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A comparison of clustering methods for the spatial reduction of renewable electricity optimisation models of Europe

Energy informatics 2022年第1期5卷 1-28页

作者： Frysztacki, Martha Maria Recht, Gereon Brown, Tom Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany Institute of Energy Technology Technical University of Berlin Berlin Germany

Modeling the optimal design of the future European energy system involves large data volumes and many mathematical constraints, typically resulting in a significant computational burden. As a result, modelers often apply reductions to their model that can have a significant effect on the accuracy of their results. This study investigates methods for spatially clustering electricity system models at transmission level to overcome the computational constraints. Spatial reduction has a strong effect both on flows in the electricity transmission network and on the way wind and solar generators are aggregated. Clustering methods applied in the literature are typically oriented either towards preserving network flows or towards preserving the properties of renewables, but both are important for future energy systems. In this work we adapt clustering algorithms to accurately represent both networks and renewables. To this end we focus on hierarchical clustering, since it preserves the topology of the transmission system. We test improvements to the similarity metrics used in the clustering by evaluating the resulting regions with measures on renewable feed-in and electrical distance between nodes. Then, the models are optimised under a brownfield capacity expansion for the European electricity system for varying spatial resolutions and renewable penetration. Results are compared to each other and to existing clustering approaches in the literature and evaluated on the preciseness of siting renewable capacity and the estimation of power flows. We find that any of the considered methods perform better than the commonly used approach of clustering by country boundaries and that any of the hierarchical methods yield better estimates than the established method of clustering with k-means on the coordinates of the network with respect to the studied parameters. © 2022, The Author(s).

关键词： K-means clustering

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Light-Field Camera Based Spatial Multiple Small Particle Tracking with Post-processing

Light-Field Camera Based Spatial Multiple Small Particle Tra...

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International Symposium on automation, Mechanical and Design Engineering, SAMDE 2021

作者： Zhang, Miao Matthes, Jörg Aleksandrov, Krasimir Gehrmann, Hans-Joachim Vogelbacher, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Institute for Technical Chemistry Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9783031099083

Multi-object detection and tracking is one of the most significant tasks in computer vision, which has been widely applied in various fields, such as biomedicine, automatic driving, and video surveillance. In our project, we aim to investigate the flight behavior of different small refuse-derived fuel particles (e.g., plastic, wood, paper, etc.) with sizes around 5 to 30 mm, which are blown into a combustion chamber (rotary kiln) via a lance, by detecting and tracking the particles. By utilizing a calibrated light-field camera, both 2D gray value images and 3D information, including the depth of the scene, are available for investigation. To obtain particle trajectories, accurate temporal localization of the particles is necessary. Thus, we perform an approach combining a 2D detection method and a 3D clustering method for precise detection of the particles at first. Subsequently, the temporal 2D particle localizations are associated into tracklets based on the Kalman filter state estimator and the global nearest neighbor algorithm. Owing to the wrong and incomplete tracklets caused by several inaccurate detections, we present a post-processing method to enhance the tracking performance in the paper. Finally, the optimized 2D particle trajectories are converted into 3D trajectories, and these obtained 3D particle trajectories are analyzed by a polynomial regression for further analysis of the particle flight behavior. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cameras

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Demand Response in Smart Districts: Model Predictive Control of Building Cooling

Demand Response in Smart Districts: Model Predictive Control...

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2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022

作者： Zwickel, Philipp Frahm, Moritz Galenzowski, Johannes Hafele, Karl-Heinz Maab, Heiko Waczowicz, Simon Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (数字)9781665480321

ISBN: (纸本)9781665480321

The present paper develops and compares three different Model Predictive Control (MPC) strategies for Demand Response (DR) of building cooling in a "smart district": Decentralized MPC (DeMPC), Centralized MPC (CeMPC), and scheduled Distributed MPC (DiMPC). A standard DeMPC approach leads to peaks in aggregated cooling power demand, as local controlling agents optimize each building decentrally. Because these peaks can stress the local power grid severely, we present and compare two additional MPC approaches, CeMPC and DiMPC, to enforce a constraint on the aggregated power use of the district. Our simulation results show that CeMPC and scheduled DiMPC reduce the peak load of the total cooling power in the district by 50 % while still providing DR and cooling the buildings adequately. © 2022 IEEE.

