Results 81 to 90 of about 111,097 (310)

Analytic Group Kernels and Lie Algebra Kernels [PDF]

Transactions of the American Mathematical Society, 1960
Made available in DSpace on 2014-12-05T21:50:04Z (GMT). No. of bitstreams: 1 0013519.pdf: 4191483 bytes, checksum: 8be73568683b59703b526632ade49bfc (MD5) Previous issue date: 1955 ; Embargo set by: Seth Robbins for item 58849 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs ; Restricted to ...
openaire   +1 more source

Influence of Test Temperature and Test Frequency on Fatigue Life of Aluminum Alloy EN AW‐2618A

Advanced Engineering Materials, EarlyView.
The influence of test temperature and test frequency on the fatigue life of EN AW‐2618A is investigated. High‐cycle fatigue tests are performed at different test temperatures and frequencies on the 1000 h/230°C overaged state. Both test parameters reduce fatigue life due to time‐dependent damage mechanisms.
Ying Han, Julian M. Rosalie, Jan Radners, Mauro Madia, Philipp von Hartrott, Birgit Skrotzki   +5 more
wiley   +1 more source

Parameterized Streaming Algorithms for Vertex Cover [PDF]

, 2014
As graphs continue to grow in size, we seek ways to effectively process such data at scale. The model of streaming graph processing, in which a compact summary is maintained as each edge insertion/deletion is observed, is an attractive one.
Chitnis, Rajesh, Cormode, Graham, Hajiaghayi, MohammadTaghi, Monemizadeh, Morteza   +3 more
core  

Feedback Vertex Set Inspired Kernel for Chordal Vertex Deletion

, 2017
Given a graph $G$ and a parameter $k$, the Chordal Vertex Deletion (CVD) problem asks whether there exists a subset $U\subseteq V(G)$ of size at most $k$ that hits all induced cycles of size at least 4.
Agrawal, Akanksha, Lokshtanov, Daniel, Misra, Pranabendu, Saurabh, Saket, Zehavi, Meirav   +4 more
core   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Hierarchies of Inefficient Kernelizability [PDF]

, 2011
The framework of Bodlaender et al. (ICALP 2008) and Fortnow and Santhanam (STOC 2008) allows us to exclude the existence of polynomial kernels for a range of problems under reasonable complexity-theoretical assumptions.
Hermelin, Danny, Kratsch, Stefan, Sołtys, Karolina, Wahlström, Magnus, Wu, Xi   +4 more
core  

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Kernelization and Parameterized Algorithms for 3-Path Vertex Cover

, 2016
A 3-path vertex cover in a graph is a vertex subset $C$ such that every path of three vertices contains at least one vertex from $C$. The parameterized 3-path vertex cover problem asks whether a graph has a 3-path vertex cover of size at most $k$.
B Brešar, B Brešar, BY Wu, CH Papadimitriou, E Prieto, F Göring, F Kardoš, FV Fomin, H Fermau, J Chen, J Katrenič, J Tu, J Wang, K Asdre, K Cameron, M Xiao, M Xiao, M Xiao, M Yannakakis, MR Fellows, R Boliac, R-W Hung, VE Alekseev, VV Lozin, Y Orlovich   +24 more
core   +1 more source

From Wafers to Electrodes: Transferring Automatic Optical Inspection (AOI) for Multiscale Characterization of Smart Battery Manufacturing

Advanced Functional Materials, EarlyView.
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley   +1 more source

Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?

Advanced Functional Materials, EarlyView.
This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee, Yunseo Kim, Hyeong‐ku Jo, Dongjoon Yoon, Byeonghyeok Im, WonJeong Yu, Eui‐Rim On, Changhwan Lee   +7 more
wiley   +1 more source