检索结果-内蒙古大学图书馆

35th IEEE International Symposium on Software Reliability engineering Workshops, ISSREW 2024

作者： Xing, Ying Huang, Jiaqi Wang, Guilong You, Yehao Yang, Bin Li, Xiaofeng Luo, Yixing Beijing University of Posts and Telecommunications School of Intelligent Engineering and Automation Beijing China Beijing University of Posts and Telecommunications School of Artifcial Intelligence Beijing China Yunnan Key Laboratory of Software Engineering Yunnan China China Unicom Research Institute Beijing China Beijing Institute of Control Engineering Software Development Center Beijing China

ISBN: (纸本)9798350367041

In recent years, the number of software vulnerabilities has gradually increased, posing a threat to the security of software, and identifying whether there are vulnerabilities in software is crucial for assuring its quality. With the development of deep learning, vulnerability detection based on deep learning has achieved good results. However, real-world software vulnerability datasets often suffer from class imbalance and a lack of labeled data, limiting the performance of deep learning models. Therefore, this paper proposes a data augmentation method to alleviate these two problems. Firstly, we treats samples with vulnerabilities in the dataset as code, and generates more samples with vulnerabilities through code refactoring to alleviate class imbalance issues. Secondly, we use the mixup method to perform linear interpolation on the embedding vectors which represent codes, and add the interpolated vectors into the training set, thereby increasing the amount of labeled training data. To evaluate our method, we conducted experiments on three projects of the Promise dataset. The experimental results show that our data augmentation method can effectively improve the effect of vulnerability detection. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Low-Latency and Energy-Efficient Task Scheduling for End-Edge-Cloud Collaborative Computing

Low-Latency and Energy-Efficient Task Scheduling for End-Edg...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Li, Jingyao Yuan, Haitao Ma, Yaofei Bi, Jing Yang, Jinhong Zhang, Jia School of Automation Science and Electrical Engineering Beihang University Beijing100191 China College of Computer Beijing University of Technology Beijing100124 China Cssc Systems Engineering Research Institute Beijing China Southern Methodist University Dept. of Computer Science DallasTX75275 United States

ISBN: (纸本)9781665410205

Mobile edge computing (MEC) is a new paradigm that improves the quality of service compared with traditional cloud computing. In MEC, computational tasks are submitted by numerous end users and are partially offloaded to edge servers or a central cloud. However, the characteristics of tasks are different from each other, and the limited resources of computational nodes are also heterogeneous, which brings great challenges to computation offloading and resource allocation for MEC. This work establishes an end-edge-cloud collaborative computing network, which consists of end devices, edge servers, and a central cloud. Task execution location and CPU running frequency determine the execution time and energy consumption to finish the tasks. Considering the aforementioned factors, a multi-objective constrained optimization problem is formulated. To solve the problem, an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) with self-adaptive crossover and mutation rates is proposed, which is called Improved NSGA-II with _Self-adaptive Crossover and Mutation (INSCM). The total execution time and energy consumption can be jointly minimized with our proposed INSCM. Numerous experiments are carried out to test the performance of INSCM. Simulation results show that INSCM effectively improves the performance of NSGA-II and surpasses random offloading and NSGA-III, which shows practical use in real-life scenarios. © 2024 IEEE.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

引用

computers, Materials & Continua 2023年第1期74卷 801-815页

作者： Yongjie Yang Shanshan Tu Raja Hashim Ali Hisham Alasmary Muhammad Waqas Muhammad Nouman Amjad Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Information Security and Cybersecurity Unit King Khalid UniversityAbhaSaudi Arabia Computer Engineering Department College of Information TechnologyUniversity of Bahrain32038Bahrain School of Engineering Edith Cowan UniversityJoondalup PerthWA6027Australia School of Engineering University of Management and TechnologyLahorePakistan

With the recent developments in the Internet of Things(IoT),the amount of data collected has expanded tremendously,resulting in a higher demand for data storage,computational capacity,and real-time processing *** computing has traditionally played an important role in establishing ***,fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility,location awareness,heterogeneity,scalability,low latency,and geographic ***,IoT networks are vulnerable to unwanted assaults because of their open and shared *** a result,various fog computing-based security models that protect IoT networks have been developed.A distributed architecture based on an intrusion detection system(IDS)ensures that a dynamic,scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is *** this study,we examined the time-related aspects of network traffic *** presented an intrusion detection model based on a twolayered bidirectional long short-term memory(Bi-LSTM)with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark *** showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy,precision,recall and F1 score.

