Die hannIT AöR (Hannoversche Informationstechnologien – Anstalt öffentlichen Rechts) ist der IT-Dienstleister der Region Hannover und ca. 30 weiterer Landkreise und Kommunen in Niedersachsen. Das Sicherheitsrechenzentrum mit verteilten Standorten bildet die systemtechnische Grundlage für den Betrieb und die Weiterentwicklung von Verwaltungsverfahren.

Das Kompetenzcenter Mobilität und GIS betreut Verkehrsinformations- und Planungssysteme, wie die elektronische Fahrplanauskunft oder die Netzverfügbarkeitskarte. Zum Leistungsangebot der hannIT AöR gehören unter anderem

• die elektronische Fahrplanauskunft in Niedersachsen und Bremen (EFA) u.a. für GVH (Großraum Verkehr Hannover) und Braunschweig ,
• der Betrieb des DELFI-Landesserver für Niedersachsen,
• die Echtzeitanbindung der ÖPNV-Unternehmen im GVH
• das multimodale Routing (ÖPNV, Auto, Fahrrad, Fußgänger …)

Darüber hinaus ist hannIT als Dienstleister maßgeblich an Projekten wie

• Connect GmbH (Datenintegration für Niedersachsen und Bremen),
• DELFI e.V. (Deutschlandweite Fahrplanauskunft),
• EU-Spirit (Verbund europäischer Auskunftssysteme)

beteiligt.

Im Projekt D4UM stellt hannIT AöR

• die Plattform (Hard- und Software) zur Verfügung,
• koordiniert die Bereitstellung von SW-Lösungen,
• arbeitet bei den Datenschutz- und Sicherheitsregeln mit
• schafft die Grundlagen für die Integration von IV-Echtzeitdaten und historischen Ganglinen in die Fahrplanauskunft EFA (Prototype)

• The Price of Hidden Curvature: An ~Ω (d5/4 √T. Rajaraman, Nived (2026).
• MindfulAgents: Personalizing Mindfulness Meditation via an Expert-Aligned Multi-Agent System. Wu, Mengyuan Millie; Jiang, Zhihan; Fan, Yuang; Feng, Richard; Dharmavaram, Sahiti; Polowitz, Mathew; Fallon, Shawn; Islam, Bashima; Benson, Lizbeth; Tung, Irene; Creswell, J. David; Xu, Xuhai N. Oliver, D. A. Shamma, H. Candello, P. César, P. Lopes, A. Bozzon, T. Kosch, V. Q. Liao, X. Ma, V. Artizzu, F. Draxler, G. López, A. V. Reinschluessel, X. Tong, P. O. T. Dugas (eds.) (2026). 1025:1–1025:25.
• Data-Driven Quality of Experience Management of Prevailing Internet Applications. Technical Report (PhD dissertation), Wehner, Nikolas (2026, January).
• Towards Robust Version Identification in the Wild: A Dataset, Benchmark, and Fine-Tuning Study. Hachmeier, Simon; Araz, R. Oguz; Bogdanov, Dmitry; Jäschke, Robert; Serra, Xavier (2026).
• Accelerated state expansion of a nanoparticle in a dark inverted potential. Tomassi, Grégoire F. M.; Veldhuizen, Daniël; Melo, Bruno; Candoli, Davide; Riera-Campeny, Andreu; Romero-Isart, Oriol; Meyer, Nadine; Quidant, Romain (2026). 8(1) L012026.
• Multi-unit recordings in the stick insect <i>Carausius morosus</i> reveal distinct mechanosensory and olfactory activity patterns among antennal lobe neurons. Gonsek, Andrea; Groh, Claudia; Dürr, Volker; Strube-Bloss, Martin (2026). Volume 17 - 2026

  In the absence of light, the stick insect Carausius morosus relies on sensory modalities such as olfaction and mechanosensation instead of vision. Within the near-range environment, these insects use their long antennae to detect obstacles and gather tactile information, enabling them to grasp contacted objects with their front legs. However, for far-range orientation, they may integrate mechanosensory inputs with additional cues from non-contact modalities, including olfaction. Here we focus on olfactory processing in stick insects, aiming to establish the stick insect as a model to study both, near-range (tactile) and far-range (olfactory, wind, sound) sensory integration and their effects on motor control. As a first step, we established long-term multi-unit recordings of neurons in the primary olfactory neuropile, the antennal lobe (AL) to confirm general principles of odour processing in insects. Indeed, our recordings revealed that hexanal, i.e. the smell of freshly cut leaves, induced a distinct pattern of activity within the AL network, corresponding to its relevance to a herbivore and confirming the significance of the AL in extracting behaviourally relevant olfactory information. Furthermore, we discovered mechanically induced activity in AL neurons likely related to airborne vibration such as sound, highlighting that both olfactory and mechanical stimuli are processed within the AL, with a substantial fraction of neurons responsive to both modalities.
• Form informs function: innervation patterns of projection neurons correspond to response profiles of mushroom body output neurons during olfactory-visual integration. Aliyam Veetil Zyndheen, Athil Althaf; Nicolaidou, Andrea Rafaela; Groh, Claudia; Dürr, Volker; Rössler, Wolfgang; Strube-Bloss, Martin (2026). Volume 17 - 2026

