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检索条件"机构=Automation and Applied Informatics"

共 2254 条记录，以下是11-20 订阅

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Real-Time Evaluation of Weighting Factorless Predictive Control of LCL Filter Equipped Grid-Side Converters using Sorting Networks

Real-Time Evaluation of Weighting Factorless Predictive Cont...

引用

2024 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2024

作者： Bándy, Kristóf Stumpf, Péter Süto, Zoltán Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary

ISBN: (纸本)9783800762620

A novel multi-cost function model-based finite-set predictive control method is presented for grid-side converters equipped with LCL filters. This approach aims to overcome the tedious tuning of weighting factors. In the method, the cost functions are established based on various state variables and their references. Then the control options are ranked based on their performance in each of the cost functions. This ranking score determines the selection of the optimal control action. The control method is validated in a low-cost custom Hardware-in-the-Loop (HIL) environment using model-based rapid-prototyping tools of Matlab/Simulink. Simulation and measurement results show the viability of the method. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Hardware-in-the-loop simulation

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Machine Learning and Dynamic Time Warping for Online Signature Verification 32

Machine Learning and Dynamic Time Warping for Online Signatu...

引用

32nd International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2024

作者： Saleem, Mohammad Budapest University of Technology and Economics Department of Automation and Applied Informatics Budapest Hungary

ISBN: (纸本)9789532901382

Signature verification is a very common task in the field of document analysis used for the identification and validation of individuals. Many approaches can be used for signature classification. Using a machine-learning-based system is one of the most common approaches. This paper uses machine learning to classify signatures as genuine or forged. It also used a dynamic time-warping approach in the preprocessing step to produce data for training purposes. This approach differs from using it in the classification phase, which is a common practice in signature verification. The work targets online signatures, which are obtained using digital devices. Different databases were used to evaluate the accuracy of the verification systems, and four different algorithms were used for classification. The results are very promising. The minimum error rate achieved was 2.09% for the MCYT-100 dataset, 3.34% for the SVC2004 dataset, 1. 6 8 % for the SigComp'11-Chinese dataset, and 3. 6 8 % for the SigComp'11- Dutch dataset. © 2024 University of Split, FESB.

关键词： Adversarial machine learning

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New Co-Simulation Variants for Emissions and Cost Reduction of Sustainable District Heating Planning 16

New Co-Simulation Variants for Emissions and Cost Reduction ...

引用

16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024

作者： Cheng, Haozhen Buccoliero, Verena Kocher, Alexander Hagenmeyer, Veit Çakmak, Huseyin K. Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe76131 Germany

ISBN: (纸本)9798350386127

Classical heating of residential areas is very energy-intensive, so alternatives are needed, including renewable energies and advanced heating technologies. Thus, the present paper introduces a new methodology for comprehensive variant analysis for future district heating planning, aiming at optimizing emissions and costs. For this, an extensive Modelica-based modelling study comprising models of heating center, heat grid pipelines and heating interface units to buildings are coupled in co-simulations. These enable a comparative analysis of the economic feasibility and sustainability for various technologies and energy carriers to be carried out. The new modular and highly parameterizable building model serves for validation of the introduced heat grid model. The results show that bio-methane as an energy source reduces carbon equivalent emissions by nearly 70% compared to conventional natural gas heating, and the use of hydrogen as an energy source reduces carbon equivalent emissions by 77% when equipped with a heat pump. In addition, the use of ground source heat pumps has a high economic viability when economic benefits are taken into account. The study findings highlight the importance of strategic planning and flexible design in the early stages of district development in order to achieve improved energy efficiency and a reduced carbon footprint. © 2024 IEEE.

关键词： Carbon capture and utilization

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Enhanced Indoor Mapping via Integration of Lidar and HoloLens 2 Data Using Iterative Closest Point Algorithm 22

Enhanced Indoor Mapping via Integration of Lidar and HoloLen...

