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    <title language="eng">ChatGPT as a Subject Matter Expert in the Parameterization of Bayesian Network Classifiers</title>
    <parentTitle language="eng">Proceedings of the 2025 28th International Conference on Information Fusion (FUSION 2025)</parentTitle>
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    <title language="eng">AI-Mediated Communication in E-Commerce: Implications for Customer Trust</title>
    <abstract language="eng">Generative artificial intelligence (AI) technologies offer new potential for marketing and customer operations, such as automation and personalization of customer service. However, more must be understood about how AI‐mediated communication (AI‐MC) affects customer trust. We conducted an online experiment to investigate the impact of AI‐MC on customer trust in an online retail context. We presented N = 294 participants with two email scenarios describing a product return context, labeled as written by either (a) a service employee, (b) a service employee assisted by AI, or (c) AI on behalf of the service employee. We further varied levels of service criticality to consider customers' perception of vulnerability. Our findings revealed higher customer trust ratings in the online retailer when the email communications were written by the service employee, compared to those written by the service employee assisted by AI. When analyzing the different components of trust, it was found that communications written by the service employee assisted by AI reduced perceptions of both the online retailer's benevolence and integrity, while communications written by AI on behalf of the employee led to lower perceived integrity of the online retailer. Surprisingly, service criticality did not affect trust ratings. We discuss the managerial implications of integrating generative AI into customer service in the context of the EU AI Act, which came into force on 1 August 2024.</abstract>
    <parentTitle language="eng">International Journal of Consumer Studies</parentTitle>
    <identifier type="issn">1470-6431</identifier>
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    <author>
      <first_name>Christine</first_name>
      <last_name>Hennighausen</last_name>
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    <author>
      <first_name>Vanessa Gabriela</first_name>
      <last_name>Yarza Navarro-Schär</last_name>
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    <author>
      <first_name>Eric</first_name>
      <last_name>Eller</last_name>
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    <id>6241</id>
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    <title language="eng">Quantitative Kernel Estimation from Traffic Signs using Slanted Edge Spatial Frequency Response as a Sharpness Metric</title>
    <abstract language="eng">The sharpness is a critical optical property of automotive cameras, measured by the Spatial Frequency Response (SFR) within the end of line (EOL) test after manufacturing. This work presents a method to estimate the blurring kernel of automotive camera for state monitoring. To achieve this, Principal Component Analysis (PCA) is performed, using synthetic kernels generated by Zemax. The PCA model is built with approximately 1300 base kernels representing spatially variant point spread functions (PSFs). This model generates kernel samples during the estimation process. Synthetic images are created by convolving the synthetic kernels with reference traffic sign images and compared with real-life data captured by an automotive camera. These synthetic data are utilized for algorithm development, and later on validation is performed on real-life data. The algorithm extracts two 45 x 45 pixels regions of interest (ROIs) containing slanted edges from the blurred image and crops matching ROIs from a reference sharp image. Each candidate kernel blurs the reference ROIs, and the resulting Spatial Frequency Response (SFR) is compared with the blurred ROIs’ SFR. Differential evolution optimization minimizes the SFR difference, selecting the kernel that best matches the observed blur. The final kernel is evaluated against the true kernel for accuracy. Structural similarity index measure (SSIM) between the original and estimated blurred ROIs ranges from 0.808 to 0.945. For true vs. estimated kernels, SSIM varies from 0.92 to 0.98. Pearson correlation coefficients range from 0.84 to 0.99, Cosine similarity from 0.86 to 0.98, and mean squared error (MSE) from 1.1 x 10-5 to 8.3 x 10-5. Validation on real-life camera images shows that the SSIM between estimated ROI is 0.82 indicating a sufficient level of accuracy in kernel estimation to detect potential degradation of the camera.</abstract>
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    <author>
      <first_name>Amit</first_name>
      <last_name>Pandey</last_name>
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    <author>
      <first_name>Zubair Akhtar</first_name>
      <last_name>Mohd</last_name>
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    <author>
      <first_name>Nandana Kappuva</first_name>
      <last_name>Veettil</last_name>
