Abstract
Tensor-based models emerged only recently in modeling and analysis of the spatiotemporal road traffic data. They outperform other data models regarding the property of simultaneously capturing both spatial and temporal components of the observed traffic dataset. In this paper, the nonnegative tensor decomposition method is used to extract traffic patterns in the form of Speed Transition Matrix (STM). The STM is presented as the approach for modeling the large sparse Floating Car Data (FCD). The anomaly of the traffic pattern is estimated using Kullback–Leibler divergence between the observed traffic pattern and the average traffic pattern. Experiments were conducted on the large sparse FCD dataset for the most relevant road segments in the City of Zagreb, which is the capital and largest city in Croatia. Results show that the method was able to detect the most anomalous traffic road segments, and with analysis of the extracted spatial and temporal components, conclusions could be drawn about the causes of the anomalies. Results are validated by using the domain knowledge from the Highway Capacity Manual and achieved a precision score value of more than 90%. Therefore, such valuable traffic information can be used in routing applications and urban traffic planning.

Abstract
Robots are currently deployed in safety-critical domains but proper techniques to assess the functional safety of their software are yet to be adopted. This is particularly critical in ROS, where highly configurable robots are built by composing third-party modules. To promote adoption, we advocate the use of lightweight formal methods, automatic techniques with minimal user input and intuitive feedback. This paper proposes a technique to automatically verify system-wide safety properties of ROS-based applications at static time. It is based in the formalization of ROS architectural models and node behaviour in Electrum, over which system-wide specifications are subsequently model checked. To automate the analysis, it is deployed as a plug-in for HAROS, a framework for the assessment of ROS software quality aimed at the ROS community. The technique is evaluated in a real robot, AgRob V16, with positive results.

Abstract
The aim of this chapter focuses on featuring firmed IoT architecture paradigms and advocating, knowingly in concrete use cases, the combined use of such architecture categories. It is common knowledge that the growing demand for embedded processing, interconnection, and integration facilities in everyday objects is being driven by a multitude of IoT projects. The smart cities, smart agriculture, manufacturing, and industrial automation areas are some of the most important application grounds. Equally important is the medical sector where specially framed in this publication, the personal home healthcare scenarios gain enormous relevance due to the potential of IoT technology application. It is also becoming clear that the IoT-trending efforts are compelling researchers into the concurrent combination of multiple IoT-computing architecture types or paradigms, to know: wide-range cloud-computing architectures, local-spread fog-computing architectures, and spottily scattered edge-computing architectures. This chapter focuses on identifying the major goals and benefits of each of these architectures classes; describing the relevant state of the art projects, which apply such architecture categories in home healthcare settings; and finally, pinpointing our own experience with home e-health demonstrative use case scenarios, where the benefits of using each of these architecture types become evident, and the concurrent combination of such IoT architectures inevitable. © 2021 Elsevier Inc.

Abstract
In this paper, we present TIV.lib, an open-source library for the content-based tonal description of musical audio signals. Its main novelty relies on the perceptually-inspired Tonal Interval Vector space based on the Discrete Fourier transform, from which multiple instantaneous and global representations, descriptors and metrics are computed-e.g., harmonic change, dissonance, diatonicity, and musical key. The library is cross-platform, implemented in Python and the graphical programming language Pure Data, and can be used in both online and offline scenarios. Of note is its potential for enhanced Music Information Retrieval, where tonal descriptors sit at the core of numerous methods and applications.

Abstract
This paper describes the design and development of a Smart Companion Pillow, named bGuard, designed by a multinational and multidisciplinary team enrolled in the European Project Semester (EPS) at Instituto Superior de Engenharia do Porto (ISEP) in the spring of 2019. Nowadays, parents spend most of the day at work and become naturally worried about the well-being of their young children, specially babies. The aim of bGuard is to provide a 24-hour remotely accessible baby monitoring service, contributing to reduce parenting stress. The team, based on the survey of related products, as well as on marketing, sustainability, ethics and deontology analyses, developed a remotely interactive Smart Companion Pillow to monitor the baby's health and room air quality. The collected data, once it is saved on an Internet of Things (IoT) platform, becomes remotely accessible. The bGuard pillow, thanks to its shape, reduces the risk of the baby rolling from back to tummy, lowering the risk of Sudden Infant Death Syndrome (SIDS).

Abstract
The case study is a widely used method in qualitative research. Although defining the case study can be simple, it is complex to develop its strategy. Furthermore, it is still often not considered to be a sufficiently robust research strategy in the education field because it does not offer well-defined and use well-structured protocols. One of the most frequent criticisms associated with the case study approach is its low validity and reliability. In this sense, this study aims to concisely explore the main difficulties inherent to the process of developing a case study, also attempting to suggest some practices that can increase its reliability, construct validity, internal and external validity.