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  • 1.
    Andreasson, Rebecca
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Effects of Visualizing Missing Data: An Empirical Evaluation2014In: 18th International Conference on Information Visualisation (IV) / [ed] Ebad Banissi, Mark W. McK. Bannatyne, Francis T. Marchese, Muhammad Sarfraz, Anna Ursyn, Gilles Venturini, Theodor G. Wyeld, Urska Cvek, Marjan Trutschl, Georges Grinstein, Vladimir Geroimenko, Sarah Kenderdine & Fatma Bouali, IEEE conference proceedings , 2014, p. 132-138Conference paper (Refereed)
    Abstract [en]

    This paper presents an empirical study that evaluates the effects of visualizing missing data on decision-making tasks. A comparison between three visualization techniques: (1) emptiness, (2) fuzziness, and (3) emptiness plus explanation, revealed that the latter technique induced significantly higher degree of decision-confidence than the visualization technique fuzziness. Moreover, emptiness plus explanation yield the highest number of risky choices of the three. This result suggests that uncertainty visualization techniques affect the decision-maker and the decisionconfidence. Additionally, the results indicate a possible relation between the degree of decision-confidence and the decision-maker's displayed risk behavior.

  • 2. Annavarjula, Vaishnavi
    et al.
    Mbiydzenyu, Gideon
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Lavesson, Niklas
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Implicit user data in fashion recommendation systems2020In: Developments of artificial intelligence technologies in computation and robotics: Proceedings of the 14th International FLINS Conference (FLINS 2020) / [ed] Zhong Li, Chunrong Yuan, Jie Lu & Etienne E. Kerre, World Scientific, 2020, p. 614-621Conference paper (Refereed)
    Abstract [en]

    Recommendation systems in fashion are used to provide recommendations to users on clothing items, matching styles, and size or fit. These recommendations are generated based on user actions such as ratings, reviews or general interaction with a seller. There is an increased adoption of implicit feedback in models aimed at providing recommendations in fashion. This paper aims to understand the nature of implicit user feedback in fashion recommendation systems by following guidelines to group user actions. Categories of user actions that characterize implicit feedback are examination, retention, reference, and annotation. Each category describes a specific set of actions a user takes. It is observed that fashion recommendations using implicit user feedback mostly rely on retention as a user action to provide recommendations.

  • 3.
    Arvidsson, Simon
    et al.
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Gullstrand, Marcus
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Sirmacek, Beril
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Sensor fusion and convolutional neural networks for indoor occupancy prediction using multiple low-cost low-resolution heat sensor data2021In: Sensors, E-ISSN 1424-8220, Vol. 21, no 4, p. 1-21, article id 1036Article in journal (Refereed)
    Abstract [en]

    Indoor occupancy prediction is a prerequisite for the management of energy consumption, security, health, and other systems in smart buildings. Previous studies have shown that buildings that automatize their heating, lighting, air conditioning, and ventilation systems through considering the occupancy and activity information might reduce energy consumption by more than 50%. However, it is difficult to use high-resolution sensors and cameras for occupancy prediction due to privacy concerns. In this paper, we propose a novel solution for predicting occupancy using multiple low-cost and low-resolution heat sensors. We suggest two different methods for fusing and processing the data captured from multiple heat sensors and we use a Convolutional Neural Network for predicting occupancy. We conduct experiments to assess both the performance of the proposed solutions and analyze the impact of sensor field view overlaps on the prediction results. In summary, our experimental results show that the implemented solutions show high occupancy prediction accuracy and real-time processing capabilities.

  • 4.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Visual Data Analysis2019In: Data science in Practice / [ed] A. Said, & V. Torra, Springer, 2019, p. 133-155Chapter in book (Refereed)
    Abstract [en]

    Data Science offers a set of powerful approaches for making new discoveries from large and complex data sets. It combines aspects of mathematics, statistics, machine learning, etc. to turn vast amounts of data into new insights and knowledge. However, the sole use of automatic data science techniques for large amounts of complex data limits the human user’s possibilities in the discovery process, since the user is estranged from the process of data exploration. This chapter describes the importance of Information Visualization (InfoVis) and visual analytics (VA) within data science and how interactive visualization can be used to support analysis and decision-making, empowering and complementing data science methods. Moreover, we review perceptual and cognitive aspects, together with design and evaluation methodologies for InfoVis and VA.

  • 5.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Identifying Root Cause and Derived Effects in Causal Relationships2017In: Human Interface and the Management of Information: Information, Knowledge and Interaction Design: 19th International Conference, HCI International 2017, Vancouver, BC, Canada, July 9–14, 2017, Proceedings, Part I / [ed] Sakae Yamamoto, Springer , 2017, p. 22-34Conference paper (Refereed)
    Abstract [en]

    This paper focuses on identifying factors that influence the process of finding a root cause and a derived effect in causal node-link graphs with associated strength and significance depictions. We discuss in detail the factors that seem to be involved in identifying a global cause and effect based on the analysis of the results of an online user study with 44 participants, who used both sequential and non-sequential graph layouts. In summary, the results show that participants show geodesic-path tendencies when selecting causes and derived effects, and that context matters, i.e., participant’s own beliefs, experiences and knowledge might influence graph interpretation.

