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Publications (10 of 25) Show all publications
Bae, J., Ventocilla, E., Riveiro, M., Helldin, T. & Falkman, G. (2017). Evaluating Multi-Attributes on Cause and Effect Relationship Visualization. In: Alexandru Telea, Jose Braz, Lars Linsen (Ed.), Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017): Volumne 3: IVAPP. Paper presented at 8th International Conference on Information Visualization Theory and Applications (IVAPP), part of the 12th International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), February 27-March 1, 2017, in Porto, Portugal (pp. 64-74). SciTePress
Open this publication in new window or tab >>Evaluating Multi-Attributes on Cause and Effect Relationship Visualization
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2017 (English)In: Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017): Volumne 3: IVAPP / [ed] Alexandru Telea, Jose Braz, Lars Linsen, SciTePress , 2017, p. 64-74Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents findings about visual representations of cause and effect relationship's direction, strength, and uncertainty based on an online user study. While previous researches focus on accuracy and few attributes, our empirical user study examines accuracy and the subjective ratings on three different attributes of a cause and effect relationship edge. The cause and effect direction was depicted by arrows and tapered lines; causal strength by hue, width, and a numeric value; and certainty by granularity, brightness, fuzziness, and a numeric value. Our findings point out that both arrows and tapered cues work well to represent causal direction. Depictions with width showed higher conjunct accuracy and were more preferred than that with hue. Depictions with brightness and fuzziness showed higher accuracy and were marked more understandable than granularity. In general, depictions with hue and granularity performed less accurately and were not preferred compared to the ones with numbers or with width and brightness.

Place, publisher, year, edition, pages
SciTePress, 2017
Keywords
Cause and effect, uncertainty, evaluation, graph visualization
National Category
Computer and Information Sciences
Research subject
Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science
Identifiers
urn:nbn:se:hj:diva-43243 (URN)10.5220/0006102300640074 (DOI)000444939500005 ()2-s2.0-85040593124 (Scopus ID)0;0;miljJAIL (Local ID)978-989-758-228-8 (ISBN)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
8th International Conference on Information Visualization Theory and Applications (IVAPP), part of the 12th International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), February 27-March 1, 2017, in Porto, Portugal
Funder
Knowledge Foundation
Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Ohlander, U., Alfredson, J., Riveiro, M. & Falkman, G. (2017). User Participation in the Design of Cockpit Interfaces. In: Marcelo Soares, Christianne Falcão & Tareq Z. Ahram (Ed.), Advances in Ergonomics Modeling, Usability & Special Populations: . Paper presented at AHFE 2016 International Conference on Ergonomics Modeling, Usability & Special Populations, July 27-31, 2016, Walt Disney World®, Florida, USA (pp. 51-58). Springer
Open this publication in new window or tab >>User Participation in the Design of Cockpit Interfaces
2017 (English)In: Advances in Ergonomics Modeling, Usability & Special Populations / [ed] Marcelo Soares, Christianne Falcão & Tareq Z. Ahram, Springer , 2017, p. 51-58Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates the nature of user participation in the process of designing fighter aircraft cockpits. The role of the users, i.e. pilots, in the design of cockpit interfaces is explored. We present the results of an on-line questionnaire with twelve designers of cockpit interfaces for fighter aircraft. The results show that the designers have highlighted the need for more opportunities to observe the pilots, and they wish to obtain more information and ideas from them. Moreover, a larger involvement from users as examiners and testers in the evaluation process was desirable. Access to users was considered unproblematic and the risk of misunderstandings was reported to be low. Moreover, the designers did not support the idea that users should design or take design decisions.

