[{"related_material":{"link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Drude_Poster.pdf","relation":"supplementary_material","description":"Poster"}]},"citation":{"apa":"Drude, L., Heymann, J., Boeddeker, C., &#38; Haeb-Umbach, R. (2018). NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing. In <i>ITG 2018, Oldenburg, Germany</i>.","short":"L. Drude, J. Heymann, C. Boeddeker, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.","mla":"Drude, Lukas, et al. “NARA-WPE: A Python Package for Weighted Prediction Error Dereverberation in Numpy and Tensorflow for Online and Offline Processing.” <i>ITG 2018, Oldenburg, Germany</i>, 2018.","bibtex":"@inproceedings{Drude_Heymann_Boeddeker_Haeb-Umbach_2018, title={NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing}, booktitle={ITG 2018, Oldenburg, Germany}, author={Drude, Lukas and Heymann, Jahn and Boeddeker, Christoph and Haeb-Umbach, Reinhold}, year={2018} }","ieee":"L. Drude, J. Heymann, C. Boeddeker, and R. Haeb-Umbach, “NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing,” in <i>ITG 2018, Oldenburg, Germany</i>, 2018.","chicago":"Drude, Lukas, Jahn Heymann, Christoph Boeddeker, and Reinhold Haeb-Umbach. “NARA-WPE: A Python Package for Weighted Prediction Error Dereverberation in Numpy and Tensorflow for Online and Offline Processing.” In <i>ITG 2018, Oldenburg, Germany</i>, 2018.","ama":"Drude L, Heymann J, Boeddeker C, Haeb-Umbach R. NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing. In: <i>ITG 2018, Oldenburg, Germany</i>. ; 2018."},"year":"2018","author":[{"last_name":"Drude","full_name":"Drude, Lukas","id":"11213","first_name":"Lukas"},{"full_name":"Heymann, Jahn","id":"9168","last_name":"Heymann","first_name":"Jahn"},{"last_name":"Boeddeker","id":"40767","full_name":"Boeddeker, Christoph","first_name":"Christoph"},{"last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242","first_name":"Reinhold"}],"date_created":"2019-07-12T05:29:54Z","oa":"1","date_updated":"2022-01-06T06:51:11Z","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Drude_Paper.pdf","open_access":"1"}],"title":"NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing","type":"conference","publication":"ITG 2018, Oldenburg, Germany","status":"public","abstract":[{"lang":"eng","text":"NARA-WPE is a Python software package providing implementations of the weighted prediction error (WPE) dereverberation algorithm. WPE has been shown to be a highly effective tool for speech dereverberation, thus improving the perceptual quality of the signal and improving the recognition performance of downstream automatic speech recognition (ASR). It is suitable both for single-channel and multi-channel applications. The package consist of (1) a Numpy implementation which can easily be integrated into a custom Python toolchain, and (2) a TensorFlow implementation which allows integration into larger computational graphs and enables backpropagation through WPE to train more advanced front-ends. This package comprises of an iterative offline (batch) version, a block-online version, and a frame-online version which can be used in moderately low latency applications, e.g. digital speech assistants."}],"user_id":"40767","department":[{"_id":"54"}],"project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"_id":"11873","language":[{"iso":"eng"}]},{"year":"2018","citation":{"mla":"Despotovic, Vladimir, et al. “Machine Learning Techniques for Semantic Analysis of Dysarthric Speech: An Experimental Study.” <i>Speech Communication 99 (2018) 242-251 (Elsevier B.V.)</i>, 2018.","short":"V. Despotovic, O. Walter, R. Haeb-Umbach, Speech Communication 99 (2018) 242-251 (Elsevier B.V.) (2018).","bibtex":"@article{Despotovic_Walter_Haeb-Umbach_2018, title={Machine learning techniques for semantic analysis of dysarthric speech: An experimental study}, journal={Speech Communication 99 (2018) 242-251 (Elsevier B.V.)}, author={Despotovic, Vladimir and Walter, Oliver and Haeb-Umbach, Reinhold}, year={2018} }","apa":"Despotovic, V., Walter, O., &#38; Haeb-Umbach, R. (2018). Machine learning techniques for semantic analysis of dysarthric speech: An experimental study. <i>Speech Communication 99 (2018) 242-251 (Elsevier B.V.)