Data4UrbanMobility nimmt an der Ausstellung „Marktplatz der Möglichkeiten“ bei dem Leibniz Startup & Industry Event “Künstliche Intelligenz” teil. Die Veranstaltung findet am 20.11.2018 im Lichthof der Leibniz Universität Hannover statt und wird vom Forschungszentrum L3S organisiert.

• Towards ML System Extensibility. Deng, Weixin; Ruan, Andy; Frisella, Megan; Chen, Kai-Hsun; Cho, SangBin; Humphries, Jack Tigar; Qiao, Rui; Wang, Stephanie (2025). 119–126.
• Fusion of GNN and GBDT Models for Graph and Node Classification. Farhan, Muhammad; Kajla, Nadeem Iqbal; Awan, Malik Daler Ali; Coustaty, Mickaël; Luqman, Muhammad Muzzamil; Bakkali, Souhail in Lecture Notes in Computer Science, L. Brun, V. Carletti, S. Bougleux, B. Gaüzère (eds.) (2025). (Vol. 15727) 167–178.
• Understanding Multidimensional Determinants of Information Security Policy Compliance in Hybrid Work Environments. Abdullah, Rafae Muhammad; Torres, Carlos I.; Carlson, John C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 18:1–18:2.
• How can information systems be designed to balance misinformation prevention with user privacy and freedom of expression on social media platforms. Alohali, Mansor; Alourani, Abdullah C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 4:1–4:2.
• Building Patient Trust in AI Healthcare Agents: Factors Influencing Acceptance and Adoption. Jing, Na C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 25:1.
• Evaluating Phishing Email Efficacy. Olea, Carlos; Christensen, Alexander; Fazio, Lisa; Cutting, Laurie; Lieb, Maxwell; Phelan, Jessica; Wise, Alyssa; Tucker, Holly C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 7:1–7:8.
• Feature Alignment in Vision Mamba to Resolve Domain Shift of Mobile Medical Devices. Shin, Jin; Kim, Hyun (2025). 1–4.
• A Geometric Perspective on Graph Similarity Learning Using Convex Hulls. Dobler, Kalvin; Riesen, Kaspar in Lecture Notes in Computer Science, L. Brun, V. Carletti, S. Bougleux, B. Gaüzère (eds.) (2025). (Vol. 15727) 103–112.
• Graph Neural Network Based on Molecular and Pharmacophoric Features for Drug Design Applications. Azevedo, Mariana; Brun, Luc; Héroux, Pierre; Lamotte, Jean Luc; Bureau, Ronan; Lepailleur, Alban in Lecture Notes in Computer Science, L. Brun, V. Carletti, S. Bougleux, B. Gaüzère (eds.) (2025). (Vol. 15727) 47–57.
• VisHubGAT: Visible Connectivity and Hub Nodes for Multimodal Entity Extraction. Telnoff, Quentin; Baitu, Baglan; Coustaty, Mickaël; Crohas, Fabrice; Doucet, Antoine in Lecture Notes in Computer Science, L. Brun, V. Carletti, S. Bougleux, B. Gaüzère (eds.) (2025). (Vol. 15727) 267–276.
• Exploring a Graph Regression Problem in River Networks. Fankhauser, Benjamin; Bigler, Vidushi; Riesen, Kaspar in Lecture Notes in Computer Science, L. Brun, V. Carletti, S. Bougleux, B. Gaüzère (eds.) (2025). (Vol. 15727) 203–213.
• Beyond Technical Training: A Cybersecurity Skills Framework for Non-Professionals. Schramm, Lena Theodora; Lin, Raymund; Wei, Hsiao-Lan C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 14:1–14:8.
• Lifting Some Secrets About Contrast Pyramids. Kropatsch, Walter G. in Lecture Notes in Computer Science, L. Brun, V. Carletti, S. Bougleux, B. Gaüzère (eds.) (2025). (Vol. 15727) 235–245.
