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arXiv 2024年

作者： Kratochvila, Lukas de Jong, Gijs Arkesteijn, Monique Bilík, Šimon Zemčík, Tomáš Horak, Karel Rellermeyer, Jan S. Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science TU Delft Delft Netherlands Department of Management in the Built Environment Faculty of Architecture and the Built Environment TU Delft Delft Netherlands Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland Dependable and Scalable Software Systems Institute of Systems Engineering Faculty of Electrical Engineering and Computer Science Leibniz University Hannover Hannover Germany

Digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orientation in exceptional situations, and faster rescue intervention. Nevertheless, creating the twins still remains a largely manual effort, due to a lack of 3D-representations, which are available only in limited amounts for some new buildings. Thus, in this paper we aim to synthesize 3D information from commonly available 2D architectural floor plans. We propose two novel pixel-wise segmentation methods based on the MDA-Unet and MACU-Net architectures with improved skip connections, an attention mechanism, and a training objective together with a reconstruction part of the pipeline, which vectorizes the segmented plans to create a 3D model. The proposed methods are compared with two other state-of-the-art techniques and several benchmark datasets. On the commonly used CubiCasa benchmark dataset, our methods have achieved the mean F1 score of 0.86 over five examined classes, outperforming the other pixel-wise approaches tested. We have also made our code publicly available to support research in the field. © 2024, CC BY.

关键词： Semantic Segmentation

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Fault diagnosis for PV arrays considering dust impact based on transformed graphical feature of characteristic curves and convolutional neural network with CBAM modules

arXiv

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arXiv 2023年

作者： Qu, Jiaqi Wei, Lu Sun, Qiang Zareipour, Hamidreza Qian, Zheng School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China School of Electronics and Information Engineering Beihang University Beijing China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China The Department of Electrical and Computer Engineering University of Calgary Calgary Canada

Various faults can occur during the operation of PV arrays, and both the dust-affected operating conditions and various diode configurations make the faults more complicated. However, current methods for fault diagnosis based on I-V characteristic curves only utilize partial feature information and often rely on calibrating the field characteristic curves to standard test conditions (STC). It is difficult to apply it in practice and to accurately identify multiple complex faults with similarities in different blocking diodes configurations of PV arrays under the influence of dust. Therefore, a novel fault diagnosis method for PV arrays considering dust impact is proposed. In the preprocessing stage, the Isc-Voc normalized Gramian angular difference field (GADF) method is presented, which normalizes and transforms the resampled PV array characteristic curves from the field including I-V and P-V to obtain the transformed graphical feature matrices. Then, in the fault diagnosis stage, the model of convolutional neural network (CNN) with convolutional block attention modules (CBAM) is designed to extract fault differentiation information from the transformed graphical matrices containing full feature information and to classify faults. And different graphical feature transformation methods are compared through simulation cases, and different CNN-based classification methods are also analyzed. The results indicate that the developed method for PV arrays with different blocking diodes configurations under various operating conditions has high fault diagnosis accuracy and reliability. Copyright © 2023, The Authors. All rights reserved.

关键词： Failure analysis

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A Fast Virtual Stenting Simulation Framework for Lattice-Based Flow Diverter Stent Design Exploration and Evaluation 7

A Fast Virtual Stenting Simulation Framework for Lattice-Bas...

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7th International Conference on instrumentation, control, and Automation, ICA 2021

作者： Nainggolan, Bonfilio Putra, Narendra Kurnia Suprijanto Institut Teknologi Bandung Faculty of Industrial Technology Engineering Physics Department Bandung Indonesia Institut Teknologi Bandung Instrumentation and Control Research Group Faculty of Industrial Technology Bandung Indonesia

ISBN: (纸本)9781665432955

Stroke is one of the leading cause of death in the world. Hemorrhagic stroke is a type of stroke caused by bleeding in the brain, most likely due to the rupture of an aneurysm. An increasingly popular treatment treatment option for the prevention of aneurysm rupture is the use of flow diverter (FD) stents. As it's name suggests, this intravascular implant is inserted to a patient's blood vessels where it is then deployed in the parent vessel of a target aneurysm, thus limiting the blood flow towards the aneurysm and decreasing the risk of rupture. In order to help with the design exploration and performance evaluation of these devices, a simulation framework that allows users to easily input FD designs using a lattice-based representation which will then be deployed virtually in a blood vessel model is proposed. This virtual stenting framework is tested on three FD designs (helical, Enterprise stent-like, and hexagonal) deployed in various vessel models using a commercially available laptop. It is found that the proposed simulation framework requires only seconds of simulation run-time, where the full workflow (case setup to FD model rendering) can be done within minutes. The proposed simulation framework are based on fully open source resources and thus provide great flexibility for collaborative FD design exploration and evaluation. © 2021 IEEE.

