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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Dominika Świerczyska Tomasz Stach Mariusz Pelc Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole PL

While willing to implement any self-learning mechanisms, the decision making process must be partially supported by recalling some previous decisions rather than triggering the reasoning process every time a decision is needed. For relatively simple systems storing previous decisions does not need any sophisticated mechanism but for some complex systems, when there are multiple decisions and many environmental information to be analysed while making those decisions, the whole context information (information about the environment state and accompanying decision) may need to be supported on one hand, by a database system (providing efficient search mechanisms) and on the other hand, by a cache-like system that would even improve decision making process by providing quick access mechanism in the most typical situations. The aim of this paper is to propose a framework for benchmarking real cache management algorithms within embedded systems.

关键词： Decision making Benchmark testing Databases Real-time systems Embedded systems Electrical engineering Electronic mail

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Building Electrical Load Forecasting through Neural Network Models with Exogenous Inputs

Building Electrical Load Forecasting through Neural Network ...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Cristina Nichiforov Grigore Stamatescu Iulia Stamatescu Ioana Făgărăşan Sergiu Stelian Iliescu University Politehnica of Bucharest Bucharest Romania Department of Automatic Control and Industrial Informatics University Politehnica of Bucharest Romania Institute of Technical Informatics Graz University of Technology Austria

As buildings become key actors in the economic and sustainable operation of future electrical grids and smart cities, reliable models which capture the underlying electrical energy consumption become an important factor for robust control algorithms. Current ubiquitous field devices supported by complex data infrastructures allow generation, storage and online analysis of large quantities of data for deriving usable black-box models of building energy patterns. The paper presents an approach to model the energy consumption of medium and large sized buildings using Non-linear Autoregressive Neural Networks with eXogenous Input (NARX). We show that the chosen network architectures offers good performance for time series prediction from historical values and external input signals such as outdoor temperature in comparison to a baseline approach. Model evaluation and validation are carried out on public dataset for replicable research outcomes.

关键词： Buildings Load modeling Predictive models Computational modeling Data models Forecasting Load forecasting

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Development of a Decision Support Tool for Intelligent Manufacturing using Classification and Correlation Analysis

Development of a Decision Support Tool for Intelligent Manuf...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Dariusz Król Jan Skowroński Maciej Zareba Krzysztof Bartecki Department of Information Systems Faculty of Computer Science and Management Wrocław University of Science and Technology Poland Legnicka 55F 53–203 Wrocław Wrocław University of Science and Technology Poland DSR Legnicka 55F 53—203 Wrocław Poland Institute of Automatic Control Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Poland

The development of the Production Unit Performance Management Tool (PUPMT), a monitoring and diagnostic tool to select basic signals that have a significant impact on output KPIs, is based on a hierarchical analysis of key performance indicators presented in the ISO 22400 standard. The growing number of quantified signals, such as ambient temperature or even the frequency of vibrations makes decision support tools more intelligent. Moreover, they also include predictive analysis in addition to online presentation of the current state of resources. PUPMT tool allows identifying key events that have a significant impact on current or future benefit in production output. It also allows what-if type analysis, running the simulation of the impact of the proposed changes, and the results of this simulation depend on the effects of similar changes that occurred in the past in a given smart manufacturing environment. Thanks to the automatic identification of potential dependencies, the proposed solution adapts to the specifics of a given environment or even a selected production unit. The paper describes the most important methods featured in the tool. Specifically, it considers a signal classification method, a signal correlation analysis and selection of key factors affecting the efficiency of the production process. In order to verify the methods various tests were carried out to calculate and control of OEE index on 20 production units. Finally, we conclude current results and future research directions.

