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2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

作者： Peng, Yatao Zhong, Youpeng Guo, Zechen Liu, Song Yu, Dapeng University of Macau State Key Lab. of Analog and Mixed-Signal VLSI IME/ECE of FST China Shenzhen International Quantum Academy China SUSTech Shenzhen Institute for Quantum Science and Engineering China

ISBN: (纸本)9798350347647

The measurement of the fast-increasing number of qubits necessitates the use of a large number of specialized cryogenic low-noise amplifiers (LNAs).). This work presents a broadband LNA designed with discrete GaAs HEMT components which operate well at ~3.6 K temperature. The dual-frequency optimum noise matching network and output matching elements of the first stage were employed to optimize the equivalent noise temperature (NT) and the input return loss in a wideband. Measurement results at 3.6 K ambient temperature show that the LNA achieved an equivalent NT of 30 dB in the 3.5 GHz to 7.5 GHz band with a minimum of 5 Kelvin at ~6.5 GHz. The best visibility of ~0.891 is achieved when using the LNA to observe a superconducting transmon qubit without using a JPA. © 2023 IEEE.

关键词： Low noise amplifiers

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On Efficient Packet Batching and Resource Allocation for GPU based NFV Acceleration 31

On Efficient Packet Batching and Resource Allocation for GPU...

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31st IEEE/ACM International Symposium on Quality of Service, IWQoS 2023

作者： Zeng, Deze Zhu, Andong Gu, Lin Chen, Quan Guo, Minyi School of Computer Science China University of Geosciences Hubei Wuhan China Nanjing University State Key Lab. for Novel Software Technology Nanjing China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China

ISBN: (纸本)9798350399738

Network Function Virtualization (NFV) has already become an essential technology for improving the scalab.lity and flexibility of modern computer networks. The performance gap has become the main issue that impedes the development of NFV. GPUs, with massive parallel processors, are advocated to accelerate the Virtualized Network Functions (VNFs). However, the special architecture and workflow of GPUs introduce new challenges, especially on the batched processing, and resource allocation. In this paper, we propose GPU-based NFV Acceleration framework (GNFA) with an efficient packet batching and resource allocation solution. Considering the increased latency caused by the accumulation of the GPU kernel invoking overhead, we first invent a latency reduction mechanism called SM Performance Compensation (SPC). A Partition and Adjustment based Batching and Resource Allocation (PABARA) algorithm that jointly considers batch size tuning and GPU thread allocation is also proposed. We have practically implemented GNFA and extensively evaluated its performance on some well-known VNFs. The experiment results show that GNFA can effectively promote the GPU resource utilization and improve the NFV performance in terms of per-packet latency. © 2023 IEEE.

关键词： Graphics processing unit

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New Algorithms for Distributed Fair k-Center Clustering: Almost Accurate as Sequential Algorithms 23

New Algorithms for Distributed Fair k-Center Clustering: Alm...

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23rd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2024

作者： Wu, Xiaoliang Feng, Qilong Huang, Ziyun Xu, Jinhui Wang, Jianxin School of Computer Science and Engineering Central South University Xiangjiang Laboratory Changsha China Department of Computer Science and Software Engineering Penn State Erie The Behrend College Erie United States Department of Computer Science and Engineering State University of New York at Buffalo Buffalo United States Hunan Provincial Key Lab on Bioinformatics Central South University Xiangjiang Laboratory Changsha China

Fair clustering problems have been paid lots of attention recently. In this paper, we study the k-Center problem under the group fairness and data summarization fairness constraints, denoted as Group Fair k-Center (GFkC) and Data Summarization Fair k-Center (DSFkC), respectively, in the massively parallel computational (MPC) distributed model. The previous best results for the above two problems in the MPC model are a 9-approximation with violation 7 (WWW 2022) and a (17 + ∊)-approximation without fairness violation (ICML 2020), respectively. In this paper, we obtain a (3 + ∊)- approximation with violation 1 for the GFkC problem in the MPC model, which is almost as accurate as the best known approximation ratio 3 with violation 1 for the sequential algorithm of the GFkC problem. Moreover, for the DSFkC problem in the MPC model, we obtain a (4 + ∊)-approximation without fairness violation, which is very close to the best known approximation ratio 3 for the sequential algorithm of the DSFkC problem. Empirical experiments show that our distributed algorithms perform better than existing state-of-the-art distributed methods for the above two problems. © 2024 International Foundation for Autonomous Agents and Multiagent Systems.

