Results 111 to 120 of about 1,480,093 (371)
Advanced Engineering Materials, EarlyView.A machine learning‐driven framework is introduced to optimize 3D‐printable microneedles for enhanced tissue anchoring and reduced insertion damage. The optimized design achieves a 6.0‐fold improvement in pull‐out‐to‐penetration energy ratio over conventional shapes.
Jegyeong Ryu +5 more
wiley +1 more source
Benchmarking least squares support vector machine classifiers. [PDF]
In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a ( convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function
Baesens, Bart +7 more
core
Structurally Colored Physically Unclonable Functions with Ultra‐Rich and Stable Encoding Capacity
Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.This study reports a design strategy for generating bright‐field resolvable physically unclonable functions with extremely rich encoding capacity coupled with outstanding thermal and chemical stability. The optical response emerges from thickness‐dependent structural color formation in ZnO features, which are fabricated by physical vapor deposition ...
Abidin Esidir +8 more
wiley +1 more source
Forecasting of Short-term Power Load Based on Improved PSO Algorithm and LS-SVM
Gong-kuang zidonghua, 2012 For problems of small samples, nonlinear, high dimensions and the local minimum of electric power load, a modeling method based on the least square support vector machine was proposed to forecast short-term power load by taking historical load ...
PAN Lei +3 more
doaj
Traffic fatalities prediction using support vector machine with hybrid particle swarm optimization
Journal of Algorithms & Computational Technology, 2018 Road traffic safety is essential, therefore in order to predict traffic fatalities effectively and promote the harmonious development of transportation, a traffic fatalities prediction model based on support vector machine is established in this paper ...
Xiaoning Gu +5 more
doaj +1 more source
An Equivalence Between Sparse Approximation and Support Vector Machines [PDF]
, 1998 Federico Girosi
openalex +1 more source
Advanced Functional Materials, EarlyView.Oct4‐nanoscript, a biomimetic nanoparticle‐based artificial transcription factor, precisely regulates cellular rejuvenation by activating Oct4 target genes, restoring epigenetic marks, and reducing DNA damage. In a progeria model, it effectively rescued aging‐associated pathologies and extended lifespan.
Hongwon Kim +8 more
wiley +1 more source
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods [PDF]
, 2000 Nello Cristianini, John Shawe‐Taylor
openalex +1 more source
Advanced Functional Materials, EarlyView.This review highlights recent advances in engineering artificial antigen‐presenting cells (aAPCs) as alternatives to dendritic cells for T cell expansion. Key design principles inspired by the immunological synapse are discussed, with emphasis on strategies for polyclonal and antigen‐specific T cell expansion.
Nguyen Thi Nguyen, Yu Seok Youn
wiley +1 more source
Knowledge-based analysis of microarray gene expression data by using support vector machines [PDF]
, 2000 Michael P. Brown +7 more
openalex +1 more source