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Ergebnisse nach Hochschule und Institut
Publikation Investigating roundabout properties and bicycle accident occurrence at Swiss roundabouts: A logistic regression approach(MDPI, 2019) Hollenstein, Daria; Hess, Martin; Jordan, Denis; Bleisch, SusanneThe positive effects of active mobility on mental and physical health as well as on air quality are widely acknowledged. Increasing the share of active travel is therefore an aim in many countries. Providing bicycle-safe infrastructure is one way to promote cycling. Roundabouts are a common traffic infrastructure and are supposed to facilitate safe and smooth traffic flow. However, data on road traffic accidents indicate an over-proportional involvement of cyclists in accidents at roundabouts. In the present study, the influence of roundabout geometry and traffic flow on bicycle accident occurrence was investigated using a logistic regression approach on twelve parameters of N = 294 mostly small- and mini-sized single-lane roundabouts in the Canton of Berne, Switzerland. Average weekday motorized traffic was identified as a major factor in explaining bicycle accident occurrence at roundabouts. Further, the radius of the central island, the location of the roundabout (in town vs. out of town) and the number of legs were significantly related to bicycle accident occurrence. While these results are in general agreement with findings from similar studies, the findings regarding the central island’s radius and the number of legs underpin the need for roundabout type-specific studies: Some parameters may not prove relevant in intermediate- to large-sized roundabouts, but become critical in small or mini roundabouts, which are common in Switzerland and numerous in the present sample.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Relationship of critical dynamics, functional connectivity, and states of consciousness in large-scale human brain networks(Elsevier, 2019) Lee, Heonsoo; Golkowski, Daniel; Jordan, Denis; Berger, Sebastian; Ilg, Rüdiger; Lee, Joseph; Mashour, George A.; Lee, UnCheol; Avidan, Michael S.; Blain-Moraes, Stefanie; Golmirzaie, Goodarz; Hardie, Randall; Hogg, Rosemary; Janke, Ellen; Kelz, Max B.; Maier, Kaitlyn; Mashour, George A.; Maybrier, Hannah; McKinstry-Wu, Andrew; Muench, Maxwell; Ochroch, Andrew; Palanca, Ben J.A.; Picton, Paul; Schwarz, E. Marlon; Tarnal, Vijay; Vanini, Giancarlo; Vlisides, Phillip E.Recent modeling and empirical studies support the hypothesis that large-scale brain networks function near a critical state. Similar functional connectivity patterns derived from resting state empirical data and brain network models at criticality provide further support. However, despite the strong implication of a relationship, there has been no principled explanation of how criticality shapes the characteristic functional connectivity in large-scale brain networks. Here, we hypothesized that the network science concept of partial phase locking is the underlying mechanism of optimal functional connectivity in the resting state. We further hypothesized that the characteristic connectivity of the critical state provides a theoretical boundary to quantify how far pharmacologically or pathologically perturbed brain connectivity deviates from its critical state, which could enable the differentiation of various states of consciousness with a theory-based metric. To test the hypothesis, we used a neuroanatomically informed brain network model with the resulting source signals projected to electroencephalogram (EEG)-like sensor signals with a forward model. Phase lag entropy (PLE), a measure of phase relation diversity, was estimated and the topography of PLE was analyzed. To measure the distance from criticality, the PLE topography at a critical state was compared with those of the EEG data from baseline consciousness, isoflurane anesthesia, ketamine anesthesia, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state. We demonstrate that the partial phase locking at criticality shapes the functional connectivity and asymmetric anterior-posterior PLE topography, with low (high) PLE for high (low) degree nodes. The topographical similarity and the strength of PLE differentiates various pharmacologic and pathologic states of consciousness. Moreover, this model-based EEG network analysis provides a novel metric to quantify how far a pharmacologically or pathologically perturbed brain network is away from critical state, rather than merely determining whether it is in a critical or non-critical state.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Accurate visual localization in outdoor and indoor environments exploiting 3D image spaces as spatial reference(International Society for Photogrammetry and Remote Sensing, 2018) Rettenmund, Daniel; Fehr, Markus; Cavegn, Stefan; Nebiker, StephanIn this paper, we present a method for visual localization and pose estimation based on 3D image spaces. The method works in indoor and outdoor environments and does not require the presence of control points or markers. The method is evaluated with different sensors in an outdoor and an indoor test field. The results of our research show the viability of single image localization with absolute position accuracies at the decimetre level for outdoor environments and 5 cm or better for indoor environments. However, the evaluation also revealed a number of limitations of single