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Pipeline Leakage Detection via Extreme Seeking Entropy 1

7th Computational Methods in Systems and Software, CoMeSySo 2023

作者： Steinbach, Jakub Seiner, Jakub Vrba, Jan Department of Computing and Control Engineering University of Chemistry and Technology in Prague Technická 1905/5 Praha 6 Czech Republic

ISBN: (数字)9783031535499

ISBN: (纸本)9783031535482

In this article, we present a case study of pipeline leakage detection via an adaptive novelty detection algorithm. The detection is based on an affine projection filter applied to a sound recording of the pipeline outlet. Adaptive weight increments of the filter are evaluated by the Extreme Seeking Entropy algorithm to estimate the amount of novelty in data. The suitability of the proposed approach is presented in three case studies where the leakage was simulated in the degassing process model by increasing the discharge flow. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adaptive filtering

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Analysis of Mimetic Muscle Rehabilitation: Multi-platform Facemarks Detection 1

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6th Computational Methods in Systems and Software, CoMeSySo 2022

作者： Tomeš, Jakub Vácha, Ondřej Štícha, Karel Kohout, Jan Mareš, Jan Department of Computing and Control Engineering University of Chemistry and Technology in Prague Technická 1905/5 Praha 616628 Czech Republic

ISBN: (数字)9783031214356

ISBN: (纸本)9783031214349

The paper deals with frameworks for the description of mimetic muscle rehabilitation of patients with facial palsy. Detection models on different platforms (Android, iOS, Windows) are compared: ARCore Augmented Faces, ARKit Face Tracking, and MediaPipe Face Mesh. They can provide data for further quantitative analysis of mimetic muscle dysfunction. The real-time nature of these facemark detectors allows for direct feedback in the form of automatic mimetic muscle detection to the patient during the rehabilitation session. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： ARCore ARKit Facemarks Facial palsy MediaPipe Mimetic exercises Rehabilitation

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Voice Recording Setup in Clinical Practice 6th

Voice Recording Setup in Clinical Practice

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6th Computational Methods in Systems and Software, CoMeSySo 2022

作者： Steinbach, Jakub Vrba, Jan Urbániová, Zuzana Department of Computing and Control Engineering University of Chemistry and Technology in Prague Technická 1905/5 166 28 Praha 6 Prague Czech Republic 3rd Faculty of Medicine Department of Otorhinolaryngology University Hospital Královské Vinohrady Charles University Staré Město Czech Republic

ISBN: (纸本)9783031214349

In this article, we introduce a novel voice recording setup in clinical practice. The aim of this setup is to take recordings of patients who underwent a surgery on vocal cords. The setup utilizes only one microphone for recording so no sound level meter measurement and calibration are required, as we want to emulate conditions where patients are taking their recording at home using smartphones or headsets. We also introduce a software for clinical practice that allows physicians to manage simple patient information and take recordings of their voice. Lastly, we propose the sequence of sounds and sentences that patients should say. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Hardware Otorhinolaryngology Voice cords Voice processing Voice recording

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3D Face Capture for Rehabilitation Progress Assessment After Brain Surgery 1

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4th Computational Methods in Systems and Software, CoMeSySo 2020

作者： Tomeš, Jakub Kohout, Jan Mareš, Jan Department of Computing and Control Engineering University of Chemistry and Technology in Prague Technická 1905/5 166 28 Praha 6 Prague Czech Republic

ISBN: (数字)9783030633226

ISBN: (纸本)9783030633219

The aim of this article is to show how modern sensors can be used in rehabilitation monitoring after a specific brain surgery that affects the facial muscles. Rehabilitation takes several months, it is important for both doctors and patients to be able to monitor progress quantitatively. To evaluate a patient’s facial disorders, the stereo-vision camera is used to detect and capture precise facial movements, which the subject is asked to perform. From these videos, specific patterns can be extracted for the rehabilitation process description. In this paper, we focused on a 3D analysis app for mobile phones. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Stereo image processing

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Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A Survey

arXiv

引用

arXiv 2022年

作者： Bilik, Simon Zemcik, Tomas Kratochvila, Lukas Ricanek, Dominik Richter, Miloslav Zambanini, Sebastian Horak, Karel Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Technická 3058/10 Brno61600 Czech Republic Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Yliopistonkatu 34 Lappeenranta53850 Finland Computer Vision Lab Institute of Visual Computing & Human-Centered Technology Faculty of Informatics TU Wien Favoritenstr. 9/193-1 ViennaA-1040 Austria

Wide use and availability of machine learning and computer vision techniques allows development of relatively complex monitoring systems in many domains. Besides the traditional industrial domain, new applications appears also in biology and agriculture, where they may be used to detect infections, parasites and weeds, but also for automated monitoring and early warning systems. This goes in concordance with the introduction of the easily accessible hardware and development kits such as the Arduino, or RaspberryPi families. In this paper, we survey 50 papers focusing on the methods of automated beehive monitoring using computer vision techniques. Particularly on the pollen and Varroa mite detection together with the bee traffic monitoring. Such systems could also be used for monitoring of honeybee colonies and for the inspection of their health state, which could potentially identify dangerous states before the situation is critical, or to better plan periodic bee colony inspections and therefore save significant costs. Further on, we also include analysis of the research trends in this application field and we outline the possible directions of new development. Our paper is also aimed at veterinary and apidology professionals and experts, who may not be familiar with machine learning to introduce them to its capabilities, hence each family of techniques is prefaced by a brief theoretical introduction and motivation related to its base method. We hope that this paper will inspire other scientists to use machine learning techniques for other applications in beehive monitoring. © 2022, CC BY.

