Data4UrbanMobility hat an der Organisation des 5. PROFILES Workshop über Dataset Profiling und Search mitgewirkt. Dieser fand am 27. Oktober 2019 während der 18. International Semantic Web Conference in Auckland statt. Daten aus dem Web, insbesondere Linked Data, Wissensgraphen und Markup-Daten sind eine informationsreiche und dynamische Quelle für mobilitätsrelevante und veranstaltungs-orientierte Informationen. Der PROFILES Workshop hat das Ziel, Ansätze zur Analyse, Beschreibung und Entdeckung von Datenquellen in Web-Daten zu bündeln, damit diese in Mobilitätsanwendungen und anderen Domänen genutzt werden können.

• Fall Advances in the Timing of Molt in Birds in the Southwestern United States. Kittelberger, Kyle D.; Neate-Clegg, Montague H. C.; cSekerciouglu, cCaugan Hakki (2026). 000–000.

  AbstractMolt is a critical event in the annual cycle of birds. Although we know an increasing amount about the impacts of climate change on the timing of other avian events, there has been relatively limited work conducted on changes in molt phenology over time. In this study, we utilized a 13-year bird-banding dataset from southeastern Utah to examine long-term trends in the molt timing of body and flight feathers during both the spring and the fall migratory seasons, accounting for temporal trends in nonmolting birds and how trends may vary between different sexes and ages of birds. We found that there were no significant temporal trends in molt timing in the spring but there were significant trends in the fall, such that birds were advancing the timing of their body and flight feather molt over time. Finally, we highlight the significant influence of climate on molt phenology: El Niño/Southern Oscillation and maximum temperature were both associated with advances in spring body molt, maximum temperature was associated with delays in fall flight feather molt timing, and precipitation was associated with advances in both fall body and flight feather molt timing. This study provides the first examination of long-term trends in the molt phenology of North American birds, showing that over the past decade, birds in the western United States have advanced their feather molt timing in the fall at a rate of roughly one day/year.
• Weakened Atlantic Meridional Overturning Circulation causes the historical North Atlantic Warming Hole. Li, Kai-Yuan; Liu, Wei (2025). 6(1) 416.

  Most oceans over the globe have experienced surface warming during the past century, but the subpolar Atlantic is quite otherwise. The sea surface temperature cooling trend to the south of Greenland, known as the North Atlantic Warming Hole, has raised debate over whether it is driven by the slowing of the Atlantic Meridional Overturning Circulation. Here we use observations as a benchmark and climate models as a tool to demonstrate that only models simulating a weakened historical Atlantic overturning can broadly reproduce the observed cooling and freshening in the warming hole region. This, in turn, indicates that the realistic Atlantic overturning slowed between 1900 and 2005, at a rate of −1.01 to −2.97thinspaceSv century−1 (1\thinspaceSv\thinspace=\thinspace106\thinspacem3\thinspaces−1), according to a sea-surface-temperature-based fingerprint index estimate. Particularly, the Atlantic overturning slowdown causes an oceanic heat transport divergence across the subpolar North Atlantic, which, while partially offset by enhanced ocean heat uptake, results in cooling over the warming hole region.
• PaCA: Partial Connection Adaptation for Efficient Fine-Tuning. Woo, Sunghyeon; Namkung, Sol; Lee, Sunwoo; Jeong, Inho; Kim, Beomseok; Jeon, Dongsuk (2025).
• Quantum Monte Carlo study of hydrodynamics in systems with particle-hole symmetry. Reingruber, Adrien; Pongsangangan, Kitinan; Assaad, Fakher; Ulybyshev, Maksim (2025). 134(20) 206303.
• Identifying Magnetotail Jet Front Signatures in a 3D + 3V Global Hybrid‐Vlasov Simulation. Pänkäläinen, Lauri; Cozzani, Giulia; Battarbee, Markus; Ganse, Urs; Pfau‐Kempf, Yann; Suni, Jonas; Palmroth, Minna (2025). 130(6)
• How HR Consultancy Services Can Transform Your Business in 2025 Mandal, Chakrika (C. Mandal, ed.) (2025). 128–132.
• Landscape structure, climate variability, and soil quality shape crop biomass patterns in agricultural ecosystems of Bavaria. Dhillon, Maninder Singh; Koellner, Thomas; Asam, Sarah; Bogenreuther, Jakob; Dech, Stefan; Gessner, Ursula; Gruschwitz, Daniel; Annuth, Sylvia Helena; Kraus, Tanja; Rummler, Thomas; Schaefer, Christian; Schönbrodt-Stitt, Sarah; Steffan-Dewenter, Ingolf; Wilde, Martina; Ullmann, Tobias (2025).
• Ion‐Mediated Tearing and Kink Instabilities in the Earth’s Magnetosphere: Hybrid‐Vlasov Simulations. Zaitsev, I.; Cozzani, G.; Alho, M.; Horaites, K.; Zhou, H.; Kit, A.; Pfau‐Kempf, Y.; Hoilijoki, S.; Ganse, U.; Battarbee, M.; Papadakis, K.; Suni, J.; Dubart, M.; Tesema‐Kebede, F.; Workayehu, A.; Tarvus, V.; Kotipalo, L.; Koikkalainen, V.; Turc, L.; Palmroth, M. (2025). 130(1)
• Integrating Colored Lights into Multimodal Robotic Storytelling. Steinhaeusser, Sophia C.; Maier, Sophia; Lugrin, Birgit (2025). 1(2) 202404.
• Exploring the Application of Time Series Foundation Models to Network Monitoring Tasks. Wehner, Nikolas; Casas, Pedro; Dietz, Katharina; Geißler, Stefan; Hoßfeld, Tobias; Seufert, Michael (2025).
• RLFuzz: Accelerating Hardware Fuzzing with Deep Reinforcement Learning. Götz, Raphael; Sendner, Christoph; Ruck, Nico; Rostami, Mohamadreza; Dmitrienko, Alexandra; Sadeghi, Ahmad-Reza (2025).

