A5026281370- Statistical Methods and Inference
- Advanced Statistical Methods and Models
- Statistical Methods and Bayesian Inference
- Traditional Chinese Medicine Studies
- Biomedical Text Mining and Ontologies
- Water Quality Monitoring and Analysis
- Advanced Neuroimaging Techniques and Applications
- Advanced Algorithms and Applications
- Insurance, Mortality, Demography, Risk Management
- Anomaly Detection Techniques and Applications
- Machine Learning in Healthcare
- Infrastructure Maintenance and Monitoring
- Advanced Chemical Sensor Technologies
- Carbon Dioxide Capture Technologies
- Pigment Synthesis and Properties
- Spectroscopy and Chemometric Analyses
- Chemical Looping and Thermochemical Processes
- Adsorption and Cooling Systems
- Mental Health Research Topics
- Advanced Image and Video Retrieval Techniques
- Bayesian Methods and Mixture Models
- Advanced Neural Network Applications
- Metal-Catalyzed Oxygenation Mechanisms
- Elevator Systems and Control
- Vehicle License Plate Recognition
Jiangsu Normal University
2021-2024
Shandong University
2023-2024
University of Nottingham
2024
Hubei University
2024
Nanjing University of Aeronautics and Astronautics
2024
China University of Geosciences
2022
Hubei University of Chinese Medicine
2020-2022
Xi'an Jiaotong University
2014-2021
East China Normal University
2019-2020
National University of Singapore
2015
Unspecific peroxygenases (UPOs), secreted by fungi, demonstrate versatility in catalyzing challenging selective oxyfunctionalizations. However, the number of and corresponding variants with tailored selectivity for a broader substrate scope is still limited due to lack efficient engineering strategies. In this study, new unspecific peroxygenase from Coprinopsis marcescibilis (CmaUPO) identified characterized. To enhance or reverse enantioselectivity wildtype (WT) CmaUPO catalyzed asymmetric...
Recent research in machine-learning techniques has led to significant progress various fields. In particular, knowledge discovery using this method become a hot topic traditional Chinese medicine. As the key clinical manifestations of patients, symptoms play role diagnosis and treatment, which evidently have their underlying medicine mechanisms.We aimed explore core potential regularity for diagnosing insomnia reveal symptoms, hidden relationships corresponding syndromes.An dataset with 807...
Most deep learning methods used in seismic interpretation aim to identify response anomaly but not geological body. As a small-scale target, the pattern of karst cave is totally different from its called string beads (SBR) Tarim Basin, China. In this paper, we present method using two fully convolutional neural networks detect and predict caves. We firstly design network cave, then use another boundary cave. To train prediction model, propose workflow generate numerous synthetic images by...
Accurate high-temperature measurement is very important for process monitoring of an industrial system. Infrared thermometers usually can handle no more than 1000 °C and should use some expensive accessories higher temperature measurements. This paper proposes a low-cost pyrometry system with nonlinear multisense partial least squares (NMSPLS). The ordinary camera different filters designed to collect the images hot object at wavelengths, NMSPLS presented predicting from obtained images. For...
The unified weighing scheme for the local-linear smoother in analysing functional data can deal with that are dense, sparse or of neither type. In this paper, we focus on convergence rate principal component analysis using method. Almost sure asymptotic consistency and rates estimators eigenvalues eigenfunctions have been established. We also provide variance estimation measurement error. Based results, number observations within each curve be any relative to sample size, which is consistent...
It is known that the redundancy at component level better than system for case of active redundancy. However, few results are available standby due to complexity convolution. This note stochastically compares allocations redundancies in series systems with exponential components versus sense likelihood ratio ordering. The established strengthen and extend some ones literature.
Abstract In this article, we focus on the estimation of varying-coefficient mixed effects models for longitudinal and sparse functional response data, by using generalized least squares method coupling a modified local kernel smoothing technique. This approach provides useful framework that simultaneously takes into account within-subject covariance all observation information in to improve efficiency. We establish both uniform consistency pointwise asymptotic normality proposed estimators...
Quantitative analysis for the flue gas of natural gas-fired generator is significant energy conservation and emission reduction. The traditional partial least squares method may not deal with nonlinear problems effectively. In paper, a extended input based on radial basis function neural network (RBFNN) used components prediction gas. For proposed method, original independent matrix RBFNN outputs hidden layer nodes are extension term matrix. Then, regression performed output to establish...
Medicine representation learning, which aims at uncovering hidden medicine relationships has emerged as a significant technique to imitate doctor’s cognitive reasoning process. The majority of present research focuses on the intuitive between medication and diagnosis, however, ignores inherent properties medicines. This study uses heterogeneous graph convolutional network (HGCN) spectral clustering (SC) algorithm investigate associated knowledge underlying clinical treatment. Based chronic...
Variables selection based on information tree for spectroscopy quantitative analysis.
A pedestrian re-identification(Re-ID) model based on joint learning method is proposed. This paper proposed a two-branch including global feature branch and branch. The uses the spatial pyramid pooling to average local informations of image increase information different receptive fields. dynamical distance optimization algorithm without additional information. Experimental results public datasets show that can effectively learn features for Re-ID outperforms existing basic person...