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44th ACM/IEEE International Conference on Software Engineering, ICSE 2024

作者： Feng, Siyue Suo, Wenqi Wu, Yueming Zou, Deqing Liu, Yang Jin, Hai Huazhong University of Science and Technology China Nanyang Technological University Singapore Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Jinyinhu Laboratory Wuhan430074 China School of Cyber Science and Engineering Hust Wuhan430074 China School of Computer Science and Technology Hust Wuhan430074 China

ISBN: (纸本)9798400702174

As software engineering advances and the code demand rises, the prevalence of code clones has increased. This phenomenon poses risks like vulnerability propagation, underscoring the growing importance of code clone detection techniques. While numerous code clone detection methods have been proposed, they often fall short in real-world code environments. They either struggle to identify code clones effectively or demand substantial time and computational resources to handle complex clones. This paper introduces a code clone detection method namely Toma using tokens and machine learning. Specifically, we extract token type sequences and employ six similarity calculation methods to generate feature vectors. These vectors are then input into a trained machine learning model for classification. To evaluate the effectiveness and scalability of Toma, we conduct experiments on the widely used BigCloneBench dataset. Results show that our tool outperforms token-based code clone detectors and most tree-based clone detectors, demonstrating high effectiveness and significant time savings. © 2024 ACM.

关键词： Machine learning

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Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need 38

Unlearnable 3D Point Clouds: Class-wise Transformation Is Al...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Wang, Xianlong Li, Minghui Liu, Wei Zhang, Hangtao Hu, Shengshan Zhang, Yechao Zhou, Ziqi Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity information, unauthorized usage of this new type data has also become a serious concern. To address this, we propose the first integral unlearnable framework for 3D point clouds including two processes: (i) we propose an unlearnable data protection scheme, involving a class-wise setting established by a category-adaptive allocation strategy and multi-transformations assigned to samples;(ii) we propose a data restoration scheme that utilizes class-wise inverse matrix transformation, thus enabling authorized-only training for unlearnable data. This restoration process is a practical issue overlooked in most existing unlearnable literature, i.e., even authorized users struggle to gain knowledge from 3D unlearnable data. Both theoretical and empirical results (including 6 datasets, 16 models, and 2 tasks) demonstrate the effectiveness of our proposed unlearnable framework. Our code is available at https://***/CGCL-codes/UnlearnablePC. © 2024 Neural information processing systems foundation. All rights reserved.

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Experimental Investigation of a Loop Heat Pipe with a Flat Evaporator

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Frontiers in Heat and Mass Transfer 2025年第2期23卷 651-662页

作者： Guoguang Li Qi Wu Hanli Bi Zhichao Jia Hongxing Zhang Jinyin Huang Jianyin Miao National Key Laboratory of Spacecraft Thermal Control Beijing Institute of Spacecraft System EngineeringChina Academy of Space TechnologyBeijing100094China

The loop heat pipe with a flat evaporator is mainly divided into two forms:rectangular evaporator and disk-shaped *** rectangular evaporator has advantages such as low heat leakage,a thin shell,and a large contact area compared to the disk-shaped ***,most of the research on rectangular evaporators focuses onworking fluids such as water,methanol,and acetone,when theseworking fluids are in operation,the internal pressure of the evaporator is less than atmospheric ***,propylene,and other working fluids can also be utilized in the loop heat pipe,these working fluids demonstrate better performance when operating within other temperature intervals,for example,the operating temperature range of ammonia is−20℃to 50℃,however,in an atmospheric pressure environment,it is very difficult for the shell of the rectangular evaporator to withstand the saturated vapor pressure of the working *** paper designs a rectangular flat plate loop heat pipe that can use ammonia as the working *** internal reinforcing structure is used to improve the pressure strength of the *** secondary wick connects the compensation chamber and the capillary wick *** experiment indicates that this kind of rectangular evaporator is unaffected by the position,and the secondary wick can effectively supply liquid under different *** thermal resistance of the evaporator wall was analyzed,and it was found that the thermal resistance of the evaporator wall was the main component of the thermal resistance of the *** heat transfer capacities of 460 W@0.5 m and 200W@10 m were *** test results indicate that by setting a reinforcing structure inside the flat plate evaporator,the evaporator can withstand internal *** with the design of the secondary wick,the flat plate evaporator can use working fluids with different pressures,expanding the range of available working fluids.