Place, publisher, year, edition, pages
Springer, 2017
Series
Advances in Intelligent Systems and Computing, ISSN 2194-5357 ; 486
Keywords
User participation, User involvement, Fighter aircraft
National Category
Human Computer Interaction Engineering and Technology
Research subject
Skövde Artificial Intelligence Lab (SAIL); INF302 Autonomous Intelligent Systems
Identifiers
urn:nbn:se:hj:diva-43247 (URN)10.1007/978-3-319-41685-4_5 (DOI)2-s2.0-84992650798 (Scopus ID)0;0;miljJAIL (Local ID)978-3-319-41685-4 (ISBN)978-3-319-41684-7 (ISBN)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
AHFE 2016 International Conference on Ergonomics Modeling, Usability & Special Populations, July 27-31, 2016, Walt Disney World®, Florida, USA
Funder
Vinnova
Available from: 2016-09-24 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Ohlander, U., Alfredson, J., Riveiro, M. & Falkman, G. (2016). A Teamwork Model for Fighter Pilots. In: Don Harris (Ed.), Engineering Psychology and Cognitive Ergonomics: 13th International Conference, EPCE 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016, Proceedings. Paper presented at 13th International Conference, EPCE 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016 (pp. 221-230). Springer
Open this publication in new window or tab >>A Teamwork Model for Fighter Pilots
2016 (English)In: Engineering Psychology and Cognitive Ergonomics: 13th International Conference, EPCE 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016, Proceedings / [ed] Don Harris, Springer, 2016, p. 221-230Conference paper, Published paper (Refereed)
Abstract [en]

Fighter pilots depend on collaboration and teamwork to perform successful air missions. However, such collaboration is challenging due to limitations in communication and the amount of data that can be shared between aircraft. In order to design future support systems for fighter pilots, this paper aims at characterizing how pilots collaborate while performing real-world missions. Our starting point is the “Big Five” model for effective teamwork, put forth by Salas et al. [1]. Fighter pilots were interviewed about their teamwork, and how they prepare and perform missions in teams. The results from the interviews were used to describe how pilots collaborate in teams, and to suggest relationships between the teamwork elements of the “Big Five” model for fighter pilots performing missions. The results presented in this paper are intended to inform designers and developers of cockpit displays, data links and decision support systems for fighter aircraft.

Place, publisher, year, edition, pages
Springer, 2016
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9736
Keywords
Team effectiveness, Teamwork, Fighter aircraft, Fighter pilots
National Category
Engineering and Technology Human Computer Interaction
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:hj:diva-43249 (URN)10.1007/978-3-319-40030-3_23 (DOI)000389412900023 ()2-s2.0-84978218415 (Scopus ID)0;0;miljJAIL (Local ID)978-3-319-40029-7 (ISBN)978-3-319-40030-3 (ISBN)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
13th International Conference, EPCE 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016
Funder
Vinnova
Available from: 2016-09-24 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Ohlander, U., Alfredson, J., Riveiro, M. & Falkman, G. (2016). Elements of team effectiveness: A qualitative study with pilots. In: 2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA): . Paper presented at IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), San Diego, CA, 21-25 March 2016 (pp. 21-27). IEEE Computer Society
Open this publication in new window or tab >>Elements of team effectiveness: A qualitative study with pilots
2016 (English)In: 2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), IEEE Computer Society , 2016, p. 21-27Conference paper, Published paper (Refereed)
Abstract [en]

Fighter pilots performing air missions rely heavily on teamwork for successful outcomes. Designing systems that support such teamwork in highly dynamic missions is a challenging task, and to the best of our knowledge, current teamwork models are not specifically adapted for this domain. This paper presents a model of task performance for military fighter pilots based on the teamwork model “Big Five” proposed by Salas, Sims, and Burke [1]. The “Big Five” model consists of eight teamwork elements that are essential for successful team performance. In-depth interviews were performed with fighter pilots to explore and describe the teamwork elements for the fighter aircraft domain. The findings from these interviews are used to suggest where in the task cycle of mission performance each teamwork element comes in to play.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016
Keywords
fighter aircraft, teamwork, fighter pilots, team effectiveness
National Category
Engineering and Technology Human Computer Interaction
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:hj:diva-43250 (URN)10.1109/COGSIMA.2016.7497781 (DOI)000390774200004 ()2-s2.0-84981298083 (Scopus ID)0;0;miljJAIL (Local ID)978-1-5090-0632-8 (ISBN)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), San Diego, CA, 21-25 March 2016
Funder
Vinnova
Available from: 2016-09-24 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Helldin, T., Riveiro, M., Pashami, S., Falkman, G., Byttner, S. & Nowaczyk, S. (2016). Supporting analytical reasoning: A study from the automotive industry. In: Sakae Yamamoto (Ed.), Human Interface and the Management of Information: Applications and Services: 18th International Conference, HCI International 2016 Toronto, Canada, July 17-22, 2016. Proceedings, Part II. Paper presented at 18th International Conference on Human Interface and the Management of Information (HCI International 2016), Toronto, Canada, July 17-22, 2016. (pp. 20-31). Springer
Open this publication in new window or tab >>Supporting analytical reasoning: A study from the automotive industry
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2016 (English)In: Human Interface and the Management of Information: Applications and Services: 18th International Conference, HCI International 2016 Toronto, Canada, July 17-22, 2016. Proceedings, Part II / [ed] Sakae Yamamoto, Springer, 2016, p. 20-31Conference paper, Published paper (Refereed)
Abstract [en]

