A5110376950- Traffic and Road Safety
- Bullying, Victimization, and Aggression
- Youth Development and Social Support
- Traffic Prediction and Management Techniques
- Urban Transport and Accessibility
- Child and Adolescent Psychosocial and Emotional Development
- Injury Epidemiology and Prevention
- Wireless Signal Modulation Classification
- Substance Abuse Treatment and Outcomes
- Chemical Synthesis and Analysis
- Air Quality Monitoring and Forecasting
- Machine Learning in Bioinformatics
- Magnetic Properties and Synthesis of Ferrites
- Magnetic Properties and Applications
- Machine Learning in Materials Science
- Sleep and Work-Related Fatigue
- Impact of Technology on Adolescents
- Computational Drug Discovery Methods
- Magneto-Optical Properties and Applications
- Child Development and Digital Technology
Northeastern University
2025
Southeast University
2019-2024
Hangzhou Dianzi University
2014
Taipei Municipal Jen-Ai Hospital
2009
To address the issue of inaccurate load forecasting amidst advancing smart grid technology and widespread integration various demand-side resources like controllable loads, distributed energy sources, storage, author proposes a deep confidence network based on improved algorithms for demand forecasting. Firstly, VMD algorithm is used to decompose data into different intrinsic mode functions (IMFs), Then combine DBN predict each IMF, Finally, overlay prediction results part obtain VMD-DBN...
Objective: The present case-control study sought to explore at-risk riding behaviors associated with e-bike related traffic crashes among riders in China.Methods: Cases were recruited from residents aged 16 years and over communities which stated “selected e-bikes as travel tools experienced the last year”. Two controls for each case randomly selected a population of who had not crash past year. cases matched by gender, age (within 5 years) school education level. Data collected using...
Objectives: This study was conducted to estimate road traffic deaths and forecast short-term in China using the Elman recurrent neural network (ERNN) model.Methods: An ERNN model developed reported police data of from 2000 2017. Different numbers neurons hidden layer were tested different combinations subgroup datasets have been used develop optimal after normalization. The mean absolute error (MAE), root square (RMSE), percentage (MAPE) measures deviation between predicted observed values....
This research aimed to identify risk factors including individual characteristics and environment circumstances related different types of school bullying (physical, relational, verbal, sexual, possession bullying) among middle students in China. Cases were the respondents reporting perpetrating behaviors three or more times past year. One control was selected for each case from those participants who not involved 12 months. Data collected between April 2019 May After considering potential...
There has been a significant amount of research on correlates bullying victimization, but most prior studies are descriptive and do not distinguish between different types bullying. The current study used case-control design to explore factors related including physical, relational, verbal, sexual, property, poly-bullying victimization. This was conducted in southern city China, 3054 cases who self-reported being victims school controls reported involved any the past 12 months. Each victim...