Value Creation with Extended Reality Technologies - A Methodological Approach for Holistic Deployments

Mit zunehmender Rechenkapazität und Übertragungsleistung von Informationstechnologien wächst die Anzahl möglicher Anwendungs-szenarien für Extended Reality (XR)-Technologien in Unternehmen. XR-Technologien sind Hardwaresysteme, Softwaretools und Methoden zur Erstellung von Inhalten, um Virtual Reality, Augmented Reality und Mixed Reality zu erzeugen. Mit der Möglichkeit, Nutzern Inhalte auf immersive, interaktive und intelligente Weise zu vermitteln, können XR-Technologien die Produktivität in Unternehmen steigern und Wachstumschancen eröffnen. Obwohl XR-Anwendungen in der Industrie seit mehr als 25 Jahren wissenschaftlich erforscht werden, gelten nach wie vor als unausgereift. Die Hauptgründe dafür sind die zugrundeliegende Komplexität, die Fokussierung der Forschung auf die Untersuchung spezifische Anwendungsszenarien, die unzu-reichende Wirtschaftlichkeit von Einsatzszenarien und das Fehlen von geeigneten Implementierungsmodellen für XR-Technologien. Grundsätzlich wird der Mehrwert von Technologien durch deren Integration in die Wertschöpfungsarchitektur von Geschäftsmodellen freigesetzt. Daher wird in dieser Arbeit eine Methodik für den Einsatz von XR-Technologien in der Wertschöpfung vorgestellt. Das Hauptziel der Methodik ist es, die Identifikation geeigneter Einsatzszenarien zu ermöglichen und mit einem strukturierten Ablauf die Komplexität der Umsetzung zu beherrschen. Um eine ganzheitliche Anwendbarkeit zu ermöglichen, basiert die Methodik auf einem branchen- und ge-schäftsprozessunabhängigen Wertschöpfungsreferenzmodell. Dar-über hinaus bezieht sie sich auf eine ganzheitliche Morphologie von XR-Technologien und folgt einer iterativen Einführungssequenz. Das Wertschöpfungsmodell wird durch ein vorliegendes Potential, eine Wertschöpfungskette, ein Wertschöpfungsnetzwerk, physische und digitale Ressourcen sowie einen durch den Einsatz von XR-Technologien realisierten Mehrwert repräsentiert. XR-Technologien werden durch eine morphologische Struktur mit Anwendungsmerk-malen und erforderlichen technologischen Ressourcen repräsentiert. Die Umsetzung erfolgt in einer iterativen Sequenz, die für den zu-grundeliegenden Kontext anwendbare Methoden der agilen Soft-wareentwicklung beschreibt und relevante Stakeholder berücksich-tigt. Der Schwerpunkt der Methodik liegt auf einem systematischen Ansatz, der universell anwendbar ist und den Endnutzer und das Ökosystem der betrachteten Wertschöpfung berücksichtigt. Um die Methodik zu validieren, wird der Einsatz von XR-Technologien in zwei industriellen Anwendungsfällen unter realen wirtschaftlichen Bedingungen durchgeführt. Die Anwendungsfälle stammen aus unterschiedlichen Branchen, mit unterschiedlichen XR-Technologiemerkmalen sowie unterschiedlichen Formen von Wert-schöpfungsketten, um die universelle Anwendbarkeit der Methodik zu demonstrieren und relevante Herausforderungen bei der Durch-führung eines XR-Technologieeinsatzes aufzuzeigen. Mit Hilfe der vorgestellten Methodik können Unternehmen XR-Technologien zielgerichtet in ihrer Wertschöpfung einsetzen. Sie ermöglicht eine detaillierte Planung der Umsetzung, eine fundierte Auswahl von Anwendungsszenarien, die Bewertung möglicher Her-ausforderungen und Hindernisse sowie die gezielte Einbindung der relevanten Stakeholder. Im Ergebnis wird die Wertschöpfung mit wirtschaftlichem Mehrwert durch XR-Technologien optimiert

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

The DeepHealth Toolkit: A key European free and open-source software for deep learning and computer vision ready to exploit heterogeneous HPC and cloud architectures

