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International Multidisciplinary Conference on Computer and Energy Science (SpliTech)

作者： Kamrul Islam Shahin Sanja Lazarova-Molnar Parisa Niloofar Mærsk Mc-Kinney Møller Institute University of Southern Denmark Odense Denmark Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Karlsruhe Germany

Livestock farming plays a key role in the global food system, the economy, and the livelihood of millions of people. One of the undesirable facts in livestock production is the still insufficient consideration of the related environmental sustainability. Globally, livestock production accounts for about 14.5% of total greenhouse gas (GHG) emissions. These emissions are significantly changing our atmosphere and their impact is increasing. The main causes of these emissions are inefficient land resource management, synthetic fertilizer application, enteric fermentation, manure-related, and animal breed. It is, therefore, important to apply appropriate farm planning and management strategies to reduce the emissions. To support the global effort, we developed an application that we introduce in this paper, FarmMOODSS, to estimate net emissions by calculating GHG emissions at the farm level. FarmMOODSS recommends an optimized feeding program for emission mitigation. A multi-objective optimization algorithm is applied for feed optimization, including an IoT data mining function. The tool is developed based on a dairy farm use case.

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An Explainable Framework for Machine learning-Based Reactive Power Optimization of Distribution Network

arXiv

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arXiv 2023年

作者： Liao, Wenlong Schäfer, Benjamin Qin, Dalin Zhang, Gonghao Wang, Zhixian Yang, Zhe Lausanne Switzerland Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Department of Electrical Engineering The Hong Kong Polytechnic University Hong Kong

To reduce the heavy computational burden of reactive power optimization of distribution networks, machine learning models are receiving increasing attention. However, most machine learning models (e.g., neural networks) are usually considered as black boxes, making it challenging for power system operators to identify and comprehend potential biases or errors in the decision-making process of machine learning models. To address this issue, an explainable machine-learning framework is proposed to optimize the reactive power in distribution networks. Firstly, a Shapley additive explanation framework is presented to measure the contribution of each input feature to the solution of reactive power optimizations generated from machine learning models. Secondly, a model-agnostic approximation method is developed to estimate Shapley values, so as to avoid the heavy computational burden associated with direct calculations of Shapley values. The simulation results show that the proposed explainable framework can accurately explain the solution of the machine learning model-based reactive power optimization by using visual analytics, from both global and instance perspectives. Moreover, the proposed explainable framework is model-agnostic, and thus applicable to various models (e.g., neural networks). © 2023, CC BY-NC-ND.

关键词： Electric power distribution

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Enhancing Force Sensing Capabilities in Exoskeleton Interfaces Using Compliant Actuator-Sensor Units - A User Study

Enhancing Force Sensing Capabilities in Exoskeleton Interfac...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Hosam Alagi Nikola Fischer Kai Behrends Iris Ftirst-Walter Jürgen Becker Michael Beigl Franziska Mathis-Ullrich Björn Hein Intelligent Process Automation and Robotics Laboratory (IPR) Institute for Anthropomatics and Robotics (IAR) Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Institute of Telematics (TM) - Pervasive Computing Systems (TECO) at Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Institut fuer Technik der Informationsverarbeitung (ITIV) at Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander University Erlangen-Nürnberg (FAU) Erlangen Germany Karlsruhe University of Applied Sciences Karlsruhe Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Reliable interaction force sensing between an exoskeleton and the human body is crucial for personalized support and efficient control. Poor donning and disturbances during movement lead to lower force measurement quality and thus to unfavorable use. In this work, we present an active smart human-robot interface by utilizing compliant actuator-sensor units (CASUs) that can be worn over clothing. These units combine capacitive force sensing and actuation using Shape-Memory Alloy (SMA) to actively compensate disturbances and improve force measurement by tightening the interface and reestablishing optimal contact. We present a pilot user study with five subjects, investigating the performance of an exoskele-ton interface featuring three integrated CASUs to compensate for non-ideal donning configurations and displacements during daily activities of walking, sitting down, and climbing the stairs. The results for a passive interface show a decrease in holding forces and force signal quality during activities. Our active interface, on the other hand, effectively compensates for disturbances, restoring high signal quality by the mean of peak-to-peak value up to 300% which leads to more distinct signals.

