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Görzen, “Trust Me, I’m Confident – Are Confident Members of the Crowd Better at Evaluating Business Model Ideas?,” presented at the Proceedings of the 42nd International Conference on Information Systems (ICIS).","chicago":"Laux, Florian, and Thomas Görzen. “Trust Me, I’m Confident – Are Confident Members of the Crowd Better at Evaluating Business Model Ideas?” In <i>Proceedings of the 42nd International Conference on Information Systems (ICIS)</i>, n.d."},"publication_status":"accepted","title":"Trust Me, I’m Confident – Are Confident Members of the Crowd Better at Evaluating Business Model Ideas?","conference":{"name":"Proceedings of the 42nd International Conference on Information Systems (ICIS)"},"date_updated":"2022-01-06T06:56:56Z","date_created":"2021-10-01T12:58:36Z","author":[{"last_name":"Laux","full_name":"Laux, Florian","id":"50293","first_name":"Florian"},{"last_name":"Görzen","full_name":"Görzen, Thomas","first_name":"Thomas"}]},{"status":"public","type":"journal_article","publication":"ChemElectroChem","language":[{"iso":"eng"}],"_id":"25272","user_id":"32","department":[{"_id":"321"},{"_id":"301"}],"year":"2021","citation":{"ama":"Engelkemeier K, Sun A, Voswinkel D, Grydin O, Schaper M, Bremser W. Zinc Anodizing: Structural Diversity of Anodic Zinc Oxide Controlled by the Type of Electrolyte. <i>ChemElectroChem</i>. Published online 2021:2155-2168. doi:<a href=\"https://doi.org/10.1002/celc.202100216\">10.1002/celc.202100216</a>","chicago":"Engelkemeier, Katja, Aijia Sun, Dietrich Voswinkel, Olexandr Grydin, Mirko Schaper, and Wolfgang Bremser. “Zinc Anodizing: Structural Diversity of Anodic Zinc Oxide Controlled by the Type of Electrolyte.” <i>ChemElectroChem</i>, 2021, 2155–68. <a href=\"https://doi.org/10.1002/celc.202100216\">https://doi.org/10.1002/celc.202100216</a>.","ieee":"K. Engelkemeier, A. Sun, D. Voswinkel, O. Grydin, M. Schaper, and W. Bremser, “Zinc Anodizing: Structural Diversity of Anodic Zinc Oxide Controlled by the Type of Electrolyte,” <i>ChemElectroChem</i>, pp. 2155–2168, 2021, doi: <a href=\"https://doi.org/10.1002/celc.202100216\">10.1002/celc.202100216</a>.","apa":"Engelkemeier, K., Sun, A., Voswinkel, D., Grydin, O., Schaper, M., &#38; Bremser, W. 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Afifi, F.J. Sauer, H. Karl, in: 2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS’21), Hyderabad, India, 2021.","mla":"Afifi, Haitham, et al. “Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding.” <i>2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS’21)</i>, 2021.","apa":"Afifi, H., Sauer, F. J., &#38; Karl, H. (2021). Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding. <i>2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS’21)</i>.","ama":"Afifi H, Sauer FJ, Karl H. Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding. In: <i>2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS’21)</i>. ; 2021.","chicago":"Afifi, Haitham, Fabian Jakob Sauer, and Holger Karl. “Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding.” In <i>2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS’21)</i>. Hyderabad, India, 2021.","ieee":"H. Afifi, F. J. Sauer, and H. Karl, “Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding,” 2021."},"_id":"25278","project":[{"name":"Akustische Sensornetzwerke - Teilprojekt \"Verteilte akustische Signalverarbeitung über funkbasierte Sensornetzwerke","_id":"27"}],"user_id":"65718","keyword":["reinforcement learning","admission control","wireless sensor networks"],"ddc":["000"],"file_date_updated":"2021-10-04T10:43:19Z","language":[{"iso":"eng"}],"publication":"2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS'21)","type":"conference","abstract":[{"text":"Using Service Function Chaining (SFC) in wireless networks became popular in many domains like networking and multimedia. It relies on allocating network resources to incoming SFCs requests, via a Virtual Network Embedding (VNE) algorithm, so that it optimizes the performance of the