  • 6.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Understanding Indirect Causal Relationships in Node-Link Graphs2017In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 36, no 3, p. 411-421Article in journal (Refereed)
    Abstract [en]

    To find correlations and cause and effect relationships in multivariate data sets is central in many data analysis problems. A common way of representing causal relations among variables is to use node-link diagrams, where nodes depict variables and edges show relationships between them. When performing a causal analysis, analysts may be biased by the position of collected evidences, especially when they are at the top of a list. This is of crucial importance since finding a root cause or a derived effect, and searching for causal chains of inferences are essential analytic tasks when investigating causal relationships. In this paper, we examine whether sequential ordering influences understanding of indirect causal relationships and whether it improves readability of multi-attribute causal diagrams. Moreover, we see how people reason to identify a root cause or a derived effect. The results of our design study show that sequential ordering does not play a crucial role when analyzing causal relationships, but many connections from/to a variable and higher strength/certainty values may influence the process of finding a root cause and a derived effect.

  • 7.
    Bae, Juhee
    et al.
    University of Skövde, Skövde, Sweden.
    Helldin, Tove
    University of Skövde, Skövde, Sweden.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Nowaczyk, Sławomir
    University of Halmstad, Halmstad, Sweden.
    Bouguelia, Mohamed-Rafik
    University of Halmstad, Halmstad, Sweden.
    Falkman, Göran
    University of Skövde, Skövde, Sweden.
    Interactive Clustering: A Comprehensive Review2020In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 53, no 1, p. 1-39, article id 1Article, review/survey (Refereed)
    Abstract [en]

    In this survey, 105 papers related to interactive clustering were reviewed according to seven perspectives: (1) on what level is the interaction happening, (2) which interactive operations are involved, (3) how user feedback is incorporated, (4) how interactive clustering is evaluated, (5) which data and (6) which clustering methods have been used, and (7) what outlined challenges there are. This article serves as a comprehensive overview of the field and outlines the state of the art within the area as well as identifies challenges and future research needs.

  • 8.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Ventocilla, Elio
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Evaluating Multi-Attributes on Cause and Effect Relationship Visualization2017In: 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 (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.

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  • 9.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Ventocilla, Elio
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Torra, Vicenç
    Högskolan i Skövde, Institutionen för informationsteknologi.
    On the Visualization of Discrete Non-additive Measures2018In: Aggregation Functions in Theory and in Practice AGOP 2017 / [ed] Torra V, Mesiar R, Baets B, Springer, 2018, p. 200-210Conference paper (Refereed)
    Abstract [en]

    Non-additive measures generalize additive measures, and have been utilized in several applications. They are used to represent different types of uncertainty and also to represent importance in data aggregation. As non-additive measures are set functions, the number of values to be considered grows exponentially. This makes difficult their definition but also their interpretation and understanding. In order to support understability, this paper explores the topic of visualizing discrete non-additive measures using node-link diagram representations.

  • 10.
    Beauxis-Aussalet, Emma
    et al.
    Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
    Behrisch, Michael
    Utrecht University, Utrecht, The Netherlands.
    Borgo, Rita
    King’s College London, London, United Kingdom.
    Chau, Duen Horng
    Georgia Tech, Atlanta, GA, USA.
    Collins, Christopher
    Ontario Tech University, Ontario, Canada.
    Ebert, David
    University of Oklahoma, Norman, OK, USA.
    El-Assady, Mennatallah
    University of Konstanz, Konstanz, Germany.
    Endert, Alex
    Georgia Tech, Atlanta, GA, USA.
    Keim, Daniel A.
    University of Konstanz, Konstanz, Germany.
    Kohlhammer, Jörn
    Fraunhofer IGD, Darmstadt, Germany.
    Oelke, Daniela
    Offenburg University, Offenburg, Germany.
    Peltonen, Jaakko
    Tampere University, Tampere, Finland.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Schreck, Tobias
    Graz University of Technology, Graz, Austria.
    Strobelt, Hendrik
    IBM Research, Cambridge, MA, USA.
    van Wijk, Jarke J
    Eindhoven University of Technology, Eindhoven, The Netherlands.
    Rhyne, Theresa-Marie
    The Role of Interactive Visualization in Fostering Trust in AI2021In: IEEE Computer Graphics and Applications, ISSN 0272-1716, E-ISSN 1558-1756, Vol. 41, no 6, p. 7-12Article in journal (Refereed)
    Abstract [en]

    The increasing use of artificial intelligence (AI) technologies across application domains has prompted our society to pay closer attention to AI's trustworthiness, fairness, interpretability, and accountability. In order to foster trust in AI, it is important to consider the potential of interactive visualization, and how such visualizations help build trust in AI systems. This manifesto discusses the relevance of interactive visualizations and makes the following four claims: i) trust is not a technical problem, ii) trust is dynamic, iii) visualization cannot address all aspects of trust, and iv) visualization is crucial for human agency in AI.

  • 11.
    Bergström, Erik
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Carlén, Urban
    University West.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    How to Include Female Students in Technical Computer Science Study Programs2016In: NU2016 Högskolan i samhället - samhället i högskolan, 2016, article id BT30Conference paper (Refereed)
    Abstract [en]

    This study examines why female students do not register in computer sciencerelated programs after submitting their application. In design for inclusion in academic culture, pedagogical implications are based on empirical findings that intend to foster a more heterogeneous group, which can be introduced to promote student’s interest in technology.

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    FULLTEXT01
  • 12.
    Dahlbom, Anders
    et al.
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Situation Modeling and Visual Analytics for Decision Support in Sports2014In: Proceedings of the 16th International Conference on Enterprise Information Systems: Volume 1 / [ed] Slimane Hammoudi, Leszek Maciaszek, José Cordeiro, SciTePress , 2014, p. 539-544Conference paper (Refereed)
    Abstract [en]

    High performance is a goal in most sporting activities, for elite athletes as well as for recreational practitioners, and the process of measuring, evaluating and improving performance is one fundamental aspect to why people engage in sports. This is a complex process which possibly involves analyzing large amounts of heterogeneous data in order to apply actions that change important properties for improved outcome. The number of computer based decision support systems in the context of data analysis for performance improvement is scarce. In this position paper we briefly review the literature, and we propose the use of information fusion, situation modeling and visual analytics as suitable tools for supporting decision makers, ranging from recreational to elite, in the process of performance evaluation.

