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1,524 results on '"Zhang, Ruoyu"'

205. CEACAM6 as a Novel Therapeutic Target to Boost HO-1-mediated Antioxidant Defense in COPD

Author

Wu, Cheng-Yu, primary, Cilic, Anis, additional, Pak, Oleg, additional, Dartsch, Ruth Charlotte, additional, Wilhelm, Jochen, additional, Wujak, Magdalena, additional, Lo, Kevin, additional, Brosien, Monika, additional, Zhang, Ruoyu, additional, Alkoudmani, Ibrahim, additional, Witte, Biruta, additional, Pedersen, Frauke, additional, Watz, Henrik, additional, Voswinckel, Robert, additional, Günther, Andreas, additional, Ghofrani, Hossein A, additional, Brandes, Ralf P, additional, Schermuly, Ralph T, additional, Grimminger, Friedrich, additional, Seeger, Werner, additional, Sommer, Natascha, additional, Weissmann, Norbert, additional, and Hadzic, Stefan, additional

Published
2023
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209. Time-Modulated Arrays in Scanning Mode Using Wideband Signals for Range-Doppler Estimation With Time-Frequency Filtering and Fusion

Author

Ma, Yue, Miao, Chen, Long, Weijun, Zhang, Ruoyu, Chen, Qiaoyu, Zhang, Jindong, and Wu, Wen

Abstract

Time-modulated array (TMA) has garnered significant interest in recent years as an alternative to phased arrays for certain applications. The TMA offer advantages such as simplicity and high accuracy when employed in scanning mode. However, a significant limitation of TMA is the constrained signal bandwidth, which must be lower than the modulation frequency to avoid aliasing. This constraint can impede progress in wideband range-Doppler (RD) estimation. To address this problem, this article proposes a TMA structure and signal processing method that integrates time, frequency, and time–frequency (TF) domains to extract information for RD estimation. The proposed methods effectively overcome the bandwidth limitation by utilizing TF filtering and data fusion techniques, thereby enhancing the performance of RD estimation in TMA. The simulation results validate the effectiveness of the proposed strategies.

Published
2024
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210. ILCAS: Imitation Learning-Based Configuration- Adaptive Streaming for Live Video Analytics With Cross-Camera Collaboration

Author

Wu, Duo, Zhang, Dayou, Zhang, Miao, Zhang, Ruoyu, Wang, Fangxin, and Cui, Shuguang

Abstract

The high-accuracy and resource-intensive deep neural networks (DNNs) have been widely adopted by live video analytics (VA), where camera videos are streamed over the network to resource-rich edge/cloud servers for DNN inference. Common video encoding configurations (e.g., resolution and frame rate) have been identified with significant impacts on striking the balance between bandwidth consumption and inference accuracy and therefore their adaption scheme has been a focus of optimization. However, previous profiling-based solutions suffer from high profiling cost, while existing deep reinforcement learning (DRL) based solutions may achieve poor performance due to the usage of fixed reward function for training the agent, which fails to craft the application goals in various scenarios. In this paper, we propose ILCAS, the first imitation learning (IL) based configuration-adaptive VA streaming system. Unlike DRL-based solutions, ILCAS trains the agent with demonstrations collected from the expert which is designed as an offline optimal policy that solves the configuration adaption problem through dynamic programming. To tackle the challenge of video content dynamics, ILCAS derives motion feature maps based on motion vectors which allow ILCAS to visually “perceive” video content changes. Moreover, ILCAS incorporates a cross-camera collaboration scheme to exploit the spatio-temporal correlations of cameras for more proper configuration selection. Extensive experiments confirm the superiority of ILCAS compared with state-of-the-art solutions, with 2–20.9% improvement of mean accuracy and 19.9–85.3% reduction of chunk upload lag.

Published
2024
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211. A Systolic Array-Based Scheduling Strategy for Sparse CNN Accelerators

Author

Zhang, Guohe, Zhang, Ruoyu, Wang, Ran, and Zhu, Siyu

Abstract

Sparse convolutional neural network (CNN) accelerators face challenges such as low utilization of processing elements (PEs), low data reuse, and high hardware sparse index addressing cost during convolution operations. This brief proposes a new scheduling strategy for feature map sparse vectors and convolution kernel sparse vectors based on the systolic array and row stationary (RS) dataflow to overcome these problems. Our approach employs a design and implementation of a sparse convolution operation module based on systolic array, simulated comprehensively in Vivado using Virtex-7 VX690T version at a clock frequency of 150 MHz with a circuit power consumption of 8.15 W. We utilized the VGG-16 model to test and analyze the sparse convolution operation module. Results indicate an average effective operation utilization rate of PE computing units processed by the VGG-16 convolution layer at 65.34%.

Published
2024
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217. Numerical simulation of cavitation cavity characteristics of double Helmholtz nozzle.

