@inproceedings{48882,
  abstract     = {{In multimodal multi-objective optimization (MMMOO), the focus is not solely on convergence in objective space, but rather also on explicitly ensuring diversity in decision space. We illustrate why commonly used diversity measures are not entirely appropriate for this task and propose a sophisticated basin-based evaluation (BBE) method. Also, BBE variants are developed, capturing the anytime behavior of algorithms. The set of BBE measures is tested by means of an algorithm configuration study. We show that these new measures also transfer properties of the well-established hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective space convergence. Moreover, we advance MMMOO research by providing insights into the multimodal performance of the considered algorithms. Specifically, algorithms exploiting local structures are shown to outperform classical evolutionary multi-objective optimizers regarding the BBE variants and respective trade-off with HV.}},
  author       = {{Heins, Jonathan and Rook, Jeroen and Schäpermeier, Lennart and Kerschke, Pascal and Bossek, Jakob and Trautmann, Heike}},
  booktitle    = {{Parallel Problem Solving from Nature (PPSN XVII)}},
  editor       = {{Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tusar, Tea}},
  isbn         = {{978-3-031-14714-2}},
  keywords     = {{Anytime behavior, Benchmarking, Continuous optimization, Multi-objective optimization, Multimodality, Performance metric}},
  pages        = {{192–206}},
  publisher    = {{Springer International Publishing}},
  title        = {{{BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems}}},
  doi          = {{10.1007/978-3-031-14714-2_14}},
  year         = {{2022}},
}

@inproceedings{48896,
  abstract     = {{Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.}},
  author       = {{Rook, Jeroen and Trautmann, Heike and Bossek, Jakob and Grimme, Christian}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  isbn         = {{978-1-4503-9268-6}},
  keywords     = {{configuration, multi-modality, multi-objective optimization}},
  pages        = {{356–359}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}}},
  doi          = {{10.1145/3520304.3528998}},
  year         = {{2022}},
}

@article{51294,
  abstract     = {{<jats:p>Der Bericht gibt Einblicke in die Tagung „Fachdidaktische Entwicklungsforschung in der Deutschdidaktik – Gegenstandsspezifische Lernprozesse in den Blick nehmen“. Diese fand am 22. und 23.03.2022 an der Bergischen Universität Wuppertal statt. Im Fokus der Tagung stand die Fragestellung, wie Design-Based Research als Forschungsmethode in der Deutschdidaktik eingesetzt werden kann. Hierzu wurden entsprechende Projekte sowohl unter methodologischer als auch unter fachdidaktischer Perspektive diskutiert.</jats:p>}},
  author       = {{Drepper, Laura and Uhl, Benjamin}},
  issn         = {{2751-6792}},
  journal      = {{Didaktik Deutsch}},
  number       = {{52/53}},
  publisher    = {{University Library J. C. Senckenberg}},
  title        = {{{Tagungsbericht: „Fachdidaktische Entwicklungsforschung in der Deutschdidaktik – Gegenstandsspezifische Lernprozesse in den Blick nehmen“ (22.03.2022 bis 23.03.2022, Bergische Universität Wuppertal)}}},
  doi          = {{10.21248/dideu.97}},
  year         = {{2022}},
}

@article{47561,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Additive manufacturing is a promising tool for tailored solutions in chemical engineering. This applies in particular to the design of lab‐scale packed bed columns. We present experimental results to characterize a lab‐scale 3D printed structured metal packing and compare it to a conventional counterpart. The results indicate that necessary adjustments for the manufacturing process of the metal material have an influence on important operating parameters, resulting in higher specific pressure drop, slightly higher liquid holdup and lower mass transfer efficiency.</jats:p>}},
  author       = {{Riese, Julia and Reitze, Arnulf and Grünewald, Marcus}},
  issn         = {{0009-286X}},
  journal      = {{Chemie Ingenieur Technik}},
  keywords     = {{Industrial and Manufacturing Engineering, General Chemical Engineering, General Chemistry}},
  number       = {{7}},
  pages        = {{993--1001}},
  publisher    = {{Wiley}},
  title        = {{{Experimental Characterization of 3D Printed Structured Metal Packing with an Enclosed Column Wall}}},
  doi          = {{10.1002/cite.202200002}},
  volume       = {{94}},
  year         = {{2022}},
}