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    FULLTEXT01
  • 13.
    Dahlbom, Anders
    et al.
    Högskolan i Skövde.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    König, Rikard
    Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT.
    Johansson, Ulf
    Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT.
    Brattberg, Peter
    Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT.
    Supporting Golf Coaching with 3D Modeling of Swings2014In: Sportinformatik X: Jahrestagung der dvs-Sektion Sportinformatik, Hamburg: Feldhaus Verlag , 2014, 10, p. 142-148Chapter in book (Refereed)
  • 14.
    Gleicher, Michael
    et al.
    University of Wisconsin - Madison, Madison, WI, United States.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics. Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Von Landesberger, Tatiana
    Universität zu Köln, Köln, Germany.
    Deussen, Oliver
    University of Konstanz, Konstanz, Germany.
    Chang, Remco
    Tufts University, Medford, MA, United States.
    Gillman, Christina
    Leipzig University, Leipzig, Germany.
    A Problem Space for Designing Visualizations2023In: IEEE Computer Graphics and Applications, ISSN 0272-1716, E-ISSN 1558-1756, Vol. 43, no 4, p. 111-120Article in journal (Refereed)
    Abstract [en]

    Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, and evaluate the things we create. The literature has many task structures (taxonomies, typologies, etc.), design spaces, and related frameworks that provide abstractions of the problems a visualization is meant to address. In this Visualization Viewpoints article, we introduce a different one, a problem space that complements existing frameworks by focusing on the needs that a visualization is meant to solve. We believe it provides a valuable conceptual tool for designing and discussing visualizations. 

  • 15.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Dahlbom, Anders
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Lebram, Mikael
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Transparency of military threat evaluation through visualizing uncertainty and system rationale2013In: Engineering Psychology and Cognitive Ergonomics: Applications and Services / [ed] Don Harris, Springer, 2013, p. 263-272Conference paper (Refereed)
    Abstract [en]

    Threat evaluation (TE) is concerned with determining the intent, capability and opportunity of detected targets. To their aid, military operators use support systems that analyse incoming data and make inferences based on the active evaluation framework. Several interface and interaction guidelines have been proposed for the implementation of TE systems; however there is a lack of research regarding how to make these systems transparent to their operators. This paper presents the results from interviews conducted with TE operators focusing on the need for and possibilities of improving the transparency of TE systems through the visualization of uncertainty and the presentation of the system rationale. © 2013 Springer-Verlag Berlin Heidelberg.

  • 16.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Davidsson, Staffan
    Volvo Car Corporation, Gothenburg, Sweden.
    Presenting system uncertainty in automotive UIs for supporting trust calibration in autonomous driving2013In: Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI’13), New York: Association for Computing Machinery (ACM) , 2013, p. 210-217Conference paper (Refereed)
    Abstract [en]

    To investigate the impact of visualizing car uncertainty on drivers' trust during an automated driving scenario, a simulator study was conducted. A between-group design experiment with 59 Swedish drivers was carried out where a continuous representation of the uncertainty of the car's ability to autonomously drive during snow conditions was displayed to one of the groups, whereas omitted for the control group. The results show that, on average, the group of drivers who were provided with the uncertainty representation took control of the car faster when needed, while they were, at the same time, the ones who spent more time looking at other things than on the road ahead. Thus, drivers provided with the uncertainty information could, to a higher degree, perform tasks other than driving without compromising with driving safety. The analysis of trust shows that the participants who were provided with the uncertainty information trusted the automated system less than those who did not receive such information, which indicates a more proper trust calibration than in the control group.

  • 17.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Ohlander, Ulrika
    Saab Aeronautics, Sweden.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Transparency of Automated Combat Classification2014In: 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 (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.

  • 18.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Explanation Methods for Bayesian Networks: review and application to a maritime scenario2009In: Proceedings of the 3rd Skövde Workshop on Information Fusion Topics (SWIFT 2009), University of Skövde , 2009, p. 28-32Conference paper (Refereed)
    Abstract [en]

    Surveillance systems analyze and present vast amounts of heterogeneous sensor data. In order to support operators while monitoring such systems, the identification of anomalous behavior or situations that might need further investigation may reduce operators’ cognitive load. Bayesian networks can be used in order to detect anomalies in data. In order to understand the outcome generated from an anomaly detection application based on Bayesian networks, proper explanations must be given to operators.

    This paper presents the findings of a literature analysis regarding what constitutes an explanation, which properties an explanation may have and a review of different explanation methods for Bayesian networks. Moreover, we present the empirical tests conducted with two of these methods in a maritime scenario. Findings from the survey and the experiments show that explanation methods for Bayesian networks can be used in order to provide operators with more detailed information to base their decisions on.

  • 19.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Pashami, Sepideh
    Halmstad University, Halmstad, Sweden.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Byttner, Stefan
    Halmstad University, Halmstad, Sweden.
    Nowaczyk, Slawomir
    Halmstad University, Halmstad, Sweden.
    Supporting analytical reasoning: A study from the automotive industry2016In: 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 (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.

