51. |
- Vinas, Victor, 1988, et al.
(author)
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Cross-connections in drinking water distribution networks: Quantitative microbial risk assessment in combination with fault tree analysis and hydraulic modelling
- 2022
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In: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 831
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Journal article (peer-reviewed)abstract
- Deficiencies in drinking water distribution networks, such as cross-connections, may lead to contamination of the drinking water and pose a serious health risk to consumers. Cross-connections and backflows are considered among the most severe public health risks in distribution networks. The aim of this paper was to provide a framework for estimating the risk of infection from cross-connection and backflow events. Campylobacter, norovirus, and Cryptosporidium were chosen as reference pathogens for this study. The theoretical framework was constructed based on the fault tree analysis methodology. National aggregated cross-connection incident data was used to calculate the probability of a contamination event occurring in Swedish networks. Three risk cases were evaluated: endemic, elevated, and extreme. Quantitative microbial risk assessment (QMRA) was used to assess daily risk of infection for average national estimates. The framework was also evaluated using local data from the Gothenburg network. The daily risk of infection from cross-connection and backflow events in Swedish networks was generally above an acceptable target level of 10−6 for all reference pathogens and modelled cases; the exception was for the Gothenburg system where the risk was lower than 10−7. An outbreak case study was used to validate the framework results. For the outbreak case study, contaminant transport in the network was simulated using hydraulic modelling (EPANET), and risk estimates were calculated using QMRA. The outbreak simulation predicted between 97 and 148 symptomatic infections, while the epidemiological survey conducted during the outbreak reported 179 cases of illness. The fault tree analysis framework was successfully validated using an outbreak case study, though it was shown on the example of Gothenburg that local data is still needed for well-performing systems. The framework can help inform microbial risk assessments for drinking water suppliers, especially ones with limited resources and expertise in this area.
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52. |
- Grabowski, Alexander, 1993
(author)
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VCSEL Equivalent Circuits and Silicon Photonics Integration
- 2022
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Doctoral thesis (other academic/artistic)abstract
- The vertical-cavity surface-emitting laser (VCSEL) is a light source of great importance for numerous industrial and consumer products. The main application areas are datacom and sensing. The datacom industry uses GaAs-based VCSELs for optical interconnects, the short-reach fiber optical communication links used to transfer large amounts of data at high rates between units within data centers and supercomputers. In the area of sensing, VCSELs are largely used in consumer products such as smart phones (e.g. face ID and camera auto focus), computer mice, and automobiles (e.g. gesture recognition and LIDAR for autonomous driving). In this work, an advanced physics-based equivalent circuit model for datacom VCSELs has been developed. The model lends itself to co-design and co-optimization with driver and receiver ICs, thereby enabling higher data rate transceivers with bandwidth limited VCSELs and photodiodes. The model also facilitates an understanding of how each physical process within the VCSEL affects the VCSEL static and dynamic performance. It has been applied to study the impact of carrier transport and capture on VCSEL dynamics. The work also includes micro-transfer-printing of GaAs-based single-mode VCSELs on silicon nitride photonic integrated circuits (PICs). Such PICs are increasingly used for e.g. compact and highly functional bio-photonic sensors. Transfer printing of VCSELs enables the much-needed on-PIC integration of power efficient light sources. The bottom-emitting VCSELs are printed above grating couplers on the PIC and optical feedback is used to control the polarization for efficient coupling to the silicon nitride waveguide. Wavelength tuning, as required by the bio-sensing application, is achieved by direct current modulation.
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53. |
- Lang, Xiao, 1992, et al.
(author)
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A semi-empirical model for ship speed loss prediction at head sea and its validation by full-scale measurements
- 2020
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In: Ocean Engineering. - : Elsevier BV. - 0029-8018. ; 209
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Journal article (peer-reviewed)abstract
- This paper proposes a semi-empirical model to estimate a ship’s speed loss at head sea. In the model, the formulas to estimate a ship’s added resistance due to waves have been further developed to better consider the ship hull forms, in addition to other main particulars. Based on the model experimental tests of 11 ships in regular head waves, the new formulas have more flexible forms and can better fit the test results than other similar models. In addition, this model proposes a significant wave height based correction factor multiplied to the conventional integration to compute wave resistance in irregular waves. This factor is supposed to consider the impact of coupled ship motions in high waves on a ship’s added resistance due to waves. The model is validated by the full-scale measurement from two vessels, a PCTC and a chemical tanker. The encountered weather conditions along the sailing routes are extracted from the reanalysis metocean data. The results indicate that the proposed model can provide quite accurate predictions of ship speed loss in head sea operations.
