Ramsey, A., Kale, A., Kassa, Y., Gandhi, R., & Ricks, B. (2023). Toward Interactive Visualizations for Explaining Machine Learning Models. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 837–852). Omaha, USA: University of Nebraska at Omaha.
Abstract: Researchers and end users generally demand more trust and transparency from Machine learning (ML) models due to the complexity of their learned rule spaces. The field of eXplainable Artificial Intelligence (XAI) seeks to rectify this problem by developing methods of explaining ML models and the attributes used in making inferences. In the area of structural health monitoring of bridges, machine learning can offer insight into the relation between a bridge’s conditions and its environment over time. In this paper, we describe three visualization techniques that explain decision tree (DT) ML models that identify which features of a bridge make it more likely to receive repairs. Each of these visualizations enable interpretation, exploration, and clarification of complex DT models. We outline the development of these visualizations, along with their validity by experts in AI and in bridge design and engineering. This work has inherent benefits in the field of XAI as a direction for future research and as a tool for interactive visual explanation of ML models.
|
|
Sterl, S., Billig, A., Taffo, F. W., & Gerhold, L. (2023). Visualizing the Psychosocial Situation in Crises and Disasters: Conceptualizing a Multi-Functional Crisis Information Platform (CIP-PS). In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 252–262). Omaha, USA: University of Nebraska at Omaha.
Abstract: Crises and disasters are becoming more frequent, long-lasting, complex, and interdependent. This can lead to negative psychosocial consequences in vulnerable population groups, increasing the need to (1) monitor psychosocial indicators and (2) make information on psychosocial topics available to decision-makers, the scientific community, and the public. In this WiPe paper, we present a way to systematically visualize, research, and document different types of psychosocial data in crises and disasters by developing a “Multi-Functional Crisis Information Platform for Psychosocial Situations”, called CIP-PS. The CIP-PS has three components, i.e., an information dashboard (CIP-DAB), a research platform (CIP-REP), and a documentation (CIP-DOC) component which together help visualize, research and document psychosocial topics, such as the psychosocial situation picture in Germany. The platform is a valuable tool for presenting relevant psychosocial information in the context of disaster public health. Its strength lies in an extensive connection between the three components related to healthcare informatics.
|
|
Benaben, F., Fertier, A., Cerabona, T., Moradkhani, N., Lauras, M., & Montreuil, B. (2023). Decision Support in uncertain contexts: Physics of Decision and Virtual Reality. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 54–66). Omaha, USA: University of Nebraska at Omaha.
Abstract: Virtual Reality (VR) is often used for its ability to mimic reality. However, VR can also be used for its ability to escape reality. In that case, on the one hand VR provides a visualization environment where the user’s senses are still in a familiar context (one can see if something is in front, behind, up, down, far or close), yet on the other hand, VR allows to escape the usual limits of reality by providing a way to turn abstract concepts into concrete and interactive objects. In this paper, the dynamic management of a complex industrial system (a supply chain) is enabled in a VR prototypical environment, through the management of a physical trajectory that can be deflected by the impact of any potentialities such as risks or opportunities, seen as physical objects in the performance space.
|
|
Christoph Lamers. (2022). Electronic Visualization for Situational Awareness in Control Rooms. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 1008–1011). Tarbes, France.
Abstract: It is generally agreed in crisis management that a comprehensive visualization of the situation is crucial for an appropriate situational awareness of the staff personnel in control rooms. Therefore an expert group of fire officers in the German State North Rhine Westphalia developed a system for this purpose known as the “tactical wall”. The core of the system is a situation map of the relevant area with so-called tactical signs, i. e. defined graphic symbols for hazards, response units and tactical measures. Moreover, the assignment of response units to tactical sectors or staging areas as well as other relevant information such as the management organization is displayed at defined places within the wall. While the system was purely manual in its original version, a new digital version was recently developed. The user interfaces of this system are web-based and can by intuitively operated after a minor training effort.
|
|
Ryan K. Williams, Nicole Abaid, James McClure, Nathan Lau, Larkin Heintzman, Amanda Hashimoto, et al. (2020). Collaborative Multi-Robot Multi-Human Teams in Search and Rescue. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 973–983). Blacksburg, VA (USA): Virginia Tech.
Abstract: Robots such as unmanned aerial vehicles (UAVs) deployed for search and rescue (SAR) can explore areas where human searchers cannot easily go and gather information on scales that can transform SAR strategy. Multi-UAV teams therefore have the potential to transform SAR by augmenting the capabilities of human teams and providing information that would otherwise be inaccessible. Our research aims to develop new theory and technologies for field deploying autonomous UAVs and managing multi-UAV teams working in concert with multi-human teams for SAR. Specifically, in this paper we summarize our work in progress towards these goals, including: (1) a multi-UAV search path planner that adapts to human behavior; (2) an in-field distributed computing prototype that supports multi-UAV computation and communication; (3) behavioral modeling that yields spatially localized predictions of lost person location; and (4) an interface between human searchers and UAVs that facilitates human-UAV interaction over a wide range of autonomy.
|
|