Author

YAN Guohui, QIU Chengjun, HUANG Gao, YAN Jiaq, and ZHANG Ruoyu

Subjects
CAVITATION, NOZZLES, COMPUTER simulation, JET nozzles, POROSITY, KINETIC energy
Abstract

Based on the Helmholtz nozzle with higher natural frequency, a double Helmholtz pulse cavitation jet nozzle is designed. The effects of the cavity ratio, cavity distance, flow path diameter and fillet radius between the two resonators on their cavitation effect, turbulent kinetic energy and outlet velocity characteristics are analyzed by numerical simulation. The results show that the change of cavity ratio, cavity distance, flow path diameter and fillet radius will affect the cavitation effect in the nozzle. When the cavity ratio of the resonant cavity is 0.84, the cavity distance is 40 mm, and the flow path diameter between the cavities is 12 mm, the cavitation bubble generation effect in the two resonant cavities is good, the cavity void fraction is high, and the turbulent kinetic energy at the nozzle outlet is strong, which is more conducive to the improvement of the pulse cavitation cleaning efficiency. When the two chamber inlets of the nozzle are rounded, the internal cavitation of the nozzle decreases dramatically and the turbulent kinetic energy decreases, which inhibits the cavitation pulse performance of the nozzle and has a reaction to improve the nozzle cleaning effect. [ABSTRACT FROM AUTHOR]

Published
2023

228. Design of Control System for Multistage Distillation Seawater Desalination Device Driven by Photovoltaic-Thermal

Author

Yan, Jiaqi, primary, Qiu, Chengjun, additional, Wang, Yuangan, additional, Wu, Ning, additional, Qu, Wei, additional, Zhuang, Yuan, additional, Yan, Guohui, additional, Wang, Ping, additional, Zhang, Ruoyu, additional, Yan, Yirou, additional, Deng, Ruonan, additional, Luo, Jiuqiang, additional, Gao, Jiaqi, additional, and Wu, Yuxuan, additional

Published
2023
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246. The effect of parent-child relationships on adolescent risk-taking behavior: the mediating role of emotion regulation self-efficacy

Author

Zhang, Ruoyu, Jiageng Wen, Yijing Cheng, and Zhang, Chen

Subjects
FOS: Psychology, Social Psychology, Developmental Psychology, Psychology, Social and Behavioral Sciences
Abstract

Previous literature has demonstrated that adolescence is characterized by a high incidence and frequency of adventurous behavior, which is closely associated with physiological conditions, cognitive abilities, social functioning, and other aspects of rapid development. From a perspective focusing on the unique aspects of adventurous behavior, various factors such as different adventurous contexts, peer influence, family factors, and individual traits play significant roles in shaping adolescents' adventurous behavior. Building upon this understanding, this study aims to explore the relationship between parent-child relationships, adolescent adventurous behavior, and self-efficacy in emotional regulation, in order to provide targeted empirical data support for improving the situation of adolescents' adventurous behavior.

Published
2023
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250. A Supported Catalyst that Enables the Synthesis of Colorless CO2‐Polyols with Ultra‐Low Molecular Weight.

Author

Kuang, Qingxian, Zhang, Ruoyu, Zhou, Zhenzhen, Liao, Can, Liu, Shunjie, Chen, Xuesi, and Wang, Xianhong

Subjects
*MOLECULAR weights, *POLYOLS, *CATALYSTS, *TELOMERIZATION, *URETHANE foam, *HYDROXYL group, *POLYMERS, *FOAM, *HETEROGENEOUS catalysts
Abstract

Ultra‐low molecular weight (ULMW) CO2‐polyols with well‐defined hydroxyl end groups represent useful soft segments for the preparation of high‐performance polyurethane foams. However, owing to the poor proton tolerance of catalysts towards CO2/epoxide telomerization, it remains challenging to synthesize ULMW yet colorless CO2‐polyols. Herein, we propose an immobilization strategy of constructing supported catalysts by chemical anchoring of aluminum porphyrin on Merrifield resin. The resulting supported catalyst displays both extremely high proton tolerance (≈8000 times the equivalents of metal centers) and independence of cocatalyst, affording CO2‐polyols with ULMW (580 g mol−1) and high polymer selectivity (>99 %). Moreover, the ULMW CO2‐polyols with various architectures (tri‐, quadra‐, and hexa‐arm) can be obtained, suggesting the wide proton universality of supported catalysts. Notably, benefiting from the heterogeneous nature of the supported catalyst, colorless products can be facilely achieved by simple filtration. The present strategy provides a platform for the synthesis of colorless ULMW polyols derived from not only CO2/epoxides, but also lactone, anhydrides etc. or their combinations. [ABSTRACT FROM AUTHOR]

Published
2023
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