Results 41 to 50 of about 184,733 (266)
Kernel locality‐constrained sparse coding for head pose estimation
In many situations, it would be practical for a computer system user interface to have a model of where a person is looking and what the user is paying attention to.
Hyunduk Kim +3 more
doaj +1 more source
Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias +3 more
wiley +1 more source
The Application of Kernel Ridge Regression for the Improvement of a Sensing Interferometric System
Sensors based on interferometric systems have been studied due to their wide range of advantages, such as high sensitivity. For these types of sensors, traditional methods, which generally depend on the linear sensitivity of one variable, have been used ...
Ana Dinora Guzman-Chavez +1 more
doaj +1 more source
MKL-SVM algorithm for pulmonary nodule recognition based on swarm intelligence optimization
To solve the problem that a single kernel learning support vector machine (SVM) cannot consider the learning and generalization abilities and parameter optimization of the multiple kernel function, a multiple kernel learning support vector machine (MKL ...
Yang LI, Jia-yue CHANG, Yu-yang WANG
doaj +1 more source
Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease
ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay +15 more
wiley +1 more source
An Info-Leak Resistant Kernel Randomization for Virtualized Systems
Given the significance that the cloud paradigm has in modern society, it is extremely important to provide security to users at all levels, especially at the most fundamental ones since these are the most sensitive and potentially harmful in the event of
Fernando Vano-Garcia +1 more
doaj +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar +2 more
wiley +1 more source
Theta Functions and Szegö Kernels
We study relations between two fundamental constructions associated to vector bundles on a smooth complex projective curve: the theta function (a section of a line bundle on the moduli space of vector bundles) and the Szegö kernel (a section of a vector bundle on the square of the curve). Two types of relations are demonstrated.
Ben-Zvi, David, Biswas, Indranil
openaire +3 more sources
Multimodal Data‐Driven Microstructure Characterization
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source

