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6th KES International Conference on Sustainable Design and Manufacturing, KES-SDM 2019

作者： Nau, Katja Scholz, Steffen G. Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany

ISBN: (纸本)9789811392702

This paper presents a safe-by-design approach developed for enhanced inks containing nanomaterials for 3D inkjet printing. Manufactured nanomaterials, like aluminium oxides and zirconium dioxide, are increasingly used for additive manufacturing today. However, the impact and interaction of nanomaterials on human health and the environment are widely discussed today. Our approach aims to describe the safe and sustainable use of nanomaterials for 3D inks. We rely on well-characterised non-toxic nanomaterials;their properties are documented in safety data sheets. In order to identify possible exposure to humans and the environment, we investigate the development of inks and their application in the 3D printing process. © 2019, Springer Nature Singapore Pte Ltd.

关键词： 3D printers

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Results of the Ontology Alignment Evaluation Initiative 2024 19

Results of the Ontology Alignment Evaluation Initiative 2024

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19th International Workshop on Ontology Matching, OM 2024

作者： Pour, Mina Abd Nikooie Algergawy, Alsayed Blomqvist, Eva Buche, Patrice Chen, Jiaoyan Cotovio, Pedro Giesteira Coulet, Adrien Cufi, Julien Dong, Hang Faria, Daniel Ferraz, Lucas Hertling, Sven He, Yuan Horrocks, Ian Ibanescu, Liliana Jain, Sarika Jiménez-Ruiz, Ernesto Karam, Naouel Kraus, Felix Lambrix, Patrick Li, Huanyu Li, Ying Monnin, Pierre Paulheim, Heiko Pesquita, Catia Sharma, Abhisek Shvaiko, Pavel Silva, Marta Sousa, Guilherme Trojahn, Cassia Vataščinová, Jana Yaman, Beyza Zamazal, Ondřej Zhou, Lu Department of Computer and Information Science Linköping University Linköping Sweden Swedish e-Science Research Centre Linköping Sweden Friedrich Schiller University Jena Germany University of Passau Germany UMR IATE INRAE University of Montpellier France Department of Computer Science The University of Manchester United Kingdom City St George's University of London United Kingdom University of Oslo Norway LASIGE Faculdade de Ciências Universidade de Lisboa Portugal Inria Paris France Centre de Recherche des Cordeliers Inserm Université Paris Cité Sorbonne Université France Department of Computer Science University of Exeter United Kingdom INESC-ID/IST University of Lisbon Portugal Data and Web Science Group University of Mannheim Germany Department of Computer Science University of Oxford United Kingdom Université Paris-Saclay INRAE AgroParisTech UMR MIA Paris-Saclay France National Institute of Technology Kurukshetra Haryana India Institute for Applied Informatics University of Leipzig Germany Karlsruhe Institute of Technology Karlsruhe Germany Université Côte d'Azur Inria CNRS I3S Sophia Antipolis France Trentino Digitale SpA Trento Italy Institut de Recherche en Informatique de Toulouse France Univ. Grenoble Alpes Inria CNRS Grenoble INP LIG GrenobleF-38000 France Prague University of Economics and Business Czech Republic ADAPT Centre Trinity College Dublin Ireland Flatfee Corp United States

The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities. The OAEI 2024 campaign offered 13 tracks and was attended by 13 participants. This paper is an overall presentation of that campaign. © 2024 Copyright for this paper by its authors.

关键词： Ontology

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The role of interpretable patterns in deep learning for morphology

arXiv

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arXiv 2020年

作者： Ács, Judit Kornai, András Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary Institute for Computer Science and Control Hungary

We examine the role of character patterns in three tasks: morphological analysis, lemmatization and copy. We use a modified version of the standard sequence-to-sequence model, where the encoder is a pattern matching network. Each pattern scores all possible N character long subwords (substrings) on the source side, and the highest scoring subword’s score is used to initialize the decoder as well as the input to the attention mechanism. This method allows learning which subwords of the input are important for generating the output. By training the models on the same source but different target, we can compare what subwords are important for different tasks and how they relate to each other. We define a similarity metric, a generalized form of the Jaccard similarity, and assign a similarity score to each pair of the three tasks that work on the same source but may differ in target. We examine how these three tasks are related to each other in 12 languages. Our code is publicly available. © 2020, CC BY-SA.

关键词： Pattern matching

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Semantic CIM2Matpower: Ontology-Based Network Topology Processor and Converter for CIM Node-Breaker Models

Semantic CIM2Matpower: Ontology-Based Network Topology Proce...

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IEEE International Conference on Smart Energy Grid Engineering (SEGE)

作者： Artem Schumilin Hüseyin Kemal Çakmak Karl-Uwe Stucky Clemens Duepmeier Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany

Smart electricity grids are key to a successful transition towards a future sustainable energy system. Network topology processing (NTP) is an important and frequently reoccurring task in most power grid analysis and simulation applications' including power flow calculations, short circuit and contingency analysis. NTP is applied to a detailed node-break-er representation of the power grid, as provided by the IEC Common Information Model (CIM). It is performed in order to obtain a reduced bus-branch representation, which serves as input to downstream analysis and simulation applications. The present paper introduces a novel approach to NTP that utilises a semantic knowledge base for network model management and exploits semantic reasoning over the formal CIM ontology and instance data. The proposed system is tested on publicly available ENTSO-E data, validated by converting the generated bus-branch model to Matpower and running power flow calculations in a power grid modelling and simulation framework.

