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)

• 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.
• Cell Tracking according to Biological Needs - Strong Mitosis-aware Multi-Hypothesis Tracker with Aleatoric Uncertainty. Kaiser, Timo; Schier, Maximilian; Rosenhahn, Bodo (2025).
• Artificial Intelligence and Machine Learning Based Plant Monitoring. Rampure, Shrutika C; P, Bhavyashree S; T, Rakshitha B (2025).
• 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.
• 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.
• 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.
• 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.
• 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).
• 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.
• VaMEx3-MarsSymphony: Technology Demonstration for Martian exploration swarm robotics. Riegler, Clemens; Kayal, Hakan; Maurer, Andreas; Mutter, Julian; Neuhaus, Lennart; Stadler, Joshua (2025).
• Pruning by Block Benefit: Exploring the Properties of Vision Transformer Blocks during Domain Adaptation. Glandorf, Patrick; Bodo, Rosenhahn (2025).
• Time-critical and confidence-based abstraction dropping methods. Schmöcker, Lennart Kampmann Robin (2025).
• 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.
• Cascade - A sequential ensemble method for continuous control tasks. Schmöcker, Robin; Dockhorn, Alexander (2025).
• A Survey of Non-Learning-Based Abstractions for Sequential Decision-Making. Schmöcker, Robin; Dockhorn, Alexander (2025). 13 100808–100830.
• Aggregation-Free Uncertainty Estimation for CTC-Based Automatic Speech Recognition. Rumberg, Lars; Gebauer, Christopher; Ostermann, Jörn (2025).
• 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.
• 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.
• 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.
• 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.
• 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.
• Protection Against Poisoning Attacks on Federated Learning-Based Spectrum Sensing \($\$\) \($ \lg $\)\\($ $\). Wasilewska, Malgorzata; Bogucka, Hanna (2025).
• 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.
• 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.
• 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.
• The evolution of bone-eating worm diversity in the Upper Cretaceous Chalk Group of the United Kingdom. Jamison-Todd, Sarah; Witts, James D.; Jones, Marc E. H.; Tangunan, Deborah; Chandler, Kim; Bown, Paul; Twitchett, Richard J. (2025). 20(4) 1–20.

  The bone-eating worm Osedax is today a member of the highly adapted invertebrate assemblages associated with whale carcasses on the ocean floor. The worm has also been found in a variety of other vertebrates in marine environments. Osedax borings are represented by the trace fossil Osspecus, which has been identified in fossil whales and marine reptiles, with the earliest occurrence in the Albian. In studies of present-day whale bones it has been found that individual species of Osedax create distinct boring morphologies. The diversity of boring geometries therefore provides a proxy for species diversity that can be applied to the fossil record to better understand the diversity, ecology, and evolution of extinct Osedax species. We examined marine reptile fossils from the Upper Cretaceous Chalk Group of the United Kingdom, and found five previously undocumented boring morphologies. These results, coupled with a re-examination of previous records of Osspecus, led to the naming of seven new ichnospecies. Using nannofossil biostratigraphy from the chalk, we constrained the ages of these occurrences and found a high species diversity in the early Late Cretaceous, indicating either a rapid diversification or an earlier origin for Osedax than previously estimated. Furthermore, we recognise five Cretaceous ichnospecies that are also found in the Cenozoic, three of which are also found in present-day whale bones.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• A Tutorial on Data-Driven Quality of Experience Modeling with Explainable Artificial Intelligence. Wehner, Nikolas; Seufert, Anika; Hoßfeld, Tobias; Seufert, Michael (2025).
• 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.
• Jahresbericht 2024. van Ackeren, Janine (2025). 90–92.
• Jahresbericht 2024. van Ackeren, Janine (2025). 90–92.
• Sibai: A Few-Shot Meta-Classifier for Poisoning Detection in Federated Learning. Götz, Melanie; Krauß, Torsten; Dmitrienko, Alexandra (2025).
• TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts. Krauß, Torsten; Dashtbani, Hamid; Dmitrienko, Alexandra (2025).
• Security and Privacy of Current and Emerging IoT Devices and Systems (Dagstuhl Seminar 2431). Crispo, Bruno; Dmitrienko, Alexandra; Tsudik, Gene; Xu, Wenyuan; Sendner, Christoph (2025).
• A Cluster-Based Trusted Secure Multipath Routing Protocol for Mobile Ad Hoc Networks. Bartwal, Himanshu; Sivaraman, Himani; Kumar, Jogendra N. Meghanathan (ed.) (2025). (Vol. 17) 89–109.