  Once hardware is manufactured, it becomes immutable, and any design flaws or vulnerabilities are permanent. Therefore, comprehensive testing of hardware designs is essential before production. However, the increasing complexity of modern processors makes static analysis and formal verification increasingly challenging. Fuzzing is a highly effective technique for detecting software vulnerabilities but adapting it to hardware presents unique challenges due to the fundamental differences between software and hardware. However, the current state-of-the-art in hardware fuzzing still has significant limitations, particularly in terms of performance, practicality, and the need for human intervention. To address these issues, we introduce RLFuzz, a novel hardware fuzzer that employs reinforcement learning to explore processors autonomously, achieving faster and more comprehensive coverage. Reinforcement learning enables the fuzzer to learn from its interactions with the processor without requiring labeled data, allowing it to more effectively select modifications for test cases and target previously unexplored areas. RLFuzz uses an asynchronous training mechanism that permits concurrent fuzzing and neural network training. To optimize RLFuzz, we performed an extensive evaluation of various deep Q-learning optimization techniques and hyper-parameters. We then tested the optimized fuzzer on three complex RISC-V cores-the Rocket core, CVA6, and BOOM-and compared its performance to a current hardware fuzzer, TheHuzz [20]. Our results show that RLFuzz achieved up to 1.77% higher coverage, and on average 2.35 times faster, and demonstrated a maximum speedup of up to 6.93 times. For branch coverage, the average speedup was 7.85 times, with a peak speedup of 92.98 times. Additionally, RLFuzz needed less time to complete 100,000 test cases and did not require any human intervention.
• Evaluating the Response of the Labrador Sea to Greenland Meltwater Influx With High-Resolution Eddy-Rich NEMO Simulations. Hoshyar, P.; Pennelly, C.; Myers, P. G. (2025). 130(5) e2024JC022102.

  Abstract The Greenland Ice Sheet has undergone substantial mass loss in recent decades primarily due to oceanic and atmospheric warming, contributing to global sea-level rise and enhanced ocean stratification. This study examines the Labrador Sea's response to increased Greenland freshwater influx using a very high-resolution, eddy-rich configuration of the NEMO ocean model. Two 9-year long experiments with identical setups, except one excluding Greenland runoff, suggest that freshwater influx leads to freshwater content increase (by up to 39\%) and intensified stratification (enhanced convective resistance by up to 29\%) in the Labrador Sea, whereas heat content remains mainly unchanged (up to 6\% increase). Strengthened stratification weakens but does not entirely stop deep convection allowing continued water mass formation within the region (maximum mixed layer depth differences of up to 635 m). A sensitivity analysis indicates warmer, saltier surface waters and colder, fresher subsurface layers when Greenland meltwater is excluded likely driven by reduced lateral exchange from the West Greenland Current system and enhanced southward Arctic Water transport across Davis Strait. Offshore freshwater exchange in the Labrador Sea interior is not solely controlled by Greenland meltwater influx but also by air-sea fluxes and deepwater formation. Over longer timescales exceeding a decade, ongoing freshening and intensified stratification could further disrupt essential oceanic processes with potential consequences for deepwater formation and Atlantic Meridional Overturning Circulation. These findings underscore the importance of accurately representing Greenland meltwater and shelf-basin exchanges in models to improve the predictions of Labrador Sea under future warming.
• Non-archimedean periods for log Calabi-Yau surfaces. Karwa, Soham; Lai, Jonathan (2025).
• Preference-Oriented Supervised Fine-Tuning: Favoring Target Model over Aligned Large Language Models. Fan, Yuchen; Hong, Yuzhong; Wang, Qiushi; Bao, Junwei; Jiang, Hongfei; Song, Yang T. Walsh, J. Shah, Z. Kolter (eds.) (2025). 23859–23867.
• An AI-Driven Card Playing Robot: An Empirical Study on Communicative Style and Embodiment with Elderly Adults. Banck, Michael; Ganal, Elisabeth; Weichert, Hanna-Finja; Puppe, Frank; Lugrin, Birgit (2025).
• 9.4 A 102ns/V 94.3%-Peak-Efficiency Symbol-Power-Tracking Supply Modulator for 5G NR Power Amplifiers. Shang, Minghao; Wang, Baochuang; Chen, Changjin; Jin, Ji; Cheng, Lin (2025). 1–3.
• Benefits of Choosing Sustainable and Natural Fragrances. Fragrances, Natural (2025).
• Atacamite Cu\($_\mathbf2$\)ClOH\($_\mathbf3$\) in high magnetic fields: Quantum criticality and dimensional reduction of a sawtooth-chain compound. Heinze, L.; Kotte, T.; Rausch, R.; Demuer, A.; Luther, S.; Feyerherm, R.; Ammerlaan, E. L. Q. N.; Zeitler, U.; Gorbunov, D. I.; Uhlarz, M.; Rule, K. C.; Wolter, A. U. B.; Kühne, H.; Wosnitza, J.; Karrasch, C.; Süllow, S. (2025). 134(21) 216701.
• Inductive Pressure Sensors Using 3D-Printed Structures With Tunable Stiffness. Bhaumik, Rahul; Preindl, Thomas; Ion, Alexandra; Ayala-Garcia, Camilo; Cohen, Nitzan; Haller, Michael; Münzenrieder, Niko (2025). 9(5) 1–4.