  Several studies have shown that honeybees have a remarkable ability to detect, learn, and discriminate different floral qualities such as colour patterns and odour bouquets. However, how they integrate this multi-sensory information at the neuronal level is less understood. The sites for multi-sensory convergence in honeybees and other insects are the mushroom bodies (MB). In this study, we focus on MB output neurons (MBON) to examine how different MBONs process olfactory, visual, and olfactory-visual compound stimuli using extracellular multi-unit recordings. By analysing functional responses, we defined three MBON subpopulations: “bimodal”, “unimodal light”, and “unimodal odour”. All three groups exhibit compound-mediated modulation in both directions, meaning that compared to the unimodal response, the response strength to the compound can be either higher or lower. This suggests the presence of a separate compound-activated pathway, especially for unimodal MBONs. Comparing our results to the morphology of the MB input regions, the calyces, which are both divided into the lip (olfaction), collar (vision), and the basal ring (bimodal), we provide evidence that the latter region might play a key role in compound signalling. By establishing a model based on information flow through the MB circuitry, we reproduced the functional phenotypes exhibited by the different MBON types.
• Fundamental Questions and Grand Challenges in Advancing Supramolecular Polymer Science. Zhou, Zixiang; Huang, Zehuan; Bai, Haotian; Chen, Quan; Chen, Xiaodong; Flood, Amar; Figueroa, Alexandra L. Ramos; Gao, Zhao; Goto, Atsushi; Han, Han; Huang, Feihe; Jin, Zhekai; Karolly, Devika; Lai, Weiheng; Le, Hong Tho; Li, Guangfeng; Li, Hongbin; Li, Yixuan; Liu, Kai; Liu, Ming; Ou, Yu; Qiu, Yunyan; Rumon, Md. Mahamudul Hasan; Scherman, Oren A.; Sun, Junqi; Tian, Wei; Wang, Chao; Wang, Ruibing; Wang, Shu; Wei, Yuanyuan; Würthner, Frank; Xu, Jiang-Fei; Yan, Xuehai; Yi, Junqi; Yin, Hang; Yuan, Chengqian; Zhang, Xi (2026). 8(8) 3704–3778.
• An agent-based model of Trypanosoma brucei social motility to explore determinants of colony pattern formation. Kuhn, Andreas; Krüger, Timothy; Engstler, Markus; Fischer, Sabine C. (2026). 22(8) 1–33.

  In vitro colonies of the unicellular parasite Trypanosoma brucei expand radially and establish fingering instabilities, a collective behavior known as social motility. The underlying mechanisms are thought to involve single-cell motility, chemical communication among cells, and mechanical interactions with the liquid boundary, but their relative contributions remain unclear. We aimed to determine which of the mechanisms are necessary to quantitatively reproduce the morphological characteristics of social motility. We developed a two-dimensional agent-based model that simulates colonies of 105−106 cells at single-cell resolution—two to four orders of magnitude larger than previous models. Cells are represented as point particles executing directional random walks with auto-chemotactic alignment and exponential colony growth. The colony boundary is modelled using a grid-based approach in which interactions with agents can locally weaken and expand it. The model was quantitatively evaluated by applying our previously established morphology metrics. We show quantitative agreement of the simulation results and experimental data in terms of colony morphology. Parameter exploration revealed that finger formation arises within a narrow range of trypanosome motility parameters that balance stochasticity and alignment, while boundary conditions modulate the speed of colony expansion. The diffusion coefficient of the chemotactic signal is the key determinant of pattern formation. Realistic behavior occurs at 2×10−11 – 10-10 m2/s which corresponds to molecules of 12.1–1690 kDa. These results demonstrate that complex colony morphologies can emerge from minimal cell-level rules, suggesting testable hypotheses for the molecular drivers of trypanosome social motility. Furthermore, our approach provides a framework for dissecting the interplay between motility, signaling, and mechanical confinement in other microbial systems exhibiting collective behavior.
• Reiches Energiepolitik: Schlecht fürs Klima – und für die Wirtschaft. Hickel, Rudolf (2026). 13–16.

  Das »Heizungsgesetz« von 2024 stand für das klimapolitische Scheitern der Ampelkoalition. Die Kampagne der »Bild« gegen den »Heizungshammer« und die Querschüsse der FDP gegen das Gesetz stießen die Regierung unter Olaf Scholz Richtung Abgrund.
• Efficacy and safety of oral treatments for allergic rhinitis in children: A network meta-analysis. Thomander, Tuuli; Gil-Mata, Sara; Riera-Serra, Pau; Vieira, Rafael José; Ferreira, André; Bognanni, Antonio; Duarte, Vítor Henrique; Viegas, Hugo; Pereira, Ana Margarida; Ferreira-da Silva, Renato; Ferreira-Cardoso, Henrique; Marques-Cruz, Manuel; Castro-Teles, João; Campos-Lopes, Miguel; Ferreira, Ana Teixeira; Lourenço-Silva, Nuno; Boechat, José Laerte; Borowiack, Ewa; Sadowska, Ewelina; Costa, Raquel Albuquerque; Perestrelo, Paula; Pereira-Macedo, Juliana; Ierodiakonou, Despo; Chu, Alexandro W L; Calvi, Izabela Pera; Torres, Maria Inês; Ribeiro, Rita Silva; Chérrez-Ojeda, Ivan; Nuñez, Juan Jose Yepes; Zuberbier, Torsten; Fernandes, Ricardo M; Fiocchi, Alessandro; Larenas-Linnemann, Désirée E; Pham-Thi, Nhân; Papadopoulos, Nikolaos G; Roberts, Graham; Valiulis, Arunas; Fonseca, João A; Schünemann, Holger J; Giovannini, Mattia; Sousa-Pinto, Bernardo; guideline panel, ARIA 2024–2025 (2026). 37(8) e70431-e70431.

