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253 results on '"Sonderegger, Andreas"'

6. Clustering of Drivers’ State Before Takeover Situations Based on Physiological Features Using Unsupervised Machine Learning

Author

de Salis, Emmanuel, Meteier, Quentin, Pelletier, Colin, Capallera, Marine, Angelini, Leonardo, Sonderegger, Andreas, Khaled, Omar Abou, Mugellini, Elena, Widmer, Marino, Carrino, Stefano, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Ahram, Tareq, editor, and Taiar, Redha, editor

Published
2022
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9. Predicting Takeover Quality in Conditionally Automated Vehicles Using Machine Learning and Genetic Algorithms

Author

de Salis, Emmanuel, Meteier, Quentin, Capallera, Marine, Angelini, Leonardo, Sonderegger, Andreas, Khaled, Omar Abou, Mugellini, Elena, Widmer, Marino, Carrino, Stefano, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Russo, Dario, editor, Ahram, Tareq, editor, Karwowski, Waldemar, editor, Di Bucchianico, Giuseppe, editor, and Taiar, Redha, editor

Published
2021
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10. Trust Indicators and Explainable AI: A Study on User Perceptions

Author

Ribes, Delphine, Henchoz, Nicolas, Portier, Hélène, Defayes, Lara, Phan, Thanh-Trung, Gatica-Perez, Daniel, Sonderegger, Andreas, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ardito, Carmelo, editor, Lanzilotti, Rosa, editor, Malizia, Alessio, editor, Petrie, Helen, editor, Piccinno, Antonio, editor, Desolda, Giuseppe, editor, and Inkpen, Kori, editor

Published
2021
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11. What Students Do While You Are Teaching – Computer and Smartphone Use in Class and Its Implication on Learning

Author

Ochs, Carli, Sonderegger, Andreas, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ardito, Carmelo, editor, Lanzilotti, Rosa, editor, Malizia, Alessio, editor, Petrie, Helen, editor, Piccinno, Antonio, editor, Desolda, Giuseppe, editor, and Inkpen, Kori, editor

Published
2021
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15. The UX Construct – Does the Usage Context Influence the Outcome of User Experience Evaluations?

Author

Sonderegger, Andreas, Uebelbacher, Andreas, Sauer, Jürgen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Lamas, David, editor, Loizides, Fernando, editor, Nacke, Lennart, editor, Petrie, Helen, editor, Winckler, Marco, editor, and Zaphiris, Panayiotis, editor

Published
2019
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23. People's reactions to decisions by human vs. algorithmic decision-makers: the role of explanations and type of selection tests.

Author

Wesche, Jenny S., Hennig, Frederike, Kollhed, Christopher Sebastian, Quade, Jessica, Kluge, Sören, and Sonderegger, Andreas

Subjects
CONFORMANCE testing, EMPLOYEE selection, TRUST, MONETARY incentives, COMMERCIAL product testing, HUMAN beings
Abstract

Research suggests that people prefer human over algorithmic decision-makers at work. Most of these studies, however, use hypothetical scenarios and it is unclear whether such results replicate in more realistic contexts. We conducted two between-subjects studies (N=270; N=183) in which the decision-maker (human vs. algorithmic, Study 1 and 2), explanations regarding the decision- process (yes vs. no, Study 1 and 2), and the type of selection test (requiring human vs. mechanical skills for evaluation, Study 2) were manipulated. While Study 1 was based on a hypothetical scenario, participants in pre-registered Study 2 volunteered to participate in a qualifying session for an attractively remunerated product test, thus competing for real incentives. In both studies, participants in the human condition reported higher levels of trust and acceptance. Providing explanations also positively influenced trust, acceptance, and perceived transparency in Study 1, while it did not exert any effect in Study 2. Type of the selection test affected fairness ratings, with higher ratings for tests requiring human vs. mechanical skills for evaluation. Results show that algorithmic decision-making in personnel selection can negatively impact trust and acceptance both in studies with hypothetical scenarios as well as studies with real incentives. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Computer-Supported Work in Partially Distributed and Co-located Teams: The Influence of Mood Feedback

Author

Sonderegger, Andreas, Lalanne, Denis, Bergholz, Luisa, Ringeval, Fabien, Sauer, Juergen, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kotzé, Paula, editor, Marsden, Gary, editor, Lindgaard, Gitte, editor, Wesson, Janet, editor, and Winckler, Marco, editor