SFC. When the load of incoming requests -- competing for the limited network resources -- increases, it becomes challenging to decide which requests should be admitted and which one should be rejected. In this work, we propose a deep Reinforcement learning (RL) solution that can learn the admission policy for different dependencies, such as the service lifetime and the priority of incoming requests. We compare the deep RL solution to a first-come-first-serve baseline that admits a request whenever there are available resources. We show that deep RL outperforms the baseline and provides higher acceptance rate with low rejections even when there are enough resources.","lang":"eng"}],"status":"public","file":[{"creator":"hafifi","date_created":"2021-10-04T10:43:19Z","date_updated":"2021-10-04T10:43:19Z","file_id":"25279","access_level":"closed","file_name":"Preprint___Reinforcement_Learning_for_Dynamic_Resource_Allocation_in_Wireless_Networks.pdf","file_size":534737,"content_type":"application/pdf","relation":"main_file","success":1}]},{"ddc":["620"],"keyword":["microphone utility","microphone selection","wireless acoustic sensor network","network delay","reinforcement learning"],"file_date_updated":"2021-10-04T10:58:07Z","language":[{"iso":"eng"}],"project":[{"name":"Akustische Sensornetzwerke - Teilprojekt \"Verteilte akustische Signalverarbeitung über funkbasierte Sensornetzwerke","_id":"27"}],"_id":"25281","user_id":"65718","abstract":[{"text":"Wireless Acoustic Sensor Networks (WASNs) have a wide range of audio signal processing applications. Due to the spatial diversity of the microphone and their relative position to the acoustic source, not all microphones are equally useful for subsequent audio signal processing tasks, nor do they all have the same wireless data transmission rates. Hence, a central task in WASNs is to balance a microphone’s estimated acoustic utility against its transmission delay, selecting a best-possible subset of microphones to record audio signals.\r\n\r\nIn this work, we use reinforcement learning to decide if a microphone should be used or switched off to maximize the acoustic quality at low transmission delays, while minimizing switching frequency. In experiments with moving sources in a simulated acoustic environment, our method outperforms naive baseline comparisons","lang":"eng"}],"file":[{"content_type":"application/pdf","relation":"main_file","success":1,"creator":"hafifi","date_created":"2021-10-04T10:58:07Z","date_updated":"2021-10-04T10:58:07Z","access_level":"closed","file_id":"25282","file_name":"ITG_2021_paper_26 (3).pdf","file_size":283616}],"status":"public","type":"conference","publication":"14. ITG Conference on Speech Communication (ITG 2021)","title":"Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities","date_updated":"2022-01-06T06:56:59Z","date_created":"2021-10-04T10:59:50Z","author":[{"first_name":"Haitham","last_name":"Afifi","id":"65718","full_name":"Afifi, Haitham"},{"first_name":"Michael","full_name":"Guenther, Michael","last_name":"Guenther"},{"first_name":"Andreas","full_name":"Brendel, Andreas","last_name":"Brendel"},{"full_name":"Karl, Holger","id":"126","last_name":"Karl","first_name":"Holger"},{"first_name":"Walter","full_name":"Kellermann, Walter","last_name":"Kellermann"}],"year":"2021","citation":{"ama":"Afifi H, Guenther M, Brendel A, Karl H, Kellermann W. Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities. In: <i>14. ITG Conference on Speech Communication (ITG 2021)</i>. ; 2021.","chicago":"Afifi, Haitham, Michael Guenther, Andreas Brendel, Holger Karl, and Walter Kellermann. “Reinforcement Learning-Based Microphone Selection in Wireless Acoustic Sensor Networks Considering Network and Acoustic Utilities.” In <i>14. ITG Conference on Speech Communication (ITG 2021)</i>, 2021.","ieee":"H. Afifi, M. Guenther, A. Brendel, H. Karl, and W. Kellermann, “Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities,” 2021.","short":"H. Afifi, M. Guenther, A. Brendel, H. Karl, W. Kellermann, in: 14. ITG Conference on Speech