关键词： Fog computing intrusion detection bi-LSTM attention mechanism

来源：评论

学校读者我要写书评

暂无评论

Finite element joint simulation model applied to fast mechanical switching of controlled resonance combination circuit breakers

引用

High Voltage 2025年第2期10卷 419-435页

作者： Puyi Cui Guoli Li Zehui Sun Jiazi Xu Guoyong Zhang Zhong Chen Weiping Guan School of Electrical Engineering and Automation Anhui UniversityHefeiChina Engineering Research Center of Power Quality Ministry of EducationAnhui UniversityHefeiChina Anhui Key Laboratory of Industrial Energy-Saving and Safety Anhui UniversityHefeiChina Anhui Collaborative Innovation Center of Industrial Energy-Saving and Power Quality Control Anhui UniversityHefeiChina Anhui Zhengguangdian Electric Power Technology Co. HefeiChina Electric Power Research Institute of State Grid Anhui Electric Power Co. Ltd.HefeiChina

Fast mechanical switches(FMSs)are critical components of DC circuit breakers(DCCBs),which require the switch action time to break to a sufficient distance within 3 ms in the DC line breaking scenario,while ensuring a long service *** breaking mechanism significantly affects the current interruption capability of *** operation of the repulsion mechanism,along with the morphology of the arc and its transformation within the interrupter chamber,collectively influence the breaking performance of the *** paper presents a comprehensive analysis of the FMSs,which serves as the pivotal component of controlled resonance combination circuit breakers(CRCBs).This study establishes a multi physics coupling simulation analysis method based on the equivalent circuit of repulsion mechanism discharge,combined with electromagnetic and solid mechanics *** constructing a full cycle magnetohydrodynamic particle arc(MHP)model and using a combined simulation of Finite Element joint model(FEJM),the evolution law of arc characteristics during the superimposed current interruption process was systematically *** focus was on analysing the physical process of the zero zone of the superimposed arc,the multi physics field coupling relationship of the arc,and the interaction mechanism with external characteristic *** combining with optimisation design methods,the effectiveness of the model was verified through experiments,FEJM provides comprehensive technical support for effectively reflecting the stress issues of core components during the breaking process of FMS and can provide accurate theoretical references for the optimisation design of mechanical motion components in *** also accurately represents the arc extinguishing process during the breaking of FMS and provides a convenient method for the selection and design of circuit parameters for the entire circuit breaker.

关键词： dc circuit breakers dccbs which interrupter chambercollectively dc line breaking repulsion mechanismalong fast mechanical switching breaking mechanism fast mechanical switches fmss finite element joint simulation model

来源：评论

学校读者我要写书评

暂无评论

Modeling and Calculation of Temperature Field in Slotless Motor Based on a New Lumped Parameter Thermal Network Method 26

Modeling and Calculation of Temperature Field in Slotless Mo...

引用

26th International Conference on Electrical Machines and Systems, ICEMS 2023

作者： Zhao, Jing Guo, Penglei Zheng, Yun Wang, You Yang, Lei Beijing Institute of Technology School of Automation Beijing China Beijing Aerospace Control Instrument Research Institute Department of Motor Power Supply Beijing China Beijing Institute of Control Engineering Beijing Key Laboratory of Long-life Technology of Precise Rotation and Transmission Mechanisms Beijing China

ISBN: (纸本)9798350317589

In order to achieve accurate analysis of the motor temperature field, the temperature field of the slotless motor is modeled and calculated based on the centralized parametric thermal network method. The distribution of the motor thermal network nodes is given, and the axial model of the motor is divided. By deriving the thermal resistance model of each component of the slotless motor, a full-domain thermal resistance network model of the motor is constructed, and the accuracy of the model is verified by comparing the results with the finite element simulation. © 2023 IEEE.

关键词： Finite element method

来源：评论

学校读者我要写书评

暂无评论

Corrosion Resistance Enhancement of Pure Zirconium in Various Environments via Microstructure Tailoring

引用

稀有金属材料与工程 2024年第8期53卷 2109-2122页

作者： Xia Chaoqun Li Ke Cui Ziyao Song Tianshuo Wu Xinyu Liu Shuguang ZouXianrui Zhang Shiliang Yang Tai Li Qiang Tianjin Key Laboratory of Materials Laminating Fabrication and Interface Control Technology School of Materials Science and EngineeringHebei University of TechnologyTianjin 300401China Industrial Technology Research Institute Hebei University of TechnologyTianjin 300401China Engineering Research Center for Electrophysical Apparatus and Application Technology Beijing Research Institute of Automation for Machinery Industry Co.LtdBeijing 100120China

The corrosion properties of pure zirconium(Zr)with different grain sizes in acid,alkali,and salt environments were *** microstructures of pure Zr were observed by optical microscope,X-ray diffractometer,and electron backscattered diffraction *** corrosion resistance of pure Zr was analyzed by electrochemical corrosion test and immersion *** show that pure Zr with grain size of 4–32μm can be obtained after annealing at 800°C for different durations,and the relationship between grain size and annealing duration is D^(3)−D_(0)^(3)=*** electrochemical corrosion and immersion corrosion test results show that the pure Zr with grain size of about 24μm(annealing at 800°C for 20 h)possesses the optimal corrosion resistance.

