Meng Wang

ORCID: 0000-0003-1272-2054
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About
Contact & Profiles
Research Areas
  • Sentiment Analysis and Opinion Mining
  • Text and Document Classification Technologies
  • Advanced Multi-Objective Optimization Algorithms
  • Random lasers and scattering media
  • Probabilistic and Robust Engineering Design
  • Thermal Radiation and Cooling Technologies
  • Photonic Crystals and Applications
  • Gas Sensing Nanomaterials and Sensors
  • Language, Metaphor, and Cognition
  • Liquid Crystal Research Advancements
  • Transition Metal Oxide Nanomaterials
  • Optimal Experimental Design Methods
  • Bayesian Methods and Mixture Models
  • Traffic Prediction and Management Techniques
  • Stock Market Forecasting Methods
  • Financial Risk and Volatility Modeling
  • Visual Attention and Saliency Detection
  • Image and Video Quality Assessment
  • Statistical Methods and Inference
  • Biomedical Text Mining and Ontologies
  • Advanced Image Fusion Techniques
  • Advanced Text Analysis Techniques

Beijing University of Technology
2007-2022

Hefei University of Technology
2021

Micro-bolometers based on VO<sub>2</sub>and carbon nanocoils are developed in this work. The photoresponse of the micro-bolometer is greatly enhanced by helical structure device.

10.1039/c9tc02833a article EN Journal of Materials Chemistry C 2019-01-01

Computer experiments can emulate the physical systems, help computational investigations, and yield analytic solutions. They have been widely employed with many engineering applications (e.g., aerospace, automotive, energy systems). Conventional Bayesian optimization did not incorporate nested structures in computer experiments. This article proposes a novel method for complex multistep or hierarchical characteristics. We prove theoretical properties of outputs given that distribution is...

10.1109/tmech.2022.3202079 article EN IEEE/ASME Transactions on Mechatronics 2022-09-09

Sentiment classification for reviews has attracted increasingly more attention from the natural language processing community. By embedding prior knowledge into learning structures, classifiers often achieve a better performance than original methods. In this paper, we propose sophisticated algorithm based on deep and information geometry in which distribution of all training samples space is treated as encoded by belief networks (DBNs). From view geometry, construct geodesic distance...

10.1109/access.2018.2848298 article EN cc-by-nc-nd IEEE Access 2018-01-01

Simultaneous distributed feedback (DFB) lasing and linear polarized random are observed in a compound cavity, which consists of grating cavity cavity. The is fabricated by interference lithography. A light-emitting polymer doped with silver nanoparticles spin-coated on the grating, forming DFB occur when periodic-random optically pumped. directionality polarization laser modified structure. These results can potentially be used to design integrated sources.

10.3390/polym10111194 article EN Polymers 2018-10-26

Predicting crash likelihood in complex driving environments is essential for improving traffic safety and advancing autonomous driving. Previous studies have used statistical models deep learning to predict crashes based on semantic, contextual, or features, but none examined the combined influence of these factors, termed roadway complexity this study. This paper introduces a two-stage framework that integrates features prediction. In first stage, an encoder extracts hidden contextual...

10.48550/arxiv.2411.17886 preprint EN arXiv (Cornell University) 2024-11-26

In this paper, we construct a wavelet linear estimator for the component of finite mixture under independent identically distributed biased observations. We evaluate its performance by determining an upper bound risk function classes.

10.4028/www.scientific.net/amm.347-350.3648 article EN Applied Mechanics and Materials 2013-08-01
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