  BACKGROUND: Allergic rhinitis is the most common chronic disease in children. Information on efficacy and safety of oral allergic rhinitis treatments in children is scarce. We aimed to comprehensively evaluate the efficacy and safety of oral medications for allergic rhinitis in children. METHODS: We performed a systematic review, searching three bibliographic databases and clinicaltrials.gov for randomized controlled trials assessing the use of oral antihistamines (OAH) or leukotriene receptor antagonists (LTRA) in children (<12 years old) with seasonal or perennial allergic rhinitis. Evaluated outcomes included the Total Nasal Symptom Score (TNSS), the Total Ocular Symptom Score (TOSS), the Rhinoconjunctivitis Quality-of-Life Questionnaire (RQLQ), development of adverse or serious adverse events, and withdrawals due to adverse events. We performed network meta-analysis at both class and individual treatment levels. Certainty in the body of evidence was assessed using the GRADE approach for network meta-analysis. RESULTS: We included eight primary studies with 906 participants. Overall, OAH were more effective against placebo in improving the TNSS (mean difference (MD) = -1.60; 95%CI = -2.25 to -0.95). On the other hand, OAH+LTRA did not demonstrate additional benefit over OAH in improving the TNSS (MD = -0.15; 95% CI = -1.18 to 0.88), and there were no important differences between individual OAH. Evidence on the TOSS was not found. No significant differences in the frequency of adverse events were observed. Certainty of evidence was low or very low for most comparisons. CONCLUSIONS: Oral treatments for allergic rhinitis appear to be effective and safe in children. However, evidence is scarce and the quality of evidence is mostly low. We performed a systematic review of randomised controlled trials assessing oral medications for allergic rhinitis in children and reporting results on nasal symptoms, ocular symptoms, quality of life and adverse events. Oral antihistamines (OAH) were found to be better than placebo, and OAH + oral leukotriene receptor antagonists (OLTRA) were not found to be better than OAH. We identified trivial differences between different OAH.
• Semi‐Natural Habitats Buffer the Effects of Crop Diversification on Arthropod Pest Control Services in Agricultural Landscapes. Perrot, Thomas; Beaumelle, Léa; Thomine, Eva; Tricault, Yann; Desneux, Nicolas; Albrecht, Matthias; Batáry, Péter; Bianchi, Felix; Birkhofer, Klaus; Bosem Baillod, Aliette; Chaplin‐Kramer, Rebecca; Cortesero, Anne‐Marie; Costamagna, Alejandro C.; Diekötter, Tim; Ekroos, Johan; Entling, Martin H.; Gagic, Vesna; Groves, Russell; Huseth, Anders; Jaworski, Coline; Kaiser, Marina; Karp, Daniel S.; Krauss, Jochen; Lavandero, Blas; Le Ralec, Anne; Lu, Yanhui; Martin, Emily A.; Mitchell, Matthew; Molina, Gonzalo A. R.; Palmu, Erkki; Perovic, David J.; Ragsdale, David; Redlich, Sarah; Samaranayake, Ishan; Saulais, Julia; Schellhorn, Nancy A.; Steffan‐Dewenter, Ingolf; Sutter, Louis; Tscharntke, Teja; Tschumi, Matthias; Rusch, Adrien (2026). 29(8) e70440.
• Addressing Class Imbalance in Diabetic Retinopathy Detection: An Enhanced Diffusion-Resampling Data Augmentation Approach. Yangue, Emmanuel; O’Connor, Ethan; Liu, Chenang (2025). 1323–1329.
• Jenseits der Logik der Empfehlung. Formale Begriffsanalyse als Grundlage für eine neue Variante zur Vermittlung von Nutzenden und journalistischen Inhalten. Uhlmann, Markus; Hirth, Johannes; Horn, Viktoria (2025). 137–155.
• LASMP: Language Aided Subset Sampling Based Motion Planner. Bhattacharjee, Saswati; Sinha, Anirban; Ghosh, Mukulika; Ekenna, Chinwe (2025). 1632–1639.
• Intelligent Retrieval and Knowledge Question-Answering System for Semi-Structured Operational Manuals. Cheng, You-Wei; Hsu, Chia-Yu; Lan, Yu-Ying (2025). 1675–1679.
• A Model-Agnostic Approach for Semantic Table Augmentation in Digital Twin Government Using LLMs and Domain-Specific Ontologies. Lee, Yewon; Son, Wonseok; Kim, Jeongsu; Chun, Sejin (2025). 1695–1700.
• Conceptual Topic Aggregation. Gutekunst, Klara M.; Dürrschnabel, Dominik; Hirth, Johannes; Stumme, Gerd P. Cellier, B. Ganter, R. Missaoui (eds.) (2025). 3–18.