</i>.","ama":"Despotovic V, Walter O, Haeb-Umbach R. Machine learning techniques for semantic analysis of dysarthric speech: An experimental study. <i>Speech Communication 99 (2018) 242-251 (Elsevier BV)</i>. 2018.","chicago":"Despotovic, Vladimir, Oliver Walter, and Reinhold Haeb-Umbach. “Machine Learning Techniques for Semantic Analysis of Dysarthric Speech: An Experimental Study.” <i>Speech Communication 99 (2018) 242-251 (Elsevier B.V.)</i>, 2018.","ieee":"V. Despotovic, O. Walter, and R. Haeb-Umbach, “Machine learning techniques for semantic analysis of dysarthric speech: An experimental study,” <i>Speech Communication 99 (2018) 242-251 (Elsevier B.V.)</i>, 2018."},"oa":"1","date_updated":"2022-01-06T06:51:12Z","author":[{"full_name":"Despotovic, Vladimir","last_name":"Despotovic","first_name":"Vladimir"},{"full_name":"Walter, Oliver","last_name":"Walter","first_name":"Oliver"},{"last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242","first_name":"Reinhold"}],"date_created":"2019-07-12T05:30:44Z","title":"Machine learning techniques for semantic analysis of dysarthric speech: An experimental study","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/SpeechCommunication_2018_Walter_Paper.pdf","open_access":"1"}],"publication":"Speech Communication 99 (2018) 242-251 (Elsevier B.V.)","type":"journal_article","abstract":[{"text":"We present an experimental comparison of seven state-of-the-art machine learning algorithms for the task of semantic analysis of spoken input, with a special emphasis on applications for dysarthric speech. Dysarthria is a motor speech disorder, which is characterized by poor articulation of phonemes. In order to cater for these noncanonical phoneme realizations, we employed an unsupervised learning approach to estimate the acoustic models for speech recognition, which does not require a literal transcription of the training data. Even for the subsequent task of semantic analysis, only weak supervision is employed, whereby the training utterance is accompanied by a semantic label only, rather than a literal transcription. Results on two databases, one of them containing dysarthric speech, are presented showing that Markov logic networks and conditional random fields substantially outperform other machine learning approaches. Markov logic networks have proved to be especially robust to recognition errors, which are caused by imprecise articulation in dysarthric speech.","lang":"eng"}],"status":"public","_id":"11916","department":[{"_id":"54"}],"user_id":"44006","language":[{"iso":"eng"}]},{"department":[{"_id":"54"}],"user_id":"44006","_id":"12898","language":[{"iso":"eng"}],"publication":"ICASSP 2018, Calgary, Canada","type":"conference","status":"public","abstract":[{"text":"Deep clustering (DC) and deep attractor networks (DANs) are a data-driven way to monaural blind source separation. Both approaches provide astonishing single channel performance but have not yet been generalized to block-online processing. When separating speech in a continuous stream with a block-online algorithm, it needs to be determined in each block which of the output streams belongs to whom. In this contribution we solve this block permutation problem by introducing an additional speaker identification embedding to the DAN model structure. We motivate this model decision by analyzing the embedding topology of DC and DANs and show, that DC and DANs themselves are not sufficient for speaker identification. This model structure (a) improves the signal to distortion ratio (SDR) over a DAN baseline and (b) provides up to 61% and up to 34% relative reduction in permutation error rate and re-identification error rate compared to an i-vector baseline, respectively.","lang":"eng"}],"author":[{"first_name":"Lukas","id":"11213","full_name":"Drude, Lukas","last_name":"Drude"},{"first_name":"Thilo","last_name":"von Neumann","full_name":"von