Abstract
The digital society’s portrait involves being daily connected to the Internet, at home, at work and in the social life. But seniors do not feel this need, despite this need is increasing as everything around them is online. So, seniors take a change on web browsing, without being aware of the it is dangers, from the theft of personal data, fake news, or online frauds. Therefore, the investigation promotes a Serious Game that exposes these insecure digital situations by challenges to a group of seniors from a network of senior universities. Web Segura is an online educational game developed on the WordPress platform and with challenges of the H5P plugin. © 2023, University of Algarve Research Centre for Arts and Communication. All rights reserved.

Abstract
Anomaly detection in the industrial context, identifying defective products and their categorization, is a prevalent task. It is aimed to acknowledge if training and testing multilabel classification models on textures to deploy on an MCU is possible. The focus is deploying lightweight models on MCUs, performing a multilabel classification on textures for industrial usage. For this purpose, a Systematic Literature Review was conducted, which allows knowing the commonly used machine learning models in industrial products anomaly detection and what methods are used to defect detection on textures. Through the Systematic Literature Review, was possible to understand the range of different and combined methods, the methods used in multilabel classification, the most common hyper-parametrizations and popular inferences engines to train machine-learning models to deploy on MCUs, and some techniques applied to overcome the restricted resources of memory and inference time associated with MCUs. © 2024 Elsevier B.V.. All rights reserved.

Abstract
Enterprise Architecture (EA) is a coherent set of principles, methods, and models that express the structure and behavior of an enterprise and its IT landscape. EA mining uses data mining techniques to automate EA models' extraction. Ontologies help to define concepts and the relationships among these concepts to describe a domain of interest. This paper presents an extensible ontology for EA mining to extract models using Application Program Interface (API) log files as the data source. The ontology development follows the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) and uses OntoUML 2.0 language to ensure its expressiveness and readability. To validate its theoretical feasibility and contribution to EA modeling, it presents a simulation of the ontology application through a controlled scenario using data structures similar to an industrial case. Then, the ontology is verified and validated, checking quality ontology criteria using specialized tools for syntactic and semantic model checking, which also aids in avoiding ontology anti-patterns.

Abstract
A significant concern that is widely discussed in the field of Higher Education is declining student participation. In several institutions, attendance is optional, allowing students to attend lectures at their convenience. This study proposes the integration of Artificial Intelligence and Gamification to improve student engagement and attendance rates. The initiative combines advanced technological strategies with conventional educational methodologies to enhance the lecture experience. The initiative is significant as formal lectures often witness dwindling student interest and frequent absenteeism, undermining the educational process and student's future career prospects. This combination has the potential to revolutionise Higher Education by providing a more interactive and engaging learning experience. While gamification has positively impacted learning in various contexts, integration with Artificial Intelligence is a game-changer, paving the way for a modernised educational experience. This innovative exploration of the AI-gamification blend sets the stage for future research and the implementation of updated academic strategies, ultimately addressing student engagement and attendance. This position paper presents the bases and foundations for understanding the problem of student attendance and engagement and the role of AI and gamification in Higher Education in alleviating it.;Uma inquietação relevante e extensamente discutida no domínio do Ensino Superior é a diminuição da participação dos estudantes. Em diversas instituições, a assiduidade é facultativa, permitindo aos estudantes a frequência às aulas segundo a sua disponibilidade. Este estudo propõe a integração da Inteligência Artificial e da Gamification como meios para melhorar o envolvimento e as taxas de assiduidade dos estudantes. A iniciativa em causa articula estratégias tecnologicamente avançadas com metodologias educativas convencionais no intuito de enriquecer a experiência de ensino. Tal iniciativa assume importância dada à constante diminuição do interesse dos estudantes e a assiduidade irregular nas aulas formais, fatores que afetam negativamente o processo de ensino e as perspetivas de carreira dos estudantes. Esta combinação ostenta o potencial de revolucionar o Ensino Superior, proporcionando uma experiência de aprendizagem mais interativa e envolvente. Embora a Gamification já tenha impactado positivamente o processo de aprendizagem em diversos contextos, a sua integração com a Inteligência Artificial surge como um elemento transformador, abrindo caminho para uma experiência educacional modernizada. Esta investigação inovadora que combina a IA e Gamification prepara as bases para investigações futuras e a implementação de estratégias académicas aprimoradas, concentrando-se principalmente no envolvimento e na assiduidade dos estudantes. Este artigo de posicionamento apresenta as bases e os fundamentos necessários para a compreensão do problema da frequência e envolvimento dos estudantes no Ensino Superior, assim como o papel da IA e da Gamification na sua mitigação.

Abstract
Cybercrime is growing rapidly, and it is increasingly important to use advanced tools to combat it and support investigations. One of the battlefronts is the forensic investigation of mobile devices to analyze their misuse and recover information. Mobile devices present numerous challenges, including a rapidly changing environment, increasing diversity, and integration with the cloud/IoT. Therefore, it is essential to have a secure and reliable toolbox that allows an investigator to thwart, discover, and solve all problems related to mobile forensics while deciphering investigations, whether criminal, civil, corporate, or other. In this work, we propose an original and innovative instantiation of a structure in a forensic toolbox for mobile devices, corresponding to a set of different applications, methods, and best practice information aimed at improving and perfecting the investigative process of a digital investigator. To ensure scientific support for the construction of the toolbox, the Design Science Research (DSR) methodology was applied, which seeks to create new and unique artifacts, drawing on the strength and knowledge of science and context. The toolbox will help the forensic investigator overcome some of the challenges related to mobile devices, namely the lack of guidance, documentation, knowledge, and the ability to keep up with the fast-paced environment that characterizes the mobile industry and market. © 2024 by the authors. Licensee ESJ, Italy.

Abstract
Business Process Automation has been gaining increasing importance in the management of companies and organizations since it reduces the time needed to carry out routine tasks, freeing employees for other, more creative and exciting things. It can be applied in the most varied business areas. Organizations from any sector of activity can also adopt it. Given these benefits, the granted success in transforming business processes would be expected. However, automation initiatives still fail. Adopting this technology can raise social, technological, ethical, methodical, and organizational issues. These facts have triggered the necessity for a summary that could extract more information about how to implement Business Process Automation (BPA), attending to the administrative processes, especially when applied in Small and Medium-sized Enterprises (SMEs). This study aims not only to review the available literature on how to implement BPA but also to typify the processes that can be automated, which technologies or tools exist for making that change, and influence factors in the procedure of BPA. We have covered more than 300 research papers published between 2016 and 2023 in reputable scientific data sources like Scopus, Web of Science/Clarivate, and ScienceDirect/Elsevier. The review revealed some paths for BPA, with some common steps. In addition, some common process characteristics fundamental to automation are exposed, as well as factors that are critical to an organization for successful automation. The results indicate that BPA is an established area in Business Process Management related to technologies/tools like Robotic Process Automation (RPA) or Cognitive-Robotic Process Automation (C-RPA), Workflow Management Systems (WfMS), Enterprise Resource Planning (ERP), and Blockchain. As far as we observed, this Systematic Literature Review (SLR) is a unique study that covers all the environmental variables for applying automation in business processes.