• Gene Co-expression Networks are Poor Proxies for Expert-Curated Gene Regulatory Networks. Sarkar, Suryadipto; Blumenthal, David B. in Lecture Notes in Computer Science, L. Brun, V. Carletti, S. Bougleux, B. Gaüzère (eds.) (2025). (Vol. 15727) 37–46.
• Fully Randomized Pointers. Phaye, Sai Dhawal; Duck, Gregory J.; Yap, Roland H. C.; Carlson, Trevor E. M. Maas, T. Harris, O. Mutlu (eds.) (2025). 94–108.
• Reworking Memory Management in CRuby: A Practitioner Report. Wang, Kunshan; Blackburn, Stephen M.; Zhu, Peter; Valentine-House, Matthew M. Maas, T. Harris, O. Mutlu (eds.) (2025). 109–121.
• Reconsidering Garbage Collection in Julia: A Practitioner Report. de Souza Amorim, Luís Eduardo; Lin, Yi; Blackburn, Stephen M.; Netto, Diogo; Baraldi, Gabriel; Daly, Nathan; Hosking, Antony L.; Pamnany, Kiran; Smith, Oscar M. Maas, T. Harris, O. Mutlu (eds.) (2025). 72–83.
• Artificial Intelligence and Machine Learning Based Plant Monitoring. Rampure, Shrutika C; P, Bhavyashree S; T, Rakshitha B (2025).
• Compiler-Assisted Crash Consistency for PMEM. Soh, Yun Joon; Liu, Sihang; Swanson, Steven; Zhao, Jishen M. Maas, T. Harris, O. Mutlu (eds.) (2025). 41–55.
• SecureMind: A Framework for Benchmarking Large Language Models in Memory Bug Detection and Repair. Wang, Huanting; Jacob, Dejice; Kelly, David; Elkhatib, Yehia; Singer, Jeremy; Wang, Zheng M. Maas, T. Harris, O. Mutlu (eds.) (2025). 27–40.
• Cyber Defense through Agentic AI Enabled Automation: An Approach to Reduce Cyber Risk. Vajpayee, Prashant; Hossain, Gahangir C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 9:1–9:2.
• Differential Well-Being Outcomes from Smart Device Adoption: A Comparative Analysis of Seniors and Non-Seniors. Liu, Dapeng; Liu, Jinyu; Song, Xinru; Saxena, Tejaswi C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 19:1–19:7.
• Arborescent Garbage Collection: A Dynamic Graph Approach to Immediate Cycle Collection. Lahaie-Bertrand, Frédéric; O’Leary, Léonard Oest; Melançon, Olivier; Feeley, Marc; Monnier, Stefan M. Maas, T. Harris, O. Mutlu (eds.) (2025). 14–26.
• Tolerate It if You Cannot Reduce It: Handling Latency in Tiered Memory. Unal, Musa; Gupta, Vishal; Pan, Yueyang; Ren, Yujie; Kashyap, Sanidhya (2025). 50–57.
• Leveraging Software Fault Tolerance for Longer Flash Hardware Lifespan. Zuck, Aviad; Johnson, Rob; Porter, Donald E.; Tsafrir, Dan (2025). 210–217.
• Modular, Full-System Verification. Malecha, Gregory; Dang, Hoang-Hai; Giarrusso, Paolo G.; Hudon, Simon; Kaiser, Jan-Oliver; Swasey, David (2025). 42–49.
• Rethinking Tiered Storage: Talk to File Systems, Not Device Drivers. Zhang, Jiyuan; Kim, Jongyul; Alverti, Chloe; Liu, Peizhe; Jia, Weiwei; Xu, Tianyin (2025). 67–73.
• Guillotine: Hypervisors for Isolating Malicious AIs. Mickens, James; Radway, Sarah; Netravali, Ravi (2025). 18–26.
• The NIC should be part of the OS. Xu, Pengcheng; Roscoe, Timothy (2025). 151–157.
• Granular Resource Demand Heterogeneity. Liang, Yizhuo; Govindan, Ramesh; Park, Seo Jin (2025). 187–194.