关键词： Stents

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Nonlinear model prediction Jacobian approximation using state-independent order reduction

Nonlinear model prediction Jacobian approximation using stat...

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International Conference on Process control (PC)

作者： Pavel Skopec Tomas Vyhlidal Jan Knobloch Department of Instrumentation and Control Engineering of Faculty of Mechanical Engineering Czech Technical University in Prague Prague Czech Republic company PT SOLUTIONS WORLDWIDE spol. s r.o. Prague Czech Republic

This paper presents a method for efficiently approximating the nonlinear model prediction Jacobian matrix using state-independent model order reduction. The predictive Jacobian matrix describes how changes in the predictive inputs affect the state prediction. This method aims to reduce computation time of nonlinear model predictive control of large-scale systems, typically with spatially distributed parameters. The approach employs a unique combination of step-wise linearization, order reduction, and time discretization to calculate predictive impulse responses, followed by the reduction inverse. The reduction transformation considered is agnostic to the current state, which contributes to saving computation time. A numerical example of continuous heating is included to demonstrate the efficiency and applicability of the method.

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Wireless Communication Technologies for Indian Smart Grid: Fitness Evaluation and Optimal Decision-making 9

Wireless Communication Technologies for Indian Smart Grid: F...

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9th IEEE International Conference on Power systems, ICPS 2021

作者： Bhatt, Jignesh Jani, Omkar Harish, V.S.K.V. Dharmsinh Desai University Faculty of Technology Department of Instrumentation and Control Engineering Nadiad India Kanoda Energy Systems Pvt. Ltd. Research and Culture Department Ahmedabad India Department of Electrical Engineering Delhi110078 India

ISBN: (纸本)9781665428736

Decision for the best efficient communication technology is a major design challenge that necessitates serious attention. Considering the impact of communication technologies on the overall smart grid resilience, a meticulous methodology is essential. A methodology presented in this work attempts to optimize the selection by balancing the communication needs of smart grid applications against capabilities of wireless technology alternatives. Fitness evaluation of communication technology of a pilot of smart grid in India conducted for validation of proposed methodology and suggested better-fit alternatives. Due to its minimal computing needs, simplicity and flexibility, the presented methodology demonstrates practical viability. © 2021 IEEE.

关键词： Decision making

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On Max Pressure Urban Traffic control with Learning

On Max Pressure Urban Traffic Control with Learning

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Information Technology International Seminar (ITIS)

作者： Adiyana Putri Endra Joelianto Herman Y Sutarto Faculty of Industrial technology Institut Teknologi Bandung Doctoral Program of Engineering Physics Bandung Indonesia Faculty of Industrial Technology Institut Teknologi Bandung Instrumentation and Control Research Group Bandung Indonesia Department of Intelligent System PT. Pusat Riset Energi (PRE) Bandung Indonesia

Managing the traffic system is a multifaceted challenge, imposing various solutions to prevent congestion. Traffic management aims to create an efficient control system with numerous advantages, including reduced fuel emissions, lower stress levels, and enhanced driving discipline. Max Pressure stands as one of the techniques for traffic control, designed to adapt and enhance network throughput by considering pressure, defined as the difference between upstream and downstream queue lengths. Recent developments have yielded improved performance in Max Pressure through learning. In this adaptive control mechanism, the concept of Max Pressure is integrated as a reward function within reinforcement learning. This study introduces the “Max Pressure learning” concept, revealing its potential for creating adaptable traffic controllers. By modifying the pressure equation and transforming it into a performance metric, the original Max Pressure concept effectively responds to diverse traffic conditions. This paper showcases research findings demonstrating the surprising effectiveness of pressure as a control mechanism in the context of the learning process. Ultimately, using pressure enables controllers to efficiently alleviate gridlock situations in traffic, highlighting its promising role in optimizing traffic management and enhancing overall traffic system performance.

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Learning-Allocation Dynamics in Coalitional Games with Transferable Utility ⁎

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IFAC-PapersOnLine 2024年第30期58卷 31-36页

作者： A. Khaleghi D. Bauso T. Namerikawa Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen 9747 AG The Netherlands Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen 9747 AG The Netherlands and also Dipartimento di Ingegneria Università di Palermo Palermo 90128 Italy Department of System Design Engineering Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa 223-8522 Japan

We consider a set of players who have to make a joint decision under uncertainty and learn via gradient dynamics how to reach the maximal profit for the coalition while the game is running and the revenue gets allocated to the players. The main result is the convergence of the intertwined learning-allocation dynamics to a stable solution which yields the maximal profit for the coalition and a stable allocation in the core of the asymptotic game.

关键词： Coalitional games game theory gradient dynamics wind energy aggregation

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Optimal RTGC Non-linear control system Based on Sliding Mode controller

Optimal RTGC Non-linear Control System Based on Sliding Mode...