  Mobile Ad Hoc Network (MANET) is a self-organizing and flexible system. MANET systems manage sensitive data from many distinct applications in various domains. Its dynamic nature increases its vulnerability to numerous types of security threats. Many of the present approaches using indirect approaches provide false approximations of trust degrees. It is significantly required a good routing system that meets Quality of Service (QoS) standards and enhances network performance. In this paper purposed cluster-based trustworthy safe multipath routing (CTSMP-Routing) for mobile ad hoc networks (MANETs). Load balancing challenge is addressed by using a modified proportional topology optimization (MPTO) approach using geographical data related to network nodes. The Enhanced Seeker Search Optimization (ESSO) approach is used to compute trust degrees after the clustering phase considering numerous network constraints including node mobility, received signal strength, energy consumption, and cooperation rate. Assumed to be the service node, the node showing the highest degree of trust manages inter-cluster routing. We have developed a hybrid soft computing approach termed the multi-layer deep recurrent neural network (ML-DRNN) to enhance the optimal path-finding process. This method selects, among many routes between source and destination nodes, the best one quickly. The outcomes of this paper demonstrate that CTSMP-Routing provides effective protection against several attack paths within the MANET environment and displays better performance in regard to quality of service (QoS) requirements.
• A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge. Ma, Le; Zhang, Ran; Han, Yikun; Yu, Shirui; Wang, Zaitian; Ning, Zhiyuan; Zhang, Jinghan; Xu, Ping; Li, Pengjiang; Ju, Wei; Chen, Chong; Wang, Dongjie; Liu, Kunpeng; Wang, Pengyang; Wang, Pengfei; Fu, Yanjie; Liu, Chunjiang; Zhou, Yuanchun; Lu, Chang-Tien (2025).
• 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.
• 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.
• 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.
• 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.
• WiFi Channel State Information-based Motion Detection Across Time-Domain. Wang, Qinhong; Wu, Zhenhua (2024). 1–5.
• Transparent Ransomware Detection in Bitcoin Transactions: Leveraging Machine Learning and Explainable AI. Mohammed, Roshan; Rezvy, Shahadate (2024). 1–5.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Enhancing URL Classification with Hyperparameter-Tuned Convolutional Neural Networks. Tran, Thuy Thi; Phan, Nghia Quoc; Huynh, Hiep Xuan (2024). 409–413.
• The Optically Thick Rotating Magnetic Wind from a Massive White Dwarf Merger Product. II. Axisymmetric Magnetohydrodynamic Simulations. Zhong, Yici; Kashiyama, Kazumi; Takasao, Shinsuke; Shigeyama, Toshikazu; Fujisawa, Kotaro (2024). 963(1) 26.

  We numerically construct a series of axisymmetric rotating magnetic wind solutions, aiming at exploring the observation properties of massive white dwarf (WD) merger remnants with a strong magnetic field, a fast spin, and an intense mass loss, as inferred for WD J005311. We investigate the magnetospheric structure and the resultant spin-down torque exerted to the merger remnant with respect to the surface magnetic flux Φ * , spin angular frequency Ω * and the mass-loss rate M ̇ . We confirm that the wind properties for σ ≡ Φ * 2 Ω * 2 / M ̇ v esc 3 ≳ 1 significantly deviate from those of the spherical Parker wind, where v esc is the escape velocity at stellar surface. For such a rotating magnetic wind sequence, we find (i) a quasiperiodic mass eruption triggered by magnetic reconnection along with the equatorial plane and (ii) a scaling relation for the spin-down torque T ≈ ( 1 / 2 ) × M ̇ Ω * R * 2 σ 1 / 4 . We apply our results to discuss the spin-down evolution and wind anisotropy of massive WD merger remnants, the latter of which could be probed by a successive observation of WD J005311 using Chandra.
• 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.
• Can Large Language Models Understand Symbolic Graphics Programs?. Qiu, Zeju; Liu, Weiyang; Feng, Haiwen; Liu, Zhen; Xiao, Tim Z.; Collins, Katherine M.; Tenenbaum, Joshua B.; Weller, Adrian; Black, Michael J.; Schölkopf, Bernhard (2024).

  Assessing the capabilities of large language models (LLMs) is often challenging, in part, because it is hard to find tasks to which they have not been exposed during training. We take one step to address this challenge by turning to a new task: focusing on symbolic graphics programs, which are a popular representation for graphics content that procedurally generates visual data. LLMs have shown exciting promise towards program synthesis, but do they understand symbolic graphics programs? Unlike conventional programs, symbolic graphics programs can be translated to graphics content. Here, we characterize an LLM's understanding of symbolic programs in terms of their ability to answer questions related to the graphics content. This task is challenging as the questions are difficult to answer from the symbolic programs alone -- yet, they would be easy to answer from the corresponding graphics content as we verify through a human experiment. To understand symbolic programs, LLMs may need to possess the ability to imagine how the corresponding graphics content would look without directly accessing the rendered visual content. We use this task to evaluate LLMs by creating a large benchmark for the semantic understanding of symbolic graphics programs. This benchmark is built via program-graphics correspondence, hence requiring minimal human efforts. We evaluate current LLMs on our benchmark to elucidate a preliminary assessment of their ability to reason about visual scenes from programs. We find that this task distinguishes existing LLMs and models considered good at reasoning perform better. Lastly, we introduce Symbolic Instruction Tuning (SIT) to improve this ability. Specifically, we query GPT4-o with questions and images generated by symbolic programs. Such data are then used to finetune an LLM. We also find that SIT data can improve the general instruction following ability of LLMs.
• Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models. Nezhurina, Marianna; Cipolina-Kun, Lucia; Cherti, Mehdi; Jitsev, Jenia (2024, June).

  Large Language Models (LLMs) are often described as being instances of foundation models - that is, models that transfer strongly across various tasks and conditions in few-show or zero-shot manner, while exhibiting scaling laws that predict function improvement when increasing the pre-training scale. These claims of excelling in different functions and tasks rely on measurements taken across various sets of standardized benchmarks showing high scores for such models. We demonstrate here a dramatic breakdown of function and reasoning capabilities of state-of-the-art models trained at the largest available scales which claim strong function, using a simple, short, conventional common sense problem formulated in concise natural language, easily solvable by humans. The breakdown is dramatic, as models also express strong overconfidence in their wrong solutions, while providing often non-sensical "reasoning"-like explanations akin to confabulations to justify and backup the validity of their clearly failed responses, making them sound plausible. Various standard interventions in an attempt to get the right solution, like various type of enhanced prompting, or urging the models to reconsider the wrong solutions again by multi step re-evaluation, fail. We take these initial observations to the scientific and technological community to stimulate urgent re-assessment of the claimed capabilities of current generation of LLMs, Such re-assessment also requires common action to create standardized benchmarks that would allow proper detection of such basic reasoning deficits that obviously manage to remain undiscovered by current state-of-the-art evaluation procedures and benchmarks. Code for reproducing experiments in the paper and raw experiments data can be found at https://github.com/LAION-AI/AIW
• 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.
• Outflows from the Youngest Stars are Mostly Molecular. Ray, T P; McCaughrean, M J; Caratti o Garatti, A; Kavanagh, P J; Justtanont, K; van Dishoeck, E F; Reitsma, M; Beuther, H; Francis, L; Gieser, C; Klaassen, P; Perotti, G; Tychoniec, L; van Gelder, M; Colina, L; Greve, Th R; Güdel, M; Henning, Th; Lagage, P O; Östlin, G; Vandenbussche, B; Waelkens, C; Wright, G (2023).