关键词： Machine learning

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Influence Study of the Anisotropic Scattering and Solar Radiation on the Radiation Working Performance of Liquid Droplet Radiator

SSRN

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SSRN 2024年

作者： Fei, Yiheng Fu, Jianghan Wang, Chenglong Tian, Wenxi Guanghui, S.U. Qiu, Suizheng Department of Nuclear Science and Technology State Key Lab. of Multiphase Flow in Power Engineering Shaanxi Key Lab. of Advanced Nuclear Energy and Technology Xi’an Jiaotong University Xi’an710049 China

The Liquid Droplet Radiator (LDR), a lightweight frameless radiant heat rejection system, is widely regarded as the optimal heat rejection solution for megawatt-scale space nuclear power systems. The LDR dissipates heat to space through its droplet layer, which plays a crucial role in determining its radiative rejection capacity. Radiation beams undergo a series of emission, scattering, and absorption processes within the layer before being emitted into space. Prior studies typically assume isotropic scattering in this process. However, this study introduces a 3D model of the LDR layer based on Mie theory and Monte-Carlo methods to investigate the impact of anisotropic scattering and solar radiation. Our calculations reveal that the working fluid exhibits strong forward anisotropic scattering characteristics. Under the anisotropic assumption, the heat rejection capability of the LDR is 27-33% higher compared to the isotropic assumption. Regarding the temperature distribution within the LDR, under the anisotropic assumption, the layer's temperature is 6 K lower at the XY boundary surface and 3 K higher at the layer median, as opposed to the isotropic assumption. We introduce the concept of the probability of a light beam escape to elucidate the distinct beam transmission mechanisms and temperature distribution. When the distance between the LDR and the sun is in the vicinity of 1 AU, the impact of solar radiation on the LDR's ability to operate is on the order of 1E-5, which is almost negligible. This study provides a theoretical foundation for calculating the heat rejection capacity during the LDR design phase. © 2024, The Authors. All rights reserved.

关键词： Solar radiation

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Poster Abstract: Real-Time Active Identification and Tracking of UAVs Using Millimeter-Wave Radar 25

Poster Abstract: Real-Time Active Identification and Trackin...

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Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems

作者： Liming Zhang Yanling Bu Yanni Yang Nanjing University of Aeronautics and Astronautics Nanjing China State Key Lab. for Novel Software Technology Nanjing University Nanjing China Shandong University Shandong China

ISBN: (纸本)9798400714795

Unmanned aerial vehicle (UAV) poses a major threat to airspace security and privacy protection. However, existing UAV identification systems face the limitations of feature extraction quality degradation under low signal-to-noise ratio (SNR) conditions, and the average delay of traditional tracking algorithms is difficult to meet the real-time requirements due to high computational complexity. To address these issues, this paper proposes mmRTD, a real-time identification and tracking system for non-cooperative UAV sensing using mmWave radar. To solve the problem of serious feature extraction distortion in low SNR environment, this paper proposes a dynamic period adjustment mechanism driven by spectrum volatility to significantly improve the quality of feature extraction under low SNR conditions. To solve the problem of insufficient real-time performance of traditional tracking methods, this paper proposes a lightweight frame-based tracking framework through the target state detection method to solve the real-time bottleneck caused by high-dimensional signal processing of traditional methods. The experimental results show that the detection accuracy of mmRTD reaches 97.2% within a range of 40 m. In particular, the first detection time of mmRTD is two orders of magnitude higher than that of the traditional scheme, which verifies its potential for real-time identification in complex scenes.

