Abstract
The Portuguese population is aging at an increasing rate, which introduces new problems, particularly in rural areas, where the population is small and widely spread throughout the territory. These people, mostly elderly, have low income and are often isolated and socially excluded. This work researches and proposes an affordable Ambient Assisted Living (AAL)-based solution to monitor the activities of elderly individuals, inside their homes, in a pervasive and non-intrusive way, while preserving their privacy. The solution uses a set of low-cost IoT sensor devices, computer vision algorithms and reasoning rules, to acquire data and recognize the activities performed by a subject inside a home. A conceptual architecture and a functional prototype were developed, the prototype being successfully tested in an environment similar to a real case scenario. The system and the underlying concept can be used as a building block for remote and distributed elderly care services, in which the elderly live autonomously in their homes, but have the attention of a caregiver when needed.

Abstract
Dyscalculia is a specific neurological affliction that disrupts a person's ability to understand and manipulate numbers. We intend to develop a serious game for children who attend primary school (up to 4th grade) and whose purpose is making the learning of basic mathematics (simple arithmetic) easier, by introducing specific mathematical problems and educational games that stimulate memory, among other aspects. To that end, we undertook a straightforward and preliminary evaluation of the serious game developed and present its results. Indeed, we believe that the findings of our pilot case study can be useful to determine some perceptions that may be vital to understanding the problems with teaching mathematics and the issues students face in this regard.

Abstract
In this paper, a new framework for accurate reliability analysis is proposed based on improving the directional simulation by using metaheuristic algorithms. Usually for highly nonlinear and complex performance functions, finding the unit vector direction requires very high calculations or impossible practically. Hence, the novel improved version incorporates the Harris Hawks Optimization algorithm, where the unit vector of direction is formulated as a constrained optimization problem and estimated using metaheuristic algorithms. Given that metaheuristic algorithms have been introduced to solve unconstrained problems, the penalty function method is used to convert the constrained problem into an unconstrained problem. The applicability of the proposed framework is firstly tested on five highly nonlinear benchmark functions and then applied to solve four high-dimensional engineering problems. The performance of six simulations-based reliability analysis methods and the first-order reliability method were compared with the proposed method. Besides the feasibility of other metaheuristic algorithms were investigated. The results show high-performance abilities of the improved version of the directional simulation for solving highly nonlinear engineering problems.

Abstract
Mobile devices, as smartphones and tablets, have presented an exponential growth, being part of our everyday life, particularly considering children [1]. Their daily habits are undoubtedly influenced by technology and the applications they use can affect socialization and learning processes [2]. Specifically, games are the most popular type of applications and have the potential to change attitudes and behaviours. Emphasizing the importance of this area, we decided to create a serious game that stimulates the children' responsibility for taking care of pets while they play, called My Buddy. In this paper, we present the development and assessment process of a 3D serious game, where the user is asked to interact with a pet and nurture it. The interface was developed based on the universal design philosophy, presenting itself attractive to children without disabilities, but also accessible to children with visual or motor disabilities. As such, we present a multimodal interface based on touch and speech commands. The game was tested in terms of usability, with a heuristic evaluation, and the results obtained highlight the potential of such interfaces.

Abstract
This research aims at investigating which web accessibility and usability tools, with the focus on the ones that warrant automation, are available to assess the quality of interfaces for people with disabilities and/or special needs, enabling them to navigate and interact with web and mobile apps. Our search strategy identified 72 scientific articles of the most rated conferences and scientific journals, from which 16 were considered for the systematic literature review (SLR). We found that, despite the existence of various tools either for web or mobile apps, they are not completely effective, covering less than 40% of all the problems encountered. Also, no tool was found capable of adapting the application interfaces according to the type of disabilities that users may present. Therefore, a new tool could be a welcome advancement to provide full accessible and usable experiences.

Abstract
In Portugal, the dropout rate of university courses is around 29%. Understanding the reasons behind such a high desertion rate can drastically improve the success of students and universities. This work applies existing data mining techniques to predict the academic dropout mainly using the academic grades. Four different machine learning techniques are presented and analyzed. The dataset consists of 331 students who were previously enrolled in the Computer Engineering degree at the Universidade de Tras-os-Montes e Alto Douro (UTAD). The study aims to detect students who may prematurely drop out using existing methods. The most relevant data features were identified using the Permutation Feature Importance technique. In the second phase, several methods to predict the dropouts were applied. Then, each machine learning technique's results were displayed and compared to select the best approach to predict academic dropout. The methods used achieved good results, reaching an Fl-Score of 81% in the final test set, concluding that students' marks somehow incorporate their living conditions.