Results 51 to 60 of about 1,419,434 (280)

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
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

Seven Insights from a Cyber Operations Maneuverist

open access: yesThe Cyber Defense Review
Cyberspace will not be mastered through borrowed concepts from other domains. As cyberspace operations continue to mature, military organizations must ensure that doctrine, force generation, and operational concepts evolve alongside operational ...
Ryan Janovic
doaj   +1 more source

Fear, Uncertainty, and Dread: Cognitive Heuristics and Cyber Threats

open access: yesPolitics and Governance, 2018
Advances in cyber capabilities continue to cause apprehension among the public. With states engaging in cyber operations in pursuit of its perceived strategic utility, it is unsurprising that images of a “Cyber Pearl Harbor” remain appealing.
Miguel Alberto Gomez, Eula Bianca Villar
doaj   +1 more source

Cyberspace Solarium Commission

open access: yes, 2020
Website of the Cyberspace Solarium Commission documenting the group's publications regarding cybersecurity strategy for the U.S.
United States. Cyberspace Solarium Commission
core  

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

open access: yesAdvanced Engineering Materials, EarlyView.
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

Embedding Airmenship in the Cyberspace Domain: The First Few Steps of a Long Walk

open access: yesThe Cyber Defense Review, 2016
Our Air Force’s use of cyberspace has continued to evolve since its beginnings as a defense and academic research project in 1960. Our reliance on this new domain ranges from cyber’s ability to connect individuals and groups globally; to its ability to ...
Burke Wilson   +9 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
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

Relationships between Cyberspace Operations and Information Operations

open access: yesAdvances in Military Technology, 2021
Today thanks to the wireless networking technologies and social networks, the inter-pretation of cyberspace has expanded. According to the three-layered structure of cyberspace, not only logical effects can be induced in this domain, e.g. by malwares, but physical and cognitive effects also appear in the physical and cyber-persona lay-ers, e.g ...
openaire   +2 more sources

CSC Final Report

open access: yes, 2020
Final report of the Cyberspace Solarium Commission documenting the findings, recommendations, and other information related to research into cybersecurity, including an overview of the challenge at hand, a summary of the historical legacy and methodology,
United States. Cyberspace Solarium Commission
core  

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

open access: yesAdvanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle   +5 more
wiley   +1 more source

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