Results 71 to 80 of about 1,490,008 (243)

Markov Logic Networks for Incremental Natural Language Understanding [PDF]

open access: yes, 2012
Kennington C, Schlangen D. Markov Logic Networks for Incremental Natural Language Understanding. In: Proceedings of the 13th Meeting of the Special Interest Group on Discourse and Dialogue (SIGdial). SIGdial; 2012: 314-323.Video of talk available here:
Kennington, Casey   +1 more
core  

Associations of Frailty With the Risk of Incident Cancer and Cancer‐Related Mortality in Veterans With Rheumatoid Arthritis

open access: yesArthritis Care &Research, EarlyView.
Objective This study investigated the association between frailty and cancer incidence and mortality in patients with rheumatoid arthritis (RA). It aimed to identify how frailty influences cancer risk and cancer‐specific outcomes. Methods This retrospective cohort study analyzed data from the Veterans’ Affairs Rheumatoid Arthritis Registry (2002–2023).
Bhavik Bansal   +12 more
wiley   +1 more source

Incremental Construction of Robust but Deep Semantic Representations for Use in Responsive Dialogue Systems [PDF]

open access: yes, 2012
Peldszus A, Schlangen D. Incremental Construction of Robust but Deep Semantic Representations for Use in Responsive Dialogue Systems. In: Hajičová E, ed.
Peldszus, Andreas   +2 more
core  

Positive Affect is Associated with Better Physical Function in Early Rheumatoid Arthritis

open access: yesArthritis Care &Research, Accepted Article.
Objective This study examined the association between positive affect and physical function in individuals with early rheumatoid arthritis (RA). Methods We analyzed baseline data from 129 adults with early RA (persistent joint symptoms for ≤ 24 months) and active disease enrolled in the Central Pain in RA 2 (CPIRA‐2) study.
Burcu Aydemir   +9 more
wiley   +1 more source

Flexural Behavior of 3D‐Printed Porous Bouligand‐Structured Polymers: Influence of Pitch Angle and Porosity

open access: yesAdvanced Engineering Materials, EarlyView.
This study examines how helicoidal architectures with different porosities respond to bending. Adjusting layer angle and spacing in 3D‐printed polymers reveals clear tradeoffs between stiffness, strength, and energy absorption. Experiments and simulations highlight designs that distribute stress effectively, offering pathways for optimizing lightweight
Praveenkumar Subhash Patil   +2 more
wiley   +1 more source

Affecting the Properties of Copper–Graphene Electroconductive Composite by Severe Plastic Deformation

open access: yesAdvanced Engineering Materials, EarlyView.
Copper‐based composites enhanced with carbon feature convenient mechanical properties and favorable electric conductivity. Processing via deformation and thermomechanical treatments can introduce advantageous microstructures further enhancing their performance. Herein, copper–graphene powder‐based composites are directly consolidated via rotary swaging
Radim Kocich   +3 more
wiley   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

open access: yesAdvanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier   +17 more
wiley   +1 more source

The PRIMA Thesaurus for Materials Science and Engineering

open access: yesAdvanced Engineering Materials, EarlyView.
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

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

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