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Study of photophysical properties of Cdq2 thin film

Materials Today: Proceedings 2022年 66卷 202-204页

作者： Lougdali, M. El Kouari, Y. Anoua, R. Zazoui, M. El Oudghiri-Idrissi, I. Abboud, Y. Zawadzka, A. Sahraoui, B. Laboratory of Materials Energy and Control System Faculty of Sciences and Technology Hassan II University of Casablanca Mohammedia B.P 146 Morocco Department of Automatic and Measurement Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Torun Poland Laboratory of Engineering Sciences for Energy National School of Applied Sciences of El Jadida El Jadida BP 1166 Morocco Faculty of Sciences Ben M'sik University of Hassan II of Casablanca Casablanca Morocco Centre for Modern Interdisciplinary Technologies Nicolaus Copernicus University Wilenska 4 Torun 87-100 Poland MOLTECH-Anjou UMR 6200 CNRS UNIV Angers 2 bd Lavoisier Angers 49045 France

In this work, the morphological and optical properties of the cadmium (II) bis(8-hydroxyquinoline) (Cdq2) thin film are presented. The film was elaborated by physical deposition technique. The Atomic Force Microscopy (AFM) image shows a homogenous surface. The transmittance was measured in the range of 300–1200 nm with UV–visible spectroscopy. The emission of the film was characterized via the photoluminescence spectroscopy, a strong luminescence has been found. The measurements done at low temperatures show a decrease of the intensity of luminescence in the temperature range of 77–300 K. © 2022

关键词： Thin films

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Convolutional neural network-based fast seizure detection from video electroencephalograms

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Biomedical Signal Processing and control 2023年 80卷

作者： Chou, Chi-Hsiang Shen, Tsu-Wang Tung, Hsin Hsieh, Peiyuan F. Kuo, Chih-En Chen, Ting-Mao Yang, Chao-Wei Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan The Department of Neurological Institute Taichung Veterans General Hospital Taichung Taiwan Department of Neurology National Yang Ming Chiao Tung University School of Medicine Taipei Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Master's Program in Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Applied Mathematics National Chung Hsing University Taichung Taiwan

Objective: Ictal stage detection in electroencephalography (EEG) is important for epilepsy diagnosis. However, it's a laborious and time-consuming task for neurologists, especially with lengthy EEG recordings (such as video-EEG). Here we applied the current deep learning techniques to improve ictal stage detection efficiency. Methods: We enrolled epileptic patients at video-EEG examination beds of our neurology department between Jan 2016 and Apr 2020. Four stages of EEG (interictal, preictal, ictal and postictal) were labeled and confirmed by neurologists. Labeled EEG signals were transformed into second-order Poincaré difference plots. The whole dataset was divided into ‘Training’, ‘Validation’ and ‘Testing’ datasets with the proportions of 45%, 5% and 50% respectively. We applied 4 Convolutional Neural Networks (CNNs), namely, AlexNet, GoogLeNet, ResNet50 and DenseNet201, to learn classifying. The top three CNNs were put into an ensemble model for datasets classification. Results: 30 epileptic patients were included: Male/Female 16/14, mean age 42.8 ± 15.0 (range 22 ∼ 81) years old. Total recorded ictal duration was 47,444 s. Overall accuracies for each of the 4 CNN models (AlexNet, GoogLeNet, ResNet50 and DenseNet201) were 78.0%, 78.3%, 81.7% and 80.8%. We omitted the AlexNet, the other 3 CNNs were put into the ensemble model. The best performance was under test with 1% of the Testing dataset yielded the overall accuracies of 85.9%. The ictal stage accuracy was 97.7%. Conclusion: Our method is a promising computer-aid deep learning approach to detect seizures on video EEG. Significance: For testing phase, selected proportion of testing dataset may influence the performances of deep learning models. © 2022 The Author(s)

关键词： Electroencephalography

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Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Gri...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Junyi Zhai Xinliang Dai Yuning Jiang Ying Xue Veit Hagenmeyer Colin N. Jones Xiao-Ping Zhang College of New Energy China University of Petroleum (UPC) China Karlsruhe Institute of Technology (KIT) Institute for Automation and Applied Informatics Germany Automatic Control Laboratory École Polytechnique Fédérale de Lausanne (EPFL) Switzerland School of Electric Power Engineering South China University of Technology (SCUT) China Department of Electronic Electrical and Systems Engineering University of Birmingham (UBir) Birmingham United Kingdom

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses significant challenges in dealing with the resulting optimal power flow (OPF) problem. In this paper, a recently proposed nonconvex distributed optimization algorithm — Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN), is tailored to solve the nonconvex AC/DC OPF problem for emerging voltage source converter (VSC) based multiterminal high voltage direct current (VSC-MTDC) meshed AC/DC hybrid systems. The proposed scheme decomposes this AC/DC hybrid OPF problem and handles it in a fully distributed way. Compared to the existing state-of-art Alternating Direction Method of Multipliers (ADMM), which is in general, not applicable for nonconvex problems, ALADIN has a theoretical convergence guarantee. Applying these two approaches to VSC-MTDC coupled with an IEEE benchmark AC power system illustrates that the tailored ALADIN outperforms ADMM in convergence speed and numerical robustness.

