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GTE: learning code AST representation efficiently and effectively

Science China(Information Sciences) 2025年第3期68卷 393-394页

作者： Yihao QIN Shangwen WANG Bo LIN Kang YANG Xiaoguang MAO College of Computer Science and Technology National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems National University of Defense Technology

With the development of deep learning in recent years, code representation learning techniques have become the foundation of many software engineering tasks such as program classification [1] and defect detection. Earlier approaches treat the code as token sequences and use CNN, RNN, and the Transformer models to learn code representations.

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How does supergravity affect combustion?

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Acta Mechanica Sinica 2024年第6期40卷 39-40页

作者： Wenjun Kong Zheng Chen School of Astronautics Beihang UniversityBejing 102206China State Key Laboratory of Turbulence and Complex System Cllege of EngineeringPeking Universy Beijing 100871Chin

It is well known that gravity may have a profound impact on the combustion process under certain conditions[1].The densities of the gaseous combustion products are typically 5-12 times lower than those of *** normal gravity conditions,the density difference generates buoyant forces that drive the flow,which affects the combustion process through flow-transport-chemistry *** example,the buoyant convection in normal gravity causes the candle flame to be shaped like a teardrop while spherical candle flame is observed in ***,microgravity combustion has drawn great attention.A series of combustion experiments have been and will be conducted in the International Space Station and Chinese Space *** fact,significant progress has been made in microgravity *** example,the discovery of steadily burning cool flames[2]in microgravity experiments was regarded as one of the"20 Breakthroughs from 20 Years of Science aboard the International Space Station".

关键词： interaction. reactant typically

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Parallel system Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control

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CSEE Journal of Power and Energy systems 2024年第1期10卷 13-28页

作者： Tianyun Zhang Jun Zhang Feiyue Wang Peidong Xu Tianlu Gao Haoran Zhang Ruiqi Si School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072HubeiChina State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence ***,there is,currently,nearly no standard technical framework for objective and quantitative intelligence *** this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation *** this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment *** results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.

关键词： AI quantitative intelligence assessment and self-evolution automated reinforcement learning Bayesian optimization corrective control parallel system

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ForkXplorer:an approach of fork summary generation

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Frontiers of Computer Science 2022年第2期16卷 1-15页

作者： Zhang ZHANG Xinjun MAO Chao ZHANG Yao LU Key Laboratory of Software Engineering for Complex Systems College of ComputerNational University of Defense TechnologyChangsha 410073China

Pull-based development has become an important paradigm for distributed software *** this model,each developer independently works on a copied repository(i.e.,a fork)from the central *** is essential for developers to maintain awareness of the state of other forks to improve collaboration *** this paper,we propose a method to automatically generate a summary of a *** first use the random forest method to generate the label of a fork,i.e.,feature implementation or a bug *** on the information of the fork-related commits,we then use the TextRank algorithm to generate detailed activity information of the ***,we apply a set of rules to integrate all related information to construct a complete fork *** validate the effectiveness of our method,we conduct 30 groups of manual experiment and 77 groups of case studies on *** propose Fea_(avg)to evaluate the performance of Fea_(avg)the generated fork summary,considering the content accuracy,content integrity,sentence fluency,and label extraction *** results show that the average of of the fork summary generated by this method is *** than 63%of project maintainers and the contributors believe that the fork summary can improve development efficiency.

关键词： open source software pull-based development fork summary distributed cooperative development

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Rare earth metal based DES assisted the VPO synthesis for n-butane selective oxidation toward maleic anhydride

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Green Energy & Environment 2023年第6期8卷 1737-1752页

作者： Muhammad Faizan Yingwei Li Xingsheng Wang Piao Song Ruirui Zhang Ruixia Liu Beijing Key Laboratory of Ionic Liquids Clean Process CAS Key Laboratory of Green Process and EngineeringState Key Laboratory of Multiphase Complex SystemInstitute of Process Engineering Chinese Academy of SciencesBeijing100190China University of Chinese Academy of Sciences Beijing100049China Zhengzhou Institute of Emerging Industrial Technology Zhengzhou450000China