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54. |
- Zwane, Sicelukwanda, et al.
(author)
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Safe Trajectory Sampling in Model-Based Reinforcement Learning
- 2023
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In: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2023-August
-
Conference paper (peer-reviewed)abstract
- Model-based reinforcement learning aims to learn a policy to solve a target task by leveraging a learned dynamics model. This approach, paired with principled handling of uncertainty allows for data-efficient policy learning in robotics. However, the physical environment has feasibility and safety constraints that need to be incorporated into the policy before it is safe to execute on a real robot. In this work, we study how to enforce the aforementioned constraints in the context of model-based reinforcement learning with probabilistic dynamics models. In particular, we investigate how trajectories sampled from the learned dynamics model can be used on a real robot, while fulfilling user-specified safety requirements. We present a model-based reinforcement learning approach using Gaussian processes where safety constraints are taken into account without simplifying Gaussian assumptions on the predictive state distributions. We evaluate the proposed approach on different continuous control tasks with varying complexity and demonstrate how our safe trajectory-sampling approach can be directly used on a real robot without violating safety constraints.
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55. |
- Bianchi Piccinini, Giulio, 1982, et al.
(author)
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How Do Drivers Respond to Silent Automation Failures? Driving Simulator Study and Comparison of Computational Driver Braking Models
- 2020
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In: Human Factors. - Chalmers University of Technology, Gothenburg, Sweden.; Volvo Group Trucks Technology, Gothenburg, Sweden.; Virginia Tech Transportation Institute, Blacksburg, USA.; University of Leeds, UK.; VTI, Gothenburg, Sweden. : SAGE Publications. - 1547-8181 .- 0018-7208. ; 62:7, s. 1212-1229
-
Journal article (peer-reviewed)abstract
- Objective: This paper aims to describe and test novel computational driver models, predicting drivers’ brake reaction times (BRTs) to different levels of lead vehicle braking, during driving with cruise control (CC) and during silent failures of adaptive cruise control (ACC). Background: Validated computational models predicting BRTs to silent failures of automation are lacking but are important for assessing the safety benefits of automated driving. Method: Two alternative models of driver response to silent ACC failures are proposed: a looming prediction model, assuming that drivers embody a generative model of ACC, and a lower gain model, assuming that drivers’ arousal decreases due to monitoring of the automated system. Predictions of BRTs issued by the models were tested using a driving simulator study. Results: The driving simulator study confirmed the predictions of the models: (a) BRTs were significantly shorter with an increase in kinematic criticality, both during driving with CC and during driving with ACC; (b) BRTs were significantly delayed when driving with ACC compared with driving with CC. However, the predicted BRTs were longer than the ones observed, entailing a fitting of the models to the data from the study. Conclusion: Both the looming prediction model and the lower gain model predict well the BRTs for the ACC driving condition. However, the looming prediction model has the advantage of being able to predict average BRTs using the exact same parameters as the model fitted to the CC driving data. Application: Knowledge resulting from this research can be helpful for assessing the safety benefits of automated driving.
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56. |
- Jacobsson, Martin, 1976-, et al.
(author)
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Deep Learning-Based Early Prediction of Intraoperative Hypotension
- 2021
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Conference paper (peer-reviewed)abstract
- This work focuses on predicting near-term onset of hypotension prior to onset using convolutional neural networks. Based solely on the arterial blood pressure curve, our initial attempt can predict an onset with 60% sensitivity and 80% specificity 5-15 minutes before onset.Clinical relevance Hypotension is common during large surgery. By identifying and treating hypotensive episodes early, preferably even before onset, hypotension and its associate post- surgery complications are reduced. Even a prediction with 80% sensitivity/specificity is valuable for the anesthesiologist.