  The formation of stars and planets is accompanied not only by the build-up of matter, i.e., accretion, but also by its expulsion in the form of highly supersonic jets that can stretch for several parsecs1,2. As accretion and jet activity are correlated and because young stars acquire most of their mass rapidly early on, the most powerful jets are associated with the youngest protostars3. This period, however, coincides with the time when the protostar and its surroundings are hidden behind many magnitudes of visual extinction. Millimetre interferometers can probe this stage but only for the coolest components3. No information is provided on the hottest (þinspace\textgreaterþinspace1000 K) constituents of the jet, i. e. the atomic, ionized, and high temperature molecular gas that are thought to make up the jet's backbone. Can we detect such a high temperature spine and what is it made up of? Here we report near-infrared JWST observations of Herbig-Haro 211, an outflow from an analogue of our Sun when it was at most a few times 104 years old. These reveal copious emission from hot molecules explaining the origin of the so-called ``Green Fuzzies''4--7 discovered nearly two decades ago by the Spitzer Space Telescope8. This outflow is found to be propagating slowly in comparison to its more evolved counterparts and, surprisingly, almost no trace of atomic or ionized emission is seen suggesting its spine is almost purely molecular.
• Are Emergent Abilities of Large Language Models a Mirage?. Schaeffer, Rylan; Miranda, Brando; Koyejo, Sanmi (2023). 55565–55581.

  Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability, appearing at seemingly unforeseeable model scales. Here, we present an alternative explanation for emergent abilities: that for a particular task and model family, when analyzing fixed model outputs, emergent abilities appear due to the researcher's choice of metric rather than due to fundamental changes in model behavior with scale. Specifically, nonlinear or discontinuous metrics produce apparent emergent abilities, whereas linear or continuous metrics produce smooth, continuous predictable changes in model performance. We present our alternative explanation in a simple mathematical model, then test it in three complementary ways: we (1) make, test and confirm three predictions on the effect of metric choice using the InstructGPT/GPT-3 family on tasks with claimed emergent abilities; (2) make, test and confirm two predictions about metric choices in a meta-analysis of emergent abilities on BIG-Bench; and (3) show to choose metrics to produce never-before-seen seemingly emergent abilities in multiple vision tasks across diverse deep networks. Via all three analyses, we provide evidence that alleged emergent abilities evaporate with different metrics or with better statistics, and may not be a fundamental property of scaling AI models.
• Refined Fuzzy Profile Matching. Rácz, Gábor; Sali, Attila; Schewe, Klaus-Dieter (2023). 26(2) 243–266.
• 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.
• Can Transformers Learn to Solve Problems Recursively?. Zhang, Shizhuo Dylan; Tigges, Curt; Biderman, Stella; Raginsky, Maxim; Ringer, Talia (2023).

