A5061864292- Human Mobility and Location-Based Analysis
- Advanced Text Analysis Techniques
- Advanced Algorithms and Applications
- Impact of Light on Environment and Health
- Data-Driven Disease Surveillance
- Distributed and Parallel Computing Systems
- Speech and Audio Processing
- COVID-19 epidemiological studies
- Opinion Dynamics and Social Influence
- Blind Source Separation Techniques
- Complex Network Analysis Techniques
- Web visibility and informetrics
- Wastewater Treatment and Nitrogen Removal
- Opportunistic and Delay-Tolerant Networks
- Tropical and Extratropical Cyclones Research
- Vascular Malformations and Hemangiomas
- Advanced Graph Neural Networks
- Occupational Health and Safety Research
- Optimal Power Flow Distribution
- Misinformation and Its Impacts
- Embedded Systems and FPGA Design
- Safety Systems Engineering in Autonomy
- Computational and Text Analysis Methods
- Systemic Sclerosis and Related Diseases
- Smart Cities and Technologies
Zhengzhou University
2024
Wuhan University
2002-2023
C-Com Satellite Systems (Canada)
2023
PLA Army Engineering University
2006-2022
Southwest University
2021
First Affiliated Hospital of Jinan University
2018
China Institute Of Communications
2010
Abstract The intermittency and randomness of distributed energy resources (DER) present challenges to power system stability. Virtual Power Plants (VPPs) address this by coordinating internal resources, reducing imbalance risks, improving economic efficiency. This paper introduces a two-stage VPPs scheduling model using sequence-to-sequence(seq2seq) with an Attention mechanism for rolling error correction renewable output. Aggregating flexible such as electric vehicles (EV) hydrogen storage...
The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape Artificial Intelligence (AI). These models are now foundational to a wide range applications, including conversational AI, recommendation systems, autonomous driving, content generation, medical diagnostics, scientific discovery. However, widespread deployment also exposes them significant safety risks, raising concerns about...
In June 4, 2020, Corona Virus Disease 2019(COVID-19) cases in Wuhan were cleared, and the epidemic situation was basically controlled. Such public safety infectious disease includes influences great pressure on national economy. At present, some countries regions world are still situation, there is an urgent need to judge infection travel risk region. a relatively fine scale down perceive surrounding then rational zoning decisions promote resumption of production work. this study, indicators...
The online public opinion is the sum of views, attitudes and emotions spread on major health emergencies through Internet, which maps out scope influence disaster situation events in real space. Based multi-source data COVID-19 context a global pandemic, this paper analyzes propagation rules disasters coupling spatial dimension geographic reality network opinion, constructs new gravity model-complex network-based model evolution chain typical events. strength that it quantifies extent impact...
The urban structure is the spatial reflection of various economic and cultural factors acting on territory. Different from physical structure, closely related to population mobility. Taxi trajectories are widely distributed, completely spontaneous, travel needs, massive in data volume. Mining it not only can help us better understand flow pattern a city, but also provides new perspective for interpreting structure. On basis taxi trajectory Chengdu, we introduce network science approach...
Osmotic power generation has emerged as an advanced technology toward water-energy nexus to tackle global water pollution. It provides a sustainable use of salinity gradient from resources yet encounters major obstacles caused by pressure-retarded osmosis (PRO) membrane fouling. Although membranes with good antifouling properties are widely studied, their functions readily lost when scratches or detachments occur through physical damage during operation and chemical degradation corrosive...
Purpose This study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) provide the graph (KG) comprehensively systematically. By presenting relationship among content, discipline, author, this focuses on providing services for discovery documents. Design/methodology/approach compiles STDBS designs a mining visualization framework. The authors define summaries' entities, attributes, relationships representation, use deep learning...
Former complex network models focused on preferential attachment to get scale-free feature, lacking random connection mechanism that inevitably exists in real-life network. In this paper, we deeply study one new model, named the Preferential-Random by introducing rand om evolving procedure of BA model. The analysis and experiment results show model is better keeping with real networks, which reveals closer ties between neighbors as well obvious small world feature. Significantly, explains...
The comments of government social media contain a lot netizens' opinions. To extract opinions quickly and accurately, this poster used BiLSTM-CRF model. verify the effectiveness model, selected microblog "China Police Online", crawled trained model on basis manual annotation. Then was to identify netizens from large number comments. experiment showed that effective could accomplish task extracting microblog.
In non-cooperative scenarios, mining spectrum monitoring data to sort electromagnetic signals is significant for communication behavior detection, network topology inference, countermeasure, etc. To overcome the obstacle of signal reconnaissance from frequency hopping, this paper proposes a sorting algorithm based on by clustering physical layer features with adaptive DBSCAN. Firstly, we analyze hopping properties and operational mode. Then, mine extract signal, without prior knowledge about...
Dual-Path RNN(DPRNN) has achieved great progress in single-channel speech separation. However, RNN-based model needs to pass information through intermediate states and it does not allow parallel computing. Meanwhile, inter-chunk modeling of DPRNN only modeled between multiples the chunk length, which means underutilization contextual information. To address these problems, we propose a multi-scale dual-path temporal convolutional network, DPTCN-ATPP. DPTCN-ATPP utilizes stacked...
Abstract Children’s books involve a large number of topics. Research on them has been paid much attention to by both scholars and practitioners. However, the existing achievements do not focus China, which is fastest growing market for children’s in world. Studies using quantitative analysis are low number, especially intellectual structure, evolution patterns, development trends topics bestsellers China. Dangdang.com , biggest Chinese online bookstore, was chosen as data source obtain...
With the development of embedded Real- Time Operation System(RTOS), researches on how to improve performance and efficiency RTOS are hot nowadays. Big programs often composed several traffic modules while communication between them has close concern with system efficiency. In this paper, a new model for multi-tasks in VxWorks operation is proposed which based UDP transmit mode concept virtual device. It overcomes shortages traditional theory satisfies real-time as well resource requirement....
Abstract It has been challenging to separate the time-frequency (TF) overlapped wireless communication signals with unknown number of sources in underdetermined cases. To address this issue, a novel blind separation strategy based on TF soft mask is proposed paper. Based clustering property sparse domain, angular probability density distribution obtained by kernel estimation (KDE) algorithm, and then source identified detecting peak points distribution. Afterwards, contribution degree...