  Modern 3-D printing techniques enable the rapid prototyping of complex mechanical structures. We leverage this capability to create customizable pressure sensors by combining soft and ferromagnetic filaments during the printing process. The resulting inductive sensors utilize a lattice structure based on a body-centered cubic unit cell, exhibiting tunable stiffness with Young's moduli ranging from 112 to 368 kPa and sensitivities between \($-$\)0.17 and \($-$\)0.11% kPa\($^-1$\). The sensors show minimal hysteresis and remain stable throughout 10 000 compression cycles. The versatility of this approach is further demonstrated through the fabrication of a fully printed inductive joystick.
• Automated Modeling of Influence Diversity with Graph Convolutional Network for Social Recommendation. Bing, Rui; Yuan, Guan; Cai, Zhuo; Li, Bohan; Zhou, Yong in Lecture Notes in Computer Science, W. Zhang, A. K. H. Tung, Z. Zheng, Z. Yang, X. Wang, H. Guo (eds.) (2024). (Vol. 14962) 33–49.
• 131TOPS/W 8b ACIM Exploiting Weight-Embedded Auto-Accumulation and Supporting Symmetric Quantization Networks. He, Wei; Bai, Puvi; Luo, Hongyang; Jin, Zhenghao; Wu, Han; Zhang, Junyi; Chao, Xingchen; Liu, Haiqi; He, Yajuan; Li, Qiang (2024). 1–2.
• 31.8 A 11.7W 9mV/A-Cross-Regulation Single-Inductor Triple-Output Buck Converter Using Unordered Power-Distributive Control for a 2A Load Transient. Wang, Baochuang; Wu, Xiaonan; Cheng, Lin (2024). 510–512.
• ABCF: An Adaptive Balanced Multimodal Website Classification Framework. Liu, Zhiyuan; Liu, Wei; Tong, Xinyang; Shen, Qi; Zheng, Qiang; Hu, Hengrui; Liu, Hong; Wang, Xiaojie W. Shen, J.-P. A. Barthès, J. Luo, T. Qiu, X. Zhou, J. Zhang, H. Zhu, K. Peng, T. Xu, N. Chen (eds.) (2024). 79–84.
• Was isst Künstliche Intelligenz?. Redecker, Eva von; Herbelot, Aurélie (2024).

  KI verbraucht Unmengen an Energie, verdaut immer mehr Daten. Wird die Maschinenherrschaft des Kapitalismus Mensch und Planeten zerstören?
• Optimizing Handovers in Integrated 5G UAV Networks: A Core-RAN Co-location Approach. Jiang, Yue; Liang, Houze; Wang, Xijun; Chen, Xiang; Huang, Xiao (2024). 596–601.
• Fed-MS: Fault Tolerant Federated Edge Learning with Multiple Byzantine Servers. Qi, Senmao; Ma, Hao; Zou, Yifei; Yuan, Yuan; Li, Peng; Yu, Dongxiao (2024). 982–992.
• BR-DeFedRL: Byzantine-Robust Decentralized Federated Reinforcement Learning with Fast Convergence and Communication Efficiency. Qiao, Jing; Zhang, Zuyuan; Yue, Sheng; Yuan, Yuan; Cai, Zhipeng; Zhang, Xiao; Ren, Ju; Yu, Dongxiao (2024). 141–150.
• Exploring the Best Practices of Query Expansion with Large Language Models. Zhang, Le; Wu, Yihong; Yang, Qian; Nie, Jian-Yun Y. Al-Onaizan, M. Bansal, Y.-N. Chen (eds.) (2024). 1872–1883.
• A 5.6 dB NF Two-Stage 110 - 125 GHz LNA Gain-Boosted by RC-over-Neutralization for Radar Applications in 28 nm CMOS. Lasserre, V.; Koop-Brinkmann, S.; Caruso, M.; Maistro, D. Dal; Volpato, G.; Le, Q. H.; Kämpfe, Thomas; Ziegler, Christian; Stapelfeldt, Finn; Issakov, Vadim (2024). 146–149.
• Fed-MoE: Efficient Federated Learning for Mixture-of-Experts Models via Empirical Pruning. Zou, Yifei; Qi, Senmao; Yuan, Yuan; Wang, Dawei; Shen, Shikun; Wu, Libing; Guo, Shaoyong; Yu, Dongxiao in Lecture Notes in Computer Science, Y. Li, Y. Zhang, J. Xu (eds.) (2024). (Vol. 15502) 128–139.
• Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint. Xiong, Wei; Dong, Hanze; Ye, Chenlu; Wang, Ziqi; Zhong, Han; Ji, Heng; Jiang, Nan; Zhang, Tong (2024).
• Plag-Llama for IoT-Enabled Data Centers: A Multivariate Time Series Forecasting Approach. Sun, Yu; Cheng, Bo; Li, Jinan; Jiang, Gaoxiang; Zhang, Tianqi; Zhou, Haibo (2024). 4376–4381.
• RACC: Rapid and Accurate INT-Based Congestion Control in RDMA Network. Zhao, Yanzhe; Wang, Shuo; Han, Siyu; Zhou, Dong; Peng, Guoyu; Huang, Tao (2024). 3811–3816.
• Task-oriented Age of Information for Remote Monitoring Systems. Gan, Shuying; Wang, Xijun; Xu, Chao; Chen, Xiang (2024). 247–252.
• Bayesian Inference from the Ground Up: The Theory of Common Sense Wagenmakers, Eric-Jan; Matzke, Dora (2024). JASP.
• COSMIC: Data Efficient Instruction-tuning For Speech In-Context Learning. Pan, Jing; Wu, Jian; Gaur, Yashesh; Sivasankaran, Sunit; Chen, Zhuo; Liu, Shujie; Li, Jinyu I. Lapidot, S. Gannot (eds.) (2024).
• The Power of Reading Support for Learners: A State-of-the-Art Analysis of Computer-Assisted Reading from an Information Systems Perspective. Haenel, M.; Wambsganss, T.; Söllner, M. (2024).

