Results 111 to 120 of about 9,444,467 (301)

Morphology, Transport, and Dynamics of Protein Adsorption in Open‐Cell Metal Foam

Advanced Engineering Materials, EarlyView.
Stainless steel (SS) open‐cell foams are shown to adsorb more protein per unit area than previously reported 316L SS and chromium oxide surfaces under static and flow conditions. An integrated approach combining 3D pore imaging, flow simulation, and protein adsorption experiments characterizes the foam’s performance.
Chinmaya Prerana Inguva, Joseph Lavoie, Afsaneh Rabiei   +2 more
wiley   +1 more source

Cryogenic Deformation Behavior of TiAl and Insights Into Embrittlement After High‐Temperature Exposure Combined With Secondary Ion Mass Spectroscopy of Near Surface Chemistry

Advanced Engineering Materials, EarlyView.
Near‐surface deuterium enrichment profiles for different microstructural types of TiAl after exposure at 700 °C in a heavy water‐containing environment. The deuterium levels are significantly higher than expected from natural occurrence, indicating that the heavy water dissociated during the exposure treatment and entered the specimens.
Jonathan D. H. Paul, Alexander Welle, Dirk Matthiessen, Michael Oehring, Fritz Appel, Florian Pyczak   +5 more
wiley   +1 more source

Support vector machines and generalisation in HEP

Journal of Physics: Conference Series, 2016
We review the concept of support vector machines (SVMs) and discuss examples of their use. One of the benefits of SVM algorithms, compared with neural networks and decision trees is that they can be less susceptible to over fitting than those other algorithms are to over training. This issue is related to the generalisation of a multivariate algorithm (
Agni Bethani, Adrian J. Bevan, Jon Hays, Tom J. Stevenson   +3 more
openaire   +4 more sources

Impact of Hydrogen Incorporation on Electronic and Magnetic Structure of X2CrNi18‐9 Stainless Steel

Advanced Engineering Materials, EarlyView.
Hydrogen uptake in austenitic stainless steel alters both its electronic and magnetic structure. Seebeck measurements reveal hydrogen‐induced shifts in the electronic density of states, while neutron scattering uncovers nanoscale inhomogeneities that grow upon hydrogen incorporation, with the most pronounced effect observed in the PBF as‐built state ...
Torben Tappe, Louis Becker, Gaurav Kanu, Thomas F. Headen, Dirk Honecker, Gabi Schierning, Santiago Benito, Sebastian Weber, Klara Lünser, Sabrina Disch   +9 more
wiley   +1 more source

Machine learning methods in chemoinformatics [PDF]

, 2014
Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion.
John B. O. Mitchell, Mitchell, J.B.O., Mitchell, J.B.O.; id_orcid   +2 more
core   +1 more source

The Study of Information Security Risk Assessment Based on Support Vector Machine

MATEC Web of Conferences, 2018
This paper establishes an information security evaluation model based on support vector machine by analyzing the factors affecting information security risk assessment.
Xie Haiyan, Wang Ying, Zhang Xianghong
doaj   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

A signal theory approach to support vector classification: the sinc kernel [PDF]

, 2009
Fourier-based regularisation is considered for the support vector machine classification problem over absolutely integrable loss functions. By invoking the modest assumption that the decision function belongs to a Paley–Wiener space, it is shown that the
Nelso, James D.B., Damper, Robert I., Guo, Baofeng, Gunn, Steve R.   +3 more
core   +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, LI Li-juan, DING Ting-ting, LIU Dui   +3 more
doaj  

Support Vector Machine Implementations for Classification & Clustering

BMC Bioinformatics, 2006
Background We describe Support Vector Machine (SVM) applications to classification and clustering of channel current data. SVMs are variational-calculus based methods that are constrained to have structural risk minimization (SRM), i.e., they provide ...
Winters-Hilt Stephen, Yelundur Anil, McChesney Charlie, Landry Matthew   +3 more
doaj   +1 more source