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IEEE International Conference on Robotics and Biomimetics

作者： Yu Wang Zhen Deng Yu Sun Binsheng Yu Peng Zhang Ying Hu Jianwei Zhang Harbin Institutes of Technology Shenzhen Graduate School Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences. The Chinese University of Hong Kong Peking University Shengzhen Hospital University of Hamburg Germany

ISBN: (纸本)9781467396769

To address the safety issues of bone drilling, especially bone screw path drilling, this paper proposes a new method to detect the bone drilling state. The proposed method performs pattern recognition based on the results of multi-sensor information fusion. A support vector machine is selected as the pattern classifier, and the adopted signals include the force, current, feed speed, rotation speed and deflection of the robotic arm. Four different drilling states, i.e., the cortical, cortical-transit-cancellous, almost-break-cortical and cancellous states, are detected, and then help the surgical robot system to achieve safe bone drilling. The proposed method is validated and analyzed through an experiments on pig scapula, and found to have potential clinical application to the bone drilling process in vertebral, leg, ear bone, mandible, and other related orthopedic surgeries.

关键词： Bone drilling multi-sensor information fusion state detection support vector machine

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Wei Li Junfei Qiao Xiao-Jun Zeng College of Electronic Information and Control Engineering Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China School of Computer Science University of Manchester Manchester U.K

ISBN: (纸本)9781467376839

This paper provides a complete solution for the problem how to accurately compute the similarity between fuzzy sets with Gaussian membership functions, which is a fundamental issue for the identification and simplification of FNNs. It is shown that there are three different types of similarities between a pair of Gaussian membership functions dependent on the relative positioning between the given pair of membership functions, and the accurate and detailed computing formulas are given in each type. A simulation example is given to compare the proposed accurate similarity analysis method with the existing approximation approaches and to show how much more accuracy can be obtained than the approximation one in terms of absolute percentage approximation error.

关键词： Fuzzy sets Fuzzy neural networks Shape Computational modeling Bismuth Knowledge discovery

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A Novel Gradient Descent Least Squares (GDLS) Algorithm for Efficient SMV Gridless Line Spectrum Estimation with Applications in Tomographic SAR Imaging

arXiv

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arXiv 2022年

作者： Shi, Ruizhe Zhang, Zhe Qiu, Xiaolan Ding, Chibiao School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Intelligent Aerospace Big Data Application Technology Jiangsu Suzhou215123 China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing100190 China

This paper presents a novel efficient method for gridless line spectrum estimation problem with single snapshot, namely the gradient descent least squares (GDLS) method. Conventional single snapshot (a.k.a. single measure vector or SMV) line spectrum estimation methods either rely on smoothing techniques that sacrifice the array aperture, or adopt the sparsity constraint and utilize compressed sensing (CS) method by defining prior grids and resulting in the off-grid problem. Recently emerged atomic norm minimization (ANM) methods achieved gridless SMV line spectrum estimation, but its computational complexity is extremely high;thus it is practically infeasible in real applications with large problem scales. Our proposed GDLS method reformulates the line spectrum estimations problem into a least squares (LS) estimation problem and solves the corresponding objective function via gradient descent algorithm in an iterative fashion with efficiency. The convergence guarantee, computational complexity, as well as performance analysis are discussed in this paper. Numerical simulations and real data experiments show that the proposed GDLS algorithm outperforms the state-of-the-art methods e.g., CS and ANM, in terms of estimation performances. It can completely avoid the off-grid problem, and its computational complexity is significantly lower than ANM. Our method has been tested in tomographic SAR (TomoSAR) imaging applications via simulated and real experiment data. Results show great potential of the proposed method in terms of better cloud point performance and eliminating the gridding effect. Copyright © 2022, The Authors. All rights reserved.

关键词： Spectrum analysis

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EAN-MapNet: Efficient Vectorized HD Map Construction with Anchor Neighborhoods

arXiv

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arXiv 2024年

作者： Xiong, Huiyuan Shen, Jun Zhu, Taohong Pan, Yuelong School of Intelligent Systems Engineering Sun Yat-sen University China Guangdong Provincial Key Laboratory of Intelligent Transport System China China Nuclear Power Design Co. Ltd. China State Key Laboratory of Nuclear Power Safety Technology and Equipment China Nuclear Power Engineering Co. Ltd. Guangdong Shenzhen518172 China