  Reading and synthesizing scientific papers is a crucial skill for students. However, many students in higher education struggle to effectively comprehend scientific texts. To address this challenge, research has leveraged computer-assisted reading (CAR) systems to improve students' reading comprehension abilities at scale. However, the research and application of CAR in higher education still lack an organized overview and clear terminology due to the multidisciplinary character of the research field (e.g., Education didactic, Human-Computer Interaction, or Information Systems). Therefore, we perform a systematic literature review on CAR from an interdisciplinary Information Systems perspective. We take the socio-technical systems theory as a lens to organize, summarize past literature as well to identify white spots for a future research agenda. The main contributions of this paper are the synthesis and consolidation of CAR to create a basis for all researchers investigating the research field of CAR in higher education.
• Mythos der Maschine?: Künstliche Intelligenz und Gesellschaftskritik. Heiland, Heiner; Schütt, Mariana; Sieron, Sandra; Syrovatka, Felix (2024). 54(217) 553–571.

  »Künstliche Intelligenz« (KI) ist allgegenwärtig. KI dominiert alle Debatten, der Einsatz von KI wird in nahezu allen Bereichen diskutiert. KI wird dabei als neue technische »Revolution« begriffen, als »Heilsbringer«, und soll die Arbeitswelt umkrempeln. Tatsächlich verbirgt sich hinter diesem Hype vor allem eine Mythologisierung der Technik. Ebenso dient KI der Machtkonzentration bei den großen Tech-Konzernen und ist für die neue geopolitische Situation relevant. Die negativen gesellschaftlichen und klimatischen Konsequenzen geraten sowohl hinter den Heilsversprechen als auch hinter den apokalyptischen Szenarien aus dem Blick.
• Diffusion Models for Visual Computing. Mitra, Niloy; Cohen-Or, Daniel; Sung, Minhyuk; Huang, Chun-Hao; Ceylan, Duygu; Guerrero, Paul in SIGGRAPH Courses ’24 (2024). 1–290.
• GNN-Based Code Annotation Logic for Establishing Security Boundaries in C Code. Gadey, Varun; Goetz, Raphael; Sendner, Christoph; Sovio, Sampo; Dmitrienko, Alexandra (2024).

  Securing sensitive operations in today's interconnected software landscape is crucial yet challenging. Modern platforms rely on Trusted Execution Environments (TEEs), such as Intel SGX and ARM TrustZone, to isolate security sensitive code from the main system, reducing the Trusted Computing Base (TCB) and providing stronger assurances. However, identifying which code should reside in TEEs is complex and requires specialized expertise, which is not supported by current automated tools. Existing solutions often migrate entire applications to TEEs, leading to suboptimal use and an increased TCB. To address this gap, we propose Code Annotation Logic (CAL), a pioneering tool that automatically identifies security sensitive components for TEE isolation. CAL analyzes codebases, leveraging a graph-based approach with novel feature construction and employing a custom graph neural network model to accurately determine which parts of the code should be isolated. CAL effectively optimizes TCB, reducing the burden of manual analysis and enhancing overall security. Our contributions include the definition of security sensitive code, the construction and labeling of a comprehensive dataset of source files, a feature rich graph based data preparation pipeline, and the CAL model for TEE integration. Evaluation results demonstrate CAL's efficacy in identifying sensitive code with a recall of 86.05%, an F1 score of 81.56%, and an identification rate of 91.59% for security sensitive functions. By enabling efficient code isolation, CAL advances the secure development of applications using TEEs, offering a practical solution for developers to reduce attack vectors.
• Resource-Adaptive Newton’s Method for Distributed Learning. Chen, Shuzhen; Yuan, Yuan; Tao, Youming; Cai, Zhipeng; Yu, Dongxiao in Lecture Notes in Computer Science, W. Wu, G. Tong (eds.) (2023). (Vol. 14422) 335–346.
• Efficient Cross Dynamic Task Assignment in Spatial Crowdsourcing. Ren, Tianyue; Zhou, Xu; Li, Kenli; Gao, Yunjun; Zhang, Ji; Li, Keqin (2023). 1420–1432.
• A real-time polyp-detection system with clinical application in colonoscopy using deep convolutional neural networks. Krenzer, Adrian; Banck, Michael; Makowski, Kevin; Hekalo, Amar; Fitting, Daniel; Troya, Joel; Sudarevic, Boban; Zoller, Wolfgang G; Hann, Alexander; Puppe, Frank (2023). 9(2) 26.
• Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. Wang, Ziqi; Wu, Yuexin; Liu, Frederick; Liu, Daogao; Hou, Le; Yu, Hongkun; Li, Jing; Ji, Heng (2023).
• Rate-Fairness Balancing with DRL in Cell-Free Massive MIMO-NOMA Networks. Pang, Mingliang; Wang, Chaowei; Wang, Wenyuan; Deng, Danhao; Jiang, Fan; Gao, Feifei; Han, Guangjie; Zhang, Zhi; Wang, Weidong (2023). 643–648.
• SIGGRAPH 2023 Course on Diffusion Models. Meng, Chenlin; Song, Jiaming; Li, Shuang; Zhu, Jun-Yan; Ermon, Stefano; Lin, Tsung-Yi; Lin, Chen-Hsuan; Kreis, Karsten in SIGGRAPH ’23 (2023). 1–113.

