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Publications

2021

A Kolmogorov Complexity for multidisciplinary domains

Authors
S. Resende, J; Almeida, M; Martins, R; Antunes, L;

Publication
Proceedings of Entropy 2021: The Scientific Tool of the 21st Century

Abstract

2021

Automatic detection of Flavescense Dorée grapevine disease in hyperspectral images using machine learning

Authors
Silva, DM; Bernardin, T; Fanton, K; Nepaul, R; Pádua, L; Sousa, JJ; Cunha, A;

Publication
Procedia Computer Science

Abstract
The technological revolution that we have been witnessing recently has allowed components miniaturization and made electronic components accessible. Hyperspectral sensors benefited from these advances and could be mounted on unmanned aerial vehicles, which was unthinkable until recently. This fact significantly increased the applications of hyperspectral data, namely in agriculture, especially in the detection of diseases at an early stage. The vineyard is one of the agricultural sectors that has the most to gain from the use of this type of data, both by the economic value and by the number of diseases the plants are exposed to. The Flavescense dorée is a disease that attacks vineyards and may conduct to a significant loss. Nowadays, the detection of this disease is based on the visual identification of symptoms performed by experts who cover the entire area. However, this work remains tedious and relies only on the human eye, which is a problem since sometimes healthy plants are torn out, while diseased ones are left. If the experts think they have found symptoms, they take samples to send to the laboratory for further analysis. If the test is positive, then the whole vine is uprooted, to limit the spread of the disease. In this context, the use of hyperspectral data will allow the development of new disease detection methods. However, it will be necessary to reduce the volume of data used to make them usable by conventional resources. Fortunately, the advent of machine learning techniques empowered the development of systems that allow better decisions to be made, and consequently save time and money. In this article, a machine learning approach, which is based on an Autoencoder to automatically detect wine disease, is proposed.

2021

Volunteer engagement: drivers and outcomes on non-profits' co-creation of value

Authors
Matos, M; Fernandes, T;

Publication
INTERNATIONAL REVIEW ON PUBLIC AND NONPROFIT MARKETING

Abstract
Engagement plays a key role for most organizations. Establishing close relationships with consumers and other stakeholders - thus promoting their loyalty and participation in the value creation process - has become an element of competitive advantage. Extant literature has focused consumer-brands relationships in commercial contexts; yet, when it comes to non-commercial or non-profit contexts - where communities of decidedly engaged individuals voluntarily invest their time and energy to a cause - research is still in its infancy. This study sets out to understand how non-profit organizations (NPO) can generate a sense of engagement among volunteers and which volunteers' behaviours - associated with that psychological state - entice value co-creation with NPO. Group interviews were carried out with volunteers to gain insights on drivers and outcomes of Volunteer Engagement (VE). Value congruence between volunteers and NPO, a sense of community, as well as perceptions of competence and autonomy, were identified as drivers of VE. The study further validated the impact of VE not only on somewhat predictable outcomes, such as NPO loyalty and advocacy, but also on the co-creation of value with NPO through the recruitment of new volunteers and the development of new ideas for service innovation.

2021

Investigation on the role of elevated gamma radiation in ion production during precipitation

Authors
Chen, X; Barbosa, S; Paatero, J; Kulmala, M; Junninen, H;