引用

22nd IEEE International Symposium on Intelligent Systems and informatics, SISY 2024

作者： Szalka, Panka Hideg, Attila Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics Budapest Hungary

ISBN: (纸本)9798350385601

This study presents an innovative method to improve the accuracy of indoor mapping by deploying and integrating a sensor that transmits two-dimensional data with a three-dimensional mesh created by another device. The Iterative Closest Point algorithm was used to coordinate the different data sets and transform their different coordinate systems into a common indoor map. Prior to this, rigorous image cleaning and matching processes are conducted to ensure the quality of the data used. The effectiveness of this methodology has been validated through multiple tests using a Lidar scanner and a HoloLens 2 Augmented Reality device. This method not only offers potential for enhancing indoor navigation and safety protocols like emergency evacuation but also presents opportunities for advancing asset tracking and other applications. © 2024 IEEE.

关键词： Indoor positioning systems

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Speech Emotion Recognition Using openSMILE and GPT 3.5 Transformer

Speech Emotion Recognition Using openSMILE and GPT 3.5 Trans...

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34th Medical informatics Europe Conference, MIE 2024

作者： Turcian, Darius Stoicu-Tivadar, Vasile Politehnica University Timișoara Department of Automation and Applied Informatics Timișoara Romania

ISBN: (纸本)9781643685335

In recent years, artificial intelligence, and machine learning (ML) models have advanced significantly, offering transformative solutions across diverse sectors. Emotion recognition in speech has particularly benefited from ML techniques, revolutionizing its accuracy and applicability. This article proposes a method for emotion detection in Romanian speech analysis by combining two distinct approaches: semantic analysis using GPT Transformer and acoustic analysis using openSMILE. The results showed an accuracy of 74% and a precision of almost 82%. Several system limitations were observed due to the limited and low-quality dataset. However, it also opened a new horizon in our research by analyzing emotions to identify mental health disorders. © 2024 The Authors.

关键词： GPT 3.5 Machine Learning openSMILE Speech Emotion Recognition

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Using Large Language Models for Extracting Structured Information From Scientific Texts

Using Large Language Models for Extracting Structured Inform...

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作者： Rettenberger, Luca Münker, Marc F. Schutera, Mark Niemeyer, Christof M. Rabe, Kersten S. Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Karlsruhe Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Institute for Biological Interfaces Karlsruhe Institute of Technology Germany

Extracting structured information from scientific works is challenging as sought parameters or properties are often scattered across lengthy texts. We introduce a novel iterative approach using Large Language Models (LLMs) to automate this process. Our method first condenses scientific literature, preserving essential information in a dense format, then retrieves predefined attributes. As a biomedical application example, our concept is employed to extract experimental parameters for preparing Metal-Organic Frameworks (MOFs) from scientific work to enable complex and information-rich applications in the biotechnology-oriented life sciences. Our open-source method automates extracting information from verbose texts, converting them into structured and easily navigable data. This considerably improves scientific literature research by utilizing the power of LLMs and paves the way for enhanced and faster information extraction from extensive scientific texts. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Information retrieval

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Towards a Real-World Dispatchable Feeder 8

Towards a Real-World Dispatchable Feeder

引用

8th IEEE Workshop on the Electronic Grid, eGRID 2023

作者： Beichter, Sebastian Beichter, Maximilian Werling, Dorina Galenzowski, Johannes Weise, Victor Hildenbrand, Christoph Wiegel, Friedrich Mikut, Ralf Waczowicz, Simon Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany

ISBN: (纸本)9798350327007

With the integration of renewable energy sources, electric vehicles, and batteries at the low-voltage distribution grid level, residential buildings are increasingly evolving from consumers to prosumers. As the prosumers burden the distribution grid with their uncertain interactions, the need for solutions to counteract this uncertainty becomes more important. One such solution is schedule-based control strategies, such as the dispatchable feeder. Thereby, the dispatchable feeder uses intelligent managed flexible components such as battery energy storage system (BESS) and controllable loads to follow a committed schedule. While the concept of the dispatchable feeder is widely discussed in the literature, the practical challenges associated with its real-world implementation remain under-explored. Therefore, this paper identifies challenges associated with the real-world implementation of the dispatchable feeder in residential buildings. Further, it discusses important future research questions regarding the concept and its valuable integration into the real world. It also proposes an experimental research infrastructure for systematically investigating the raised questions using the real-world laboratory of the Energy Lab 2.0. © 2023 IEEE.

