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SSRN 2023年

作者： Langner, Felix Frahm, Moritz Wang, Weimin Matthes, Jörg Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany Department of Engineering Technology University of North Carolina at Charlotte CharlotteNC28223 United States

Using Model Predictive Control (MPC) is a promising method for enabling grid-interactive efficient buildings. Since MPC relies on a building model and the forecasts of external disturbances to derive optimal inputs, the uncertainties due to forecast errors and model inaccuracies can deteriorate the control performance. Most existing MPC studies for built environment are deterministic MPC (DMPC) without consideration of uncertainties even though several different methods (e.g., stochastic MPC) are available in literature to deal with them. Hence, in the present paper, a hierarchical-stochastic MPC (HSMPC) is proposed and its performance is compared with deterministic, stochastic, and hierarchical MPC for power management in a residential building with distributed energy resources. The control objective is the cost-optimal scheduling of a heat pump, a battery for energy storage, and a rooftop photovoltaic system. Measurement data is used to identify the building model. The results for one-week simulation in winter show that 1) the deterministic MPC results in an unacceptable level of temperature constraint violations in two out of five rooms;2) the hierarchical MPC can reduce the temperature constraint violations to an acceptable level at the expense of increased cost;3) the stochastic MPC achieves the same reduction in temperature constraint violations as the hierarchical MPC but at slightly lower costs;and 4) the new proposed HSMPC results in both lower temperature constraint violations and lower financial expenses than the use of stochastic or hierarchical MPC individually. © 2023, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Importance of environment design in reinforcement learning: A study of a robotic environment

arXiv

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arXiv 2021年

作者： Farsang, Mónika Szegletes, Luca Department of Automation and Applied Informatics Budapest University of Technology and Economics

An in-depth understanding of the particular environment is crucial in reinforcement learning (RL). To address this challenge, the decision-making process of a mobile collaborative robotic assistant modeled by the Markov decision process (MDP) framework is studied in this paper. The optimal state-action combinations of the MDP are calculated with the non-linear Bellman optimality equations. This system of equations can be solved with relative ease by the computational power of Wolfram Mathematica, where the obtained optimal action-values point to the optimal policy. Unlike other RL algorithms, this methodology does not approximate the optimal behavior, it gives the exact, explicit solution, which provides a strong foundation for our study. With this, we offer new insights into understanding the action selection mechanisms in RL by presenting various small modifications on the very same schema that lead to different optimal policies. © 2021, CC BY.

关键词： Dynamic programming

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A Fused Machine Learning Approach for Intrusion Detection System

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Computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan Muhammad Adnan Khan Amir Mosavi School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of *** interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and *** learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit *** intrusion detection system controls the flow of network traffic with the help of computer *** deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network *** this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network *** Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious *** proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

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Image Processing Methods for Detecting Voids in the Solder Joints of Surface-Mounted Components

Image Processing Methods for Detecting Voids in the Solder J...

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International Spring Seminar on Electronics Technology

作者： Oliver Krammer Á rpá d Varga Attila Gé czy Kristó f Csorba Department of Electronics Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

Void formation in the lead-free solder joints of electrical components can significantly affect their mechanical properties and thermal performance. Void-detection methods have been investigated in this paper, which are able to identify and measure voids in meniscus-shaped solder joints of surface mounted components automatically. In the experiment, 0603 size resistors (1.5 × 0.75 mm) were soldered onto a testboard, and X-ray images were acquired about the samples then. The image processing methods for the void detection were implemented in OpenCV-Python. At first, the properties of the images were analyzed (for example, calculating the histogram), and then the area, including the resistor and solder pads, was extracted by masking. Several methods were investigated for identifying voids in the images; Canny edge detection, global-and adaptive thresholding, and blob detection algorithm. The accuracy of the extraction methods was evaluated by identifying voids on a test image manually and comparing the results to that provided by the different methods. Canny edge detection was the best in our case, but global thresholding and blob detection are also promising solutions.

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Comparison of optimization algorithms for installation error calibration of accelerometer arrays

Comparison of optimization algorithms for installation error...

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International Symposium on Computational Intelligence and informatics

作者： Richard Pesti Peter Sarcevic Dominik Csík Istvan Nagy Akos Odry Doctoral School of Applied Informatics and Applied Mathematics Óbuda University Budapest Hungary Department of Mechatronics and Automation University of Szeged Szeged Hungary Bánki Donát Faculty of Mechanical and Safety Engineering Óbuda University Budapest Hungary

Accelerometers play a crucial role in localization problems, but their accuracy depends on the precision of the calibration process. In this paper, a comparison of optimization algorithms is presented within the scope of between sensor error calibration. The Particle Swarm optimization (PSO) and Genetic Algorithm (GA) are proposed for the problem, and tested in three different setups. Moreover, the MATLAB built-in fmincon minimization algorithm is also evaluated for calibration parameter estimation. A custom fitness function is proposed to obtain the between sensor misalignment and bias errors, for two accelerometers. The analysis highlights that the algorithms can successfully determine the between sensor error parameters. The conducted comparison shows that fmincon reached an outstanding speed in terms of convergency, but in overall PSO has produced better results compared to GA and fmincon. PSO is more suitable for the calibration problem because of its robustness and stability characteristics.

