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    Wyświetlanie 1-4 z 4
    Tytuł:
    Examining the success factors of smart watch : a behavioral perspective on consumers
    Badanie czynników sukcesu inteligentnego zegarka : behawioralna perspektywa konsumentów
    Autorzy:
    Lin, Chih Wei
    Yang, Chin-Cheng
    Sia, Wei Yeng
    Tang, Kai-Yu
    Powiązania:
    https://bibliotekanauki.pl/articles/404795.pdf
    Data publikacji:
    2019
    Wydawca:
    Politechnika Częstochowska
    Tematy:
    perceived playfulness
    compatibility
    technology acceptance model
    innovation diffusion theory
    postrzegana użyteczność
    kompatybilność
    model akceptacji technologii
    teoria dyfuzji innowacji
    Opis:
    The purpose of this study was to investigate factors influencing consumers’ intention to use Apple Watch by applying Decomposed Theory of Planned Behavior (DTPB). The subject of the study was the Apple Watch users in Taiwan. The researcher used purposive and snowball sampling as the sampling method, a total of 350 surveys were issued, 327 valid surveys were collected and the effective response rate was 93.43%. The collected data were analyzed by confirmatory factor analysis and structural equation model. The results are illustrated as follow. First, the overall behavior model of Apple Watch users constructed by Decomposed Theory of Planned Behavior in this study fitted well. Second, the research model has well explanatory power to wearable device users, which is R² of attitudes, subjective norms and perceived behavioral control on behavior intentions have reached 63%. Third, perceived usefulness and perceived playfulness are the most two important influencing factors on attitudes. Interpersonal influence is the most important influencing factor to subjective norm. The most influencing factor of perceived behavioral control is facilitating condition.
    Celem tego badania było zbadanie czynników wpływających na zamiar korzystania przez Apple z zegarka przez zastosowanie dekompozycji teorii planowanego zachowania (DTPB). Przedmiotem badania byli użytkownicy Apple Watch na Tajwanie. Badacz zastosował celowe i śnieżkowe pobieranie próbek jako metodę pobierania próbek, wykonano w sumie 350 badań, zebrano 327 ważnych badań, a efektywny odsetek odpowiedzi wyniósł 93,43%. Zebrane dane przeanalizowano za pomocą potwierdzającej analizy czynnikowej i modelu równań strukturalnych. Wyniki zostały zilustrowane w następujący sposób. Po pierwsze, ogólny model zachowania użytkowników Apple Watch skonstruowany przez Dekomponowaną Teorię Planowanego Zachowania (DTPB) w tym badaniu dobrze skonstruowany. Po drugie, model badawczy wyjaśnia użytkownikom tych urządzeń, subiektywnych norm i postrzeganej kontroli behawioralnej nad zamiarami zachowań osiągnął 63%. Po trzecie, postrzegana użyteczność i postrzegana zabawa to dwa najważniejsze czynniki wpływające na postawy użytkowników.
    Źródło:
    Polish Journal of Management Studies; 2019, 20, 2; 368-378
    2081-7452
    Pojawia się w:
    Polish Journal of Management Studies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evaluation of the Optimum Machining Stability of a Milling Tool with Different Flutes and Overhangs
    Autorzy:
    Lin, Yung-Chih
    Wu, Kung-Da
    Shih, Wei-Cheng
    Hung, Jui-Pin
    Powiązania:
    https://bibliotekanauki.pl/articles/102194.pdf
    Data publikacji:
    2019
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    machining stability
    material remove rate
    milling cutter
    tooling condition
    stabilność obróbki
    szybkość usuwania materiału
    frez
    stan narzędzi
    Opis:
    In machining practice, the selection of the tooling condition of the cutters is an important task for milling operation with better surface quality and material remove rates. This study was therefore aimed at evaluating the influence of the tooling condition, such as the flutes and overhang length, on the machining efficiency of a milling machine by using the machining stability analysis method. Essentially, the machining stability was calculated based on the measured frequency response functions of the milling cutter, while it was also affected by the changing milling tooling path. Therefore, the machining stabilities in different feeding directions, referred to as polar stability boundary, were evaluated to show the strength and weakness of a specific cutter in contouring machining. The current results show that the overhang length greatly affects the dynamic characteristics and the limited cutting depths of the milling cutter. The stability boundaries of the machining conditions can be enhanced by appropriately adjusting the overhang of the milling cutter. Besides, the 2-flute cutter shows a larger cutting depth for surface contouring as compared to the 4-flute cutter, which is expected to increase the material remove rate under stable machining. As a whole, this study provides valuable references for enhancing the machining efficiency through the use of different tooling conditions.
