The role of wireless communications in guaranteeing safe and resource-efficient intelligent transportation systems (ITS) is of great significance. With the advent of a new technological epoch in cellular network development, various novel technical solutions are being considered as key enablers for future 5G-beyond and 6G networks. In this position paper, we identify and discuss three key pillars in the wireless network evolution that we suppose to be the foundation for the practical deployment of mass ITS. We first show how edge-located solutions may help in data delivery, next we present the role of the integrated communications and sensing paradigm (ICAS) in vehicular communications, and finally, we concentrate on advances in cellular-based sidelink communications.
This work proposes an educational scenario of game-based learning. The scenario is based on a novel serious game, that gets high school students acquainted with the Sustainable Development Goals (SDGs) and promotes the development of their computational thinking skills. Game-based learning is built upon collaborative problem solving and evolves around an interactive story augmented with small quests/inquiries. Students work together to navigate the serious game on the SDGs. As students complete SDGs-related quests/inquiries, the story evolves. The challenge is a game expansion with custom settings (backdrops/avatars) that will take place in Scratch, allowing students to differentiate their learning path. For the game, that was developed in Scratch visual programming environment, this works suggests an educational scenario and indicative student activities for hybrid (synchronous and asynchronous) education. Using the Flipped Classroom instructional strategy, the scenario starts asynchronously, unfolds synchronously, and is completed asynchronously. The proposed serious game follows the guided discovery method for the acquaintance with the SDGs and the accompanying educational scenario aims for students to acquire the required programming skills to develop a small interactive application on the SDGs. Through game expansion challenge students hone their programming skills in a purposeful and entertaining way. An evaluation by students concludes the work.
Sustainable development denotes the enhancement of living standards in the present without compromising future generations’ resources. Sustainable Development Goals (SDGs) quantify the accomplishment of sustainable development and pave the way for a world worth living in for future generations. Scholars can contribute to the achievement of the SDGs by guiding the actions of practitioners based on the analysis of SDG data, as intended by this work. We propose a framework of algorithms based on dimensionality reduction methods with the use of Hilbert Space Filling Curves (HSFCs) in order to semantically cluster new uncategorised SDG data and novel indicators, and efficiently place them in the environment of a distributed knowledge graph store. First, a framework of algorithms for insertion of new indicators and projection on the HSFC curve based on their transformer-based similarity assessment, for retrieval of indicators and load-balancing along with an approach for data classification of entrant-indicators is described. Then, a thorough case study in a distributed knowledge graph environment experimentally evaluates our framework. The results are presented and discussed in light of theory along with the actual impact that can have for practitioners analysing SDG data, including intergovernmental organizations, government agencies and social welfare organizations. Our approach empowers SDG knowledge graphs for causal analysis, inference, and manifold interpretations of the societal implications of SDG-related actions, as data are accessed in reduced retrieval times. It facilitates quicker measurement of influence of users and communities on specific goals and serves for faster distributed knowledge matching, as semantic cohesion of data is preserved.
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