Results 101 to 110 of about 7,794,647 (291)

Support vector machine-based classification of schizophrenia patients and healthy controls using structural magnetic resonance imaging from two independent sites.

PLoS ONE, 2020
Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support vector machines can classify patients and healthy ...
Maeri Yamamoto, Epifanio Bagarinao, Itaru Kushima, Tsutomu Takahashi, Daiki Sasabayashi, Toshiya Inada, Michio Suzuki, Tetsuya Iidaka, Norio Ozaki   +8 more
doaj   +1 more source

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Complex and Hypercomplex-Valued Support Vector Machines: A Survey

Applied Sciences, 2019
In recent years, the field of complex, hypercomplex-valued and geometric Support Vector Machines (SVM) has undergone immense progress due to the compatibility of complex and hypercomplex number representations with analytic signals, as well as the power ...
Nancy Arana-Daniel
doaj   +1 more source

SVM-Maj: a majorization approach to linear support vector machines with different hinge errors [PDF]

Support vector machines (SVM) are becoming increasingly popular for the prediction of a binary dependent variable. SVMs perform very well with respect to competing techniques. Often, the solution of an SVM is obtained by switching to the dual.
Groenen, P.J.F., Bioch, J.C., Nalbantov, G.I.   +2 more
core  

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Symmetry‐Guided Multifunctional Acoustic System Based on Mechanically Actuated Sonic Crystals

Advanced Engineering Materials, EarlyView.
This study presents the design, simulation, and experimental validation of amultifunctional acoustic metamaterial based on rotationally engineered sonic crystals.By tuning cylinder orientations, controllable band gaps and six distinct functionalities—including switching, topological insulation, beam splitting, and logic operations—areachieved ...
Yuanyan Zhao, Sriram Subramanian, Gianluca Memoli   +2 more
wiley   +1 more source

Comparison of Triply Periodic Minimal Surface Energy Absorbers Under Uniaxial Compressive Loading

Advanced Engineering Materials, EarlyView.
This study investigates LCD 3D printed Triply Periodic Minimal Surface (TPMS) structures as mechanical energy absorbers. By comparing various base designs and layered combinations under uniaxial compression, it identifies that a Diamond‐Gyroid sandwich structure offers superior performance.
Sergej Grednev, Noah‐Lean Roschlaub, Anne Jung   +2 more
wiley   +1 more source

Support Vector Machines for Credit Scoring: a performance comparison between classical Machine Learning and Quantum-enhanced approach [PDF]

Risk Management Magazine
The objective of this paper is to demonstrate that traditional statistical problems in credit scoring can be solved efficiently by implementing a quantum-enhanced version of the traditional Support Vector Machines algorithm.
Mattia Bacigalupo , Pier Giuseppe Giribone   +1 more
doaj   +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
Suykens, Johan, Vandewalle, Joos, De Moor, Bart, Van Gestel, Tony, Vanthienen, Jan, Baesens, Bart, Dedene, Guido, Viaene, Stijn   +7 more
core  

Extending twin support vector machine classifier for multi-category classification problems [PDF]

, 2013
© 2013 – IOS Press and the authors. All rights reservedTwin support vector machine classifier (TWSVM) was proposed by Jayadeva et al., which was used for binary classification problems.
Liu, X, Xie, J, Gao, X, Shi, Y, Hone, K, Xie, W   +5 more
core   +1 more source