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1,016 results on '"Chen, Yuning"'

1. See Behind Walls in Real-time Using Aerial Drones and Augmented Reality

Author

Yang, Sikai, Yang, Kang, Chen, Yuning, Zhao, Fan, and Du, Wan

Subjects
Computer Science - Multiagent Systems, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction
Abstract

This work presents ARD2, a framework that enables real-time through-wall surveillance using two aerial drones and an augmented reality (AR) device. ARD2 consists of two main steps: target direction estimation and contour reconstruction. In the first stage, ARD2 leverages geometric relationships between the drones, the user, and the target to project the target's direction onto the user's AR display. In the second stage, images from the drones are synthesized to reconstruct the target's contour, allowing the user to visualize the target behind walls. Experimental results demonstrate the system's accuracy in both direction estimation and contour reconstruction., Comment: 6 pages

Published
2024

2. MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer Recharge

Author

Chen, Yuning, Yang, Kang, An, Zhiyu, Holder, Brady, Paloutzian, Luke, Bali, Khaled, and Du, Wan

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

The rapid decline in groundwater around the world poses a significant challenge to sustainable agriculture. To address this issue, agricultural managed aquifer recharge (Ag-MAR) is proposed to recharge the aquifer by artificially flooding agricultural lands using surface water. Ag-MAR requires a carefully selected flooding schedule to avoid affecting the oxygen absorption of crop roots. However, current Ag-MAR scheduling does not take into account complex environmental factors such as weather and soil oxygen, resulting in crop damage and insufficient recharging amounts. This paper proposes MARLP, the first end-to-end data-driven control system for Ag-MAR. We first formulate Ag-MAR as an optimization problem. To that end, we analyze four-year in-field datasets, which reveal the multi-periodicity feature of the soil oxygen level trends and the opportunity to use external weather forecasts and flooding proposals as exogenous clues for soil oxygen prediction. Then, we design a two-stage forecasting framework. In the first stage, it extracts both the cross-variate dependency and the periodic patterns from historical data to conduct preliminary forecasting. In the second stage, it uses weather-soil and flooding-soil causality to facilitate an accurate prediction of soil oxygen levels. Finally, we conduct model predictive control (MPC) for Ag-MAR flooding. To address the challenge of large action spaces, we devise a heuristic planning module to reduce the number of flooding proposals to enable the search for optimal solutions. Real-world experiments show that MARLP reduces the oxygen deficit ratio by 86.8% while improving the recharging amount in unit time by 35.8%, compared with the previous four years., Comment: Accepted by KDD 2024

Published
2024
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4. Profiling ovarian cancer tumor and microenvironment during disease progression for cell-based immunotherapy design

Author

Li, Yan-Ruide, Ochoa, Christopher J, Zhu, Yichen, Kramer, Adam, Wilson, Matthew, Fang, Ying, Chen, Yuning, Singh, Tanya, Di Bernardo, Gabriella, Zhu, Enbo, Lee, Derek, Moatamed, Neda A, Bando, Joanne, Zhou, Jin J, Memarzadeh, Sanaz, and Yang, Lili

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Ovarian Cancer, Vaccine Related, Cancer, Rare Diseases, Immunization, Orphan Drug, Clinical Research, Good Health and Well Being, Therapy
Abstract

Ovarian cancer (OC) is highly lethal due to late detection and frequent recurrence. Initial treatments, comprising surgery and chemotherapy, lead to disease remission but are invariably associated with subsequent relapse. The identification of novel therapies and an improved understanding of the molecular and cellular characteristics of OC are urgently needed. Here, we conducted a comprehensive analysis of primary tumor cells and their microenvironment from 16 chemonaive and 10 recurrent OC patient samples. Profiling OC tumor biomarkers allowed for the identification of potential molecular targets for developing immunotherapies, while profiling the microenvironment yielded insights into its cellular composition and property changes between chemonaive and recurrent samples. Notably, we identified CD1d as a biomarker of the OC microenvironment and demonstrated its targeting by invariant natural killer T (iNKT) cells. Overall, our study presents a comprehensive immuno-profiling of OC tumor and microenvironment during disease progression, guiding the development of immunotherapies for OC treatment, especially for recurrent disease.

Published
2023

6. Satellite downlink scheduling under breakpoint resume mode

Author

Chang, Zhongxiang, Chen, Yuning, and Zhou, Zhongbao

Subjects
Computer Science - Artificial Intelligence
Abstract

A novel problem called satellite downlink scheduling problem (SDSP) under breakpoint resume mode (SDSP-BRM) is studied in our paper. Compared to the traditional SDSP where an imaging data has to be completely downloaded at one time, SDSP-BRM allows the data of an imaging data be broken into a number of pieces which can be downloaded in different playback windows. By analyzing the characteristics of SDSP-BRM, we first propose a mixed integer programming model for its formulation and then prove the NP-hardness of SDSP-BRM. To solve the problem, we design a simple and effective heuristic algorithm (SEHA) where a number of problem-tailored move operators are proposed for local searching. Numerical results on a set of well-designed scenarios demonstrate the efficiency of the proposed algorithm in comparison to the general purpose CPLEX solver. We conduct additional experiments to shed light on the impact of the segmental strategy on the overall performance of the proposed SEHA.

Published
2022

31. Emergent Morphogenesis for Robot Swarms in 3D Space

Author

Hu, Linqiang, Chen, Yuning, Zhou, Ziqing, Zhao, Zhile, Dong, Xinyang, Guan, Yuxiang, Gan, Zhongxue, Ouyang, Chun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Ren, Zhang, editor, Wang, Mengyi, editor, and Hua, Yongzhao, editor

Published
2023
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32. An Optimized Flocking Motion with Attention Module for Obstacle Avoidance

Author

Zhou, Ziqing, Hu, Linqiang, Chen, Yuning, Dong, Xinyang, Zhao, Zhile, Guan, Yuxiang, Gan, Zhongxue, Ouyang, Chun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Ren, Zhang, editor, Wang, Mengyi, editor, and Hua, Yongzhao, editor

Published
2023
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40. Widely tunable cavity-enhanced frequency combs

Author

Silfies, Myles C., Kowzan, Grzegorz, Chen, Yuning, Lewis, Neomi, Hou, Ryan, Baehre, Robin, Gross, Tobias, and Allison, Thomas K.

Subjects
Physics - Optics, Physics - Applied Physics
Abstract

We describe the cavity-enhancement of frequency combs over a wide tuning range of 450-700 nm (> 7900 cm$^{-1}$), covering nearly the entire visible spectrum. Tunable visible frequency combs from a synchronously-pumped optical parametric oscillator are coupled into a 4-mirror, dispersion-managed cavity with a finesse of 600 to 1400. An intracavity absorption path length enhancement greater than 190 is obtained over the entire tuning range, while preserving intracavity spectral bandwidths capable of supporting sub-200 fs pulse durations. These tunable cavity-enhanced frequency combs can find many applications in nonlinear optics and spectroscopy.

Published
2020
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