关键词： Legged locomotion Force measurement Cooling Force Exoskeletons Metals Stairs Robot sensing systems Sensors Reliability

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ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles

arXiv

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arXiv 2022年

作者： Quintana, Matias Stoeckmann, Till Park, June Young Turowski, Marian Hagenmeyer, Veit Miller, Clayton Singapore Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Department of Civil Engineering University of Texas Arlington United States

Data-driven building energy prediction is an integral part of the process for measurement and verification, building benchmarking, and building-to-grid interaction. The ASHRAE Great Energy Predictor III (GEPIII) machine learning competition used an extensive meter data set to crowdsource the most accurate machine learning workflow for whole building energy prediction. A significant component of the winning solutions was the pre-processing phase to remove anomalous training data. Contemporary pre-processing methods focus on filtering statistical threshold values or deep learning methods requiring training data and multiple hyper-parameters. A recent method named ALDI (Automated Load profile Discord Identification) managed to identify these discords using matrix profile, but the technique still requires user-defined parameters. We develop ALDI++, a method based on the previous work that bypasses user-defined parameters and takes advantage of discord similarity. We evaluate ALDI++ against a statistical threshold, variational auto-encoder, and the original ALDI as baselines in classifying discords and energy forecasting scenarios. Our results demonstrate that while the classification performance improvement over the original method is marginal, ALDI++ helps achieve the best forecasting error improving 6% over the winning's team approach with six times less computation time. © 2022, CC BY.

关键词： Matrix algebra

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Adaptive Feedforward Control for DC/DC Converters in Microgrids - A Power Hardware in the Loop Study

Adaptive Feedforward Control for DC/DC Converters in Microgr...

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International Smart Grid Workshop and Certificate Program (ISGWCP)

作者： Jan Wachter Lutz Gröll Veit Hagenmeyer Institute for Automation and Applied Informatics (IAI) Karlsruhe Institute of Technology Karlsruhe Germany

This paper presents the application of an adaptive feedforward control approach based on radial basis functions for grid-tied Ćuk converters. A stability analysis provides a theoretical foundation for the expected stable operating range as well as bounds for the control signal at the operating points. With a power hardware in the loop implementation of the approach the feasibility for real-time application is shown, which is further illustrated by operating scenarios. Further, practical experience concerning the choice of the control parameters is presented along with the resulting advantages and limitations of the approach.

关键词： Microgrids Hardware Stability analysis Real-time systems Smart grids

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Performance optimization of the elliptically vibrating screen with a hybrid MACO-GBDT algorithm

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Particuology 2021年第3期19卷 193-206页

作者： Zhiquan Chen Zhanfu Li Huihuang Xia Xin Tong College of Mechanical Engineering and Automation Huaqiao UniversityXiamen 361021China Fujian Key Laboratory of Digital Equipment Fujian University of TechnologyFuzhou 350118China Institute for Applied Materials(IAM) Karlsruhe Institute of Technology(KIT)Hermann-von Helmholtz-Platz 176344 Eggenstein-LeopoldshafenGermany

As a typical screening apparatus,the elliptically vibrating screen was extensively employed for the size classification of granular *** efforts have been paid on the improvement of sieving performance,but the optimization problem was still perplexing the researchers due to the complexity of sieving *** the present paper,the sieving process of elliptically vibrating screen was numerically simulated based on the Discrete Element Method(DEM).The production quality and the processing capacity of vibrating screen were measured by the screening efficiency and the screening time,*** sieving parameters including the length of semi-major axis,the length ratio of two semi-axes,the vibration frequency,the inclination angle,the vibration direction angle and the motion direction of screen deck were ***,the Gradient Boosting Decision Trees(GBDT)algorithm was adopted in the modelling task of screening *** trained prediction models with sufficient generalization performance were obtained,and the relative importance of six parameters for both the screening indexes was *** that,a hybrid MACO-GBDT algorithm based on the Ant Colony Optimization(ACO)was proposed for optimizing the sieving performance of vibrating *** the single objective optimization of screening efficiency and the stepwise optimization of screening results were ***,the reliability of the MACO-GBDT algorithm were examined by the numerical *** optimization strategy provided in this work would be helpful for the parameter design and the performance improvement of vibrating screens.

关键词： Discrete Element Method(DEM) Elliptically vibrating screen Sieving performance Gradient Boosting Decision Trees(GBDT) Ant Colony Optimization(ACO)algorithm

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An Evaluation of Graph Algorithms for the Wind Farm Cable Layout Problem under Electrical Aspects

An Evaluation of Graph Algorithms for the Wind Farm Cable La...

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International Universities Power Engineering Conference (UPEC)

作者： Sascha Gritzbach Hüseyin Çakmak Pascal Mehnert Torsten Ueckerdt Veit Hagenmeyer Institute of Theoretical Informatics Karlsruhe Institute of Technology Karlsruhe Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Karlsruhe Institute of Technology Karlsruhe Germany

The task of the Wind Farm Cable Layout Problem is to design a cable system between turbines and substations such that all turbine output can be transmitted to the substations. This problem can be modelled with different levels of complexity. While a higher level of complexity yields solutions that can be implemented in a real-world setting more readily, problem instances also become more difficult to solve or even remain intractable. More simplistic models are easier to solve but their usability could be inhibited. One such more simplistic model for installation cost minimization contains a network flow and a suitable minimum-cost flow algorithm provides good cable layouts on instances with up to 500 turbines within tens of seconds. The question remains whether those cable layouts are suitable for electrical implementation as well. We propose a workflow to evaluate the cable layouts generated from such algorithms under electrical aspects. This workflow converts the output of cable layout optimization algorithms to power flow models. The power flow models are simulated using the simulation framework eASiMOV. The evaluation of the power flow simulations under electrical metrics shows that output from the minimum-cost flow algorithm and from an approach solving a Mixed-Integer Linear Program perform very well under electrical aspects on a vast majority of input instances. For the remaining minority we are able to identify structures in the solutions that result in a worse performance. These observations can be used by the algorithm engineers as possible directions for future improvements.