Deep eutectic solvents(DESs) are now considered a new class of ionic liquid analogs that have been generously used in various ***, vanadium phosphorus oxide(VPO) catalysts are synthesized in combination with a deep eutectic solvent containing rare earth metal(rE-DES), and their catalytic performance in n-butane selective oxidation to produce maleic anhydride(MA) is evaluated. The rE-DES is produced from the interaction of choline chloride(ChCl) and rare earth metal salts(Cerium, Europium, Lanthanum, and Samarium metal salt)(ChCl:rE = 1:0.5–1:3) under mild conditions. It was found that DESs served as structural modifiers and electronic promoters during VPO synthesis. It regulated the chemical state of the catalyst surface, such as the vanadium valence state, acid-base properties, and ratios of V^(4+)/V^(5+),Lat–O/Sur–O and P/V. Various characterization techniques, such as FT-IR, DSC, XRD, SEM, EDS, TEM, Raman, TGA, NH3-TPD, and XPS,were used to examine its physical and chemical characteristics. These characteristics were correlated with the catalytic performance. The VPO catalyst modified by rE-DES showed a significant enhancement of n-butane conversion and MA selectivity while suppressing the selectivity of CO and CO_(2)as well as the CO/CO_(2)ratio compared to the unpromoted VPO catalyst. Especially for Ce-DES-VPO, it increased the n-butane conversion and MA mass yield up to approximately 11% and 10%, respectively. In addition, we evaluated the catalytic performance under different activation atmospheres.

关键词： earth anhydride vanadium

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Deep learning-based software engineering: progress,challenges, and opportunities

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Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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Nonlinear impedance control with trajectory adaptation for collaborative robotic grinding

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Science China(Technological Sciences) 2023年第7期66卷 1928-1936页

作者： HAN FengTao TAM SikYuen CAO ZhiHong ZHAO XingWei TAO Bo DING Han State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Intelligent Manufacturing System Technology for Complex Products Beijing Institute of Electronic System EngineeringBeijing 100854China ROKAE(Beijing)Technology Co. Ltd.Beijing 100193China

Stiffness adjustment is an important feature of human arm *** adaptive variable impedance control can adapt to the robotic stiffness,but may result in a large *** this paper,nonlinear impedance control is proposed for collaborative robotic grinding,where nonlinear force feedback is designed to compensate for the nonlinear stiffness of the ***,the interaction system can be linearization to ensure the system ***,a target trajectory adaptation strategy is studied to ensure the force tracking ***,switching law between trajectory tracking and force tracking is proposed when the robot performs a complex grinding *** stability of the switch control as well as the trajectory adaptation law is *** are conducted in a robotic grinding test rig,where the robot is used to grind a turbine *** results show that the nonlinear impedance control can obtain stable grinding force,and have better grinding quality than the linear impedance control.

关键词： impedance control robotic grinding trajectory adaptation force tracking

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Neighborhood Subgraph-based Illicit Transaction Detection in Cryptocurrency Networks 12

Neighborhood Subgraph-based Illicit Transaction Detection in...

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12th IEEE International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2024

作者： Jin, Shenghao Yang, Qiwen Chen, Shengyu Zhang, Hui Beihang University State Key Laboratory of Complex & Critical Software Environment School of Computer Science & Engineering Beijing China

ISBN: (纸本)9798331510633

With the widespread adoption of cryptocurrencies, associated illicit activities such as money laundering, fraud, extortion, and Ponzi schemes have garnered significant attention. Traditional studies have extensively employed graph neural network technologies to identify illicit transactions, typically treating the entire transaction network as input to classify its nodes. Although these methods perform well on small-scale networks, they face performance limitations when processing large-scale blockchain transaction data. To address this issue, we propose a neighborhood subgraph-based method for detecting illicit transactions, integrating GCN and LSTM. In this approach, the GCN captures and integrates information from adjacent nodes for each transaction, facilitating a deep understanding of network structures. The LSTM is tasked with capturing the sequence and variations in fund flows, effectively tracking the direction and temporal characteristics of the money flow. Experimental results indicate that when using 3-hop neighborhood subgraphs, our model's performance surpasses other GCN-based methods. Compared to previous models that require considering the entire transaction network, our approach only needs to utilize information from an average of 80 nodes, significantly improving efficiency. © 2024 IEEE.

关键词： Graph neural networks

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Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

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Weak signal detection method based on novel composite multistable stochastic resonance

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Chinese Physics B 2023年第5期32卷 178-187页

作者：焦尚彬高蕊薛琼婕史佳强 Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China

The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer *** propose a novel composite multistable stochastic-resonance(NCMSR)model combining the Gaussian potential model and an improved bistable *** with the traditional multistable stochastic resonance method,all the parameters in the novel model have no symmetry,the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system *** model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation,the NCMSR model has a higher utilization of *** the output signal-to-noise ratio as the index,weak periodic signal is detected based on the NCMSR model in Gaussian noise andαnoise environment respectively,and the detection effect is *** application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer *** outstanding advantages of this method in weak signal detection are verified,which provides a theoretical basis for industrial practical applications.

关键词： weak signal detection composite multistable stochastic resonance bearing fault detection

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