  Diffusion models have been successfully used in various applications such as text-to-image generation, 3D assets generation, controllable image editing, video generation, natural language generation, audio synthesis, and motion generation. The rate of progress on diffusion models is astonishing. In the year 2022 alone, diffusion models have been applied to many large-scale text-to-image foundation models, such as DALL-E 2 [Ramesh et al. 2022], Imagen [Saharia et al. 2022], Stable Diffusion [Rombach et al. 2022], and eDiff-I [Balaji et al. 2022]; video generation models such as Imagen Video [Ho et al. 2022] and Make-a-video [Singer et al. 2022]; 3D asset generation models such as Magic3D [Lin et al. 2022] and DreamFusion [Poole et al. 2022]. This course covers the advances in diffusion models over the last few years and will be tailored to the computer graphics community. We will first cover the fundamental machine learning and deep learning techniques relevant to diffusion models. Next, we will present state-of-the-art techniques for the application of diffusion models to high-fidelity image synthesis, controllable image generation, compositional representation learning, and 3D asset generation. Finally, we will conclude with a discussion on the future application of this technology, societal impact and open research problems. After the course, the attendees will learn basic knowledge about diffusion models and how such models can be applied to different applications such as image generation, image editing, and 3D asset generation.
• Von der Schwierigkeit, den Kopf zum Himmel zu heben Weil, Simone (2023). Westend, Frankfurt am Main.

  Mutig, entschlossen und mit beispiellosem Einsatz kämpfte Simon Weil zeit ihres Lebens für eine bessere Welt. Dabei stellte sie die leidvolle Erfahrung der Fabrikarbeiter und -arbeiterinnen in den Mittelpunkt ihres Engagements. Überraschenderweise steht Weils Vision zur Lösung der sozialen Frage in engem Verhältnis zu Gott. Dabei geht es ihr aber keinesfalls um ein Aufgeben des Weltlichen im Glauben. Die Ordensschwester Britta Müller-Schauenburg beschreibt Weils Haltung in ihrem Vorwort vielmehr als einen "geistlichen Umgang" mit "geistlosen Routinen": Fremdbestimmtheit und Sinnlosigkeitsempfindungen, die sich wie die soziale Ungerechtigkeit bis heute weiter ausbreiten. Weils Texte, die jetzt endlich auf Deutsch vorliegen, legen davon ein eindrucksvolles Zeugnis ab.
• A 150nA IQ, 850mA ILOAD, 90% Efficiency over 10μA to 400mA Loading Range. Wang, Baochuang; Xie, Yiling; Guo, Jianping; Cheng, Lin (2023). 1–2.
• What should I Ask: A Knowledge-driven Approach for Follow-up Questions Generation in Conversational Surveys. Ge, Yubin; Xiao, Ziang; Diesner, Jana; Ji, Heng; Karahalios, Karrie; Sundaram, Hari C.-R. Huang, Y. Harada, J.-B. Kim, S. Chen, Y.-Y. Hsu, E. Chersoni, P. A, W. H. Zeng, B. Peng, Y. Li, J. Li (eds.) (2023). 113–124.
• Global and Adaptive Local Label Correlation for Multi-label Learning with Missing Labels. Jiang, Qingxia; Li, Peipei; Zhang, Yuhong; Hu, Xuegang (2023). 1–8.
• A User Interface for Automatic Polyp Detection Based on Deep Learning with Extended Vision. Krenzer, Adrian; Troya, Joel; Banck, Michael; Sudarevic, Boban; Flisikowski, Krzysztof; Meining, Alexander; Puppe, Frank (2022). 851–868.
• New concept for colonoscopy including side optics and artificial intelligence. Troya, Joel; Krenzer, Adrian; Flisikowski, Krzysztof; Sudarevic, Boban; Banck, Michael; Hann, Alexander; Puppe, Frank; Meining, Alexander (2022). 95(4) 794–798.
• Effective Learning and Online Modulation for Robotic Variable Impedance Skills. Zhai, Xueqian; Ou, Yangmin; Xu, Zhihao; Jiang, Li; Zhou, Xuefeng; Wu, Hongmin (2022). 1–6.
• Pilot study of a new freely available computer-aided polyp detection system in clinical practice. Lux, Thomas J; Banck, Michael; Saßmannshausen, Zita; Troya, Joel; Krenzer, Adrian; Fitting, Daniel; Sudarevic, Boban; Zoller, Wolfram G; Puppe, Frank; Meining, Alexander; others (2022). 37(6) 1349–1354.
• A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems. Fitting, Daniel; Krenzer, Adrian; Troya, Joel; Banck, Michael; Sudarevic, Boban; Brand, Markus; Böck, Wolfgang; Zoller, Wolfram G; Rösch, Thomas; Puppe, Frank; others (2022). 57(11) 1397–1403.
• BaGuaLu: targeting brain scale pretrained models with over 37 million cores. Ma, Zixuan; He, Jiaao; Qiu, Jiezhong; Cao, Huanqi; Wang, Yuanwei; Sun, Zhenbo; Zheng, Liyan; Wang, Haojie; Tang, Shizhi; Zheng, Tianyu; Lin, Junyang; Feng, Guanyu; Huang, Zeqiang; Gao, Jie; Zeng, Aohan; Zhang, Jianwei; Zhong, Runxin; Shi, Tianhui; Liu, Sha; Zheng, Weimin; Tang, Jie; Yang, Hongxia; Liu, Xin; Zhai, Jidong; Chen, Wenguang J. Lee, K. Agrawal, M. F. Spear (eds.) (2022). 192–204.
• UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Prediction. Wu, Huanqin; Liu, Wei; Li, Lei; Nie, Dan; Chen, Tao; Zhang, Feng; Wang, Di in Findings of ACL, C. Zong, F. Xia, W. Li, R. Navigli (eds.) (2021). (Vol. ACL/IJCNLP 2021) 825–835.
• Kinematic control of wheeled mobile manipulators subject to inherent physical constraints and noise disturbances. Li, Xiaoxiao; Xu, Zhihao; Li, Shuai; Jiang, Kanyang; Zhou, Xuefeng; Jiang, Li (2021). 417–422.
• SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels. Dahiya, Kunal; Agarwal, Ananye; Saini, Deepak; K, Gururaj; Jiao, Jian; Singh, Amit; Agarwal, Sumeet; Kar, Purushottam; Varma, Manik in Proceedings of Machine Learning Research, M. Meila, T. Zhang (eds.) (2021). (Vol. 139) 2330–2340.
• Weakly-Supervised Video Moment Retrieval via Semantic Completion Network. Lin, Zhijie; Zhao, Zhou; Zhang, Zhu; Wang, Qi; Liu, Huasheng (2020). 11539–11546.
• CIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization. Li, Lei; Xie, Yang; Liu, Wei; Liu, Yinan; Jiang, Yafei; Qi, Siya; Li, Xingyuan M. K. Chandrasekaran, A. de Waard, G. Feigenblat, D. Freitag, T. Ghosal, E. H. Hovy, P. Knoth, D. Konopnicki, P. Mayr, R. M. Patton, M. Shmueli-Scheuer (eds.) (2020). 225–234.
• Maintenance of Range Skyline Query. Li, Xiaoxue; Shi, Yuanquan; Zhou, Xu; Li, Kenli E. Chen, G. Antoniou (eds.) (2020). 615–620.
• Designing a Conversational Agent as a Formative Course Evaluation Tool. Wambsganss, Thiemo; Winkler, Rainer; Schmid, Pascale; Söllner, Matthias N. Gronau, M. Heine, H. Krasnova, K. Poustcchi (eds.) (2020). 1234–1249.

