Unveiling Emotions: Attitudes Toward Affective Technology

With its ability to sense and/or generate human emotions, affective computing calls for a new generation of technology. This study brings affective technologies into focus which can sense human emotions. Compared to other types of technology, affective technologies have distinct characteristics—anthropomorphism, uncontrollability, capturing of highly sensitive data, unfamiliarity, and complexity—with fundamental effects on the interaction with humans. These characteristics of affective technology create a feeling of uncertainty about how such a system works. However, the attitudes people exhibit toward the usage, notably trust, such as affective assistance systems has received only scant attention. Hence, we define attitudes toward affective technology and contribute to the literature by proposing a research model that we analyzed using a quantitative methodology with 303 participants. From the theoretical model, we derive implications for theory, practice, and design

Reference and Affect: What role in computation and the neurosciences

Twenty First Century computational neuroscience and Twenty First Century psychoanalysis have two very different ways of representing the mental life of the subject, each with its own merits and limitations. This paper performs a superimposition of Peircean semiotics onto André Green’s model of unconscious representation. The idea of reference in Peirce (distinct from representation) can be better understood in light of how affect emerges from the unconscious according to Green. The mental representation, according to Greene, is accompanied by a quantum of affect. From this I construct a theory of reference: the role of affect within mental representation is what we can describe as the “feeling” of reference. While this is primarily a contribution to linguistics or semiotic theory, it could also be used to think about how the sciences consider their objects of knowledge—in this case the mental life of the subject. Perhaps the most relevant example is the application of neuroscience to computing and in particular “affective computing”, the computational recognition of human emotion

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