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Publications

2024

Responsible Consumption and Production in the Context of Sustainable Cities

Authors
Almeida, F;

Publication
Advances in Electronic Government, Digital Divide, and Regional Development - Sustainable Smart Cities and the Future of Urban Development

Abstract
Municipalities are key players in their role as sustainable development planners and have a responsibility to change behavior at the local level. This study uses a panel of French municipalities to explore their role in promoting responsible consumption and production practices. A questionnaire was set up to obtain data from 186 citizens, of which 77 come from rural areas and 109 from urban zones. The findings reveal that French municipalities have a wide influence on the consumption and more responsible production of individuals through their actions. They encourage inhabitants to reduce energy and water consumption, waste management, and local and organic consumption. French citizens are mainly influenced by social and economic factors, while political and marketing factors are of little relevance. Furthermore, there are no differences in the importance and involvement of citizens in responsible consumption and production actions between rural and urban municipalities.

2024

Enhancing Cross-Modal Medical Image Segmentation Through Compositionality

Authors
Eijpe, A; Corbetta, V; Chupetlovska, K; Beets-Tan, R; Silva, W;

Publication
Lecture Notes in Computer Science - Deep Generative Models

Abstract

2024

Implications of seasonal and daily variation on methane and ammonia emissions from naturally ventilated dairy cattle barns in a Mediterranean climate: A two-year study

Authors
Rodrigues, ARF; Silva, ME; Silva, VF; Maia, MRG; Cabrita, ARJ; Trindade, H; Fonseca, AJM; Pereira, JLS;

Publication
SCIENCE OF THE TOTAL ENVIRONMENT

Abstract
Seasonal and daily variations of gaseous emissions from naturally ventilated dairy cattle barns are important figures for the establishment of effective and specific mitigation plans. The present study aimed to measure methane (CH4) and ammonia (NH3) emissions in three naturally ventilated dairy cattle barns covering the four seasons for two consecutive years. In each barn, air samples from five indoor locations were drawn by a multipoint sampler to a photoacoustic infrared multigas monitor, along with temperature and relative humidity. Milk production data were also recorded. Results showed seasonal differences for CH4 and NH3 emissions in the three barns with no clear trends within years. Globally, diel CH4 emissions increased in the daytime with high intra-hour variability. The average hourly CH4 emissions (g h-1 livestock unit- 1 (LU)) varied from 8.1 to 11.2 and 6.2 to 20.3 in the dairy barn 1, from 10.1 to 31.4 and 10.9 to 22.8 in the dairy barn 2, and from 1.5 to 8.2 and 13.1 to 22.1 in the dairy barn 3, respectively, in years 1 and 2. Diel NH3 emissions highly varied within hours and increased in the daytime. The average hourly NH3 emissions (g h-1 LU-1) varied from 0.78 to 1.56 and 0.50 to 1.38 in the dairy barn 1, from 1.04 to 3.40 and 0.93 to 1.98 in the dairy barn 2, and from 0.66 to 1.32 and 1.67 to 1.73 in the dairy barn 3, respectively, in years 1 and 2. Moreover, the emission factors of CH4 and NH3 were 309.5 and 30.6 (g day- 1 LU-1), respectively, for naturally ventilated dairy cattle barns. Overall, this study provided a detailed characterization of seasonal and daily gaseous emissions variations highlighting the need for future longitudinal emission studies and identifying an opportunity to better adequate the existing mitigation strategies according to season and daytime.

2024

Evaluating Constrained Users Ability to Interact with Virtual Reality Applications

Authors
Ribeiro, T; Henriques, PR; Oliveira, E; Rodrigues, NE;

Publication
2024 IEEE 12TH INTERNATIONAL CONFERENCE ON SERIOUS GAMES AND APPLICATIONS FOR HEALTH, SEGAH 2024

Abstract
This article introduces an immersive Virtual Reality (VR) application designed to assess the interaction capabilities of users with physical and cognitive limitations, including older adults and individuals with disabilities, as well as ICU patients. The VR application encompasses six tasks varying in complexity, each designed to evaluate different aspects of VR interaction skills, such as movements of the head, arms, and fingers, alongside more intricate activities like pick-and-place, pointing, and painting.The paper details the VR application's specifications, including its system architecture, deployment framework, and data structure. The application's efficacy was tested through three pilot studies in a retirement home setting. The analysis focused on examining correlations among various factors, including age, cognitive abilities (evaluated using the Mini-Mental Status Examination), and previous VR experience. The findings reveal significant correlations, illuminating the effects of age, cognitive capacity, and past VR interactions on task performance. The results emphasize the importance of accounting for user-specific attributes, prior experiences, and cognitive abilities in the design of VR-based therapeutic interventions.

2024

Automatic Food Labels Reading System

Authors
Pires, D; Filipe, V; Gonçalves, L; Sousa, A;

Publication
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Abstract
Growing obesity has been a worldwide issue for several years. This is the outcome of common nutritional disorders which results in obese individuals who are prone to many diseases. Managing diet while simultaneously dealing with the obligations of a working adult can be difficult. Today, people have a very fast-paced life and sometimes neglect food choices. In order to simplify the interpretation of the Nutri-score labeling this paper proposes a method capable of automatically reading food labels with this format. This method is intended to support users when choosing the products to buy based on the letter identification of the label. For this purpose, a dataset was created, and a prototype mobile application was developed using a deep learning network to recognize the Nutri-score information. Although the final solution is still in progress, the reading module, which includes the proposed method, achieved an encouraging and promising accuracy (above 90%). The upcoming developments of the model include information to the user about the nutritional value of the analyzed product combining it’s Nutri-score label and composition. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

2024

Performance evaluation and benchmarking to inform dispatching rules for hydropower plants

Authors
Barbosa, F; Casacio, L; Bacalhau, ET; Leitao, A; Guimaraes, L;

Publication
UTILITIES POLICY

Abstract
Hydropower currently generates more than all other renewable energies combined. Considering the challenges of climate change and the transition to green energy, it is expected to remain the world's largest source of renewable electricity generation. This paper proposes a tool for performance evaluation and benchmarking of hydropower generation to inform dispatching. Through them, strengths and weaknesses of asset operations can be set, identifying areas with the best performance, gathering insights from their strategies and best practices, and comprehending factors that lead to variations in performance levels. The results allow for optimising energy resource use by indicating the dispatching rules with maximum power production and minimum wearand-tear impact. This framework allows the formulation of practical guidelines for dispatching policies. The proposed methodology is applied to analyse two real-world case studies: the Vogelgr & uuml;n run of river hydropower plant (France) and the Frades 2 pump-storage powerplant (Portugal).

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