  Today's graduating students face ever-changing environments when they enter their job life. Educational institutions must therefore continuously develop their course structure and content in order to prepare their students to be future employees. A very important means for developing the courses is the students' course evaluations. Due to financial and organizational restrictions, these course evaluations are usually carried out quantitatively and at the end of the semester. However, past research has shown that this kind of evaluation faces certain constraints such as low acceptance rates, only time-related insights and low-quality answers that do not really help the lecturer to improve the course. Drawing on social response theory, we propose that conversational agents as a formative course evaluation tool are able to address the mentioned problems by interactively engaging with students. Therefore, we propose a set of design principles and evaluate them with our prototype Eva.
• Engaging Learners in Online Video Lectures with Dynamically Scaffolding Conversational Agents. Winkler, Rainer; Hobert, Sebastian; Fischer, Tizian; Salovaara, Antti; Söllner, Matthias; Leimeister, Jan Marco (2020).

  Online education creates new opportunities for learners, which has led to sharply increasing enrollment in the last few years. Despite these benefits, past research shows that the lack of individual interaction with educators creates low learner engagement that leads to high attrition rates, which remains a major challenge in the field. Dynamically scaffolding conversational agents built into online video lectures promise to address this problem by individually interacting with learners, similar to educators’ scaffolding behavior. These agents are equipped with recent natural language processing capabilities, creating human-like conversations that help learners to be more engaged in the learning process. To test our hypothesis, we built a dynamically scaffolding conversational agent named Sara and compared it with an often-implemented static conversational agent built into two online video lectures. We deployed a lab experiment with 182 learners. The neurophysiological measurements revealed that Sara significantly improved learner engagement partly explained by differences in learners’ perceptions in the way they experienced the interaction. This study connects to already existing conversational agent studies in online education and highlights the importance of including dynamically scaffolding conversational agents in online video lectures to address the problem of low learner engagement in online education.
• Complexity-efficient Fano Decoding of Polarization-adjusted Convolutional (PAC) Codes. Rowshan, Mohammad; Burg, Andreas; Viterbo, Emanuele (2020). 200–204.
• A Two-Stage Clustering Algorithm Based on Improved K-Means and Density Peak Clustering. Xiao, Na; Zhou, Xu; Huang, Xin; Yang, ZhiBang Y. Gao, R. Möller, X. Wu, R. Kotagiri (eds.) (2019). 296–301.
• A caveat on the Savage–Dickey density ratio: The case of computing Bayes factors for regression parameters. Heck, Daniel W. (2019). 72(2) 316–333.