关键词： Substations Power cables Layout Software algorithms Wind farms Power system stability Software

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Experimental validation of demand side response rates for frequency control

Experimental validation of demand side response rates for fr...

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IEEE Electronic Power Grid (eGrid)

作者： Leo Casasola-Aignesberger Friedrich Wiegel Simon Waczowicz Veit Hagenmeyer Sergio Martinez Department of electrical engineering Escuela Técnica Superior de Ingenieros Industriales Universidad Politécnica de Madrid Madrid Spain Institute for Automation and Applied Informatics Karlsruhe Institute of Technology (KIT)

Renewable energy generation is replacing conventional synchronous generators in electrical power systems around the world. A side effect of this trend is a reduction in system inertia and the power available for frequency control. In this study, the authors investigate an island power system of interest under different conditions with varying levels of demand side response penetration and analyze its impact on frequency behavior. The obtained simulation results are then complemented with a series of experiments carried out using a combination of real hardware and Power-Hardware-In-the-Loop equipment, to test the validity and limitations of the simulation results. In summary, demand side response can notably improve the frequency response of an island power system, but excessive demand side response leads to unacceptable frequency oscillations.

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The analysis of surface roughness of the samples produced by 3D printing 31

The analysis of surface roughness of the samples produced by...

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31st Joint Seminar on the Development of Materials Science in Research and Education, DMSRE 2022

作者： Oravcová, J. Labašová, E. Slovak University of Technology in Bratislava Faculty of Materials Science and Technology in Trnava Institute of Applied Informatics Automation and Mechatronics Ulica Jána Bottu 2781/25 Trnava917 24 Slovakia

This paper deals with measurement and analysis of surface roughness of samples produced by 3D printing, Gembird white and Verbatim white. Process parameters such as print speed, print layer thickness, and print material changed when the samples were printed. The surface roughness of the samples was measured using the TR200 roughness meter. The paper analyzes the roughness parameter Ra, which represents the mean arithmetic deviation of the profile. © Published under licence by IOP Publishing Ltd.

关键词： Surface roughness

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Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics

arXiv

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arXiv 2024年

作者： Seiffarth, Johannes Blöbaum, Luisa Paul, Richard D. Friederich, Nils Yamachui Sitcheu, Angelo Jovin Mikut, Ralf Scharr, Hanno Grünberger, Alexander Nöh, Katharina Institute of Bio- and Geosciences IBG-1: Biotechnology Forschungszentrum Jülich GmbH Jülich Germany RWTH Aachen University Aachen Germany Multiscale Bioengineering Bielefeld University Bielefeld Germany Institute for Advanced Simulation IAS-8: Data Analytics and Machine Learning Forschungszentrum Jülich GmbH Jülich Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany Institute of Biological and Chemical Systems Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany Microsystems in Bioprocess Engineering Karlsruhe Institute of Technology Karlsruhe Germany

Tracking the development of living cells in live-cell time-lapses reveals crucial insights into single-cell behavior and presents tremendous potential for biomedical and biotechnological applications. In microbial live-cell imaging (MLCI), a few to thousands of cells have to be detected and tracked within dozens of growing cell colonies. The challenge of tracking cells is heavily influenced by the experiment parameters, namely the imaging interval and maximal cell number. For now, tracking benchmarks are not widely available in MLCI and the effect of these parameters on the tracking performance are not yet known. Therefore, we present the largest publicly available and annotated dataset for MLCI, containing more than 1.4 million cell instances, 29k cell tracks, and 14k cell divisions. With this dataset at hand, we generalize existing tracking metrics to incorporate relevant imaging and experiment parameters into experiment-aware metrics. These metrics reveal that current cell tracking methods crucially depend on the choice of the experiment parameters, where their performance deteriorates at high imaging intervals and large cell colonies. Thus, our new benchmark quantifies the influence of experiment parameters on the tracking quality, and gives the opportunity to develop new data-driven methods that generalize across imaging and experiment parameters. The benchmark dataset is publicly available at https://***/doi/10.5281/zenodo.7260136. © 2024, CC BY.

关键词： Cytology

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