Published
2013
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30. A Contextual Multimodal System for Increasing Situation Awareness and Takeover Quality in Conditionally Automated Driving

Author

Meteier, Quentin, De Salis, Emmanuel, Widmer, Marino, Angelini, Leonardo, Carrino, Stefano, Sonderegger, Andreas, Khaled, Omar Abou, and Mugellini, Elena

Subjects
BF Psychology, QA75 Electronic computers. Computer science
Abstract

Advanced driver assistances are becoming increasingly common in commercial cars, not only to assist but also to free drivers from manual driving whenever possible. Soon, drivers should be allowed to engage in non-driving-related tasks. The fact that responsibility for driving is shifting from humans to machines must be considered in the development of these assistances in order to guarantee safety and trust. In this article, we introduce AdVitam (for Advanced Driver-Vehicle Interaction to Make future driving safer), an autonomous system aiming at maintaining driver’s situation awareness and optimizing takeover quality during conditionally automated driving. The information conveyed to drivers is dynamically adapted to achieve these goals, depending on the driving environment and the driver’s physiological state. This system consists of three connected modules. The first module (Driver State) predicts the driver’s state with machine learning and physiological signals as inputs. The second module (Supervision) uses different interfaces (a haptic seat, a personal device, and ambient lights) to maintain the drivers’ situation awareness during the autonomous driving phases. The third module (Intervention) is a machine learning model that chooses the most appropriate combination among haptic, auditory, and visual modalities to request the driver to take over control and thus optimize takeover quality. To evaluate the system and each module independently, a preliminary user study with 35 drivers was conducted in a fixed-base driving simulator. All participants drove in two different environments (rural and urban). In addition, the activation of the Supervision and Intervention modules were manipulated as two between-subject factors. Results show that conveying information on the driving environment status through multimodal interfaces increases drivers’ situation awareness (i.e., better identification of potential problems in the environment) and trust in the automated vehicle. However, the system does not show positive outcomes on takeover quality. Besides, the Driver State module provided consistent predictions with the experimental manipulation. The system proposed in this paper could lead to better acceptance and safety when conditionally automated vehicles will be released by increasing drivers’ trust during phases of automated driving.

Published
2023
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32. ANT

Author

Neff, Patrick, Sonderegger, Andreas, cai, danpeng, Lemay, Delphine, Shabestari, Payam, Naas, Adrian, Nussbaumer, Jasmin, and Kleinjung, Tobias

Abstract

Advancing neurotherapy (of tinnitus)

Published
2022
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33. The Influence of Product Aesthetics and User State in Usability Testing

Author

Sauer, Juergen and Sonderegger, Andreas

Abstract

An empirical study examined the effects of two influencing factors in usability tests on user performance and usability ratings. Product aesthetics (high vs. low) as the main independent factor and prior usage event (positive vs. negative) as a subsidiary independent factor were varied in a between-participants design. 60 participants took part in the experiment, completing a number of typical tasks of mobile phone users. The results showed that increased product aesthetics had a positive effect on perceived usability and led to longer task completion times. After a negative usage event had been experimentally induced, usability ratings dropped as expected but user performance on subsequent tasks remained unaffected. An important implication of the study is that the aesthetic properties of a product may have multiple effects that go beyond perceived product attractiveness. (Contains 2 figures and 2 tables.)

Published
2011
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36. Reuse in construction : a compendium of circular architecture

Author

Stricker, Eva, Brandi, Guido, Sonderegger, Andreas, Angst, Marc, Buser, Barbara, Massmünster, Michel, Stricker, Eva, Brandi, Guido, Sonderegger, Andreas, Angst, Marc, Buser, Barbara, and Massmünster, Michel