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  • 20.
    Huhnstock, Nikolas Alexander
    et al.
    University of Skövde, Skövde, Sweden.
    Karlsson, Alexander
    University of Skövde, Skövde, Sweden.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL). University of Skövde, Skövde, Sweden.
    Steinhauer, H. Joe
    University of Skövde, Skövde, Sweden.
    An Infinite Replicated Softmax Model for Topic Modeling2019In: Modeling Decisions for Artificial Intelligence: 16th International Conference, MDAI 2019, Milan, Italy, September 4–6, 2019, Proceedings / [ed] Vicenç Torra, Yasuo Narukawa, Gabriella Pasi, Marco Viviani, Springer, 2019, p. 307-318Conference paper (Refereed)
    Abstract [en]

    In this paper, we describe the infinite replicated Softmax model (iRSM) as an adaptive topic model, utilizing the combination of the infinite restricted Boltzmann machine (iRBM) and the replicated Softmax model (RSM). In our approach, the iRBM extends the RBM by enabling its hidden layer to adapt to the data at hand, while the RSM allows for modeling low-dimensional latent semantic representation from a corpus. The combination of the two results is a method that is able to self-adapt to the number of topics within the document corpus and hence, renders manual identification of the correct number of topics superfluous. We propose a hybrid training approach to effectively improve the performance of the iRSM. An empirical evaluation is performed on a standard data set and the results are compared to the results of a baseline topic model. The results show that the iRSM adapts its hidden layer size to the data and when trained in the proposed hybrid manner outperforms the base RSM model.

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    Fulltext
  • 21.
    Huhnstock, Nikolas Alexander
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Karlsson, Alexander
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Steinhauer, H. Joe
    Högskolan i Skövde, Institutionen för informationsteknologi.
    On the behavior of the infinite restricted boltzmann machine for clustering2018In: SAC '18 Proceedings of the 33rd Annual ACM Symposium on Applied Computing / [ed] Hisham M. Haddad, Roger L. Wainwright, Richard Chbeir, New York, NY, USA: Association for Computing Machinery (ACM) , 2018, p. 461-470Conference paper (Refereed)
    Abstract [en]

    Clustering is a core problem within a wide range of research disciplines ranging from machine learning and data mining to classical statistics. A group of clustering approaches so-called nonparametric methods, aims to cluster a set of entities into a beforehand unspecified and unknown number of clusters, making potentially expensive pre-analysis of data obsolete. In this paper, the recently, by Cote and Larochelle introduced infinite Restricted Boltzmann Machine that has the ability to self-regulate its number of hidden parameters is adapted to the problem of clustering by the introduction of two basic cluster membership assumptions. A descriptive study of the influence of several regularization and sparsity settings on the clustering behavior is presented and results are discussed. The results show that sparsity is a key adaption when using the iRBM for clustering that improves both the clustering performances as well as the number of identified clusters.

  • 22.
    Johansson, Ulf
    et al.
    Department of Information Technology, University of Borås, Sweden.
    Konig, R.
    Department of Information Technology, University of Borås, Sweden.
    Brattberg, P.
    Department of Information Technology, University of Borås, Sweden.
    Dahlbom, A.
    School of Informatics, University of Skövde, Sweden.
    Riveiro, Maria
    Department of Information Technology, University of Borås, Sweden.
    Mining trackman golf data2016In: Proceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015, IEEE, 2016, p. 380-385Conference paper (Refereed)
    Abstract [en]

    Recently, innovative technology like Trackman has made it possible to generate data describing golf swings. In this application paper, we analyze Trackman data from 275 golfers using descriptive statistics and machine learning techniques. The overall goal is to find non-trivial and general patterns in the data that can be used to identify and explain what separates skilled golfers from poor. Experimental results show that random forest models, generated from Trackman data, were able to predict the handicap of a golfer, with a performance comparable to human experts. Based on interpretable predictive models, descriptive statistics and correlation analysis, the most distinguishing property of better golfers is their consistency. In addition, the analysis shows that better players have superior control of the club head at impact and generally hit the ball straighter. A very interesting finding is that better players also tend to swing flatter. Finally, an outright comparison between data describing the club head movement and ball flight data, indicates that a majority of golfers do not hit the ball solid enough for the basic golf theory to apply.

  • 23.
    Kinkeldey, Christoph
    et al.
    Lab for Geoinformatics and Geovisualization (g2lab), HafenCity University Hamburg, Hamburg, Germany.
    MacEachren, Alan M.
    GeoVISTA Center and Department of Geography, Penn State University, University Park, PA, USA.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Schiewe, Jochen
    Lab for Geoinformatics and Geovisualization (g2lab), HafenCity University Hamburg, Hamburg, Germany.
    Evaluating the effect of visually represented geodata uncertainty on decision-making: Systematic review, lessons learned, and recommendations2017In: Cartography and Geographic Information Science, ISSN 1523-0406, E-ISSN 1545-0465, Vol. 44, no 1, p. 1-21Article, review/survey (Refereed)
    Abstract [en]

    For many years, uncertainty visualization has been a topic of research in several disparate fields, particularly in geographical visualization (geovisualization), information visualization, and scientific visualization. Multiple techniques have been proposed and implemented to visually depict uncertainty, but their evaluation has received less attention by the research community. In order to understand how uncertainty visualization influences reasoning and decision-making using spatial information in visual displays, this paper presents a comprehensive review of uncertainty visualization assessments from geovisualization and related fields. We systematically analyze characteristics of the studies under review, i.e., number of participants, tasks, evaluation metrics, etc. An extensive summary of findings with respect to the effects measured or the impact of different visualization techniques helps to identify commonalities and differences in the outcome. Based on this summary, we derive “lessons learned” and provide recommendations for carrying out evaluation of uncertainty visualizations. As a basis for systematic evaluation, we present a categorization of research foci related to evaluating the effects of uncertainty visualization on decision-making. By assigning the studies to categories, we identify gaps in the literature and suggest key research questions for the future. This paper is the second of two reviews on uncertainty visualization. It follows the first that covers the communication of uncertainty, to investigate the effects of uncertainty visualization on reasoning and decision-making.