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    <author>
      <first_name>Bernhard</first_name>
      <last_name>Wunderle</last_name>
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    <author>
      <first_name>Gordon</first_name>
      <last_name>Elger</last_name>
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    <id>6235</id>
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    <completedDate>2025-10-01</completedDate>
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    <title language="eng">AWARE2ALL: Human Centric Interaction and Safety Systems for Increasing the Share of Automated Vehicles</title>
    <abstract language="eng">The AWARE2ALL project is designed to address the new challenges of Highly Automated Vehicles (HAVs) from a human-centric perspective. These vehicles will allow occupants to engage in non-driving activities, rising research questions about occupant behavior, activities, and Human-Machine Interfaces (HMI) to keep them aware of the situation and the automation mode. The project aims to ensure safe operation of HAVs by developing safety and HMI systems that provide a holistic understanding of the scene. This includes continuous monitoring of the interior situation and advanced passive safety systems for occupant safety, as well as a surround perception system and external HMI for the safety of Human Road Users (HRUs). AWARE2ALL is paving the way for HAV deployment by effectively addressing changes in road safety and interactions between different road users caused by the emergence of HAVs. It is developing innovative technologies, assessment tools, and methodologies to adapt to new scenarios in mixed traffic. The project builds on previous research and aims to mitigate new safety risks associated with the introduction of HAVs.</abstract>
    <parentTitle language="eng">Transport Transitions: Advancing Sustainable and Inclusive Mobility, Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland-Volume 1: Safe and Equitable Transport</parentTitle>
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    <author>
      <first_name>Marcos</first_name>
      <last_name>Nieto</last_name>
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      <first_name>Ciaran</first_name>
      <last_name>McNally</last_name>
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      <first_name>Oihana</first_name>
      <last_name>Otaegui</last_name>
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      <first_name>Páraic</first_name>
      <last_name>Carroll</last_name>
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      <first_name>Maria</first_name>
      <last_name>Panou</last_name>
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      <first_name>Beatriz</first_name>
      <last_name>Martinez-Pastor</last_name>
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    <author>
      <first_name>Christian</first_name>
      <last_name>Birkner</last_name>
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      <first_name>Bidisha</first_name>
      <last_name>Ghosh</last_name>
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      <first_name>Ondrej</first_name>
      <last_name>Vaculin</last_name>
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      <first_name>Marina</first_name>
      <last_name>Efthymiou</last_name>
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      <last_name>Rodríguez</last_name>
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      <first_name>Nikolaos</first_name>
      <last_name>Valantasis-Kanellos</last_name>
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    <collection role="persons" number="23939">Birkner, Christian</collection>
    <collection role="persons" number="26510">Vaculin, Ondrej</collection>
    <thesisPublisher>Technische Hochschule Ingolstadt</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-haw/files/6235/978-3-031-88974-5_112.pdf</file>
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    <id>6236</id>
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    <pageLast/>
    <pageNumber>29</pageNumber>
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    <publisherName>arXiv</publisherName>
    <publisherPlace>Ithaca</publisherPlace>
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    <completedDate>2025-10-01</completedDate>
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    <title language="eng">Asymptotic behavior of the Arrow–Hurwicz differential system with Tikhonov regularization</title>
    <abstract language="eng">In a real Hilbert space setting, we investigate the asymptotic behavior of the solutions of the classical Arrow–Hurwicz differential system combined with Tikhonov regularizing terms. Under some newly proposed conditions on the Tikhonov terms involved, we show that the solutions of the regularized Arrow–Hurwicz differential system strongly converge toward the element of least norm within its set of zeros. Moreover, we provide fast asymptotic decay rate estimates for the so-called primal-dual gap function and the norm of the solutions' velocity. If, in addition, the Tikhonov regularizing terms are decreasing, we provide some refined estimates in the sense of an exponentially weighted moving average. Under the additional assumption that the governing operator of the Arrow–Hurwicz differential system satisfies a reverse Lipschitz condition, we further provide a fast rate of strong convergence of the solutions toward the unique zero. We conclude our study by deriving the corresponding decay rate estimates with respect to the so-called viscosity curve. Numerical experiments illustrate our theoretical findings.</abstract>