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57. |
- Rosén, Julia
(author)
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What did you expect? : A human-centered approach to investigating and reducing the social robot expectation gap
- 2024
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Doctoral thesis (other academic/artistic)abstract
- We live in a complex world where we proactively plan and execute various behaviors by forming expectations in real time. Expectations are beliefs regarding the future state of affairs and they play an integral part of our perception, attention, and behavior. Over time, our expectations become more accurate as we interact with the world and others around us. People interact socially with other people by inferring others' purposes, intentions, preferences, beliefs, emotions, thoughts, and goals. Similar inferences may occur when we interact with social robots. With anthropomorphic design, these robots are designed to mimic people physically and behaviorally. As a result, users predominantly infer agency in social robots, often leading to mismatched expectations of the robots' capabilities, which ultimately influences the user experience. In this thesis, the role and relevance of users' expectations in first-hand social human-robot interaction (sHRI) was investigated. There are two major findings. First, in order to study expectations in sHRI, the social robot expectation gap evaluation framework was developed. This framework supports the systematic study and evaluation of expectations over time, considering the unique context where the interaction is unfolding. Use of the framework can inform sHRI researchers and designers on how to manage users’ expectations, not only in the design, but also during evaluation and presentation of social robots. Expectations can be managed by identifying what kinds of expectations users have and aligning these through design and dissemination which ultimately creates more transparent and successful interactions and collaborations. The framework is a tool for achieving this goal. Second, results show that previous experience has a strong impact on users’ expectations. People have different expectations of social robots and view social robots as both human-like and as machines. Expectations of social robots can vary according to the source of the expectation, with those who had previous direct experiences of robots having different expectations than those who relied on indirect experiences to generate expectations. One consequence of these results is that expectations can be a confounding variable in sHRI research. Previous experience with social robots can prime users in future interactions with social robots. These findings highlight the unique experiences users have, even when faced with the same robot. Users' expectations and how they change over time shapes the users’ individual needs and preferences and should therefore be considered in the interpretation of sHRI. In doing so, the social robot expectation gap can be reduced.
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58. |
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59. |
- Dima, Elijs, 1990-, et al.
(author)
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Joint effects of depth‑aiding augmentations and viewing positionson the quality of experience in augmented telepresence
- 2020
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In: Quality and User Experience. - Switzerland : Springer Nature. - 2366-0139 .- 2366-0147. ; 5
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Journal article (peer-reviewed)abstract
- Virtual and augmented reality is increasingly prevalent in industrial applications, such as remote control of industrial machinery,due to recent advances in head-mounted display technologies and low-latency communications via 5G. However, theinfluence of augmentations and camera placement-based viewing positions on operator performance in telepresence systemsremains unknown. In this paper, we investigate the joint effects of depth-aiding augmentations and viewing positionson the quality of experience for operators in augmented telepresence systems. A study was conducted with 27 non-expertparticipants using a real-time augmented telepresence system to perform a remote-controlled navigation and positioningtask, with varied depth-aiding augmentations and viewing positions. The resulting quality of experience was analyzed viaLikert opinion scales, task performance measurements, and simulator sickness evaluation. Results suggest that reducing thereliance on stereoscopic depth perception via camera placement has a significant benefit to operator performance and qualityof experience. Conversely, the depth-aiding augmentations can partly mitigate the negative effects of inferior viewingpositions. However the viewing-position based monoscopic and stereoscopic depth cues tend to dominate over cues basedon augmentations. There is also a discrepancy between the participants’ subjective opinions on augmentation helpfulness,and its observed effects on positioning task performance.
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60. |
- Larsson, Clara, et al.
(author)
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Visualizing Invisible Environmental Data in VR: Development and Implementation of Design Concepts for Communicating Urban Air Quality in a Virtual City Model
- 2023
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In: Communications in Computer and Information Science Volume 1819 CCIS, Pages 253 - 267. - : Springer. - 1865-0929 .- 1865-0937. ; , s. 253-267
-
Conference paper (peer-reviewed)abstract
- As cities continue to grow, the desire to combine densification with sustainability and greenery may present a challenge to air quality, resulting from reduced ventilation caused by dense buildings and vegetation. To support the careful urban planning required, effective and interactive tools that can visualize and communicate information about air quality to stakeholders are essential. In a transdisciplinary research project aiming to explore such visualizations a prototype pedagogical virtual reality tool was developed, allowing users to explore the impact of aspects of the built environment upon urban air quality. The tool was evaluated with adolescents in upper secondary school through interviews and observations, as well as with the general public through a questionnaire study. This paper provides insights, potential solutions, and initial assessments relevant to data visualization in 3D and immersive analytics in urban planning and stakeholder communication. Identified challenges include difficulties with color association and data distinguishability, and as well as tool complexity relating to the many features requested by experts involved in a transdisciplinary project.
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