  The vast growth of data has rendered traditional manual inspection infeasible, necessitating the adoption of computational methods for efficient data exploration. Topic modeling has emerged as a powerful tool for analyzing large-scale textual datasets, enabling the extraction of latent semantic structures. However, existing methods for topic modeling often struggle to provide interpretable representations that facilitate deeper insights into data structure and content.
• Effective Quantization Technique for Enhancing Model Performance on Resource-Constrained Devices. Andalib, Nelum; Selimi, Mennan (2025). 1–4.
• The Geometric Structure of Topic Models. Hirth, Johannes; Hanika, Tom in Lecture Notes in Computer Science, P. Cellier, B. Ganter, R. Missaoui (eds.) (2025). (Vol. 15941) 19–34.
• LDP-QWSP: A General Local Differential Privacy Framework for QoS-Based Web Service Prediction. Luo, Fuchang; Wu, Haonan; Peng, Shunshun; Wu, Quanwang; Wang, Hongbing; Yang, Mengmeng; Guo, Taolin in Lecture Notes in Computer Science, M. Aiello, S. Deng, J. M. Murillo, I. Georgievski, B. Benatallah, Z. Wang (eds.) (2025). (Vol. 16321) 207–215.
• Das Auskunftsrecht nach Art. 15 DSGVO. Stoklas, Jonathan; Huppmann, Oscar (2025). (3)
• EuGH: Personenbezug – absoluter oder relativer Ansatz bei pseudonymisierten Daten?. Stoklas, Jonathan (2025). 20 01442.
• Der Personenbezug von KI-Modellen nach dem EDSA. Stoklas, Jonathan (2025). 12 01313.
• Online-Werbung – Ein Datenschutzfiasko? Der Fall WetterOnline. Stoklas, Jonathan (2025). 01197.
• Cyber Resilience Act der EU in Kraft getreten. Stoklas, Jonathan (2025). 1 01103.
• Brochure Segmentation Methodology. Ismailov, Aykut; Hristov, Vladimir (2025). 1–5.
• Paired-EMS: Enhancing Electrical Muscle Stimulation (EMS)-based Force Feedback Experience by Stimulating Both Muscles in Antagonistic Pairs. Cheng, Chia-Yu; Chen, Yu; Handani, Sitaresmi Wahyu; Balabantaray, Avijit; Chen, Mike Y. F. ’Floyd’ Mueller, P. Kyburz, J. R. Williamson, C. Sas, M. L. Wilson, P. O. T. Dugas, I. Shklovski (eds.) (2024). 426:1–426:7.
• Conveying Emotions through Shape-changing to Children with and without Visual Impairment. Neto, Isabel; Hu, Yuhan; Correia, Filipa; Rocha, Filipa; Hoffman, Guy; Nicolau, Hugo; Paiva, Ana F. ’Floyd’ Mueller, P. Kyburz, J. R. Williamson, C. Sas, M. L. Wilson, P. O. T. Dugas, I. Shklovski (eds.) (2024). 49:1–49:16.
• How Low is Low? Crowdworker Perceptions of Microtask Payments in Work versus Leisure Situations. Jiang, Ling; Wagner, Christian F. ’Floyd’ Mueller, P. Kyburz, J. R. Williamson, C. Sas, M. L. Wilson, P. O. T. Dugas, I. Shklovski (eds.) (2024). 642:1–642:11.
• RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection. Cheng, Yuqi; Cao, Yunkang; Chen, Rui; Shen, Weiming (2024). 2123–2128.
• Open-Source CFD Simulation of Magnetic Rotating Swimmers with Experimental Validation. Lu, Yitong; Ramos, Jocelyn; Sarda, Deeksha; Shah, Dipan J.; Becker, Aaron T.; Leclerc, Julien (2024). 3779–3784.
• Tackling Environmental Variability: Few Shot Segmentation for Domain-Adaptive Weed Segmentation in Agricultural Robotics. Catalano, Nico; Leone, Monica; Matteucci, Matteo (2024). 583–588.
• Synthesizing Distribution Grid Congestion Data Using Multivariate Conditional Time Series Generative Adversarial Networks. Demirel, Gökhan; Hauf, Jan; Butt, Hallah Shahid; Förderer, Kevin; SchtiferiD, Benjamin; Hagenmeyer, Veit (2024). 385–390.
• Multiband Dynamics Compressor with Automatic Parameter Learning. Ionita, Horia Sebastian; Popa, Victor; Morosanu, Bogdan (2024). 1–4.
• BlipFill: Completing Authentic Images with BLIP-enhanced Subject Representation. Wang, Heqing; Cao, Tianwei; Jin, Ling; Liu, Weidong; Wang, Rui; Ma, Zhanyu X. Chen, J. Fang (eds.) (2024). 112–118.
• EuGH: Online-Apotheken, Gesundheitsdaten – Wie weitgehend ist der Anwendungsbereich von Art. EWG_DSGVO Artikel 9 DS-GVO?. Stoklas, Jonathan (2024). 21 01874.
• Dimensionality Reduction for Machine Learning-based Argument Mining. Segura-Tinoco, Andrés; Cantador, Iván M. Alshomary, C.-C. Chen, S. Muresan, J. Park, J. Romberg (eds.) (2023). 89–99.
• Overview of PragTag-2023: Low-Resource Multi-Domain Pragmatic Tagging of Peer Reviews. Dycke, Nils; Kuznetsov, Ilia; Gurevych, Iryna M. Alshomary, C.-C. Chen, S. Muresan, J. Park, J. Romberg (eds.) (2023). 187–196.