关键词： pure zirconium grain size various environments corrosion resistance

来源：评论

学校读者我要写书评

暂无评论

A Novel Hybrid Transformer-Based Framework for Solar Irradiance Forecasting under Incomplete Data Scenarios

引用

IEEE Transactions on Industrial Informatics 2024年第6期20卷 8605-8615页

作者： Zhang, Hanjin Li, Bin Su, Shun-Feng Yang, Wankou Xie, Liping Southeast University School of Economics and Management Nanjing210096 China National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518063 China

Accurate prediction of solar irradiance is crucial for the effective utilization of solar energy. However, in real-world scenarios, complex irradiance patterns and prevalent incomplete data pose challenges to precise forecasting, resulting in additional uncertainties and instability. To address these issues, this study proposes a novel irradiance forecasting model that integrates a Mask-Transformer data imputation module and a prediction module centered around the typical patterns representation mechanism. The Mask-Transformer leverages a mask modeling mechanism to model the context of missing data, facilitating accurate estimation of missing values and reducing noise and uncertainty in the input data. The typical patterns representation mechanism comprises a series decomposition module and a feature fusion module, providing the module with the capability to mitigate nonlinearity and nonstationarity in solar irradiance data. This enhancement leads to improved short-term forecasting performance while maintaining long-term forecasting capabilities. Experimental results on two datasets demonstrate that the proposed model exhibits sufficient robustness and accuracy, making it effective in scenarios with incomplete data. © 2005-2012 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Cubature Kalman Fusion Filtering Under Amplify-and-Forward Relays With Randomly Varying Channel Parameters

引用

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 356-368页

作者： Jiaxing Li Zidong Wang Jun Hu Hongli Dong Hongjian Liu the Department of Applied Mathematics Harbin University of Science and Technology IEEE the Department of Computer Science Brunel University London the School of Automation Harbin University of Science and Technology the Artificial Intelligence Energy Research Institute Northeast Petroleum University the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University the National Key Laboratory of Continental Shale Oil of China Northeast Petroleum University the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University the School of Mathematics and Physics Anhui Polytechnic University

In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.

关键词： Amplify-and-forward (AaF) relays covariance intersection fusion cubature Kalman filtering multi-sensor systems uniform boundedness

来源：评论

学校读者我要写书评

暂无评论

Strategic Gradient Transmission With Targeted Privacy-Awareness in Model Training: A Stackelberg Game Analysis

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4635-4648页

作者： Sun, Hezhe Wang, Yufei Yang, Huiwen Huo, Kaixuan Li, Yuzhe Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China Liaoning ATS Intelligent Transportation Technology Company Ltd. Research Institute Shenyang110004 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong999077 Hong Kong

Privacy-aware machine learning paradigms have sparked widespread concern due to their ability to safeguard the local privacy of data owners, preventing the leakage of private information to untrustworthy platforms or malicious third parties. This article focuses on characterizing the interactions between the learner and the data owner within this privacy-aware training process. Here, the data owner hesitates to transmit the original gradient to the learner due to potential cybersecurity issues, such as gradient leakage and membership inference. To address this concern, we propose a Stackelberg game framework that models the training process. In this framework, the data owner's objective is not to maximize the discrepancy between the learner's obtained gradient and the true gradient but rather to ensure that the learner obtains a gradient closely resembling one deliberately designed by the data owner, while the learner's objective is to recover the true gradient as accurately as possible. We derive the optimal encoder and decoder using mismatched cost functions and characterize the equilibrium for specific cases, balancing model accuracy and local privacy. Numerical examples illustrate the main results, and we conclude with expanding discussions to suggest future investigations into reliable countermeasure designs. © 2020 IEEE.

关键词： Game theory

来源：评论

学校读者我要写书评

暂无评论

Quasi-Z Source Inverter control of PV Grid-Connected Based on Fuzzy PCI

引用

Journal of Electronic Science and Technology 2021年第3期19卷 274-286页

作者： Tao Hou Chen-Yang Zhang Hong-Xia Niu School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou 730070 Automatic Control Research Institute Lanzhou Jiaotong UniversityLanzhou 730070

The photovoltaic grid-connected inverter is an important interface between the photovoltaic power generation system and power *** high-quality operation is directly related to the output power quality of the power *** order to further optimize the control effect of the quasi-Z source grid-connected photovoltaic inverter,a fuzzy proportional complex integral control(PCI)method is proposed for the current internal loop *** method can eliminate the steady-state error,and has the characteristic of zero steady-state error adjustment for the AC disturbance signal of a specific *** inductance-capacitance-inductance(LCL)filter is adopted in the grid-connected circuit,and the feedback capacitive current is taken as the control variable of the inner loop to form the active damping control method,which can not only effectively suppress the resonance of the LCL circuit,but also significantly inhibit the high-order harmonics in the grid-connected ***,a system simulation model is built in MATLAB/Simulink to verify the superiority and effectiveness of the proposed method.

关键词： Frequency of harmonic distortion fuzzy proportional complex integral inductance-capacitance-inductance(LCL)filtering circuit photovoltaic grid-connection quasi-Z source inverter

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：