Zobrazeno 1 - 10
of 57
pro vyhledávání: '"MinSeung Kim"'
Publikováno v:
Sensors, Vol 24, Iss 12, p 3979 (2024)
A multichannel speech enhancement system usually consists of spatial filters such as adaptive beamformers followed by postfilters, which suppress remaining noise. Accurate estimation of the power spectral density (PSD) of the residual noise is crucia
Externí odkaz:
https://doaj.org/article/56ea3e1c93844ddbb5e06062996cb863
Autor:
Minseung Kim, Jaehyun Kim
Publikováno v:
Annals of Pediatric Endocrinology & Metabolism, Vol 27, Iss 4, Pp 289-299 (2022)
Purpose Data regarding cardiometabolic risk factors (CMRFs) and metabolic syndrome (MetS) by body mass index (BMI) category in Korean youth are sparse. Methods Among the participants of the Korea National Health and Nutrition Examination Survey 2007
Externí odkaz:
https://doaj.org/article/a7d486d0042c458696dc29f66cefad0c
Publikováno v:
Energies, Vol 17, Iss 4, p 940 (2024)
DC transformers have emerged as essential devices for medium voltage DC (MVDC)-low voltage DC (LVDC) distribution systems. However, conventional step-down single-level converters have limits on the voltage level of the MVDC-LVDC distribution system.
Externí odkaz:
https://doaj.org/article/1f05bc99968048b98db500f1766f07e2
Publikováno v:
IEEE Access, Vol 10, Pp 119283-119289 (2022)
The Conformer has shown impressive performance for speech enhancement by exploiting the local and global contextual information, although it requires high computational complexity and many parameters. Recently, multi-layer perceptron (MLP)-based mode
Externí odkaz:
https://doaj.org/article/29f4768d2a2c47e89fdc5742d854d6b4
Publikováno v:
Sensors, Vol 23, Iss 1, p 111 (2022)
Online multi-microphone speech enhancement aims to extract target speech from multiple noisy inputs by exploiting the spatial information as well as the spectro-temporal characteristics with low latency. Acoustic parameters such as the acoustic trans
Externí odkaz:
https://doaj.org/article/e82c44a92ffc49adbb6168c1293b7b4b
Autor:
Richard Bradley, Ilias Tagkopoulos, Minseung Kim, Yiannis Kokkinos, Theodoros Panagiotakos, James Kennedy, Geert De Meyer, Phillip Watson, Jonathan Elliott
Publikováno v:
Journal of Veterinary Internal Medicine, Vol 33, Iss 6, Pp 2644-2656 (2019)
Abstract Background Advanced machine learning methods combined with large sets of health screening data provide opportunities for diagnostic value in human and veterinary medicine. Hypothesis/Objectives To derive a model to predict the risk of cats d
Externí odkaz:
https://doaj.org/article/f4f8f76e776146099467a078cb594ead
Autor:
Ameen Eetemadi, Navneet Rai, Beatriz Merchel Piovesan Pereira, Minseung Kim, Harold Schmitz, Ilias Tagkopoulos
Publikováno v:
Frontiers in Microbiology, Vol 11 (2020)
Food and human health are inextricably linked. As such, revolutionary impacts on health have been derived from advances in the production and distribution of food relating to food safety and fortification with micronutrients. During the past two deca
Externí odkaz:
https://doaj.org/article/9af075fa77a049c5a56361306f0ea81e
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-12 (2018)
How reproducible evolutionary processes are remains an important question in evolutionary biology. Here, the authors compile a compendium of more than 15,000 mutation events for Escherichia coli under 178 distinct environmental settings, and develop
Externí odkaz:
https://doaj.org/article/3d716d97abf6460ea0ada536a16d3e36
Publikováno v:
Nature Communications, Vol 7, Iss 1, Pp 1-12 (2016)
Multi-omics data integration is a great challenge. Here, the authors compile a database of E. coliproteomics, transcriptomics, metabolomics and fluxomics data to train models of recurrent neural network and constrained regression, enabling prediction
Externí odkaz:
https://doaj.org/article/99ed3ae0d5e148ff8d397f4572e0ceba
Publikováno v:
PLoS Computational Biology, Vol 13, Iss 9, p e1005661 (2017)
Protein inference, the identification of the protein set that is the origin of a given peptide profile, is a fundamental challenge in proteomics. We present DeepPep, a deep-convolutional neural network framework that predicts the protein set from a p
Externí odkaz:
https://doaj.org/article/e019d5a703044174a43ea6dd8ff552df