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- A multidisciplinary engineering-based approach for tunnelling strengthening with a new fibre reinforced shotcrete technologyPublication . Barros, Joaquim; Costelha, Hugo; Bento, David; Brites, Nelson; Luís, Rui; Patrício, Hugo; Cunha, Vítor M.C.F.; Bento, Luís; Miranda, Tiago; Coelho, Paulo; Azenha, Miguel; Neves, Carlos; Salehian, Hamidreza; Moniz, Gonçalo; Nematollahi, Mojtaba; Teixeira, Abel; Taheri, Mahsa; Mezhyrych, Anton; Hosseinpour, Emad; Correia, Tales; Kazemi, Hamid; Hassanshahi, Omid; Rashiddel, Alireza; Esmail, BriarThis paper describes the relevant research activities that are being carried out on the development of a novel shotcrete technology capable of applying, autonomously and in real time, fibre reinforced shotcrete (FRS) with tailored properties regarding the optimum structural strengthening of railway tunnels (RT). This technique allows to apply fibre reinforced concrete (FRC) of strain softening (SSFRC) and strain hardening (SHFRC) according to a multi-level advanced numerical simulation that considers the relevant nonlinear features of these FRC, as well as their interaction with the surrounding soil, for an intended strengthening performance of the RT. Building information modelling (BIM) is used for assisting on the development of data files of the involved design software, integrating geometric assessment of a RT, damages from inspection and diagnosis, and the characteristics of the FRS strengthening solution. A dedicated computational tool was developed to design FRC with target properties. The preliminary experimental results on the evaluation of the relevant mechanical properties of the FRS are presented and discussed, as well as the experimental tests on the bond between FRS and current substrates found in RT. Representative numerical simulations were performed to demonstrate the structural performance of the proposed FRS-based strengthening technique. Computational tools capable of assuring, in real time, the aimed thickness of the layers forming the FRS strengthening shell were also developed. The first generation of a mechanical device for controlling the amount of fibres to be added, in real time, to the FRS mixture was conceived, built and tested. A mechanism is also being developed to improve the fibre distribution during its introduction through the mechanical device to avoid fibre balling. This work describes the relevant achievements already attained, as introduces the planned future initiatives in the scope of this project.
- A Deep Learning Approach for Red Lesions Detection in Video Capsule EndoscopiesPublication . Coelho, Paulo; Pereira, Ana; Leite, Argentina; Salgado, Marta; Cunha, AntónioThe wireless capsule endoscopy has revolutionized early diagnosis of small bowel diseases. However, a single examination has up to 10 h of video and requires between 30–120 min to read. Computational methods are needed to increase both efficiency and accuracy of the diagnosis. In this paper, an evaluation of deep learning U-Net architecture is presented, to detect and segment red lesions in the small bowel. Its results were compared with those obtained from the literature review. To make the evaluation closer to those used in clinical environments, the U-Net was also evaluated in an annotated sequence by using the Suspected Blood Indicator tool (SBI). Results found that detection and segmentation using U-Net outperformed both the algorithms used in the literature review and the SBI tool.