关键词： Loop heat pipe with a flat evaporator reinforced structure secondary wick

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EagerLog: Active Learning Enhanced Retrieval Augmented Generation for Log-based Anomaly Detection

EagerLog: Active Learning Enhanced Retrieval Augmented Gener...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Duan, Chiming Jia, Tong Yang, Yong Liu, Guiyang Liu, Jinbu Zhang, Huxing Zhou, Qi Li, Ying Huang, Gang School of Software and Microelectronics Peking University Beijing China Institute for Artificial Intelligence Peking University Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China National Key Laboratory of Data Space Technology and System Beijing China Alibaba Cloud Computing Company Hangzhou China

ISBN: (纸本)9798350368741

Logs record essential information about system operations and serve as a critical source for anomaly detection, which has generated growing research interest. Utilizing large language models (LLMs) within a retrieval-augmented generation (RAG) framework for log-based anomaly detection is an effective approach due to its strong generalization capabilities and efficient few-shot performance. However, the effectiveness of this method hinges on the quality of the knowledge source, which can be impacted by noise and changes within the software systems. Facing these problems, in this paper, we propose a novel log-based anomaly detection method named EagerLog, employing active learning to choose the logs for humans to label, thereby adding them to the knowledge source, thus enhancing the knowledge source and maintaining its quality. Our experiments on three open datasets (BGL, Thunderbird, Zookeeper) and one industrial dataset demonstrate that EagerLog can achieve 93.65% F1 score with approximately 10 labeled log sequences, surpassing existing methods by 15.32%. © 2025 IEEE.

关键词： Active Learning Anomaly Detection Log Analysis Retrieval Augmented Generation

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An end-to-end repair-based joint training framework for weakly supervised pavement crack segmentation

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Multimedia Tools and Applications 2024年第16期84卷 1-19页

作者： Zhou, Hui Tao, Huanjie Duan, Qianyue Hu, Zhenwu Deng, Yishi School of Computer Science Northwestern Polytechnical University Xi’an710129 China School of Cyberspace Security Northwestern Polytechnical University Xi’an710129 China Engineering Research Center of Embedded System Integration Ministry of Education Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China

Weakly supervised pavement crack segmentation aims to assign each pixel of pavement surface images a category label (crack or non-crack) using limited annotation information. Most existing methods adopt the multi-stage approach based on the class activation map (CAM), which outputs from a pre-trained crack classification model, to generate the pixel-level pseudo labels, and then train a segmentation model using these pseudo labels. However, these methods have two notable drawbacks: (i) CAM focuses primarily on the most discriminative regions of the image, potentially resulting in an incomplete estimation of crack regions, and (ii) the process of obtaining pixel-level pseudo labels from CAM is complex and may introduce noise. To avoid these issues, we propose an end-to-end repair-based joint training framework for weakly supervised pavement crack segmentation. Specifically, to better guide the model to pay more attention to the repair process of crack regions, we introduce the segmentation loss, which assigns different weights for crack regions and background regions, through the Residual Project Network. Additionally, to alleviate the impact of the domain gap between synthetic and real datasets, we introduce the consistency loss through the joint training paradigm of unpaired data that incorporates both crack and non-crack images into the training process simultaneously. Furthermore, to enable the model to effectively extract local features and reduce the model's computational complexity, we introduce the Lightweight Multi-head Self-attention module. The experiment results on the CRACK500 dataset, the CFD dataset, and the AEL dataset demonstrate that our model achieves better performance than some existing weakly supervised pavement segmentation methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Repair

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Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms 13

Last-X-Generation Archiving Strategy for Multi-Objective Evo...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Shu, Tianye Nan, Yang Shang, Ke Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China Southern University of Science and Technology Shenzhen518055 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

ISBN: (纸本)9798350308365

For evolutionary multi-objective optimization algorithms (EMOAs), an external archive can be utilized for saving good solutions found throughout the evolutionary process. Recent studies showed that a solution set selected from an external archive is usually superior to the final population. That is, the incorporation of an external archive improves the performance of EMOAs. However, the computation time for maintaining an external archive is long, especially when the archive size is large. To solve this issue, a simple archiving strategy is to save all solutions generated in the last several generations. In this paper, we examine this archiving strategy for three representative EMOAs on artificial test problems (Minus-DTLZ and WFG) and real-world problems (RE). Our results show that archiving the last several generations clearly improves the performance of EMOAs without severely increasing the computation time. © 2024 IEEE.

关键词： Optimization algorithms

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Multiparameter sensitivity analysis of tilt-to-length coupling noise in Taiji test mass interferometer

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Journal of Astronomical Telescopes, Instruments, and systems 2025年第1期11卷

作者： Xie, Fei Peng, Xiaodong Tang, Wenlin Zhao, Mengyuan Ma, Xiaoshan UCAS Hangzhou Institute for Advanced Study School of Fundamental Physics and Mathematical Sciences Hangzhou China Chinese Academy of Sciences National Space Science Center Key Laboratory of Electronics and Information Technology for Space System Beijing China University of Chinese Academy of Sciences Beijing China Taiji Laboratory for Gravitational Wave Universe Hangzhou China Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Hangzhou China Xi'an University of Finance and Economics School of Information Xi'an China Chinese Academy of Sciences Institute of Engineering Thermophysics National Key Laboratory of Science and Technology on Advanced Light-duty Gas-turbine Beijing China