• Spin Transport Across a Nonmagnet Ferrimagnet Interface. Choge, Hillary Kirwa; Barasa, Godfrey; Agumba, John Onyango (2023). 1–6.
• Coding Together: On Co-located and Remote Collaboration between Children with Mixed-Visual Abilities. Rocha, Filipa; Correia, Filipa; Neto, Isabel; Pires, Ana Cristina; Guerreiro, João; Guerreiro, Tiago João; Nicolau, Hugo A. Schmidt, K. Väänänen, T. Goyal, P. O. Kristensson, A. Peters, S. Mueller, J. R. Williamson, M. L. Wilson (eds.) (2023). 606:1–606:14.
• Adaptive Empathy Learning Support in Peer Review Scenarios. Wambsganss, Thiemo; Söllner, Matthias; Koedinger, Kenneth R.; Leimeister, Jan Marco S. D. J. Barbosa, C. Lampe, C. Appert, D. A. Shamma, S. M. Drucker, J. R. Williamson, K. Yatani (eds.) (2022). 227:1–227:17.
• Simultaneous Parameter Estimation and Tracking Control without Persistence of Excitation with Application in Ink-Jet Deposition. Jafari, Bashir Hosseini; Davoodi, Mohammadreza; Gans, Nicholas R. (2022). 735–742.
• CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities. Lee, Mina; Liang, Percy; Yang, Qian S. D. J. Barbosa, C. Lampe, C. Appert, D. A. Shamma, S. M. Drucker, J. R. Williamson, K. Yatani (eds.) (2022). 388:1–388:19.
• Learning from Healthcare Providers’ Strategies: Designing Technology to Support Effective Child Patient-Provider Communication. Seo, Woosuk; Buyuktur, Ayse G.; Verma, Sanya; Kim, Hyeryoung; Choi, Sung Won; Sedig, Laura; Park, Sun Young Y. Kitamura, A. Quigley, K. Isbister, T. Igarashi, P. Bjørn, S. M. Drucker (eds.) (2021). 660:1–660:15.
• Armstrong: An Empirical Examination of Pointing at Non-Dominant Arm-Anchored UIs in Virtual Reality. Li, Zhen; Chan, Joannes; Walton, Joshua; Benko, Hrvoje; Wigdor, Daniel; Glueck, Michael Y. Kitamura, A. Quigley, K. Isbister, T. Igarashi, P. Bjørn, S. M. Drucker (eds.) (2021). 123:1–123:14.
• The Impact of Oil Price Fluctuations on Investment in the Shale Oil Sector. Zaid, Zuhaira; Li, Jizu; Zuhaira, Hind Ghanim (2021). 112–116.
• Multi-scale Hybrid Transformer Networks: Application to Prostate Disease Classification. Santhirasekaram, Ainkaran; Pinto, Karen; Winkler, Mathias; Aboagye, Eric O.; Glocker, Ben; Rockall, Andrea G. in Lecture Notes in Computer Science, T. F. Syeda-Mahmood, X. Li, A. Madabhushi, H. Greenspan, Q. Li, R. M. Leahy, B. Dong, H. Wang (eds.) (2021). (Vol. 13050) 12–21.
• Forecasting Electricity Consumption Data from Paraguay Using a Machine Learning Approach. Gallardo, José A.; García-Torres, Miguel; Gómez-Vela, Francisco; Morales, Félix; Divina, Federico; Becerra-Alonso, David; Velázquez, Gustavo; Daumas-Ladouce, Federico; Noguera, José Luis Vázquez; Ayala, Carlos Sauer; Pinto-Roa, Diego P.; Gardel-Sotomayor, Pedro E.; Román, Julio César Mello in Advances in Intelligent Systems and Computing, H. Sanjurjo-González, I. Pastor-López, P. G. Bringas, H. Quintián, E. Corchado (eds.) (2021). (Vol. 1401) 685–694.
• PrivacyMic: Utilizing Inaudible Frequencies for Privacy Preserving Daily Activity Recognition. Iravantchi, Yasha; Ahuja, Karan; Goel, Mayank; Harrison, Chris; Sample, Alanson P. Y. Kitamura, A. Quigley, K. Isbister, T. Igarashi, P. Bjørn, S. M. Drucker (eds.) (2021). 198:1–198:13.
• ArgueTutor: An Adaptive Dialog-Based Learning System for Argumentation Skills. Wambsganss, Thiemo; Kueng, Tobias; Söllner, Matthias; Leimeister, Jan Marco Y. Kitamura, A. Quigley, K. Isbister, T. Igarashi, P. Bjørn, S. M. Drucker (eds.) (2021). 683:1–683:13.
• AL: An Adaptive Learning Support System for Argumentation Skills. Wambsganss, Thiemo; Niklaus, Christina; Cetto, Matthias; Söllner, Matthias; Handschuh, Siegfried; Leimeister, Jan Marco R. Bernhaupt, F. ’Floyd’ Mueller, D. Verweij, J. Andres, J. McGrenere, A. Cockburn, I. Avellino, A. Goguey, P. Bjøn, S. Zhao, B. P. Samson, R. Kocielnik (eds.) (2020). 1–14.
• Sara, the Lecturer: Improving Learning in Online Education with a Scaffolding-Based Conversational Agent. Winkler, Rainer; Hobert, Sebastian; Salovaara, Antti; Söllner, Matthias; Leimeister, Jan Marco R. Bernhaupt, F. ’Floyd’ Mueller, D. Verweij, J. Andres, J. McGrenere, A. Cockburn, I. Avellino, A. Goguey, P. Bjøn, S. Zhao, B. P. Samson, R. Kocielnik (eds.) (2020). 1–14.
