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7th International Conference on High Performance Compilation, Computing and Communications, HP3C 2023

作者： Liu, Yifan Yuan, Quande Zhang, Guoyin School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China School of Computer Technology and Engineering Changchun Institute of Technology Jilin Changchun China

ISBN: (纸本)9781450399883

In traditional visual simultaneous localization and mapping (vSLAM) systems, feature points are critical for feature matching and pose estimation. However, visual odometry keyframes often contain many dynamic points, which can adversely affect the accuracy of the SLAM system. To address this issue, this paper proposes a dynamic feature point elimination algorithm based on the YOLOv5 target detection network and optical flow method using image processing techniques. Specifically, the YOLOv5 network is used to identify regions in the image that may contain dynamic objects, which are then divided into sub-regions. Depth information from the depth image and feature points from the dynamic regions are used to obtain feature points with depth information. These feature points are then clustered using the GMM clustering algorithm, and dynamic feature points are eliminated based on the clustering results. Experimental results show that the proposed algorithm effectively eliminates dynamic points in the image, thus improving the accuracy of the SLAM system. © 2023 ACM.

关键词： Optical flows

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Modeling of Trust in Social Relationships for Secure Communication in Social Internet of Things 4

Modeling of Trust in Social Relationships for Secure Communi...

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4th International Conference on Blockchain technology and Information Security, ICBCTIS 2024

作者： Khan, Salabat Amin, Farhan Khan, Mansoor School of Computer and Information Engineering Qilu Institute of Technology Shandong Jinan China School of Computer Science and Engineering Yeungnam University Korea Republic of School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Shandong Jinan China

ISBN: (纸本)9798331528324

Herein, a social trust model is presented for investigating social relationships and social networks in the real world. Our proposal addresses the design of conceptual concepts to easily implement and develop complex applications that require direct interaction among objects. The secure social relationship paradigm guarantees network navigability, even if there are more objects on the traditional Internet of Things (IoT). This paradigm shift is very interesting, but very limited researchers have worked in this direction. Therefore, the core objective of our article is to study and classify these objects and emphasize the importance and the characteristics of trust in social objects and their relationships. Herein, five types of secure social relationships were identified and explained with real scenarios. Finding new social relationships and understanding different features and characteristics helps the researcher understand their structure and, thus, build trust between smart objects. Based on these social relationships we propose secure social relationship modeling. The achieved experimental result shows that our proposed model outperforms as compared to the state-of-the-art model. The efficiency is measured based on processing time and precision. We present a critical alternative vision based on the most recent literature. We discuss social relations along with strengths and weaknesses. Our critical analysis guides the reader to understand this paradigm in-depth and its impact on future technologies, i.e., artificial social intelligence. We also present the major ongoing research activities and highlight the most important technical and critical challenges associated with these objects, such as inter-object relations, support and definition of new communication primitives, and security and privacy concerns. © 2024 IEEE.

关键词： Secure relationships Secure social network analysis Security Social Network Analytics Social networks Trust

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Triboelectric-electromagnetic hybrid generator with swing-blade structures for effectively harvesting distributed wind energy in urban environments

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Nano Research 2023年第9期16卷 11621-11629页

作者： Yangyang Yan Jinzhi Zhu Yuejun Zhang Zhaohui Wang Lin Jiang Zhong Lin Wang Jianyang Zhu Tinghai Cheng Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and TechnologyWuhan 430081China Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 101400China Georgia Institute of Technology AtlantaGA 30332-0245USA Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China

The wind energy in cities cannot be exploited effectively because natural wind is unstable and ***,a triboelectricelectromagnetic hybrid generator with swing-blade structures(SBS-TEHG)was designed to effectively harvest intermittent and continuous wind energy in an urban ***,the spring structure and base were considered to realize the maximum output performance of triboelectric ***,the computational fluid dynamics method was applied to optimize the structure of the SBS-TEHG to improve its aerodynamic *** starting wind speed of the SBS-TEHG was 2 m/s,and its energy conversion efficiency was 9.04%,159%higher than that of the SBS-TEHG without guide plates at 4 m/*** results demonstrated that the SBS-TEHG lit 105 light-emitting diodes(LEDs)under the intermittent-wind harvesting mode at a wind frequency of 1 Hz when the single swing blade operated,while a wireless PM_(2.5)&PM_(10)sensor was powered by the SBS-TEHG after a period of operation under the continuous-wind harvesting *** findings of this study provide a novel solution for lowspeed wind energy harvesting in cities and demonstrate the potential of SBS-TEHG as a distributed energy source.