In the era of big data, it is imperative to assist the human analyst in the endeavor to find solutions to ill-defined problems, i.e. to “detect the expected and discover the unexpected” (Yi et al., 2008). To their aid, a plethora of analysis support systems is available to the analysts. However, these support systems often lack visual and interactive features, leaving the analysts with no opportunity to guide, influence and even understand the automatic reasoning performed and the data used. Yet, to be able to appropriately support the analysts in their sense-making process, we must look at this process more closely. In this paper, we present the results from interviews performed together with data analysts from the automotive industry where we have investigated how they handle the data, analyze it and make decisions based on the data, outlining directions for the development of analytical support systems within the area.

Place, publisher, year, edition, pages
Springer, 2016
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9735
Keywords
analytical reasoning, sense-making, visual analytics, truck data analysis, big data
National Category
Human Computer Interaction
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:hj:diva-43254 (URN)10.1007/978-3-319-40397-7_3 (DOI)000389467600003 ()2-s2.0-84978877445 (Scopus ID)0;0;miljJAIL (Local ID)978-3-319-40396-0 (ISBN)978-3-319-40397-7 (ISBN)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
18th International Conference on Human Interface and the Management of Information (HCI International 2016), Toronto, Canada, July 17-22, 2016.
Projects
BIDAF - A Big Data Analytics Framework for a Smart Society
Funder
Knowledge Foundation, BIDAF 2014/32
Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Ohlander, U., Alfredson, J., Riveiro, M. & Falkman, G. (2015). Understanding Team Effectiveness in a Tactical Air Unit. In: Don Harris (Ed.), Engineering Psychology and Cognitive Ergonomics: 12th International Conference, EPCE 2015, Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015, Proceedings. Paper presented at 12th International Conference on Engineering Psychology and Cognitive Ergonomics (EPCE 2015), Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015 (pp. 472-479). Springer
Open this publication in new window or tab >>Understanding Team Effectiveness in a Tactical Air Unit
2015 (English)In: Engineering Psychology and Cognitive Ergonomics: 12th International Conference, EPCE 2015, Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015, Proceedings / [ed] Don Harris, Springer, 2015, p. 472-479Conference paper, Published paper (Refereed)
Abstract [en]

Effective team work is regarded as a key factor for success in missions performed by fighter aircraft in a Tactical Air Unit (TAU). Many factors contrib-ute to how a team will succeed in their mission. From the existing literature on teamwork, Salas, Sims and Burke [1], suggested five main factors and three sup-porting mechanisms for effective team work. These were proposed as the “Big Five” of teamwork. This article investigates if the model offered by Salas et al. is applicable to a TAU of fighter aircraft. Semi-structured interviews were carried out with six fighter pilots. The results of these interviews imply that the model has relevance for the teamwork in a TAU. Moreover, this paper discusses impli-cations for the design of future decision-support systems that support team effec-tiveness. 