• Learning from Positive Adaptations of Pediatric Cancer Patients to Design Health Technologies. Park, Sun Young; Seo, Woosuk; Berry, Andrew B. L.; Kim, Hyeryoung; Verma, Sanya; Choi, Sung Won; Buyuktur, Ayse G. R. Bernhaupt, F. ’Floyd’ Mueller, D. Verweij, J. Andres, J. McGrenere, A. Cockburn, I. Avellino, A. Goguey, P. Bjøn, S. Zhao, B. P. Samson, R. Kocielnik (eds.) (2020). 1–12.
• Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design. Yang, Qian; Steinfeld, Aaron; Rosé, Carolyn P.; Zimmerman, John R. Bernhaupt, F. ’Floyd’ Mueller, D. Verweij, J. Andres, J. McGrenere, A. Cockburn, I. Avellino, A. Goguey, P. Bjøn, S. Zhao, B. P. Samson, R. Kocielnik (eds.) (2020). 1–13.
• Join.Love: A Sociotechnical Genealogy of the Legalization of Same-Sex Marriage. Bardzell, Jeffrey; Freeman, Guo; Bardzell, Shaowen; Chen, Pei-Ying R. Bernhaupt, F. ’Floyd’ Mueller, D. Verweij, J. Andres, J. McGrenere, A. Cockburn, I. Avellino, A. Goguey, P. Bjøn, S. Zhao, B. P. Samson, R. Kocielnik (eds.) (2020). 1–13.
• Simulation of WiMAX and Logical Segmentation of its Application. Musa, Abdulwaheed; Paul, Babu Sena (2019). 1–5.
• Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes. Yang, Qian; Steinfeld, Aaron; Zimmerman, John S. A. Brewster, G. Fitzpatrick, A. L. Cox, V. Kostakos (eds.) (2019). 238.
• Analysis of Solar and Fossil Fuel Powered Base Transceiver Stations. Musa, Abdulwaheed; Paul, Babu Sena (2019). 1–5.
• Multi-Objective Optimization of Run-of-River Small Hydro-PV Hybrid Power Systems. Hounnou, Amèdédjihundé H. J.; Dubas, Frédéric; Fifatin, François-Xavier; Aza-Gnandji, Maurel; Chamagne, Didier; Vianou, Antoine (2019). 1–7.
• Understanding and Designing for Deaf or Hard of Hearing Drivers on Uber. Lee, Sooyeon; Hubert-Wallander, Bjorn; Stevens, Molly; Carroll, John M. S. A. Brewster, G. Fitzpatrick, A. L. Cox, V. Kostakos (eds.) (2019). 529.
• CYCLOHEXANE – PHENOL BINARY LIQUID MIXTURE: BEHAVIOR AND PARAMETERS AT CRITICAL CONDITIONS Saadeddin, Iyad (2019). (Vol. 8)
• Designing Theory-Driven User-Centric Explainable AI. Wang, Danding; Yang, Qian; Abdul, Ashraf M.; Lim, Brian Y. S. A. Brewster, G. Fitzpatrick, A. L. Cox, V. Kostakos (eds.) (2019). 601.
• Supporting Coping with Parkinson’s Disease Through Self Tracking. Mishra, Sonali R.; Klasnja, Predrag V.; Woodburn, John MacDuffie; Hekler, Eric B.; Omberg, Larsson; Kellen, Michael; Mangravite, Lara M. S. A. Brewster, G. Fitzpatrick, A. L. Cox, V. Kostakos (eds.) (2019). 107.
• Beyond the Patient Portal: Supporting Needs of Hospitalized Patients. Haldar, Shefali; Mishra, Sonali R.; Khelifi, Maher; Pollack, Ari H.; Pratt, Wanda S. A. Brewster, G. Fitzpatrick, A. L. Cox, V. Kostakos (eds.) (2019). 366.
• Rich Representations of Visual Content for Screen Reader Users. Morris, Meredith Ringel; Johnson, Jazette; Bennett, Cynthia L.; Cutrell, Edward R. L. Mandryk, M. Hancock, M. Perry, A. L. Cox (eds.) (2018). 59.
• Supporting Collaborative Health Tracking in the Hospital: Patients’ Perspectives. Mishra, Sonali R.; Miller, Andrew D.; Haldar, Shefali; Khelifi, Maher; Eschler, Jordan; Elera, Rashmi G.; Pollack, Ari H.; Pratt, Wanda R. L. Mandryk, M. Hancock, M. Perry, A. L. Cox (eds.) (2018). 650.
• Mobile Multimedia-Based Tourism Promotion Development. Sutopo, Hadi; Abadi, Ferryal (2018). 451–454.
• Cross-Lingual Argumentative Relation Identification: from English to Portuguese. Rocha, Gil; Stab, Christian; Cardoso, Henrique Lopes; Gurevych, Iryna N. Slonim, R. Aharonov (eds.) (2018). 144–154.
• Formal approach for a verified implementation of Global EDF in Trampoline. Boukir, Khaoula; Béchennec, Jean-Luc; Déplanche, Anne-Marie Y. Ouhammou, F. Ridouard, E. Grolleau, M. Jan, M. Behnam (eds.) (2018). 83–92.
• Frame- and Entity-Based Knowledge for Common-Sense Argumentative Reasoning. Botschen, Teresa; Sorokin, Daniil; Gurevych, Iryna N. Slonim, R. Aharonov (eds.) (2018). 90–96.
• PD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation Projection. Eger, Steffen; Rücklé, Andreas; Gurevych, Iryna N. Slonim, R. Aharonov (eds.) (2018). 131–143.
• Description Means for Information Artifacts Throughout the Life Cycle of CPPS. Lüder, Arndt; Schmidt, Nicole; Hell, Kristofer; Röpke, Hannes; Zawisza, Jacek (2017). 169–183.
