@inproceedings{NunnKummertMuelleretal.2009, author = {Nunn, Christian and Kummert, Anton and M{\"u}ller, Dennis and Meuter, Mirko and M{\"u}ller-Schneiders, Stefan}, title = {An improved adaboost learning scheme using LDA features for object recognition}, series = {Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems, St. Louis, MO, USA, October 3-7, 2009}, booktitle = {Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems, St. Louis, MO, USA, October 3-7, 2009}, publisher = {IEEE}, address = {Piscataway, N.J.}, isbn = {978-1-4244-5521-8}, doi = {10.1109/ITSC.2009.5309856}, pages = {1 -- 6}, year = {2009}, language = {en} } @inproceedings{ZhaoMeuterNunnetal.2012, author = {Zhao, Kun and Meuter, Mirko and Nunn, Christian and Muller, Dennis and Muller-Schneiders, Stefan and Pauli, Josef}, title = {A novel multi-lane detection and tracking system}, series = {2012 IEEE Intelligent Vehicles Symposium (IV)}, booktitle = {2012 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, isbn = {978-1-4673-2119-8}, doi = {10.1109/IVS.2012.6232168}, pages = {1084 -- 1089}, year = {2012}, language = {en} } @inproceedings{GaudryHuberFlueckigeretal.2022, author = {Gaudry, Arnaud and Huber, Florian and Fl{\"u}ckiger, Julien and Quir{\´o}s, L and Rutz, Adriano and Kaiser, M and Grondin, A and Marcourt, Laurence and Ferreira Queiroz, E and Wolfender, Jean-Luc and Allard, Pierre-Marie}, title = {Short Lecture "Mass spectrometry-based sample vectorization for exploration of large chemodiverse datasets and efficient identification of new antiparasitic compounds"}, series = {Planta Medica}, volume = {88}, booktitle = {Planta Medica}, number = {15}, publisher = {Thieme}, issn = {1439-0221}, doi = {10.1055/s-0042-1758983}, year = {2022}, subject = {Massenspektrometrie}, language = {en} } @book{Huber2024, author = {Huber, Florian}, title = {Hands-on Introduction to Data Science with Python}, edition = {v0.21}, publisher = {Zenodo}, doi = {10.5281/zenodo.10074474}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-49548}, pages = {365}, year = {2024}, abstract = {In today's world, data is generated at an unprecedented pace, and our ability to harness it is changing the way we live, work, and even think. Data science, the interdisciplinary field that blends statistics, computer science, and domain-specific knowledge, empowers us to extract insights from this vast ocean of data. As data science becomes increasingly essential across various industries and sectors, there is a growing need for skilled professionals who can make sense of data and transform it into actionable information. This book is designed to give you a very broad and at the same time a very practical hands-on tour through the full spectrum of data science approaches}, subject = {Data Science}, language = {en} } @techreport{FitzenJoschkoKahraman2024, author = {Fitzen, Julian and Joschko, Marcel and Kahraman, Hasan}, title = {Wer verfolgt mich? - Die Krux mit dem Tracking}, series = {Problemf{\"a}lle des E-Business - Tracking und Anonymit{\"a}t}, journal = {Problemf{\"a}lle des E-Business - Tracking und Anonymit{\"a}t}, number = {A}, editor = {Rakow, Thomas C.}, address = {D{\"u}sseldorf}, organization = {Hochschule D{\"u}sseldorf}, pages = {1 -- 20}, year = {2024}, abstract = {Diese Seminararbeit beleuchtet das Thema Online-Tracking und seine Auswirkungen auf die Privatsph{\"a}re und den Datenschutz. Es wird untersucht, wer mit welchen Zielen digitale Spuren hinterl{\"a}sst, insbesondere im E-Commerce. Die Rolle von Unternehmen im Tracking-Prozess und der Einsatz verschiedener Technologien wie Cookies und Cross-Device-Tracking werden diskutiert. Dar{\"u}ber hinaus werden Handlungsoptionen f{\"u}r Nutzer und ethische Aspekte, einschließlich der Einhaltung der DSGVO, diskutiert. Ziel der Arbeit ist es, ein Bewusstsein f{\"u}r die Komplexit{\"a}t und die ethischen Herausforderungen des Trackings zu schaffen und Wege zum Schutz der Nutzerdaten aufzuzeigen.}, language = {de} } @misc{OPUS4-4426, title = {Problemf{\"a}lle des E-Business - Tracking und Anonymit{\"a}t}, volume = {Arbeitspapier des Lehrgebiets Datenbanken und E-Business, Nr. 1/2024}, editor = {Rakow, Thomas C.