Results 141 to 150 of about 2,188,345 (345)

Even-hole-free graphs [PDF]

, 2008
In this thesis we consider the class of simple graphs defined by excluding even holes (i.e. chordless cycles of even length). These graphs are known as even-hole-free graphs. We first prove that every even-hole-free graph has a node whose neighborhood is
Da Silva, Murilo Vicente Gonçalves
core  

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

New Theoretical Insights and Algorithmic Solutions for Reconstructing Score Sequences from Tournament Score Sets

Axioms
The score set of a tournament is defined as the set of its distinct out-degrees. In 1978, Reid proposed the conjecture that for any set of nonnegative integers D, there exists a tournament T with a score set D.
Bowen Liu, Jiashu Wang, Boris Melnikov
doaj   +1 more source

Comparative study for broadband direction of arrival estimation techniques

, 2012
This paper reviews and compares three different linear algebraic signal subspace techniques for broadband direction of arrival estimation --- (i) the coherent signal subspace approach, (ii) eigenanalysis of the parameterised spatial correlation matrix ...
Weiss, Stephan, Hussin, Mohammed Nuri, Lambotharan, Sangarapillai, Alrmah, Mohamed Abubaker   +3 more
core  

Polynomial approach to discrete-time adaptive control: Software implementation for industrial application [PDF]

, 2015
The main aim of this paper is to present a preliminary industrial software implementation of selected discrete-time adaptive control algorithms into the Matlab and Pascal environment.
Matušů, Radek, Prokop, Roman, Pekař, Libor   +2 more
core  

A Polynomial Time Algorithm For 0-1 Integer Linear Programmings

, 2023
A polynomial-time algorithm for 0-1 integer linear programmings has been proposed. This method continues the classic idea of solving ILP with its LP relaxation. The innovation is that every constraint in the LP is reconstructed into a strong cut.
Zhang, G. Q.
core  

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

RSU deployment planning based on approximation algorithm in urban VANET

Tongxin xuebao, 2018
To minimize the number of RSU deployed to cover a specific area,a c street model transforming the area covering problem to streets covering problem was designed,and a greedy-based polynomial (GBP) time approximation algorithm was developed to obtain the ...
Junyu ZHU, Chuanhe HUANG, Xiying FAN, Kuangyu QIN, Bin FU   +4 more
doaj   +2 more sources

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source