    Źródło:
    Advances in Science and Technology. Research Journal; 2019, 13, 2; 56-64
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prevalence, characteristics, and work-related risk factors of low back pain among hospital nurses in Taiwan: A cross-sectional survey
    Autorzy:
    Lin, Pei-Hsin
    Tsai, Yun-An
    Chen, Wei-Chih
    Huang, Shih-Fong
    Powiązania:
    https://bibliotekanauki.pl/articles/2180113.pdf
    Data publikacji:
    2012-03-01
    Wydawca:
    Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
    Tematy:
    low back pain
    nurses
    prevalence
    Taiwan
    Opis:
    Background: Low back pain is a common health problem among hospital nurses. However, the prevalence, characteristics, and work-related risk factors of low back pain have not been widely investigated in Taiwan. Materials and Methods: This study used a cross-sectional survey of 217 hospital nurses to gather self-reported information on the prevalence of back pain, demographic and pain characteristics, and work-related risk factors from 178 respondents who indicated a past history of back pain. The association between the characteristics of back pain and work-related risk factors was also examined. Results: The lifetime prevalence of back pain was 82.03%, and the point prevalence of back pain was 43.78%. The mean pain score is 41.67. The number of years at work was significantly associated with the pain score for an individual’s most recent episode of back pain, the extent of bothersomeness of back pain and leg pain, and the extent to which back pain interfered with normal work. Conclusion: Back pain is common among hospital nurses in Taiwan. Years at work are significantly associated with pain severity and disability caused by back pain.
    Źródło:
    International Journal of Occupational Medicine and Environmental Health; 2012, 25, 1; 41-50
    1232-1087
    1896-494X
    Pojawia się w:
    International Journal of Occupational Medicine and Environmental Health
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Moving object detection for complex scenes by merging BG modeling and deep learning method
    Autorzy:
    Lin, Chih-Yang
    Huang, Han-Yi
    Lin, Wei-Yang
    Ng, Hui-Fuang
    Muchtar, Kahlil
    Nurdin, Nadhila
    Powiązania:
    https://bibliotekanauki.pl/articles/23944823.pdf
    Data publikacji:
    2023
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    video surveillance
    deep learning
    moving object detection
    Opis:
    In recent years, many studies have attempted to use deep learning for moving object detection. Some research also combines object detection methods with traditional background modeling. However, this approach may run into some problems with parameter settings and weight imbalances. In order to solve the aforementioned problems, this paper proposes a new way to combine ViBe and Faster-RCNN for moving object detection. To be more specific, our approach is to confine the candidate boxes to only retain the area containing moving objects through traditional background modeling. Furthermore, in order to make the detection able to more accurately filter out the static object, the probability of each region proposal then being retained. In this paper, we compare four famous methods, namely GMM and ViBe for the traditional methods, and DeepBS and SFEN for the deep learning-based methods. The result of the experiment shows that the proposed method has the best overall performance score among all methods. The proposed method is also robust to the dynamic background and environmental changes and is able to separate stationary objects from moving objects. Especially the overall F-measure with the CDNET 2014 dataset (like in the dynamic background and intermittent object motion cases) was 0,8572.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 3; 151--163
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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