  • 24.
    König, Rikard
    et al.
    University of Borås, Borås, Sweden.
    Johansson, Ulf
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). University of Borås, Borås, Sweden.
    Riveiro, Maria
    University of Skövde, Skövde, Sweden.
    Brattberg, Peter
    University of Borås, Borås, Sweden.
    Modeling golf player skill using machine learning2017In: Machine Learning and Knowledge Extraction, Springer, 2017, p. 275-294Conference paper (Refereed)
    Abstract [en]

    In this study we apply machine learning techniques to Modeling Golf Player Skill using a dataset consisting of 277 golfers. The dataset includes 28 quantitative metrics, related to the club head at impact and ball flight, captured using a Doppler-radar. For modeling, cost-sensitive decision trees and random forest are used to discern between less skilled players and very good ones, i.e., Hackers and Pros. The results show that both random forest and decision trees achieve high predictive accuracy, with regards to true positive rate, accuracy and area under the ROC-curve. A detailed interpretation of the decision trees shows that they concur with modern swing theory, e.g., consistency is very important, while face angle, club path and dynamic loft are the most important evaluated swing factors, when discerning between Hackers and Pros. Most of the Hackers could be identified by a rather large deviation in one of these values compared to the Pros. Hackers, which had less variation in these aspects of the swing, could instead be identified by a steeper swing plane and a lower club speed. The importance of the swing plane is an interesting finding, since it was not expected and is not easy to explain. © 2017, IFIP International Federation for Information Processing.

  • 25.
    Lagerstedt, Erik
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Thill, Serge
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Agent Autonomy and Locus of Responsibility for Team Situation Awareness2017In: HAI '17: Proceedings of the 5th International Conference on Human Agent Interaction, New York: Association for Computing Machinery (ACM) , 2017, p. 261-269Conference paper (Refereed)
    Abstract [en]

    Rapid technical advancements have led to dramatically improved abilities for artificial agents, and thus opened up for new ways of cooperation between humans and them, from disembodied agents such as Siris to virtual avatars, robot companions, and autonomous vehicles. It is therefore relevant to study not only how to maintain appropriate cooperation, but also where the responsibility for this resides and/or may be affected. While there are previous organisations and categorisations of agents and HAI research into taxonomies, situations with highly responsible artificial agents are rarely covered. Here, we propose a way to categorise agents in terms of such responsibility and agent autonomy, which covers the range of cooperation from humans getting help from agents to humans providing help for the agents. In the resulting diagram presented in this paper, it is possible to relate different kinds of agents with other taxonomies and typical properties. A particular advantage of this taxonomy is that it highlights under what conditions certain effects known to modulate the relationship between agents (such as the protégé effect or the "we"-feeling) arise.

  • 26.
    Lagerstedt, Erik
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Thill, Serge
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Interacting with Artificial Agents2015In: Thirteenth Scandinavian Conference on Artificial Intelligence / [ed] Sławomir Nowaczyk, IOS Press, 2015, p. 184-185Conference paper (Refereed)
  • 27.
    Niklasson, Lars
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Johansson, Fredrik
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Dahlbom, Anders
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Ziemke, Tom
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Brax, Christoffer
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Kronhamn, Thomas
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Smedberg, Martin
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Warston, Håkan
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Gustavsson, Per M.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    A Unified Situation Analysis Model for Human and Machine Situation Awareness2007In: INFORMATIK 2007: Informatik trifft Logistik: Band 2: Beiträge der 37. Jahrestagung der Gesellschaft für Informatik e.V. (GI) 24. - 27. September 2007 in Bremen / [ed] Otthein Herzog, Karl-Heinz Rödiger, Marc Ronthaler, Rainer Koschke, Bonn: Gesellschaft für Informatik , 2007, p. 105-109Conference paper (Refereed)
  • 28.
    Niklasson, Lars
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Johansson, Fredrik
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Dahlbom, Anders
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Falkman, Göran
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Ziemke, Tom
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Brax, Christoffer
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Kronhamn, Thomas
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Smedberg, Martin
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Warston, Håkan
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Gustavsson, Per M.
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Extending the scope of Situation Analysis2008In: Proceedings of the 11th International Conference on Information Fusion (FUSION 2008), Cologne, Germany, June 30–July 3, 2008, IEEE Press , 2008, p. 454-461Conference paper (Refereed)
    Abstract [en]

    The use of technology to assist human decision making has been around for quite some time now. In the literature, models of both technological and human aspects of this support can be identified. However, we argue that there is a need for a unified model which synthesizes and extends existing models. In this paper, we give two perspectives on situation analysis: a technological perspective and a human perspective. These two perspectives are merged into a unified situation analysis model for semi-automatic, automatic and manual decision support (SAM)2. The unified model can be applied to decision support systems with any degree of automation. Moreover, an extension of the proposed model is developed which can be used for discussing important concepts such as common operational picture and common situation awareness.

  • 29.
    Nilsson, Maria
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Ziemke, Tom
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Investigating human-computer interaction issues in information-fusion-based decision support2008Report (Other academic)
    Abstract [en]

    Information fusion is a research area which focuses on how to combine information from many different sources to support decision making. Commonly used information fusion systems are often complex and used in military and crises management domains. The focus of information fusion research so far has been mainly on the technological aspects. There is still a lack of understanding relevant user aspects that affect the information fusion systems as a whole. This paper presents a framework of HCI issues which considers users as embedded in the context of information fusion systems. The framework aims at providing insights regarding factors that affect user interaction to inform the development of future information fusion systems. Design considerations are presented together with a heuristic evaluation of an information fusion prototype.

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  • 30.
    Ohlander, Ulrika
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Alfredson, Jens
    Saab Aeronautics, Saab AB, Linköping.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    A Teamwork Model for Fighter Pilots2016In: 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 (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.