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Raman microscopic measurement of materials used on banknotes

Raman microscopic measurement of materials used on banknotes

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Circuits, Systems, Communications and Computers (CSCC), International Conference on

作者： Hana Tomášková Vladimír Vašek Department of electronic and measurements Faculty of Applied informatics Tomas Bata University in Zlin Zlín Czech Republic Department of automation and control engineering Faculty of Applied informatics Tomas Bata University in Zlin Zlín Czech Republic

ISBN: (纸本)9781665481878

The successful verification of the authenticity of banknotes, or the detection of counterfeits, is based on the combination of an effective measuring system and computer technology. In this paper, a modern diagnostic method Raman microscopy together with an exploratory tool for processing and interpreting multi-dimensional datasets, and cluster analysis, are used to study structural differences between paper and orange ink used on genuine banknotes. Six currencies of European countries were selected for this study: Croatian kuna, Czech crown, euro, Great British Pound, Polish zloty, and Swiss franc. Raman microscopy offers non-destructive, rapid analysis without any sample preparation and pre-processing, with the potential to recognize structural modification of substances, together with the advantages of optical microscopy. Cotton fibres, $\text{TiO}_{2}$ in two different modifications, and other additives are successfully identified within the spectra. The patterns found in mathematically processed Raman data, especially between the paper, indicate both, the similarities and differences across the various banknotes, even of the same currency. The results serve as a base of the spectral database for authenticity control of banknotes and classification of the materials used.

关键词： Optical fibers Optical microscopy Databases Statistical analysis Microscopy Process control Ink

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Feasibility of Comparing Constructive Spatial Processes in Real and Virtual Spaces Among School-Age Children: A Randomized Pilot Study

Feasibility of Comparing Constructive Spatial Processes in R...

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Cognitive Aspects of Virtual Reality (CVR), IEEE International Conference on

作者： Márk Agoston Pulay Dalma Geszten Vince Abosa Szakál Bertalan Forstner Dóra Szentándrasi Department of Ergonomics and Psychology Faculty of Economic and Social Sciences Budapest University of Technology and Economics Budapest Hungary Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary The Moholy-Nagy University of Art and Design Budapest Hungary

Nowadays new information and communication technologies (IT) directly influence teaching methods, practices and resources. The use of virtual reality (VR) technology in education enables new approaches that can enhance, guide, and stimulate students' interest in learning while allowing them to experience the subject and acquire sensory and intuitive cognition in a more personal and realistic environment. This research aims to answer the question: can constructive spatial activity with real materials in real space be replaced by virtual space and digital tools in terms of assessing stability and knowledge acquisition? This current pilot study aims to examine the feasibility of our research setup and analysis methods while children are asked to perform an intuitive creative process to construct a structure in real and digital space. We involved twelve school-age (8,47 years average) from an elementary school, and we randomly allocated them to group 1 (real space construction) and to group 2 (tablet application construction). We created a behavioral coding scheme for the widely used and validated Noldus Observer XT (version 15) video behavior analyzer software. The video analyses showed that the creation phases defined in the construction process appeared on both real space and in a virtual setting, confirming the assumption that the acquisition of knowledge and skills related to stability can also be phased. Based on our pilot research on a small sample, the chosen observation and research methodology is feasible. We predict that the real-space constructive task applied in the measurement can be replaced by a digital interface to experience stability.

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A MATLAB virtual laboratory to support learning of auto-tuning PID approaches

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IFAC-PapersOnLine 2024年第7期58卷 73-78页

作者： J.A. Rossiter A. Visioli S. Dormido R. Bars Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK Dipartimento di Ingegneria Meccanica e Industiale University of Brescia Italy Universidad Nacional de Educacion a Distancia Madrid Spain Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary

This paper presents a small number of MATLAB APPs and livescript files designed to help students both understand and implement PID tuning. The paper presents the thinking behind the use of MATLAB and the topic itself before then describing the proposed resources in detail. The resources split into files with detailed mathematical and coding background students can use for self-study and assignments, and a virtual laboratory which is more intuitive and interactive and useful for familiarisation with core concepts. The files were recently added to the control101 toolbox (Rossiter, 2023).

关键词： Control101 toolbox PID compensation virtual laboratories independent learning

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An efficent indoor positioning method using machine learning and multiple Wi-Fi acces points

An efficent indoor positioning method using machine learning...

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Measurement and Simulation (ATOMS), Advanced Topics on

作者： Rareş Dobre-Baron Teodor Petriţa Sorin Nanu Faculty of Electronics Telecomunications and Information Technology Politehnica University of Timişoara Timişoara Romania Department of Communications Politehnica University of Timişoara Timişoara Romania Department of Automation and Applied Informatics Politehnica University of Timişoara Timişoara Romania

ISBN: (数字)9798350358377

ISBN: (纸本)9798350358384

In order to respond to a challenge, we set up a simple but efficient indoor positioning system, using off the shelf Wi-Fi access points (AP). The challenges of level positioning are overcome with a machine learning (ML) algorithm, which takes as input measured levels of multiple APs. Our approach to the problem is trying to solve the voluntary localization of a person within their home or another familiar habitat, in need for medical assistance, and also in the case of an industrial robot within the assembly room of a factory.

关键词： Location awareness Portable computers Computer architecture Machine learning Position measurement Industrial robots Software Production facilities Software measurement Wireless fidelity

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

arXiv

引用

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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