Abstract
Mild is a smart stress relief solution created by DSTRS, an European Project Semester student team enrolled at the Instituto Superior de Engenharia do Porto in the spring of 2022. This paper details the research performed, concerning ethics, marketing, sustainability and state-of-the-art, the ideas, concept and design pursued, and the prototype assembled and tested by DSTRS. The designed kit comprises a bracelet, pair of earphones with case, and a mobile app. The bracelet reads the user heart beat and temperature to automatically detect early stress signs. The case and mobile app command the earphones to play sounds based on the user readings or on user demand. Moreover, the case includes a tactile distractor, a scent diffuser and vibrates. This innovative multi-sensory output, combining auditory, olfactory, tactile and vestibular stimulus, intends to sooth the user. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
Web 2.0 platforms, like wikis and social networks, rely on crowdsourced data and, as such, are prone to data manipulation by ill-intended contributors. This research proposes the transparent identification of wiki manipulators through the classification of contributors as benevolent or malevolent humans or bots, together with the explanation of the attributed class labels. The system comprises: (i) stream-based data pre-processing; (ii) incremental profiling; and (iii) online classification, evaluation and explanation. Particularly, the system profiles contributors and contributions by combining features directly collected with content- and side-based engineered features. The experimental results obtained with a real data set collected from Wikivoyage – a popular travel wiki – attained a 98.52% classification accuracy and 91.34% macro F-measure. In the end, this work seeks to address data reliability to prevent information detrimental and manipulation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
The latest technological advances drive the emergence of countless real-time data streams fed by users, sensors, and devices. These data sources can be mined with the help of predictive and classification techniques to support decision-making in fields like e-commerce, industry or health. In particular, stream-based classification is widely used to categorise incoming samples on the fly. However, the distribution of samples per class is often imbalanced, affecting the performance and fairness of machine learning models. To overcome this drawback, this paper proposes Bplug, a balancing plug-in for stream-based classification, to minimise the bias introduced by data imbalance. First, the plug-in determines the class imbalance degree and then synthesises data statistically through non-parametric kernel density estimation. The experiments, performed with real data from Wikivoyage and Metro of Porto, show that Bplug maintains inter-feature correlation and improves classification accuracy. Moreover, it works both online and offline. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
Intensive cattle farming as a means of protein production contributes with the direct emission of greenhouse gases and the indirect contamination of soil and water. The public awareness towards this issue is growing in western cultures, leading to the stagnation of meat consumption and to the willingness to adopt alternative sustainable sources of protein. A solution is to farm insects as they present a reduced environmental impact and constitute a well-known source of protein. However, for westerners, eating insects implies a cultural change as they are still seen as dirty and disgusting. In 2022, a team of five EPS@ISEP students chose to design a solution for this problem followed by the assembly and test of the corresponding proof-of-concept prototype. They decided to design a home farming kit to grow mealworms driven by ethical, sustainable and the market needs. Exploring the insect life-cycle, the kit provides protein for humans and animals, chitin for soil bacteria and frass for plants. It can also be used as an educational tool for children to learn about sustainability, social responsibility and insect life-cycles, helping to overtake the cultural barrier against insect eating from a young age. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Abstract
Tourists nowadays tend to avoid tourist traps and are looking for engaging ways to explore cities in the limited time they have. Standard options to explore cities seldom offer a combination between efficiency and fun. Furthermore, a search for an exploration city app returns an unlimited supply of lookalike websites and apps, all claiming to be the best. This paper reports the development of QRioCity, an efficient and exciting way to explore cities, by the “Dragonics” student team. QRioCity offers users the option to sign up for a playful tour through the city of Porto using a public kiosk with an interactive touchscreen. There is no limit to the number of teams playing simultaneously nor there is need to provide personal data. The teams are led through the city using clues and are proposed assignments, like scanning QR codes, to earn points. At the end of the game, every team receives discount coupons for local shops or stores depending on their score, even when they play alone. This way QRioCity helps tourists enjoying the local city life while offering municipalities a chance to strengthen their local economy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.