image visual localization in real-world environments. Some of them could be addressed by an alternative AR-based localization approach, which we also present and compare in this paper. We then discuss the strengths and weaknesses of the two approaches and show possibilities for combining them to obtain accurate and robust visual localization in an absolute coordinate frame.04B - Beitrag KonferenzschriftPublikation Exploratory geovisualizations for supporting the qualitative analysis and synthesis of place-related emotion data(North American Cartographic Information Society, 2019) Bleisch, Susanne; Hollenstein, DariaLocations become places through personal significance and experience. While place data are not emotion data, per se, personal significance and experience are often emotional. In this paper, we explore the potential of using visual data exploration to support the qualitative analysis of place-related emotion data. To do so, we draw upon Creswell’s (2009) definition of place to define a generic data model that contains emotion data for a given location and its locale. For each data dimension in our model, we present symbolization options that can be combined to create a range of interactive visualizations, specifically supporting re-expression. We discuss the usefulness of example visualizations, created based on a data set from a pilot study on how elderly women experience their neighborhood. We find that the visualizations support four broad qualitative data analysis tasks: revising categorizations, making connections and relationships, aggregating for synthesis, and corroborating evidence by combining sense of place with locale information to support a holistic interpretation of place data. In conclusion, the paper contributes to the literature in three ways. It provides a generic data model and associated symbolization options, and uses examples to show how place-related emotion data can be visualized. Further, the example visualizations make explicit how re-expression, the combination of emotion data with locale information, and visualization of vagueness and linked data support the analysis of emotion data. Finally, we advocate for visualization-supported qualitative data analysis in interdisciplinary teams so that more suitable maps are used and so that cartographers can better understand and support qualitative data analysis.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Visual feature engineering(Institut Geomatik, Hochschule für Architektur, Bau und Geomatik FHNW, 2018) Bleisch, SusanneFeature engineering is a key concept in machine learning describing the process of defining the characteristics of an observed phenomenon in a way that makes it usable by an algorithm (e.g., [3]). This process often includes domain knowledge to make the features, as well as the results of the algorithms, meaningful in the respective application area. In data analysis generally, including visual data analysis, the obtained results or insights are often dependent on the employed analysis method as well as the parameters and their imensions used. A simple but well-known example is the modifiable area unit problem [5]. Depending on the size and form of the spatial units chosen to aggregate the data, different visualizations and potentially interpretations of the information may result. In some cases, the chosen methods or algorithms and their parameters can be argued to be the right ones to support a specific analysis task, in other cases a sensitivity analysis may be helpful in determining the optimal values. Additionally, visual analytics, allowing tight integration of the interaction with the methods and parameters and the visualizations, has the potential to support the evaluation of the right or sensible analysis method and its parameters as well as to provide provenance information for the finally employed approach.05 - Forschungs- oder ArbeitsberichtPublikation Robust and accurate image-based georeferencing exploiting relative orientation constraints(Copernicus, 2018) Cavegn, Stefan; Blaser, S.; Nebiker, Stephan; Haala, N.Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2 cm in an indoor area, and 3 cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2–3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Development of a portable high performance mobile mapping system using the robot operating system(Copernicus, 2018) Blaser, Stefan; Cavegn, Stefan; Nebiker, StephanThe rapid progression in digitalization in the construction industry and in facility management creates an enormous demand for the efficient and accurate reality capturing of indoor spaces. Cloud-based services based on georeferenced metric 3D imagery are already extensively used for infrastructure management in outdoor environments. The goal of our research is to enable such services for indoor applications as well. For this purpose, we designed a portable mobile mapping research platform with a strong focus on acquiring accurate 3D imagery. Our system consists of a multi-head panorama camera in combination with two multi-profile LiDAR scanners and a MEMS-based industrial grade IMU for LiDAR-based online and offline SLAM. Our modular implementation based on the Robot Operating System enables rapid adaptations of the sensor configuration and the acquisition software. The developed workflow provides for completely GNSS-independent data acquisition and camera pose estimation using LiDAR-based SLAM. Furthermore, we apply a novel image-based georeferencing approach for further improving camera poses. First performance evaluations show an improvement from LiDAR-based SLAM to image-based georeferencing by an order of magnitude: from 10–13 cm to 1.3–1.8 cm in absolute 3D point accuracy and from 8–12 cm to sub-centimeter in relative 3D point accuracy.