@inproceedings{32573,
  author       = {{Maehren, Marcel and Nieting, Philipp and Hebrok, Sven Niclas and Merget, Robert and Somorovsky, Juraj and Schwenk, Jörg}},
  booktitle    = {{31st USENIX Security Symposium (USENIX Security 22)}},
  publisher    = {{USENIX Association}},
  title        = {{{TLS-Anvil: Adapting Combinatorial Testing for TLS Libraries}}},
  year         = {{2022}},
}

@article{53240,
  author       = {{Tavana, Madjid and Azadmanesh, Abdolreza and Nasr, Arash Khalili and Mina, Hassan}},
  issn         = {{1368-3500}},
  journal      = {{Current Issues in Tourism}},
  keywords     = {{Tourism, Leisure and Hospitality Management, Geography, Planning and Development}},
  number       = {{22}},
  pages        = {{3709--3734}},
  publisher    = {{Informa UK Limited}},
  title        = {{{A multicriteria-optimization model for cultural heritage renovation projects and public-private partnerships in the hospitality industry}}},
  doi          = {{10.1080/13683500.2021.2015299}},
  volume       = {{25}},
  year         = {{2022}},
}

@article{53241,
  author       = {{Khalili-Damghani, Kaveh and Tavana, Madjid and Ghasemi, Peiman}},
  issn         = {{0254-5330}},
  journal      = {{Annals of Operations Research}},
  keywords     = {{Management Science and Operations Research, General Decision Sciences}},
  number       = {{1}},
  pages        = {{103--141}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{A stochastic bi-objective simulation–optimization model for cascade disaster location-allocation-distribution problems}}},
  doi          = {{10.1007/s10479-021-04191-0}},
  volume       = {{309}},
  year         = {{2022}},
}

@article{53245,
  author       = {{Moazzeni, Sahar and Tavana, Madjid and Mostafayi Darmian, Sobhan}},
  issn         = {{0959-6526}},
  journal      = {{Journal of Cleaner Production}},
  publisher    = {{Elsevier BV}},
  title        = {{{A dynamic location-arc routing optimization model for electric waste collection vehicles}}},
  doi          = {{10.1016/j.jclepro.2022.132571}},
  volume       = {{364}},
  year         = {{2022}},
}

@article{53253,
  author       = {{Tavana, Madjid and Nazari-Shirkouhi, Salman and Mashayekhi, Amir and Mousakhani, Saeed}},
  issn         = {{2662-2556}},
  journal      = {{Operations Research Forum}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{An Integrated Data Mining Framework for Organizational Resilience Assessment and Quality Management Optimization in Trauma Centers}}},
  doi          = {{10.1007/s43069-022-00132-0}},
  volume       = {{3}},
  year         = {{2022}},
}

@article{53256,
  author       = {{Hashemi, Seyed Emadedin and Tavana, Madjid and Bakhshi, Maryam}},
  issn         = {{2661-8907}},
  journal      = {{SN Computer Science}},
  number       = {{4}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering}}},
  doi          = {{10.1007/s42979-022-01208-8}},
  volume       = {{3}},
  year         = {{2022}},
}