• Stop Taking the Scenic Route: the Shortest Distance Between the CPU and the NIC is MMIO. Liew, Wei Siew; Rahaman, Md Ashfaqur; McMahon, James; Stutsman, Ryan; Nagarajan, Vijay (2025). 144–150.
• Understanding the limitations of pubsub systems. Adya, Atul; Bogle, Phil; Meek, Colin (2025). 165–171.
• Analyzing Metastable Failures. Isaacs, Rebecca; Alvaro, Peter; Majumdar, Rupak; Kumar, Kiran; Reddy, Muniswamy; Salamati, Mahmoud; Soudjani, Sadegh (2025). 172–178.
• How Human Behavior Can Mitigate AI-Generated Cybersecurity Threats. Noordeen, Abdul Rahman; Bantan, May C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 17:1–17:3.
• The Case for Energy Clarity. Chung, Fan; Kuo, Henry; Candea, George (2025). 202–209.
• Towards Resource-Efficient Compound AI Systems. Chaudhry, Gohar Irfan; Choukse, Esha; Goiri, Íñigo; Fonseca, Rodrigo; Belay, Adam; Bianchini, Ricardo (2025). 218–224.
• Panel: Workforce Implications of Learned passivity. Slyke, Craig Van; Mansour, Joseph; Joseph, Damien; Sumner, Mary; Zaza, Sam C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 26:1–26:2.
• On the Attitudes of GameDev Industry Artists towards GenAI. Preliminary Results. Sikorski, Lukasz; Matulewski, Jacek; Czerwonka, Malgorzata C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 2:1–2:6.
• Software as a Service (SaaS) and Firm Performance: The Necessity of Differentiating between Vertical and Horizontal SaaS. Shapouri, Fatemeh; Ward, Kerry; Lumbard, Kevin; Setor, Tenace C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 12:1–12:7.
• Unleashing the Machine : Exploring the Dual Power of AI’s Agentic Behavior and Anthropomorphic Design in an Agents Decision-Making. Pallepogu, Jayabhushan Praneeth; Gupta, Saurabh C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 11:1–11:2.
• "Not My First Choice": Why Software Testing Struggles to Attract Early-Career Professionals. Mulgund, Pavankumar; Singh, Raghvendra; Gillenson, Mark; Li, Yafang; Oliver, Carol C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 13:1–13:8.
• Gender Disparities in STEM Education and Academia: an Open Data Approach from Bolivia. Jiménez, Elizabeth; Guzman, Indira R.; Lens, Alexandro Israel C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 21:1–21:2.
• Financial Inclusion in a Cashless Society: Moderating a Darkside of Cashless Societies. Abayomi, Olushola; Noordeen, Abdul Rahman C. K. Riemenschneider, Y. W. Sullivan, M. Dinger, M. Bantan, N. Roberts (eds.) (2025). 16:1–16:3.
• EMD: Fair and Efficient Dynamic Memory De-bloating of Transparent Huge Pages. Gangar, Parth; Panwar, Ashish; Gopinath, K. M. Maas, T. Harris, O. Mutlu (eds.) (2025). 1–13.
• TierTrain: Proactive Memory Tiering for CPU-Based DNN Training. Swaminathan, Sathvik; Kumar, Sandeep; Prasad, Aravinda; Subramoney, Sreenivas M. Maas, T. Harris, O. Mutlu (eds.) (2025). 56–71.
• Gray-in-Young: A Generational Garbage Collection for Processing-in-Memory. Morimoto, Ryu; Ichinose, Kazuki; Ugawa, Tomoharu M. Maas, T. Harris, O. Mutlu (eds.) (2025). 122–133.
• Time-critical and confidence-based abstraction dropping methods. Schmöcker, Lennart Kampmann Robin (2025).
• Protection Against Poisoning Attacks on Federated Learning-Based Spectrum Sensing \($\$\) \($ \lg $\)\\($ $\). Wasilewska, Malgorzata; Bogucka, Hanna (2025).