关键词： mmWave sensing

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Geometric parameters optimization on storage performance degradation of ultrasonic motor based on simulation analysis 6

Geometric parameters optimization on storage performance deg...

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6th International Conference on Mechanical, Electric, and Industrial engineering, MEIE 2023

作者： Tan, Bijiao Wang, Hao Zhang, Zhaolin Huang, Shouqing Peng, Haoyuan Yan, Qi Beijing Shenzhou Aerospace Software Technology Co. Ltd. Beijing China Beijing Key Lab. of Environ. Reliability Test Technol. for Aerosp. Mechanical Electrical Products Beijing Institute of Spacecraft Environment Engineering Beijing China

The performance of ultrasonic motor will drift due to material degradation and other reasons during long-term storage, which will directly affect the working performance after storage. Aiming at the optimization design of geometric parameters for performance storage degradation, this paper takes the piezoelectric constant d31 of ceramic chip and the elastic modulus of colloid as the characterization parameters of product storage degradation, and takes the stator tooth spacing and the thickness of rubber layer as the analysis objects of product geometric parameters optimization, and proposes a simulation analysis method based on finite element model. Through the analysis of the simulation results, it is found that the increase of the stator tooth spacing will lead to the increase of the change rate of the 5-wave modal frequency with the degradation of the material properties, and the decrease of the overall change rate of the amplitude. However, properly reducing the thickness of the adhesive layer can effectively reduce the influence of the degradation of the piezoelectric properties of the ceramic chip and the hardening of the gel on the frequency response characteristics of the stator of the ultrasonic motor under long-term storage. © Published under licence by IOP Publishing Ltd.

关键词： Frequency response

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Poster Abstract: IMU-assisted Image Stitching for Scenes with Obstructions Based on Camera Motion Sensing 25

Poster Abstract: IMU-assisted Image Stitching for Scenes wit...

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Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems

作者： Saibing Han Yanling Bu Yanchao Zhao Lei Xie College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China State Key Lab. for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9798400714795

Image stitching is often affected by obstructions such as pedestrians and vehicles. Traditional methods often ignore obstructions or retain them, leading to artifacts. They also cause edge distortion due to fixed-perspective stitching. To address above issues, this poster presents IIS, an IMU-assisted Image Stitching method. It uses IMU data for perspective pre-alignment, projecting images to an intermediate perspective to reduce edge distortion. It simultaneously removes obstructions and mitigating their impact. A weighted target scene stitching strategy is integrated to further enhance stitching quality. IIS effectively reduces artifacts and maintains high computational efficiency.

关键词： image stitching

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Effects of Intercritical Annealing Temperature on the Microstructure and Deformation Behavior of a Cold Rolled 10Mn TRIP/TWIP Steel 6

Effects of Intercritical Annealing Temperature on the Micros...

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6th International Conference on ThermoMechanical Processing, TMP 2022

作者： Sun, Shenghui Cai, Minghui Ding, Hua School of Materials Science & Engineering Northeastern University Shenyang110819 China Key Lab. of Lightweight Structural Materials Liaoning Province Northeastern University Shenyang110819 China State Key Lab. of Rolling and Automotion Northeastern University Shenyang110819 China

ISBN: (纸本)9787502492441

In the present work, SEM, EBSD, TEM and XRD methods were used to study the effects of intercritical annealing (IA) temperature on the microstructural evolution and mechanical properties of a newly designed cold rolled medium-Mn steel, Fe-10.12Mn-0.3C-3.84Al-0.45Si (in wt.%). Experimental results showed that as the IA temperature increased, both the morphologies of austenite and ferrite changed from the lath-shaped to the mixed equiaxed/block- and lath-shaped ones. The volume fraction of retained austenite increased with increasing the IA temperature, reaching a maximum of ∼69% at 800 °C. A good trade-off between ultimate tensile strength (∼1032 MPa) and elongation (∼61%) was achieved when the cold-rolled sheets were subjected to intercritical annealing at 800 °C. The product of strength and elongation (PSE) is above 62 GPa·%, which far exceeds the index of PSE (30 GPa·%) of the thirdgeneration advanced high strength steel. The excellent strength-ductility combination is mainly attributed to the bimodal-size distribution and the herogeneous morphologies (equiaxed, block, and plate) of austenite, which can provide a sustainable TRIP effect as well as a coordinated TWIP effect during tensile deformation and thus enhanced the strain hardening ability of materials. © TMP 2022 - Proceedings. All rights reserved.