关键词： triboelectric nanogenerator swing-blade structure low-speed wind energy computational fluid dynamics distributed energy source

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AFSTGCN:Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network

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Digital Communications and Networks 2024年第2期10卷 292-303页

作者： Yuteng Xiao Kaijian Xia Hongsheng Yin Yu-Dong Zhang Zhenjiang Qian Zhaoyang Liu Yuehan Liang Xiaodan Li School of Information and Control Engineering China University of Mining and TechnologyXuzhou221116China Department of Informatics University of LeicesterLeicesterLE17RHUK The Affiliated Changshu Hospital of Soochow University Changshu215500China School of Computer Science and Engineering Changshu Institute of TechnologySuzhou215500China

The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other ***,it is important to construct a digital twin ***,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted *** this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)***,we fuse the spatial-temporal graph based on the interrelationship of spatial ***,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding ***,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)*** module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like *** dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted *** on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.

关键词： Adaptive adjacency matrix Digital twin Graph convolutional network Multivariate time series prediction Spatial-temporal graph

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A Real-Time Semantic Segmentation Method Based on Transformer for Autonomous Driving

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computers, Materials & Continua 2024年第12期81卷 4419-4433页

作者： Weiyu Hao Jingyi Wang Huimin Lu Donald Bren School of Information and Computer Sciences University of CaliforniaIrvineCA 92612USA Department of Control Engineering Kyushu Institute of TechnologyKitakyushu804-8550Japan School of Automation Southeast UniversityNanjing210096China

While traditional Convolutional Neural Network(CNN)-based semantic segmentation methods have proven effective,they often encounter significant computational challenges due to the requirement for dense pixel-level predictions,which complicates real-time *** address this,we introduce an advanced real-time semantic segmentation strategy specifically designed for autonomous driving,utilizing the capabilities of Visual *** leveraging the self-attention mechanism inherent in Visual Transformers,our method enhances global contextual awareness,refining the representation of each pixel in relation to the overall *** enhancement is critical for quickly and accurately interpreting the complex elements within driving sce-narios—a fundamental need for autonomous *** experiments conducted on the DriveSeg autonomous driving dataset indicate that our model surpasses traditional segmentation methods,achieving a significant 4.5%improvement in Mean Intersection over Union(mIoU)while maintaining real-time *** paper not only underscores the potential for optimized semantic segmentation but also establishes a promising direction for real-time processing in autonomous navigation *** work will focus on integrating this technique with other perception modules in autonomous driving to further improve the robustness and efficiency of self-driving perception frameworks,thereby opening new pathways for research and practical applications in scenarios requiring rapid and precise decision-making *** experimentation and adaptation of this model could lead to broader implications for the fields of machine learning and computer vision,particularly in enhancing the interaction between automated systems and their dynamic environments.

关键词： Visual transformer semantic segmentation autonomous driving

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Stochastic Analysis of Cyber Threats in Information Systems

Stochastic Analysis of Cyber Threats in Information Systems

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2024 Wave Electronics and its Application in Information and Telecommunication Systems, WECONF 2024

作者： Sukhoplyuev, D.I. Nazarov, A.N. Institute Of Information Technology Mirea Russian Technology University Moscow Russia Federal Research Center Computer Science And Control Of Russian Academy Of Sciences Moscow Russia

ISBN: (纸本)9798350364989

This research delves into stochastic methods for density estimation, focusing on techniques such as kernel density estimation (KDE), jittering, and handling multimodality. It aims to leverage these methods to detect cyber threats based on the density distributions of system queries. KDE provides a nonparametric approach to estimating the probability density function of a random variable, allowing for flexible modeling of complex data patterns. Jittering introduces controlled randomness into data points, enhancing the robustness of density estimation against overfitting and improving generalization performance. Moreover, addressing multimodality is crucial for accurately capturing diverse behaviors within the query distributions, which is essential for cyber threat detection in heterogeneous environments. By combining these stochastic methods, this study seeks to enhance the reliability and efficiency of cyber threat detection systems by providing more nuanced insights into the underlying data distributions, thus enabling proactive measures against emerging threats. © 2024 IEEE.

