Results 51 to 60 of about 5,834,158 (292)

MKL-SVM algorithm for pulmonary nodule recognition based on swarm intelligence optimization

工程科学学报, 2021
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

Annals of Clinical and Translational Neurology, EarlyView.
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, Merve Alaylioglu, Erdi Sahin, Sanem Sultan Yoruk Oner, Gulce Iskan, Gulce Cosku Yilmaz Cakan, Gozde Kizilates‐Evin, Emre Hari, Elif Kurt, Erdinc Dursun, Basar Bilgic, Hasmet Hanagasi, Hakan Gurvit, Tamer Demiralp, Duygu Gezen‐Ak, Bedia Samanci   +15 more
wiley   +1 more source

CSF Cytokine Network Organization Predicts Progression Independent of Relapse and MRI Activity in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progression independent of relapse activity is a major determinant of long‐term disability in multiple sclerosis, but its immunopathologic basis remains incompletely understood. We investigated whether relapse‐independent progression in radiologically stable relapsing–remitting multiple sclerosis is associated with distinct ...
Antonio Bruno, Matteo Conti, Ettore Dolcetti, Federica Azzolini, Angela Borrelli, Roberta Fantozzi, Mario Stampanoni Bassi, Giovanni Galifi, Giuseppe Maccarrone, Luca Montaguti, Marco Cervigni, Maddalena Dal Pozzo, Roberto Furlan, Annamaria Finardi, Girolama Alessandra Marfia, Marco Salvetti, Antonella Conte, Fabio Buttari, Diego Centonze, Luana Gilio   +19 more
wiley   +1 more source

Parsimonious Kernel Fisher Discrimination

, 2007
By applying recent results in optimization transfer, a new algorithm for kernel Fisher Discriminant Analysis is provided that makes use of a non-smooth penalty on the coefficients to provide a parsimonious solution.
Harrison, Robert F., Willett, Peter, Robert F. Harrison, Pasupa, Kitsuchart, Kitsuchart Pasupa, Peter Willett   +5 more
core   +1 more source

An Info-Leak Resistant Kernel Randomization for Virtualized Systems

IEEE Access, 2020
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, Hector Marco-Gisbert   +1 more
doaj   +1 more source

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Gear fault diagnosis method based on wavelet-packet independent component analysis and support vector machine with kernel function fusion

Advances in Mechanical Engineering, 2018
Aiming at the problem of gear fault diagnosis, in order to effectively extract the features and improve the accuracy of gear fault diagnosis, the method based on wavelet-packet independent component analysis and support vector machine with kernel ...
Lizheng Pan, Dashuai Zhu, Shigang She, Aiguo Song, Xianchuan Shi, Suolin Duan   +5 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Theta Functions and Szegö Kernels

, 2002
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

Research on Kernel Extreme Learning Machine Algorithm for Key Node Identification in Aviation Network

Hangkong gongcheng jinzhan, 2021
Accurately identifying the key nodes of aviation network through technical means is of important theoretical significance and reference value for the normal operation of aviation network in peacetime and defense and repair in wartime.
NIU Junfeng, GAN Xusheng, SUN Jingjuan, TU Congliang   +3 more
doaj   +1 more source