• Neu
Sachdeva / Watanobe / Bhalla | Big Data Analytics in Astronomy, Science, and Engineering | E-Book | www2.sack.de
E-Book

E-Book, Englisch, 386 Seiten

Reihe: Lecture Notes in Computer Science

Sachdeva / Watanobe / Bhalla Big Data Analytics in Astronomy, Science, and Engineering

13th International Conference on Big Data Analytics, BDA 2025, Aizu, Japan, December 15–17, 2025, Proceedings
Erscheinungsjahr 2026
ISBN: 978-3-032-23241-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

13th International Conference on Big Data Analytics, BDA 2025, Aizu, Japan, December 15–17, 2025, Proceedings

E-Book, Englisch, 386 Seiten

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-032-23241-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark



This book constitutes the proceedings of the 13th International Conference on Big Data Analytics in Astronomy, Science, and Engineering, BDA 2025, which took place in Aizu, Japan during November 26-28, 2025.

The 23 full papers in this book were carefully reviewed and selected from 145 submissions. They were organized in topical sections as follows: Big Data: Management and Visualization ; Data Science: Architecture and Systems; Data Science and Applications; Information Security and Cloud Computing.

Sachdeva / Watanobe / Bhalla Big Data Analytics in Astronomy, Science, and Engineering jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


.- Big Data: Management and Visualization
.- EHRInsight:  A Self-Correcting Agent- Based Framework for   Querying and Visualizing EHR Data.
.- Big Data-Driven Federated Knowledge Graph for Adverse Drug Reaction Prediction.
.- Multimodal Intelligence for Healthcare: Combining Text and Medical Images through Vision-Language Models.
.- Geometry-Driven Selectivity in Macrocyclization via Rigid-Body Simulation.
.- Unifying Diverse Data Horizons with Functional Synergy using Polyglot Persistence.
.- Data Science: Architecture and Systems
.- HomeoCure: LLM-RAG Framework for Symptom-Based Homeopathy Remedy Recommendation.
.- A Collaborative and Adaptive Framework for Transformer-based Topic Modelling.
.- Intelligent Routing for Smart and Sustainable Transportation: Multi Modal Real-Time Data based Deep Reinforcement Learning Framework.
.- INFERMed: A PK/PD-Aware Retrieval-Augmented System for Explainable Drug-Drug Interaction Analysis.
.- EnergyTwin: A Multi-Agent System for Simulating and Coordinating Energy Microgrids.
.- Auto_WGCNA: A Reproducible R Pipeline from Gene Counts to Hub Gene Identification.
.- Data Science and Applications
.- Meta-Prompting Generative AI for Standards-Based IT Project Management Documentation Using Business Data Semantics.
.- Epileptic Seizure Prediction Using a Lightweight Separable Vision Transformer and EEG Spectrograms.
.- Improved Interaction Prediction in PPI Networks using Graph Neural Networks.
.- DILI-MAFNet: A Multimodal Attention Fusion Network for Drug Induced Liver Injury Prediction.
.- Safeguarding Plurality: The Digital Preservation of Diverse Worldviews.
.- Detection of Shock Risk Triggers Using Time-aware Dynamic-Window RAG with LLMs.
.- Detection of Biases in fact-checking Using LLMs.
.- Information Security and Cloud Computing
.- Load Balancing Algorithm: Hybrid Energy Efficiency in Cloud Computing.
.- Towards Trustworthy Off-Chain Payments: A Secure Lightning Network Model.
.- Practical considerations for deploying frugal AI in the IoT-Edge- Cloud continuum.
.- SAFE: Probabilistic Framework to characterize Honest Reviewers.
.- Quantum Computing.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.