Abstract
Europe's position in the current cloud market needs to be improved. This market is currently dominated by non-European players by 75%, shaping the way that Europe is deploying and using cloud services. Although these players are bound to laws and regulations of foreign powers, such as PR China and USA, generating legitimate concerns for the EU, its businesses and citizens. EU's digital future resides on having installed secure, high-quality data processing capacity. This can only be offered by cloud services both centrally and at the edge. In this context NOUS's ambition is completely in line with the European Strategy for data as aims to create the foundations for a European Cloud Service which exploits the HPC network and tackles specific-to-the-EU-economy requirements as well as leverages different data spaces (Mobility, Energy, Green Deal and Manufacturing).

Abstract
Climate change is causing the emergence of new pest species and diseases, threatening economies, public health, and food security. In Europe, olive groves are crucial for producing olive oil and table olives; however, the presence of the olive fruit fly (Bactrocera Oleae) poses a significant threat, causing crop losses and financial hardship. Early disease and pest detection methods are crucial for addressing this issue. This work presents a pioneering comparative performance study between two state-of-the-art object detection models, YOLOv5 and YOLOv8, for the detection of the olive fruit fly from trap images, marking the first-ever application of these models in this context. The dataset was obtained by merging two existing datasets: the DIRT dataset, collected in Greece, and the CIMO-IPB dataset, collected in Portugal. To increase its diversity and size, the dataset was augmented, and then both models were fine-tuned. A set of metrics were calculated, to assess both models performance. Early detection techniques like these can be incorporated in electronic traps, to effectively safeguard crops from the adverse impacts caused by climate change, ultimately ensuring food security and sustainable agriculture. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

Abstract
Immersive Virtual Reality (iVR) is a promising educational tool for learning a second/foreign language. However, interactive iVR studies remain in their infancy, with more research required to validate what and how it can be implemented. This study focuses on the English listening dimension and evaluates the impact of a realistic interactive iVR compared to traditional listening exercises. The results were favourable and indicated that interactive iVR positively impacts the users' knowledge retention compared to a traditional listening approach. Likewise, the users revealed a preference for using iVR for learning when compared to traditional listening exercises, as well as higher user satisfaction with the iVR experiment.

Abstract
This paper presents a study comparing different user interface modes (Controller-Based Selection, Object Interaction, and Voice Recognition) within immersive Virtual Reality (iVR) environments for foreign language learning. Given the rapid advancements and potential of iVR in education, there is a need for focused research on optimising user interfaces for effective learning experiences. This study aimed to identify optimal interfaces for integrating iVR applications as complementary educational tools while gauging student preferences. Participants engaged in interactive learning tasks across the three conditions, with assessments focused on System Usability, Presence, User Satisfaction, Cybersickness, Learning Outcomes, and Task Duration. Findings indicate high usability across all conditions, with a preference observed for Controller-Based Selection and Object Interaction. Object Interaction showed strong motivational appeal but required more time to complete tasks than Controller-Based. Therefore, for time-constrained educational settings, the Controller-Based Selection interface is practical due to its lower physical effort requirement. Despite recent advances, our study found Voice Recognition interaction to be the least preferred interaction method, indicating a need for further technological improvements to boost its acceptance and effectiveness in educational contexts.

Abstract
Over the years, various immersive virtual training environments (iVTEs) have been developed, allowing companies to start transitioning to Virtual Reality (VR) technologies to train their personnel. This transition forces companies to start using game engines as a foundation to develop such iVTEs, which also requires a multidisciplinary team. When developing such training environments, challenges on how to present tasks to users arise. The way these tasks are presented can dictate the efficacy of the VR training application. This paper presents three different task presentation methodologies (avatar animation, videos, and instruction manual) and assesses them using 36 participants, divided into those three groups. Usability, sense of presence, satisfaction, cybersickness, and technology acceptance variables were studied and results indicated that only the total number of actions performed had differences between groups where the instruction manual reported the higher number of actions (usability) when compared to the other conditions. Therefore it was concluded that the instruction manual proved to be where users kept losing focus and making more actions. It was also concluded that all conditions had a similar sense of presence, satisfaction, cybersickness, and acceptance scores.

Abstract
Cybersickness refers to the negative symptoms caused by exposure to a Virtual Reality (VR) experience. The literature is consensual that cybersickness is a key factor in an experience, as the non-existence of cybersickness provides an optimal virtual experience. Thus, it is of utmost importance to evaluate cybersickness when assessing VR applications to understand the impact of this factor on the user experience and, ultimately, on the VR application viability. However, there is a lack of Portuguese instruments to evaluate this variable. To tackle this, this aimed to translate and validate the Simulator Sickness Questionnaire (SSQ) to Portuguese so it can be used with the Portuguese population and maintain its psychometric properties. The new instrument was validated using a sample of 603 Portuguese subjects aged between 16 and 79. Based on the observed results, the obtained theoretical model shows that the Portuguese version of the SSQ is valid for properly evaluating cybersickness in VR experiences with Portuguese samples.