A5034843347- Advanced machining processes and optimization
- Advanced Surface Polishing Techniques
- Advanced Machining and Optimization Techniques
- Additive Manufacturing Materials and Processes
- Welding Techniques and Residual Stresses
- Additive Manufacturing and 3D Printing Technologies
- Metallurgy and Material Forming
- Metal Alloys Wear and Properties
- Tunneling and Rock Mechanics
- High Entropy Alloys Studies
- AI in cancer detection
- Mathematical Dynamics and Fractals
- Metal Forming Simulation Techniques
- Chaos control and synchronization
- Advanced Measurement and Metrology Techniques
- Injection Molding Process and Properties
- Manufacturing Process and Optimization
- Remote Sensing in Agriculture
- Domain Adaptation and Few-Shot Learning
- Non-Destructive Testing Techniques
- Laser and Thermal Forming Techniques
- Anomaly Detection Techniques and Applications
- Erosion and Abrasive Machining
- Educational Technology and Pedagogy
- Nonlinear Dynamics and Pattern Formation
Shandong University
2016-2025
Northeastern University
2024-2025
Shandong Jianzhu University
2017-2024
Xi’an Jiaotong-Liverpool University
2021-2024
Beijing Children’s Hospital
2024
Capital Medical University
2024
China University of Geosciences
2007-2024
Zhejiang Gongshang University
2024
Guangdong Special Equipment Inspection and Research Institute
2024
Shandong Special Equipment Inspection Institute
2024
Yield prediction is of great significance for yield mapping, crop market planning, insurance, and harvest management. Remote sensing becoming increasingly important in prediction. Based on remote data, progress has been made this field by using machine learning, especially the Deep Learning (DL) method, including Convolutional Neural Network (CNN) or Long Short-Term Memory (LSTM). Recent experiments area suggested that CNN can explore more spatial features LSTM ability to reveal phenological...
In this work, the tensile behavior and microhardness of 316L stainless steel fabricated by selective laser melting under different process parameters were investigated. The ultimate strength decreased slightly with increasing energy input, while opposite tendency was observed for elongation to failure. Microstructure characterizations performed relate pore morphology, pool geometry, solidification cell structure, grain sizes mechanical performance as-built samples. Fine grains high fraction...
Accurate and timely estimation of crop yield at a small scale is great significance to food security harvest management. Recent studies have proven remote sensing an efficient method for machine learning, especially deep can infer good prediction by integrating multisource datasets such as satellite data, climate soil so on. However, there are some bottleneck challenges improve accuracy. First, the popular data used fall into two major groups-time-series constant data. Surprisingly little...
Single-source domain generalization (SDG) in medical image segmentation is a challenging yet essential task as shifts are quite common among clinical datasets. Previous attempts most conduct global-only/random augmentation. Their augmented samples usually insufficient diversity and informativeness, thus failing to cover the possible target distribution. In this paper, we rethink data augmentation strategy for SDG segmentation. Motivated by class-level representation invariance style...
In this work, multi-criteria decision-making (MCDM) techniques namely the additive ratio assessment (ARAS) method and combinative distance-based (CODAS) are applied for predicting automobile radiator performance under 27 different operating conditions using multiwall carbon nanotubes (MWCNTs)- based nanofluid. The (MWCNTs) – SG-based nanofluids were prepared at concentrations of 0.2, 0.4, 0.6 vol %. Thermal transport properties density, specific heat capacity, thermal conductivity, viscosity...
We consider the problem of volumetric (3D) unsupervised domain adaptation (UDA) in cross-modality medical image segmentation, aiming to perform segmentation on unannotated target (e.g. MRI) with help labeled source CT). Previous UDA methods analysis usually suffer from two challenges: 1) they focus processing and analyzing data at 2D level only, thus missing semantic information depth level; 2) one-to-one mapping is adopted during style-transfer process, leading insufficient alignment...
The purpose of this study is to evaluate the sustainability indicators aluminium hybrid composite material (AA6082 + 3wt%SiC+1wt .%MoS2) under different eco-friendly cooling strategies such as dry, MQL, LCO2, MQL LCO2. A variety social, economic, and environmental aspects Total cycle time (TTCT), productivity, machining cost (CT) Energy consumption (Ec), Carbon emission analysis (Cee), Cutting force (CF) Surface Roughness (Ra) are considered in study. novel sustainable approach overall...
Aluminium hybrid metal matrix composites have significantly increased in many advanced applications owing to their unique properties. However, these are difficult machine because of hard reinforcements the matrix. After identifying optimum cutting conditions, it's crucial identify tool wear mechanisms keep surface roughness within desired range, especially with composites. Hence, present work mainly focuses on mechanism PVD-coated TiAlN inserts during end milling Al 6082 MQL, CO2, and a...
The coral reef geomorphic zone classification (CRGZC) map can provide a wealth of information for coastal management and protection. Remote sensing plays an important role in CRGZC by virtue its speed, wide range, low cost. Although many excellent results have been achieved this field, there are still some shortcomings. With the development machine learning, such methods gradually introduced to CRGZC, yet research application deep learning relatively few. In paper, based on ICESat-2 data...