关键词： Model predictive control

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MEMS LiDAR Sensor Simulation for Autonomous Driving: A Novel Framework Using Open-source Tools 56

MEMS LiDAR Sensor Simulation for Autonomous Driving: A Novel...

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56th International Symposium on Robotics, ISR Europe 2023

作者： Berens, Felix Elser, Stefan Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe76344 Germany Institute for Artificial Intelligence Ravensburg-Weingarten University of Applied Sciences Weingarten88250 Germany

ISBN: (纸本)9783800761418

Sensor data is essential for the development of methods in autonomous driving like object detection, odometry, or SLAM. MEMS LiDAR sensors can be very valuable for autonomous vehicles because they are less prone to shock and wear compared to motorized optomechanical LiDAR sensors. Recording real-world data is complicated and expensive. An alternative is simulated data, but for MEMS LiDAR sensors there is no publicly available software to simulate this type of sensor. With this paper, we introduce a method to simulate data recorded by a MEMS LiDAR sensor like the Blickfeld Cube 1 (and other MEMS LiDAR sensors as well). For this, we use the open-source autonomous driving simulation environment CARLA. Our method can be used to generate a large amount of MEMS LiDAR data faster and cheaper than it would be possible using real-world sensors). We compare our synthetic point cloud with a real-world point cloud and evaluate the similarity. Moreover, we demonstrate the application of our method on the problem of the optimal sensor configuration. © VDE VERLAG GMBH Berlin Offenbach.

关键词： Autonomous Driving MEMS LiDAR Simulate Data

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Impact of Annotation Noise on Histopathology Nucleus Segmentation

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Current Directions in Biomedical Engineering 2022年第2期8卷 197-200页

作者： Schilling, Marcel P. Ahuja, Niket Rettenberger, Luca Scherr, Tim Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen 76344 Germany

Deep learning is often used for automated diagnosis support in biomedical image processing scenarios. Annotated datasets are essential for the supervised training of deep neural networks. The problem of consistent and noise-free annotation remains for experts such as pathologists. The variability within an annotator (intra) and the variability between annotators (inter) are current challenges. In clinical practice or biology, instance segmentation is a common task, but a comprehensive and quantitative study regarding the impact of noisy annotations lacks. In this paper, we present a concept to categorize and simulate various types of annotation noise as well as an evaluation of the impact on deep learning pipelines. Thereby, we use the multi-organ histology image dataset MoNuSeg to discuss the influence of annotator variability. We provide annotation recommendations for clinicians to achieve high-quality automated diagnostic algorithms. © 2022 The Author(s), published by De Gruyter.

关键词： Deep neural networks

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TreeSwap: Data Augmentation for Machine Translation via Dependency Subtree Swapping

TreeSwap: Data Augmentation for Machine Translation via Depe...

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2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023

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

ISBN: (纸本)9789544520922

Data augmentation methods for neural machine translation are particularly useful when limited amount of training data is available, which is often the case when dealing with low-resource languages. We introduce a novel augmentation method, which generates new sentences by swapping objects and subjects across bisentences. This is performed simultaneously based on the dependency parse trees of the source and target sentences. We name this method TreeSwap. Our results show that TreeSwap achieves consistent improvements over baseline models in 4 language pairs in both directions on resource-constrained datasets. We also explore domain-specific corpora, but find that our method does not make significant improvements on law, medical and IT data. We report the scores of similar augmentation methods and find that TreeSwap performs comparably. We also analyze the generated sentences qualitatively and find that the augmentation produces a correct translation in most cases. Our code is available on Github1. © 2023 Incoma Ltd. All rights reserved.

关键词： Computational linguistics

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Unsupervised GAN epoch selection for biomedical data synthesis

Unsupervised GAN epoch selection for biomedical data synthes...