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      <last_name>Battahi</last_name>
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      <first_name>Zaki</first_name>
      <last_name>Chbani</last_name>
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      <first_name>Simon</first_name>
      <last_name>Niederländer</last_name>
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      <first_name>Hassan</first_name>
      <last_name>Riahi</last_name>
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    <thesisPublisher>Technische Hochschule Ingolstadt</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-haw/files/6236/2411.17656v2.pdf</file>
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    <id>6228</id>
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    <pageNumber>8</pageNumber>
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    <publisherName>arXiv</publisherName>
    <publisherPlace>Ithaca</publisherPlace>
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    <completedDate>2025-09-26</completedDate>
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    <title language="eng">Comparison of Localization Algorithms between Reduced-Scale and Real-Sized Vehicles Using Visual and Inertial Sensors</title>
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    <author>
      <first_name>Tobias</first_name>
      <last_name>Kern</last_name>
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    <author>
      <first_name>Leon</first_name>
      <last_name>Tolksdorf</last_name>
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    <author>
      <first_name>Christian</first_name>
      <last_name>Birkner</last_name>
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    <id>6223</id>
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    <publisherName>IEEE</publisherName>
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    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2025-09-22</completedDate>
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    <title language="eng">Convolutional Neural Networks and Thresholding Approaches for Single and Multi-Sensor Detection of Partial Discharges in Electrical Machine Stators</title>
    <parentTitle language="eng">Proceedings of the 15th International 2025 IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED)</parentTitle>
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      <first_name>Marcelo Lobo</first_name>
      <last_name>Heldwein</last_name>
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      <first_name>Christian</first_name>
      <last_name>Endisch</last_name>
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    <abstract language="eng">Driving automation aims to enhance comfort, safety, and traffic flow by removing the human driver from the control loop. However, the human experience of commuting involves more than just reaching a destination or assuming the role of a driver. Factors like personal driving style and courtesy towards fellow road users are integral to the driving experience but often overlooked in the development of driving algorithms for automated vehicles. In this study, we explored the needs of passengers in highly automated vehicles. A qualitative use case analysis was conducted (N=16). In a second study, N=15 participants experienced the resulting use cases in an automated vehicle. In these scenarios, they were able to interact with the automation through a cooperation HMI. Results indicate that most participants expressed a desire for cooperative driving, albeit varying with the driving situation. Moreover, allowing cooperation improves passengers’ overall experience by satisfying psychological needs for autonomy, security, competence, and relatedness.</abstract>
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    <abstract language="deu">Mit der auf seiner Dissertation aufbauenden Monografie Wissen in Zahlen? Zur Herstellung quantitativen Wissens in der Sozialwissenschaft, zeigt Andreas Schadauer anhand von zwei empirischen Fallstudien auf, wie Umfragedaten zunächst zu Zahlen und Statistiken werden, denen im weiteren Verlauf der Rezeption ein nahezu faktischer Status der Objektivität zugeschriebenwird. Dafür zeichnet er in der ersten Fallstudie den Weg der Daten nach, die im Rahmen der Household Finance and Consumption Survey (HFCS) der Österreichischen Nationalbank (OeNB) zwischen 2010–2011 generiert wurden. Als zweite Fallstudie wählt er die österreichische Immobilienvermögenserhebung von 2008, die zum Zeitpunkt der Feldforschung bereits abgeschlossen war. Beide Datensätze wurden mit dem Anspruch an Repräsentativität generiert und stellen in der österreichischen Debatte um die nationale Vermögensverteilung wichtige Referenzen dar.&#13;
&#13;
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