Results 251 to 260 of about 14,502,685 (316)

International Classification of Functioning-Based Analysis of Activity Limitations and Participation in Hospitalized Elderly Patients in Poland: A Cross-Sectional Study. [PDF]

Med Sci Monit
Wiśniowska-Szurlej A, Brożonowicz J, Wilmowska-Pietruszyńska A, Sozański B, Hernández-Lázaro H, Sozańska A.   +5 more
europepmc   +1 more source

Structure-in-Void Quasi-Bound State in the Continuum Metasurface for Deeply Subwavelength Nanostructure Metrology. [PDF]

ACS Nano
Bijloo F, den Boef AJ, Kraus PM, Koenderink AF.   +3 more
europepmc   +1 more source

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Surrogate Sample-Assisted Particle Swarm Optimization for Feature Selection on High-Dimensional Data

IEEE Transactions on Evolutionary Computation, 2023
With the increase of the number of features and the sample size, existing feature selection (FS) methods based on evolutionary optimization still face challenges such as the “curse of dimensionality” and the high computational cost.
Xianfang Song, Yong Zhang, Dunwei Gong, Hui Liu, Wan-qiu Zhang   +4 more
semanticscholar   +1 more source

Sampling and interpolation in two dimensions

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
The aim of this paper is to consider the interpretation of limited data sets to represent functions which are bandlimited. It is shown that limited data leads to a degree of non-uniqueness of interpolation and extrapolation that only the imposition of a priori constraints can reduce.
B. Cochrane, K. P. Dawson, Michael A. Fiddy, Trevor J. Hall   +3 more
openaire   +1 more source

Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample

IEEE Transactions on Industrial Informatics, 2020
Massive volumes of data are needed for deep learning (DL) models to provide accurate diagnosis results. Numerous studies of fault diagnosis systems have demonstrated the effectiveness of DL models over shallow machine learning (SL) in terms of feature ...
S. R. Saufi, Z. Ahmad, M. Leong, M. H. Lim   +3 more
semanticscholar   +1 more source

Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017.

Science Bulletin, 2019
2019 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved. As the world strives to reduce the impact of population growth, urbanization, agricultural expansion, and climate change on food security, energy and water
P. Gong, Han Liu, Meinan Zhang, Congcong Li, Jie Wang, Huabing Huang, N. Clinton, Luyan Ji, Wenyu Li, Yuqi Bai, Bin Chen, Bing Xu, Zhiliang Zhu, Cui Yuan, Hoi Ping Suen, Jing Guo, Nan Xu, Weijia Li, Yuanyuan Zhao, Jun Yang, Chaoqing Yu, Xi Wang, H. Fu, Le Yu, I. Dronova, Fengming Hui, X. Cheng, Xueli Shi, Fengjin Xiao, Qiufeng Liu, Lianchun Song   +30 more
semanticscholar   +1 more source

Variational Autoencoder-Based Dimensionality Reduction for High-Dimensional Small-Sample Data Classification

International Journal of Computational Intelligence and Applications, 2020
Classification problems in which the number of features (dimensions) is unduly higher than the number of samples (observations) is an essential research and application area in a variety of domains, especially in computational biology.
M.S. Mahmud, J. Huang, Xianghua Fu
semanticscholar   +1 more source

Renormalized multicanonical sampling in multiple dimensions

Physical Review E, 2016
This paper extends to two and three dimensions the recently proposed renormalized multicanonical sampling procedure [D. Yevick, Int. J. Mod. Phys. C 27, 1650033 (2016)IJMPEO0129-183110.1142/S0129183116500339], which generates the density of states of a system from that of a smaller system.
Yong Hwan, Lee, David, Yevick
openaire   +2 more sources

S-Trap, an Ultrafast Sample-Preparation Approach for Shotgun Proteomics.

Journal of Proteome Research, 2018
The success of shotgun proteomic analysis depends largely on how samples are prepared. Current approaches (such as those that are gel-, solution-, or filter-based), although being extensively employed in the field, are time-consuming and less effective ...
Milkessa HaileMariam, R. V. Eguez, Harinder Singh, S. Bekele, G. Ameni, R. Pieper, Yanbao Yu   +6 more
semanticscholar   +1 more source

Data Sample Dimensionality Reduction Using a Modified Autoencoder

Bionics of Intelligence
The article examines the optimization of the dimensionality reduction process for medical data samples using a modified autoencoder. The proposed approach involves preliminary data processing through the autoencoder to extract the most informative ...
N. Miroshnychenko, I.G. I.G, Perova
semanticscholar   +1 more source