Meta-KANSEI modeling with Valence-Arousal fMRI dataset of brain

Background: Traditional KANSEI methodology is an important tool in the field of psychology to comprehend the concepts and meanings; it mainly focusses on semantic differential methods. Valence-Arousal is regarded as a reflection of the KANSEI adjectives, which is the core concept in the theory of effective dimensions for brain recognition. From previous studies, it has been found that brain fMRI datasets can contain significant information related to Valence and Arousal. Methods: In this current work, a Valence-Arousal based meta-KANSEI modeling method is proposed to improve the traditional KANSEI presentation. Functional Magnetic Resonance Imaging (fMRI) was used to acquire the response dataset of Valence-Arousal of the brain in the amygdala and orbital frontal cortex respectively. In order to validate the feasibility of the proposed modeling method, the dataset was processed under dimension reduction by using Kernel Density Estimation (KDE) based segmentation and Mean Shift (MS) clustering. Furthermore, Affective Norm English Words (ANEW) by IAPS (International Affective Picture System) were used for comparison and analysis. The data sets from fMRI and ANEW under four KANSEI adjectives of angry, happy, sad and pleasant were processed by the Fuzzy C-Means (FCM) algorithm. Finally, a defined distance based on similarity computing was adopted for these two data sets. Results: The results illustrate that the proposed model is feasible and has better stability per the normal distribution plotting of the distance. The effectiveness of the experimental methods proposed in the current work was higher than in the literature. Conclusions: mean shift can be used to cluster and central points based meta-KANSEI model combining with the advantages of a variety of existing intelligent processing methods are expected to shift the KANSEI Engineering (KE) research into the medical imaging field

30th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems. The amount and complexity of information itself, the number of abstraction levels of information, and the size of databases and knowledge bases are continuously growing. Conceptual modelling is one of the sub-areas of information modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

持続可能なデザインへの興味を高めるための教育的支援開発

筑波大学 (University of Tsukuba)201

Natural Language Processing: Emerging Neural Approaches and Applications

This Special Issue highlights the most recent research being carried out in the NLP field to discuss relative open issues, with a particular focus on both emerging approaches for language learning, understanding, production, and grounding interactively or autonomously from data in cognitive and neural systems, as well as on their potential or real applications in different domains

Multiparametric interfaces for fine-grained control of digital music

Digital technology provides a very powerful medium for musical creativity, and the way in which we interface and interact with computers has a huge bearing on our ability to realise our artistic aims. The standard input devices available for the control of digital music tools tend to afford a low quality of embodied control; they fail to realise our innate expressiveness and dexterity of motion. This thesis looks at ways of capturing more detailed and subtle motion for the control of computer music tools; it examines how this motion can be used to control music software, and evaluates musicians’ experience of using these systems. Two new musical controllers were created, based on a multiparametric paradigm where multiple, continuous, concurrent motion data streams are mapped to the control of musical parameters. The first controller, Phalanger, is a markerless video tracking system that enables the use of hand and finger motion for musical control. EchoFoam, the second system, is a malleable controller, operated through the manipulation of conductive foam. Both systems use machine learning techniques at the core of their functionality. These controllers are front ends to RECZ, a high-level mapping tool for multiparametric data streams. The development of these systems and the evaluation of musicians’ experience of their use constructs a detailed picture of multiparametric musical control. This work contributes to the developing intersection between the fields of computer music and human-computer interaction. The principal contributions are the two new musical controllers, and a set of guidelines for the design and use of multiparametric interfaces for the control of digital music. This work also acts as a case study of the application of HCI user experience evaluation methodology to musical interfaces. The results highlight important themes concerning multiparametric musical control. These include the use of metaphor and imagery, choreography and language creation, individual differences and uncontrol. They highlight how this style of interface can fit into the creative process, and advocate a pluralistic approach to the control of digital music tools where different input devices fit different creative scenarios

Shifting Interfaces: art research at the intersections of live performance and technology

Merged with duplicate record 10026.1/809 on 08.20.2017 by CS (TIS)This collection of published works is an outcome of my practice-led inter-disciplinary collaborative artistic research into deepening understanding of creative process in the field of contemporary dance. It comprises thirty written works published from 1999 to 2007 in various formats and platforms. This collection is framed by a methodological discussion that provides insight into how this research has intersected over time with diverse fields of practice including contemporary dance, digital and new media arts and non-art domains such as cognitive and social science. Fields are understood in the context of this research to be largely constituted out of the expert practices of individual collaborators. This research starts from an interest in the Impact of new media technologies on dance making/ choreography. The collection of works show evidence, established in the first two publications, of an evolving engagement with two concepts related to this interest: (1) the 'algorithm' as a process-level connection or bridge between dance composition and computation; (2) the empirical study of movement embedded as a 'knowledge base' in the practices of both computer animation and dance and thus forming a special correspondence between them. This collection provides evidence of this research through a period of community-building amongst artists using new media technologies in performance, and culminates in the identification of an emerging 'community of practice' coming together around the formation of a unique body of knowledge pertaining to dance. The late 1990s New Media Art movement provided a supportive context for Important peer-to-peer encounters with creators and users of software tools and platforms in the context of inter-disciplinary art-making. A growing interest in software programming as a creative practice opened up fresh perspectives on possible connections with dance making. It became clear that software's utility alone, including artistic uses of software, was a limited conception. This was the background thinking that informed the first major shift in the research towards the design of software that might augment the creative process of expert choreographers and dancers. This shift from software use to its design, framed by a focus on the development of tools to support dance creation, also provided strong rationale to deepen the research into dance making processes. In the second major phase of the research presented here, scientific study is brought collaboratively to bear on questions related to choreographic practice. This lead to a better understanding of ways in which dancers and choreographers, as 'thinking bodies', interact with their design tools and each other in the context of creation work. In addition to this collection, outcomes of this research are traceable to other published papers and art works it has given rise to. Less easily measureable, but just as valuable, are the sustained relations between individuals and groups behind the 'community of practice' now recognised for its development of unique formats for bringing choreographic ideas and processes into contact, now and in the future, with both general audiences and other specialist practices