  Neural networks have in recent years shown promise for helping software engineers write programs and even formally verify them. While semantic information plays a crucial part in these processes, it remains unclear to what degree popular neural architectures like transformers are capable of modeling that information. This paper examines the behavior of neural networks learning algorithms relevant to programs and formal verification proofs through the lens of mechanistic interpretability, focusing in particular on structural recursion. Structural recursion is at the heart of tasks on which symbolic tools currently outperform neural models, like inferring semantic relations between datatypes and emulating program behavior. We evaluate the ability of transformer models to learn to emulate the behavior of structurally recursive functions from input-output examples. Our evaluation includes empirical and conceptual analyses of the limitations and capabilities of transformer models in approximating these functions, as well as reconstructions of the ``shortcut" algorithms the model learns. By reconstructing these algorithms, we are able to correctly predict 91 percent of failure cases for one of the approximated functions. Our work provides a new foundation for understanding the behavior of neural networks that fail to solve the very tasks they are trained for.
• 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.
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. Srivastava, Aarohi; Rastogi, Abhinav; Rao, Abhishek; Shoeb, Abu Awal Md; Abid, Abubakar; Fisch, Adam; Brown, Adam R; Santoro, Adam; Gupta, Aditya; Garriga-Alonso, Adri�; Kluska, Agnieszka; Lewkowycz, Aitor; Agarwal, Akshat; Power, Alethea; Ray, Alex; Warstadt, Alex; Kocurek, Alexander W; Safaya, Ali; Tazarv, Ali; Xiang, Alice; Parrish, Alicia; Nie, Allen; Hussain, Aman; Askell, Amanda; Dsouza, Amanda; Slone, Ambrose; Rahane, Ameet; Iyer, Anantharaman S; Andreassen, Anders; Madotto, Andrea; Santilli, Andrea; Stuhlmüller, Andreas; Dai, Andrew; La, Andrew; Lampinen, Andrew; Zou, Andy; Jiang, Angela; Chen, Angelica; Vuong, Anh; Gupta, Animesh; Gottardi, Anna; Norelli, Antonio; Venkatesh, Anu; Gholamidavoodi, Arash; Tabassum, Arfa; Menezes, Arul; Kirubarajan, Arun; Mullokandov, Asher; Sabharwal, Ashish; Herrick, Austin; Efrat, Avia; Erdem, Aykut; Karakaş, Ayla; Roberts, B Ryan; Loe, Bao Sheng; Zoph, Barret; Bojanowski, Bartłomiej; Özyurt, Batuhan; Hedayatnia, Behnam; Neyshabur, Behnam; Inden, Benjamin; Stein, Benno; Ekmekci, Berk; Lin, Bill Yuchen; Howald, Blake; Orinion, Bryan; Diao, Cameron; Dour, Cameron; Stinson, Catherine; Argueta, Cedrick; Ramírez, César Ferri; Singh, Chandan; Rathkopf, Charles; Meng, Chenlin; Baral, Chitta; Wu, Chiyu; Callison-Burch, Chris; Waites, Chris; Voigt, Christian; Manning, Christopher D; Potts, Christopher; Ramirez, Cindy; Rivera, Clara E; Siro, Clemencia; Raffel, Colin; Ashcraft, Courtney; Garbacea, Cristina; Sileo, Damien; Garrette, Dan; Hendrycks, Dan; Kilman, Dan; Roth, Dan; Freeman, Daniel; Khashabi, Daniel; Levy, Daniel; González, Daniel Moseguí; Perszyk, Danielle; Hernandez, Danny; Chen, Danqi; Ippolito, Daphne; Gilboa, Dar; Dohan, David; Drakard, David; Jurgens, David; Datta, Debajyoti; Ganguli, Deep; Emelin, Denis; Kleyko, Denis; Yuret, Deniz; Chen, Derek; Tam, Derek; Hupkes, Dieuwke; Misra, Diganta; Buzan, Dilyar; Mollo, Dimitri Coelho; Yang, Diyi; Lee, Dong-Ho; Schrader, Dylan; Shutova, Ekaterina; Cubuk, Ekin Dogus; Segal, Elad; Hagerman, Eleanor; Barnes, Elizabeth; Donoway, Elizabeth; Pavlick, Ellie; Rodola, Emanuele; Lam, Emma; Chu, Eric; Tang, Eric; Erdem, Erkut; Chang, Ernie; Chi, Ethan A; Dyer, Ethan; Jerzak, Ethan; Kim, Ethan; Manyasi, Eunice Engefu; Zheltonozhskii, Evgenii; Xia, Fanyue; Siar, Fatemeh; Martínez-Plumed, Fernando; Happé, Francesca; Chollet, Francois; Rong, Frieda; Mishra, Gaurav; Winata, Genta Indra; de Melo, Gerard; Kruszewski, Germán; Parascandolo, Giambattista; Mariani, Giorgio; Wang, Gloria; Jaimovitch-López, Gonzalo; Betz, Gregor; Gur-Ari, Guy; Galijasevic, Hana; Kim, Hannah; Rashkin, Hannah; Hajishirzi, Hannaneh; Mehta, Harsh; Bogar, Hayden; Shevlin, Henry; Schütze, Hinrich; Yakura, Hiromu; Zhang, Hongming; Wong, Hugh Mee; Ng, Ian; Noble, Isaac; Jumelet, Jaap; Geissinger, Jack; Kernion, Jackson; Hilton, Jacob; Lee, Jaehoon; Fisac, Jaime Fernández; Simon, James B; Koppel, James; Zheng, James; Zou, James; Kocoń, Jan; Thompson, Jana; Wingfield, Janelle; Kaplan, Jared; Radom, Jarema; Sohl-Dickstein, Jascha; Phang, Jason; Wei, Jason; Yosinski, Jason; Novikova, Jekaterina; Bosscher, Jelle; Marsh, Jennifer; Kim, Jeremy; Taal, Jeroen; Engel, Jesse; Alabi, Jesujoba; Xu, Jiacheng; Song, Jiaming; Tang, Jillian; Waweru, Joan; Burden, John; Miller, John; Balis, John U; Batchelder, Jonathan; Berant, Jonathan; Frohberg, Jörg; Rozen, Jos; Hernandez-Orallo, Jose; Boudeman, Joseph; Guerr, Joseph; Jones, Joseph; Tenenbaum, Joshua B; Rule, Joshua S; Chua, Joyce; Kanclerz, Kamil; Livescu, Karen; Krauth, Karl; Gopalakrishnan, Karthik; Ignatyeva, Katerina; Markert, Katja; Dhole, Kaustubh D; Gimpel, Kevin; Omondi, Kevin; Mathewson, Kory; Chiafullo, Kristen; Shkaruta, Ksenia; Shridhar, Kumar; McDonell, Kyle; Richardson, Kyle; Reynolds, Laria; Gao, Leo; Zhang, Li; Dugan, Liam; Qin, Lianhui; Contreras-Ochando, Lidia; Morency, Louis-Philippe; Moschella, Luca; Lam, Lucas; Noble, Lucy; Schmidt, Ludwig; He, Luheng; Colón, Luis Oliveros; Metz, Luke; Şenel, Lütfi Kerem; Bosma, Maarten; Sap, Maarten; ter Hoeve, Maartje; Farooqi, Maheen; Faruqui, Manaal; Mazeika, Mantas; Baturan, Marco; Marelli, Marco; Maru, Marco; Quintana, Maria Jose Ramírez; Tolkiehn, Marie; Giulianelli, Mario; Lewis, Martha; Potthast, Martin; Leavitt, Matthew L; Hagen, Matthias; Schubert, Mátyás; Baitemirova, Medina Orduna; Arnaud, Melody; McElrath, Melvin; Yee, Michael A; Cohen, Michael; Gu, Michael; Ivanitskiy, Michael; Starritt, Michael; Strube, Michael; Swędrowski, Michał; Bevilacqua, Michele; Yasunaga, Michihiro; Kale, Mihir; Cain, Mike; Xu, Mimee; Suzgun, Mirac; Walker, Mitch; Tiwari, Mo; Bansal, Mohit; Aminnaseri, Moin; Geva, Mor; Gheini, Mozhdeh; T, Mukund Varma; Peng, Nanyun; Chi, Nathan A; Lee, Nayeon; Krakover, Neta Gur-Ari; Cameron, Nicholas; Roberts, Nicholas; Doiron, Nick; Martinez, Nicole; Nangia, Nikita; Deckers, Niklas; Muennighoff, Niklas; Keskar, Nitish Shirish; Iyer, Niveditha S; Constant, Noah; Fiedel, Noah; Wen, Nuan; Zhang, Oliver; Agha, Omar; Elbaghdadi, Omar; Levy, Omer; Evans, Owain; Casares, Pablo Antonio Moreno; Doshi, Parth; Fung, Pascale; Liang, Paul Pu; Vicol, Paul; Alipoormolabashi, Pegah; Liao, Peiyuan; Liang, Percy; Chang, Peter; Eckersley, Peter; Htut, Phu Mon; Hwang, Pinyu; Miłkowski, Piotr; Patil, Piyush; Pezeshkpour, Pouya; Oli, Priti; Mei, Qiaozhu; Lyu, Qing; Chen, Qinlang; Banjade, Rabin; Rudolph, Rachel Etta; Gabriel, Raefer; Habacker, Rahel; Risco, Ramon; Millière, Raphaël; Garg, Rhythm; Barnes, Richard; Saurous, Rif A; Arakawa, Riku; Raymaekers, Robbe; Frank, Robert; Sikand, Rohan; Novak, Roman; Sitelew, Roman; LeBras, Ronan; Liu, Rosanne; Jacobs, Rowan; Zhang, Rui; Salakhutdinov, Ruslan; Chi, Ryan; Lee, Ryan; Stovall, Ryan; Teehan, Ryan; Yang, Rylan; Singh, Sahib; Mohammad, Saif M; Anand, Sajant; Dillavou, Sam; Shleifer, Sam; Wiseman, Sam; Gruetter, Samuel; Bowman, Samuel R; Schoenholz, Samuel S; Han, Sanghyun; Kwatra, Sanjeev; Rous, Sarah A; Ghazarian, Sarik; Ghosh, Sayan; Casey, Sean; Bischoff, Sebastian; Gehrmann, Sebastian; Schuster, Sebastian; Sadeghi, Sepideh; Hamdan, Shadi; Zhou, Sharon; Srivastava, Shashank; Shi, Sherry; Singh, Shikhar; Asaadi, Shima; Gu, Shixiang Shane; Pachchigar, Shubh; Toshniwal, Shubham; Upadhyay, Shyam; Shyamolima; Debnath; Shakeri, Siamak; Thormeyer, Simon; Melzi, Simone; Reddy, Siva; Makini, Sneha Priscilla; Lee, Soo-Hwan; Torene, Spencer; Hatwar, Sriharsha; Dehaene, Stanislas; Divic, Stefan; Ermon, Stefano; Biderman, Stella; Lin, Stephanie; Prasad, Stephen; Piantadosi, Steven T; Shieber, Stuart M; Misherghi, Summer; Kiritchenko, Svetlana; Mishra, Swaroop; Linzen, Tal; Schuster, Tal; Li, Tao; Yu, Tao; Ali, Tariq; Hashimoto, Tatsu; Wu, Te-Lin; Desbordes, Théo; Rothschild, Theodore; Phan, Thomas; Wang, Tianle; Nkinyili, Tiberius; Schick, Timo; Kornev, Timofei; Tunduny, Titus; Gerstenberg, Tobias; Chang, Trenton; Neeraj, Trishala; Khot, Tushar; Shultz, Tyler; Shaham, Uri; Misra, Vedant; Demberg, Vera; Nyamai, Victoria; Raunak, Vikas; Ramasesh, Vinay; Prabhu, Vinay Uday; Padmakumar, Vishakh; Srikumar, Vivek; Fedus, William; Saunders, William; Zhang, William; Vossen, Wout; Ren, Xiang; Tong, Xiaoyu; Zhao, Xinran; Wu, Xinyi; Shen, Xudong; Yaghoobzadeh, Yadollah; Lakretz, Yair; Song, Yangqiu; Bahri, Yasaman; Choi, Yejin; Yang, Yichi; Hao, Yiding; Chen, Yifu; Belinkov, Yonatan; Hou, Yu; Hou, Yufang; Bai, Yuntao; Seid, Zachary; Zhao, Zhuoye; Wang, Zijian; Wang, Zijie J; Wang, Zirui; Wu, Ziyi (2022).