关键词： Semantics Data models Load modeling Unified modeling language Ontologies Switches Power grids

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On Verification of Designed Energy Systems Using Distributed Co-Simulations

On Verification of Designed Energy Systems Using Distributed...

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International Workshop/Symposium on Distributed Simulation and Real-Time Applications (DS-RT)

作者： Anselm Erdmann Anna Marcellan Dominik Hering Michael Suriyah Carolin Ulbrich Martin Henke André Xhonneux Dirk Müller Rutger Schlatmann Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Institute of Combustion Technology German Aerospace Center Stuttgart Germany Institute of Energy and Climate Research Energy Systems Engineering (IEK-10) Forschungszentrum Jülich GmbH Jülich Germany Institute of Electric Energy Systems and High-Voltage Technology Karlsruhe Institute of Technology Karlsruhe Germany PVcomB Helmholtz-Zentrum Berlin für Materialien und Energie GmbH Berlin Germany

ISBN: (数字)9781728173436

ISBN: (纸本)9781728173443

An essential part of the energy systems design procedure is simulation, since it serves as a tool for verification of the respective design. It serves the verifying of a stable operation of developed energy systems infrastructure, before it comes to the realization. As energy systems integration becomes an important part in a low carbon energy scenario in the future, the cooperation of experts specialized in various domains crucial to single aspects of the energy system is indispensable. Cosimulation, yet, enables the modelling in the familiar environment of the experts, but requires a detailed coordination of the simulation interfaces between the specific expert models. Hence, standardized interfaces are crucial to the efficient use of expert knowledge in distributed co-simulations. Therefore, in the presented paper a workflow for the co-simulation development of energy systems simulations, which simplifies the coordination procedure significantly by standardizing the interfaces between the models and their simulations, is introduced. The approach is exemplarily applied to the energy system design of a district comprising electricity and heat in order to show its successful performance.

关键词： Adaptation models Tools Mathematical model System analysis and design Data models Standards

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MagnetoShield: Prototype of a Low-Cost Magnetic Levitation Device for Control Education

MagnetoShield: Prototype of a Low-Cost Magnetic Levitation D...

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IEEE Education Engineering (EDUCON)

作者： Gergely Takács Jakub Mihalík Erik Mikuláš Martin Gulan Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology in Bratislava Bratislava Slovakia

ISBN: (数字)9781728109305

ISBN: (纸本)9781728109312

This article presents a prototype reference design for a low-cost miniature magnetic levitation experiment. The proposed device is built as an Arduino expansion module, thus may be installed on a broad range of microcontroller prototyping boards. The open-source hardware design uses off-the-shelf and widely available components and 3D printing technology, thus its overall material cost is minimal. This way, the magnetic levitation experiment is transformed into a pocket laboratory that can be borrowed by students for take-home experiments. In addition to the device itself, we present an open-source application programming interface and the outline of classroom examples in modeling, system identification and closed-loop control.

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Semi-Automatic Generation Of Tight Binary Masks And Non-Convex Isosurfaces For Quantitative Analysis Of 3d Biological Samples

Semi-Automatic Generation Of Tight Binary Masks And Non-Conv...

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IEEE International Conference on Image Processing

作者： Sourabh Bhide Ralf Mikut Maria Leptin Johannes Stegmaier Director’s Research Unit European Molecular Biology Laboratory Heidelberg Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany European Molecular Biology Organization Heidelberg Germany Institute of Imaging and Computer Vision RWTH Aachen University Aachen Germany

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Current in vivo microscopy allows us detailed spatiotemporal imaging (3D+t) of complete organisms and offers insights into their development on the cellular level. Even though the imaging speed and quality is steadily improving, fullyautomated segmentation is often not accurate enough in lowsignal image regions. This is particularly true while imaging large samples (100 μm -1 mm) and deep inside the specimen. Drosophila embryogenesis, widely used as a developmental paradigm, presents an example for such a challenge, especially where cell outlines need to imaged - a general challenge in other systems as well. To deal with the current bottleneck in analyzing quantitatively the 3D+t light-sheet microscopy images of Drosophila embryos, we developed a collection of semi-automatic open-source tools. The presented methods include a semi-automatic masking procedure, automatic projection of non-convex 3D isosurfaces to 2D representations as well as cell segmentation and tracking.

