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2024 International Conference on Optical Communication and Optoelectronic Technology, OCOT 2024

作者： Ma, Wendi Wen, Hong Hou, Wenjing Yao, Ruixiang Zhu, Yanxu Yan, Dibao Zhao, Ziang School of Aeronautics and Astronautics University of Elec. Science and Tech. of China Chengdu611731 China Aircrat Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781510683266

The injection of false data attack (FDIA) poses a serious threat to smart grids, and accurate detection of FDIAs is crucial for the secure and stable operation of the grid. A promising approach for FDIA detection based on edge computing is to adopt a scheme that involves prediction before classification, taking into account the temporal correlations of measurement data. This paper proposes a FDIA detection model based on temporal convolutional network (TCN). The model effectively captures long-term dependencies in sequential data, thereby enhancing data prediction performance. Simulation results demonstrate that TCN exhibits superior detection performance under common neural network architectures, compared to typical recurrent neural network (RNN) models. This improvement facilitates highlighting the differences between injected false data and genuine data during the subsequent classification stage, making anomaly detection algorithms more capable of identifying abnormal situations and thereby enhancing the accuracy of FDIA detection. © 2024 SPIE.

关键词： Spatio-temporal data

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Integrated Airborne Radar-Communication Waveform Design Based on the Complementary P4-OFDM Signal

Integrated Airborne Radar-Communication Waveform Design Base...

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2024 International Conference on Optical Communication and Optoelectronic Technology, OCOT 2024

作者： Zhao, Ziang Wen, Hong Song, Huanhuan Wang, Yongfeng Yao, Ruixiang Ma, Wendi Pang, Yv School of Aeronautics and Astronautics University of Elec. Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781510683266

To meet the specific demands of airborne radar and communication systems, this study introduces an integrated radar-communication waveform design based on selecting the optimal dual sequence of complementary P4-OFDM signals. This waveform leverages the cyclic shift counts of complementary P4 codes to carry communication information, achieving dual functionality in target detection and data transmission. To enhance the data transmission rate, the study innovatively developed a dual cyclic shift signal, which expands the number of states represented by P4 codes using a pair of primary and secondary original sequences. This signal offers exceptionally high speed and distance resolution for radar detection and maintains a low bit error rate in communications, making it particularly suitable for airborne environments where the priority is on communication reliability over efficiency. © 2024 SPIE.

关键词： Bit error rate

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A Study of Two Types of Introductory Exercise Problems for Network Programming Learning with Python 23

A Study of Two Types of Introductory Exercise Problems for N...

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11th International Conference on Computer and Communications Management, ICCCM 2023

作者： Lu, Xiqin Funabiki, Nobuo Ueda, Kiyoshi Kao, Wen-Chung Department of Information and Communication Systems Distributed System Design Lab. Okayama University Okayama Japan Department of Computer Science Control Software Lab. Nihon University Koriyama Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

ISBN: (纸本)9798400707735

Network programming is the act of writing computer codes for communications between programs or processes in different computers across networks. It is crucial for applications and services using networks, including e-commerce, gaming, and social media. However, university courses of educating it are very limited. As a result, it has become important to develop and offer IT tools to support self-studies of network programming by novices. In this paper, we present a study of two types of introductory exercise problems, namely, Grammar-concept Understanding Problem (GUP) and Comment Insertion Problem (CIP), for self-studies of five basic network protocols of TCP/IP, ARP, SMTP, POP3, and SSH with Python. A GUP instance requests to answer the keyword such as a library function in the given source code that corresponds to the grammar concept described in the question. A CIP instance requests to insert the comment at each blank of the code. String matching is adopted to mark any answer at the browser-based answer interface. Through solving them, it is expected to understand the meaning of important words and the code structure for network programming. As preliminary evaluations, we generated six GUP and CIP instances respectively, and assigned them to 10 students in Okayama University, Japan. The results confirmed that the proposal is proper for novices to learn network programming with Python. © 2023 ACM.

关键词： Python

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Parameter Estimation and Tracking control of MIMO Linear systems Without Prior Knowledge of control Signs and Parameter Bounds

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IEEE Transactions on Automatic control 2024年第6期70卷 3695-3710页

作者： Xu, Yuchun Zhang, Yanjun Zhang, Ji-Feng Chinese Academy of Sciences Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Beijing100190 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology State Key Lab of Automation Intelligent Unmanned Systems Beijing100081 China University of Chinese Academy of Sciences School of Mathematics Sciences Beijing100149 China Zhongyuan University of Technology School of Automation and Electrical Engineering Zhengzhou450007 China Chinese Academy of Sciences Academy of Mathematics and Systems Science Beijing100190 China