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Semantic Segmentation of Street Scenes Using a Hybridisation between 3D Features and CNNs

Semantic Segmentation of Street Scenes Using a Hybridisation...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Lavinia Ferariu Teodor-Andrei Sauciuc Department of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Iași Romania

ISBN: (数字)9781728189567

ISBN: (纸本)9781728189574

Semantic segmentation (SS) provides pixel-wise label maps explaining the content of the images. To alleviate the accuracy of the labels, this paper proposes SS schemes based on CNNs and 3D features. Mainly, the CNNs receive multidimensional hybrid input arrays of 3D and color features, from which valuable context-aware information could be extracted. The suggested SS method accepts a single CNN working with all the features concomitantly, or an ensemble of CNNs driven by subsets of 3D features. The role of CNNs is discussed both for feature extraction and classification. Thus, the final label map is directly generated by CNNs or is produced by Random Forest (RF) using features provided by the last neural layers. The approach is exemplified for an application assisting persons with visual deficiencies. The experiments show increased performance for the CNNs processing the whole set of 3D features. Also, the CNNs driven by 3D features (in block or subsets) offer refined context-aware features for RF.

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Bio-inspired Coordination and control of Autonomous Vehicles in Future Manufacturing and Goods Transportation

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IFAC-PapersOnLine 2020年第2期53卷 10861-10866页

作者： Constantin F. Caruntu Carlos M. Pascal Anca Maxim Ovidiu Pauca Department of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Iasi Romania t) Continental Automotive Romania Iasi Romania

The will to apply bio-inspired techniques to coordinate and control autonomous X vehicles (AXVs) has increased tremendously during the last decade due to their advantages in the face of complexity in today’s demanding applications. Thus, several bio-inspired approaches for multiple-entities optimization have been proposed in the literature for various limited applications, e.g., drone coordination, mobile robot formation maintenance. In all these strategies, the entities must plan their path and control their movements while coordinating their behavior w.r.t. the other members, and they must avoid collisions, so the task could be very difficult in the unstructured environments present in future manufacturing plants and goods transportation. Future applications of these bio-inspired techniques for coordination and control of AXVs include large warehouses, manufacturing, logistics, last-mile delivery, etc. The AXVs could be grouped to carry larger goods or they can act as swarm members when they do not have a common goal, but they must interact while they move to complete the allocated tasks and intersect their paths with the paths of other entities. As such, this paper illustrates the concept of applying such bio-inspired coordination and control techniques for the development of future manufacturing and goods transportation, a discussion being carried out regarding the advantages and disadvantages of several techniques for their use in specific applications.

关键词： Bio-inspired coordination Bio-inspired control Autonomous vehicles Intelligent manufacturing systems Goods transportation Last-mile logistics Formation maintenance

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Design and Implementation of Adaptive NMPC in industrial applications: case study

Design and Implementation of Adaptive NMPC in industrial app...

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International Carpathian control Conference (ICCC)

作者： Stepan Ozana Filip Krupa Jakub Nemcik Gergely Takacs Jakub Mozaryn Petr Beremlijski Abhaya Singh Aleksandra Kawala-Sterniuk Department of Cybernetics and Biomedical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic Institute of Automation Measurement and Applied Informatics Slovak University of Technology in Bratislava Bratislava Slovak Republic Institute of Automatic Control and Robotics Warsaw University of Technology Warsaw Poland Department of Applied Mathematics VSB-Technical University of Ostrava Ostrava Czech Republic Department of engineering University of Sannio Sannio Italy Department of Electrical Power and Renewable Energy Opole University of Technology Opole Poland

This paper deals with the design and implementation of adaptive nonlinear predictive control (NMPC). The resulting control system is deployed on a softPLC embedded target in real-time via the REXYGEN control system. The paper describes functional prototype using softPLC hosting the NMPC algorithm applied for a nonlinear system consisting of three coupled tanks. The NMPC algorithm is solved via the receding horizon control method (RHC), formulated as a nonlinear programming problem (NLP) and numerically computed using the SOLNP solver. The adaptivity is provided by online identification via moving horizon estimation (MHE), keeping the model updated to avoid a model-plant mismatch. The methodology described in this paper can be easily transferred to a wider group of industrial nonlinear processes. Such created control unit can run in a standalone mode or can be connected to some exiting control system providing a necessary computational power and thus upgrading the quality of control significantly.