  • 31.
    Ohlander, Ulrika
    et al.
    Saab Aeronautics, Saab AB, Linköping.
    Alfredson, Jens
    Saab Aeronautics, Saab AB, Linköping.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Elements of team effectiveness: A qualitative study with pilots2016In: 2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), IEEE Computer Society , 2016, p. 21-27Conference 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.

  • 32.
    Ohlander, Ulrika
    et al.
    Saab AB, Saab Aeronautics, Linköping, Sweden and University of Skövde, Skövde, Sweden.
    Alfredson, Jens
    Saab AB, Saab Aeronautics, Linköping, Sweden.
    Riveiro, Maria
    University of Skövde, Skövde, Sweden.
    Falkman, Göran
    University of Skövde, Skövde, Sweden.
    Fighter pilots’ teamwork: a descriptive study2019In: Ergonomics, ISSN 0014-0139, E-ISSN 1366-5847, Vol. 62, no 7, p. 880-890Article in journal (Refereed)
    Abstract [en]

    The execution of teamwork varies widely depending on the domain and task in question. Despite the considerable diversity of teams and their operation, researchers tend to aim for unified theories and models regardless of field. However, we argue that there is a need for translation and adaptation of the theoretical models to each specific domain. To this end, a case study was carried out on fighter pilots and it was investigated how teamwork is performed in this specialised and challenging environment, with a specific focus on the dependence on technology for these teams. The collaboration between the fighter pilots is described and analysed using a generic theoretical model for effective teamwork from the literature. The results show that domain-specific application and modification is needed in order for the model to capture fighter pilot’s teamwork. The study provides deeper understanding of the working conditions for teams of pilots and gives design implications for how tactical support systems can enhance teamwork in the domain.

    Practitioner summary: This article presents a qualitative interview study with fighter pilots based on a generic theoretical teamwork model applied to the fighter domain. The purpose is to understand the conditions under which teams of fighter pilots work and to provide guidance for the design of future technological aids.

  • 33.
    Ohlander, Ulrika
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Alfredson, Jens
    Saab Aeronautics, Saab AB, Linköping, Sweden.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Understanding Team Effectiveness in a Tactical Air Unit2015In: 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 (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. 

  • 34.
    Ohlander, Ulrika
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Alfredson, Jens
    Saab Aeronautics, Saab AB, Linköping, Sweden.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    User Participation in the Design of Cockpit Interfaces2017In: Advances in Ergonomics Modeling, Usability & Special Populations / [ed] Marcelo Soares, Christianne Falcão & Tareq Z. Ahram, Springer , 2017, p. 51-58Conference 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.

  • 35.
    Ohlander, Ulrika
    et al.
    Saab Aeronautics, Saab AB, Linköping, Sweden; School of Informatics, University of Skövde, Sweden.
    Alfredson, Jens
    Saab Aeronautics, Saab AB, Linköping, Sweden.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
    Helldin, Tove
    School of Informatics, University of Skövde, Sweden.
    Falkman, Göran
    School of Informatics, University of Skövde, Sweden.
    The Effects of Varying Degrees of Information on Teamwork a Study on Fighter Pilots2023In: Human Factors and Ergonomics Society Annual Meeting Proceedings, ISSN 1071-1813, E-ISSN 2169-5067, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, ISSN 2169-5067, Vol. 67, no 1, p. 1965-1970Article in journal (Refereed)
    Abstract [en]

    A team of fighter pilots in a distributed environment with limited access to information rely on technology to pursue teamwork. In order to design systems that support distributed teamwork, it is, therefore, necessary to understand how access to information affects the team members. Certain factors, such as mutual performance monitoring, shared mental models, adaptability, and backup behavior are considered essential for effective teamwork. We investigate these factors in this work, focusing on how visually communicated information affects fighter pilots’ perception of these factors. For that, a questionnaire including the teamwork factors in relation to certain defined scenarios that contain various levels of information was distributed to fighter pilots. We show that the studied factors are affected by the level of information available to the pilots. Especially, mutual performance monitoring increases with the degree of available information.

  • 36.
    Ohlson, Nils-Erik
    et al.
    Siemens Energy AB.
    Bäckstrand, Jenny
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Artificial Intelligence-enhanced Sales & Operations Planning in an Engineer-to-order context2021Conference paper (Refereed)
  • 37.
    Ohlson, Nils-Erik
    et al.
    Jönköping University, School of Engineering, JTH, Industrial Product Development, Production and Design.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Bäckstrand, Jenny
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Identification of tasks to be supported by machine learning to reduce Sales & Operations Planning challenges in an engineer-to-order context2022In: SPS2022: Proceedings of the 10th Swedish production symposium / [ed] A. H. C. Ng, A. Syberfelt, D. Högberg & M. Holm, Amsterdam: IOS Press, 2022, p. 39-50Conference paper (Refereed)
    Abstract [en]

    Sales and Operations Planning (S&OP) is a process that aims to align dimensioning efforts in a company, based on one integrated plan and with clear decision milestones. The alignment is cross-functional and connects different operations functions with each other to set an overall delivery ability. There are always challenges connecting different functions in a company which most S&OP practitioners agree with, still, that is one of the things that the S&OP-process should bridge. Digital solutions such as Enterprise Resource Planning (ERP) and other more or less sophisticated tools have contributed to an improved cross functional communication over time. S&OP in an Engineer-to-order (ETO) context, especially where engineering is a major or an equal portion as e.g., make-to-stock (MTS) and make-to-order (MTO) contexts, may experience even further challenges. Technologies within Industry 4.0 are changing the way S&OP is carried out; one of the most relevant ones is Artificial Intelligence (AI), particularly, Machine Learning (ML) that analyses data collected during these processes to find patterns and extract knowledge. The intent with this paper is to, based on S&OP-challenges, see if ML can be used to improve these challenges.

