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Detection of a Quasiperiodic Phenomenon of a Binary Star System Using Convolutional Neural Network

Intelligent automation & Soft Computing 2023年第9期37卷 2519-2535页

作者： Denis Benka Sabína Vasová Michal Kebísek Maximilián Strémy Institute of Applied Informatics Automation and MechatronicsFaculty of Materials Science and TechnologySlovak University of TechnologyTrnava91724Slovakia

Pattern recognition algorithms are commonly utilized to discover certain patterns,particularly in image-based *** study focuses on quasiperiodic oscillations(QPO)in celestial objects referred to as cataclysmic variables(CV).We are dealing with interestingly indistinct QPO signals,which we analyze using a power density spectrum(PDS).The confidence in detecting the latter using certain statistical approaches may come out with less significance than the *** work with real and simulated QPO data of a CV called MV *** primary statistical tool for determining confidence levels is sigma *** aforementioned CV has scientifically proven QPO existence,but as indicated by our analysis,the QPO ended up falling below 1-σ,and such QPOs are not noteworthy based on the former *** intend to propose and ultimately train a convolutional neural network(CNN)using two types of QPO data with varying amounts of training dataset *** aim to demonstrate the accuracy and viability of the classification using a CNN in comparison to sigma *** resulting detection rate of our algorithm is very plausible,thus proving the effectiveness of CNNs in this scientific area.

关键词： Convolutional neural network quasi-periodic oscillation cataclysmic variable simulation

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Nonlinear Identification of a Continuous Stirred-Tank Reactor using WSDP Models

Nonlinear Identification of a Continuous Stirred-Tank Reacto...

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11th International Conference on Control, automation and Systems (ICCAS)/Robot World Conference

作者： Nguyen-Vu Truong Intelligent Robotics and Automation Laboratory (IRAL) Institute of Applied Mechanics and Informatics Vietnam Academy of Science and Technology Viet Nam

ISBN: (纸本)9788993215038

This paper presents the application of Wavelet based State Dependent Parameter (WSDP) models to the identification of a Continuous Stirred-Tank Reactor (CSTR). Here, in order to characterize the process dynamics which is highly nonlinear and multi-variable dependent, 2-D WSDP model is used. The simulation results demonstrate the effectiveness and advantages of the identified model.

关键词： Tanks (containers)

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LQR and Pole Placement Controllers with Integral Action Design Technique and Performance Analysis for Control of Temperature Field in Continuous Casting Process 24

LQR and Pole Placement Controllers with Integral Action Desi...

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24th International Carpathian Control Conference, ICCC 2023

作者： Zarghoon, Sohaibullah Belavy, Cyril Solvak University of Technology Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Bratislava Slovakia

ISBN: (纸本)9798350310221

This paper presents the design of Linear Quadratic Regulator and Pole Placement controllers with integral action using MATLAB and Simulink for controlling the temperature field in the secondary cooling zone of a continuous casting process. The secondary cooling zone in continuous casting represents a distributed parameter system. During steel production, the type of steel produced changes continuously, necessitating a control system that can respond quickly and flexibly. We compared the performance of the Linear Quadratic Regulator and Pole Placement control techniques for the temperature field in the secondary cooling zone by analyzing the system's response. The simulation results demonstrate that the Linear Quadratic Regulator technique outperforms the Pole Placement technique for the specified system. © 2023 IEEE.

关键词： Continuous casting

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Prediction of Fluorescent Ki67 Staining in 3D Tumor Spheroids

Prediction of Fluorescent Ki67 Staining in 3D Tumor Spheroid...