关键词： Conferences Cybernetics

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Application of Cognitive Changes Markers for Diagnostics’ Purposes and in Neurofeedback Therapy

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IFAC-PapersOnLine 2019年第27期52卷 520-523页

作者： Magda Zolubak Mariusz Pelc Michal Podpora Wojciech Chlewicki Katarzyna Cichon Aleksandra Kawala-Sterniuk Opole University of Technology - Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland West Pomeranian University of Technology in Szczecin - Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland University of Greenwich - Department of Computing and Information Systems - Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK

Thanks to the automation of diagnostic processes based on the EEG signal and the creation of classifications of various attention disorders based on the analysis of the EEG signals (as diagnostic markers) - it may be possible to refer patients to appropriate specialists and provide them with appropriate neurofeedback-based treatment. The marker method proposed by the authors of the hereof paper is based on analysis of the EEG, which signal can be widely use in screening diagnostics. The proposed solution in this work may be used for neurofeedback or Brain Computer Interfaces (BCI). In this paper the authors presented implementation of markers for the purpose of analysis of some memory disorders and short-time attention disorder. The study is still in progress. Presented results have initial-study character.

关键词： EEG neurofeedback BCI algoritms

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Challenges in differentiating between attention disorders based on EEG recordings in neurofeedback therapy

Challenges in differentiating between attention disorders ba...

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Applications of Electromagnetics in Modern Techniques and Medicine (PTZE)

作者： Żołubak Magda Pelc Mariusz Kawala-Janik Aleksandra Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computing and Information Systems University of Greenwitch Greenwitch England

The aim of this article is to show problems with the analysis of various cognitive disorders in the registered EEG signal and the effects of the neurofeedback therapy. Most of the disorders tested in ICD-10 have electroencephalographic readings associated with Beta bands and slow waves. All problems with attention deficit have similar records in the EEG signal and similar training protocols are used in their therapy and the results of the therapy are visible in more than 10 training sessions.

关键词： Electroencephalography Training Neurofeedback Medical treatment Protocols Cancer Pediatrics

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Behavioural Approach to Network Anomaly Detection for Resource-Constrained System – Presentation of the Novel Solution – Preliminary Study

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IFAC-PapersOnLine 2019年第27期52卷 121-126页

作者： Mariusz Pelc Dawid Galus Magda Zolubak Stepan Ozana Wojciech Chlewicki Katarzyna Cichon Michal Podpora Aleksandra Kawala-Sterniuk Opole University of Technology – Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland University of Greenwich – Department of Computing and Information Systems – Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK VSB – Technical University Ostrava – FEECS Department of Cybernetics and Biomedical Engineering Ostrava Czech Republic West Pomeranian University of Technology in Szczecin – Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland

In this paper some preliminary results of network anomaly detection for resource-constrained systems have been presented. All described algorithms are embedded into a three-tier system application. The presented solution is a response to nowadays trends in computer/network security domain that indicate gradual shifting from signature-based anomaly detection typically based on some selected statistical measures toward systems that are based on behavioural analysis of computer systems and/or networks. The presented system requirements, explain relevant terminology as well as we include some selected results and their analysis. The solution is potentially destined for very resource-constrained systems (IoT specifically), all tests were carried out in an example network to additionally analyse their effect of the presented approach on the computer resources.

关键词： Network Anomaly Detection Behavioural Analysis Internet of Things

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Single trial ERP amplitudes reveal the time course of acquiring representations of novel faces in individual participants

arXiv

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arXiv 2020年

作者： Sommer, Werner Stapor, Katarzyna Kończak, Grzegorz Kotowski, Krzysztof Fabian, Piotr Ochab, Jeremi Bereś, Anna Ślusarczyk, Grażyna Humboldt-University at Berlin Department of Psychology Germany Silesian University of Technology Institute of Computer Science Gliwice Poland University of Economics in Katowice Department of Statistics Econometrics and Mathematics Poland Silesian University of Technology Department of Applied Informatics Gliwice Poland Silesian University of Technology Department of Algorithmics and Software Gliwice Poland Jagiellonian University Department of Theory of Complex Systems Krakow Poland Jagiellonian University Department of Cognitive Neuroscience and Neuroergonomics Krakow Poland Jagiellonian University Department of Design and Computer Graphics Krakow Poland Institut für Psychologie Humboldt-Universität zu Berlin Rudower Chaussee 18 Berlin12489 Germany Faculty of Automatic Control Electronics and Computer Science Department of Applied Informatics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