• Leveraging Large Language Models for Automated Definition Extraction with TaxoMatic A Case Study on Media Bias. Spinde, Timo; Lin, Luyang; Hinterreiter, Smi; Echizen, Isao (2025). (Vol. 19)

  This paper introduces TaxoMatic, a framework that leverages large language models to automate definition extraction from academic literature. Focusing on the media bias domain, the framework encompasses data collection, LLM-based relevance classification, and extraction of conceptual definitions. Evaluated on a dataset of 2,398 manually rated articles, the study demonstrates the frameworks effectiveness, with Claude-3-sonnet achieving the best results in both relevance classification and definition extraction. Future directions include expanding datasets and applying TaxoMatic to additional domains.
• NewsUnfold: Creating a News-Reading Application That Indicates Linguistic Media Bias and Collects Feedback. Hinterreiter, Smi; Wessel, Martin Paul; Schliski, Fabian; Echizen, Isao; Latoschik, Marc Erich; Spinde, Timo J. An, Y.-R. Lin, Y. Mejova, E. Mustafaraj, J. Kulshrestha, I. Weber (eds.) (2025). 804–822.
• Heat Storage Pattern Linked to the Atlantic Meridional Overturning Circulation Slowdown. Ren, Qiuping; Li, Yuanlong; Hu, Shineng; Xie, Shang-Ping; Lyu, Yilong; Wang, Fan (2025). 52(13) e2025GL116801.

  Abstract The Atlantic Ocean has absorbed ∼30% of Earth's excess heat under anthropogenic warming and witnessed enhanced warming since the mid-20th century. Yet, mechanisms governing the Atlantic warming, particularly the role of Atlantic Meridional Overturning Circulation (AMOC), remain uncertain. Through ocean-only and coupled model experiments, we confirm the key role of the weakened AMOC in the enhanced Atlantic heat storage. Physically, the reduced poleward heat transport of AMOC causes an additional heat pile-up in the 15°S–45°N regions with a lag time of ∼10 years. Based on this dynamical linkage, we propose that the regional enhanced heat storage in the 15°S–45°N Atlantic relative to the global average serves as a fingerprint for the long-term AMOC change. The observed heat storage indicates an overall AMOC slowdown by only 1.31 ± 0.39 Sv since the 1950s. Considering the pronounced natural variability, this weak anthropogenic AMOC slowdown probably has not emerged yet.
• VIA-VR: A Platform to Streamline the Development of Virtual Reality Serious Games for Healthcare. Truman, Samuel; Von Mammen, Sebastian (2025). 463–468.
• VIA-VR: A Platform to Streamline the Development of Virtual Reality Serious Games for Healthcare. Truman, Samuel; Von Mammen, Sebastian (2025). 463–468.
• Aggregation-Free Uncertainty Estimation for CTC-Based Automatic Speech Recognition. Rumberg, Lars; Gebauer, Christopher; Ostermann, Jörn (2025).
• A Survey of Non-Learning-Based Abstractions for Sequential Decision-Making. Schmöcker, Robin; Dockhorn, Alexander (2025). 13 100808–100830.
• Cascade - A sequential ensemble method for continuous control tasks. Schmöcker, Robin; Dockhorn, Alexander (2025).
• Cell Tracking according to Biological Needs - Strong Mitosis-aware Multi-Hypothesis Tracker with Aleatoric Uncertainty. Kaiser, Timo; Schier, Maximilian; Rosenhahn, Bodo (2025).
• Pruning by Block Benefit: Exploring the Properties of Vision Transformer Blocks during Domain Adaptation. Glandorf, Patrick; Bodo, Rosenhahn (2025).
• VaMEx3-MarsSymphony: Technology Demonstration for Martian exploration swarm robotics. Riegler, Clemens; Kayal, Hakan; Maurer, Andreas; Mutter, Julian; Neuhaus, Lennart; Stadler, Joshua (2025).
