New centrality measure for symmetric networks: g-core and local g-core

Happy to share our recent accepted papers (led by Ruide and 郭斌全), on game theory in Open RAN and scheduling federated learning over satellite networks, in IEEE GLOBECOM 2025 and IEEE TrustCom 2025 respectively! 𝐀 𝐔𝐬𝐞𝐫-𝐭𝐨-𝐔𝐬𝐞𝐫 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐑𝐞𝐬𝐞𝐥𝐥𝐢𝐧𝐠 𝐆𝐚𝐦𝐞 𝐢𝐧 𝐎𝐩𝐞𝐧 𝐑𝐀𝐍 𝐰𝐢𝐭𝐡 𝐁𝐮𝐟𝐟𝐞𝐫 𝐑𝐨𝐥𝐥𝐨𝐯𝐞𝐫 Ruide Cao, Marie Siew, David Yau IEEE Globecom 2025. In this paper, we propose a user-to-user resource reselling model for Open RAN that improves efficiency by reducing data loss and spectrum wastage. Our model models the carryover of unmet demand across time slots, along with how users’ internal buffer states relate to any PRBs purchased. https://lnkd.in/gqQKyqcY 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐏𝐫𝐢𝐯𝐚𝐜𝐲-𝐏𝐫𝐞𝐬𝐞𝐫𝐯𝐢𝐧𝐠 𝐅𝐞𝐝𝐞𝐫𝐚𝐭𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐢𝐧 𝐋𝐚𝐫𝐠𝐞-𝐒𝐜𝐚𝐥𝐞 𝐋𝐄𝐎 𝐒𝐚𝐭𝐞𝐥𝐥𝐢𝐭𝐞 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 Binquan Guo, Junteng Cao, Marie Siew, Binbin Chen, Tony Q. S. Quek, Zhu Han IEEE TrustCom 2025 https://lnkd.in/gcDwHZ5p We propose a discrete temporal graph–based on-demand scheduling framework to accelerate Federated Learning in large-scale Low-Earth-Orbit (LEO) satellite systems, addressing the prolonged training times caused by limited bandwidth and dynamic network topologies.

⭐️We are thrilled to share our recent publication, Concurrent Double-Ended Priority Queues, accepted as a brief announcement at the 39th International Symposium on Distributed Computing (DISC 2025). 📄The paper, written by Panagiota Fatourou, Eric Ruppert and Ioannis Xiradakis, explores the first general-purpose methodology for constructing linearizable and lock-free concurrent Double-Ended Priority Queues (DEPQ). 📈This work presents a transformation that builds a concurrent Double-Ended Priority Queue from any existing linearizable concurrent (single-ended) priority queue. https://lnkd.in/dqG5JE2u Η δράση υλοποιείται στο πλαίσιο του Εθνικού ��χεδίου Ανάκαμψης και Ανθεκτικότητας Ελλάδα 2.0 με τη χρηματοδότηση της Ευρωπαϊκής Ένωσης – NextGenerationEU The project is implemented under the National Recovery and Resilience Plan “Greece 2.0”, with funding from the European Union – NextGenerationEU

On 14th August 2025, the Physical Sciences Data Infrastructure (PSDI) hosted a webinar titled “Seekest thou the road to, all that’s digital and FAIR – the Ballad of the ELN Journey”, presented by Dr. Samantha Pearman-Kanza,. The session explores the sociotechnical challenges of implementing Electronic Lab Notebooks (ELNs) to achieve FAIR (Findable, Accessible, Interoperable, Reusable) data in research labs. For those who missed the live session or wish to revisit the discussion, the full webinar is available on our YouTube channel: https://lnkd.in/eVyucgtx The slides are available on Zenodo: https://lnkd.in/e-rKQYfP

🔬 Our new paper is out! “Messengers: breaking echo chambers in collective opinion dynamics with homophily” with Mohsen Raoufi and Pawel Romanczuk Now published in npj Complexity and available open access.  📘 What the paper is about In collective decision-making, agents exchange information locally to converge on a shared estimate. But when agents preferentially interact with like-minded peers (homophily), echo chambers can emerge and block consensus. Our work addresses how to overcome that obstacle in spatially embedded systems. 🧠 Key ideas & contributions > We model agents moving through a continuous information landscape, sampling local signals while interacting only within a limited communication radius.   > As homophily guides interactions, networks can become fragmented: clusters of agents reinforce their own views and fail to integrate information across groups.   > To counteract that, we introduce a new behavioral role: Messengers. These agents stop updating their opinion and instead carry their last known opinion as they roam the space, acting like mobile bridges across disconnected clusters.   > We let agents probabilistically switch between being normal "Exploiters" and Messengers via a Dichotomous Markov Process. The switching dynamics (how often, for how long) critically shape performance.   > Through simulations and analysis, we map out regimes where a balanced mix of Messengers and Exploiters helps the collective break free from echo chambers and reach high‐precision consensus. Too few or too many Messengers degrade performance.   > We validate that these benefits hold across different spatial information landscapes.  🚀 Why it matters & where it applies > The idea of embodied "data ferries" (Messengers) suggests a decentralized, scalable way to mitigate fragmentation in collective systems. > Our work gives insights into how to design robust collective intelligence in contexts where connection is limited or interactions are selective. > The echo‐chamber dynamics we simulate have conceptual echoes in social or information networks (e.g. polarization), and the Messenger mechanism offers a metaphorical tool for thinking about bridging disconnected communities. If you’re interested, here’s the open-access link to the full article: https://lnkd.in/esBGbKay