  Language models demonstrate both quantitative improvement and new qualitative textlessptextgreatercapabilities with increasing scale. Despite their potentially transformative textlessptextgreaterimpact, these new capabilities are as yet poorly characterized. In order to textlessptextgreaterinform future research, prepare for disruptive new model capabilities, and textlessptextgreaterameliorate socially harmful effects, it is vital that we understand the present textlessptextgreaterand near-future capabilities and limitations of language models. To address textlessptextgreaterthis challenge, we introduce the Beyond the Imitation Game benchmark \textlessp\textgreater(BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 450 textlessptextgreaterauthors across 132 institutions. Task topics are diverse, drawing problems from textlessptextgreaterlinguistics, childhood development, math, common-sense reasoning, biology, textlessptextgreaterphysics, social bias, software development, and beyond. BIG-bench focuses on textlessptextgreatertasks that are believed to be beyond the capabilities of current language textlessptextgreatermodels. We evaluate the behavior of OpenAI's GPT models, Google-internal dense textlessptextgreatertransformer architectures, and Switch-style sparse transformers on BIG-bench, textlessptextgreateracross model sizes spanning millions to hundreds of billions of parameters. In textlessptextgreateraddition, a team of human expert raters performed all tasks in order to provide textlessptextgreatera strong baseline. Findings include: model performance and calibration both textlessptextgreaterimprove with scale, but are poor in absolute terms (and when compared with \textlessp\textgreaterrater performance); performance is remarkably similar across model classes, textlessptextgreaterthough with benefits from sparsity; tasks that improve gradually and textlessptextgreaterpredictably commonly involve a large knowledge or memorization component, textlessptextgreaterwhereas tasks that exhibit "breakthrough" behavior at a critical scale often textlessptextgreaterinvolve multiple steps or components, or brittle metrics; social bias typically textlessptextgreaterincreases with scale in settings with ambiguous context, but this can be textlessptextgreaterimproved with prompting.
• In-Depth Analysis and Systematic Literature Review on Risk Based Access Control in Cloud. Sadia Hussain, M. Hasan Islam; Abbas, Haider (M. H. I. Sadia Hussain; H. Abbas, eds.) (2022). 12(9) 1–22.