Neumann, Thilo"},{"last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold"}],"date_created":"2019-07-30T14:22:53Z","date_updated":"2022-01-06T06:51:24Z","oa":"1","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/ICASSP_2018_Drude2_Paper.pdf","open_access":"1"}],"title":"Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation","related_material":{"link":[{"description":"Slides","relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2018/ICASSP_2018_Drude2_Slides.pdf"}]},"citation":{"chicago":"Drude, Lukas, Thilo von Neumann, and Reinhold Haeb-Umbach. “Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation.” In <i>ICASSP 2018, Calgary, Canada</i>, 2018.","ieee":"L. Drude, T. von Neumann, and R. Haeb-Umbach, “Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation,” in <i>ICASSP 2018, Calgary, Canada</i>, 2018.","ama":"Drude L, von Neumann T, Haeb-Umbach R. Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation. In: <i>ICASSP 2018, Calgary, Canada</i>. ; 2018.","apa":"Drude, L., von Neumann, T., &#38; Haeb-Umbach, R. (2018). Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation. In <i>ICASSP 2018, Calgary, Canada</i>.","mla":"Drude, Lukas, et al. “Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation.” <i>ICASSP 2018, Calgary, Canada</i>, 2018.","bibtex":"@inproceedings{Drude_von Neumann_Haeb-Umbach_2018, title={Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation}, booktitle={ICASSP 2018, Calgary, Canada}, author={Drude, Lukas and von Neumann, Thilo and Haeb-Umbach, Reinhold}, year={2018} }","short":"L. Drude, T. von Neumann, R. Haeb-Umbach, in: ICASSP 2018, Calgary, Canada, 2018."},"year":"2018"},{"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2018/ICASSP_2018_Drude_Paper.pdf"}],"title":"Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation","author":[{"last_name":"Drude","full_name":"Drude, Lukas","id":"11213","first_name":"Lukas"},{"first_name":" Takuya ","last_name":"Higuchi,","full_name":"Higuchi,,  Takuya "},{"last_name":"Kinoshita","full_name":"Kinoshita, Keisuke ","first_name":"Keisuke "},{"first_name":"Tomohiro ","last_name":"Nakatani","full_name":"Nakatani, Tomohiro "},{"last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold"}],"date_created":"2019-07-30T14:42:15Z","date_updated":"2022-01-06T06:51:24Z","oa":"1","citation":{"short":"L. Drude,  Takuya  Higuchi, K. Kinoshita, T. Nakatani, R. Haeb-Umbach, in: ICASSP 2018, Calgary, Canada, 2018.","mla":"Drude, Lukas, et al. “Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation.” <i>ICASSP 2018, Calgary, Canada</i>, 2018.","bibtex":"@inproceedings{Drude_Higuchi,_Kinoshita_Nakatani_Haeb-Umbach_2018, title={Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation}, booktitle={ICASSP 2018, Calgary, Canada}, author={Drude, Lukas and Higuchi,  Takuya  and Kinoshita, Keisuke  and Nakatani, Tomohiro  and Haeb-Umbach, Reinhold}, year={2018} }","apa":"Drude, L., Higuchi,  Takuya , Kinoshita, K., Nakatani, T., &#38; Haeb-Umbach, R. (2018). Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation. In <i>ICASSP 2018, Calgary, Canada</i>.","ieee":"L. Drude,  Takuya  Higuchi, K. Kinoshita, T. Nakatani, and R. Haeb-Umbach, “Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation,” in <i>ICASSP 2018, Calgary, Canada</i>, 2018.","chicago":"Drude, Lukas,  Takuya  Higuchi, Keisuke  Kinoshita, Tomohiro  Nakatani, and Reinhold Haeb-Umbach. “Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation.” In <i>ICASSP 2018, Calgary, Canada</i>, 2018.","ama":"Drude L, Higuchi,  Takuya , Kinoshita K, Nakatani T, Haeb-Umbach R. Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation. In: <i>ICASSP 2018, Calgary, Canada</i>. ; 2018."