🗺️ Data Sources and Models for Integrated Mobility and Transport Solutions 🧑 Pierfrancesco Bellini, Stefano Bilotta, Enrico Collini, Marco Fanfani and Paolo Nesi* 🏫 Università degli Studi di Firenze 🔎 The number of data sources and models in the #mobility and #transport domain strongly proliferated in the last decade. Most formats have been created to enable specific and innovative applications. On the other hand, the available data models present a certain degree of complexity in terms of their integration and management due to partial overlaps, and in most cases, they could be exploited alternatively to implement the same smart and latest innovative solutions. This paper offers an overview of data models, standards and their relationships. A second contribution highlights any possible exploitation of data models for implementing operational processes for city transportation management and for the feeding of simulation and optimization processes that produce other data results in other data models. The final goal in most cases is the monitoring and control of city transport conditions, as well as the tactic and strategic planning of city infrastructure. This work was developed in the context of the CN MOST, a national center of sustainable mobility in Italy, and it is based on exploiting the Snap4City platform. https://lnkd.in/g2QrdsAm

With over 47,000 views, this special issue published in Big Data and Cognitive Computing MDPI (BDCC, ISSN 2504-2289) explores a variety of methods, tools, and applications for sentiment analysis in social networks. The special issue analyzes the impact of digital transformation on society through a range of studies of social media data. Guest edited by Dr. Maria Chiara Caschera, Dr. Patrizia Grifoni and Dr. Fernando Ferri of the Institute of Research on Population and Social Policies, Italy. Read the Open Access MDPI Books reprint: https://brnw.ch/21wWOlq #mdpi #openaccess #socialmedia #research #mdpibooks

A new Special Issue opens for submission! Title: Symmetry/Asymmetry in Fuzzy #MultiCriteria #DecisionMaking: Application in Management and Engineering Editor: Aleksandar Milić and Adis Puška Modern approaches to solving multi-criteria decision-making (MCDM) problems usually indicate the existence of asymmetry in defining the weighting coefficients of the criteria, i.e., in the selection of alternatives. On the other hand, symmetry is rare and can usually be found when performing a sensitivity analysis of the model. Also, in research, it can be seen that many uncertainties accompany MCDM processes. Even though several areas that consider uncertainties have been developed, the most represented area remains fuzzy logic. In the last twenty years, fuzzy logic has been greatly expanded, and the initial classical fuzzy numbers have been modified to unrecognizable proportions. Despite the development of newer approaches, some authors stuck to the original fuzzy numbers, considering them sufficient for solving MCDM problems. The application of the fuzzy MCDM model is noticeable in many areas... Details: https://brnw.ch/21wWXcl #callforpapers #mdpisymmetry

I’m happy to share that my paper titled “An Analysis of Densely Connected Convolutional Networks Integrated with Word2Vec Embedding for Turkish News Classification” which was originally presented at UBMK ( International Conference on Computer Science and Engineering) has been published in IEEE Xplore 🎉 DenseNet (Densely Connected Convolutional Networks) is a robust deep learning model known for its outstanding performance in computer vision tasks, thanks to its efficient feature utilization. The dense connections allow for feature reuse and enhance the learning process, which is especially beneficial for tasks involving deep hierarchical patterns, such as classification. In text classification, DenseNet can process Word2Vec embeddings to extract complex, hierarchical features essential for accurate categorization. 📄 The full paper is now available on IEEE Xplore: https://lnkd.in/dFifiMau

🚀 HPCW 3.0 is here — now open-source! The High-Performance Climate and Weather (HPCW) benchmarking suite has just released version 3.0, marking a major step forward for open, reproducible performance testing in weather and climate simulations. 🌍 What’s HPCW? HPCW simplifies benchmarking on new supercomputing platforms, focusing on applications used in climate and weather research. It automates the process of building and running complex models — making performance testing accessible, consistent, and easier to compare across systems. 💡 Why it matters While supercomputers are traditionally ranked using the LINPACK benchmark (Top500), real-world applications like weather and climate modelling demand a broader view of performance. HPCW fills this gap — complementing benchmarks such as Green500 and Graph500 with domain-specific workloads. ⚙️ What’s new in v3.0 Now fully open-source 🎉 Includes leading European models such as ICON, NEMO, and ecTrans Adds the first Japanese model – NICAM, through collaboration with the HANAMI project Officially supported on top-tier systems including DKRZ/Levante, ECMWF/HPC2020, R-CCS/Fugaku, and BSC/MareNostrum5 🔗 Explore HPCW: https://lnkd.in/dwWfBdiA 📘 Documentation: https://lnkd.in/dYHnc3Au 🙌 Contributions and collaborations are welcome — join us in building the next generation of benchmarking tools for weather and climate computing. #HPC #Supercomputing #ClimateModeling #WeatherPrediction #OpenSource #Benchmarking #HPCW #ScienceTech