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Evaluating the impact of visualization of risk upon emergency route-planning(Taylor & Francis, 2019) Cheong, Lisa; Kinkeldey, Christoph; Burfurd, Ingrid; Bleisch, Susanne; Duckham, MattThis paper reports on a controlled experiment evaluating how different cartographic representations of risk affect participants’ performance on a complex spatial decision task: route planning. The specific experimental scenario used is oriented towards emergency route-planning during flood response. The experiment compared six common abstract and metaphorical graphical symbolizations of risk. The results indicate a pattern of less-preferred graphical symbolizations associated with slower responses and lower-risk route choices. One mechanism that might explain these observed relationships would be that more complex and effortful maps promote closer attention paid by participants and lower levels of risk taking. Such user considerations have important implications for the design of maps and mapping interfaces for emergency planning and response. The data also highlights the importance of the ‘right decision, wrong outcome problem’ inherent in decision-making under uncertainty: in individual instances, more risky decisions do not always lead to worse outcomes.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Teaching ordinal patterns to a computer. Efficient encoding algorithms based on the Lehmer code(MDPI, 2019) Berger, Sebastian; Kravtsiv, Andrii; Schneider, Gerhard; Jordan, DenisOrdinal patterns are the common basis of various techniques used in the study of dynamical systems and nonlinear time series analysis. The present article focusses on the computational problem of turning time series into sequences of ordinal patterns. In a first step, a numerical encoding scheme for ordinal patterns is proposed. Utilising the classical Lehmer code, it enumerates ordinal patterns by consecutive non-negative integers, starting from zero. This compact representation considerably simplifies working with ordinal patterns in the digital domain. Subsequently, three algorithms for the efficient extraction of ordinal patterns from time series are discussed, including previously published approaches that can be adapted to the Lehmer code. The respective strengths and weaknesses of those algorithms are discussed, and further substantiated by benchmark results. One of the algorithms stands out in terms of scalability: its run-time increases linearly with both the pattern order and the sequence length, while its memory footprint is practically negligible. These properties enable the study of high-dimensional pattern spaces at low computational cost. In summary, the tools described herein may improve the efficiency of virtually any ordinal pattern-based analysis method, among them quantitative measures like permutation entropy and symbolic transfer entropy, but also techniques like forbidden pattern identification. Moreover, the concepts presented may allow for putting ideas into practice that up to now had been hindered by computational burden. To enable smooth evaluation, a function library written in the C programming language, as well as language bindings and native implementations for various numerical computation environments are provided in the supplements.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Portable image-based high performance mobile mapping system in underground environments. System configuration and performance evalutation.(Copernicus, 2019) Blaser, S.; Nebiker, Stephan; Wisler, D.The progression in urbanization increases the need for different types of underground infrastructure. Consequently, infrastructure and life cycle management are rapidly gaining in importance. Mobile reality capturing systems and cloud-based services exploiting georeferenced metric 3D imagery are already extensively used for infrastructure management in outdoor environments. These services minimise dangerous and expensive field visits or measurement campaigns. In this paper, we introduce the BIMAGE Backpack, a portable image-based mobile mapping system for 3D data acquisition in indoor environments. The system consists of a multi-head panorama camera, two multi-profile laser scanners and an inertial measurement unit. With this system, we carried out underground measurement campaigns in the Hagerbach Test Gallery, located in Flums Hochwiese, Switzerland. For our performance evaluations in two different tunnel sections, we employed LiDAR SLAM as well as advanced image-based georeferencing. The obtained absolute accuracies were in the range from 6.2 to 7.4 cm. The relative accuracy, which for many applications is even more important, was in the range of 2–6 mm. These figures demonstrate an accuracy improvement of the subsequent image-based georeferencing over LiDAR SLAM by about an order of magnitude. The investigations show the application potential of image-based portable mobile mapping systems for infrastructure inventory and management in large underground facilities.01A - Beitrag in wissenschaftlicher Zeitschrift