},"year":"2018","related_material":{"link":[{"description":"Poster","relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2018/ICASSP_2018_Drude_Poster.pdf"}]},"language":[{"iso":"eng"}],"department":[{"_id":"54"}],"user_id":"44006","_id":"12900","status":"public","abstract":[{"text":"Deep attractor networks (DANs) are a recently introduced method to blindly separate sources from spectral features of a monaural recording using bidirectional long short-term memory networks (BLSTMs). Due to the nature of BLSTMs, this is inherently not online-ready and resorting to operating on blocks yields a block permutation problem in that the index of each speaker may change between blocks. We here propose the joint modeling of spatial and spectral features to solve the block permutation problem and generalize DANs to multi-channel meeting recordings: The DAN acts as a spectral feature extractor for a subsequent model-based clustering approach. We first analyze different joint models in batch-processing scenarios and finally propose a block-online blind source separation algorithm. The efficacy of the proposed models is demonstrated on reverberant mixtures corrupted by real recordings of multi-channel background noise. We demonstrate that both the proposed batch-processing and the proposed block-online system outperform (a) a spatial-only model with a state-of-the-art frequency permutation solver and (b) a spectral-only model with an oracle block permutation solver in terms of signal to distortion ratio (SDR) gains.","lang":"eng"}],"publication":"ICASSP 2018, Calgary, Canada","type":"conference"},{"abstract":[{"text":"This work examines acoustic beamformers employing neural networks (NNs) for mask prediction as front-end for automatic speech recognition (ASR) systems for practical scenarios like voice-enabled home devices. To test the versatility of the mask predicting network, the system is evaluated with different recording hardware, different microphone array designs, and different acoustic models of the downstream ASR system. Significant gains in recognition accuracy are obtained in all configurations despite the fact that the NN had been trained on mismatched data. Unlike previous work, the NN is trained on a feature level objective, which gives some performance advantage over a mask related criterion. Furthermore, different approaches for realizing online, or adaptive, NN-based beamforming are explored, where the online algorithms still show significant gains compared to the baseline performance.","lang":"eng"}],"status":"public","type":"conference","publication":"ICASSP 2018, Calgary, Canada","language":[{"iso":"eng"}],"_id":"12901","user_id":"44006","department":[{"_id":"54"}],"year":"2018","citation":{"chicago":"Boeddeker, Christoph, Hakan Erdogan, Takuya Yoshioka, and Reinhold Haeb-Umbach. “Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition.” In <i>ICASSP 2018, Calgary, Canada</i>, 2018.","ieee":"C. Boeddeker, H. Erdogan, T. Yoshioka, and R. Haeb-Umbach, “Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition,” in <i>ICASSP 2018, Calgary, Canada</i>, 2018.","ama":"Boeddeker C, Erdogan H, Yoshioka T, Haeb-Umbach R. Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition. In: <i>ICASSP 2018, Calgary, Canada</i>. ; 2018.","short":"C. Boeddeker, H. Erdogan, T. Yoshioka, R. Haeb-Umbach, in: ICASSP 2018, Calgary, Canada, 2018.","bibtex":"@inproceedings{Boeddeker_Erdogan_Yoshioka_Haeb-Umbach_2018, title={Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition}, booktitle={ICASSP 2018, Calgary, Canada}, author={Boeddeker, Christoph and Erdogan, Hakan and Yoshioka, Takuya and Haeb-Umbach, Reinhold}, year={2018} }","mla":"Boeddeker, Christoph, et al. “Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition.” <i>ICASSP 2018, Calgary, Canada</i>, 2018.","apa":"Boeddeker, C., Erdogan, H., Yoshioka, T., &#38; Haeb-Umbach, R. (2018). Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition. In <i>ICASSP 2018, Calgary, Canada</i>."},"related_material":{"link":[{"relation":"supplementary_material","description":"Poster","url":"https://groups.uni-paderborn.de/nt/pubs/2018/ICASSP_2018_Boeddeker_Slides.pdf"}]},"title":"Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/ICASSP_2018_Boeddeker_Paper.pdf","open_access":"1"}],"date_updated":"2022-01-06T06:51:24Z","oa":"1","author":[{"id":"40767","full_name":"Boeddeker, Christoph","last_name":"Boeddeker","first_name":"Christoph"},{"full_name":"Erdogan, Hakan","last_name":"Erdogan","first_name":"Hakan"},{"full_name":"Yoshioka, Takuya","last_name":"Yoshioka","first_name":"Takuya"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"date_created":"2019-07-30T14:53:58Z"},{"issue":"1","page":"1-1","intvolume":"        10","citation":{"ama":"Hellebrand S, Henkel J, Raghunathan A, Wunderlich H-J. Guest Editors’ Introduction - Special Issue on Approximate Computing. <i>IEEE Embedded Systems Letters</i>. 