}, address = {D{\"u}sseldorf}, organization = {Hochschule D{\"u}sseldorf}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-44262}, pages = {49}, year = {2024}, abstract = {Im E-Business werden die automatisierbaren Gesch{\"a}ftsprozesse von Unternehmen zusammengefasst. Im Seminar der Veranstaltung zu diesem Thema sollten die Teilnehmer zu einer vorgegebenen Fragestellung, die erfahrungsgem{\"a}ß hohe Anforderungen an die technische und organisatorische Umsetzung einer Beantwortung erfordert, eine Ausarbeitung aufgrund einer Recherche wissenschaftlicher und technischer Ver{\"o}ffentlichungen sowie eine Website im WordPress CMS nach vorgegebenem Muster erstellen. Zu zwei Fragestellungen sind in diesem Arbeitspapier die Ausarbeitungen enthalten: o Wer verfolgt mich? - Die Krux mit dem Tracking o Wie gut, dass keiner weiß - Anonymit{\"a}t im Web (inklusive Dark Net) Zur Erg{\"a}nzung der Ausarbeitung werden die Webseiten als Ausdruck angef{\"u}gt, auch wenn sie hier nicht die interaktiven M{\"o}glichkeiten zeigen.}, language = {de} } @techreport{BuegeSchoopSelinski2024, author = {B{\"u}ge, Till and Schoop, Sven and Selinski, Luca}, title = {Wie gut, dass keiner weiß - Anonymit{\"a}t im Web (inklusive Dark Net)}, series = {Problemf{\"a}lle des E-Business - Tracking und Anonymit{\"a}t}, journal = {Problemf{\"a}lle des E-Business - Tracking und Anonymit{\"a}t}, editor = {Rakow, Thomas C.}, address = {D{\"u}sseldorf}, organization = {Hochschule D{\"u}sseldorf}, pages = {1 -- 20}, year = {2024}, abstract = {In dieser Arbeit wird ein umfassender {\"U}berblick {\"u}ber die Entwicklung und die gegenw{\"a}rtige Bedeutung von Anonymit{\"a}t im Internet, einschließlich des Dark Nets, gegeben. Durch die Analyse verschiedener wissenschaftlicher Arbeiten beleuchten wir die vielschichtigen Aspekte und Auswirkungen der Anonymit{\"a}t im Web. Wir diskutieren technische Mittel zur Wahrung der Anonymit{\"a}t, wie den Tor- Browser und VPNs, und betrachten die sozialen Implikationen von Anonymit{\"a}t auf individueller, gruppenspezifischer und politischer Ebene. Besonderes Augenmerk liegt auf den positiven und negativen Folgen von Anonymit{\"a}t, insbesondere in Bezug auf Datenschutz, Meinungsfreiheit und Cyberkriminalit{\"a}t. Unsere Analyse verdeutlicht, dass Anonymit{\"a}t im Internet ein komplexes Ph{\"a}nomen ist, das je nach Nutzung positive und negative Effekte haben kann. Diese Arbeit schließt mit einem Ausblick auf zuk{\"u}nftige Forschungsrichtungen ab, unterstreicht die Notwendigkeit einer ausgewogenen Betrachtung und diskutiert die Herausforderungen bei der Bek{\"a}mpfung von Cyberkriminalit{\"a}t im Dark Web, w{\"a}hrend gleichzeitig die Privatsph{\"a}re und Sicherheit der Nutzer gesch{\"u}tzt werden.}, language = {de} } @incollection{Rakow2023, author = {Rakow, Thomas C.}, title = {Die Entwicklung von Lehrinhalten im Fach Datenbanken}, series = {Forschungsreport 2022, Hochschule D{\"u}sseldorf}, booktitle = {Forschungsreport 2022, Hochschule D{\"u}sseldorf}, editor = {Wojciechowski, Manfred}, address = {D{\"u}sseldorf}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-42822}, publisher = {Hochschule D{\"u}sseldorf}, pages = {112 -- 113}, year = {2023}, abstract = {Im Projekt EILD.nrw wurden Open Educational Resources (OER) f{\"u}r die Lehre im Fach Datenbanken entwickelt. Lehrende k{\"o}nnen die Tools und Kurse in einer Vielzahl von Lernszenarien einsetzen. Studierende der Informatik und Anwendungsf{\"a}cher lernen den kompletten Lebenszyklus von Datenbanken kennen. Zu diesem Zweck wurden Quizze, interaktive Tools, Lehrvideos und Kurse f{\"u}r Lernmanagementsysteme entwickelt und unter einer Creative Commons-Lizenz ver{\"o}ffentlicht.}, language = {de} } @article{deJongeMildauMeijeretal.2022, author = {de Jonge, Niek F. and Mildau, Kevin and Meijer, David and Louwen, Joris J. R. and Bueschl, Christoph and Huber, Florian and van der Hooft, Justin J. J.