Abstract
The constant stream of news nowadays highlights the necessity for meticulous assessment to ensure that the information accurately reaches its intended audience with the least amount of delay least delay. Despite the flexibility and efficiency of Deep Learning (DL) models, their intricate training and substantial resource demands pose significant challenges for their deployment in real-time applications. In this regard, this study evaluates the performance of resource-efficient Machine Learning (ML) techniques – Multinomial Naive Bayes (MNB), Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR) – in categorizing news. Based on the results, all the evaluated models attain a commendable level of accuracy in news categorization. Notably, the SVM excels, achieving an accuracy rate of 98% and a mean squared error of 0.28. This performance exemplifies the robust effectiveness of classical ML models in the categorization of news, particularly when enhanced by a suitably tailored preprocessing pipeline. © 2024, Universidade do Porto - Faculdade de Engenharia. All rights reserved.

Abstract
Fintech has revolutionized the financial sector, providing a new way of providing banking services. Since Fintech can provide the same services as traditional banks but entirely online, it is a competitor. As a result, consumers' relationships with banking have inevitably changed, and it is therefore relevant to analyze these changes. The main objective of this study is to understand people's perceptions of Fintech, their level of knowledge about it, and the impact of its emergence on traditional banking. The study sample consisted of 174 participants. A quantitative methodology was used to test the hypotheses formulated. The results show that participants who know about Fintech and perceive it as safe have a greater intention of changing banks. On the other hand, they perceive that supervision and regulation in traditional banks is higher than in Fintech. Among the reasons for becoming a Fintech customer, the most mentioned were lower costs and the fact that they provide greater convenience and ease of use. It will be in Fintech's interest to continue working with regulators so that the sector makes progress in this area and consumers can recognize greater equality between traditional banks and Fintech in the future.

Abstract
Customer value is influenced by several factors, which impose major challenges to global Supply Chains (SCs) and their management. This study aims to understand how companies tackle these challenges by focusing their global SC management on major strategies and supporting practices. Based on customer value theory, and recognising major trends affecting what end consumers value, we identify four global SC strategies: customer-driven, service-driven, resource-efficient, and closed-loop. A multiple case study carried out in eleven companies in the consumer goods industry explores the practices adopted per each SC strategy in managing global sourcing, production, and distribution networks. Results show the key requirement of selecting tailored practices for SC management that align with the context and the value expected by customers. Operational SC practices entail managing collaborative actions both up and downstream and competing with other SCs and can benefit from the implementation of appropriate digital technologies for customer value creation and delivery, as well as for continuous learning about customer needs.

Abstract
Due to the complementarity of renewable energy sources, there has been a focus on technology hybridization in recent years. In the area of hybrid offshore power plants, the current research projects mostly focus on the combinational implementation of wind, solar, and wave energy technologies. Accordingly, considering the already existing offshore wind farms, there is the potential for the implementation of hybrid power plants by adding wave energy converters and floating photovoltaics. In this work, a stochastic sizing model is developed for the hybridization of existing offshore wind farms using wave energy converters and floating photovoltaics considering the export cable capacity limitation. The problem is modeled from an investor perspective to maximize the economic profits of the hybridization, while the costs and revenues regarding the existing units and the export cable are excluded. Furthermore, to tackle the uncertainties of renewable energy generation, as well as the energy price, a scenario generation method based on copula theory is proposed to consider the dependency structure between the different random variables. Altogether, the hybridization study is modeled in a mixed integer linear programming optimization framework considering the net present value of the project as the objective function. The results showed that hybrid-sources-based energy generation provided the highest economic profit in the studied cases in the different geographical locations. Furthermore, the technical specifications of the farms have also been considerably improved providing more stable energy generation, guaranteeing a minimum level of power in a high share of the time, and with a better utilization of the capacity of the cable while the curtailment of energy is maintained within the acceptable range.

Abstract
Some of the fundamental activities of the software development process relate to the discipline of Requirements Engineering. Their objectives are to discover, analyze, document, verify and manage the requirements that will be part of the software. The requirements are the system's characteristics, which are identified based on information provided by users or experts in the field. The effective management of this information is essential to ensure that the system meets the needs of those who will use it. Considering that the requirements are information, we carried out research to propose a framework contemplating a set of tools used by the information management to assist the requirements management process's activities. This article aims to present the FIRMa - Framework based on Information Management to Requirements Management, and the results of an evaluation carried out by a group of eighteen specialists in Requirements Engineering, who gave their opinion about the tools contemplated by the framework, as well as defined steps and the guidelines elaborated for its use. The evaluation results showed that FIRMa could contribute to the requirements management process's activities and increase the project's chances of success.

Abstract