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SICE International Symposium on control systems (ISCS)

作者： Steven Bandong Cristian MP Napitupulu Yul Yunazwin Nazaruddin Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Engineering Physics Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Department of Engineering Physics Instrumentation and Control Research Group Institut Teknologi Bandung Bandung Indonesia National Center for Sustainable Transportation Technology Institut Teknologi Bandung Bandung Indonesia

The high traffic of containers between countries and continents demands the implementation of automation at cargo seaports. Rubber Tyred Gantry Crane (RTGC) is one of the main components for loading and unloading at container yards which needs to move the container accurately to the desired position and minimize the sway during this process. This paper attempts to examine non-linear control using the sliding mode controller (SMC) method for MIMO control problems in RTGC. The control objective is to reduce the swing angle and move the container to the desired position and height by means of the force of two motors on RTGC. The detailed derivation of the nonlinear RTGC model, the design of SMC and its sliding surface are introduced in this paper. In order to optimize the performance of the SMC control action, the Particle Swarm Optimization (PSO) and Grid search methods are employed in the investigation. The obtained results demonstrate that the SMC exhibits satisfactory control performance and effectively reduces chattering across various initial conditions and system parameters.

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Development of a Virtual Balloon Angioplasty Treatment Simulation Device Based on the Spring-Damper Method

Development of a Virtual Balloon Angioplasty Treatment Simul...

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International Conference on instrumentation control and Automation (ICA)

作者： Muhammad Ihsan Maulana Bonfilio Nainggolan Mikha Hilliard Faqihza Mukhlish Narendra Kurnia Putra Engineering Physics Department Faculty of Industrial Engineering Institut Teknologi Bandung Bandung Indonesia Department of Physics Arizona State University Tempe AZ US Engineering Physics Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Center for Instrumentation Technology and Automation (CITA) ITB Engineering Physics Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

Stroke is one of the chronic conditions that lead to an 85% of death rate from cardiovascular disease in this world. A stroke is when brain cells will not work correctly or even stop working because brain cells do not get enough oxygen from the bloodstream. Most stroke cases are caused by plaque accumulation inside the blood vessel walls. This kind of condition is commonly known as stenosis. One of the methods for treating stenosis is using balloon angioplasty (BA) to revascularize the blockage area of plaque layers inside the vessels. Most ICAS rehabilitation devices are expensive because were imported from other countries. In order to reinforce the BA fabrication locally, we develop an in silico simulation program to represent the actual phenomenon physically during the stenosis treatment using BA. Thus, the result given will be a reliable recommendation for device *** BA deployment algorithm is virtually implemented using a spring-damper model analogy with the lineal spring approach. This approach allows obtaining physical information such as pressure along the blood vessel model. Thus, it can be evaluated regarding the standard clinical reference about blood vessel conditions. The simulation results were given in the meantime for 5 - 106 seconds, depending on the several parameters used. The pressure distribution of revascularized blood vessels was also obtained, assuming a uniform modulus of elasticity.

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Application of Deep Learning Models for Vocal Cords Detection in Laryngoscopic Imagery

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Procedia Computer Science 2024年 246卷 5007-5016页

作者： Jan Vrba Jakub Steinbach Matouš Cejnek Tomáš Jirsa Zuzana Urbániová Department of mathematics informatics and cybernetics University of Chemistry and Technology in Prague Technická 5 166 28 Praha 6-Dejvice Prague Czech Republic Department of Instrumentation and Control Engineering Faculty of Mechanical Engineering Czech Technical University in Prague Technická 1902/4 160 00 Praha 6 Czech Republic Department of Otorhinolaryngology 3rd Faculty of Medicine and Faculty Hospital Královské Vinohrady Charles University Ruská 87 100 00 Praha 10 Prague Czech Republic

The accurate location of vocal cords is crucial in medical imaging applications for diagnostic and therapeutic purposes. In this study, we evaluated the performance of state-of-the-art object detection models, including the YOLO, EfficientDet D1, Faster R-CNN and Single Shot Detector architectures, for the task of vocal cord detection. Using a data set of annotated medical images, we conducted comprehensive experiments to compare the models in terms of mean average precision (mAP) and inference time. Our results indicate that YOLOv8m achieved the highest performance, with a mAP@[0.5:0.95] of 0.778 and an inference time of 4.7 milliseconds. EfficientDet D1, Faster R-CNNs, and Single Shot Detectors trailed behind with slightly lower mAP scores. These findings highlight the efficacy of YOLOv8m for vocal cord localization on the utilized dataset. In addition, our study provides valuable information for the selection of suitable object detection models in medical imaging applications, facilitating better diagnosis and treatment planning in laryngology and otolaryngology.

关键词： Voice pathology detection object detection YOLO deep learning machine learning vocal folds vocal cords laryngoscopic imaging ORL otorhinolaryngology

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