}, title = {Good practices and recommendations for using and benchmarking computational metabolomics metabolite annotation tools}, series = {Metabolomics}, volume = {18}, journal = {Metabolomics}, number = {12}, publisher = {Springer Nature}, issn = {1573-3890}, doi = {10.1007/s11306-022-01963-y}, pages = {22}, year = {2022}, abstract = {Background Untargeted metabolomics approaches based on mass spectrometry obtain comprehensive profiles of complex biological samples. However, on average only 10\% of the molecules can be annotated. This low annotation rate hampers biochemical interpretation and effective comparison of metabolomics studies. Furthermore, de novo structural characterization of mass spectral data remains a complicated and time-intensive process. Recently, the field of computational metabolomics has gained traction and novel methods have started to enable large-scale and reliable metabolite annotation. Molecular networking and machine learning-based in-silico annotation tools have been shown to greatly assist metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery. Aim of review We highlight recent advances in computational metabolite annotation workflows with a special focus on their evaluation and comparison with other tools. Whilst the progress is substantial and promising, we also argue that inconsistencies in benchmarking different tools hamper users from selecting the most appropriate and promising method for their research. We summarize benchmarking strategies of the different tools and outline several recommendations for benchmarking and comparing novel tools. Key scientific concepts of review This review focuses on recent advances in mass spectral library-based and machine learning-supported metabolite annotation workflows. We discuss large-scale library matching and analogue search, the current bloom of mass spectral similarity scores, and how molecular networking has changed the field. In addition, the potentials and challenges of machine learning-supported metabolite annotation workflows are highlighted. Overall, recent developments in computational metabolomics have started to fundamentally change metabolomics workflows, and we expect that as a community we will be able to overcome current method performance ambiguities and annotation bottlenecks.}, subject = {Metabolomik}, language = {en} } @article{deJongeLouwenChekmenevaetal.2023, author = {de Jonge, Niek F. and Louwen, Joris J. R. and Chekmeneva, Elena and Camuzeaux, Stephane and Vermeir, Femke J. and Jansen, Robert S. and Huber, Florian and van der Hooft, Justin J. J.}, title = {MS2Query: reliable and scalable MS2 mass spectra-based analogue search}, series = {Nature Communications}, volume = {14}, journal = {Nature Communications}, publisher = {Springer}, issn = {2041-1723}, doi = {10.1038/s41467-023-37446-4}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-46105}, pages = {12}, year = {2023}, abstract = {Metabolomics-driven discoveries of biological samples remain hampered by the grand challenge of metabolite annotation and identification. Only few metabolites have an annotated spectrum in spectral libraries; hence, searching only for exact library matches generally returns a few hits. An attractive alternative is searching for so-called analogues as a starting point for structural annotations; analogues are library molecules which are not exact matches but display a high chemical similarity. However, current analogue search implementations are not yet very reliable and relatively slow. Here, we present MS2Query, a machine learning-based tool that integrates mass spectral embedding-based chemical similarity predictors (Spec2Vec and MS2Deepscore) as well as detected precursor masses to rank potential analogues and exact matches. Benchmarking MS2Query on reference mass spectra and experimental case studies demonstrate improved reliability and scalability. Thereby, MS2Query offers exciting opportunities to further increase the annotation rate of metabolomics profiles of complex metabolite mixtures and to discover new biology.}, subject = {Metabolomik}, language = {en} }