A5091644203- Wireless Signal Modulation Classification
- Autonomous Vehicle Technology and Safety
- Millimeter-Wave Propagation and Modeling
- Network Security and Intrusion Detection
- Anomaly Detection Techniques and Applications
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- UAV Applications and Optimization
- Infrastructure Maintenance and Monitoring
- Power Transformer Diagnostics and Insulation
- COVID-19 epidemiological studies
- Marine and coastal ecosystems
- Medical Imaging and Analysis
- Radar Systems and Signal Processing
- COVID-19 diagnosis using AI
- Digital Media Forensic Detection
- Fault Detection and Control Systems
- Wireless Communication Security Techniques
- Face recognition and analysis
- Energy Load and Power Forecasting
- Augmented Reality Applications
- Advanced SAR Imaging Techniques
- Artificial Intelligence in Healthcare and Education
- Microfluidic and Bio-sensing Technologies
- Advanced MIMO Systems Optimization
Shandong Management University
2023-2025
Shandong University
2020-2021
The Intrusion Detection System (IDS) is an effective tool utilized in cybersecurity systems to detect and identify intrusion attacks. With the increasing volume of data generation, possibility various forms attacks also increases. Feature selection crucial often necessary enhance performance. structure dataset can impact efficiency machine learning model. Furthermore, imbalance pose a problem, but sampling approaches help mitigate it. This research aims explore (ML) for IDS, specifically...
Nowadays, automatic modulation classification (AMC) has become a key component of next-generation drone communication systems, which are crucial for improving efficiency in non-cooperative environments. The contradiction between the accuracy and current methods hinders practical application AMC systems. In this paper, we propose real-time method based on lightweight mobile radio transformer (MobileRaT). constructed is trained iteratively, accompanied by pruning redundant weights information...
Abstract This paper presents a new Edge-AI algorithm for real-time and multi-feature (social distancing, mask detection, facial temperature) measurement to minimize the spread of COVID-19 among individuals. has extenuated need an intelligent surveillance video system that can monitor status social measure temperature faces simultaneously using deep learning (DL) models. In this research, we utilized fusion three different YOLOv4-tiny object detectors each task integrated system. DL model is...
Artificial Intelligence (AI) and Machine Learning (ML) have experienced rapid growth in both industry academia. However, the current ML AI models demand significant computing processing power to achieve desired accuracy results, often restricting their use high-capability devices. With advancements embedded system technology substantial development Internet of Things (IoT) industry, there is a growing desire integrate techniques into resource-constrained systems for ubiquitous intelligence....
At present, the design of modern vehicles requires improving driving performance while meeting emission standards, leading to increasingly complex power systems. In autonomous systems, accurate, real-time vehicle speed prediction is one key factors in achieving automated driving. Accurate and optimal control based on future speeds are strategies for dealing with ever-changing actual environments. However, predicting driver behavior uncertain may be influenced by surrounding environment, such...
The fault detection of manned submersibles plays a very important role in protecting the safety submersible equipment and personnel. However, diving sensor data is scarce high-dimensional, so this paper proposes method, which made up feature selection module based on hierarchical clustering Autoencoder (AE), improved Deep Convolutional Generative Adversarial Networks (DCGAN)-based augmentation using Neural Network (CNN) with LeNet-5 structure. First, developed to select features that have...
This work focuses on maximizing the sum rate of ultra-reliable low-latency communication (URLLC) systems by leveraging unmanned aerial vehicle-mounted reconfigurable intelligent surface (UAV-RIS) to provide short packet services for users based non-orthogonal multiple access (NOMA) protocol. To optimize system, a joint optimization is performed with respect power allocation, UAV position, decoding order, and RIS phase shifts. As original problem non-convex integer problem, it challenging...
With the frequent occurrence of haze in recent years, air quality has attracted more and public attention. Realtime acquisition can help people to obtain environmental status time avoid pollution exposure. However, confusion sensor system behavior or errors transmission process result missing data. Missing data interpolation (MDI) is task predicting parts dataset. The problem draws difficulties decision-making process, there an urgent need for accurate effective estimation methods impute...
Variations in the quantity of plankton impact entire marine ecosystem. It is great significance to accurately assess dynamic evolution for monitoring environment and global climate change. In this paper, a novel method introduced deep-sea community detection ecosystem using an underwater robotic platform. The videos were sampled at distance 1.5 m from ocean floor, with focal length 1.5–2.5 m. optical flow field used detect community. We showed that each moving do not overlap space two...
Future Unmanned Aerial Vehicle (UAV)-assisted wireless communication systems are expected to utilize wide bandwidths available at terahertz (THz) frequencies enhance system throughput. To compensate for the severe path loss in THz band, it is essential have a multitude of antennas UAV generate narrow beams directional transmission. However, severely limit its spatial coverage, which greatly affects efficiency large-scale access UAV-assisted systems. Moreover, combination massive and large...