关键词： Cold rolling

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Investigating the Impact of Bug Dependencies on Bug-Fixing Time Prediction 17

Investigating the Impact of Bug Dependencies on Bug-Fixing T...

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17th ACM/IEEE International Symposium on Empirical software engineering and Measurement, ESEM 2023

作者： Li, Chenglin Zhao, Yangyang Yang, Yibiao Zhou, Yuming Nie, Liming Ding, Zuohua School of Computer Science and Technology Zhejiang Sci-Tech University Hangzhou China Nanjing University State Key Lab for Novel Software Technology Nanjing China School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781665452236

Background: Bug dependencies refer to the link relationships between bugs and related issues, which are commonly observed in software evolution. It has been found that bugs with bug dependencies often take longer time to be resolved than other bugs without any dependencies. Despite the potential impact of bug dependencies on bug-fixing time, previous studies use traditional metrics without considering bug dependencies to build bug-fixing time prediction models. As a result, there is currently little empirical evidence to support the use of bug dependencies in improving prediction accuracy. Aims: We aim to conduct a comprehensive empirical study to investigate the value of considering bug dependencies for bug-fixing time prediction. Method: We define a set of bug dependency metrics based on bug dependencies. We first investigate the correlation between bug dependency metrics and bug-fixing time to investigate whether bugs with more complex dependencies are more time-consuming to be fixed. Next, we employ principal component analysis to study whether bug dependency metrics capture additional dimensions of a bug compared to traditional metrics. Finally, we build multivariate prediction models to explore whether considering bug dependencies can improve the effectiveness of bug-fixing time prediction. Results: The experimental results suggest that: (1) bugs with more complex dependencies require more time to be fixed;(2) bug dependency metrics are complementary to traditional metrics;(3) considering bug dependencies can improve the effectiveness of bug-fixing time prediction. Conclusions: These findings highlight the importance of considering bug dependencies in bug-fixing time prediction, and provide valuable insights into the potential impact of bug dependencies on software development processes. © 2023 IEEE.

关键词： Principal component analysis

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Sparse Bayesian Network for Fast Micro-Doppler Analysis

Sparse Bayesian Network for Fast Micro-Doppler Analysis

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jiongge Zhang Hang Dong Long Tian Xiongpeng He Huimin Sun Yuan Liu Pilot School of Software Engineering Xidian University Key Lab. of Radar Signal Processing Xidian University Pilot School of Software Engineering Xidian University Xi’an China Electronic Engineering Research Institute Xi’an China Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Micro-Doppler Analysis (MDA) of rigid-body targets is crucial for various practical downstream tasks such as target imaging and recognition. Radar echoes from micro-moving targets typically represent non-stationary signals and are often described using the parameterized Time-Varying Auto Regressive (TVAR) model. Sparse Bayesian Learning (SBL) is commonly employed to estimate time-invariant coefficients, thereby achieving high-resolution micro-Doppler time-frequency distributions. Despite its effectiveness, SBL-based optimization methods often face inefficiency due to the computational burden of inverse operation. To address this challenge and enhance the efficiency of MDA based on TVAR model, we propose a Sparse Bayesian Network (SBN) that unfolds a fast Mean Field SBL (MF) using a deep variational autoencoding framework. This method retains the optimization effectiveness of SBL while incorporating the inference efficiency of Deep Neural Networks (DNNs). Our proposed method demonstrates strong generalization capabilities, performing well on both simulated and measured radar echoes.

关键词： Time-frequency analysis Target recognition Radar measurements Computational modeling Optimization methods Radar Radar imaging Signal processing Bayes methods Speech processing

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