Abstract
Technological developments have had a major impact on the intensive use of electronic equipment, networked or connected to the internet, factors that have boosted the emergence and growth of cybercrime. Measures to mitigate and combat the phenomenon, taking into account its complexity and specificity, must involve all public entities with responsibility in the sector, in a global effort to promote digital literacy in the areas of cybersecurity and computer crime prevention. These comprehensive actions should use digital technologies based on artificial intelligence (AI), such as virtual assistants, whose characteristics allow the massification of information transmission, while enhancing the digital inclusion of users. Government entities are engaged in adopting technologies based on chatbots, with their presence in several areas of public administration. Despite the evolution, these resources have not yet been made available by the entities responsible for mitigating computer crime. On the other hand, although there are government programs aimed at increasing the digital skills of citizens, namely regarding the protection of devices, digital content or personal data, they are not designed for the specificities of cybercrime. In this context, a system based on chatbots, implemented in a digital governance context, by law enforcement agencies, with resources shared with other government entities can contribute to the prevention of cybercrime. © 2022 IEEE.

Abstract
This reference distills information about emerging technologies and applications for smart city design and sustainable urban planning. Chapters present technology use-cases that have radical novelty and high scalability with a prominent impact on community living standards. These technologies prepare urban and rural dwellings for the transformation to the smart world.Applications and techniques highlighted in the book use a combination of artificial intelligence and IoT technologies in areas like transportation, energy, healthcare, education, governance, and manufacturing, to name a few.The book serves as a learning resource for smart city design and sustainable infrastructure planning. Scholars and professionals who are interested in understanding ways for transforming communities into smart communities can also benefit from the cases presented in the book.

Abstract
Current developments in heat pumps, supported by innovative business models, are driving several industry sectors to take a proactive role in future district heating and cooling networks in cities. For instance, supermarkets and data centers have been assessing the reuse of waste heat as an extra source for the district heating network, which would offset the additional investment in heat pumps. This innovative business model requires complete deregulation of the district heating market to allow industrial heat producers to provide waste heat as an additional source in the district heating network. This work proposes the application of innovative market designs for district heating networks, inspired by new practices seen in the electricity sector. More precisely, pool and Peer-to-Peer (P2P) market designs are addressed, comparing centralized and decentralized market proposals. An illustrative case of a Nordic district heating network is used to assess the performance of each market design, as well as the potential revenue that different heat producers can obtain by participating in the market. An important conclusion of this work is that the proposed market designs are in line with the new trends, encouraging the inclusion of new excess heat recovery players in district heating networks.

Abstract
This work proposes an architecture to treat georeferenced data from the OpenStreetMap to plan routes. The methodology considers the following steps: collecting data, incorporating data into a data manager, importing data into a data model, executing routing algorithms, and visualizing routes. Our proposal incorporates the following features characterizing each street segment: safety & security, comfort, accessibility, air quality, time, and distance. Routes can be calculated considering any specified weighting system of these features. The outcome of the application of this architecture allows to calculate and visualize routes from georeferenced data, which can support researchers in the study of multi-criteria routes. Furthermore, this framework enhances the OSM data model adding a multi-criteria dimension for route planning.

Abstract
Neonatal sepsis is characterized by the system’s extreme response to an infection and persists as one of the biggest life-threatening diseases. The gold standard treatment is administrating an antibiotic, which, unfortunately, is often made too late. The diagnosis should be easier, faster, and achieved through non-invasive methods. Recently, entropy, a non-linear feature, has been applied to different physiological signals to detect diseases having very promising results. In this study, several entropy measures were applied to the breathing cycle duration (TTot) of the respiratory signals for 20 neonates. In total, 18 distinct methods of entropy were initially applied to 30-minute segments. Using Spearman’s correlation, it was detected strong correlation similarities between some of the measures. On the other hand, bubble, attention, phase, and spectral entropies were negatively correlated with all the other measures. To detect the presence of Sepsis, the slope of the multiscale entropy index was analyzed. Also, a changing point in the slope was probed, when possible, and then was applied linear regression to two subsets of data, before and after the changing point. Effectively, the Wilcoxon Sign Rank Test showed that the results for the total slope of the Sample, Corrected Conditional, Distribution, Permutation, Fuzzy, Gridded Distribution, Incremental, and Entropy of Entropy were statistically significant to infer that entropy decreases with time. Nonetheless, further work should confirm these results with a larger dataset that includes healthy and pathological neonates. © 2022 IEEE.

Abstract
Reasoning about spatial information is fundamental in natural language to fully understand relationships between entities and/or between events. However, the complexity underlying such reasoning makes it hard to represent formally spatial information. Despite the growing interest on this topic, and the development of some frameworks, many problems persist regarding, for instance, the coverage of a wide variety of linguistic constructions and of languages. In this paper, we present a proposal of integrating ISO-Space into a ISO-based multilayer annotation scheme, designed to annotate news in European Portuguese. This scheme already enables annotation at three levels, temporal, referential and thematic, by combining postulates from ISO 24617-1, 4 and 9. Since the corpus comprises news articles, and spatial information is relevant within this kind of texts, a more detailed account of space was required. The main objective of this paper is to discuss the process of integrating ISO-Space with the existing layers of our annotation scheme, assessing the compatibility of the aforementioned parts of ISO 24617, and the problems posed by the harmonization of the four layers and by some specifications of ISO-Space. © European Language Resources Association (ELRA).