Abstract

Abstract
A anorexia nervosa é uma perturbação mental que afeta diferentes áreas da vida do indivíduo, impactando o seu bem-estar físico, social e mental. A população-alvo desta doença são jovens. Os jogos são atrativos para estes, e tem recentemente havido um crescimento no uso de jogos como ferramentas de apoio ao tratamento de diferentes doenças mentais. Porém, a prevenção e tratamento da anorexia nervosa possui poucos jogos que contemplem a complexidade da doença. Neste contexto, este resumo refere-se a uma tese de doutoramento que propõe o desenvolvimento de princípios para o design de jogos para a prevenção e tratamento da anorexia nervosa.

Abstract
Centro de Reabilitacao Profissional de Gaia (CRPG) is a Portuguese public association that promotes the social, educational, occupational, and rehabilitation aspects of people with disabilities. The CRPG project presented in this paper is directly related to the Rehabilitation and reintegration of labor accidents and occupational diseases (RAC/LCA) victims. The solution presented in this paper heavily relied on user research of the institution's procedures and the patients themselves. Their habits, goals, needs, and mental models allowed a better understanding of the heterogeneity of patient's injuries, which usually affected memory, motion, and cognition in different ways and severity. The User Centered-Design methodological approach also encompasses a comparative analysis of mobile applications in Google Play and Apple App Store related to disabilities and features some main features identified by CRPG; interviews with patients and with CRPG stakeholders; personas and contextual scenarios development, requirements, and features definition, workflow, wireflows, lo and high fidelity prototype, formative evaluation with end users. The usability and accessibility test results suggest the viability and efficacy of multiple interaction modalities in improving the accessibility of the application, ensuring a broader reach to the CRPG community with future implications as good practices in the inclusiveness of applications in other contexts.

Abstract
Language-guided generative models are increasingly used in audiovisual production. Image diffusion allows for the development of video sequences and some of its coordination can be established by text prompts. This research automates a video production pipeline leveraging CLIP-guidance with longform text inputs and a separate text-to-speech system. We introduce a method for producing frame-accurate video and audio summaries using a virtual timeline and document a set of video outputs with diverging parameters. Our approach was applied in the production of the film Irreplaceable Biography and contributes to a future where multimodal generative architectures are set as underlying mechanisms to establish visual sequences in time. We contribute to a practice where language modelling is part of a shared and learned representation which can support professional video production, specifically used as a vehicle throughout the composition process as potential videography in physical space.

Abstract
Currently, distributed software systems have evolved at an unprecedented pace. Modern software-quality requirements are high and require significant staff support and effort. This study investigates the use of a supervised machine learning model, a Multi-Layer Perceptron (MLP), for anomaly detection in microservices. The study covers the creation of a microservices infrastructure, the development of a fault injection module that simulates application-level and service-level anomalies, the creation of a system monitoring dataset, and the creation and validation of the MLP model to detect anomalies. The results indicate that the MLP model effectively detects anomalies in both domains with higher accuracy, precision, recovery, and F1 score on the service-level anomaly dataset. The potential for more effective distributed system monitoring and management automation is highlighted in this study by focusing on service-level metrics such as service response times. This study provides valuable information about the effectiveness of supervised machine learning models in detecting anomalies across distributed software systems.

Abstract
Information and Communication Technologies are driving the improvement of industrial processes. According to the Industry 4.0 (I4.0) paradigm, digital systems provide real-time information to humans and machines, increasing flexibility and efficiency in production environments. Based on the I4.0 Design Principles concept, Virtual Assistants can play a vital role in processing production data and offer contextualized and real-time information to the workers in the production environment. This systematic review paper explored Virtual Assistant applications in the context of I4.0, discussing the Technical Assistance Design Principle and identifying the characteristics, services, and limitations regarding Virtual Assistant use in the production environments. The results showed that Virtual Assistants offer Physical and Virtual Assistance. Virtual Assistance provides real-time contextualized information mainly for support, while Physical Assistance is oriented toward task execution. Regarding services, the applications include integration with legacy systems and static information treatment. The limitations of the applications incorporate concerns about information security and adapting to noisy and unstable environments. It is possible to assume that the terminology of Virtual Assistants is not standardized and is mentioned as chatbots, robots, and others. Besides the worthy insights of this research, the small number of resulting papers did not allow for generalizations. Future research should focus on broadening the search scope to provide more-significant conclusions and research possibilities with new AI models and services, including the emergent Industry 5.0 concept.