@article{40988,
  abstract     = {{Increasing the metal-to-ligand charge transfer (MLCT) excited state lifetime of polypyridine iron(II) complexes can be achieved by lowering the ligand's π* orbital energy and by increasing the ligand field splitting. In the homo- and heteroleptic complexes [Fe(cpmp)2]2+ (12+) and [Fe(cpmp)(ddpd)]2+ (22+) with the tridentate ligands 6,2’’-carboxypyridyl-2,2’-methylamine-pyridyl-pyridine (cpmp) and N,N’-dimethyl-N,N’-di-pyridin-2-ylpyridine-2,6-diamine (ddpd) two or one dipyridyl ketone moieties provide low energy π* acceptor orbitals. A good metal-ligand orbital overlap to increase the ligand field splitting is achieved by optimizing the octahedricity through CO and NMe units between the coordinating pyridines which enable the formation of six-membered chelate rings. The push-pull ligand cpmp provides intra-ligand and ligand-to-ligand charge transfer (ILCT, LL'CT) excited states in addition to MLCT excited states. Ground and excited state properties of 12+ and 22+ were accessed by X-ray diffraction analyses, resonance Raman spectroscopy, (spectro)electrochemistry, EPR spectroscopy, X-ray emission spectroscopy, static and time-resolved IR and UV/Vis/NIR absorption spectroscopy as well as quantum chemical calculations.}},
  author       = {{Weber, Sebastian and Zimmermann, Ronny T. and Bremer, Jens and Abel, Ken L. and Poppitz, David and Prinz, Nils and Ilsemann, Jan and Wendholt, Sven and Yang, Qingxin and Pashminehazar, Reihaneh and Monaco, Federico and Cloetens, Peter and Huang, Xiaohui and Kübel, Christian and Kondratenko, Evgenii and Bauer, Matthias and Bäumer, Marcus and Zobel, Mirijam and Gläser, Roger and Sundmacher, Kai and Sheppard, Thomas L.}},
  issn         = {{1867-3880}},
  journal      = {{ChemCatChem}},
  keywords     = {{Inorganic Chemistry, Organic Chemistry, Physical and Theoretical Chemistry, Catalysis}},
  number       = {{8}},
  publisher    = {{Wiley}},
  title        = {{{Digitization in Catalysis Research: Towards a Holistic Description of a Ni/Al2O3 Reference Catalyst for CO2 Methanation}}},
  doi          = {{10.1002/cctc.202101878}},
  volume       = {{14}},
  year         = {{2022}},
}

@inproceedings{34674,
  abstract     = {{Smart home systems contain plenty of features that enhance wellbeing in everyday life through artificial intelligence (AI). However, many users feel insecure because they do not understand the AI’s functionality and do not feel they are in control of it. Combining technical, psychological and philosophical views on AI, we rethink smart homes as interactive systems where users can partake in an intelligent agent’s learning. Parallel to the goals of explainable AI (XAI), we explored the possibility of user involvement in supervised learning of the smart home to have a first approach to improve acceptance, support subjective understanding and increase perceived control. In this work, we conducted two studies: In an online pre-study, we asked participants about their attitude towards teaching AI via a questionnaire. In the main study, we performed a Wizard of Oz laboratory experiment with human participants, where participants spent time in a prototypical smart home and taught activity recognition to the intelligent agent through supervised learning based on the user’s behaviour. We found that involvement in the AI’s learning phase enhanced the users’ feeling of control, perceived understanding and perceived usefulness of AI in general. The participants reported positive attitudes towards training a smart home AI and found the process understandable and controllable. We suggest that involving the user in the learning phase could lead to better personalisation and increased understanding and control by users of intelligent agents for smart home automation.}},
  author       = {{Sieger, Leonie Nora and Hermann, Julia and Schomäcker, Astrid and Heindorf, Stefan and Meske, Christian and Hey, Celine-Chiara and Doğangün, Ayşegül}},
  booktitle    = {{International Conference on Human-Agent Interaction}},
  keywords     = {{human-agent interaction, smart homes, supervised learning, participation}},
  location     = {{Christchurch, New Zealand}},
  publisher    = {{ACM}},
  title        = {{{User Involvement in Training Smart Home Agents}}},
  doi          = {{10.1145/3527188.3561914}},
  year         = {{2022}},
}

@inproceedings{52924,
  author       = {{Tirtarasa, Satyadharma and Turhan, Anni-Yasmin}},
  booktitle    = {{SAC ’22: The 37th {ACM/SIGAPP} Symposium on Applied Computing, Virtual Event, April 25 - 29, 2022}},
  editor       = {{Hong, Jiman and Bures, Miroslav and Park, Juw Won and Cerný, Tomás}},
  pages        = {{903–910}},
  publisher    = {{ACM}},
  title        = {{{Computing generalizations of temporal ϵL concepts with next and global}}},
  doi          = {{10.1145/3477314.3507136}},
  year         = {{2022}},
}

@inproceedings{47286,
  author       = {{Gutfleisch, Marco and Klemmer, Jan H. and Busch, Niklas and Acar, Yasemin and Sasse, M. Angela and Fahl, Sascha}},
  booktitle    = {{43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022}},
  pages        = {{893–910}},
  publisher    = {{IEEE}},
  title        = {{{How Does Usable Security (Not) End Up in Software Products? Results From a Qualitative Interview Study}}},
  doi          = {{10.1109/SP46214.2022.9833756}},
  year         = {{2022}},
}

