Results 81 to 90 of about 192,525 (251)
In the digital society of "open sharing of information and interconnection of everything", the information traces characterized with "massive, multi-source and explosive growth" in the internet provide rich "mineral deposits" for open-source intelligence
YUAN Weilin +7 more
doaj
Use of Open-Source Epidemic Intelligence for Infectious Disease Outbreaks, Ukraine, 2022
Formal infectious disease surveillance in Ukraine has been disrupted by Russia’s 2022 invasion, leading to challenges with tracking and containing epidemics.
Anjali Kannan +6 more
doaj +1 more source
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
The role of new technologies in transforming open-source intelligence [PDF]
The new technologies change the paradigm of information in society. The quality and use of intelligence depend on the quality of information, information and decision-makers.
Gabriela TATU
doaj
The PRIMA Thesaurus for Materials Science and Engineering
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa +8 more
wiley +1 more source
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
Empowering LLMs with Toolkits: An Open-Source Intelligence Acquisition Method
The acquisition of cybersecurity threat intelligence is a critical task in the implementation of effective security defense strategies. Recently, advancements in large language model (LLM) technology have led to remarkable capabilities in natural ...
Xinyang Yuan +4 more
doaj +1 more source

