Abstract
Enterprise Architecture (EA) is a coherent set of principles, methods, and models that express the structure of an enterprise and its IT landscape. EA mining uses data mining techniques to automate EA modelling tasks. Ontologies help to define concepts and the relationships among these concepts to describe a domain of interest This work presents an extensible ontology for EA mining focused on extracting architectural models that use logs from an API gateway as the data source. The proposed ontology was developed using the OntoUML language to ensure its quality and avoid anti-patterns through ontology rule checks. Then, a hypothesized scenario using data structures close to the real is used to simulate the ontology application and validate its theoretical feasibility as well as its contribution to the Enterprise Architecture Management field. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

Abstract
The application of machine learning (ML) algorithms to electronic health records (EHR) data allows the achievement of data-driven insights on various clinical problems and the development of clinical decision support (CDS) systems to improve patient care. However, data governance and privacy barriers hinder the use of data from multiple sources, especially in the medical field due to the sensitivity of data. Federated learning (FL) is an attractive data privacy-preserving solution in this context by enabling the training of ML models with data from multiple sources without any data sharing, using distributed remotely hosted datasets. The Secur-e-Health project aims at developing a solution in terms of CDS tools encompassing FL predictive models and recommendation systems. This tool may be especially useful in Pediatrics due to the increasing demands on Pediatric services, and the current scarcity of ML applications in this field compared to adult care. Herein we provide a description of the technical solution proposed in this project for three specific pediatric clinical problems: childhood obesity management, pilonidal cyst post-surgical care and retinography imaging analysis.

Abstract
This study seeks to assess the academic community's knowledge and perception of open innovation. While the so-called closed innovation is rooted in the discourse of future managers, open innovation, being a relatively recent paradigm, may be an unknown form of innovation and therefore its potential is underused. What is the perception of open innovation among students and faculty at a private Portuguese university? The technical procedure was based on a survey, and 64 responses were obtained (the population corresponds to 3666 people). It was shown that the theme of open innovation, despite being recognized in the academic world, is still little known in the community. Although Portugal is a country of meager funds for innovation, which should lead to a greater focus on open innovation, this may not be happening due to the lack of trust in strangers that exists culturally in Portugal, and that may be currently hindering open innovation partnerships. Finally, in order to identify possible relationships between gender and perceptions regarding open innovation, we applied the chi-square test of independence (X-2) in relation to gender. This exploratory study verified the existence of gender equality regarding the variables analyzed on open innovation.

Abstract
The emergence of the COVID-19 pandemic required swift adaptations within public spaces, particularly in view of the uncertainties enveloping the transmission dynamics of the virus. Among the prominently contacted surfaces, door handles have garnered significant attention in research efforts aiming to curtail transmission risks. A notable proposition emerged to obviate the necessity of direct physical contact with handles, thereby introducing a novel approach. Thus, the manufacturing modality of three-dimensional (3D) printing was naturally embraced, primarily attributable to its expeditious prototyping capabilities. Although the extant literature and the open-source community have proffered diverse panaceas, this inquiry embarked on rectifying certain inadequacies that had afflicted antecedent methodologies. Elaborate exposition is provided pertaining to the progression of the developmental trajectory and the concomitant design refinements. In a bid to substantiate the efficaciousness of the produced solution, the finite element analysis (FEA) was judiciously employed to assess two distinct loading scenarios: during the installation phase and the subsequent operation of the contrivance. The empirical findings manifest the commendable load tolerance, with the proposed solution being capable of withstand forces exceeding 15 N. Furthermore, even under the most adverse circumstances, the device evinced a maximal displacement of 15 mm. Collectively, the corollaries borne out of this scholarly investigation corroborate the efficacy, utilitarian functionality, and ergonomic viabilities of the proposed solutions and manufacturing process. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Abstract

Abstract
Over the past few decades, road transportation emissions have increased. Vehicles are among the most significant sources of pollutants in urban areas. As such, several studies and public policies emerged to address the issue. Estimating greenhouse emissions and air quality over space and time is crucial for human health and mitigating climate change. In this study, we demonstrate that it is feasible to utilize raw GPS data to measure regional pollution levels. By applying feature engineering techniques and using a microscopic emissions model to calculate vehicle-specific power (VSP) and various specific pollutants, we identify areas with higher emission levels attributable to a fleet of taxis in Porto, Portugal. Additionally, we conduct network analysis to uncover correlations between emission levels and the structural characteristics of the transportation network. These findings can potentially identify emission clusters based on the network's connectivity and contribute to developing an emission inventory for an urban city like Porto.