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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Zahn, Frederik Kleinert, Tobias Hagenmeyer, Veit Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Karlsruhe Germany Rwth Aachen University Chair of Process Control Engineering Aachen Germany

ISBN: (纸本)9798350316339

Differential flatness has been defined in the literature for continuous time dynamical systems and for discrete time systems. We define flatness of automata from the perspective of behavioral systems theory, and synthesize a flatness definition for hybrid automata. These new definitions allow for feedforward trajectory generation for flat hybrid automata. Additionally, we provide necessary and sufficient conditions of hybrid automaton flatness for different types of continuous state constraints and switching conditions, and how to compute whether a hybrid automaton is flat. We illustrate feedforward trajectory generation based on our findings for a robotic manipulator example. © 2024 IEEE.

关键词： Continuous time systems

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ML-Based XPS Quantification Supported by Synthetic Dataset Generation

ML-Based XPS Quantification Supported by Synthetic Dataset G...

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作者： Orth, André Höfer, Hawo Nefedov, Alexei Jalali, Mehrdad Wöll, Christof Reischl, Markus Eggenstein-Leopoldshafen Germany Institute for Automation and Applied Informatics KIT Eggenstein-Leopoldshafen Germany Institute of Functional Interfaces KIT Eggenstein-Leopoldshafen Germany

With growing interest in laboratory automation and high-throughput systems, the amount of generated experimental data is rapidly increasing while analysis methods still require many manual work hours from experts. This is prevalent in X-ray photoelectron spectroscopy (XPS), where quantification is a complex, time-consuming, and error-prone task. We therefore propose a neural network-based workflow to make this process more approachable. As training data availability ranges from insufficient to non-existent, our workflow creates a synthetic dataset containing XPS signals and corresponding area percentages based on binding energies supplied by the user. As a result, no previous measurements are needed. After training on the synthetic data, the neural network can predict area percentages of the known binding energies with high confidence. This workflow can therefore be adapted for XPS quantification tasks to filter significant data and supervise processes. Moreover, this enables non-experts to analyze spectra and can help experts to reduce focus on important spectra. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Binding energy

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ON RESILIENCE OF FUTURE DECARBONISED ENERGY SYSTEMS IN EUROPE 8

ON RESILIENCE OF FUTURE DECARBONISED ENERGY SYSTEMS IN EUROP...

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8th International Hybrid Power Plants and Systems Workshop, HYB 2024

作者： Lotze, Jonas Moser, Massimo Hagenmeyer, Veit Department of Strategic Grid Planning TransnetBW GmbH Stuttgart Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany

ISBN: (纸本)9781837241521

The general scope the present model-based research is to analyse climate-neutral scenarios for Europe and to assess the respective resilience of the energy system. Two scenarios are therefore examined, one with an unrestricted global hydrogen market and the other with improved European energy resilience that limits pipeline imports of hydrogen from non-European countries. Key findings include increasing electrification of the heat and transport sectors, widespread use of Power-to-X appliances and, as a result, a doubling of total electricity consumption in Europe. On the power generation side, there is a need for massive expansion of renewables such as wind and photovoltaics. The analysis shows that a more resilient energy system will require additional electrolysis capacity, hydrogen storage and hydrogen grid capacity. The marginal cost of hydrogen will also increase as a result, and a higher price level will subsequently reduce the demand for hydrogen. The overall conclusion is that a transition from fossil fuels to renewables will, in any case, make the energy system much less dependent on imports and thus more resilient. © Energynautics GmbH.

关键词： Carbon capture and utilization

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From News to Summaries: Building a Hungarian Corpus for Extractive and Abstractive Summarization 30

From News to Summaries: Building a Hungarian Corpus for Extr...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Barta, Botond Lakatos, Dorina Nagy, Attila Nyist, Milán Konor Ács, Judit HUN-REN Institute for Computer Science and Control Hungary Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary

ISBN: (纸本)9782493814104

Training summarization models requires substantial amounts of training data. However for less resourceful languages like Hungarian, openly available models and datasets are notably scarce. To address this gap our paper introduces HunSum-2 an open-source Hungarian corpus suitable for training abstractive and extractive summarization models. The dataset is assembled from segments of the Common Crawl corpus undergoing thorough cleaning, preprocessing and deduplication. In addition to abstractive summarization we generate sentence-level labels for extractive summarization using sentence similarity. We train baseline models for both extractive and abstractive summarization using the collected dataset. To demonstrate the effectiveness of the trained models, we perform both quantitative and qualitative evaluation. Our dataset, models and code are publicly available, encouraging replication, further research, and real-world applications across various domains. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： abstractive summarization extractive summarization Hungarian

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Proactive Control of Production Systems Using Proposed Data Integration Strategies 7th

Proactive Control of Production Systems Using Proposed Data ...

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7th Computational Methods in Systems and Software, CoMeSySo 2023

作者： Burčiar, Fedor Kováč, Szabolcs Važan, Pavel Faculty of Materials Science and Technology in Trnava Institute of Applied Informatics Automation and Mechatronics Slovak University of Technology in Bratislava Trnava Slovakia

ISBN: (纸本)9783031548123

Developments in the production sector during recent years have led to rapid growth in usage of automated systems when it comes to communication and data exchange. Such systems help businesses with acquiring new customers, while also providing means to react to sudden changes in product demand and competition with the rest of the market. These circumstances put pressure on small to medium businesses to implement expensive systems into their production infrastructure without proper integration with the rest of the available hardware or software. Installing such systems often leads to further expenses in operator education and training. This paper touches upon the problems faced by these businesses, which if left neglected, could in certain extreme cases lead to unrecoverable financial losses. The proposed solutions help with lightening the pressure by incorporating fully automated integration strategies. Using various experiments, the applicability of these strategies has been verified using the Witness Horizon simulator which incorporates a Digital Twin of the AFB Festo production line. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Data integration

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Detection of a Quasiperiodic Phenomenon of a Binary Star System Using Convolutional Neural Network

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Intelligent automation & Soft Computing 2023年第9期37卷 2519-2535页

作者： Denis Benka Sabína Vasová Michal Kebísek Maximilián Strémy Institute of Applied Informatics Automation and MechatronicsFaculty of Materials Science and TechnologySlovak University of TechnologyTrnava91724Slovakia

Pattern recognition algorithms are commonly utilized to discover certain patterns,particularly in image-based *** study focuses on quasiperiodic oscillations(QPO)in celestial objects referred to as cataclysmic variables(CV).We are dealing with interestingly indistinct QPO signals,which we analyze using a power density spectrum(PDS).The confidence in detecting the latter using certain statistical approaches may come out with less significance than the *** work with real and simulated QPO data of a CV called MV *** primary statistical tool for determining confidence levels is sigma *** aforementioned CV has scientifically proven QPO existence,but as indicated by our analysis,the QPO ended up falling below 1-σ,and such QPOs are not noteworthy based on the former *** intend to propose and ultimately train a convolutional neural network(CNN)using two types of QPO data with varying amounts of training dataset *** aim to demonstrate the accuracy and viability of the classification using a CNN in comparison to sigma *** resulting detection rate of our algorithm is very plausible,thus proving the effectiveness of CNNs in this scientific area.

关键词： Convolutional neural network quasi-periodic oscillation cataclysmic variable simulation

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Boost short-term load forecasts with synthetic data from transferred latent space information

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Energy informatics 2022年第1期5卷 1-20页

作者： Heidrich, Benedikt Mannsperger, Lisa Turowski, Marian Phipps, Kaleb Schäfer, Benjamin Mikut, Ralf Hagenmeyer, Veit Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany

Sustainable energy systems are characterised by an increased integration of renewable energy sources, which magnifies the fluctuations in energy supply. Methods to to cope with these magnified fluctuations, such as load shifting, typically require accurate short-term load forecasts. Although numerous machine learning models have been developed to improve short-term load forecasting (STLF), these models often require large amounts of training data. Unfortunately, such data is usually not available, for example, due to new users or privacy concerns. Therefore, obtaining accurate short-term load forecasts with little data is a major challenge. The present paper thus proposes the latent space-based forecast enhancer (LSFE), a method which combines transfer learning and data augmentation to enhance STLF when training data is limited. The LSFE first trains a generative model on source data similar to the target data before using the latent space data representation of the target data to generate seed noise. Finally, we use this seed noise to generate synthetic data, which we combine with real data to enhance STLF. We evaluate the LSFE on real-world electricity data by examining the influence of its components, analysing its influence on obtained forecasts, and comparing its performance to benchmark models. We show that the Latent Space-based Forecast Enhancer is generally capable of improving the forecast accuracy and thus helps to successfully meet the challenge of limited available training data. © 2022, The Author(s).

