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24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Busygina, Anna V. Kim, Alexandra Yu. Gazizov, Talgat R. Tomsk State University of Control Systems and Radioelectronics Department of Television and Control Tomsk Russia Tomsk State University of Control Systems and Radioelectronics Department of Telecommunications and Fundamentals of Radio Engineering Tomsk Russia

ISBN: (纸本)9798350336870

The paper discusses the existing approaches to considering individual educational trajectories and ways of their practical implementation in the activities of educational organizations. To develop a graduate's competence model, we present a method that is based on an analysis of industry requirements and professional standards. The proposed method was used to develop an up-to-date list of professional competencies of a radio engineer (master's degree). Moreover, a model of an educational program was developed that supports individual educational trajectories for an enlarged group of training areas and specialties 11.04.00 'Electronics, Radio engineering, and Communication systems'. This model describes the volume of the main structural elements, the content of blocks and modules of the educational program, and tools for building an individual educational trajectory, taking into account the current legislation. The proposed approach to building an individual educational trajectory is employed from the moment a student enters the educational process until the moment he enters the state final attestation. © 2023 IEEE.

关键词： Trajectories

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CPL-SLAM: Centralized Collaborative Multirobot Visual-Inertial SLAM Using Point-and-Line Features

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IEEE Internet of Things Journal 2025年第12期12卷 21866-21875页

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment Key Laboratory of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Laboratory of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Carleton University School of Information Technology Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

Traditional visual-inertial Simultaneous Localization and Mapping (SLAM) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues, such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intrarobot and interrobot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

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Graph-guided masked autoencoder for process anomaly detection

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Process Safety and Environmental Protection 2024年 186卷 1345-1357页

作者： Jia, Mingwei Xu, Danya Yang, Tao Yao, Yuan Liu, Yi Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Chemical Engineering National Tsing Hua University Hsinchu300044 Taiwan

Developing an accurate and reliable anomaly detection model is of great significance for safe operation in the process industry. To minimize false positives, it is crucial to accurately model the intricate topological and nonlinear connections among variables. In this study, a process anomaly detection method based on graph-guided masked autoencoder (GGMAE) is proposed by introducing the concept of the graph to the process industry. GGMAE first constructs a topology graph according to the process flowchart. Then, the patch and mask mechanism forces GGMAE to learn the process intrinsic information to reconstruct the input according to the variable topological relationship and temporal characteristics. Additionally, Kullback-Leibler divergence is used as the loss to ensure that the distribution of input and output is consistent. Experiments on two publicly available anomaly detection benchmarks demonstrate the superiority of GGMAE over existing methods. Visualization of the results demonstrates the physically compliant reconstruction logic. © 2024 The Institution of chemical Engineers

关键词： Anomaly detection

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On moment relaxations for linear state feedback controller synthesis with non-convex quadratic costs and constraints 63

On moment relaxations for linear state feedback controller s...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Gramlich, Dennis Gao, Sheng Zhang, Hao Scherer, Carsten W. Ebenbauer, Christian Rwth Aachen University Chair of Intelligent Control Systems Aachen52074 Germany Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai200092 China University of Stuttgart Chair of Mathematical Systems Theory Stuttgart70569 Germany

ISBN: (纸本)9798350316339

We present a simple and effective way to account for non-convex costs and constraints in state feedback synthesis, and an interpretation for the variables in which state feedback synthesis is typically convex. We achieve this by deriving the controller design using moment matrices of state and input. It turns out that this approach allows the consideration of non-convex constraints by relaxing them as constraints on the expected value of quadratic functions, and that the variables in which state feedback synthesis is typically convexified can be identified with blocks of these moment matrices. The employed relaxation can lead to constraint violation along sample paths. © 2024 IEEE.