• The Resound Sphere: Co-Exploring Alternatives for Community Remote Practice of Faith. Wolf, Sara; Chatting, David; Morris, Ben; Claisse, Caro; Durrant, Abigail C. (2025).
• The Resound Sphere: Co-Exploring Alternatives for Community Remote Practice of Faith. Wolf, Sara; Chatting, David; Morris, Ben; Claisse, Caro; Durrant, Abigail C. (2025).
• Assessment of Abrupt Shifts in CMIP6 Models Using Edge Detection. Terpstra, Sjoerd; Falkena, Swinda K. J.; Bastiaansen, Robbin; Bathiany, Sebastian; Dijkstra, Henk A.; von der Heydt, Anna S. (2025). 6(3) e2025AV001698.

  Abstract Past research has shown that multiple climate subsystems might undergo abrupt shifts, such as the Arctic Winter sea ice or the Amazon rainforest, but there are large uncertainties regarding their timing and spatial extent. In this study we investigated when and where abrupt shifts occur in the latest generation of earth system models (CMIP6) under a scenario of 1% annual increase in CO2. We considered 82 ocean, atmosphere, and land variables across 57 models. We used a Canny edge detection method to identify abrupt shifts occurring on yearly to decadal timescales, and performed a connected component analysis to quantify the spatial extent of these shifts. The systems analyzed include the North Atlantic subpolar gyre, Tibetan Plateau, land permafrost, Amazon rainforest, Antarctic sea ice, monsoon systems, Arctic summer sea ice, Arctic winter sea ice, and Barents sea ice. Except for the monsoon systems, we found abrupt shifts in all of these across multiple models. Despite large inter-model variations, higher levels of global warming consistently increase the risk of abrupt shifts in CMIP6 models. At a global warming of 1.5°C, six out of 10 studied climate subsystems already show large-scale abrupt shifts across multiple models.
• VR Cybersickness Classification using Machine Learning Models on Open-Access EEG Datasets from the Human Vestibular Network. Li, Gang; Byeon, Hae-Rin; Cho, Sung-Bae; Pollick, Frank E. (2025). 171–175.
• Low-Constraint Ray Optimization for Photogrammetric Shallow Water Bathymetry. Liebender, C.; Meyer, P.; Bleier, M.; Nüchter, A. in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-2/W10-2025 (2025). 163–168.

  This paper presents a raytracing-based approach for estimating the depth of shallow water bodies. Based on a calibrated, multi-view camera setup above the water surface, we find correspondences that lie below the surface in pairs of two views. We trace rays from each camera to each triangulated correspondence, as if no interface is present in the scene. Using snell’s law, we then compute refracted rays to optimize an objective function with a theoretical optimum as the Hesse normal form of the water surface. The challenge of our work is to keep the number of constraints in our mathematical model as low as possible. For a practical evaluation, we record images with two different setups: a laboratory setting with a box filled with water at a depth of 14.5 cm and a water roll-of container at 2.2 m, and use both fiducial markers as well as computed features as correspondences. Our results show that with a well-setup optimizer, our method converges towards the true water plane and is usable to estimate the depth of our setups.
• Robustness of Question Answering Systems in the Biomedical Domain: a study of the BioASQ dataset. Reeves, Andrew; Dong, Hang (2025). 247–252.

  Robustness is a critical consideration when integrating artificial intelligence (AI) systems into decision-making processes. This concern is particularly relevant for generative AI systems, which are designed to consistently produce convincing outputs but can be prone to hallucinations, risking overconfidence in their outputs. This paper investigates the performance of fine-tuning and retrieval augmented generation (RAG) under external data quality perturbations, including typographical errors and factual inaccuracies. Results from experiments using the BioASQ Task 12b question answering dataset and PubMed articles showed nuanced trade-offs, with either RAG or fine-tuning performing better for different scenarios. Furthermore, an analysis of LLMs’ self-reported confidence scores indicated a tendency toward overconfidence, particularly in the presence of inconsistent or erroneous context data. A novel mitigation strategy, leveraging an LLM for data quality error correction was evaluated, but the results demonstrated limited effectiveness, highlighting the need for more advanced correction techniques.