  Security in Cloud is one of the most foremost and critical feature, which can ensure the confidence of the Scientific community on Cloud environment. With the dynamic and ever changing nature of the Cloud computing environment, static access control models become obsolete. Hence, dynamic access control models are required, which is still an emergent and underdeveloped domain in Cloud security. These models utilize not only access policies but also contextual and real-time information to determine the access decision. Out of these dynamic models the Risk-based Access control model, estimates the security risk value related to the access request dynamically to determine the access decision. The exclusive working pattern of this access control model makes it an excellent choice for dynamically changing environment that rules the cloud’s environment. This paper provides a systematic literature appraisal and evaluation of risk-based access control models to provide a detailed understanding of the topic. The contributions of selected articles have been summarized. The security risks in cloud environment have been reviewed, taking in the account of both Cloud Service Provider and Cloud Customer perspectives. Additionally, risk factors used to build the risk-based access control model were extracted and analyzed. Finally, the risk estimation techniques used to evaluate the risks of access control operations have also been identified.
• 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.
• Physical Properties of Trojan and Centaur Asteroids. Barueci, M A; Cruikshank, D P; Mottola, S; Lazzarin, M (2021).

  Trojans and Centaurs are primitive, peculiar objects orbiting in the middle solar system. Both groups characteristically have low albedos and red colors. Physical observations of Trojans reveal featureless reddish spectra, implying surfaces probably rich in complex organic solid materials. The interiors are expected to be rich in H2O ice and other volatile material. Centaurs have surfaces showing dramatically different spectral reflectances, from neutral to very red. Some spectra are featureless, while others show signatures of water ice, methanol, or other light hydrocarbons. Trojans were formed near Jupiter’s orbit, while Centaurs were formed far beyond Jupiter’s orbit, but both were formed at low temperatures at which water exists as solid ice.
• 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.
• How runaway stars boost galactic outflows. Andersson, Eric P; Agertz, Oscar; Renaud, Florent (2020). 494(3) 3328–3341.

  Roughly 10 per cent of OB stars are kicked out of their natal clusters before ending their life as supernovae. These so-called runaway stars can travel hundreds of parsecs into the low-density interstellar medium, where momentum and energy from stellar feedback is efficiently deposited. In this work, we explore how this mechanism affects large-scale properties of the galaxy, such as outflows. To do so we use a new model that treats OB stars and their associated feedback processes on a star-by-star basis. With this model, we compare two hydrodynamical simulations of Milky Way-like galaxies, one where we include runaways, and one where we ignore them. Including runaway stars leads to twice as many supernovae explosions in regions with gas densities ranging from \\($10\textasciicircum\-5\\textbackslash, \textbackslashmathrm\\textbackslash,cm\textasciicircum\-3\\\$\) to \\($10\textasciicircum\-3\\textbackslash, \textbackslashmathrm\\textbackslash,cm\textasciicircum\-3\\\$\). This results in more efficient heating of the inter-arm regions, and drives strong galactic winds with mass loading factors boosted by up to one order of magnitude. These outflows produce a more massive and extended multiphase circumgalactic medium, as well as a population of dense clouds in the halo. Conversely, since less energy and momentum is released in the dense star-forming regions, the cold phase of the interstellar medium is less disturbed by feedback effects.
• 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.
• The prediction of moisture adsorption isotherm for commercial sodium bicarbonate powder. Clément, Yué Bi Yao; Djakalia, Bouatene; Clément, Akmel Djédjro; Kablan, Tano (2018). 9(3) 1829–1836.