Publication

Abstract
<p>Air ions are ubiquitous in the atmosphere. These charge carriers can be found in various forms as charged molecules, nanoclusters as well as aerosol particles. The population of air ions normally concentrates in the cluster size range (0.8 – 1.7 nm in mobility equivalent diameters) in the absence of particle formation processes. A concentration burst in the intermediate size range (1.7 – 7 nm) can be typically observed during atmospheric new particle formation (NPF) and in precipitation episodes <sup>1</sup>. Contrary to the intermediate ions formed during NPF that favour growth to larger sizes, intermediate ion bursts resulting from precipitation tend to shrink <sup>2,3</sup>. The production of intermediate ions during precipitation has been attributed to the Lenard effect and they are usually referred to as the balloelectric ions <sup>3</sup>.</p><p>During precipitation the rain-out and wash-out of radon progeny increase the gamma dose at ground level <sup>4</sup>. Being a type of ionising radiation, gamma creates positive and negative charges in the air. These charges are either lost in recombination or transformed into air ions. It is therefore interesting to understand whether the precipitation-associated elevation in gamma radiation plays any role in forming or neutralising the balloelectric ions. At SMEAR II station in Hyytiälä, Finland <sup>5</sup>, we have conducted measurements of air ions, gamma radiation, precipitation together with other meteorological parameters. A similar establishment of the measurement set stands also at SMEAR Estonia station in Jarvseljä, Estonia <sup>6</sup>. The data collected at Hyytiälä from 2017.7 to 2018.8 show that the intermediate ion concentration correlates with rainfall only when the precipitation intensity is greater than 1 mm/h. For milder rainfall with the precipitation intensity being 0.1-1 mm/h, the intermediate ion concentration increases with an increase in the gamma counts. The work is under progress and we intend to extend the analysis to Jarvseljä data for a comprehensive understanding of the observations.</p><p>Acknowledgements: This work received financial supports from European Regional Development Fund (project MOBTT42) under the Mobilitas Pluss programme and from Estonian Research Council project PRG714.</p><p>References:</p><p>1. Tammet, H., Komsaare, K. & Hõrrak, U. Intermediate ions in the atmosphere. Atmospheric Research <strong>135-136</strong>, 263-273, doi:10.1016/j.atmosres.2012.09.009 (2014).</p><p>2. Hõrrak, U. et al. Formation of Charged Nanometer Aerosol Particles Associated with Rainfall: Atmospheric Measurements and Lab Experiment. Report Series in Aerosol Science <strong>80</strong>, 180-185 (2006).</p><p>3. Tammet, H., Hõrrak, U. & Kulmala, M. Negatively charged nanoparticles produced by splashing of water. Atmos. Chem. Phys. <strong>9</strong>, 357–367 (2009).</p><p>4. Paatero, J. & Hatakka, J. Wet deposition efficiency of short-lived radon-222 progeny in central Finland. Boreal Env. Res. <strong>4</strong>, 285-293 (1999).</p><p>5. Hari, P. & Kulmala, M. Station for measuring ecosystem-atmosphere relations (SMEAR II). Boreal Environ. Res. <strong>10</strong>, 315-322 (2005).</p><p>6. Noe, S. M. et al. SMEAR Estonia: Perspectives of a large-scale forest ecosystem – atmosphere research infrastructure. Forestry Studies <strong>63</strong>, doi:10.1515/fsmu-2015-0009 (2015).</p>

2021

Post-Quantum Authentication with Lightweight Cryptographic Primitives

Authors
Faria, H; Valença, JM;

Publication
IACR Cryptol. ePrint Arch.

Abstract

2021

Service operation vessels for offshore wind farm maintenance: Optimal stock levels

Authors
Neves Moreira, F; Veldman, J; Teunter, RH;

Publication
RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Abstract
Service operation vessels are becoming the dominant mode for the maintenance of most offshore wind farms. To minimize turbine downtime, it is essential to bring the right components to the wind farm, while budget and volume constraints prohibit having excess inventories on board. This setting can be interpreted as a repair kit problem, which seeks to define a set of components that may be necessary for on-site maintenance operations in a given time period during which emergency resupply is costly. Current repair kit problem approaches however, do not cater sufficiently for some of the characteristics of offshore wind farm maintenance, including weather-dependent deterioration and the possibility to perform emergency resupplies. We propose mixed-integer programming models both to determine (tactical model) and validate (operational model) repair kits when maintenance operations are performed under different weather conditions. The models are flexible enough to be used with real world data considering multiple turbines composed of different deteriorating components, service operation vessels characteristics (speed and volumetric capacity), different weather conditions, and emergency resupplies. An important feature of this approach is its ability to consider detailed maintenance and vessel routing operations to test and validate repair kits in realistic wind farm environments. We provide valuable insights on the composition of repair kits and on relevant business indicators for a set of different scenarios. The practical implications are that repair kits should be adapted depending on weather forecasts and that considerable downtime reductions can be achieved by allowing emergency resupplies. © 2021 The Author(s)

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