关键词： Computer vision

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Robot-based image analysis for evaluating rehabilitation after brain surgery

Robot-based image analysis for evaluating rehabilitation aft...

引用

作者： Kohout, Jan Crha, Jan Trnková, Kateřina Štícha, Karel Mareš, Jan Chovanec, Martin University of Chemistry and Technology in Prague Department of Computing and Control Engineering Technická 1905/5 Praha 6 166 28 Czech Republic Faculty Hospital Královské Vinohrady Department of Otorhinolaryngology Šrobárova 1150/50 Praha 10 100 34 Czech Republic

After certain types of brain surgery, patients are often affected by changes in both their dynamic balance and facial disorder. Because rehabilitation takes several months, it is important that both doctors and patients are able to monitor progress quantitatively. At present, such quantification is subjective and highly dependent on the doctor’s opinion. Thus, we here investigate the use of robot-based image analysis for measuring rehabilitation. To evaluate a patient’s dynamic balance, we developed a mobile robotic platform that uses a stereovision camera (MS Kinect) to capture a video of the subject walking along a hospital corridor. To evaluate a patient’s facial disorders, the same camera is used in a static mode to detect and capture precise facial movements that the subject is asked to perform. From these videos, specific patterns can be extracted for rehabilitation process description. © 2018, Brno University of Technology. All rights reserved.

关键词： Computer vision

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Multichannel time-series modelling and Prediction by wavelet networks 8

Multichannel time-series modelling and Prediction by wavelet...

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8th European Signal Processing Conference, EUSIPCO 1996

作者： Prochazka, Ales Smith, Jonathan Department of Computing and Control Engineering Prague University of Chemical Technology Technicka 1905 Prague 616628 Czech Republic School of Engineering Systems and Design South Bank University 103 Borough Road LondonSE1OAA United Kingdom

Multichannel time-series result from observations of a given engineering, biomedical, econometric or environ mental variable taken at different locations. Processing this type of signal presents problems associated with its extrapolation in given space ranges and its possible prediction. This paper presents a comparison of sea sonal AH modelling of such signals and the application of wavelet networks to the system identification and pre diction of a particular signal. The choice of wavelet functions and the optimization of their coefficients is discussed as well. Each method suggested in the paper is verified for simulated signals at first and then used for the analysis of real signals, including the observa tion of air pollution. All algorithms are written in the MATLAB environment. © 2015 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Time series

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The MS kinect image and depth sensors use for gait features detection

The MS kinect image and depth sensors use for gait features ...

引用

作者： Prochazka, A. Schatz, M. Tupa, O. Yadollahi, M. Vysata, O. Walls, M. Institute of Chemical Technology Dept of Computing and Control Engineering Technická 5 Prague 6166 28 Czech Republic Charles University Department of Neurology Sokolská 581 Hradec Králové500 05 Czech Republic

ISBN: (纸本)9781479957514

Movement disorders, problems with motion and gait stability related to aging form a very intensively studied research area. The paper presents a contribution to these topics through the use of data acquired by motion sensors and namely image and depth sensors of the MS Kinect. While video sequences obtained by complex camera systems can be used for the precise gait features evaluation, it is possible to use much cheaper devices for diagnostic purposes accurate enough in many cases. The experimental part of the study presents video sequences and depth sensors data acquisition for 18 individuals with the Parkinson's disease and 18 healthy age-matched controls using the proposed graphical user interface in the clinical environment. Results presented include the estimation of gait features to distinguish gait disorders and to classify individuals in the early stage of possible serious diseases. The accuracy achieved was higher then 90 % for given sets of individuals. © 2014 IEEE.

关键词： Graphical user interfaces

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A structured mathematical model of PHA biopolymer production process

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Archives of control Sciences 2013年第3期23卷 351-360页

作者： Finkeová, Jana Hrnčiřík, Pavel Mareš, Jan Vovsík, Jaroslav Hudeček, Ondřej Náhlík, Jan Department of Computing and Control Engineering Institute of Chemical Technology Prague Technická 5 166 28 Prague 6 Czech Republic

The paper describes a mathematical model of PHA biopolymer production process by Pseudomonas putida KT2442 where the octanoic acid is used as a substrate. The process is modeled using mass balances for fed-batch cultivation. Proper fitting to experimental data is obtained by identification of the model parameters. The model exhibits good agreement with experiments and its possible application for control is considered in the paper.

关键词： Bacteria

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A robust approach to using of the redundant information in the temperature calibration

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AIP Conference Proceedings 2013年第1期1552卷 498-503页

作者： R. Strnad L. Kňazovická M. Šindelář J. Kukal Czech Metrology Institute Okružní 31 638 00 Brno Czech Republic Czech Metrology Institute Okružní 31 638 00 Brno Czech Republic and Department of Computing and Control Engineering Institute of Chemical Technology Prague Technická 5 166 28 Prague 6 Czech Republic Department of Computing and Control Engineering Institute of Chemical Technology Prague Technická 5 166 28 Prague 6 Czech Republic

In the calibration laboratories are used standard procedures for calculating of the calibration model coefficients based on well described standards (EN 60751, ITS-90, EN 60584, etc.). In practice, sensors are mostly calibrated in more points and redundant information is used as a validation of the model. This paper will present the influence of including all measured points with respect to their uncertainties to the measured models using standard weighted least square methods. A special case with regards of the different level of the uncertainty of the measured points in case of the robust approach will be discussed. This will go to the different minimization criteria and different uncertainty propagation methodology. This approach also will eliminate of the influence of the outline measurements in the calibration. In practical part will be three cases of this approach presented, namely industrial calibration according to the standard EN 60751, SPRT according to the ITS-90 and thermocouple according to the standard EN 60584.

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