Yun Li

Distributed Fusion Filter for Multi-rate Sampling Stochastic Singular Systems with Multiplicative Noises

2015 · International Journal of Multimedia and Ubiquitous Engineering

The distributed fusion filtering problem is studied for multi-rate sampling stochastic singular linear systems with multiple sensors and stochastic multiplicative noises. The system is described at the highest sampling rate and different sensors may have …

Particle filter with Lamarckian inheritance for nonlinear filtering

2016

The particle filter (PF) offers significant advantages over other nonlinear filters for non-Gaussian systems. However, it suffers from particle degeneracy and impoverishment, which can lead to deteriorated estimation performance. Through analyzing the filtering and Lamarckian …

Fusion Estimation for Multi-sensor Nonlinear System with Disorder and Packet Loss

2020

For a multi-sensor nonlinear system with disorder and packet loss, a fusion estimation algorithm is presented in this paper. Firstly, for equally spaced measurement sampling system, the disorder measurement is sorted by using measurement prediction …

Chinese Lexical Simplification

2020 · arXiv (Cornell University)

Lexical simplification has attracted much attention in many languages, which is the process of replacing complex words in a given sentence with simpler alternatives of equivalent meaning. Although the richness of vocabulary in Chinese makes …

Improving the Prediction of Benign or Malignant Breast Masses Using a Combination of Image Biomarkers and Clinical Parameters

2021 · Frontiers in Oncology

Background: Breast cancer is one of the leading causes of death in female cancer patients. The disease can be detected early using Mammography, an effective X-ray imaging technology. The most important step in mammography is …

Learning Task-aware Robust Deep Learning Systems

2020 · arXiv (Cornell University)

Many works demonstrate that deep learning system is vulnerable to adversarial attack. A deep learning system consists of two parts: the deep learning task and the deep model. Nowadays, most existing works investigate the impact …

Detecting Outliers in Data Streams Based on Minimum Rare Pattern Mining and Pattern Matching

2022 · Information Technology And Control

Outliers are the major factors to influence the accuracy of data-based processing, thus, they must be discovered from collected datasets to guarantee data security. With the widely use of sensors and other monitoring equipment, data …

Chinese Lexical Substitution: Dataset and Method

2023

Existing lexical substitution (LS) benchmarks were collected by asking human annotators to think of substitutes from memory, resulting in benchmarks with limited coverage and relatively small scales. To overcome this problem, we propose a novel …

E-DoH: Elegantly Detecting the Depths of Open DoH Service on the Internet

2024 · arXiv (Cornell University)

In recent years, DNS over Encrypted (DoE) methods have been regarded as a novel trend within the realm of the DNS ecosystem. In these DoE methods, DNS over HTTPS (DoH) provides encryption to protect data …

Flux Dynamics of CO<sub>2</sub> in a Rubber Plantation in Xishuangbanna <?A3B2 pi6?>and Its Influencing Factors

2024 · EARTH AND ENVIRONMENT

<p indent="0mm">Rubber plantations are important artificial forest ecosystems in tropical regions of China, and accurate assessment of their carbon source and sink status is crucial.Based on the carbon flux observation from Xishuangbanna rubber plantation ecosystem …

Large Language Models for Human-like Autonomous Driving: A Survey

2024 · arXiv (Cornell University)

Large Language Models (LLMs), AI models trained on massive text corpora with remarkable language understanding and generation capabilities, are transforming the field of Autonomous Driving (AD). As AD systems evolve from rule-based and optimization-based methods …

LLM-Empowered Few-Shot Node Classification on Incomplete Graphs with Real Node Degrees

2024

Graphs constructed from real-world scenarios are often incomplete due to privacy restrictions or resource limitations, posing significant challenges for node classification, especially when labeled data are scarce. In many scenarios of incomplete graphs, the real …

Transmission Line Meteorological Risk Classification Using Multi-Source Incomplete Data

2025

In this paper, an innovative meteorological risk classification method is proposed to solve the problem of risk prediction of transmission lines under the complex and changeable meteorological data environment. This method is based on the …

MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning

2025 · arXiv (Cornell University)

Medical Large Vision-Language Models (Med-LVLMs) have shown strong potential in multimodal diagnostic tasks. However, existing single-agent models struggle to generalize across diverse medical specialties, limiting their performance. Recent efforts introduce multi-agent collaboration frameworks inspired by …