关键词： Probability density function

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Comparison of Two AC Current De-tumbling Methods for Uncooperative Space Target through Electromagnetic Characteristic Analysis 1

Comparison of Two AC Current De-tumbling Methods for Uncoope...

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1st Aerospace Frontiers Conference, AFC 2024

作者： Du, Lei Chen, Zhen Hu, Hengzai Liu, Xiangdong Zhang, Qiang Zhang, Kemo Liu, Hui School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Control Engineering Beijing100191 China Beijing Institute Computer for Application Beijing100089 China

ISBN: (纸本)9781510681613

A large number of space debris with rotational motion occupy scarce orbital resources, thus, a de-tumbling phase may be necessary prior to the capturing phase to reduce the risk of collision. A new contactless AC current de-tumbling method based on the principle of electromagnetic eddy current is proposed in this paper. Firstly, an analysis is conducted on external disturbances affecting the attitude of the debris and de-tumbling device, such as magnetic field perturbations. Compared to the electromagnetic forces acting on de-tumbling device, the influence of the geomagnetic force on detumbling device can be negligible. However, the geomagnetic torque acting on de-tumbling device cannot be ignored. Then, the advantages and disadvantages of the two AC current cases are compared and analyzed, and the method to increase the de-tumbling torque can be obtained by adjusting the frequency of the three phase AC current. Finally, the three-dimensional attitude dynamics of the uncooperative space target is established taking a spinning cylinder as the hypothetical target of de-tumbling. Simulation shows that the de-tumbling method is effective and the de-tumbling rate can be greatly improved by adjusting the frequency of the three phase AC current. © 2024 SPIE.

关键词： Space debris

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Asymptotic Approximations of a Regulator and a Convergent Iteration Process for a Singularly Perturbed Problem 16

Asymptotic Approximations of a Regulator and a Convergent It...

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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Dmitriev, Mikhail Makarov, Dmitry Moscow Institute of Physics and Technology Federal Research Center 'Computer Science and Control' of Ras Moscow Russia

ISBN: (纸本)9798350337907

The paper considers the construction of asymptotic expansions in a singularly perturbed weakly nonlinear control problem to design an approximate controller. The asymptotic expansions are used to construct interpolation and extrapolation procedures and are obtained by applying the SDRE technique and analyzing a convergent iterative process. The experiments performed showed the efficiency of the proposed approach. © 2023 IEEE.

关键词： controllers

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Scalable and Low-Cost Remote Lab Platforms: Teaching Industrial Robotics Using Open-Source Tools and Understanding Its Social Implications 16th

Scalable and Low-Cost Remote Lab Platforms: Teaching Indust...

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16th International Conference on Social Robotics, ICSR + AI 2024

作者： Kumar, Amit Jose, Jaison Jain, Archit Kulkarni, Siddharth Arya, Kavi Centre for Systems and Control Indian Institute of Technology Bombay Mumbai India Embedded Real-Time Systems / e-Yantra Lab Indian Institute of Technology Bombay Mumbai India Computer Science and Engineering Department Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9789819635214

With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal Robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Costs

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On convergence of covariance matrix of empirical Bayes hyper-parameter estimator

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control Theory and technology 2024年第2期22卷 149-162页

作者： Yue Ju Biqiang Mu Tianshi Chen School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong KongShenzhenShenzhen518172GuangdongChina Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology10044StockholmSweden Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of SciencesBeijing100190China

Regularized system identification has become the research frontier of system identification in the past *** related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to *** this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been ***,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is *** general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance ***,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter *** this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting ***,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.

关键词： Regularized system identification Hyper-parameter estimator Empirical Bayes Convergence of covariance matrix

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