High-definition (HD) map is crucial for autonomous driving systems. Most existing works design map elements detection heads based on the DETR decoder. However, the initial queries lack explicit incorporation of physical positional information, and vanilla self-attention entails high computational complexity. Therefore, we propose EAN-MapNet for Efficiently constructing HD map using Anchor Neighborhoods. Firstly, we design query units based on the anchor neighborhoods, allowing non-neighborhood central anchors to effectively assist in fitting the neighborhood central anchors to the target points representing map elements. Then, we propose grouped local self-attention (GL-SA) by leveraging the relative instance relationship among the queries. This facilitates direct feature interaction among queries of the same instances, while innovatively employing local queries as intermediaries for interaction among queries from different instances. Consequently, GL-SA significantly reduces the computational complexity of self-attention while ensuring ample feature interaction among queries. On the nuScenes dataset, EAN-MapNet achieves a state-of-the-art performance with 63.0 mAP after training for 24 epochs, surpassing MapTR by 12.7 mAP. Furthermore, it considerably reduces memory consumption by 8198M compared to MapTRv2. Copyright © 2024, The Authors. All rights reserved.

关键词： Computational complexity

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Towards Query-Efficient Decision-Based Adversarial Attacks Through Frequency Domain

Towards Query-Efficient Decision-Based Adversarial Attacks T...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jianhao Fu Xiang Ling Yaguan Qian Changjiang Li Tianyue Luo Jingzheng Wu Intelligent Software Research Center Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences Nanjing Nanjing Institute of Software Technology Key Laboratory of System Software (Chinese Academy of Sciences) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Zhejiang University of Science and Technology Stony Brook University

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Deep neural networks are vulnerable to adversarial examples, where decision-based attacks can generate adversarial examples based solely on the predicted labels. However, these attacks typically require excessive queries to attack one example. Considering this challenge, we propose FBA (Frequency based Boundary Attack), a decision-based attack against the limitation of query efficiency. FBA incorporates a novel search process, utilizing high-frequency based importance sampling for efficient gradient estimation. Empirical results confirm the superior query efficiency of our method. Specifically, FBA surpasses SOTA attacks by achieving a 54% average improvement in query efficiency, quantified by the reduction in perturbation size within the same number of queries.

关键词： Technological innovation Monte Carlo methods Frequency-domain analysis Perturbation methods Estimation Artificial neural networks

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A Novel Neutral-Point Potential Balance Control Method Based on Voltage Feedback for Neutral-Point Clamped Three-Level Inverter

SSRN

引用

SSRN 2022年

作者： Fan, Bo Cao, Zhe Wang, Chunguang Niu, Zongxian Yang, Chenhui Wu, Xiaodan Information Engineering College Henan University of Science and Technology Luoyang471023 China Henan Key Laboratory of Robot and Intelligent Systems Henan University of Science and Technology Luoyang471023 China KRC Crane System Co. Ltd Luoyang471023 China

Neutral-point potential imbalance is not only an inherent problem of neutral-point clamped three-level converters, but also the key factor affecting their performance. The traditional capacitor neutral-point potential balance control methods based on space vector modulation, such as VSVPWM, have several shortcomings including the uncompensated region of neutral-point voltage and the slow dynamic response. A novel voltage feedback control method on neutral-point potential balance is proposed in this paper. A coefficient is introduced to define the degree of neutral-point potential imbalance. The composite signal composed of this coefficient and neutral point current is designed. Based on the improved reasonable sectors' division, the suitable small vectors are selected by this composite signal to obtain the switching sequence of power devices. The voltage feedback control method is employed to realize accurate neutral-point potential balance of NPC three-level inverter. The experimental results show that this method can quickly balance the neutral-point potential fluctuation caused by disturbance. It has the advantages of low switching loss, stable output voltage and current waveform, and good dynamic performance. © 2022, The Authors. All rights reserved.

关键词： Voltage control

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Mid-Iong Term Photovoltaic Power Forecasting Method Considering Periodicity Characterization

Mid-Iong Term Photovoltaic Power Forecasting Method Consider...

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IEEE/IAS Industrial and Commercial Power system Asia (I&CPS Asia)

作者： Minyi Zhuo Ming Yang Peng Li Yi Sun Rui Liu Zhijie Zheng Bingke Shi Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan China Power Grid Planning Research Department Economic & Technology Research Institute of State Grid Shandong Electric Power Company Jinan China

ISBN: (数字)9798350352290

ISBN: (纸本)9798350352306

Accurate forecasting of mid-long term photovoltaic power plays a key role in site planning, operation scheduling and mid-long term plan development for new power system. Meanwhile, the uncertainty in solar power generation is a key factor influencing the precision of its forecasting. This paper proposes a mid-long term PV power forecasting method considering periodic characterization, which first obtains the key meteorological factors through the maximal information coefficient, and extracts the timing features through ARIMA model for mid-long term PV power periodic component prediction. Then the results obtained from above are inputted to the LSTM model, which is trained using raw data to obtain the final PV power prediction results with high accuracy. Validation is carried out through the model's RMSE, MAE and MAPE metrics and the comparison of the model's forecasting results with traditional GRU model.