• Steamboat: Attention-Based Multiscale Delineation of Cellular Interactions in Tissues. Liang, Shaoheng; Tang, Junjie; Wang, Guanghan; Ma, Jian in Lecture Notes in Computer Science, S. Sankararaman (ed.) (2025). (Vol. 15647) 432–436.
• Unified Integration of Spatial Transcriptomics Across Platforms. Haber, Ellie; Deshpande, Ajinkya; Ma, Jian; Krieger, Spencer in Lecture Notes in Computer Science, S. Sankararaman (ed.) (2025). (Vol. 15647) 371–375.
• Applying Cfahp to Explore the Key Models of Semiconductor Pre-Sales. Kao, Fei-Hon; Hsieh, Chia-Hsiang; Pei, Wen in Frontiers in Artificial Intelligence and Applications, R. Mizoguchi, P. Dillenbourg, Z. Zhu (eds.) (2025). (Vol. 151) 149–156.
• Transparent Ransomware Detection in Bitcoin Transactions: Leveraging Machine Learning and Explainable AI. Mohammed, Roshan; Rezvy, Shahadate (2024). 1–5.
• News Ninja: Gamified Annotation of Linguistic Bias in Online News. Hinterreiter, Smi; Spinde, Timo; Oberdörfer, Sebastian; Echizen, Isao; Latoschik, Marc Erich (2024). 8(CHI PLAY, Article 327)

  Recent research shows that visualizing linguistic bias mitigates its negative effects. However, reliable automatic detection methods to generate such visualizations require costly, knowledge-intensive training data. To facilitate data collection for media bias datasets, we present News Ninja, a game employing data-collecting game mechanics to generate a crowdsourced dataset. Before annotating sentences, players are educated on media bias via a tutorial. Our findings show that datasets gathered with crowdsourced workers trained on News Ninja can reach significantly higher inter-annotator agreements than expert and crowdsourced datasets with similar data quality. As News Ninja encourages continuous play, it allows datasets to adapt to the reception and contextualization of news over time, presenting a promising strategy to reduce data collection expenses, educate players, and promote long-term bias mitigation.
• Exploring the Feasibility of Virtual Reality in Post-Stroke Rehabilitation: Medical Perspectives on Motion Health VR. Castillo, Julian Felipe Villada; López, Jose Fernando; Muñoz, John Edison; Gallo, Oscar Henao in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 144–158.
• A Methodological Overview About Hand Tracking and Cognitive Influences in Virtual Reality. Madrigal, Omar Correa; Muhamethanov, Ilnur Radikovich; Vladimirovna, Vlada Kugurakova in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 14–24.
• Characterization of Interactive Multimedia Experiences in Inclusive School Contexts Considering Learning Analytics. Beltrán, Paola A. Castillo; Alegría, Andrés Fernando Solano; Ayala, Carlos A. Peláez; Munar, Leonardo Saavedra; la Rosa Alzate, Emma A. De in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 67–79.
• Evaluation Heuristics to Improve Usability in Ecommerce Platforms. Muñoz, Alejandra Yicel Vargas; Collazos, César A.; Granollers, Toni in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 104–119.
• WiFi Channel State Information-based Motion Detection Across Time-Domain. Wang, Qinhong; Wu, Zhenhua (2024). 1–5.
• Real-Time Hardware Emulation for Spatial-Temporal Correlated Multiple Channels. Yang, Ling; Fang, Sheng; Zheng, Yongfeng; Xie, Yuetian; Ding, Yuan; Wang, Longjun; Hua, Boyu; Zhu, Qiuming (2024). 1441–1445.
• Performance Evaluation of Novel Photon-Counting Micro-CT System for Preclinical Spectral Imaging and its Applications. Xue, Mengjia; Liu, Qian; Xie, Tianwu (2024). 1–6.