  The quality of preserved sodium bicarbonate powder is largely dependent on its moisture content, moisture migration and moisture uptake of the sodium bicarbonate during storage. Therefore, the water activity level, which corresponds to a range of equilibrium moisture contents, must be determined by, for example, the use of moisture isotherms. Sorption isotherms are therefore of great importance in post-harvest procedures, especially for predicting drying and storage, which help to establish the final moisture content of the product under certain environmental condition. Moisture sorption isotherm of sodium bicarbonate powder was determined at laboratory condition (29 ± 1°C) and relative humidity (7-97%), using the standard static gravimetric method. Adsorption isotherm of sodium bicarbonate was type III following Brunauer’s classification. Equilibrium moisture content data were correlated by several equations including two-parameter equations (BET, Kuhn, Hasley, and Oswin), three parameter equation (GAB); and the GAB equation presented the best adjustment for the data over the range of water activities investigated, according to statistical procedures. However, results demonstrated that the BET and Kuhn equations described the sodium bicarbonate adsorption isotherm much better than the GAB equation for the range of water activity ranging from 0.07 to 0.5. The content of water adsorbed in the monomolecular layer was calculated (GABXm = 4.702 g H2O/100 g solids; BETXm = 7.442 g H2O/100 g solids).
• Large granulation cells on the surface of the giant star π1 Gruis. Paladini, C.; Baron, F.; Jorissen, A.; Le Bouquin, J.-B.; Freytag, B.; Van Eck, S.; Wittkowski, M.; Hron, J.; Chiavassa, A.; Berger, J.-P.; Siopis, C.; Mayer, A.; Sadowski, G.; Kravchenko, K.; Shetye, S.; Kerschbaum, F.; Kluska, J.; Ramstedt, S. (2018). 553(7688) 310–312.

  Convection plays a major part in many astrophysical processes, including energy transport, pulsation, dynamos and winds on evolved stars, in dust clouds and on brown dwarfs. Most of our knowledge about stellar convection has come from studying the Sun: about two million convective cells with typical sizes of around 2,000 kilometres across are present on the surface of the Sun-a phenomenon known as granulation. But on the surfaces of giant and supergiant stars there should be only a few large (several tens of thousands of times larger than those on the Sun) convective cells, owing to low surface gravity. Deriving the characteristic properties of convection (such as granule size and contrast) for the most evolved giant and supergiant stars is challenging because their photospheres are obscured by dust, which partially masks the convective patterns. These properties can be inferred from geometric model fitting, but this indirect method does not provide information about the physical origin of the convective cells. Here we report interferometric images of the surface of the evolved giant star π1 Gruis, of spectral type S5,7. Our images show a nearly circular, dust-free atmosphere, which is very compact and only weakly affected by molecular opacity. We find that the stellar surface has a complex convective pattern with an average intensity contrast of 12 per cent, which increases towards shorter wavelengths. We derive a characteristic horizontal granule size of about 1.2 × 1011 metres, which corresponds to 27 per cent of the diameter of the star. Our measurements fall along the scaling relations between granule size, effective temperature and surface gravity that are predicted by simulations of stellar surface convection.
• Execution Time Prediction for Apache Spark. Gao, Zhipeng; Wang, Ting; Wang, Qian; Yang, Yang (2018). 47–51.
• In Search of Actionable Patterns of Lowest Cost - A Scalable Graph Method. Tzacheva, Angelina A. (2018). 10(6) 1–19.

  Action Rules are rule based systems for discovering actionable patterns which are hidden in a large dataset. All recommended patterns from Action Rules incur some form of cost to the users. It is obvious that recommendations are interesting to the users only if the cost that the user pays for the recommended actions is low. In other words, the recommendations should be profitable or valuable to the user when they perform a chain of actions, at the lowest possible cost. In the modern era of big data, organizations are collecting massive amounts of data, growing constantly. Finding low cost actionable patterns for such large data in these domains, is time consuming and requires a scalable approach. In this work, we introduce the notion of Action Graph and propose an algorithm to search the Action Graph for actionable patterns of lowest cost. We apply the proposed algorithm to three datasets in transportation, medical, and business domains. Results show how these domains can benefit from the discovered actionable recommendations of low cost.
• Radial velocities of K–M dwarfs and local stellar kinematics. Sperauskas, J; Bartašiūtė, S; Boyle, R P; Deveikis, V; Raudeliūnas, S; Upgren, A R (2016). 596 A116-A116.

  Aims. The goal of this paper is to present complete radial-velocity data for the spectroscopically selected McCormick sample of nearby K-M dwarfs and, based on these and supplementary data, to determine the space-velocity distributions of late-type stars in the solar neighborhood. Methods. We analyzed nearly 3300 measurements of radial velocities for 1049 K-M dwarfs, that we obtained during the past decade with a CORAVEL-type instrument, with a primary emphasis on detecting and eliminating from kinematic calculations the spectroscopic binaries and binary candidates. Combining radial-velocity data with Hipparcos/Tycho-2 astrometry we calculated the space-velocity components and parameters of the galactic orbits in a three-component model potential for the stars in the sample, that we use for kinematical analysis and for the identification of possible candidate members of nearby stellar kinematic groups. Results. We present the catalog of our observations of radial velocities for 959 stars which are not suspected of velocity variability, along with the catalog of U,V,W velocities and Galactic orbital parameters for a total of 1088 K-M stars which are used in the present kinematic analysis. Of these, 146 stars were identified as possible candidate members of the known nearby kinematic groups and suspected subgroups. The distributions of space-velocity components, orbital eccentricities, and maximum distances from the Galactic plane are consistent with the presence of young, intermediate-age and old populations of the thin disk and a small fraction (\textasciitilde3\%) of stars with the thick disk kinematics. The kinematic structure gives evidence that the bulk of K-M type stars in the immediate solar vicinity represents a dynamically relaxed stellar population. The star MCC 869 is found to be on a retrograde Galactic orbit (V = -262 km s-1) of low inclination (4°) and can be a member of stellar stream of some dissolved structure. The Sun's velocity with respect to the Local Standard of Rest, derived from the distributions of space-velocity components, is (UȮ,VȮ,WȮ) = (9.0 ± 1.4,13.1 ± 0.6,7.2 ± 0.8) km s-1. The radial solar motion derived via the Strömberg's relation, VȮ = 14.2 ± 0.8 km s-1, agrees within the errors with the value obtained directly from the V distribution of stars on nearly circular orbits.
• A Comparison of Four Series of CISCO Network Processors. Sadaf Abaei Senejani1, Hossein Karimi2 (2016).
• 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.
• PISA 2000: Dokumentation der Erhebungsinstrumente Kunter, Mareike; Schümer, Gundel; Artelt, Cordula; Baumert, Jürgen; Klieme, Eckhard; Neubrand, Michael; Prenzel, Manfred; Schiefele, Ulrich; Schneider, Wolfgang; Stanat, Petra; Tillmann, Klaus-Jürgen; Weiß, Manfred (2002).
• The All-Variable Binary WR140 (HD 193793, WCT+O4, P=7.94 yr). Van Der Hucht, K.A; Williams, P.M; Pollock, A.M.T; Hidayat, B.; McCain, C.F; Spoelstra, T.A.Th; Wamsteker, W.M (1991). 143 251–251.

