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

Abstract
Objective: The present investigation aims to identify the explanatory factors for academic satisfaction, as well as the influence that the identified factors have on the degree of academic satisfaction in its global context and on the chances of the institution's recommendation to friends and family.   Method: The investigation was conducted with a sample of 290 students from the Federal Institute of Education, Science, and Technology of Piauí (FIEPI-Campus Oeiras). The instrument used for data collection was a questionnaire. The statistical techniques used were of a descriptive, exploratory, and multivariate nature for the treatment, analysis, and validation of the results.   Results and Discussion: The results indicate that Academic Satisfaction is determined by the factors (1) Teaching Environment and (2) Structural Environment and that there is a significant decrease in Academic Satisfaction when students move from the group from High School to Higher Education due to the determinants satisfaction.   Research Implications: The development of strategies for the maintenance and attraction of new students by FIEPI-Campus Oeiras and other educational institutions must be based on academic satisfaction considering their specificities, namely, concerning the different perceptions and expectations generated by students about educational services.   Originality/Value: The relevance of this investigation is based on the fact that the measurement of student satisfaction by a given educational institution becomes essential for it to understand the perception of its students about its products and services, enabling the identification of new ways of generating satisfaction and loyalty.

Abstract
The progressive and complex nature of Parkinson's disease (PD) may largely benefit from regular and personalised monitoring, which is beyond the current clinical practice and routinely available systems. This paper proposes a simple and effective system to address this issue by using a wearable device to quantify a key PD's motor symptom - gait impairment as a proof-of-concept for a future broader approach. In this study, 60 inertial signals were collected from the ankle in 41 PD patients during a clinical standard gait assessment exercise. Each exercise iteration was classified by a specialised neurologist based on the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). A signal processing and feature extraction pipeline was employed to characterise gait, followed by a statistical analysis of their ability to differentiate between the 5 levels of impairment. The results revealed that 4 of the 8 studied features exhibited high discriminatory power between different severity levels of gait impairment, with statistical significance. The distinguishing capability of these 4 extracted features - gait consistency, rotation angle, mean height and length of steps - holds great promise for the development of a gait severity quantification remote monitoring for PD patients at home or on the move, proving the concept of the usefulness of wearable devices for regular and personalised PD symptom monitoring.

Abstract
Manufacturing industry is experiencing another revolution towards the digitalization of industrial processes. Different value chain actors must share specific and sensitive data according to business and data requirements. Digital architectures must ensure seamless and comprehensive communications between actors according to agreed-upon vocabularies. The digital representation of machines and other types of equipment, including crucial information about their static and dynamic operational data, is made possible by the ontological modelling of Asset Administration Shells (AAS), which is proposed in this paper as modular and semantically interoperable resources. These Cognitive Digital Twins are herein defined with de facto domain ontologies that model the semantics of the current operation, status and configurations of assets. This paper reports a proof-of-concept technical implementation that demonstrates an innovative digital architecture that connects and communicates active and modular Digital Twin of a machine in a bi-directional, connecting this asset to a digital manufacturing service provider.