Place, publisher, year, edition, pages
Springer, 2015
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9174
Keywords
Team effectiveness, fighter aircraft, tactical air unit
National Category
Computer Sciences
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:hj:diva-43262 (URN)10.1007/978-3-319-20373-7_45 (DOI)2-s2.0-84947247735 (Scopus ID)0;0;miljJAIL (Local ID)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
12th International Conference on Engineering Psychology and Cognitive Ergonomics (EPCE 2015), Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015
Funder
Vinnova
Available from: 2015-09-25 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Riveiro, M. & Falkman, G. (2014). Detecting anomalous behavior in sea traffic: A study of analytical strategies and their implications for surveillance systems. International Journal of Information Technology and Decision Making, 13(2), 317-360
Open this publication in new window or tab >>Detecting anomalous behavior in sea traffic: A study of analytical strategies and their implications for surveillance systems
2014 (English)In: International Journal of Information Technology and Decision Making, ISSN 0219-6220, Vol. 13, no 2, p. 317-360Article in journal (Refereed) Published
Place, publisher, year, edition, pages
World Scientific, 2014
Keywords
analytical reasoning, Anomaly detection, decision making, maritime traffic monitoring
National Category
Human Computer Interaction Computer Sciences
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:hj:diva-43263 (URN)10.1142/S021962201450045X (DOI)000336410700005 ()2-s2.0-84894705090 (Scopus ID)0;0;miljJAIL (Local ID)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Available from: 2014-05-01 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Riveiro, M., Helldin, T., Falkman, G. & Lebram, M. (2014). Effects of visualizing uncertainty on decision-making in a target identification scenario. Computers & graphics, 41(1), 84-98
Open this publication in new window or tab >>Effects of visualizing uncertainty on decision-making in a target identification scenario
2014 (English)In: Computers & graphics, ISSN 0097-8493, E-ISSN 1873-7684, Vol. 41, no 1, p. 84-98Article in journal (Refereed) Published
Abstract [en]

This paper presents an empirical study that addresses the effects the visualization of uncertainty has on decision-making. We focus our investigations on an area where uncertainty plays an important role and the decision time is limited. For that, we selected an air defense scenario, where expert operators have a few minutes to make a well-informed decision based on uncertain sensor data regarding the identity of an object and where the consequences of a late or wrong decision are severe. An approach for uncertainty visualization is proposed and tested using a prototype that supports the interactive analysis of multivariate spatio-temporal sensor data. The uncertainty visualization embeds the accuracy of the sensor data values using the thickness of the lines in the graphical representation of the sensor values. Semi-transparent filled circles represent the uncertain position, while a track quality value between 0 and 1 accounts for the quality of the estimated track for each target. Twenty-two experienced air traffic operators were divided into two groups (with and without uncertainty visualization) and carried out identification and prioritization tasks using the prototype. The results show that the group aided by visualizations of uncertainty needed significantly fewer attempts to make a final identification, and a significant difference between the groups when considering the identities and priorities assigned was observed (participants with uncertainty visualization selected higher priority values and more hostile and suspect identities). These results may show that experts put themselves in the ``worst-case scenario" in the presence of uncertainty when safety is an issue. Additionally, the presentation of uncertainty neither increased the participants' expressed workload, nor the time needed to make a classification. However, the inclusion of the uncertainty information did not have a significant effect on the performance (true positives, false negatives and false positives) or the participants' expressed confidence in their decisions.

Place, publisher, year, edition, pages
Elsevier, 2014
Keywords
Uncertainty visualization, Decision-making, Confidence, Performance, Workload, Target identification
National Category
Human Computer Interaction
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL); Interaction Lab (ILAB)
Identifiers
urn:nbn:se:hj:diva-43265 (URN)10.1016/j.cag.2014.02.006 (DOI)000336349700008 ()2-s2.0-84897553740 (Scopus ID)0;0;miljJAIL (Local ID)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Available from: 2014-05-02 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Riveiro, M., Helldin, T. & Falkman, G. (2014). Influence of Meta-Information on Decision-Making: Lessons Learned from Four Case Studies. In: Proceedings of the 4th International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2014): . Paper presented at 2014 IEEE International Inter-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), March 3-6, San Antonio, USA. IEEE Communications Society
Open this publication in new window or tab >>Influence of Meta-Information on Decision-Making: Lessons Learned from Four Case Studies
2014 (English)In: Proceedings of the 4th International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2014), IEEE Communications Society , 2014Conference paper, Published paper (Refereed)
Abstract [en]