关键词： Three-dimensional displays Image segmentation Two dimensional displays Embryo Shape Isosurfaces Computer architecture

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Explicit spline-based continuous-time MPC: a study on design and performance

引用

IFAC-PapersOnLine 2020年第2期53卷 7013-7019页

作者： Boris Rohaľ-Ilkiv Martin Gulan Peter Minarčík Institute of Automation Measurement and Applied Informatics Faculty of Mechanical engineering Slovak University of Technology in Bratislava Námestie slobody 17 812 31 Bratislava Slovakia

This paper presents a continuous-time model predictive control scheme based on B-spline functions used for signals and model approximation. The proposed controller offers two interesting advantages. First, it formulates the control signal as a continuous polynomial spline function, the nature of which is determined by its control polygon that is subject of optimization. Second, all continuous constraints assumed over prediction horizon are consistently transformed into constraints imposed on a finite number of elements of this control polygon. Using parametric quadratic programming we further show how to obtain an explicit representation of the proposed controller, which is known for its efficient online implementation. The featured simulation study demonstrates that by a suitable choice of number and position of knots of the spline function over the prediction horizon it is possible to substantially reduce the number of critical regions of the explicit controller while preserving control performance, and to mitigate the direct correlation between number of regions and chosen length of prediction horizon.

关键词： explicit model predictive control parametric programming linear systems B-spline functions continuous-time control efficient implementation

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Physics-Informed Machine Learning for Power Grid Frequency Modeling

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PRX Energy 2023年第4期2卷 043003-043003页

作者： Johannes Kruse Eike Cramer Benjamin Schäfer Dirk Witthaut Forschungszentrum Jülich Institute for Energy and Climate Research (IEK-STE) Jülich 52428 Germany Institute for Theoretical Physics University of Cologne Köln 50937 Germany Forschungszentrum Jülich Institute for Energy and Climate Research—Energy Systems Engineering (IEK-10) Jülich 52428 Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen 76344 Germany

The operation of power systems is affected by diverse technical, economic, and social factors. Social behavior determines load patterns, electricity markets regulate the generation, and weather-dependent renewables introduce power fluctuations. Thus, power system dynamics must be regarded as a nonautonomous system whose parameters vary strongly with time. However, the external driving factors are usually only available on coarse scales and the actual dependencies of the dynamic system parameters are generally unknown. Here, we propose a physics-informed machine learning model that bridges the gap between large-scale drivers and short-term dynamics of the power system. Integrating stochastic differential equations and artificial neural networks, we construct a probabilistic model of the power grid frequency dynamics in continental Europe. Its probabilistic prediction outperforms the daily average profile, which is an important benchmark, on a time horizon of 15 min. Using the integrated model, we identify and explain the parameters of the dynamical system from the data, which reveal their strong time-dependence and their relation to external drivers such as wind power feed-in and fast generation ramps. Finally, we generate synthetic time series from the model, which successfully reproduce central characteristics of the grid frequency such as their heavy-tailed distribution. All in all, our work emphasizes the importance of modeling power system dynamics as a stochastic nonautonomous system with both intrinsic dynamics and external drivers.

关键词： Grid stability Stochastic processes Machine learning Stochastic differential equations Time series analysis

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A Study of Falkner-Skan Flow of Casson Fluid with Development of Empirical Regression Model for Wall Heat and Concentration Flux

SSRN

引用

SSRN 2022年

作者： Hussain, Dilawar Asghar, Zaheer Zeeshan, Ahmed Alsulami, Hamed Band, Shahab S. Mosavi, Amir Department of Mathematics & Statistics FBAS International Islamic University Islamabad IslamabadH-10 Pakistan Centre for Mathematical Sciences Pakistan Institute of Engineering and Applied Sciences Nilore Islamabad45650 Pakistan Centre for Physics and Applied Mathematics Pakistan Institute of Engineering and Applied Sciences Nilore Islamabad45650 Pakistan -Research Group Department of Mathematics Faculty of Science King Abdulaziz University P.O. Box 80203 Jeddah21589 Saudi Arabia Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan John von Neumann Faculty of Informatics Obuda University Budapest Hungary Institute of Information Engineering Automation and Mathematics Slovak University of Technology in Bratislava Bratislava Slovakia

In this communication, authors ambition is to investigate the sensitivity of heat flux at solid liquid interface of Falkner-Skan (FS) flow of Casson fluid on a moving wedge. Alongside, authors intended to develop an empirical model in terms of involving parameters. Sensitivity analysis is an essential toll in engineering and manufacturer process to examine the effect of different input factors and reduces the experimental cost and save valuable time. The FS flow in this case is observed under the influence of induced magnetic field. The mathematical model of the flow experiments are adopted from El-Dabe et al. [1] which was solved numerically by using computational software MATLAB and achieved reliable solutions- validated by comparing the numerical results with published results. Researchers and scientists have used a variety of empirical methods to investigate the sensitivity of the output variables. The most effective method for determining the relationship between input parameters and output responses is the correlation development method. A data set is extracted for wall heat flux and Sherwood number at random points, and finally by using RSM the correlation of input parameter and output responses are developed. The statistical results of ANOVA are presented in tabular form by using RSM. © 2022, The Authors. All rights reserved.

关键词： Sensitivity analysis

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