关键词： Benchmarking

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LQR and Pole Placement Controllers with Integral Action Design Technique and Performance Analysis for Control of Temperature Field in Continuous Casting Process 24

LQR and Pole Placement Controllers with Integral Action Desi...

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24th International Carpathian Control Conference, ICCC 2023

作者： Zarghoon, Sohaibullah Belavy, Cyril Solvak University of Technology Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Bratislava Slovakia

ISBN: (纸本)9798350310221

This paper presents the design of Linear Quadratic Regulator and Pole Placement controllers with integral action using MATLAB and Simulink for controlling the temperature field in the secondary cooling zone of a continuous casting process. The secondary cooling zone in continuous casting represents a distributed parameter system. During steel production, the type of steel produced changes continuously, necessitating a control system that can respond quickly and flexibly. We compared the performance of the Linear Quadratic Regulator and Pole Placement control techniques for the temperature field in the secondary cooling zone by analyzing the system's response. The simulation results demonstrate that the Linear Quadratic Regulator technique outperforms the Pole Placement technique for the specified system. © 2023 IEEE.

关键词： Continuous casting

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Simulation and Control of a Continuously Cast Steel Billet in an Induction Furnace∗ 9

Simulation and Control of a Continuously Cast Steel Billet i...

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9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Zarghoon, Sohaibullah Bartalsky, Lukas Belavy, Cyril Institute of Automation Measurement and Applied Informatics Slovak University of Technology Faculty of Mechanical Engineering Bratislava Slovakia

ISBN: (纸本)9798350311402

This paper presents a solution to a problem that Khan Steel Company in Afghanistan encountered in their induction furnace. The motivation for deploying induction heating technology in the industry is outlined, including a description of the current situation. Basic approaches for managing this technology, critical to the industry's success, are also provided. The process of creating an induction heating model using the COMSOL Multiphysics environment is described, with emphasis placed on the importance of starting the machine and determining the system's dynamics once it is in production mode. Finally, an identification and control proposal based on the distributed parameter system is presented, followed by a demonstration of the proposed control system using simulation results. © 2023 IEEE.

关键词： Induction heating

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Dissolved ozone sensing in water and blood based on commercial screen-printed and BDD electrodes

Dissolved ozone sensing in water and blood based on commerci...

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2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Petani, Lisa Llupa, Lea Peng, Zhen Ogata, Genki Koker, Liane Gengenbach, Ulrich Einaga, Yasuaki Pylatiuk, Christian Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Karlsruhe Germany Keio University Department of Chemistry Yokohama Japan

ISBN: (纸本)9798350300260

Dissolved ozone sensing in water is crucial for a variety of applications, including water treatment, food processing, and medical therapies, as ozone is widely used as an oxidising agent in these processes. Furthermore, dissolved ozone sensing in blood is important for medical therapies. We present a novel dissolved ozone sensor for measurement in water, based on commercially available screen-printed electrodes covered with different porous membranes made of polytetrafluoroethylene (PTFE) and non porous membranes made of polydimethylsiloxane (PDMS). With PTFE, a root mean squared error (RMSE), which is the difference between the novel sensor and the reference spectrometer, of 3.62 mg l-1 can be achieved, while with PDMS a RMSE of 6.34 mg l-1 is obtained. Also, we investigated the measurement of dissolved ozone in blood with membrane-free and electrolyte-free boron-doped diamond (BDD) electrodes. The proposed dissolved ozone sensors offer a promising solution for inexpensive monitoring of dissolved ozone concentrations in water and blood with a compact design. © 2023 IEEE.

关键词： amperometry disposable electrochemistry low-cost medical applications ozone therapy sensors water treatment

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