Abstract
Ideally, to carry out screening for eye diseases, it is expected to use specialized medical equipment to capture retinal fundus images. However, since this kind of equipment is generally expensive and has low portability, and with the development of technology and the emergence of smartphones, new portable and cheaper screening options have emerged, one of them being the D-Eye device. When compared to specialized equipment, this equipment and other similar devices associated with a smartphone present lower quality and less field-of-view in the retinal video captured, yet with sufficient quality to perform a medical pre-screening. Individuals can be referred for specialized screening to obtain a medical diagnosis if necessary. Two methods were proposed to extract the relevant regions from these lower-quality videos (the retinal zone). The first one is based on classical image processing approaches such as thresholds and Hough Circle transform. The other performs the extraction of the retinal location by applying a neural network, which is one of the methods reported in the literature with good performance for object detection, the YOLO v4, which was demonstrated to be the preferred method to apply. A mosaicing technique was implemented from the relevant retina regions to obtain a more informative single image with a higher field of view. It was divided into two stages: the GLAMpoints neural network was applied to extract relevant points in the first stage. Some homography transformations are carried out to have in the same referential the overlap of common regions of the images. In the second stage, a smoothing process was performed in the transition between images.

Abstract
The Switched Reluctance Generator (SRG) has been widely studied for Wind Energy Conversion Systems (WECS). However, a major drawback of the SRG system adopting the conventional control is the slow response of the DC link voltage controller. In this paper, a Proportional Resonant (PR) control strategy is proposed to control the output voltage of the SRG system to improve the fast response. The SRG model has a high non-linearity, which makes the design of controllers a difficult task. For this reason, the important practical engineering aspect of this work is the role played by the SRG model linearization in testing the sensitivity of the PR controller performance to specific parameter changes. The characteristics of steady-state behaviors of the SRG-based WECS under different control approaches are simulated and compared. The controller is implemented on a digital signal processor (TMS320F28379D). The experimental results are carried out using a 250 W 8/6 SRG prototype to assess the performance of the proposed control compared with the traditional Proportional Integral (PI) control strategy. The experimental results show that the PR control enhances the steady-state performance of the SR power generation system in WECS. Compared to PI control, the rise and settling times are reduced by 45% and 43%, respectively, without an overshoot.

Abstract
Higher Education Institutions use social media as a marketing channel to attract and engage users so that the institution is promoted and thus a wide range of benefits can be achieved. These institutions are evaluated globally on various success parameters, being published in rankings. In this paper, we analyze the publishing strategies and compare the results with their overall ranking positions. The results show that there is a tendency to find a particular strategy in the top ranked universities. We also found cases where the strategies are less prominent and do not match the ranking positions. Copyright © 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

Abstract
Underwater autonomous manipulation is the capability of a mobile robot to perform intervention tasks that require physical contact with unstructured environments without continuous human supervision. Being difficult to assess the behaviour of existing motion planner algorithms, this research proposes a new planner evaluation metric to identify well-behaved planners for specialized tasks of inspection and monitoring of man-made underwater structures. This metric is named NEMU and combines three different performance indicators: effectiveness, safety and adaptability. NEMU deals with the randomization of sampling-based motion planners. Moreover, this article presents a benchmark of multiple planners applied to a 6 DoF manipulator operating underwater. Results conducted in real scenarios show that different planners are better suited for different tasks. Experiments demonstrate that the NEMU metric can be used to distinguish the performance of planners for particular movement conditions. Moreover, it identifies the most promising planner for collision-free motion planning, being a valuable contribution for the inspection of maritime structures, as well as for the manipulation procedures of autonomous underwater vehicles during close range operations.

Abstract

Abstract
The process of developing Dockerfiles is perceived by many developers as slow and based on trial-and-error, and it is hardly immediate to see the result of a change introduced into a Dockerfile. In this work we propose a plugin for Visual Studio Code, which we name Dockerlive, and that has the purpose of shortening the length of feedback loops. Namely, the plugin is capable of providing information to developers on a number of Dockerfile elements, as the developer is writing the Dockerfile. We achieve this through dynamic analysis of the resulting container, which the plugin builds and runs in the background. © 2022 IEEE.