GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Hindawi Limited  (3)
  • 1
    Online Resource
    Online Resource
    Hindawi Limited ; 2020
    In:  Advances in Civil Engineering Vol. 2020 ( 2020-06-16), p. 1-12
    In: Advances in Civil Engineering, Hindawi Limited, Vol. 2020 ( 2020-06-16), p. 1-12
    Abstract: This study investigated the compressive behaviour of super-long pile foundations with large diameters. Three 52 m, 73 m, and 83 m long piles with a diameter of 1500 mm, 1500 mm, and 1800 mm were cast and tested, respectively. Given that large loading was required, an improved compressive static load test was introduced, and the load transfer mechanism, shaft resistance development, and distribution were analysed. This study found that the transferred load decreased along the pile during each applied load, but the gradients were different. For most layers, when increasing the load, the shaft resistance developed in the upper layers first, while the shaft resistance from the lower part did not always fully develop. Moreover, the “mutual compensation” phenomenon was discovered, which was when the shaft softening occurred from one soil layer, the shaft hardening of the other soil would occur simultaneously. Under consideration of the soil layer differences around these piles, it was recommended that shaft and base grouting should be applied on 52 m and 73 m piles, while only shaft grouting should be applied on the 83 m pile. For this longest pile design, whose toe resistance was discovered to be very small, increasing the pile length was not appropriate; thus, it was preferable to increase the pile diameter to increase the ultimate bearing capacity.
    Type of Medium: Online Resource
    ISSN: 1687-8086 , 1687-8094
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2449760-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    Hindawi Limited ; 2023
    In:  Computational Intelligence and Neuroscience Vol. 2023 ( 2023-3-16), p. 1-18
    In: Computational Intelligence and Neuroscience, Hindawi Limited, Vol. 2023 ( 2023-3-16), p. 1-18
    Abstract: Osteoporosis is a significant global health concern that can be difficult to detect early due to a lack of symptoms. At present, the examination of osteoporosis depends mainly on methods containing dual-energy X-ray, quantitative CT, etc., which are high costs in terms of equipment and human time. Therefore, a more efficient and economical method is urgently needed for diagnosing osteoporosis. With the development of deep learning, automatic diagnosis models for various diseases have been proposed. However, the establishment of these models generally requires images with only lesion areas, and annotating the lesion areas is time-consuming. To address this challenge, we propose a joint learning framework for osteoporosis diagnosis that combines localization, segmentation, and classification to enhance diagnostic accuracy. Our method includes a boundary heat map regression branch for thinning segmentation and a gated convolution module for adjusting context features in the classification module. We also integrate segmentation and classification features and propose a feature fusion module to adjust the weight of different levels of vertebrae. We trained our model on a self-built dataset and achieved an overall accuracy rate of 93.3% for the three label categories (normal, osteopenia, and osteoporosis) in the testing datasets. The area under the curve for the normal category is 0.973; for the osteopenia category, it is 0.965; and for the osteoporosis category, it is 0.985. Our method provides a promising alternative for the diagnosis of osteoporosis at present.
    Type of Medium: Online Resource
    ISSN: 1687-5273 , 1687-5265
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2023
    detail.hit.zdb_id: 2388208-6
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Online Resource
    Online Resource
    Hindawi Limited ; 2020
    In:  Complexity Vol. 2020 ( 2020-11-20), p. 1-9
    In: Complexity, Hindawi Limited, Vol. 2020 ( 2020-11-20), p. 1-9
    Abstract: In this paper, the stability and stabilization issues for a class of delayed neural networks with time-varying hybrid impulses are investigated. The hybrid effect of two types of impulses including both stabilizing and destabilizing impulses is considered simultaneously in the analysis of systems. To characterize the occurrence features of impulses, the concepts of average impulse interval and average impulse strength are employed. Based on the analysis of stability, a pinning impulsive controller which can ensure the global exponential stability of the studied neural networks is designed by pinning a small fraction of neurons. Finally, two numerical examples are given to illustrate the effectiveness of the proposed control schemes for delayed neural networks with hybrid impulses.
    Type of Medium: Online Resource
    ISSN: 1099-0526 , 1076-2787
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2004607-8
    SSG: 11
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...