Browsing by Issue Date, starting with "2024-12-19"
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- Food and Tourism Nexus, challenges and opportunitiesPublication . Delgado, Amélia; Barateiro, Luísa; Rodriguez, Rosmel; Staszewska AnnaWe aim at examining the interplay between tourism trends and nutrition, based on the perspectives from multiple stakeholders. The question: “Can the tourism sector be leveraged to highlight local cultural identity and biodiversity, by promoting local and seasonal foods as distinctive assets?”, encloses political, economic, and environmental challenges. Key themes include the influence of tourism on local food habits and businesses, the spreading out of ultra-processed foods, and the role of digital platforms and social media in shaping food-tourism dynamics. Suggestions on strategies to encourage sustainable practices are sought after.
- An automation system for predictive maintenance of electric machines applied to pumping systemsPublication . Azinheira, Gonçalo José de Sousa; Semião, Jorge Filipe Leal CostaThis thesis presents the development and implementation of an automation system for predictive maintenance of electric machines in pumping systems. The work integrates Industry 4.0 technologies such as IoT devices, machine learning algorithms, and advanced sensor systems to enhance the reliability and efficiency of industrial operations. A complete test bench was developed, featuring an electric pump, water reservoir, automation and control board, energy meter, vibration sensors, pressure sensors, motorized valves, and temperature sensors, allowing automated test procedures including fault-injection behaviors through valve control. The research bridges the gap between theoretical models of predictive maintenance and their practical implementation in industrial environments, emphasizing the importance of automation and data-driven decision-making. The core achievements include the successful development and deployment of a system capable of real-time data acquisition, advanced vibration analysis, and fault prediction using machine learning. A detailed analysis was conducted to determine optimal data processing procedures prior to analysis, and automation-based sensors were integrated with electronic-based sensors in a unified predictive maintenance system. Machine learning algorithms demonstrated the feasibility of implementing predictive maintenance within standard automation pumping systems by successfully predicting faults induced in the test pump. The developed system not only reduces unexpected failures but also aligns with modern demandsfor sustainability and operational efficiency. By combining data acquisition, real-time analysis, and predictive modeling, the research offers a comprehensive approach that can be adapted across various industries reliant on electric machines.
- PT-PT synthetic speech detectionPublication . Santos, Rafael Geraldo dos; Oliveira, José Valente de; Sousa, Joana CoutinhoRecent developments in the field of artificial intelligence (AI) have led to the creation of powerful generative models. These models have demonstrated such capabilities that it becomes nearly impossible for a human to distinguish between generated and human utterances, between synthetic and natural speech. A relatively recent example of this fact is the deepfake video of former U.S. President Barack Obama [1]. This video not only serves as a demonstration of the capabilities of AI models but also highlights the potential for misinformation, as these models can deceive individuals into believing in fabricated scenarios. This extends to the realm of synthetic speech, where models like Google Duplex [2], leveraging WaveNet technology, a deep neural network for seamless speech creation, exhibit an impressive degree of realism and naturalness. For this reason, two situations may arise. The first is related to new business opportunities, such as the creation of realistic voiceovers for films and animations or enhancement in the communication for individuals with hearing or speech impairments [3]. The other, raises concerns about privacy and security since voice impersonation is easily achievable with today’s tools. Given this fact, an analysis of approaches applied in the ASVspoof challenge [4] was carried on. The ultimate goal is to develop a system capable of distinguishing between real voices and cloned voices, by adapting the research done on this chal lenge to the portuguese from Portugal (PT-PT) language. For this purpose, we first created a PT-PT dataset using both text-to-speech (TTS) and speech-to-speech (STS). Then, we employed and implemented some models from the literature and tested in several datasets that encompass both english and PT-PT voices, to evaluate their per formance and reach conclusions. From this, we found out that while this is a difficult task, by augmenting the data with different impulse response devices (IRs) and com pressions codecs, there was an improvement in the generalization to different attacks from different datasets. Overall, after the evaluation process the best models found through statistical anal ysis were the ResNet-OC and ECAPA-TDNN. Being our goal tailored to PT-PT, by fine-tuning them, we further improved their performance. At the end future steps are highlighted, one of which may be very important to complement the work made so far, which is the integration of the fraud detection component
- On the function of MOB proteins in cell division and developmentPublication . Blekastad, Oda Frøydis; Tavares, Álvaro Augusto Marques; Baião, InêsThis thesis investigates the essential functions of MOB proteins in various cellular processes, focusing on mitosis and spermiogenesis. By employing a combination of genetic techniques and molecular biology approaches in Drosophila melanogaster and human cells, we have elucidated some critical roles of MOB proteins in these processes. Our findings demonstrate the involvement of MOB proteins in chromosome segregation during mitosis, highlighting their importance in maintaining genomic stability. Additionally, we have identified their subcellular localization during Drosophila spermiogenesis, suggesting its potential roles in sperm development. Furthermore, this study has revealed the association of MOB protein dysfunction with disease phenotypes, including micronucleation, multinucleation, and infertility. These findings underscore the significance of MOB proteins in human health and provide potential avenues for future research and therapeutic interventions. In conclusion, this thesis further advances our knowledge of the essential functions of MOB proteins and their implications for cellular processes. Future studies can expand upon these findings to develop a more comprehensive understanding of MOB protein biology and explore their potential as therapeutic targets.