Abstract

Abstract
Currently, Unmanned Aerial Vehicles (UAVs) are considered in the development of various applications in agriculture, which has led to the expansion of the agricultural UAV market. However, Nano Aerial Vehicles (NAVs) are still underutilised in agriculture. NAVs are characterised by a maximum wing length of 15 centimetres and a weight of fewer than 50 g. Due to their physical characteristics, NAVs have the advantage of being able to approach and perform tasks with more precision than conventional UAVs, making them suitable for precision agriculture. This work aims to contribute to an open-source solution known as Nano Aerial Bee (NAB) to enable further research and development on the use of NAVs in an agricultural context. The purpose of NAB is to mimic and assist bees in the context of pollination. We designed this open-source solution by taking into account the existing state-of-the-art solution and the requirements of pollination activities. This paper presents the relevant background and work carried out in this area by analysing papers on the topic of NAVs. The development of this prototype is rather complex given the interactions between the different hardware components and the need to achieve autonomous flight capable of pollination. We adequately describe and discuss these challenges in this work. Besides the open-source NAB solution, we train three different versions of YOLO (YOLOv5, YOLOv7, and YOLOR) on an original dataset (Flower Detection Dataset) containing 206 images of a group of eight flowers and a public dataset (TensorFlow Flower Dataset), which must be annotated (TensorFlow Flower Detection Dataset). The results of the models trained on the Flower Detection Dataset are shown to be satisfactory, with YOLOv7 and YOLOR achieving the best performance, with 98% precision, 99% recall, and 98% F1 score. The performance of these models is evaluated using the TensorFlow Flower Detection Dataset to test their robustness. The three YOLO models are also trained on the TensorFlow Flower Detection Dataset to better understand the results. In this case, YOLOR is shown to obtain the most promising results, with 84% precision, 80% recall, and 82% F1 score. The results obtained using the Flower Detection Dataset are used for NAB guidance for the detection of the relative position in an image, which defines the NAB execute command.

Abstract
O Exame Nacional de Desempenho de Estudantes (ENADE) compõe uma das bases avaliativas do Sistema Nacional de Avaliação da Educação Superior e tem como principal propósito, avaliar o rendimento dos estudantes a partir da sua formação nos cursos de graduação. Por isso, este trabalho identificou a possibilidade de se basear nesses resultados para aprimorar os processos de ensino-aprendizagem. Para tanto, este artigo apresenta o planejamento, criação e avaliação de uma plataforma de aprendizagem Web responsiva, baseada no ENADE e que utiliza elementos de gamificação com o propósito de aumentar o engajamento dos estudantes. O software foi avaliado, por meio de questionários de aceitação tecnológica, aplicados com 38 usuários e que apresentou resultados promissores, com média geral de 4,71 entre 5 pontos possíveis.

Abstract
Indoor Air Quality (IAQ) pertains to the air quality within a specific space and is directly linked to the well-being and comfort of its occupants. In line with this objective, this research presents a real-time system dedicated to monitoring and predicting IAQ, encompassing both thermal comfort and gas concentration. The system initiates with a data acquisition, wherein a set of sensors captures environmental parameters and transmits this data for storage in a database. The measured parameters are analyzed by a neural network algorithm that predicts anomalies based on historical data. The neural network model generated predictions from 75.9% to 98.1% (depending on the parameter) of precision during regular situations. After that, a test with smoke in the same place was done to validate the model, and the results showed it could detect anomalies. Finally, prediction data are stored in a new database and displayed on a dashboard for monitoring in real-time measured and prediction data. © 2023 IEEE.

Abstract
It is important to properly test developed software because this may contribute to fewer bugs going unreported in deployed software. Often, little attention is spent on the topic of software testing in curricula, yielding graduate students without adequate preparation to deal with the quality standards required by the industry. This problem could be tackled by introducing bite-sized software testing education capsules that allow teachers to introduce software testing to their students in a less time-consuming manner and with a hands-on component that will facilitate learning. In order to design appropriate software testing educational tools, it is necessary to consider both the software testing needs of the industry and the cognitive models of students. This work-in-progress paper proposes an experimental design to gain an understanding of the cognitive strategies used by students during test case design based on real-life cases. Ultimately, the results of the experiment will be used to develop educational support for teaching software testing.

Abstract
Inclusive mobility represents an essential component of the smart and sustainable mobility ecosystem. Moreover, smart parking has gained greater importance given the vital contribution to reducing the carbon footprint. However, currently, existing solutions are not yet inclusive as they do not include the required information for the comfort and safety of people with reduced mobility, for whom the time it takes to park the vehicle is sometimes not the most important factor when compared to the suitability of the parking space considering the displacement objectives. The main contribution of this paper is a conceptual and technological architecture for an inclusive and real-time solution for parking assistance in a small urban environment. The architecture uses a crowd-sourcing approach, a Geographic Information System, a set of external APIs, the GPS, and a mobile solution for interaction with the citizen. The solution will be built from a previous work developed in the city of Viana do Castelo in Portugal and intends to be evaluated by the Sustainable Urban Mobility Indicators (SUMI) proposed by the European Commission.