2018;10(1):1-1. doi:<a href=\"https://doi.org/10.1109/les.2018.2789942\">10.1109/les.2018.2789942</a>","chicago":"Hellebrand, Sybille, Joerg Henkel, Anand Raghunathan, and Hans-Joachim Wunderlich. “Guest Editors’ Introduction - Special Issue on Approximate Computing.” <i>IEEE Embedded Systems Letters</i> 10, no. 1 (2018): 1–1. <a href=\"https://doi.org/10.1109/les.2018.2789942\">https://doi.org/10.1109/les.2018.2789942</a>.","ieee":"S. Hellebrand, J. Henkel, A. Raghunathan, and H.-J. Wunderlich, “Guest Editors’ Introduction - Special Issue on Approximate Computing,” <i>IEEE Embedded Systems Letters</i>, vol. 10, no. 1, pp. 1–1, 2018.","mla":"Hellebrand, Sybille, et al. “Guest Editors’ Introduction - Special Issue on Approximate Computing.” <i>IEEE Embedded Systems Letters</i>, vol. 10, no. 1, IEEE, 2018, pp. 1–1, doi:<a href=\"https://doi.org/10.1109/les.2018.2789942\">10.1109/les.2018.2789942</a>.","bibtex":"@article{Hellebrand_Henkel_Raghunathan_Wunderlich_2018, title={Guest Editors’ Introduction - Special Issue on Approximate Computing}, volume={10}, DOI={<a href=\"https://doi.org/10.1109/les.2018.2789942\">10.1109/les.2018.2789942</a>}, number={1}, journal={IEEE Embedded Systems Letters}, publisher={IEEE}, author={Hellebrand, Sybille and Henkel, Joerg and Raghunathan, Anand and Wunderlich, Hans-Joachim}, year={2018}, pages={1–1} }","short":"S. Hellebrand, J. Henkel, A. Raghunathan, H.-J. Wunderlich, IEEE Embedded Systems Letters 10 (2018) 1–1.","apa":"Hellebrand, S., Henkel, J., Raghunathan, A., &#38; Wunderlich, H.-J. (2018). Guest Editors’ Introduction - Special Issue on Approximate Computing. <i>IEEE Embedded Systems Letters</i>, <i>10</i>(1), 1–1. <a href=\"https://doi.org/10.1109/les.2018.2789942\">https://doi.org/10.1109/les.2018.2789942</a>"},"year":"2018","volume":10,"author":[{"first_name":"Sybille","full_name":"Hellebrand, Sybille","id":"209","last_name":"Hellebrand","orcid":"0000-0002-3717-3939"},{"full_name":"Henkel, Joerg","last_name":"Henkel","first_name":"Joerg"},{"first_name":"Anand","full_name":"Raghunathan, Anand","last_name":"Raghunathan"},{"first_name":"Hans-Joachim","full_name":"Wunderlich, Hans-Joachim","last_name":"Wunderlich"}],"date_created":"2019-08-28T08:40:58Z","date_updated":"2022-01-06T06:51:27Z","publisher":"IEEE","doi":"10.1109/les.2018.2789942","title":"Guest Editors' Introduction - Special Issue on Approximate Computing","publication":"IEEE Embedded Systems Letters","type":"journal_article","status":"public","department":[{"_id":"48"}],"user_id":"209","_id":"12974","language":[{"iso":"eng"}]},{"language":[{"iso":"eng"}],"article_type":"original","department":[{"_id":"53"}],"user_id":"16148","_id":"15845","status":"public","publication":"International Journal of Engineering Research & Innovation","type":"journal_article","title":"Smart charging management system of plugged-in EVs based on user driving patterns in micro-grids","volume":10,"author":[{"first_name":"Ali","last_name":"Ameli","full_name":"Ameli, Ali"},{"last_name":"Krauter","orcid":"0000-0002-3594-260X","full_name":"Krauter, Stefan","id":"28836","first_name":"Stefan"},{"last_name":"Ameli","full_name":"Ameli, Mohammad Taghi","first_name":"Mohammad Taghi"},{"last_name":"Moslehpour","full_name":"Moslehpour, Saeid","first_name":"Saeid"}],"date_created":"2020-02-10T09:45:43Z","date_updated":"2022-01-06T06:52:38Z","intvolume":"        10","citation":{"ama":"Ameli A, Krauter S, Ameli MT, Moslehpour S. Smart charging management system of plugged-in EVs based on user driving patterns in micro-grids. <i>International Journal of Engineering Research &#38; Innovation</i>. 