At the present time, we are immersed in the convergence between Big Data, High-Performance Computing and Artificial Intelligence. Technological progress in these three areas has accelerated in recent years, forcing different players like software companies and stakeholders to move quickly. The European Union is dedicating a lot of resources to maintain its relevant position in this scenario, funding projects to implement large-scale pilot testbeds that combine the latest advances in Artificial Intelligence, High-Performance Computing, Cloud and Big Data technologies. The DeepHealth project is an example focused on the health sector whose main outcome is the DeepHealth toolkit, a European unified framework that offers deep learning and computer vision capabilities, completely adapted to exploit underlying heterogeneous High-Performance Computing, Big Data and cloud architectures, and ready to be integrated into any software platform to facilitate the development and deployment of new applications for specific problems in any sector. This toolkit is intended to be one of the European contributions to the field of AI. This chapter introduces the toolkit with its main components and complementary tools, providing a clear view to facilitate and encourage its adoption and wide use by the European community of developers of AI-based solutions and data scientists working in the healthcare sector and others. iThis chapter describes work undertaken in the context of the DeepHealth project, “Deep-Learning and HPC to Boost Biomedical Applications for Health”, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825111.Peer Reviewed"Article signat per 19 autors/es: Marco Aldinucci, David Atienza, Federico Bolelli, Mónica Caballero, Iacopo Colonnelli, José Flich, Jon A. Gómez, David González, Costantino Grana, Marco Grangetto, Simone Leo, Pedro López, Dana Oniga, Roberto Paredes, Luca Pireddu, Eduardo Quiñones, Tatiana Silva, Enzo Tartaglione & Marina Zapater "Postprint (author's final draft

Misaligned Values in Software Engineering Organizations

The values of software organizations are crucial for achieving high performance; in particular, agile development approaches emphasize their importance. Researchers have thus far often assumed that a specific set of values, compatible with the development methodologies, must be adopted homogeneously throughout the company. It is not clear, however, to what extent such assumptions are accurate. Preliminary findings have highlighted the misalignment of values between groups as a source of problems when engineers discuss their challenges. Therefore, in this study, we examine how discrepancies in values between groups affect software companies' performance. To meet our objectives, we chose a mixed method research design. First, we collected qualitative data by interviewing fourteen (\textit{N} = 14) employees working in four different organizations and processed it using thematic analysis. We then surveyed seven organizations (\textit{N} = 184). Our analysis indicated that value misalignment between groups is related to organizational performance. The aligned companies were more effective, more satisfied, had higher trust, and fewer conflicts. Our efforts provide encouraging findings in a critical software engineering research area. They can help to explain why some companies are more efficient than others and, thus, point the way to interventions to address organizational challenges.Comment: accepted for publication in Journal of Software: Evolution and Proces

How to improve our understanding of group decision making with the help of artificial intelligence

Within science we primarily obtain knowledge of a specific field by reading the published results of theoretical and empirical studies. It is argued that this approach may lead to a biased and incomplete perspective of a research area. It is proposed to also use methods from Artificial Intelligence to elicit, model and use the knowledge of experts. It is expected that especially their heuristic knowledge is relevant for problem solving and consultancy applications. An illustrative example concludes the paper

AEOLIX Reference Book

This is a documentation on the AEOLIX Reference Book (ARB), a website created during the project to collect, highlight and present emerging trends, technologies and practices that are of interest to the problem domain of the project (http://reference.aeolix.eu). The purpose of this document is to present the content of the website

The impact of digital disruption in the maintenance service industry, in the oil and gas sector

Master's thesis in Technology and Operations managementThe industry is on the brink on what many consider as paradigm shift due to disruptive technological developments. The current trend of automation, Internet of things, big data analysis, cloud computing, together with the emergence of artificial intelligence, advanced robotics and autonomous vehicles has been labelled as a digital disruption. A combination of better computing power and data storage, together with more reasonable pricing structures makes the digital disruption more accessible and possible to any industry. There is broad consensus among think tanks, experts and industrial leaders that organization needs to embrace this development to stay relevant and competitive in the future. The thesis is an exploratory research to examine how the digital disruption will impact the maintenances service industry in the Oil and Gas sector. To understand the complexity of the transformation, it covers analysis of multiple elements that includes: expectations and semantics, technological solutions and services, changes in competences and skill sets, changes in business model and strategy, stakeholder perspective, and a summary of risk and opportunities. The research is conducted with a mixed-method approach, which covers quantitative survey data from global trends, together with qualitative case studies and interviews from relevant stakeholders in the industry. The research highlights that the digital disruption is more than a buzzword or an incremental change towards existing business models and practices. Digital technologies enable a whole new way to create and harness value, and is about to transform the nature of work tasks and future job requirements. Data driven technologies will require more digital literacy of the entire workforce, which puts an added pressure on training and development. Digital talents, such as data analysts and computer scientists are becoming more central to the business operations, and requires more cross-functional collaboration across the organization. Organizational structure and culture must adapt to a digital environment, where employees are empowered to make business decisions and initiate digital innovation efforts. The digital disruption will also reshape the organizational environment, which results in reshaping existing stakeholder relationships and the introduction of new ones. Change management is going to be key to succeed in the digital transformation, and viewing it as an opportunity rather than a threat will decide the fate of success for many organizations.publishedVersio