Abstract
The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-To-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05° ± 18, 50° was found, whereas the mean signed error was 1, 09°. Large deviations between the manual and automatic annotations (> 30°) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-Time application. In conclusion, a successful automatic real-Time method for orientation of the segmented left ventricle is proposed. © 2016 SPIE.

Abstract
In the previous edition of ISSRE we used a straightforward hunting metaphor to call the attention of the research community to the importance of considering human aspects in software testing - in particular, to research challenges that affect practitioners in the industry. Our focus was on the unit testing level. As a result, we proposed a framework to indicate research directions in three cognitive support dimensions defined to this level of testing. In the present work, we advance in this area considering the visualization domain. We demonstrate an immediate application of our framework to help derive information on how visualizations for unit testing are currently addressing each cognitive support dimension. Our results demonstrate the lack of concern with adequate procedures for both planning and validation of the visualizations regarding cognitive support aspects. These issues affect the capacity of the proposals to support users and put under risk the solutions' reliability.

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Wireless Underground Networks (WUN) have many applications, such as border surveillance, agriculture monitoring, and infrastructure monitoring. Recent studies have shown that they are feasible and have deployment advantages over wired networks, but only a few WUN evaluations in multiple access scenarios have been done. This paper presents a simulation study on medium access for a WUN with 4 nodes buried, and one node aboveground. The simulations were carried out using the ns-3 simulator and they evaluate both Wi-Fi, and Lr-Wpan networks for dry and wet soils. We verified that for the same number of concurrent nodes, the use of the RTS/CTS mechanism has a much higher influence than the soil water content. Furthermore, a study about the feasibility of using Wi-Fi fingerprinting for positioning above the ground based on the buried infrastructure revealed promising results.

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A new small-sized autonomous surface vehicle actuated by a water-jet has been developed at INESC TEC for search and rescue of victims at sea. This paper describes the vehicle main components and presents the control and guidance laws governing the motion and enabling it to perform line-following and target tracking missions. Results from field trials are presented, demonstrating the capabilities and the performances of the vehicle along with its control layer.

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