Abstract

Abstract
The extraction of accurate geometric measurements from images normally requires the use of metric cameras and stereoscopic observations. However, as good-quality digital cameras are widely available in mobile devices (smartphones, tablets), there is great interest to develop alternative approaches, suitable for these devices. This paper presents a methodology to compute the surface area and volume of a spheroid-shaped object, such as many types of fruit, from a single image acquired by a standard (non-metric) camera and a basic calibration target. An iterative process is used to establish a 3D spheroid out of the observed 2D ellipse, after which auxiliary images of height, resolution and surface area of each pixel on the 3D object surface are created. The method was tested with a data set of 2400 images, of 10 different objects, 2 calibration targets, 2 cameras and 2 mark types. The average relative errors (< d>) in establishing the 3D object semi-diameters were 0.863% and 0.791%. The semi-diameters are used to compute the object’s surface area (< d> = 1.557%) and volume (< d> = 2.365%). The estimation of the sub-region (mark) surface area over the modelled 3D object resulted in < d> = 2.985%, much lower that what is obtained ignoring the fact that the mark is not on the reference (calibration) plane (< d> = 50.7%), thus proving the effectiveness of the proposed iterative process to model the 3D object (spheroid). © 2020, Springer Nature Singapore Pte Ltd.

Abstract

Abstract
Objectives: Artificial intelligence (AI) is poised to transform breast cancer care. However, most scientists, engineers, and clinicians are not prepared to contribute to the AI revolution in healthcare. In this paper, we describe our experiences teaching a new undergraduate course for American students that aims to prepare the next generation for cross-cultural designthinking, which we believe is crucial for AI to achieve its full potential in breast cancer care. Materials and methods: The key course activities are planning, conducting, and interpreting interviews of healthcare professionals from both Portugal and the United States. Since the course is offered as a short-term faculty-led study abroad program in Portugal, students are able to explore the impact of culture on healthcare delivery and the design of healthcare technologies. Results: The learning assessments demonstrated student growth in several areas pertinent for future development of AI for breast cancer care. With respect to understanding breast cancer care, prior to taking this course, most students had underestimated the impact of cancer and its treatment on women's quality of life and most were unaware of the importance of multidisciplinary care teams. Regarding AI in medicine, students became more mindful of data privacy issues and the need to consider the effect of AI on healthcare professionals. Conclusion: This course illustrates the potential benefits for AI in medicine of introducing future scientists, engineers, and clinicians to cross cultural design-thinking early in their educational experiences. (C) 2020 The Author(s). Published by Elsevier Ltd.

Abstract
The tendency to use renewable energies in DC microgrids (MGs) has been increased in the past decades. Due to the unpredictable behavior of renewable resources, it is vital to utilize energy storage resources in the MG structure. The generation sources and storages in DC MGs should be chosen in order to meet the maximum demand in both grid-connected and islanded mode. Also, penetration of power electronic based devices is essential to connect these resources to the network. The control of these devices are another challenge in this regard. So, a proper configuration along with an efficient control approach is needed for development of DC MGs. In this paper, a new structure for DC MG is presented which includes solar photovoltaic (PV) as generation sources and supercapacitor and battery as storages. Furthermore, an innovative control method based on voltage variations is introduced for the proposed structure. It is shown that simultaneous usage of battery and supercapacitor improves the performance of the MG in handling the abrupt load changes in the both grid-connected and islanded mode operations. To evaluate the performance of the proposed structure and control algorithm, different conditions are simulated in MATLAB/Simulink software and the results are presented. The results confirm a high degree of performance for proposed structure and control method.

Abstract
In the Mediterranean region, climate change is likely to generate an increase in water demand and the deterioration of its quality. The adoption of precision viticulture and the best available techniques aiming at sustainable production, minimizing the impact on natural resources and reducing production costs, has therefore been a goal of winegrowers. In this work, the water footprint (WFP) in the wine sector was evaluated, from the vineyard to the bottle, through the implementation of a methodology based on field experiments and life cycle assessment (LCA) on two Portuguese case studies. Regarding direct water footprint, it ranged from 366 to 899 L/FU (0.75 L bottle), with green water being the most significant component, representing more than 50% of the overall water footprint. The approach used in the current study revealed that although more than 97.5% of the water footprint is associated with vineyard, the winery stage is responsible for more than 75% of the global warming potential indicator. A linear correlation between the carbon footprint and the indirect blue water footprint was also observed for both case studies. Climate change is expected to cause an earlier and prolonged water stress period, resulting in an increase of about 40% to 82% of blue WFP.