Generative artificial intelligence is currently used for disparate purposes, including education, particularly concerning STEM disciplines, among which Mathematics is prominent. Given the importance of both mathematical and digital skills in the world today, it is useful to inquire about the impact of this novel AI form on the didactics in Mathematics, by considering it in conjunction with accustomed technologies for more effectiveness. A survey directed at more than 60 teachers instructing at military academies and universities in several European Union Member States allows us to investigate the relationship between using generative AI and performing certain teaching choices under the methodological domain. Furthermore, we assessed the tandem between AI and traditional digital tools, both as a feature itself and in terms of repercussions on the methodologies instructors adopted. Quantitative analyses of scaled responses, performed by means of both descriptive and inferential statistics, are considered along with reflections on the qualitative answers, in the spirit of a mixed methods approach. As main outcome, we found that teachers’ use of generative AI is associated with paying more attention to specific mathematical skills during lectures, and with using teaching practices possessing a solid methodological base. Additionally, we detected interesting insights concerning integration with the use of other digital tools, resulting in instructing practices being favored by both kinds of technology, thus confirming AI as a complementary tool, rather than a replacement. The study was conducted within the framework of the DIMAS project, an international initiative aimed at deepening learners’ interest in Mathematics and taking advantage of digital tools to provide students with more manageable mathematical problems and applications.

Mathematical and digital skills are recognized as key competencies for lifelong learning. In Mathematics education, identifying appropriate methodologies and tools to increase motivation and engagement is crucial, particularly in interdisciplinary contexts such as security and defence. Through a survey administered to 2,000 students and teachers at military academies and universities in several European Member States, this study investigates the role of technology in promoting students' motivation to learn Mathematics in this field, including non-STEM majors. The research also examines the perceived effectiveness of various teaching methodologies and digital tools in teaching Mathematics from different perspectives. The study follows a mixed methods approach, combining quantitative and qualitative analyses of the responses to the survey through statistical inference techniques. Findings indicate that digital tools positively impact students’ perception of Mathematics, supporting self-assessment and interactive problem-solving. Additionally, both students and instructors favor practical methodologies such as problem-solving, learning by doing, and collaborative learning, while the integration of gamification and AI-based tools remains limited. The results contribute to a deeper understanding of best practices for teaching and learning Mathematics in security and defence contexts and provide insights for future research in other interdisciplinary and applied fields. Our analysis took place in accordance with international partners from the European project DIMAS, which aims at increasing interest in studying Mathematics in the field of security and defence and at providing more understandable Mathematics problems and Mathematics applications using digital tools.

Real-Time Location Systems (RTLS) have become very popular in recent years. These systems provide a contemporary layer of automation named automatic object location detection. Location measurements involve the transmission and reception of signals between hardware components of a system. A RTLS consists of at least two separate hardware components: a signal transmitter and a measuring unit. The positioning of the components in the monitored area is of great importance (regarding both location accuracy and resources required). This work presents the development of 3D software that can simulate the installation of a RTLS network in a virtual representation of the real world, helping in the decision making for the setup of such a network. The software utilizes a modified site survey algorithm, specifically developed to suit the needs of RTLS. Furthermore, it is capable of identifying the distance between two wireless nodes and the type and size of obstacles between them (walls, furniture, reflecting surfaces) calculating their effect on the formation of the network.

The earth surface and human activities are interrelated in a complicated manner, and therefore it is somehow difficult to be monitored and managed. On this context it is required to develop effective directives of policies for environmental protection and management. In order to exploit context in imagery, a methodological approach employed data processing techniques was proposed in this work This approach was applied on a LANDSAT-TM satellite image and other digital geo-data (such as scanned geologic maps, topographic maps, etc) of a selected study area in Greece. The proposed scheme generally consisted of the following stages: (1) remote sensing methods and analysis for extracting the required thematic information to be used as input data and (2) fuzzy representation of the intrinsic land cover classes in the geodata through an object-oriented knowledge base design. The inherent land cover classes were represented by their intrinsic spectral and geometric attributes, texture, spatial context and association and fuzzy membership functions.