关键词： State feedback

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Deep convolutional autoencoder thermography for artwork defect detection

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Quantitative InfraRed Thermography Journal 2024年第6期21卷 367-383页

作者： Liu, Yi Wang, Fumin Liu, Kaixin Mostacci, Miranda Yao, Yuan Sfarra, Stefano Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou China Shanxi Key Laboratory of Signal Capturing & Processing North University of China Taiyuan China Professional Restorer Celano Italy Department of Chemical Engineering National Tsing Hua University Hsinchu Taiwan Department of Industrial and Information Engineering and Economics University of L’Aquila L’Aquila Italy

Infrared thermography is a cost-effective non-destructive evaluation technique that plays a critical role in extracting information about defects in cultural heritage such as works of art. However, in-depth studies on the internal structure of contemporary artworks using infrared thermography remain lacking, and therefore, a deep convolutional autoencoder thermography (DCAT) data analysis method is proposed for defect detection of contemporary artworks. In the proposed method, original data are enhanced by convolution to reduce the noise and inhomogeneous background in the original thermal images;subsequently, a deep autoencoder is used to extract nonlinear features from the enhanced thermographic data, and the results of the hidden layer are visualised. These visualised images highlight information regarding the internal structure and defects of the artwork. The case study on a handmade replica of Picasso’s ‘La Bouteille de Suze’, reproduced exactly as the original, has shown that DCAT significantly improved the accuracy of defect detection when compared with that of commonly used methods. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Nondestructive examination

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Stochastic Unit Commitment: Model Reduction via Learning

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Current Sustainable/Renewable Energy Reports 2023年第2期10卷 36-44页

作者： Liu, Xuan Conejo, Antonio J. Constante Flores, Gonzalo E. Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States Department of Integrated Systems Engineering The Ohio State University ColumbusOH43210 United States Davidson School of Chemical Engineering Purdue University West LafayetteIN47907 United States

Purpose of Review: As weather-dependent renewable generation increases its share in the generation mix of most electric energy systems, a stochastic unit commitment becomes the natural day-ahead scheduling tool. However, such a tool is generally computationally intractable if a detailed uncertainty description is considered. Taking this into account, we proposed a learning method to make the stochastic unit commitment problem tractable. Recent Findings: Recent advances in statistical learning and machine learning to address optimization problems can be advantageously applied to the rather intractable stochastic unit commitment problem. Considering these advances, we explore simple learning techniques to drastically reduce the size of a stochastic unit commitment problem without significantly altering its optimal solution. Summary: The considered stochastic unit commitment problem is formulated as a two-stage stochastic programming problem. The first stage represents commitment decisions, while the second one represents the operation conditions under different scenarios. Taking into account historical solved instances (or proxies for them), we reduce the size (measured by numbers of constraints and variables) of the stochastic unit commitment problem by (i) fixing unchanged binary variables and by (ii) eliminating inactive inequality constraints. Our numerical results show that the reduced problem generally requires significantly less time to solve while obtaining high-quality solutions, which are very close to or indistinguishable from the one obtained by solving the original problem. We use an Illinois 200-bus system to illustrate and characterize the performance of the proposed problem-reduction method. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Stochastic programming

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Carbon Capture and Utilization Technology to Upgrading Biogas Using Bubble Column Reactor: Effect of Concentration of Ca(OH)₂ Solution on CO₂ Removal 6th

Carbon Capture and Utilization Technology to Upgrading Bioga...

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6th International Conference on Mechanical engineering, ICOME 2023

作者： Febrada, Mayongga Heriz Maharani, Wanda Oktavia Kusdianto Mahdania, Suci Machmudah, Siti Rozy, Mohammad Irwan Fatkhur Winardi, Sugeng Chemical Engineering Department Faculty of Industrial Technology and Systems Engineering Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia

The CO2 content in biogas has several effects that need to be considered, such as affecting its calorific value or energy value. The higher the CO2 content, the lower the heating value of the biogas. One way to absorb... 详细信息

ISBN: (纸本)9789819781966

The CO₂ content in biogas has several effects that need to be considered, such as affecting its calorific value or energy value. The higher the CO₂ content, the lower the heating value of the biogas. One way to absorb CO₂ is by carbonation using a solution of Ca(OH)₂ to become CaCO₃. Synthesis of CaCO₃ by carbonation to obtain high quality products is still being carried out in terms of phase, morphology, and particle size. Ca(OH)₂ slurry was prepared with various concentrations, namely 0.05 M, 0.07 M, and 0.1 M. Scanning Electron Microscopy/Energy Dispersive Spectroscopy (SEM–EDS) and X-Ray Diffraction (XRD) test carried out to analyze the properties of CaCO₃. The Precipitated Calcium Carbonate (PCC) crystalline phase at all concentrations is all calcite with scalenohedral morphology. The difference in the concentration of Ca(OH)2 has a significant effect to CO₂ absorption and the morphology of PCC. The higher the concentration of Ca(OH)₂ slurry, the higher the percentage of CO₂ absorption in biogas, but with the effect of likely forming scalenohedral morphology that are commonly used in the paper industry to enhance opacity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Absorption Bubble column Ca(OH)2 Concentration CO2 Reduction Precipitated calcium carbonate

