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Wyszukujesz frazę "Orłowski, Karol" wg kryterium: Autor


Wyświetlanie 1-9 z 9
Tytuł:
The structure of the teacher Machiavellianism model in social interactions in a school environment
Autorzy:
Bańka, Augustyn
Orłowski, Karol
Powiązania:
https://bibliotekanauki.pl/articles/430272.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
teacher personality
Machiavellianism
the Dark Triad,
structural equations modeling
Opis:
The aim of this article is to present study results concerning the structure of teacher Machiavellianism. Machiavellianism was researched extensively throughout the last 40 years as a personality feature comprising traits related to leadership manipulation tactics. Psychology describes Machiavellianism as a part of the universal model called “the dark triad of personality” alongside with subclinical narcissism, subclinical psychopathy and low empathy. The teacher Machiavellianism model presented in this article, as opposed to the universal models, strongly accentuates the context-specifi c variables related to the organization of life in a school, alongside with personality variables. To achieve a new insight into the mechanism of how teacher Machiavellianism is generated, structural equation modeling (SEM) was used, which incorporates personality variables such as: self-effi cacy, disposition for gratitude, values, one’s personal resources, professional burnout, alongside context-specifi c variables like: organizational culture, work attitude, tenure and specialization in the tasks performed. Results of two studies are shown, discussing the empirical structure of teacher Machiavellianism components in relation to the initial theoretical model.
Źródło:
Polish Psychological Bulletin; 2012, 43, 4; 215-222
0079-2993
Pojawia się w:
Polish Psychological Bulletin
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Advancing Chipboard Milling Process Monitoring through Spectrogram-Based Time Series Analysis with Convolutional Neural Network using Pretrained Networks
Autorzy:
Kurek, Jarosław
Szymanowski, Karol
Chmielewski, Leszek
Orłowski, Arkadiusz
Powiązania:
https://bibliotekanauki.pl/articles/27323142.pdf
Data publikacji:
2023
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Instytut Informatyki Technicznej
Tematy:
convolutional neural networks
CNN
vgg16
vgg19
resnet34
tool state monitoring
chipboard milling
Opis:
This paper presents a novel approach to enhance chipboard milling process monitoring in the furniture manufacturing sector using Convolutional Neural Networks (CNNs) with pretrained architectures like VGG16, VGG19, and RESNET34. The study leverages spectrogram representations of time-series data obtained during the milling process, providing a unique perspective on tool condition monitoring. The efficiency of the CNN models in accurately classifying tool conditions into distinct states (‘Green’, ‘Yellow’, and ‘Red’) based on wear levels is thoroughly evaluated. Experimental results demonstrate that VGG16 and VGG19 achieve high accuracy, however with longer training times, while RESNET34 offers faster training at the cost of reduced precision. This research not only highlights the potential of pretrained CNNs in industrial applications but also opens new avenues for predictive maintenance and quality control in manufacturing, underscoring the broader applicability of AI in industrial automation and monitoring systems.
Źródło:
Machine Graphics & Vision; 2023, 32, 2; 89--108
1230-0535
2720-250X
Pojawia się w:
Machine Graphics & Vision
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-9 z 9

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