This paper discusses the results of four empirical evaluations that assess the effects that visualizing system metainformation have on decision-making, particularly on confidence, trust, workload, time and performance. These four case studies correspond to the analysis of (1) the effects that visualizing uncertainty associated with sensor values (position, speed, altitude, etc. and track quality) have on decision-making on a ground to air defense scenario; (2) the effects that the visualization of the car’s certainty on its own capability of driving autonomously have on drivers’ trust and performance; (3) the influence that the visualization of various qualifiers associated with the proposals given by the support system has on air traffic operators carrying out identification tasks and (4) the effects that the presentation of different abstraction levels of information have on classification tasks carried out by fighter pilots. We summarize the results of these four case studies and discuss lessons learned for the design of future computerized support systems regarding the visualization of meta-information.

Place, publisher, year, edition, pages
IEEE Communications Society, 2014
Keywords
system meta-information, uncertainty, decisionmaking, trust, situation awareness, decision support
National Category
Computer Sciences Human Computer Interaction
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:hj:diva-43267 (URN)10.1109/CogSIMA.2014.6816534 (DOI)000341577900003 ()2-s2.0-84902076083 (Scopus ID)0;0;miljJAIL (Local ID)978-1-4799-3564-2 (ISBN)978-1-4799-3565-9 (ISBN)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
2014 IEEE International Inter-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), March 3-6, San Antonio, USA
Note

Presentation: http://www.cogsima2014.org/Program.html

Available from: 2014-05-02 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Helldin, T., Ohlander, U., Falkman, G. & Riveiro, M. (2014). Transparency of Automated Combat Classification. In: Don Harris (Ed.), Engineering Psychology and Cognitive Ergonomics: 11th International Conference, EPCE 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings. Paper presented at 11th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2014, Held as Part of 16th International Conference on Human-Computer Interaction, HCI International 2014, Heraklion, Crete, Greece, 22 June 2014 through 27 June 2014 (pp. 22-33). Springer
Open this publication in new window or tab >>Transparency of Automated Combat Classification
2014 (English)In: Engineering Psychology and Cognitive Ergonomics: 11th International Conference, EPCE 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings / [ed] Don Harris, Springer , 2014, p. 22-33Conference paper, Published paper (Refereed)
Abstract [en]

We present an empirical study where the effects of three levels of system transparency of an automated target classification aid on fighter pilots’ performance and initial trust in the system were evaluated. The levels of transparency consisted of (1) only presenting text–based information regarding the specific object (without any automated support), (2) accompanying the text-based information with an automatically generated object class suggestion and (3) adding the incorporated sensor values with associated (uncertain) historic values in graphical form. The results show that the pilots needed more time to make a classification decision when being provided with display condition 2 and 3 than display condition 1. However, the number of correct classifications and the operators’ trust ratings were the highest when using display condition 3. No difference in the pilots’ decision confidence was found, yet slightly higher workload was reported when using display condition 3. The questionnaire results report on the pilots’ general opinion that an automatic classification aid would help them make better and more confident decisions faster, having trained with the system for a longer period.

Place, publisher, year, edition, pages
Springer, 2014
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 8532
Keywords
Classification support, automation transparency, uncertainty visualization, fighter pilots
National Category
Computer Sciences
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:hj:diva-43271 (URN)10.1007/978-3-319-07515-0_3 (DOI)000342845800003 ()2-s2.0-84903643576 (Scopus ID)0;0;miljJAIL (Local ID)978-3-319-07514-3 (ISBN)978-3-319-07515-0 (ISBN)0;0;miljJAIL (Archive number)0;0;miljJAIL (OAI)
Conference
11th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2014, Held as Part of 16th International Conference on Human-Computer Interaction, HCI International 2014, Heraklion, Crete, Greece, 22 June 2014 through 27 June 2014
Funder
Vinnova
Available from: 2014-11-04 Created: 2019-03-05 Last updated: 2019-08-23Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8884-2154

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