• Exploring Accessibility: The First Interaction of Visually Impaired Users with the UNAD Virtual Campus. Puerto, Lina Mercedes Lozano; M, Gustavo E. Constaín; Barbero, Jonathan Chacón in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 129–143.
• Writing UX Requirements in Acceptance Criteria: A Case Study in Startups. Souza, Jonathan; Zaina, Luciana in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 340–353.
• Measure of Coolness on the Blind User Experience. de Sousa Santana, Rosangela Divina; Ferreira, Deller James; de Oliveira Berreta, Luciana in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 228–241.
• SME Users in Industry 4.0. Study of the Metalworking Industry in Argentina. Mon, Alicia; Giorgio, Horacio René Del; Roark, Geraldina Yesica; Sueldo, Carolina Saavedra; Colo, Ivo Perez; Paula, Mariano De in Communications in Computer and Information Science, V. A. Delgado, P. H. Ruiz, C. A. M. Escobar (eds.) (2024). (Vol. 2332) 281–295.
• VNExpirationDate: A Novel Expiration Date Dataset and a Robust Framework for Expiration Date Recognition on Complex Packaging in Vietnam. Tien, Le-Thanh; Hien, Hua-Nguyen-Minh; Ny, Hoang-Thi-Xuan; An, Nguyen-Huu; Quang, Dung-Cam (2024). 388–392.
• Enhancing URL Classification with Hyperparameter-Tuned Convolutional Neural Networks. Tran, Thuy Thi; Phan, Nghia Quoc; Huynh, Hiep Xuan (2024). 409–413.
• A Novel Method for Wearable Activity Recognition with Feature Evolvable Streams. Wang, Yixiao; Hu, Chunyu; Liu, Hong; Lyu, Lei; Yuan, Lin in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, A. B. Zaslavsky, Z. Ning, V. Kalogeraki, D. Georgakopoulos, P. K. Chrysanthis (eds.) (2023). (Vol. 593) 392–407.
• Secure Cloud Storage System for Digital Evidence. Malina, Lukas; Muzikant, Petr; Nohava, Martin; Hajny, Jan; Dufka, Antonín; Svenda, Petr; Stupka, Václav (2023). 134–139.
• Refined Fuzzy Profile Matching. Rácz, Gábor; Sali, Attila; Schewe, Klaus-Dieter (2023). 26(2) 243–266.
• FieldHAR: A Fully Integrated End-to-End RTL Framework for Human Activity Recognition with Neural Networks from Heterogeneous Sensors. Liu, Mengxi; Zhou, Bo; Zhao, Zimin; Hong, Hyeonseok; Kim, Hyun; Suh, Sungho; Rey, Vítor Fortes; Lukowicz, Paul (2023). 110–118.
• Random Location Poisoning Backdoor Attack Against Automatic Modulation Classification in Wireless Networks. Li, Zixin; Jiang, Hang; Zhang, Sicheng; Xiang, Wei; Lin, Yun (2023). 1–6.
• Multi-antenna covert communications in random wireless networks with full-duplex relay. Liu, Yan; Wu, Huihui; Shen, Yulong; Jiang, Xiaohong J. Hong, M. Bures, J. W. Park, T. Cerný (eds.) (2022). 1960–1966.
• A Gamified Approach To Automatically Detect Biased Wording And Train Critical Reading. Hinterreiter, Smi (2021).

  Biased media has an effect on the public perception of occurring events. By altering word choice, outlets can alter beliefs and views. A gold standard data set is needed to train sufficient classifiers that detect biased wording. This work aims to develop a game that trains players to read news critically while collecting their annotations. The vision is to tackle the complex problem of media bias detection with a very scalable, high quality, and gold standard data set to overcome the drawbacks of current models in the area.
• Game Theory Based Power Allocation Method for Inter-satellite Links in LEO/MEO Two-layered Satellite Networks. Zhang, Huaming; Li, Qiang; Zhang, Yijin; Li, Xun (2021). 398–403.