• Identification of Artifacts in Life Cycle Phases of CPPS. Lüder, Arndt; Schmidt, Nicole; Hell, Kristofer; Röpke, Hannes; Zawisza, Jacek (2017). 139–167.
• Fundamentals of Artifact Reuse in CPPS. Lüder, Arndt; Schmidt, Nicole; Hell, Kristofer; Röpke, Hannes; Zawisza, Jacek (2017). 113–138.
• When Personal Tracking Becomes Social: Examining the Use of Instagram for Healthy Eating. Chung, Chia-Fang; Agapie, Elena; Schroeder, Jessica; Mishra, Sonali R.; Fogarty, James; Munson, Sean A. G. Mark, S. R. Fussell, C. Lampe, m. c. schraefel, J. P. Hourcade, C. Appert, D. Wigdor (eds.) (2017). 1674–1687.
• Supporting Easy Physical-to-Virtual Creation of Mobile VR Maze Games: A New Genre. Gai, Wei; Yang, Chenglei; Bian, Yulong; Shen, Chia; Meng, Xiangxu; Wang, Lu; Liu, Juan; Dong, Mingda; Niu, Chengjie; Lin, Cheng G. Mark, S. R. Fussell, C. Lampe, m. c. schraefel, J. P. Hourcade, C. Appert, D. Wigdor (eds.) (2017). 5016–5028.
• Opportunities and Design Considerations for Peer Support in a Hospital Setting. Haldar, Shefali; Mishra, Sonali R.; Khelifi, Maher; Pollack, Ari H.; Pratt, Wanda G. Mark, S. R. Fussell, C. Lampe, m. c. schraefel, J. P. Hourcade, C. Appert, D. Wigdor (eds.) (2017). 867–879.
• Toward Usable Evidence: Optimizing Knowledge Accumulation in HCI Research on Health Behavior Change. Klasnja, Predrag V.; Hekler, Eric B.; Korinek, Elizabeth V.; Harlow, John; Mishra, Sonali R. G. Mark, S. R. Fussell, C. Lampe, m. c. schraefel, J. P. Hourcade, C. Appert, D. Wigdor (eds.) (2017). 3071–3082.
• KitPaDy: Robot co-worker in kitting process: Basic concept and computation of working time. Wakabayashi, Yuta; Kamioka, Masaya; Kinugawa, Jun; Kosuge, Kazuhiro (2017). 320–327.
• Prediction of electromagnetic wave attenuation in dust storms using Mie scattering. Musa, Abdulwaheed; Paul, Babu Sena (2017). 603–608.
• Model-based active viewpoint transfer for purposive perception. Zhang, Liang-Jun; Gu, Chaochen; Wu, Kaijie; Huang, Ye; Guan, Xin-Ping (2017). 1085–1089.
• Closing the Gap: Supporting Patients’ Transition to Self-Management after Hospitalization. Pollack, Ari H.; Backonja, Uba; Miller, Andrew D.; Mishra, Sonali R.; Khelifi, Maher; Kendall, Logan; Pratt, Wanda J. Kaye, A. Druin, C. Lampe, D. Morris, J. P. Hourcade (eds.) (2016). 5324–5336.
• "Not Just a Receiver": Understanding Patient Behavior in the Hospital Environment. Mishra, Sonali R.; Haldar, Shefali; Pollack, Ari H.; Kendall, Logan; Miller, Andrew D.; Khelifi, Maher; Pratt, Wanda J. Kaye, A. Druin, C. Lampe, D. Morris, J. P. Hourcade (eds.) (2016). 3103–3114.
• Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help. Yang, Qian; Zimmerman, John; Steinfeld, Aaron; Carey, Lisa; Antaki, James F. J. Kaye, A. Druin, C. Lampe, D. Morris, J. P. Hourcade (eds.) (2016). 4477–4488.
• Benefits of Enterprise Architecture Management - Insights from European Experts. Schmidt, Rainer; Möhring, Michael; Härting, Ralf-Christian; Reichstein, Christopher; Zimmermann, Alfred; Luceri, Sandro in Lecture Notes in Business Information Processing, J. Ralyté, S. España, O. Pastor (eds.) (2015). (Vol. 235) 223–236.
• Automatic tuning of impedance parameter using configuration space for two dimensional assembly system. Saksena, Abhilasha; Nammoto, Takashi; Kinugawa, Jun; Kosuge, Kazuhiro (2015). 1110–1117.
• EMTP-based analysis of pre-insertion resistor and point on wave switching methodology. Zondi, Simphiwe; Bokoro, Pitshou N.; Paul, Babu Sena (2015). 1–5.
• Graph Grammar Specification for the Populational Level of Multi-agent System Organizations. de Mello, Andre Moura; Foss, Luciana; da Costa Cavalheiro, Simone André (2013). 97–104.
• Model-based compliant motion control scheme for assembly tasks using vision and force information. Nammoto, Takashi; Kosuge, Kazuhiro; Hashimoto, Koichi (2013). 948–953.
• Experimental evaluation of NFC reliability between an RFID tag and a smartphone. Mareli, Mahlaku; Rimer, Suvendi; Paul, Babu Sean; Ouahada, Khmaies; Pitsillides, A. (2013). 1–5.
• PERFORMANCE ANALYSIS OF FINGERPRINTING EXTRACTION ALGORITHM IN VIDEO COPY DETECTION SYSTEM. Rubini, R.Gnana; Selvy, P.Tamije; Prabha, P.Anantha (2012). 2(1) 45–55.

