Results 201 to 210 of about 1,725,284 (283)
When prediction fails: a computational complexity view of stress. [PDF]
Budaev S, Lai F, Morgan R, Rønnestad I.
europepmc +1 more source
This study proposes a potential device design for joint cartilage replacement. Silica‐polytetrahydrofuran (SiO2‐PolyTHF) hybrids with customizable mechanical properties were developed to mimic the characteristics of a natural meniscus. These were synthesized through a two‐pot sol–gel hybrid process.
Yu‐Chien Lin +12 more
wiley +1 more source
Algorithmic Complexity in Textile Patterns
Algorithmic complexity, also called Kolmogorov complexity and Kolmogorov-Chaitin complexity, motivates the use of techniques to approximate the complexity of objects and measure similarity between them.
Metzler, Heidi
core
Governing algorithms, empowering people: how ethical AI oversight shapes trust, technostress, and employee autonomy in AI-enabled HRM. [PDF]
Patnaik T, Gnankob RI, Nanda NS.
europepmc +1 more source
Rotary 3D Printing With Integrated Electroplating
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria +5 more
wiley +1 more source
Semantic Algorithmic Information Theory: From Kolmogorov Complexity to Semantic Equivalence. [PDF]
Wu J, Wang S, Niu K, She Y, Zhang P.
europepmc +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
The Physics, Information, and Computation of Perennial Learning: Kolmogorov Complexity, Information Distance, and Port-Hamiltonian Thermodynamics. [PDF]
Bajaj C.
europepmc +1 more source
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source