The neural correlates of face individuation – the acquisition of memory representations for novel faces – have been studied only in coarse detail and disregarding individual differences between learners. In their seminal study, (Tanaka, Curran, Porterfield, & Collins, 2006) required the identification of a particular novel face across 70 trials and found that the N250 component in the ERP became more negative from the first to the second half of the experiment, where it reached a similar amplitude as a well-known face. We were unable to directly replicate this finding in our study when we used the original spilt of trials. However, when we applied a different split of trials we observed very similar changes in N250 amplitude. Then, we developed and applied a new two-step explorative-confirmative non-parametric method based on permutation testing to determine the time course of face individuation in individual participants based on single trial N250 amplitudes. We show that the assumption of a steep initial increase of N250 amplitude across multiple presentations of the target face, followed by a plateau, yields plausible results in fitting linear trends for most participants. The transition point from initial acquisition to the plateau phase differed strongly between participants and tended to be earlier when performance in target face recognition was better. Hence, face individuation may be accounted for by a biphasic process of early, fast acquisition, followed by a slower, asymptotic consolidation or maintenance phase. The current approach might be fruitfully applied to further investigations into face individuation and their neural correlates. © 2020, CC BY-NC-ND.

关键词： Face recognition

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Artificial Neural Network Capability for Human Being Identification Based on ECG

Artificial Neural Network Capability for Human Being Identif...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Volodymyr Khoma Mariusz Pelc Yuriy Khoma Institute of Automatics Opole University of Technology Opole Poland Institute of Informatics Opole University of Technology Opole Poland Institute of Computer Technology Automatic and Metrology National University Lviv Polytechnic Lviv Ukraine

In this paper we presented a method for human being identification based on ECG supported by Artificial Neural Networks. We also propose structure of such identification system with description of its functional elements. To provide an insight into efficiency of the proposed methodology we compare it to alternative approaches based on Logistic Regression and K-Nearest Neighbour. All experiments were performed on several representative data (existing ECG records of real patients).

关键词： Electrocardiography Artificial neural networks Biometrics (access control) Databases Classification algorithms Heart beat Logistics

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Impulsive noise removal in color digital images based on the concept of digital paths 13

Impulsive noise removal in color digital images based on the...

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13th International Conference on Computer Science and Education, ICCSE 2018

作者： Smolka, Bogdan Malinski, Lukasz Institute of Automatic Control Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Division of Industrial Informatics Silesian University of Technology Krasinskiego 8 Katowice40-019 Poland

ISBN: (纸本)9781538654958

In the paper a fast technique of impulsive noise suppression in color images is described. The proposed method is utilizing the concept of digital paths which link the central pixel of a filtering window with its boundary. Each path is assigned a cost and the minimum one is treated as a measure of the central pixel corruption. If the minimum cost of a link between the window center and its boundary is high, then the central pixel is treated as corrupted. The filter output is a weighted average of a pixel and its robust estimate, in which the minimum cost is used for the creation of a soft switching rule for the filter output. The performed experiments revealed excellent properties of the novel approach, especially in case of highly distorted images. The computational complexity of the proposed technique is low and it can be used in real time applications. © 2018 IEEE.

关键词： Pixels

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A norm-based approach to the minimum-energy multivariable perfect control design

A norm-based approach to the minimum-energy multivariable pe...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Wojciech P. Hunek Dariusz Pączko Tomasz Feliks Marek Krok Institute of Control Engineering Institute of Mathematics and Applied Informatics Opole University of Technology Opole Poland

In this paper a minimum-energy problem of perfect control algorithm dedicated to LTI MIMO plants described in the discrete-time state-space framework is shown. Following the new facts concerning the above-mentioned issue, a new solution based on the mathematical norms utilizing some generalized inverse formulas is given in this paper. The simulation instance confirms the correctness of a new intriguing method, which certainly leads to the final proof of whole, undiscovered yet, modern control theory.

关键词： MIMO communication Estimation Linear systems control design Mathematical model control engineering

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