Dealing with the uncertain high-frequency gain matrix, denoted as Kp, is a fundamental problem in multivariable adaptive control systems. In this paper, we propose a new solution for parameter estimation and adaptive control for a general class of multi-input multi-output discrete-time linear time-invariant systems. The proposed scheme does not require any prior knowledge of the sign or bound information of Kp, and thus, significantly relaxes the design conditions in traditional multivariable adaptive control systems. Compared with the commonly used Nussbaum gain or multi-model techniques for addressing the unknown signs of Kp, the proposed scheme does not rely on any additional design conditions or any switching mechanism, while still ensuring closed-loop stability and asymptotic output tracking. Specifically, an output feedback adaptive control law is developed based on a matrix decomposition technique, which leads to derivation of a modified estimation error model. Subsequently, a gradient-based parameter update law is formulated only relying on the non-zero condition of the leading principle minors of Kp. Through designing gain functions and stable filters, the controller is always non-singular and does not involve any causal contradiction problem. Simulation study showcases the design process and demonstrates the effectiveness of the proposed scheme. © 1963-2012 IEEE.

关键词： MIMO systems

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Color liquid crystal grating based color holographic 3D display system with large viewing angle

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Light(Science & Applications) 2024年第1期13卷 103-112页

作者： Di Wang Yi-Long Li Fan Chu Nan-Nan Li Zhao-Song Li Sin-Doo Lee Zhong-Quan Nie Chao Liu Qiong-Hua Wang School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing 100191China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Display Technology Research Center Seoul National UniversityGwanak-ro 1Gwanak-guSeoul 08826Republic of Korea Key Lab of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China

Holographic 3D display is highly desirable for numerous applications ranging from medical treatments to military ***,it is challenging to simultaneously achieve large viewing angle and high-fidelity color reconstruction due to the intractable constraints of existing ***,we conceptually propose and experimentally demonstrate a simple and feasible pathway of using a well-designed color liquid crystal grating to overcome the inevitable chromatic aberration and enlarge the holographic viewing angle,thus enabling large-viewing-angle and color holographic 3D *** use of color liquid crystal grating allows performing secondary diffraction modulation on red,green and blue reproduced images simultaneously and extending the viewing angle in the holographic 3D display *** principle,a chromatic aberration-free hologram generation mechanism in combination with the color liquid crystal grating is proposed to pave the way for on such a superior holographic 3D *** proposed system shows a color viewing angle of~50.12°,which is about 7 times that of the traditional system with a single spatial light *** work presents a paradigm for achieving desirable holographic 3D display,and is expected to provide a new way for the wide application of holographic display.

关键词： holographic angle crystal

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Improving Motor Imagery Classification in BCI systems Using EMD and Multi-Layer CNNs 14

Improving Motor Imagery Classification in BCI Systems Using ...

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14th International Conference on Computer and Knowledge engineering, ICCKE 2024

作者： Arghand, Reza Chaibakhsh, Ali Radman, Moein University of Guilan Intelligent Systems and Advanced Control Lab Faculty of Mechanical Engineering Rasht Guilan41996-13776 Iran University of Essex Brain-Computer Interfacing and Neural Engineering Laboratory School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom

ISBN: (纸本)9798331511272

Brain-Computer Interface (BCI) systems are relatively new technologies that could play a significant role in aiding the recovery of impaired activities resulting from neuromuscular disabilities in affected individuals. Accurate recognition and classification of motor imagery in BCI systems present a challenge, leading to extensive research in recent years aimed at improving the accuracy of these systems. In this study, a combination of the Empirical Mode Decomposition (EMD) method and a multi-layer Convolutional Neural Network (CNN) is employed. Initially, the signal is decomposed into Intrinsic Mode Functions (IMFs) using EMD, and all IMFs across all trials are analyzed to select the best ones, which are then fed into the CNN as inputs. Additionally, the study incorporates the fusion of three CNN networks, each corresponding to a different IMF. The features extracted from these networks are combined and used to train an SVM classifier. The proposed method achieved an accuracy of 86.1% on the BCI-2a 2008 dataset, outperforming other state-of-the-art approaches. ©2024 IEEE.

关键词： Brain computer interface

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Discussion on application of FLIC-Fluent coupled simulation technology on medium-scale and large-scale municipal solid waste incinerators 6

Discussion on application of FLIC-Fluent coupled simulation ...

