Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future

In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.The present work was developed under the EUREKA–ITEA3 Project CyberFactory#1 (ITEA-17032), co-funded by Project CyberFactory#1PT (ANI|P2020 40124), from FEDER Funds through NORTE2020 program and from National Funds through FCT under the project UID/EEA/00760/2019 and by the Federal Ministry of Education and Research (BMBF, Germany, funding No. 01IS18061C).info:eu-repo/semantics/publishedVersio

Emerging business models

Magretta (2002) suggests, using the example of American Express in the nineteenth century, that: " a successful business model represents a better way than the existing alternatives. It may offer more value to a discrete group of customers. Or it may completely replace the old way of doing things and become the standard for the next generation of entrepreneurs to beat". Adding substance with: "… all new business models are variations on the generic value chain underlying all businesses. Broadly speaking, this chain has two parts. Part one includes all the activities associated with making something: designing it purchasing raw materials, manufacturing and so on. Part two includes all the activities associated with selling something: finding and reaching customers, transacting a sale, distributing the product or delivering the service. A new business model's plot may turn on designing a new product for an unmet need … Or it may turn on a process innovation, a better way of making or selling or distributing an already.

Towards Active Evidence-Based Learning in Engineering Education:A Systematic Literature Review of PBL, PjBL, and CBL

Ajuts: This research was funded by The ECIU University project (project number 612521-EPP-1-2019-1-NL-EPPKA2-EUR-UNIV), co-funded by the ERASMUS+ Programme of the European Union.Implementing active learning methods in engineering education is becoming the new norm and is seen as a prerequisite to prepare future engineers not only for their professional life, but also to tackle global issues. Teachers at higher education institutions are expected and encouraged to introduce their students to active learning experiences, such as problem-, project-, and more recently, challenge-based learning. Teachers have to shift from more traditional teacher-centered education to becoming instructional designers of student-centered education. However, instructional designers (especially novice) often interpret and adapt even well-established methods, such as problem-based learning and project-based learning, such that the intended value thereof risks being weakened. When it comes to more recent educational settings or frameworks, such as challenge-based learning, the practices are not well established yet, so there might be even more experimentation with implementation, especially drawing inspiration from other active learning methods. By conducting a systematic literature analysis of research on problem-based learning, project-based learning, and challenge-based learning, the present paper aims to shed more light on the different steps of instructional design in implementing the three methods. Based on the analysis and synthesis of empirical findings, the paper explores the instructional design stages according to the ADDIE (analysis, design, development, implementation, and evaluation) model and provides recommendations for teacher practitioners