  The Savage?Dickey density ratio is a simple method for computing the Bayes factor for an equality constraint on one or more parameters of a statistical model. In regression analysis, this includes the important scenario of testing whether one or more of the covariates have an effect on the dependent variable. However, the Savage?Dickey ratio only provides the correct Bayes factor if the prior distribution of the nuisance parameters under the nested model is identical to the conditional prior under the full model given the equality constraint. This condition is violated for multiple regression models with a Jeffreys?Zellner?Siow prior, which is often used as a default prior in psychology. Besides linear regression models, the limitation of the Savage?Dickey ratio is especially relevant when analytical solutions for the Bayes factor are not available. This is the case for generalized linear models, non-linear models, or cognitive process models with regression extensions. As a remedy, the correct Bayes factor can be computed using a generalized version of the Savage?Dickey density ratio.
• Fast Fault-Tolerant Sampling via Random Walk in Dynamic Networks. Yuan, Yuan; Li, Feng; Yu, Dongxiao; Yu, Jiguo; Wu, Yu; Lv, Weifeng; Cheng, Xiuzhen (2019). 536–544.
• A Novel Clustering Algorithm based on Directional Propagation of Cluster Labels. Xiao, Na; Li, Kenli; Zhou, Xu; Li, Keqin (2019). 1–8.
• TopicInk: Visualizing Disaster-Related Textual Data Using LDA Topic Modeling: Vast Challenge 2019: Honorable Mention for Clear Articulation of Methodology. Guo, Chen; Liu, Xiang; Cai, Evie; Chen, Yingjie Victor; Qian, Zhenyu Cheryl; Li, Rui R. Chang, D. A. Keim, R. Maciejewski (eds.) (2019). 124–125.
• CIST@CLSciSumm-19: Automatic Scientific Paper Summarization with Citances and Facets. Li, Lei; Zhu, Yingqi; Xie, Yang; Huang, Zuying; Liu, Wei; Li, Xingyuan; Liu, Yinan in CEUR Workshop Proceedings, M. K. Chandrasekaran, P. Mayr (eds.) (2019). (Vol. 2414) 196–207.
• Smart Hydroponics: Solar Powered Hydroponics System using Dual Axis Solar Tracker. Shetty, Savitha; Shetty, Saritha; Rodrigues, Joshva; B, Priya Kamath; R, Sowmya M (2018).
• Seq2RDF: An End-to-end Application for Deriving Triples from Natural Language Text. Liu, Yue; Zhang, Tongtao; Liang, Zhicheng; Ji, Heng; McGuinness, Deborah L. in CEUR Workshop Proceedings, M. van Erp, M. Atre, V. López, K. Srinivas, C. Fortuna (eds.) (2018). (Vol. 2180)
• Remotely View User Activities and Impose Rules and Penalties in a Local Area Network Environment. Buctuanon, Marisa; Debalucos, Roldan; Villalon, John Glenn M. B. Nunes, M. McPherson (eds.) (2018). 128–132.
• MMH: Multi-Modal Hash for Instant Mobile Video Search. Gao, Wenhui; Liu, Xinchen; Ma, Huadong; Li, Yanan; Liu, Liang (2018). 57–62.
• Fine-grained Coordinated Cross-lingual Text Stream Alignment for Endless Language Knowledge Acquisition. Ge, Tao; Dou, Qing; Ji, Heng; Cui, Lei; Chang, Baobao; Sui, Zhifang; Wei, Furu; Zhou, Ming E. Riloff, D. Chiang, J. Hockenmaier, J. Tsujii (eds.) (2018). 2496–2506.
• “L’Aimable Visir” : Pierre David’s Consulship under Hüsrev Mehemed Pasha’s Rule as Governor of Bosnia. Cascavilla, Giuseppe Pio (2018). 41 611–645.
• Identifying most preferential skyline product combinations under price promotion. Yang, ZhiBang; Zhou, Xu; Zeng, Yifu; Zeng, Fei; Zhou, Yantao (2016). 1824–1828.
• Embedded system for real-time person detecting in infrared images/videos using super-resolution and Haar-like feature techniques. Ramos, Gilberto Guadalupe Jara; Sánchez-García, Juan Carlos; Ponomariov, Volodymyr (2015). 1–6.
• Language and Domain Independent Entity Linking with Quantified Collective Validation. Wang, Han; Zheng, Jinguang; Ma, Xiaogang; Fox, Peter; Ji, Heng L. Màrquez, C. Callison-Burch, J. Su, D. Pighin, Y. Marton (eds.) (2015). 695–704.
• Parameter estimation for LP regularized image deconvolution. Zhou, Xu; Zhou, Fugen; Bai, Xiangzhi (2015). 4892–4896.
• Exploiting Task-Oriented Resources to Learn Word Embeddings for Clinical Abbreviation Expansion. Liu, Yue; Ge, Tao; Mathews, Kusum; Ji, Heng; McGuinness, Deborah L. K. B. Cohen, D. Demner-Fushman, S. Ananiadou, J. Tsujii (eds.) (2015). 92–97.
• Parallel algorithm for solving penta-diagonal linear systems. Zhu, Cheng; Li, Kenli; Yang, Wangdong; Zhou, Xu (2015). 2437–2442.
• Uncertain dynamic skyline queries for uncertain databases. Yang, ZhiBang; Yang, Xiaoniu; Zhou, Xu (2015). 1797–1802.
• RaceFree: an efficient multi-threading model for determinism. Lu, Kai; Zhou, Xu; Wang, Xiaoping; Zhang, Wenzhe; Li, Gen A. Nicolau, X. Shen, S. P. Amarasinghe, R. W. Vuduc (eds.) (2013). 297–298.
• Combining Social Cognitive Theories with Linguistic Features for Multi-genre Sentiment Analysis. Li, Hao; Chen, Yu; Ji, Heng; Muresan, Smaranda; Zheng, Dequan (2012). 127–136.
• Relabeling Distantly Supervised Training Data for Temporal Knowledge Base Population. Tamang, Suzanne; Ji, Heng J. Fan, R. Hoffman, A. Kalyanpur, S. Riedel, F. M. Suchanek, P. P. Talukdar (eds.) (2012). 25–30.
• A novel solution for the P2P network observer placement problem on DNA-based supercomputing. Yue, Guangxue; Zhou, Xu; Li, Kenli; Li, Renfa; Zhao, Liping; Yu, Xiang (2010). 185–189.
• A novel and fast parallel solution for the vertex cover problem on DNA-based supercomputing. Zhou, Xu; Yue, Guangxue; Li, Kenli; Yu, Xiang; Li, Renfa (2010). 190–194.
• Transducing Logical Relations from Automatic and Manual GLARF. Meyers, Adam; Kosaka, Michiko; Ji, Heng; Xue, Nianwen; Harper, Mary P.; Sun, Ang; Xu, Wei; Liao, Shasha (2009). 116–120.
• The effects of high quality translations of named entities in cross-language information exploration. Wu, Dan; He, Daqing; Ji, Heng; Grishman, Ralph (2008). 1–8.
• A study of using an out-of-box commercial MT system for query translation in CLIR. Wu, Dan; He, Daqing; Ji, Heng; Grishman, Ralph F. Lazarinis, E. N. Efthimiadis, J. Vilares, J. Tait (eds.) (2008). 71–76.
• Building a Parallel Spatio-Temporal Data-Text Corpus for Summary Generation. Turner, Ross; Sripada, Gowri Somayajulu; Reiter, Ehud Baruch; Davy, Ian (2008). 28–35.

