VISIONBR Tecnologia e Informatica (Brazil)

A modified corneal lasso suture technique for reversing hyperopia after radial keratotomy is described. 3 concentric sutures were placed in a loop on the cornea to promote the restructuring of the flattened cornea and restore its prolate shape. As a result, the patient's myopia returned, improving near vision and providing more treatment options for dissatisfied patients.

ABSTRACT P-band radar interferometry is a promising tool for digital terrain modelling in forested areas such as the Amazon due to the ability of P-band to penetrate densely forested areas. The quality of Digital Terrain Models (DTMs) is a primary requirement for many geoscience applications because DTM accuracy is an essential variable for characterizing landform shapes. This article presents a multicriteria evaluation of the overall quality of a digital terrain model produced using P-band SAR interferometric processing. The evaluation considers behaviours related to elevation and slope and analyses the impact of landscape properties such as slope and aspect. The multicriteria accuracy of the study showed promising results about the realism of landforms, according to applied geomorphological criteria, and also in the visual comparison between the produced DTM and the reference. The study provided an estimate of the accuracy of P-band radar DTM in terms of elevation with a standard deviation of 2.36 m and in terms of slope with a mean error of approximately −4°, a standard deviation of 4.74°, and a RMSE (Root Mean Square Error) slope error of 6.14°, using a reference DTM derived from an airborne LiDAR (Light Detection and Ranging) survey. The spatial behaviour of these errors and their sensitivity to slope and aspect were analysed. The investigation of hydrographic inconsistencies in the DTM was conducted based on various criteria, including identifying depressions along watercourses and adhering to Horton’s law. Finally, the effects of the acquisition, processing, and resampling processes are revealed through indicators such as the rose histogram. This multicriteria study demonstrates the suitability of airborne P-band radar interferometry for digital elevation modelling in tropical rainforest environments.

Abstract. Forest plantations play an important role ecologically, contribute to carbon sequestration and support billions of dollars of economic activity each year through sustainable forest management and forest sector value chains. As the global demand for forest products and services increases, the marketplace is seeking more reliable data on forest plantations. Remote sensing technologies allied with machine learning, and most recently deep learning techniques, provide valuable data for inventorying forest plantations and related valuation products. In this work, deep semantic segmentation with U-net architecture was used to detect forest plantation areas using Sentinel-2 and CBERS-4A images of different areas of Brazil. First, the U-net models were built from an area of the Centre-East of Paraná State, and then the best models were tested in 3 new areas that present different characteristics. The U-net models built with Sentinel-2 images achieved promising results for areas similar to the ones used in the training set, with F1-score ranging from 0.9171 to 0.9499 and with Kappa values between 0.8712 to 0.9272, demonstrating the feasibility of deep semantic segmentation to detect forest plantations.

Advanced differential SAR interferometry (A-DInSAR) has been used as an effective monitoring tool in mining environments. This work presents an investigation of surface displacement in the Germano iron mining complex (Mariana, Minas Gerais, Brazil), where on November 5, 2015, the Fundão tailings dam collapsed. Initially, the analysis was performed with 14 Sentinel-1 images, acquired from May 8, 2015, to November 4, 2015, and focused on the Fundão dam before its rupture to detect prior signs of surface deformations. The analysis after the Fundão dam collapse was conducted in the Germano area using 43 Sentinel-1 images, acquired from November 16, 2015 to May 15, 2017, and aimed at detecting surface displacement on the remaining infrastructure, the Sela&Tulipa and Selinha dikes and the main Germano tailings dam, which were directly or indirectly affected by the accident. The results reveal precursor signals of surface displacement at the Fundão dam prior to rupture, particularly on the left abutment setback sector where the collapse started according to a witness, reaching accumulated values of up to −60 mm. The results provided by the A-DInSAR analysis after the dam collapse indicate a stability in the Sela&Tulipa and Selinha dikes as well as in the main Germano dam, which is corroborated by in situ topographic measurements. On the auxiliary dikes within the Germano reservoir, accumulated displacement of up to −90 mm caused by settlements and continuous traffic of vehicles was detected. In addition, the detected accumulate displacement within the reservoir showed values of up to −120 mm, in general caused by settlements of the waste dry material due to the inactivity of the mining process. The investigation emphasized the important role that satellite-based A-DInSAR can play in mitigating possible accidents and for operational planning and risk assessment in mining operations.

This paper presents an incoherent change detection algorithm (CDA) for synthetic aperture radar (SAR) images based on logistic regression. The input data consists of a set of 24 SAR images acquired in a test site in northern Sweden [1]. Subsets of these images are trained based on pixel amplitude, flight heading and neighboring features such as local mean, standard deviation and skewness. The proposed method intends to explore the advantadges from both pixel- and object-based approaches, while evaluating multiple features in amplitude-only SAR images. Preliminary results based on K-fold cross-validation have shown that the proposed CDA achieves good performance when compared to the results presented in [1].

Na manufatura de produtos metlicos, o forjamento o processo de transformao a quente de materiais dcteis, como aos e ligas, atravs de conformao mecnica efetuada com esforo de compresso por uma prensa, de modo que eles assumam os formatos desejados. Este processo normalmente utilizado para produzir peas de formas complexas e com uma maior preciso dimensional de acordo com a especificidade exigida pelo cliente final. Para obter resultados de qualidade, foi necessria a implantao de tcnicas de medio indireta de ltima gerao, que proporcionam ganho de tempo e a reduo de desperdcio de energia e material, alm de aumentar a segurana, reduzindo a presena de pessoas prximas aos materiais para medies manuais. O presente trabalho trata da criao de um sistema de viso que, por meio de anlise de imagem, capaz de coletar a medida do perfil de barras em uma Forjaria em tempo real,