关键词： Renewable energy

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Ultrasonic and VCSEL sensor fusion for distance measurement in parking assistance 24

Ultrasonic and VCSEL sensor fusion for distance measurement ...

引用

24th International Conference on Control Systems and Computer Science, CSCS 2023

作者： Sandru, Florin-Daniel Ungureanu, Vlad-Ilie Silea, Ioan Politehnica University Timisoara Automation and Applied Informatics Timisoara Romania

ISBN: (纸本)9798350313390

Parking assistance is a desired and common feature of vehicles manufactured in the present years. For a vehicle to offer valuable information for such a system, in most of the cases, ultrasonic sensors are used to measure distance. Being dependent on a single type of sensor can result in an unreliable measurement, especially if that sensor is in an environment that affects its measurement capabilities. This paper proposes a combination of an ultrasonic sensor and a light-based measurement of distance sensor. The focus is on overcoming the technological weak points of each individual solution and obtaining more accurate measurements through sensor fusion. The fusion is based on the usage of an individual Kalman filter per sensor and an external fusion block that uses the Kalman filter outputs. Apart from being presented in graphical form, the results are analyzed using mean absolute percentage error as a relevant metric. © 2023 IEEE.

关键词： Ultrasonic sensors

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Low Latency Video Streaming System for VR Teleoperation over 5G Networks 3

Low Latency Video Streaming System for VR Teleoperation over...

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024

作者： Blázovics, László Kovács, Viktor Gótzy, Márton Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics BudapestH-1111 Hungary

ISBN: (纸本)9798350378009

With the introduction of 5G networks, high-speed low-latency network connections became available for mobile and embedded devices without the limited range of WiFi networks. Although the source and the destination can now be hundreds of kilometres away, the communication between them can be flawless. Our goal is to have a low cost, low power, lightweight device that is able to stream video for UAV (unmanned aerial vehicles), mobile robot teleoperation over 5G networks to AR/VR (augmented/virtual reality) applications, to large distances without the need for line of sight. In this paper we compare the latency of existing low cost video streamer solutions (UAV camera streaming, single board computer) and present a custom hardware-software solution optimized for low latency, while conducting measurements over different network types (wired, campus 5G, public 5G). We have shown that the custom device was able to achieve with significantly lower latency (50-80 ms direct over direct connection, about 100-150 ms over public 5G). © 2024 IEEE.

关键词： 5G mobile communication systems

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Using Weka API for creating a custom classification application 17

Using Weka API for creating a custom classification applicat...

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17th IEEE International Symposium on applied Computational Intelligence and informatics, SACI 2023

作者： Robu, Raul Arseni-Ailoi, Paul Ungureanu-Anghel, Dan Politehnica University of Timisoara Faculty of Automation and Computers Department of Automation and Applied Informatics Timisoara Romania

ISBN: (纸本)9798350321104

In real world applications, classification models can be built by repeatedly going through the steps of data preprocessing, building classification models with different dedicated algorithms, testing the resulted models, until building a good enough classification model is achieved. The model built in this way can be used in order to perform predictions on new data, with a degree of trust resulted by testing the model. All the operations described above can be done with Weka, which is a very powerful machine learning tool. The authors consider that after going through the previous steps, for many real world applications, it would be beneficial to go through a supplementary step, of developing a custom application for data classification, specific to the realized study. The proposed application will use the Weka API, which will allow it to rebuild the selected classification model, save and load it in/from a binary file and then make predictions with the help of a user interface perfectly adapted to the data set used. The proposed application makes it easier to make predictions for a final beneficiary. The paper presents how such a custom classification application can be developed, using the Weka API and Java programming language. In order to validate the proposed solution, the authors have built a custom application for the classification of data of patients who may have heart diseases, starting from the Cleveland heart disease data set, obtained from the UCI Machine Learning Repository. The proposed application allows saving and loading the classification model through serialization and deserialization, so that building it in order to make predictions is necessary only once. © 2023 IEEE.

关键词： Forecasting

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