  We describe a corpus of naturally occurring road ice weather forecasts and the associated weather prediction data they are based upon. We also show how observations from an analysis of this corpus have been applied to build a prototype Natural Language Generation (NLG) system for producing road ice forecasts. While this corpus occurs in a narrow domain, it has much wider applicability due to the nature of its spatial descriptions, whose primary communicative goal is to describe the interaction between meteorological parameters and geographic features.
• Linear stability of a surfactant-laden annular film in a time-periodic pressure-driven flow through a capillary. Wei, Hsien-Hung; Halpern, David; Grotberg, James B. (2005). 285(2) 769–780.

  This paper analyzes the effect of surfactant on the linear stability of an annular film in a capillary undergoing a time-periodic pressure gradient force. The annular film is thin compared to the radius of the tube. An asymptotic analysis yields a coupled set of equations with time-periodic coefficients for the perturbed fluid–fluid interface and the interfacial surfactant concentration. Wei and Rumschitzki (submitted for publication) previously showed that the interaction between a surfactant and a steady base flow could induce a more severe instability than a stationary base state. The present work demonstrates that time-periodic base flows can modify the features of the steady-flow-based instability, depending on surface tension, surfactant activity, and oscillatory frequency. For an oscillatory base flow (with zero mean), the growth rate decreases monotonically as the frequency increases. In the low-frequency limit, the growth rate approaches a maximum corresponding to the growth rate of a steady base flow having the same amplitude. In the high-frequency limit, the growth rate reaches a minimum corresponding to the growth rate in the limit of a stationary base state. The underlying mechanisms are explained in detail, and extension to other time-periodic forms is further exploited.
• The effects of insoluble surfactants on the linear stability of a core-annular flow. Wei, Hsien-Hung; Rumschitzki, David S. (2005). 541 115–142.

  The effects of an insoluble surfactant on the linear stability of a two-fluid core–annular flow in the thin annulus limit, for axisymmetric disturbances with wavelengths large compared to the annulus thickness, h0 , are the focus of this investigation. A base shear flow affects the interfacial surfactant distribution, thereby inducing Marangoni forces that, along with capillary forces, affect the fluid–fluid interface stability. The resulting system's stability differs markedly from that of the same system with zero base flow. In the thin-annulus limit (the ratio ε of the undisturbed annulus thickness to core radius tends to zero), common in applications, a scaling and asymptotic analysis yields a coupled set of equations for the perturbed fluid–fluid interface shape and surfactant concentration. The linear dynamics of the annular film fully determine these equations, i.e. the core dynamics are slaved to the film dynamics. The theory provides a unified view of the mechanism of stability in three different regimes of capillary number Ca (defined as the product of the core viscosity, μ1 , and the centreline velocity, W0 , divided by the interface tension, σ∗0 , that corresponds to an undisturbed (signified by the subscript 0) uniform surfactant concentration, Γ∗0 ). In the absence of a base flow or in the limit of small Ca(≪ε2) , Marangoni forces deriving from non-uniformities in the interface concentration of insoluble surfactants oppose the net capillary forces. These latter forces normally stabilize the longitudinal curvature and destabilize the circumferential curvature of perturbations to the interface. In the limit of large Ca(≫ε2) , Marangoni forces destabilize disturbances with wavelengths that are large compared to the annulus thickness. For moderately small Ca(∼ε2) , increasing the Marangoni number Ma (defined as the product of (−∂σ∗/∂Γ∗)0 and Γ∗0 , divided by μ1W0) from zero increases the growth rates of all disturbances (with wavelengths ≫h0) and, consequently, reduces the marginal wavelength below that typical of the capillary instability. However a further increase in Ma eventually reverses these trends. A very large value for Ma stiffens the interface, which opposes any local variation of the tangential velocity along the interface, and this is true whether or not there is a base flow. In the limit of infinite Ma, the growth rate of the instability is 1/4 of that of the clean interface and the marginal wavenumber, non-dimensionalized by the undisturbed core circumference, returns to its clean interface (capillary) value of 1. All trends are explained physically.
• Monte Carlo Methods in Bayesian Computation Chen, Ming-Hui; Shao, Qi-Man; Ibrahim, Joseph George in Springer Series in Statistics (2000). Springer, New York.

  Sampling from the posterior distribution and computing posterior quanti­ ties of interest using Markov chain Monte Carlo (MCMC) samples are two major challenges involved in advanced Bayesian computation. This book examines each of these issues in detail and focuses heavily on comput­ ing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo (MC) methods for estimation of posterior summaries, improv­ ing simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, Highest Poste­ rior Density (HPD) interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. Also extensive discussion is given for computations in­ volving model comparisons, including both nested and nonnested models. Marginal likelihood methods, ratios of normalizing constants, Bayes fac­ tors, the Savage-Dickey density ratio, Stochastic Search Variable Selection (SSVS), Bayesian Model Averaging (BMA), the reverse jump algorithm, and model adequacy using predictive and latent residual approaches are also discussed. The book presents an equal mixture of theory and real applications. Similar content being
• On the multiple microphone method for measuring in-duct acoustic properties in the presence of mean flow. Jang, Seung-Ho; Ih, Jeong-Guon (1998). 103(3) 1520–1526.
• On the multiple microphone method for measuring in-duct acoustic properties in the presence of mean flow. Jang, Seung-Ho; Ih, Jeong-Guon (1998). 103(3) 1520–1526.
• Latas: fenomenologija izdajstva. Karadžić, Radovan (1981). 249–258.
• Sarajevski atentat : izvorne stenografske bilješke sa glavne rasprave protiv Gavrila Principa i drugova, održane u Sarajevu 1914 g Bogićević, Vojislav (1954). Državni arhiv NR BiH, Sarajevo.