• Multi-modal Medical Image Fusion Based on GAN and the Shift-Invariant Shearlet Transform. Wang, Lei; Chang, Chunhong; Hao, Benli; Liu, Chunxiang T. Park, Y.-R. Cho, X. Hu, I. Yoo, H. G. Woo, J. Wang, J. C. Facelli, S. Nam, M. Kang (eds.) (2020). 2538–2543.
• Execution Time Prediction for Apache Spark. Gao, Zhipeng; Wang, Ting; Wang, Qian; Yang, Yang (2018). 47–51.
• Sorption properties of sodium bicarbonate. Walawska, Barbara; Szymanek, Arkadiusz; Pajdak, Anna; Nowak, Marzena; Hala, Bożena (2012). (Vol. 66) 1169–1176.
• Patterns for configuration requirements of Software-as-a-Service. Shim, Jaekeun; Han, Jongdae; Kim, Jindae; Lee, Byungjeong; Oh, Jaewon; Wu, Chisu W. C. Chu, W. E. Wong, M. J. Palakal, C.-C. Hung (eds.) (2011). 155–161.
• Service Forest: Enabling Dynamic Service Composition in Mobile Ad Hoc Networks. Huang, Jun; Bai, Yuebin; Zhang, Zhiyuan; Kong, Jing; Qian, Depei (2007). 174–177.
• Effects of capillary condensation on the caking of bulk sucrose. Billings, S.W.; Bronlund, J.E.; Paterson, A.H.J. (2006). 77(4) 887–895.

  Caking in sucrose is a major problem for the sugar industry, especially during transportation. Liquid bridging in sucrose is the first step towards caking. This paper demonstrates, by measuring the strength of the liquid bridges and then the strength of the subsequently formed solid bridges under different water activity conditions that the critical water activity for initiation of caking is about 0.8. The identification of this point allows the conditions under which bulk sucrose is stored and transported to be specified to prevent the occurrence of water activities going above this critical level to eliminate caking.
• Deriving Relation Keys from XML Keys. Wang, Qing; Wu, Hongwei; Xiao, Jianchang; Zhou, Aoying; Zhou, Junmei in CRPIT, K.-D. Schewe, X. Zhou (eds.) (2003). (Vol. 17) 227–235.
• Water activity in concentrated sucrose solutions and its consequences for the availability of water in the film of syrup surrounding the sugar crystal. Starzak, Maciej; Mathlouthi, Mohamed (2002). 127 175–185.

  A thermodynamically rigorous chemical model of water activity in the sucrose-water system is proposed. The model covers practically the entire composition range including very high sugar concentrations. It employs the concept of the semi-ideal solution according to which all the departures from ideal behavior are attributed to chemical reactions occurring in the system, while physical interactions are neglected. The model accounts for sucrose hydration and clustering as well as water association. All the reactions are assumed to attain chemical equilibrium. Two different mechanisms of sucrose hydration (linear and bridging) are included. The concept of independent binding sites, originally proposed by Schönert (1986), has been extended to describe both the probability of sucrose/water and sucrose/sucrose interactions. An equilibrium "mixture" model of liquid water, involving the formation of simple water clusters, has been incorporated in order to account for the water/water interactions. Experimental data (vapor pressure, boiling point elevation, equilibrium relative humidity, and heat of dilution) from selected literature sources have been used to validate the model and estimate its parameters. The proposed model can be used as a mathematical tool in solving various practical problems encountered in the sugar and food industry, such as the behavior of crystalline sugar during conditioning and storage, stickiness, re-crystallization of amorphous sugar, its stability in foods and pharmaceuticals. It is postulated that the driving force for migration of water from sugar crystals should be defined in terms of the water activity rather than the nominal content of water in solution. Diffusion processes occurring in the film of syrup surrounding the sugar crystal are briefly outlined. The key role of sucrose hydration and clustering in establishing the driving force of monomeric water in the syrup film is discussed in detail.
• The occult underground Webb, James (1988). Open Court, LaSalle, Ill.