Abstract

Abstract
The aim of this article is to show how autoethnography is a useful and revealing research methodology that should be encouraged in academia, especially in higher education. With objectivity, autoethnography, which is a relatively new approach, may be a path toward deeper cultural discussions that are so important in everyday life. Moreover, autoethnography leads to important reflexive and critical observations made by students. Autoethnography is a readily accessible, low-cost methodology and thus very appealing to students and younger researchers. With this article, the author exemplifies autoethnographic accounts and narrates three different stories that occurred while trekking with three different trekking guides in Patagonia (El Chalten), Argentina. Argentinian culture, in South America, is the focus. Researchers need to be careful of misleading statements in the literature, such as that in Argentina modesty is apparently not tolerated. We found that two of our guides and leaders - Mariano and Liz - both had modest (and pleasant) demeanors. Hence, we conclude that it is important to maintain an open mind and resist categorizing people. This is a vital point of cultural studies that is often not taken seriously. Cultures are made up of individuals and thus many differences can be found in the midst of an attempted standardization, and the desire to put everyone in the same "basket".

Abstract
This article presents the contribution of the Polytechnic Institute of Castelo Branco (IPCB) within the scope of PPS1 of the PRODUTECH SIF program - Solutions for the Future Industry, in terms of the definition of modules for scalability, adaptation, plug-and-play, with interoperability between processes and technologies inter/intra industrial plants. More specifically, its contribution for the definition, implementation and evaluation of OPC- UA device discovery services. Adopting the CompactRIO platform developed on PPS2 as a physical basis for a Smartbox, its development was extended during the present task with a view to incorporating and validating the adopted service discovery mechanisms in the program.

Abstract

Abstract
This study proposes a hierarchical optimisation strategy for the energy dispatch and volt/var control problem of a photovoltaic-battery microgrid cluster (MGC) operating autonomously. The proposed approach takes advantage of the decentralised control architecture existing in multi-microgrids (MMGs) framework by distributing the management responsibilities between the microgrid central controllers (MGCCs) and the central autonomous management controller (CAMC). In the first stage, the optimisation strategy solves a multi-temporal active power scheduling problem for the MGC based on consumption and generation forecasts. In the second stage, the reactive power and volt/var control are addressed by taking into account the medium-voltage (MV) and low-voltage levels independently. For this purpose, each MGCC computes the V(Q) capability area of operation at the boundary bus with the MV grid. Then, the CAMC performs an optimal power flow at the MV level for each time step, whose results at the boundary bus are considered in the last stage to schedule reactive power at the MGCC level. The effectiveness of the proposed strategy is demonstrated in a cluster of three microgrids. It keeps the modularity, interoperability and scalability characteristics of the MMG concept by clearly defining the roles and the information to be exchanged between the CAMC and the MGCC.

Abstract
Precision Agriculture (PA) has a fundamental role in the sustainability of agricultural systems, supporting decision-making of agricultural crops, increasing yield and quality in production. In the present research a PA approach for viticulture was made combining remote sensing data and robotic monitoring. With this approach it was intended to perform a spatial-temporal analysis of the grapevine phenology, according the 3 periods of the grape's biological cycle reproductive cycle, peak of the season and vegetative dormancy - corresponding to the years of 2017/18, for a specific area of the Green Wine Region, from Celorico de Basto (Portugal). The proposed methodology is based in the automation of spatial analyses through Geographical Information Systems (GIS), Google Earth Engine (GEE) and Python programming language. GEE was used for image acquisition and processing data of several indices, as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI) and Visible Atmospherically Resistant Index ( VARI). Regarding the geoprocessing of environmental factors, it was considered the following parameters: precipitation, temperature and soil moisture. Afterwards, NDVI was selected for a space-time analysis of the vineyard phenology, once this index represents a close dynamic to the vineyard biological cycle. From the relation between environmental factors and NDVI it was possible to interpret the space-time dynamics of the vineyard phenology. Finally, a spatial interpolation of yield and NDVI was made to understand the influence of NDVI in the yield. It can be assumed that the NDVI does not have a statistically significant influence on vineyard yield.