  Recently Williams et al. (1990, M.N.R.A.S. 243, 662) presented new observations of the W C 7 + 0 4 - 5 Wolf-Rayet system HD 193793 (WR140) made between 1979 and 1989 at infrared, radio, UV and X-ray wavelengths. Striking variations were evident in all four regimes.
• The occult underground Webb, James (1988). Open Court, LaSalle, Ill.
• Advanced Combinatorics Comtet, Louis (1974). Springer Netherlands, Dordrecht.

  Notwithstanding its title, the reader will not find in this book a systematic account of this huge subject. Certain classical aspects have been passed by, and the true title ought to be "Various questions of elementary combina­ torial analysis". For instance, we only touch upon the subject of graphs and configurations, but there exists a very extensive and good literature on this subject. For this we refer the reader to the bibliography at the end of the volume. The true beginnings of combinatorial analysis (also called combina­ tory analysis) coincide with the beginnings of probability theory in the 17th century. For about two centuries it vanished as an autonomous sub­ ject. But the advance of statistics, with an ever-increasing demand for configurations as well as the advent and development of computers, have, beyond doubt, contributed to reinstating this subject after such a long period of negligence. For a long time the aim of combinatorial analysis was to count the different ways of arranging objects under given circumstances. Hence, many of the traditional problems of analysis or geometry which are con­ cerned at a certain moment with finite structures, have a combinatorial character. Today, combinatorial analysis is also relevant to problems of existence, estimation and structuration, like all other parts of mathema­ tics, but exclusively forjinite sets.
• Differential thermal analysis of the decomposition of sodium bicarbonate and its simple double salts. Barall, Edward M.; Rogers, L.B. (1966). 28(1) 41–51.

  The thermal decompositions of sodium bicarbonate, trona, and Wegscheider's salt (Na2CO3·3NaHCO3) have been studied in a closed system by means of differential thermal analysis (DTA) and X-ray diffraction analyses of reactants and products. The energies of activation of the thermal decompositions of these materials have been calculated from the differential thermograms using Kissinger's equations. The decomposition products of trona, sodium bicarbonate, and Wegscheider's salt have been identified by X-ray diffraction. A reaction sequence involving the formation of Wegscheider's salt has been proposed to explain the thermal anomalies previously observed in the decomposition of sodium bicarbonate in a closed system. A DTA cell design suitable for the study of decompositions and dehydrations in a sealed, self-generated atmosphere at constant pressure is described.
• Stellar Atmospheres; a Contribution to the Observational Study of High Temperature in the Reversing Layers of Stars. Payne, Cecilia Helena (1925).
• On the equilibrium of the Sun’s atmosphere. Schwarzschild, K. (1906). 195 41–53.

  In granulation, sun spots, and prominences, the sun's surface displays changing conditions and stormy variations. In order to understand the physical relations of these phenomena, it is customary, as first approximation, to subsititute mean steady-state conditions for these spatial and temporal variations, thus obtaining a mechanical or hydrostatic equilibrium of the solar atmosphere. Until now attention has generally been concentrated on the socalled adiabatic equilibrium, which is analogous to the conditions prevailing in our atmosphere when it has been thoroughly mixed by ascending and descending currents. In this paper I wish to call attention at another type of equilibrium, which we call radiative equilibrium. Radiative equilibrium in a strongly radiating and absorbing atmosphere will be established when radiative heat transfer predominates over heat transfer due to convective mixing. It would be difficult to decide a priori whether adiabatic or radiative equilibrium predominates in the sun. However, we have observational data from which we can come to some conclusions on this matter. The solar disc is not uniformly bright; in fact, the light intensity decreases with increasing distance from the center. With certain plausible assumptions it is possible to deduce the temperature distribution within the atmosphere from the intensity distribution at the surface. The result we obtain is that the equilibrium conditions of the solar atmosphere correspond generally to those of radiative equilibrium. Our considerations leading to this result require that Kirchhoff's law is valid, or, in other words, that radiation in the solar atmosphere is pure thermal radiation. We require further that conditions vary smoothly as we descend into the sun, so that there is no discontinuous transition between a more or less transparent chromosphere and an opaque photosphere consisting of luminous clouds. We neglect the effect of light-scattering due to atmospheric particles, whose importance A.textasciitildeSchuster first pointed out, as well as refraction, on which H.V.textasciitildeSeeliger bases his explanation of the observed brightness distribution. We further neglect the variation of absorption with wavelength, the decrease of gravity with height, and the spherical propagation of radiation. Thus our considerations are neither complete nor compelling, but by explaining a simple idea in its simplest form, they may form the basis for further speculations.