关键词： Photovoltaic systems Accuracy Uncertainty Meteorological factors Predictive models Feature extraction Data models Power systems Planning Forecasting

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Traffic Control Task Scheduling Optimization Approach of Urban Road Intersection Based on Edge Computing

Traffic Control Task Scheduling Optimization Approach of Urb...

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Artificial Intelligence, Networking and Information technology (AINIT), International Seminar on

作者： Xiang Fu Fei Wang Nan Ji Yilong Ren School of Transportation Science and Engineering Beihang University BUAA Beijing China Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China Intelligent Transport System (ITS) R & D Center Shanghai Urban Construction Design and Research Institute (Group) Co. Ltd. Shanghai China

ISBN: (纸本)9781665412971

With the development of Connected Automated Vehicles (CAV), there will be a long period of mixed driving, which causes the traffic control task at intersections becomes much more complicated. The control tasks would include not only the traffic signal timing optimization but also the computing tasks for different levels of vehicles. Current control task management methods are proved to be inferior to solve this problem. In this paper, we propose an intersection control task scheduling optimization approach based on edge computing. Firstly, the traffic control edge computing system for intersections is constructed. Then, different types of control tasks are listed. Criticality and timeliness are introduced to calculate the control task's dynamic priority. The control task scheduling optimization model, which considering these two parameters is proposed. At last, the improved Hungarian algorithm is applied to solve the proposed task scheduling optimization model. Simulation results show that our proposed methods can effectively reduce task processing costs and ensure the critical tasks execute firstly.

关键词： Processor scheduling Computational modeling Heuristic algorithms Traffic control Scheduling Timing Task analysis

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Analysis of influencing factors in hybrid state estimation

Analysis of influencing factors in hybrid state estimation

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Xueliang Yu Hengxu Zhang Jianmei Cao Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan P. R. China State Grid of China Technology College Jinan P. R. China

ISBN: (纸本)9781509054190

Hybrid state estimation has become a significant tool to utilize PMU measurements in modern power dispatch center. Factors affecting estimation accuracy are discussed in this paper, including measurement number, PMU number and measurement uncertainty. And it also explores the extent of impacts with simulation results. PMU current phasors are transformed into pseudo power injections and their uncertainties are calculated by uncertainty propagation theory. PMU numbers and their optimal deployment are determined by integer quadratic programming approach. Monte Carlo simulations are carried out in IEEE 14-bus system in this paper.

关键词： Phasor measurement units Measurement uncertainty Transmission line measurements Power measurement Voltage measurement Current measurement Uncertainty

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User Behavior-Based Collaborative Filtering Recommendation Algorithm and Visualization in Second-Hand Trading Platform

User Behavior-Based Collaborative Filtering Recommendation A...

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Sensors, Electronics and Computer Engineering (ICSECE), IEEE International Conference on

作者： Rui Qiao Xin Wang Xiaoben Zhong School of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei China China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan Hubei China Yunnan College of Business Management Anning China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

In the backdrop of the digital era, the demand for second-hand trading within campuses has seen a significant rise. This project aims at designing a second-hand trading platform that merges the latest technological trends, providing a secure and convenient trading environment for students. The system utilizes Spring Boot for backend development and Vue along with ElementUI for constructing the user interface, ensuring efficient operation and enhancing user interaction experience. The server employs Spring Boot's built-in Tomcat, simplifying the deployment process. For data persistence, Mybatis framework is used for flexible and efficient interactions with the MySQL database. The platform introduces a collaborative filtering algorithm based on user behavior for smart product recommendations, further improving the user experience. The system integrates core modules such as user management, product browsing, shopping cart functionalities, and order processing, innovatively introducing an offline transaction confirmation mechanism to ensure transaction security and reliability while avoiding legal risks associated with online payments. With its B/S architecture, the platform operates more smoothly, making it more accessible to users. Experimental results demonstrate that the platform has a user-friendly interface and efficient data processing capabilities, receiving widespread recognition and praise from users, proving its practicality and innovativeness.

关键词： Law Collaborative filtering Market research User experience Sensor systems Servers Security Reliability Springs intelligent sensors

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