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Verification of Railway control systems Using Model Checking and CTL, Explained Through a Case Study

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Periodica Polytechnica Transportation engineering 2024年第4期52卷 402-411页

作者： Lukács, Gábor Bartha, Tamás Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Kende street 13-17. BudapestH-1111 Hungary

Systematic faults can often occur during the development of a system. The later such faults are discovered, the more expensive it can be to correct them. In systems engineering practice, there are many methods and tools to reduce the likelihood of systematic faults. In this paper, we present the application of a formal model–based verification technique – called model checking – to assist railway engineers in designing and verifying the safety-related functionality of railway control systems. The proposed process is part of a specification-verification environment that facilitates the construction of correct, complete, consistent, and verifiable functional specifications during development. The results and experience in model checking are illustrated by a case study of a vehicle detection point, a common component in this domain. The model checking of the case study has been performed in the widely used UPPAAL modeling and simulation framework, which can also verify formal properties and generate a counterexample in case of a property violation. By analyzing the counterexample, the designer can gain insights into the system's behavior and identify potential design flaws or failures. Model checking can be used to achieve a higher quality functional specification that is typically more complete and/ or contains fewer faults compared to the traditional development approach. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Railroads

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AggFollower: Aggressiveness Informed Car-Following Modeling

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Chen, Xianda Yuan, Xinyi Zhu, Meixin Zheng, Xinhu Shen, Shaojie Wang, Xuesong Wang, Yinhai Wang, Fei-Yue Guangzhou China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong SAR China School of Transportation Engineering Tongji University Shanghai China Department of Civil and Environmental Engineering University of Washington Seattle WA USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection, acceleration pattern, and fuel consumption. However, existing car-following research used limited categories of driving style through pre-defined patterns and failed to encode driving style into data-driven car-following models. To address these limitations, we propose the Aggressiveness Informed Car-Following (AICF) modeling approach, which embeds driving style as a dynamic input feature in data-driven car-following models. In detail, We design driving aggressiveness tokens using four physical quantities (jerk, acceleration, relative speed, and relative spacing) to capture the heterogeneity of driving aggressiveness. These tokens were then embedded into a physics-informed Long Short-Term Memory (LSTM) based car-following model for trajectory prediction. To evaluate the effectiveness of our approach, we conducted extensive experiments based on 12,540 car-following events extracted from the HighD dataset and 24,093 events from the Lyft dataset. Compared to models devoid of considerations for driving aggressiveness levels, AICF exhibits superior efficacy in mitigating the Mean Square Error (MSE) of spacing and collision rate. To the best of our knowledge, this is the first work to directly incorporate real-time driving aggressiveness tokens as input features into data-driven car-following models, enabling a more comprehensive understanding of aggressiveness in car-following behavior. IEEE

关键词： Long short-term memory

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Adapting RL control Policies to Changing Dynamics for Improved Robustness 2nd

Adapting RL Control Policies to Changing Dynamics for Impr...

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2nd International Conference on Cognitive Mobility, COGMOB 2023

作者： Szoke, Laszlo Farkas, Peter Aradi, Szilard Becsi, Tamas Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Budapest Hungary Robert Bosch Kft. Budapest Budapest Hungary

ISBN: (纸本)9783031876196

Learning to drive requires obtaining a skill that can be transferred to vehicles with different dynamics. After a short time of adaptation, humans are able to maneuver completely different vehicles. General Reinforcement Learning-based (RL) agents fell short in such scenarios since they encompass the environment dynamics in their control. If this environment changes, e.g., the expected next state differs, their performance decreases. In this work, we address this phenomenon and extend a conventional RL algorithm with modules that support adaptation to diverse environmental dynamics. We show how our method compares against baselines and what benefits it holds over them. With our results, the paper opens a line of work on making RL agents more general by preserving the behavior and decomposing it from the realizing control while keeping the method in the model-free realm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Robustness (control systems)

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