  • 38.
    Pettersson, Tobias
    et al.
    Jönköping University, School of Engineering. University of Skövde; ITAB Shop Products AB Sweden.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics. Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Löfström, Tuwe
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).
    Explainable local and global models for fine-grained multimodal product recognition2023Conference paper (Refereed)
    Abstract [en]

    Grocery product recognition techniques are emerging in the retail sector and are used to provide automatic checkout counters, reduce self-checkout fraud, and support inventory management. However, recognizing grocery products using machine learning models is challenging due to the vast number of products, their similarities, and changes in appearance. To address these challenges, more complex models are created by adding additional modalities, such as text from product packages. But these complex models pose additional challenges in terms of model interpretability. Machine learning experts and system developers need tools and techniques conveying interpretations to enable the evaluation and improvement of multimodal production recognition models.

    In this work, we propose thus an approach to provide local and global explanations that allow us to assess multimodal models for product recognition. We evaluate this approach on a large fine-grained grocery product dataset captured from a real-world environment. To assess the utility of our approach, experiments are conducted for three types of multimodal models.

    The results show that our approach provides fine-grained local explanations while being able to aggregate those into global explanations for each type of product. In addition, we observe a disparity between different multimodal models, in what type of features they learn and what modality each model focuses on. This provides valuable insight to further improve the accuracy and robustness of multimodal product recognition models for grocery product recognition.

  • 39.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
    A design theory for uncertainty visualization?2023In: Dagstuhl Reports, E-ISSN 2192-5283, Vol. 12, no 8, p. 12-13Article in journal (Refereed)
    Abstract [en]

    Despite the large volume of research on uncertainty visualization, we do not fully understand the impact of uncertainty visualization on decision-making. There is evidence of both positive and negative effects of visually depicted uncertainty on decision-making.

    This talk presents examples of evaluations carried out with practitioners in various application areas, including autonomous driving, air traffic risk assessment and maritime surveillance. I summarise the effects of the uncertainty visualizations provided on the users and their decision-making processes in these evaluations.

    Finally, we discuss the need for a design theory/space of uncertainty visualization and elaborate on the multiple dimensions/variables that such a design space should have.

  • 40.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Cognitive Evaluation of Uncertainty Visualization Methods for Decision Making2007In: Symposium on Applied Perception in Graphics and Visualization (APGV 2007), ACM Press, 2007, p. 133-133Conference paper (Refereed)
    Abstract [en]

    Uncertainty constitutes a major obstacle to effective decision making. This work presents perceptual and cognitive principles from Tufte, Chambers and Bertin as well as results from user experiments for the theoretical evaluation of uncertainty visualization techniques that aid decision making. These principles can be used in future theoretical evaluations of existing or newly developed uncertainty visualization methods before usability testing with actual users.

  • 41.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Evaluation of Normal Model Visualization for Anomaly Detection in Maritime Traffic2014In: ACM Transactions on Interactive Intelligent Systems, ISSN 2160-6455, E-ISSN 2160-6463, Vol. 4, no 1, p. 1-24Article in journal (Refereed)
    Abstract [en]

    Monitoring dynamic objects in surveillance applications is normally a demanding activity for operators, not only because of the complexity and high dimensionality of the data but also because of other factors like time constraints and uncertainty. Timely detection of anomalous objects or situations that need further investigation may reduce operators' cognitive load. Surveillance applications may include anomaly detection capabilities, but their use is not widespread, since they usually generate a high number of false alarms, they do not provide appropriate cognitive support for operators, and their outcomes can be difficult to comprehend and trust. Visual analytics can bridge the gap between computational and human approaches to detecting anomalous behavior in traffic data, making this process more transparent. As a step toward this goal of transparency, this article presents an evaluation that assesses whether visualizations of normal behavioral models of vessel traffic support two of the main analytical tasks specified during our field work in maritime control centers. The evaluation combines quantitative and qualitative usability assessments. The quantitative evaluation, which was carried out with a proof-of-concept prototype, reveals that participants who used the visualization of normal behavioral models outperformed the group which did not do so. The qualitative assessment shows that domain experts have a positive attitude towards the provision of automatic support and the visualization of normal behavioral models, since these aids may reduce reaction time and increase trust in and comprehensibility of the system

  • 42.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Evaluation of Uncertainty Visualization Techniques for Information Fusion2007Conference paper (Refereed)
    Abstract [en]

    This paper highlights the importance of uncertainty visualization in information fusion, reviews general methods of representing uncertainty and presents perceptual and cognitive principles from Tufte, Chambers and Bertin as well as users experiments documented in the literature. Examples of uncertainty representations in information fusion are analyzed using these general theories. These principles can be used in future theoretical evaluations of existing or newly developed uncertainty visualization techniques before usability testing with actual users.

  • 43.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
    Expectations, trust, and evaluation2023In: Dagstuhl Reports, E-ISSN 2192-5283, Vol. 12, no 8, p. 109-109Article in journal (Refereed)
    Abstract [en]

    This talk focuses on the role of expectations in designing explanations from Artificial Intelligence/Machine Learning (AI/ML) -based systems. Explanations are crucial for system understanding that, in turn, are very relevant to supporting trust and trust calibration in such systems. I discuss the connections between expectations, explanations and trust in human-AI/ML system interaction.

    I present two recent studies ([1, 2]) investigating if expectations modulate what people want to see and when from an AI/ML system when carrying out analytical tasks.