Abstract

Das Bauen mit wiederverwendeten Bauteilen ist derzeit eines der meistbeachteten Phänomene der europäischen Architekturdiskussion. Dieses 2021 in Deutsch erschienene und nun auch in Englisch vorliegende Buch ist ein umfassendes Kompendium, das allen Fragen zur Wiederverwendung von Bauteilen im Detail nachgeht. Interdisziplinäre Fachgespräche verorten die Wiederverwendung innerhalb der Rahmenbedingungen heutiger Bau- und Planungspraxis, Essays stellen zirkulär gedachte Bauten und Konstruktionen vor, acht Thesen zeigen architektonische Herausforderungen sowie Potenziale und ein umfassender Aufsatz erläutert die Kulturgeschichte der Bauteilwiederverwendung. Mit Beiträgen von Andreas Abegg, Marc Angst, Guido Brandi, Barbara Buser, Arne Vande Capelle, Michael Eidenbenz, Nathanea Elte, Deborah Fehlmann, Patric Fischli-Boson, Oya Atalay Franck, Michaël Ghyoot, Pascal Hentschel, Meinrad Huser, Christian Kohler, Marc Loeliger, Ákos Moravánszky, Kerstin Müller, Andreas Oefner, Katrin Pfäffli, Michael Pöll, Tina Puffert, François Renaud, Barbara Rentsch, Alexis Ringli, Andreas Sonderegger, Eva Stricker, Cyrille Veron und Barbara Zeleny.

Published
2022

44. Bauteile wiederverwenden : ein Kompendium zum zirkulären Bauen

Author

Stricker, Eva, Brandi, Guido, Sonderegger, Andreas, Angst, Marc, Buser, Barbara, and Massmünster, Michel

Subjects
Bauteilwiedervewendung, Nachhaltiges Bauen, 720: Architektur, Ressourceneffizienz, 690: Hausbau und Bauhandwerk, Reuse, Wiederverwendung
Abstract

In Zusammenarbeit mit Institut Konstruktives Entwerfen, ZHAW Departement Architektur, Gestaltung und Bauingenieurwesen zusammen mit Baubüro in situ AG und Zirkular GmbH

Published
2021

47. Social stress in human-machine systems: opportunities and challenges of an experimental research approach.

Author

Sauer, Juergen, Sonderegger, Andreas, Thuillard, Simon, and Semmer, Norbert K.

Subjects
*JOB stress prevention, *PREVENTION of psychological stress, *OCCUPATIONAL roles, *WORK environment, *RESEARCH methodology, *TASK performance, *JOB performance, *CORPORATE culture
Abstract

This article presents some deliberations on methodological approaches to researching the effects of work-related social stress on performance, with particular consideration being given to machine-induced social stress. The article proposes a broad methodological approach to examine such effects. A particular focus is placed on performance after-effects (e.g. unscheduled probe tasks), extra-role behaviour, and task management behaviour because of conventional performance measures (i.e. scheduled tasks) often being unimpaired by social stressors. The role of the 'performance protection mode' as an important concept is discussed. A distinction is made between three facets of after-effects: performance-related, behavioural, and emotional. Unscheduled probe tasks and voluntary tasks are proposed to measure performance-related and behavioural after-effects. Propositions for specific experimental scenarios are made, allowing for sufficiently realistic simulations of social stress at work. The availability of such lab-based simulations of work environments offers good opportunities for this line of experimental research, which is expected to gain in importance since highly automated systems may modify the impact of human-induced social stress or may even represent a social stressor themselves. Finally, the considerations presented in this article are not only of relevance to the domain of social stress but to experimental stress research in general. [ABSTRACT FROM AUTHOR]

Published
2023
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48. Ming Shan Digital Experience

Author

Henchoz, Nicolas, primary, Charvolin, Margaux, additional, Ribes, Delphine, additional, Défayes, Lara, additional, DuchÊne, Cédric, additional, Groves, Emily, additional, and Sonderegger, Andreas, additional

Published
2021
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50. Pictorial Scales in Research and Practice A Review

Author

Sauer, Juergen, Baumgartner, Juergen, Frei, Naomi, Sonderegger, Andreas, Sauer, Juergen, Baumgartner, Juergen, Frei, Naomi, and Sonderegger, Andreas

Abstract

The present article is concerned with the theoretical foundations and practical aspects of developing pictorial scales. It aims to assess the potential of pictorial scales compared to verbal scales. The article provides a review of existing pictorial scales with a view to identifying suitable methodological approaches for developing such scales. The review showed that the development and especially validation of many pictorial scales did not follow a stringent methodological approach. A category system is proposed, which allows the classification of different types of pictorial scales. Finally, we present a first draft of a theoretical framework, which can provide guidance for the future development of pictorial scales. The present work carries the implication that a specific methodological approach is needed, which focuses more strongly on the particular needs of designing pictorial scales (e.g., testing the comprehensibility of pictures).

Published
2021
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