A5034548901- Advanced Data and IoT Technologies
- MicroRNA in disease regulation
- Wireless Signal Modulation Classification
- Image Processing Techniques and Applications
- Robotics and Sensor-Based Localization
- Circular RNAs in diseases
- Advanced Image and Video Retrieval Techniques
- Radar Systems and Signal Processing
- Neural Networks and Applications
- Satellite Communication Systems
- Pharmacological Effects and Toxicity Studies
- Opportunistic and Delay-Tolerant Networks
- Vitamin D Research Studies
- Distributed Sensor Networks and Detection Algorithms
- Time Series Analysis and Forecasting
- Tryptophan and brain disorders
- Cancer-related molecular mechanisms research
- Cognitive Radio Networks and Spectrum Sensing
- Gait Recognition and Analysis
- Indoor and Outdoor Localization Technologies
- UAV Applications and Optimization
- Advanced SAR Imaging Techniques
Jiangxi Provincial Children's Hospital
2025
Guizhou Normal University
2021-2024
Second Xiangya Hospital of Central South University
2014
Central South University
2014
Hepatocellular carcinoma (HCC) is a prevalent primary liver malignancy and leading cause of cancer-related mortality worldwide. Despite advancements in therapeutic strategies, the 5-year survival rate for individuals undergoing curative resection remains between 10% 15%. Consequently, identifying molecular targets that specifically inhibit proliferation metastasis HCC cells critical improving treatment outcomes. Database analysis using Targetscan identified complementary binding sites...
Abstract To solve the problem of bit error rate (BER) performance degradation over strong solar wind turbulence channel, this paper addresses to Gaussian minimum frequency shift keying (GMSK) demodulation using machine learning. First, by analyzing scintillation characteristics telemetry signal caused during superior conjunction, K distribution channel model is innovatively established channel. Then, approximate probability density function studied Laguerre orthogonal polynomial for...
In a cognitive satellite network (CSN) with GEO and LEO satellites, there is large propagation losses between the sensing ground station. The results of spectrum from single may be inaccurate, which will create serious interference in primary system. Cooperative (CSS) has become key technology for solving above problems recent years. However, most current CSS techniques are model-driven. They difficult to model implement CSNs since their detection performance strongly dependent on an assumed...
Abstract The radar cross section (RCS) is an important parameter that reflects the scattering characteristics of targets. Based on monostatic RCS time series' statistical features by sliding window segmentation, a novel window‐statistical‐gated recurrent unit (SW‐S‐GRU) method for target recognition (RTR) proposed using GRU. divides series into many segments obtaining as input deeper are extracted from segmented and then classified Under model precession motion, simulation results show...
Abstract Statistical features are commonly used in radar target recognition tasks using cross section as the data source. The traditional statistical feature extraction way may not make better use of information, making classification results slightly worse. Here, a new sliding window segmentation method is proposed for extracting to improve accuracy task and investigate separability extracted after segmentation. show that by our than other ways. BP neural network, SVM KNN algorithms...
Distributed unmanned combat is a new style shaping future information warfare, for which network communication crucial. This study constructed the star topology of LTE-based distributed platform against background using vehicles in combat. The performances vehicle and LTE wireless base station under are simulated analyzed discrete-event simulator NS3. results show that structure adaptable network; uplink downlink performance indicators reach high level; data can be transmitted effectively.