    We found out that,

    • For matched expectations, an explanation is often not required at all, while if one is, it is of the factual type
    • For mismatched expectations, the picture is less clear, primarily because there does not seem to be a unique strategy, although mechanistic explanations are requested more often than other types

    Overall, user expectations are a significant variable in determining the most suitablecontent of explanations (including whether an explanation is needed at all). More research isneeded to investigate the relationship between expectations and explanations, and how theysupport trust calibration.

  • 44.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL). University of Skövde.
    Explainable AI for maritime anomaly detection and autonomous driving2020In: Dagstuhl Reports, E-ISSN 2192-5283, Vol. 9, no 11, p. 29-30Article in journal (Refereed)
  • 45.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Research proposal: Information Visualization for Information Fusion2007Report (Other academic)
    Abstract [en]

    Information fusion is a field of research that strives to establish theories, techniques and tools that exploit synergies in data retrieved from multiple sources. In many real-world applications huge amounts of data need to be gathered, evaluated and analyzed in order to make the right decisions. An important key element of information fusion is the adequate presentation of the data that guides decision-making processes efficiently. This is where theories and tools developed in information visualization, visual data mining and human computer interaction (HCI) research can be of great support. This report presents an overview of information fusion and information visualization, highlighting the importance of the latter in information fusion research. Information visualization techniques that can be used in information fusion are presented and analyzed providing insights into its strengths and weakness. Problems and challenges regarding the presentation of information that the decision maker faces in the ground situation awareness scenario (GSA) lead to open questions that are assumed to be the focus of further research

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  • 46.
    Riveiro, Maria
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    The importance of visualization and interaction in the anomaly detection process2013In: Innovative approaches of data visualization and visual analytics / [ed] Mao Lin Huang & Weidong Huang, Information Science Reference , 2013, p. 133-150Chapter in book (Refereed)
  • 47.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Visual Analytics for Maritime Anomaly Detection2011Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The surveillance of large sea areas typically involves  the analysis of huge quantities of heterogeneous data.  In order to support the operator while monitoring maritime traffic, the identification of anomalous behavior or situations that might need further investigation may reduce operators' cognitive load. While it is worth acknowledging that existing mining applications support the identification of anomalies, autonomous anomaly detection systems are rarely used for maritime surveillance. Anomaly detection is normally a complex task that can hardly be solved by using purely visual or purely computational methods. This thesis suggests and investigates the adoption of visual analytics principles to support the detection of anomalous vessel behavior in maritime traffic data. This adoption involves studying the analytical reasoning process that needs to be supported,  using combined automatic and visualization approaches to support such process, and evaluating such integration. The analysis of data gathered during interviews and participant observations at various maritime control centers and the inspection of video recordings of real anomalous incidents lead to a characterization of the analytical reasoning process that operators go through when monitoring traffic. These results are complemented with a literature review of anomaly detection techniques applied to sea traffic. A particular statistical-based technique is implemented, tested, and embedded in a proof-of-concept prototype that allows user involvement in the detection process. The quantitative evaluation carried out by employing the prototype reveals that participants who used the visualization of normal behavioral models outperformed the group without aid. The qualitative assessment shows that  domain experts are positive towards providing automatic support and the visualization of normal behavioral models, since these aids may reduce reaction time, as well as increase trust and comprehensibility in the system. Based on the lessons learned, this thesis provides recommendations for designers and developers of maritime control and anomaly detection systems, as well as guidelines for carrying out evaluations of visual analytics environments.

  • 48.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Visually supported reasoning under uncertain conditions: Effects of domain expertise on air traffic risk assessment2016In: Spatial Cognition and Computation, ISSN 1387-5868, E-ISSN 1573-9252, Vol. 16, no 2, p. 133-153Article in journal (Refereed)
    Abstract [en]

    This article investigates the impact that domain expertise has on risk assessment when analyzing uncertain geographical and sensor data. The differences between novice and expert air traffic operators were examined taking into account the performance of identifying and classifying threatening targets, the time needed to carry out such classifications, and the confidence reported for each decision. The results show that confidence was significantly higher for the expert group. This was supported by the after-test questionnaire because none of the novice participants reported being more confident with the visualizations of uncertainty provided. No significant differences regarding time and performance were found between the groups, even if experts needed, on average, more time to make a decision. Based on the collected logs, the experienced participants more often accessed the detailed information for each object presented by the tool tip. Both the time taken and the data accessed might indicate that experts had better situation awareness. Finally, the experts reported higher workload values related to performance.

  • 49.
    Riveiro, Maria
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Bergström, Erik
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Carlén, Urban
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Inför en ökad jämställdhet i datavetenskapliga utbildningsprogram2012Conference paper (Refereed)
  • 50.
    Riveiro, Maria
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Dahlbom, Anders
    Högskolan i Skövde.
    König, Rikard
    Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT.
    Johansson, Ulf
    Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT.
    Brattberg, Peter
    Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT.
    Supporting Golf Coaching and Swing Instruction with Computer-Based Training Systems2015In: Learning and Collaboration Technologies: Second International Conference, LCT 2015, Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015, Proceedings / [ed] Panayiotis Zaphiris, Andri Ioannou, 2015, p. 279-290Conference paper (Refereed)
    Abstract [en]

    Golf is a popular sport around the world. Since an accomplished golf swing is essential for succeeding in this sport, golf players spend a considerable amount of time perfecting their swing. In order to guide the design of future computer-based training systems that support swing instruction, this paper analyzes the data gathered during interviews with golf instructors and participant observations of actual swing coaching sessions. Based on our field work, we describe the characteristics of a proficient swing, how the instructional sessions are normally carried out and the challenges professional instructors face. Taking into account these challenges, we outline which desirable capabilities future computer-based training systems for professional golf instructors should have.

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