ALBERT — All Library Books, journals and Electronic Records Telegrafenberg

1

Unbekannt

Strengthening Solutions for Deep Reinforced Concrete Beam with Cutout Opening (2021)

Bahrami, Alireza ; Ågren, Felicia ; Kollberg, Kim

Molecular Diversity Preservation International

In: Buildings . 2021; 11(8): 370. Published 2021 Aug 20. doi: 10.3390/buildings11080370.

zur Merkliste hinzufügen auf der Merkliste

Details

Publikationsdatum: 2021-08-20

Beschreibung: Since reinforced concrete (RC) buildings have long service life, cutout openings are generally needed in their load-bearing walls as a sustainable solution in order to meet new requirements of their users. However, the cutout openings decrease the load-bearing capacity of the walls, which may result in the failure of the buildings. In this paper, we investigate the possibility of making a door opening in a load-bearing RC wall of an existing building in Gävle in Sweden. The wall studied in the current paper rests on two individual supports at its two ends; thus, it is considered as a deep beam. However, it is called an examined wall (EW) here. The StruSoft FEM-Design software is used in this study to model, analyze, and design the building based on the Eurocodes and Swedish national annex. The potential need for the EW to be strengthened when the cutout opening is made is also evaluated. It is concluded that strengthening the EW with cutout opening is needed. Different strengthening solutions are proposed for the EW. Moreover, the situation of the EW with the solutions is assessed with regard to the utilization ratio, deflection, and weight. Consequently, it is demonstrated that the proposed strengthening solutions function well for the EW.

Digitale ISSN: 2075-5309

Thema: Architektur, Bauingenieurwesen, Vermessung

Publiziert von Molecular Diversity Preservation International

Permalink

	Standort	Signatur	Erwartet	Verfügbarkeit

Andere fanden auch interessant ...

AKTUELLE ARTIKEL

S·F·X

Volltext

2

Unbekannt

A Novel Affine Covariant Feature Mismatch Removal for Feature Matching (2021)

Shen, Liang ; Zhu, Jiahua ; Fan, Chongyi ; [weitere]

Institute of Electrical and Electronics Engineers

In: IEEE Transactions on Geoscience and Remote Sensing. 2021; 1-13. Published 2021 Jan 01. doi: 10.1109/tgrs.2021.3104146. [early online release]

zur Merkliste hinzufügen auf der Merkliste

Details

Publikationsdatum: 2021-01-01

Print ISSN: 0196-2892

Digitale ISSN: 1558-0644

Thema: Architektur, Bauingenieurwesen, Vermessung , Geographie

Publiziert von Institute of Electrical and Electronics Engineers

Permalink

	Standort	Signatur	Erwartet	Verfügbarkeit

Andere fanden auch interessant ...

AKTUELLE ARTIKEL

S·F·X

Volltext

3

Unbekannt

An Automatic Cloud Detection Neural Network for High-Resolution Remote Sensing Imagery With Cloud-Snow Coexistence (2021)

Chen, Yang ; Weng, Qihao ; Tang, Luliang ; [weitere]

Institute of Electrical and Electronics Engineers

In: IEEE Geoscience and Remote Sensing Letters. 2021; 1-5. Published 2021 Jan 01. doi: 10.1109/lgrs.2021.3102970. [early online release]

zur Merkliste hinzufügen auf der Merkliste

Details

Publikationsdatum: 2021-01-01

Print ISSN: 1545-598X

Digitale ISSN: 1558-0571

Thema: Architektur, Bauingenieurwesen, Vermessung , Geographie , Geologie und Paläontologie

Publiziert von Institute of Electrical and Electronics Engineers

Permalink

	Standort	Signatur	Erwartet	Verfügbarkeit

Andere fanden auch interessant ...

AKTUELLE ARTIKEL

S·F·X

Volltext

4

Unbekannt

Design of an Ultrasound-Navigated Prostate Cancer Biopsy System for Nationwide Implementation in Senegal (2021)

Fichtinger, Gabor ; Mousavi, Parvin ; Ungi, Tamas ; [weitere]

Molecular Diversity Preservation International

In: Journal of Imaging. 2021; 7(8): 154. Published 2021 Aug 20. doi: 10.3390/jimaging7080154.

zur Merkliste hinzufügen auf der Merkliste

Details

Publikationsdatum: 2021-08-20

Beschreibung: This paper presents the design of NaviPBx, an ultrasound-navigated prostate cancer biopsy system. NaviPBx is designed to support an affordable and sustainable national healthcare program in Senegal. It uses spatiotemporal navigation and multiparametric transrectal ultrasound to guide biopsies. NaviPBx integrates concepts and methods that have been independently validated previously in clinical feasibility studies and deploys them together in a practical prostate cancer biopsy system. NaviPBx is based entirely on free open-source software and will be shared as a free open-source program with no restriction on its use. NaviPBx is set to be deployed and sustained nationwide through the Senegalese Military Health Service. This paper reports on the results of the design process of NaviPBx. Our approach concentrates on “frugal technology”, intended to be affordable for low–middle income (LMIC) countries. Our project promises the wide-scale application of prostate biopsy and will foster time-efficient development and programmatic implementation of ultrasound-guided diagnostic and therapeutic interventions in Senegal and beyond.

Digitale ISSN: 2313-433X

Thema: Informatik

Publiziert von Molecular Diversity Preservation International

Permalink

	Standort	Signatur	Erwartet	Verfügbarkeit

Andere fanden auch interessant ...

AKTUELLE ARTIKEL

S·F·X

Volltext

5

Unbekannt

Cross-Project Defect Prediction Method Based on Manifold Feature Transformation (2021)

Zhao, Yu ; Zhu, Yi ; Yu, Qiao ; [weitere]

Molecular Diversity Preservation International

In: Future Internet. 2021; 13(8): 216. Published 2021 Aug 20. doi: 10.3390/fi13080216.

zur Merkliste hinzufügen auf der Merkliste

Details

Publikationsdatum: 2021-08-20

Beschreibung: Traditional research methods in software defect prediction use part of the data in the same project to train the defect prediction model and predict the defect label of the remaining part of the data. However, in the practical realm of software development, the software project that needs to be predicted is generally a brand new software project, and there is not enough labeled data to build a defect prediction model; therefore, traditional methods are no longer applicable. Cross-project defect prediction uses the labeled data of the same type of project similar to the target project to build the defect prediction model, so as to solve the problem of data loss in traditional methods. However, the difference in data distribution between the same type of project and the target project reduces the performance of defect prediction. To solve this problem, this paper proposes a cross-project defect prediction method based on manifold feature transformation. This method transforms the original feature space of the project into a manifold space, then reduces the difference in data distribution of the transformed source project and the transformed target project in the manifold space, and finally uses the transformed source project to train a naive Bayes prediction model with better performance. A comparative experiment was carried out using the Relink dataset and the AEEEM dataset. The experimental results show that compared with the benchmark method and several cross-project defect prediction methods, the proposed method effectively reduces the difference in data distribution between the source project and the target project, and obtains a higher F1 value, which is an indicator commonly used to measure the performance of the two-class model.

Digitale ISSN: 1999-5903

Thema: Informatik

Publiziert von Molecular Diversity Preservation International

Permalink