2018;10(1).","ieee":"A. Ameli, S. Krauter, M. T. Ameli, and S. Moslehpour, “Smart charging management system of plugged-in EVs based on user driving patterns in micro-grids,” <i>International Journal of Engineering Research &#38; Innovation</i>, vol. 10, no. 1, 2018.","chicago":"Ameli, Ali, Stefan Krauter, Mohammad Taghi Ameli, and Saeid Moslehpour. “Smart Charging Management System of Plugged-in EVs Based on User Driving Patterns in Micro-Grids.” <i>International Journal of Engineering Research &#38; Innovation</i> 10, no. 1 (2018).","apa":"Ameli, A., Krauter, S., Ameli, M. T., &#38; Moslehpour, S. (2018). Smart charging management system of plugged-in EVs based on user driving patterns in micro-grids. <i>International Journal of Engineering Research &#38; Innovation</i>, <i>10</i>(1).","short":"A. Ameli, S. Krauter, M.T. Ameli, S. Moslehpour, International Journal of Engineering Research &#38; Innovation 10 (2018).","bibtex":"@article{Ameli_Krauter_Ameli_Moslehpour_2018, title={Smart charging management system of plugged-in EVs based on user driving patterns in micro-grids}, volume={10}, number={1}, journal={International Journal of Engineering Research &#38; Innovation}, author={Ameli, Ali and Krauter, Stefan and Ameli, Mohammad Taghi and Moslehpour, Saeid}, year={2018} }","mla":"Ameli, Ali, et al. “Smart Charging Management System of Plugged-in EVs Based on User Driving Patterns in Micro-Grids.” <i>International Journal of Engineering Research &#38; Innovation</i>, vol. 10, no. 1, 2018."},"year":"2018","issue":"1","publication_identifier":{"issn":["2152 4157"]},"publication_status":"published"},{"title":"Tailored UV Emission by Nonlinear IR Excitation from ZnO Photonic Crystal Nanocavities","date_created":"2018-03-20T07:39:36Z","publisher":"American Chemical Society (ACS)","year":"2018","language":[{"iso":"eng"}],"ddc":["530"],"keyword":["tet_topic_phc"],"file":[{"relation":"main_file","content_type":"application/pdf","file_id":"3915","file_name":"2018-03 Hoffmann ACS Photonics - Tailored UV Emission by nonlinear IR excitation from ZnO photonic crystal nanocavities.pdf","access_level":"open_access","file_size":2935858,"creator":"fossie","date_created":"2018-08-16T07:49:44Z","date_updated":"2018-08-21T10:38:31Z"}],"publication":"ACS Photonics","doi":"10.1021/acsphotonics.7b01228","author":[{"first_name":"Sandro P.","full_name":"Hoffmann, Sandro P.","last_name":"Hoffmann"},{"first_name":"Maximilian","full_name":"Albert, Maximilian","last_name":"Albert"},{"last_name":"Weber","full_name":"Weber, Nils","first_name":"Nils"},{"last_name":"Sievers","full_name":"Sievers, Denis","first_name":"Denis"},{"first_name":"Jens","last_name":"Förstner","orcid":"0000-0001-7059-9862","id":"158","full_name":"Förstner, Jens"},{"first_name":"Thomas","last_name":"Zentgraf","orcid":"0000-0002-8662-1101","full_name":"Zentgraf, Thomas","id":"30525"},{"orcid":"https://orcid.org/0000-0002-3787-3572","last_name":"Meier","full_name":"Meier, Cedrik","id":"20798","first_name":"Cedrik"}],"volume":5,"date_updated":"2022-01-06T06:51:58Z","oa":"1","citation":{"apa":"Hoffmann, S. P., Albert, M., Weber, N., Sievers, D., Förstner, J., Zentgraf, T., &#38; Meier, C. (2018). Tailored UV Emission by Nonlinear IR Excitation from ZnO Photonic Crystal Nanocavities. <i>ACS Photonics</i>, <i>5</i>, 1933–1942. <a href=\"https://doi.org/10.1021/acsphotonics.7b01228\">https://doi.org/10.1021/acsphotonics.7b01228</a>","short":"S.P. Hoffmann, M. Albert, N. Weber, D. Sievers, J. Förstner, T. Zentgraf, C. Meier, ACS Photonics 5 (2018) 1933–1942.","bibtex":"@article{Hoffmann_Albert_Weber_Sievers_Förstner_Zentgraf_Meier_2018, title={Tailored UV Emission by Nonlinear IR Excitation from ZnO Photonic Crystal Nanocavities}, volume={5}, DOI={<a href=\"https://doi.org/10.1021/acsphotonics.7b01228\">10.1021/acsphotonics.7b01228</a>}, journal={ACS Photonics}, publisher={American Chemical Society (ACS)}, author={Hoffmann, Sandro P. and Albert, Maximilian and Weber, Nils and Sievers, Denis and Förstner, Jens and Zentgraf, Thomas and Meier, Cedrik}, year={2018}, pages={1933–1942} }","mla":"Hoffmann, Sandro P., et al. “Tailored UV Emission by Nonlinear IR Excitation from ZnO Photonic Crystal Nanocavities.” <i>ACS Photonics</i>, vol. 5, American Chemical Society (ACS), 2018, pp. 1933–42, doi:<a href=\"https://doi.org/10.1021/acsphotonics.7b01228\">10.1021/acsphotonics.7b01228</a>.","ama":"Hoffmann SP, Albert M, Weber N, et al. 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