Results 171 to 180 of about 133,855 (339)
Cosine Products, Fourier Transforms, and Random Sums [PDF]
Kent E. Morrison
openalex +1 more source
Impact of distance measures in adaptive K-means clustering on load profiles and spatial patterns of distributed substations in Thailand. [PDF]
Prompook T+8 more
europepmc +1 more source
Capillary‐Driven 3D Open Fluidic Networks for Versatile Continuous Flow Manipulation
The capillary‐driven 3D open fluidic networks (OFNs), composed of connected polyhedral frames, enable precise, programmable, and versatile manipulation of unary, binary, and multiple continuous flows in both spatial and temporal dimensions. OFNs represent a significant leap beyond conventional microfluidics, unlocking new possibilities for selective ...
Shuangmei Wu+4 more
wiley +1 more source
Long-Range Dependence in Word Time Series: The Cosine Correlation of Embeddings. [PDF]
Wieczyński P, Dębowski Ł.
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On a characterization of the cosine [PDF]
openaire +2 more sources
This review discusses recent innovations in electrochemical CO2 reduction reactions (eCO2RR) and hydrogen evolution reaction cell designs. The latest advancements in in situ cells for operando characterization are also presented. Optimizations in flow patterns, membrane electrode assemblies, electrolyte engineering, and counter‐anodic reactions provide
Zhangsen Chen+3 more
wiley +1 more source
Discrete cosine transform in error control coding [PDF]
Ja‐Ling Wu, Jitae Shin
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JESTR: Joint Embedding Space Technique for Ranking candidate molecules for the annotation of untargeted metabolomics data. [PDF]
Kalia A+3 more
europepmc +1 more source
Thermionics in Topological Materials
Thermionics is one of the fundamental energy conversion mechanisms in solid state systems. Recent development in topological materials opens new avenues in developing thermionic systems and devices. Due to the linear energy dispersion and topological protection of charge transport, these new materials are promising candidates for high efficiency ...
Sunchao Huang+8 more
wiley +1 more source
AI‐Driven Defect Engineering for Advanced Thermoelectric Materials
This review presents how AI accelerates the design of defect‐tuned thermoelectric materials. By integrating machine learning with high‐throughput data and physics‐informed representations, it enables efficient prediction of thermoelectric performance from complex defect landscapes.
Chu‐Liang Fu+9 more
wiley +1 more source