Communication (ITG 2021), 2021.","mla":"Afifi, Haitham, et al. “Reinforcement Learning-Based Microphone Selection in Wireless Acoustic Sensor Networks Considering Network and Acoustic Utilities.” <i>14. ITG Conference on Speech Communication (ITG 2021)</i>, 2021.","bibtex":"@inproceedings{Afifi_Guenther_Brendel_Karl_Kellermann_2021, title={Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities}, booktitle={14. ITG Conference on Speech Communication (ITG 2021)}, author={Afifi, Haitham and Guenther, Michael and Brendel, Andreas and Karl, Holger and Kellermann, Walter}, year={2021} }","apa":"Afifi, H., Guenther, M., Brendel, A., Karl, H., &#38; Kellermann, W. (2021). Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities. <i>14. ITG Conference on Speech Communication (ITG 2021)</i>."},"has_accepted_license":"1"},{"status":"public","type":"conference","publication":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","language":[{"iso":"eng"}],"user_id":"65718","project":[{"name":"Akustische Sensornetzwerke - Teilprojekt \"Verteilte akustische Signalverarbeitung über funkbasierte Sensornetzwerke","_id":"27"}],"_id":"25293","citation":{"bibtex":"@inproceedings{Gunther_Afifi_Brendel_Karl_Kellermann_2021, title={Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks}, DOI={<a href=\"https://doi.org/10.1109/icassp39728.2021.9414528\">10.1109/icassp39728.2021.9414528</a>}, booktitle={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, author={Gunther, Michael and Afifi, Haitham and Brendel, Andreas and Karl, Holger and Kellermann, Walter}, year={2021} }","mla":"Gunther, Michael, et al. “Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks.” <i>ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>, 2021, doi:<a href=\"https://doi.org/10.1109/icassp39728.2021.9414528\">10.1109/icassp39728.2021.9414528</a>.","short":"M. Gunther, H. Afifi, A. Brendel, H. Karl, W. Kellermann, in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.","apa":"Gunther, M., Afifi, H., Brendel, A., Karl, H., &#38; Kellermann, W. (2021). Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks. <i>ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. <a href=\"https://doi.org/10.1109/icassp39728.2021.9414528\">https://doi.org/10.1109/icassp39728.2021.9414528</a>","ieee":"M. Gunther, H. Afifi, A. Brendel, H. Karl, and W. Kellermann, “Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks,” 2021, doi: <a href=\"https://doi.org/10.1109/icassp39728.2021.9414528\">10.1109/icassp39728.2021.9414528</a>.","chicago":"Gunther, Michael, Haitham Afifi, Andreas Brendel, Holger Karl, and Walter Kellermann. “Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks.” In <i>ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>, 2021. <a href=\"https://doi.org/10.1109/icassp39728.2021.9414528\">https://doi.org/10.1109/icassp39728.2021.9414528</a>.","ama":"Gunther M, Afifi H, Brendel A, Karl H, Kellermann W. Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks. 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ACM, 2021. <a href=\"https://doi.org/10.1145/3446871.3469757\">https://doi.org/10.1145/3446871.3469757</a>."},"year":"2021"},{"date_updated":"2022-01-06T06:57:06Z","volume":53,"author":[{"last_name":"Schulte","full_name":"Schulte, Carsten","id":"60311","first_name":"Carsten"},{"first_name":"Brett","last_name":"A. Becker","full_name":"A. Becker, Brett"}],"date_created":"2021-10-05T14:18:48Z","title":"ITiCSE 2021 recap","doi":"10.1145/3483403.3483405","issue":"3","year":"2021","intvolume":"        53","page":"3-4","citation":{"apa":"Schulte, C., &#38; A. Becker, B. (2021). ITiCSE 2021 recap. <i>ACM SIGCSE Bull.</i>, <i>53</i>(3), 3–4. <a href=\"https://doi.org/10.1145/3483403.3483405\">https://doi.org/10.1145/3483403.3483405</a>","mla":"Schulte, Carsten, and Brett A. Becker. “ITiCSE 2021 Recap.” <i>ACM SIGCSE Bull.</i>, vol. 53, no. 3, 2021, pp. 3–4, doi:<a href=\"https://doi.org/10.1145/3483403.3483405\">10.1145/3483403.3483405</a>.","bibtex":"@article{Schulte_A. 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