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作者： Böhland, Moritz Bruch, Roman Löffler, Katharina Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany

Supervised Neural Networks are used for segmentation in many biological and biomedical applications. To omit the time-consuming and tiring process of manual labeling, unsupervised Generative Adversarial Networks (GANs) can be used to synthesize labeled data. However, the training of GANs requires extensive computation and is often unstable. Due to the lack of established stopping criteria, GANs are usually trained multiple times for a heuristically fixed number of epochs. Early stopping and epoch selection can lead to better synthetic datasets resulting in higher downstream segmentation quality on biological or medical data. This article examines whether the Frechet Inception Distance (FID), the Kernel Inception Distance (KID), or the WeightWatcher tool can be used for early stopping or epoch selection of unsupervised GANs. The experiments show that the last trained GAN epoch is not necessarily the best one to synthesize downstream segmentation data. On complex datasets, FID and KID correlate with the downstream segmentation quality, and both can be used for epoch selection. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Generative adversarial networks

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ZeitGeist: A Generic Tool Supporting the Dissemination of Time Series Data Following FAIR Principles 15

ZeitGeist: A Generic Tool Supporting the Dissemination of Ti...

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15th International Conference on Knowledge Management and Information Systems, KMIS 2023 as part of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023

作者： Schmidt, Andreas Koubaa, Mohamad Anis Schweikert, Jan Stucky, Karl-Uwe Süß, Wolfgang Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Department of Computer Science and Business Information Systems University of Applied Sciences Karlsruhe Germany

ISBN: (纸本)9789897586712

An important point for the widespread dissemination of FAIR-data is the lowest possible entry barrier for preparing and providing data to other scientists according to the FAIR criteria. If scientists have to manually extract, transform and annotate the data according to the FAIR criteria and then export it to make it available to the public, this requires a significant investment of time that does not primarily reward the scientist who prepares and provides the data. The Energy Lab at KIT is running a large cluster of an Influx database management system with energy related time series data being stored in a variety of individual databases over periods of up to 15 years. In order to increase the willingness to make data available to the scientific public, we develop a tool that greatly supports and automates the publication and annotation process of time series data stored in Influx databases. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Database systems

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Monte Carlo Simulation in a Digital Calibration Certificate 15th

Monte Carlo Simulation in a Digital Calibration Certificate

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15th EAI International Conference on automation and Control in Theory and Practice, ARTEP 2023

作者： Sammarah, George Halaj, Martin Bartalský, Lukáš Palenčár, Jakub Slovak University of Technology in Bratislava Faculty of Mechanical Engineering Institute of Automation Measurement and Applied Informatics Bratislava Slovakia

ISBN: (纸本)9783031319662

To establish trust in the measurement results, the metrological traceability of the measuring devices utilized must be ensured. This can be accomplished by confirming or calibrating the instruments. In reality, the information received during calibration is given in the traditional calibration certificate, and the user of the certified instrument decides how to utilize it in the measurement. Here comes the role of the digital calibration certificate that unlocks several features of this kind of calibration certificate that the user can use during its own measurements. In our case, the digital calibration certificate provides the option of supplying a large amount of additional data that may be usefully employed in various different tests. There are several methods for solving this kind of a problem. The paper discusses one method to this problem which is called the "Monte Carlo Method" and shows it using a specific case to give you a closer sight of this problem. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Calibration

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Control of Temperature Field in the Secondary Cooling Zone of Continuous Casting Process Based on Robust Internal Model Control (IMC) Approach 15th

Control of Temperature Field in the Secondary Cooling Zone o...

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15th EAI International Conference on automation and Control in Theory and Practice, ARTEP 2023

作者： Zarghoon, Sohaibullah Bartalský, Lukáš Belavý, Cyril Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology in Bratislava Bratislava Slovakia

ISBN: (纸本)9783031319662

As the cast strand moves through the secondary cooling zone in a continuous casting machine, the secondary cooling zone is typically separated into a number of zones to control the cooling rate. The secondary cooling zone’s primary tasks in terms of heat transfer are to deliver the amount of water necessary to completely solidify a strand within the parameters of continuous casting operation, such as steel grade and casting speed, or the system can the ability to control the strand’s thermal conditions from below the mold to the end of the secondary cooling zone, such as the required strand surface temperature. In this paper, the controller parameter optimization process will be done in Simulink using a robust control toolbox, and a robust method based on IMC controllers will be selected for control synthesis with the consideration of the controlled system uncertainty, and the result will be displayed as temperature fields, which represent the system with distributed parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Continuous casting

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