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Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

arXiv

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arXiv 2022年

作者： Zhai, Junyi Dai, Xinliang Jiang, Yuning Xue, Ying Hagenmeyer, Veit Jones, Colin N. Zhang, Xiao-Ping Qingdao China City & Energy Research Institute Suzhou China Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Automatic Control Laboratory EPFL Switzerland School of Electric Power Engineering South China University of Technology Guangzhou China Department of Electronic Electrical and Systems Engineering University of Birmingham Birmingham United Kingdom

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses significant challenges in dealing with the resulting optimal power flow (OPF) problem. In this paper, a recently proposed nonconvex distributed optimization algorithm—Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN), is tailored to solve the nonconvex AC/DC OPF problem for emerging voltage source converter (VSC) based multiterminal high voltage direct current (VSC-MTDC) meshed AC/DC hybrid systems. The proposed scheme decomposes this AC/DC hybrid OPF problem and handles it in a fully distributed way. Compared to the existing state-of-art Alternating Direction Method of Multipliers (ADMM), which is in general, not applicable for nonconvex problems, ALADIN has a theoretical convergence guarantee. Applying these two approaches to VSC-MTDC coupled with an IEEE benchmark AC power system illustrates that the tailored ALADIN outperforms ADMM in convergence speed and numerical robustness. Copyright © 2022, The Authors. All rights reserved.

关键词： Constrained optimization

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Distributed AC Optimal Power Flow: A Scalable Solution for Large-Scale Problems

arXiv

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arXiv 2025年

作者： Dai, Xinliang Jiang, Yuning Guo, Yi Jones, Colin N. Diehl, Moritz Hagenmeyer, Veit Institute for Automation and Applied Informatics The Karlsruhe Institute of Technology Germany Automatic Control Laboratory EPFL Switzerland Urban Energy Systems Laboratory Swiss Federal Laboratory for Materials Science and Technology Switzerland Department of Mathematics University of Freiburg Germany

This paper introduces a novel distributed optimization framework for large-scale AC Optimal Power Flow (OPF) problems, offering both theoretical convergence guarantees and rapid convergence in practice. By integrating smoothing techniques and the Schur complement, the proposed approach addresses the scalability challenges and reduces communication overhead in distributed AC OPF. Additionally, optimal network decomposition enables efficient parallel processing under the single program multiple data (SPMD) paradigm. Extensive simulations on large-scale benchmarks across various operating scenarios indicate that the proposed framework is 2 to 5 times faster than the state-of-the-art centralized solver IPOPT on modest hardware. This paves the way for more scalable and efficient distributed optimization in future power system applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Parallel processing systems

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Closed-loop control of anesthesia and hemodynamic system: a Model Predictive control approach

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IFAC-PapersOnLine 2021年第15期54卷 37-42页

作者： Anca Maxim Dana Copot “Gheorghe Asachi” Technical University of Iasi Department of Automatic Control and Applied Informatics Blvd. D. Mangeron 27 700050 Iasi Romania Research group of Dynamical Systems and Control Ghent University Tech Lane Science Park 125 9052 Ghent Belgium EEDT—Core Lab on Decision and Control Flanders Make Consortium Tech Lane Science Park 131 9052 Ghent Belgium

This paper proposes a Model Predictive control (MPC) approach of both anesthesia and hemodynamic systems. The designed control strategy has been validated on a novel and unique patient simulator. The aim of this paper is to evaluate the feasibility MIMO closed-loop control of anesthesia and hemodynamic variables taking into account the interaction (synergic and antagonistic) between subsystems. The proposed methodology takes into account patient variability, is robust to subsystems interaction and meets the clinical objectives. The algorithm is tested in simulation on a hypnosis-hemodynamic combined model for use during general anesthesia. The preliminary results are promising and show the effectiveness of the control procedure.

关键词： anesthesia hemodynamic regulation closed-loop control of anesthesia Model Predictive control optimal drug dosing

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Travel Time Minimization at Roundabouts for Connected and Automated Vehicles

Travel Time Minimization at Roundabouts for Connected and Au...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Ovidiu Pauca Constantin F. Caruntu Department of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Iasi Romania t) Continental Automotive Romania Iasi

ISBN: (数字)9781728189567

ISBN: (纸本)9781728189574

The results obtained so far from the industry and academia illustrate that fully automated vehicles are increasingly closer to be deployed in series on the roads, but they need to be connected between them and with the infrastructure for optimal performances. The roundabout type of intersection contributes to decreasing the number of accidents, but it's performance is reduced when the traffic volume increases. In this case, the intersection becomes an area of bottlenecks. To minimize the travel time of connected and automated vehicles through roundabouts by reducing the waiting time before entering it, in this paper, a centralized controller for a roundabout was proposed. It has the task of computing and sending the waiting time for the vehicles that want to travel through the intersection such that the total time to traverse it is minimized and the collisions are avoided.

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