Tilt-to-length (TTL) coupling noise is a significant noise source for test mass interferometers in Laser Interferometer space Antenna or Taiji, but identifying key parameters is a challenge due to the large number of influencing factors and complex interrelationships. Simulation models based on the heterodyne interference process and the signal readout of the test mass interferometer were constructed to generate a dataset containing different parameters and corresponding to the longitudinal path length noise caused by TTL coupling. The eXtreme Gradient Boosting (XGBoost) model was employed to fit the nonlinear relationships between the parameters and TTL coupling noise. Based on the fitting results of the XGBoost model, the sensitivity of single factor and multiple factors was performed using SHapley Additive exPlanation (SHAP) values and attribution value matrix, and the results were validated by the analytical models. Without reducing the fitting accuracy, the parameter dimension was decreased from ∼60 to 11 according to sensitivities, retaining those most relevant to angular misalignment. The results showed that the angle of the test mass, the angle of the beam splitters and mirrors, and the lateral offset of the test mass had a significant impact on TTL coupling noise. The introduction of machine learning methods into the study of TTL coupling contributes to a deeper understanding of noise mechanisms and provides references for optimizing the instrument design of the Taiji program. © 2025 SPIE. All rights reserved.

关键词： Laser interferometry

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Research of photon counting imaging detector based on delay line anode 10

Research of photon counting imaging detector based on delay ...

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10th Symposium on Novel Optoelectronic Detection technology and Applications

作者： Liu, Yong'an Zhang, Yalong Yang, Xianghui Zhang, Ruili Liu, Zhe Sheng, Lizhi State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

Photon counting imaging detector based on microchannel plate (MCP) and position-sensitive anode readout has the ability to detect single photon, and has been widely used in space detection, high-energy physics and bioluminescence imaging. Traditionally, the detector consists of photocathode, electron multiplication part and position decoding part, in which position decoding is accomplished by position sensitive anode. The delay line anode not only has high spatial resolution and large detection area, but also has high count rate. Based on the principle of delay line decoding, an induction readout cross delay line anode (XDL) is designed and fabricated. And the performance of the detector is tested by using the experimental system. The results show that the width of XDL anode output pulse (FWHM) is about 4ns, the spatial resolution of the detector is better than 100μm, and the dark count rate is 2s). © 2025 SPIE.

关键词： Photocathodes

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Development of China's spaceborne SAR satellite,processing strategy,and application:take Gaofen-3 series as an example

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地球空间信息科学学报（英文版） 2024年第1期27卷 221-236页

作者： Guo Zhang Shunyao Wang Zhenwei Chen Yuzhi Zheng Ruishan Zhao Taoyang Wang Yu Zhu Xinzhe Yuan Wei Wu Weitao Chen State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina School of Law Wuhan UniversityWuhanChina School of Geomatics Liaoning Technical UniversityFuxinChina School of Remote Sensing and Information Engineering Wuhan UniversityWuhanChina Institute of Spacecraft System Engineering China Academy of Space TechnologyBeijingChina National Disaster Reduction Center of China Ministry of Emergency ManagementBeijingChina School of Computer Science China University of GeosciencesWuhanChina Key Laboratory of Space Ocean Remote Sensing and Application Ministry of Natural Resources of the People's Republic of ChinaBeijingChina

After mastering the key technologies of manufacturing spaceborne Synthetic Aperture Radar(SAR),China's SAR satellites have been successfully launched into *** the only civil microwave satellite listed in the"national High-resolution Earth Observation system Major Project,"the Gaofen-3(GF-3)01 satellite is the first C-band multi-polarization SAR satellite with a resolution of 1 ***-3 series satellites stand out among civil SAR satellites worldwide because of their high resolution,wide swath,high geometric radiation quality,multiple imaging modes,and long operation *** GF-3 series satellites as an example,this study introduces the development of China's civil SAR satellites,as well as their processing strategies and *** success of the GF-3 series satellites shows that China's SAR remote sensing technology has stepped into a new era of high-quality and high-precision Earth observations.

关键词： High-resolution Synthetic Aperture Radar(SAR) GaoFen-3(GF-3)satellites earth observation

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LSTM-BP Model: Enhancing Prediction Accuracy for Medium Earth Orbit Satellites 4

LSTM-BP Model: Enhancing Prediction Accuracy for Medium Eart...

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4th International Conference on Electronic Information Engineering and Computer technology, EIECT 2024

作者： Guo, Yang Li, Bingchuan Pang, Qinghao Yang, Xu Zhao, Zhengxu Liu, Xinghui Qingdao University of Technology Shandong Key Laboratory of Space Debris Monitoring and Low-orbit Satellite Networking Qingdao China National Astronomical Observatories Chinese Academy of Sciences Beijing China Shandong Vheng Data Technology Co. Ltd Qingdao University of Technology Yantai China

ISBN: (纸本)9798331528850

To improve the low accuracy of the SGP4 model in short-term orbit prediction for medium Earth orbit satellites and the instability in LSTM model training, this paper proposes and develops an LSTM-BP prediction model. Compared to the SGP4 model, the LSTM model enhances the learning of historical data, better handling long-term dependencies and improving the model's representation capability and accuracy. The LSTM-BP model not only increases prediction accuracy but also mitigates the gradient instability issue in LSTM models to some extent. The model has been validated through several sets of generalization experiments, with a significant reduction in error following corrections. For example, along the X-axis, the maximum absolute error decreased from 54.9795 km to 2.3821 km. © 2024 IEEE.

关键词： Prediction models

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