  A video fingerprint is a recognizer that is derived from a piece of video content. The video fingerprinting methods obtain unique features of a video that differentiates one video clip from another. It aims to identify whether a query video segment is a copy of video from the video database or not based on the signature of the video. It is difficult to find whether a video is a copied video or a similar video, since the features of the content are very similar from one video to the other. The main focus of this paper is to detect that the query video is present in the video database with robustness depending on the content of video and also by fast search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithms are adopted in this paper to achieve robust, fast, efficient and accurate video copy detection. As a first step, the Fingerprint Extraction algorithm is employed which extracts a fingerprint through the features from the image content of video. The images are represented as Temporally Informative Representative Images (TIRI). Then, the second step is to find the presence of copy of a query video in a video database, in which a close match of its fingerprint in the corresponding fingerprint database is searched using inverted-filebased method. The proposed system is tested against various attacks like noise, brightness, contrast, rotation and frame drop. Thus the performance of the proposed system on an average shows high true positive rate of 98% and low false positive rate of 1.3% for different attacks.
• Direct and indirect feed-in for inductive power transfer systems with multiple loads. Gleissner, Michael; Söllner, Matthias; Schmidt, Hans-Peter (2011). 1–5.
• Dynamic Arrangement of Control in a Personalized Learning System Based on User Competency. Lee, Youngseok; Cho, Jungwon; Han, Sungjae; Choi, Byung-Uk in Communications in Computer and Information Science, T.-H. Kim, H. Adeli, H. S. Cho, O. Gervasi, S. S. Yau, B. H. Kang, L. J. G. Villalba (eds.) (2011). (Vol. 261) 468–474.
• Graph Grammars: A Comparison between Verification Methods. de Mello, Andre Moura; Junior, Luiz Carlos Lemos; Foss, Luciana; da Costa Cavalheiro, Simone André (2011). 88–94.
• User experience at google: focus on the user and all else will follow. Au, Irene; Boardman, Richard; Jeffries, Robin; Larvie, Patrick; Pavese, Antonella; Riegelsberger, Jens; Rodden, Kerry; Stevens, Molly M. M. Czerwinski, A. M. Lund, D. S. Tan (eds.) (2008). 3681–3686.
• Implicit user-adaptive system engagement in speech and pen interfaces. Oviatt, Sharon L.; Swindells, Colin; Arthur, Alexander M. M. Czerwinski, A. M. Lund, D. S. Tan (eds.) (2008). 969–978.
• Exploring affective design for physical controls. Swindells, Colin; MacLean, Karon E.; Booth, Kellogg S.; Meitner, Michael J. M. B. Rosson, D. J. Gilmore (eds.) (2007). 933–942.
• Automatic Generation of Component-level Dynamic Equations Using Extensible Element Linear Graph Method. Li, Yingzhe; Lin, Zhongqin; Wang, Hao; Chen, Yong (2006). 118–123.
• Developing Interoperable Business Processes Using Web Services and Policies. Maamar, Zakaria; Benslimane, Djamal; Mostéfaoui, Ghita Kouadri; Subramanian, Sattanathan; Ghedira, Chirine G. Doumeingts, J. P. Müller, G. Morel, B. Vallespir (eds.) (2006). 475–487.