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6th International Conference on intelligent Computing, Communication, and Devices, ICCD 2023

作者： Zhang, Hongze Guangxi Key Laboratory of Machine Vision and Intelligent Control Guangxi Wuzhou China Guangxi Colleges and Universities Key Lab. of Image Processing and Intelligent Information System Guangxi Wuzhou China School of Electronics and Information Engineering Wuzhou University Guangxi Wuzhou China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

Today, the world economy is in the stage of rapid development, followed by the rising quantity, the decreasing moisture content, and the increasing heat value of Municipal Solid Waste (MSW). Since waste incineration has the advantages of excellent volume reduction effect, high resource utilization efficiency, and less secondary pollution to the environment, waste incineration disposal technology has received extensive attention worldwide. With the continuous increase of the urban population, the amount of sewage sludge is growing year by year. The process of the sludge incineration system is highly complicated, and the cost of construction and operation is high. The waste incinerator can process not only MSW but also sewage sludge. Therefore, the co-incineration of sewage sludge with MSW in the existing waste incinerator is a safe and effective way to dispose of sewage sludge. In this paper, the simulation results of Computational Fluid Dynamics (CFD) are analyzed for medium-scale and large-scale waste incinerators, characterized by high moisture content, high ash content, low heat value of sewage sludge, and incomplete combustion and high pollutant emissions in waste incinerators. With FLIC-Fluent coupled simulation method, the critical information such as temperature field, velocity field, concentration field of principal components, and the pollutant emissions can be predicted. Based on the CFD simulation results, the performance and structure of waste incinerators can be optimized, and the new products can be designed and developed. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Waste incineration

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Research on Lightweight Small Object Detection Method with Fusion Attention Mechanism

Research on Lightweight Small Object Detection Method with F...

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2023 China Automation Congress, CAC 2023

作者： Dai, Haowen Liu, Bingyou Wan, Guoyang Qi, Jingjing Wan, Luanfei School of Electrical Engineering Anhui Polytechnic University Wuhu China Anhui Polytechnic University The Key Lab. of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Wuhu China Anhui Dar Intelligent Control System Co. Ltd. Wuhu China Wuhu Institute of Technology Wuhu China

ISBN: (纸本)9798350303759

In the task of small object detection, due to the relatively small size of the objects, complex situations such as occlusion and overlap may arise in high-density scenes. These factors can significantly increase the issues of missed detections and false detections in object detection tasks. To address the aforementioned issues, this paper proposes a lightweight small object detection model, YOLOv5s-MGC. Firstly, we introduce an improved Mobilenetv3 network to replace the backbone network of YOLOv5s, aiming to improve the network's capability for effective feature extraction. Secondly, we incorporate the GSConv module into the feature fusion network to reduce model parameters and strengthen the network's ability in fusing feature information. Finally, we have integrated Convolutional Block Attention Module (CBAM) at the forefront of the detection heads, achieving the fusion of fine-grained features. We assessed our approach on the openly accessible dataset 'SHWD' and contrasted the results with the baseline YOLOv5s and various SOTA object detection models. Precisely, our method attains an accuracy of 91.1%, exceeding the baseline module by 1.6%. Furthermore, the module size is reduced to 1.97MB and it achieves a 52.4 FPS. In comparison to other prevailing algorithms, YOLOv5s-MGC enables efficient and accurate small object detection. © 2023 IEEE.

关键词： Object detection

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State Estimation for Discrete-Time Semi-Markovian Jump Piecewise-Affine systems with Complex Semi-Markovian Kernel 63

State Estimation for Discrete-Time Semi-Markovian Jump Piece...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Tang, Qi Liu, Tao Sun, Xi-Ming University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Shenzhen Institute of Research and Innovation The University of Hong Kong Hong Kong Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China

ISBN: (纸本)9798350316339

This paper addresses state estimation for discretetime semi-Markovian jump piecewise-affine (PWA) systems. To handle uncertainties caused by unknown disturbances, we propose an analysis method that considers all transfer paths between different regions within the same mode. We then examine the mean-square exponential stability and L∞ performance of the error dynamic system by constructing Lyapunov functions that depend on mode, region, and sojourn time. The related criteria are derived using ellipsoidal outer approximation. Based on these criteria, we design L∞ observers. Finally, we demonstrate the applicability of our method through a numerical example. © 2024 IEEE.

关键词： Lyapunov functions

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Improved Hybrid Attention Learning System for Remaining Useful Life Prediction 42

Improved Hybrid Attention Learning System for Remaining Usef...

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42nd Chinese control Conference, CCC 2023

作者： Li, Zhi Sun, Tao Ma, Song Yang, Bin Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tsinghua University Department of Automation Beijing100084 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789887581543

Remaining useful life (RUL) prediction can improve the availab.lity and efficiency of equipment or system by providing timely maintenance suggestions. In this paper, an improved hybrid attention learning system for RUL prediction is developed. By introducing adaptive weighting, a hybrid attention mechanism with self attention and external attention is designed. The mechanism enhances the attention to samples with similar performance degradation patterns, and improves the feature extraction ability of the learning system for sensor data with strong temporal correlation. Finally, we conducted a series of simulation experiments on the commercial modular aviation propulsion system simulation (C-MAPSS) dataset to verify the effectiveness and superiority of the proposed method in RUL prediction. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Learning systems

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