@inproceedings{47287,
  author       = {{Stransky, Christian and Wiese, Oliver and Roth, Volker and Acar, Yasemin and Fahl, Sascha}},
  booktitle    = {{43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022}},
  pages        = {{860–875}},
  publisher    = {{IEEE}},
  title        = {{{27 Years and 81 Million Opportunities Later: Investigating the Use of Email Encryption for an Entire University}}},
  doi          = {{10.1109/SP46214.2022.9833755}},
  year         = {{2022}},
}

@inproceedings{47288,
  author       = {{Jancar, Jan and Fourné, Marcel and Braga, Daniel De Almeida and Sabt, Mohamed and Schwabe, Peter and Barthe, Gilles and Fouque, Pierre-Alain and Acar, Yasemin}},
  booktitle    = {{43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022}},
  pages        = {{632–649}},
  publisher    = {{IEEE}},
  title        = {{{"They’re not that hard to mitigate": What Cryptographic Library Developers Think About Timing Attacks}}},
  doi          = {{10.1109/SP46214.2022.9833713}},
  year         = {{2022}},
}

@inproceedings{47285,
  author       = {{Wermke, Dominik and Wöhler, Noah and Klemmer, Jan H. and Fourné, Marcel and Acar, Yasemin and Fahl, Sascha}},
  booktitle    = {{43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022}},
  pages        = {{1880–1896}},
  publisher    = {{IEEE}},
  title        = {{{Committed to Trust: A Qualitative Study on Security & Trust in Open Source Software Projects}}},
  doi          = {{10.1109/SP46214.2022.9833686}},
  year         = {{2022}},
}

@inproceedings{47284,
  author       = {{Munyendo, Collins W. and Acar, Yasemin and Aviv, Adam J.}},
  booktitle    = {{43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022}},
  pages        = {{2304–2319}},
  publisher    = {{IEEE}},
  title        = {{{"Desperate Times Call for Desperate Measures": User Concerns with Mobile Loan Apps in Kenya}}},
  doi          = {{10.1109/SP46214.2022.9833779}},
  year         = {{2022}},
}

@inproceedings{46307,
  abstract     = {{Exploratory Landscape Analysis is a powerful technique for numerically characterizing landscapes of single-objective continuous optimization problems. Landscape insights are crucial both for problem understanding as well as for assessing benchmark set diversity and composition. Despite the irrefutable usefulness of these features, they suffer from their own ailments and downsides. Hence, in this work we provide a collection of different approaches to characterize optimization landscapes. Similar to conventional landscape features, we require a small initial sample. However, instead of computing features based on that sample, we develop alternative representations of the original sample. These range from point clouds to 2D images and, therefore, are entirely feature-free. We demonstrate and validate our devised methods on the BBOB testbed and predict, with the help of Deep Learning, the high-level, expert-based landscape properties such as the degree of multimodality and the existence of funnel structures. The quality of our approaches is on par with methods relying on the traditional landscape features. Thereby, we provide an exciting new perspective on every research area which utilizes problem information such as problem understanding and algorithm design as well as automated algorithm configuration and selection.}},
  author       = {{Seiler, Moritz and Prager, Raphael Patrick and Kerschke, Pascal and Trautmann, Heike}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference}},
  isbn         = {{9781450392372}},
  pages        = {{657–665}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes}}},
  doi          = {{10.1145/3512290.3528834}},
  year         = {{2022}},
}

@inproceedings{46304,
  abstract     = {{In recent years, feature-based automated algorithm selection using exploratory landscape analysis has demonstrated its great potential in single-objective continuous black-box optimization. However, feature computation is problem-specific and can be costly in terms of computational resources. This paper investigates feature-free approaches that rely on state-of-the-art deep learning techniques operating on either images or point clouds. We show that point-cloud-based strategies, in particular, are highly competitive and also substantially reduce the size of the required solver portfolio. Moreover, we highlight the effect and importance of cost-sensitive learning in automated algorithm selection models.}},
  author       = {{Prager, Raphael Patrick and Seiler, Moritz and Trautmann, Heike and Kerschke, Pascal}},
  booktitle    = {{Parallel Problem Solving from Nature — PPSN XVII}},
  editor       = {{Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tušar, Tea}},
  isbn         = {{978-3-031-14714-2}},
  pages        = {{3–17}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods}}},
  doi          = {{10.1007/978-3-031-14714-2_1}},
  year         = {{2022}},
}