Results 51 to 60 of about 257 (142)

Clinical Aspects and Prognosis Evaluation of Cirrhotic Patients Hospitalized with Acute Kidney Injury

Canadian Journal of Gastroenterology and Hepatology, Volume 2019, Issue 1, 2019., 2019
Background. Acute kidney injury occurs in approximately 20% of hospitalized cirrhotic patients. Mortality is estimated at 60% within a month and 65% within a year. Aims. To evaluate survival in 30 days and in 3 months of cirrhotic patients hospitalized with acute kidney injury, identifying factors associated with mortality. Methods.
Célio Geraldo de Oliveira Gomes, Marcus Vinicius Melo de Andrade, Ludmila Resende Guedes, Henrique Carvalho Rocha, Roberto Gardone Guimarães, Fernando Antônio Castro Carvalho, Eduardo Garcia Vilela, Quirino Lai   +7 more
wiley   +1 more source

A Novel Method of Pure Output Modal Identification Based on Multivariate Variational Mode Decomposition

Structural Control and Health Monitoring, Volume 2024, Issue 1, 2024.
This paper proposes a novel parameterized frequency‐domain modal parameter identification method, called direct modal variational mode decomposition (DMVMD), based on the multivariate variational mode decomposition (MVMD) framework and the principle of modal superposition. Under the constraint of normalized mode shapes, this paper theoretically derives
Tao Li, Rui Hou, Kangkang Zheng, Lingfeng Li, Bo Liu, Chia-Ming Chang   +5 more
wiley   +1 more source

A Multisource Uncertainty Fusion Reliability Evaluation Method for the Control Rod Drive Mechanism of Nuclear Power Plants

International Journal of Energy Research, Volume 2024, Issue 1, 2024.
The reliability of a pressurized water reactor power plant’s control rod drive mechanism (CRDM) is affected by many factors, such as operation states, unit performance, and dynamic environments. Multiple sources of uncertainties, including random, interval, and fuzzy, exist when analyzing the reliability of CRDMs.
Zhihu Gao, Bo Sun, Zeyu Wu, Yang Xi, Qiang Feng, Zili Wang, Yeli Zhou, Junlin Pan, Jiankun Xu, Chaofan Sun   +9 more
wiley   +1 more source

Deep learning hybrid models with multivariate variational mode decomposition for estimating daily solar radiation

Alexandria Engineering Journal
Solar energy is one of the renewable and clean energy sources. Accurate solar radiation (SR) estimates are therefore needed in solar energy applications.
Shahab S. Band, Sultan Noman Qasem, Rasoul Ameri, Hao-Ting Pai, Brij B. Gupta, Saeid Mehdizadeh, Amir Mosavi   +6 more
doaj   +1 more source

Intelligent Bearing Fault Diagnosis Based on Multivariate Symmetrized Dot Pattern and LEG Transformer

Machines, 2022
Deep learning based on vibration signal image representation has proven to be effective for the intelligent fault diagnosis of bearings. However, previous studies have focused primarily on dealing with single-channel vibration signal processing, which ...
Bin Pang, Jiaxun Liang, Han Liu, Jiahao Dong, Zhenli Xu, Xin Zhao   +5 more
doaj   +1 more source

Bearing Fault Prediction Based on Mixed Domain Features and GWO‐SVM

Journal of Electrical and Computer Engineering, Volume 2024, Issue 1, 2024.
The rotating machinery is composed of rolling bearing connection, so the fault identification of rolling bearing is a very critical task. We propose a bearing fault identification algorithm based on grey wolf optimizer (GWO) to address the common problems of high signal noise, inability of a single indicator to accurately reflect the true state of ...
Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao, Antonio J. Marques Cardoso   +7 more
wiley   +1 more source

A customised 1D-CNN for recognition of freezing of gait in Parkinson’s disease using multivariate decomposition techniques

Open Computer Science
The freezing of gait (FoG) presents a sudden challenge in sustaining movement which becomes a common gait issue in people with later stages of Parkinson’s disease (PD). FoG often results in falls that reduces the individual’s impact on life.
Rajendran Nancy, Selvaraj Thomas G., Pennagaram Krushnakumar Kalkeseetharaman, Ashwala Ravi T., Muthu Sinnasamy Pandian Subathra   +4 more
doaj   +1 more source

Enhanced Deep Representation Learning Extreme Learning Machines for EV Charging Load Forecasting by Improved Artemisinin Optimization and Multivariate Variational Mode Decomposition

Energies
The Electric Vehicle (EV) industry is developing rapidly, and EVs are becoming an increasingly important choice for the future of transportation. Therefore, accurately forecasting the electricity demand for EVs is crucial.
Anjie Zhong, Honghai Li, Zhongyi Tang, Zhirong Zhang   +3 more
doaj   +1 more source

Short-Term Load Forecasting for a Renewable-Rich Power System Using an IMVMD-XLSTM

Energies
The high penetration of photovoltaic and wind power introduces strong non-stationarity and multi-scale fluctuations into power system load profiles, challenging the accuracy of short-term load forecasting (STLF).
Qiujing Lin, Hongquan Zhu, Xiaolong Wang, Xiangang Peng   +3 more
doaj   +1 more source

Fault diagnosis method using MVMD signal reconstruction and MMDE-GNDO feature extraction and MPA-SVM

Frontiers in Physics
To achieve a comprehensive and accurate diagnosis of faults in rolling bearings, a method for diagnosing rolling bearing faults has been proposed.
Min Mao, Chengjiang Zhou, Bingwei Xu, Dongjin Liao, Jingzong Yang, Shuangyao Liu, Yiqing Li, Tong Tang   +7 more
doaj   +1 more source