Xin Xie

ORCID: 0000-0002-4225-854X
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About
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Research Areas
  • Hydrological Forecasting Using AI
  • Power Systems and Technologies
  • Advanced Authentication Protocols Security
  • Water Quality Monitoring Technologies
  • UAV Applications and Optimization
  • Wireless Communication Security Techniques
  • Water Treatment and Disinfection
  • Water Quality and Pollution Assessment
  • Wastewater Treatment and Nitrogen Removal
  • Web Applications and Data Management
  • Text Readability and Simplification
  • Educational Technology and Assessment
  • Groundwater and Watershed Analysis
  • Advanced SAR Imaging Techniques
  • Privacy-Preserving Technologies in Data
  • Topic Modeling
  • IoT and Edge/Fog Computing
  • Smart Grid and Power Systems
  • Energy Load and Power Forecasting
  • Cinema and Media Studies
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Mobile Crowdsensing and Crowdsourcing
  • Constructed Wetlands for Wastewater Treatment
  • RFID technology advancements
  • Explainable Artificial Intelligence (XAI)

Beihang University
2023-2025

Beijing Institute of Technology
2024

China National Environmental Monitoring Center
2023

Harbin Institute of Technology
2023

Tianjin University
2023

Hefei University of Technology
2023

Huawei Technologies (China)
2008

ABSTRACTThe emergence of AI has revolutionized video production, enabling innovative approaches in artistic creation. With self-media's rise and demand for user-generated content, drives personalized, efficient production. However, research lacks comprehensive reviews AI's impact on film TV. This study fills the gap by analyzing influence using a five-sub-field framework. Through literature integration, we assess production's potential, proposing new process paradigm. sheds light...

10.1080/17517575.2023.2246188 article EN Enterprise Information Systems 2023-08-17

Large Language Models (LLMs) usually suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events generate text with incorrect facts owing to outdated/noisy data. To this end, many editing approaches for LLMs have emerged -- aiming subtly inject/edit updated adjust undesired behavior while minimizing the impact on unrelated inputs. Nevertheless, due significant differences among various methods and variations in task setups, there is no standard...

10.48550/arxiv.2308.07269 preprint EN other-oa arXiv (Cornell University) 2023-01-01

The high spatial resolution and displacement sensitivity of mmWave radar have significantly enhanced the performance wireless sensing. However, improved sensing capabilities also led to growing concerns about privacy leakage. Attackers can make fine-grained analysis various user activities by exploiting data. This article presents mmFilter, a privacy-level data filter designed protect privacy, which proposes signal reversion methodology perform targeted perturbations in specific feature...

10.1109/mcom.011.2200580 article EN IEEE Communications Magazine 2023-10-02

With the increasing number of mobile devices, crowdsensing (MCS) has garnered significant attention in research. However, computing infrastructures such as edge/cloud nodes, which are necessary for processing sensor data, not always readily available. To address this issue, we propose a cooperative framework that enables offloading data to nearby devices with unused computational resources (known helpers) processing. Our approach considers scenario multiple sources and helpers, where tasks...

10.1109/tmc.2023.3323350 article EN IEEE Transactions on Mobile Computing 2023-10-10

Motivated by diverse secure requirements of multi-user in UAV systems, we propose a collaborative secret and covert transmission method for multi-antenna ground users to unmanned aerial vehicle (UAV) communications. Specifically, based on the power domain non-orthogonal multiple access (NOMA), two with distinct security requirements, named Bob Carlo, superimpose their signals transmit combined signal Alice. An adversary Willie attempts simultaneously eavesdrop Bob's confidential message...

10.48550/arxiv.2407.05738 preprint EN arXiv (Cornell University) 2024-07-08

Short-term power prediction is one of the important tasks in daily operation energy system. With popularity smart grid, it brings more difficulties to accuracy electricity prediction. The purpose this study explore characteristics short-term data achieve efficient and accurate provide a reference for grid management. Firstly, according various prediction, paper builds shortterm models by using SVM LS-SVM, respectively. Then, compares results two single with test values. It found that curve...

10.1117/12.2680264 article EN 2023-05-31
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