ofthe microblog.
    Źródło:
    Computer Assisted Methods in Engineering and Science; 2024, 31, 2; 139-155
    2299-3649
    Pojawia się w:
    Computer Assisted Methods in Engineering and Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Applying the relational modelling and knowledge-based techniques to the emitter database design
    Autorzy:
    Dudczyk, J.
    Matuszewski, J.
    Wnuk, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/309249.pdf
    Data publikacji:
    2003
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    bazy danych
    sieć semantyczna
    modelowanie relacyjne
    emitter database
    relational modelling
    knowledge-based-techniques
    semantic networks
    confidence factor
    Opis:
    The appropriate emitter database is one of the most important elements in the present electronic intelligence (ELINT) system. This paper provides an overview of the relational modelling, which is used to construct the emitter database for current ELINT systems. The method described, delivers the entities' relational diagram that is independent from the manner of the data storage in further process of implementation. This approach ensures the integrity of the measured data. The process of final emitter identification is based on "the knowledge-based approach" which was implemented during the process of constructing the database.
    Źródło:
    Journal of Telecommunications and Information Technology; 2003, 1; 51-54
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Segmentation of bone structures with the use of deep learning techniques
    Autorzy:
    Krawczyk, Zuzanna
    Starzyński, Jacek
    Powiązania:
    https://bibliotekanauki.pl/articles/2128158.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    deep learning
    semantic segmentation
    U-net
    FCN
    ResNet
    computed tomography
    technika deep learning
    głęboka nauka
    segmentacja semantyczna
    tomografia komputerowa
    Opis:
    The paper is focused on automatic segmentation task of bone structures out of CT data series of pelvic region. The authors trained and compared four different models of deep neural networks (FCN, PSPNet, U-net and Segnet) to perform the segmentation task of three following classes: background, patient outline and bones. The mean and class-wise Intersection over Union (IoU), Dice coefficient and pixel accuracy measures were evaluated for each network outcome. In the initial phase all of the networks were trained for 10 epochs. The most exact segmentation results were obtained with the use of U-net model, with mean IoU value equal to 93.2%. The results where further outperformed with the U-net model modification with ResNet50 model used as the encoder, trained by 30 epochs, which obtained following result: mIoU measure – 96.92%, “bone” class IoU – 92.87%, mDice coefficient – 98.41%, mDice coefficient for “bone” – 96.31%, mAccuracy – 99.85% and Accuracy for “bone” class – 99.92%.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e136751, 1--8
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Segmentation of bone structures with the use of deep learning techniques
    Autorzy:
    Krawczyk, Zuzanna
    Starzyński, Jacek
    Powiązania:
    https://bibliotekanauki.pl/articles/2173574.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    deep learning
    semantic segmentation
    U-net
    FCN
    ResNet
    computed tomography
    technika deep learning
    głęboka nauka
    segmentacja semantyczna
    tomografia komputerowa
    Opis:
    The paper is focused on automatic segmentation task of bone structures out of CT data series of pelvic region. The authors trained and compared four different models of deep neural networks (FCN, PSPNet, U-net and Segnet) to perform the segmentation task of three following classes: background, patient outline and bones. The mean and class-wise Intersection over Union (IoU), Dice coefficient and pixel accuracy measures were evaluated for each network outcome. In the initial phase all of the networks were trained for 10 epochs. The most exact segmentation results were obtained with the use of U-net model, with mean IoU value equal to 93.2%. The results where further outperformed with the U-net model modification with ResNet50 model used as the encoder, trained by 30 epochs, which obtained following result: mIoU measure – 96.92%, “bone” class IoU – 92.87%, mDice coefficient – 98.41%, mDice coefficient for “bone” – 96.31%, mAccuracy – 99.85% and Accuracy for “bone” class – 99.92%.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e136751
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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