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作者： Bruch, Roman Vitacolonna, Mario Rudolf, Rüdiger Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany Institute of Molecular and Cell Biology Mannheim University of Applied Sciences Mannheim Germany

3D cell culture models are important tools for the development and testing of new therapeutics. In combination with immunoassays and 3D confocal microscopy, crucial information like morphological or metabolic changes can be examined during drug testing. However, a common limitation of immunostainings is the number of dyes that can be imaged simultaneously, as overlaps in the spectral profiles of the different dyes may result in cross talk. We therefore present a 3D deep learning method, able to predict fluorescent stainings of specific antigens on the basis of a nuclei staining. Using the proliferation marker Ki67, we showed that the presented model was able to predict the Ki67 staining with a strong correlation to the real signal. Additional analysis showed, that the model was not relying on signal cross talk. This approach, based on staining of the cell nuclei and subsequent prediction of the target antigen, could reduce the number of parallel antigen stains to a minimum and incompatible staining panels could be circumvented in the future. © 2022 The Author(s), published by De Gruyter.

关键词： Forecasting

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Simulation and Control of a Continuously Cast Steel Billet in an Induction Furnace∗ 9

Simulation and Control of a Continuously Cast Steel Billet i...

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9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Zarghoon, Sohaibullah Bartalsky, Lukas Belavy, Cyril Institute of Automation Measurement and Applied Informatics Slovak University of Technology Faculty of Mechanical Engineering Bratislava Slovakia

ISBN: (纸本)9798350311402

This paper presents a solution to a problem that Khan Steel Company in Afghanistan encountered in their induction furnace. The motivation for deploying induction heating technology in the industry is outlined, including a description of the current situation. Basic approaches for managing this technology, critical to the industry's success, are also provided. The process of creating an induction heating model using the COMSOL Multiphysics environment is described, with emphasis placed on the importance of starting the machine and determining the system's dynamics once it is in production mode. Finally, an identification and control proposal based on the distributed parameter system is presented, followed by a demonstration of the proposed control system using simulation results. © 2023 IEEE.

关键词： Induction heating

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Dissolved ozone sensing in water and blood based on commercial screen-printed and BDD electrodes

Dissolved ozone sensing in water and blood based on commerci...

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2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Petani, Lisa Llupa, Lea Peng, Zhen Ogata, Genki Koker, Liane Gengenbach, Ulrich Einaga, Yasuaki Pylatiuk, Christian Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Karlsruhe Germany Keio University Department of Chemistry Yokohama Japan

ISBN: (纸本)9798350300260

Dissolved ozone sensing in water is crucial for a variety of applications, including water treatment, food processing, and medical therapies, as ozone is widely used as an oxidising agent in these processes. Furthermore, dissolved ozone sensing in blood is important for medical therapies. We present a novel dissolved ozone sensor for measurement in water, based on commercially available screen-printed electrodes covered with different porous membranes made of polytetrafluoroethylene (PTFE) and non porous membranes made of polydimethylsiloxane (PDMS). With PTFE, a root mean squared error (RMSE), which is the difference between the novel sensor and the reference spectrometer, of 3.62 mg l-1 can be achieved, while with PDMS a RMSE of 6.34 mg l-1 is obtained. Also, we investigated the measurement of dissolved ozone in blood with membrane-free and electrolyte-free boron-doped diamond (BDD) electrodes. The proposed dissolved ozone sensors offer a promising solution for inexpensive monitoring of dissolved ozone concentrations in water and blood with a compact design. © 2023 IEEE.

关键词： amperometry disposable electrochemistry low-cost medical applications ozone therapy sensors water treatment

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Technical sound event classification applying recurrent and convolutional neural networks 1

Technical sound event classification applying recurrent and ...

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1st International Conference on Deep Learning Theory and Applications, DeLTA 2020

作者： Rieder, Constantin Germann, Markus Mezger, Samuel Scherer, Klaus Peter Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen Germany

ISBN: (纸本)9789897584411

In many intelligent technical assistance systems (especially diagnostics), the sound classification is a significant and useful input for intelligent diagnostics. A high performance classification of the heterogeneous sounds of any mechanical components can support the diagnostic experts with a lot of information. Classical pattern recognition methods fail because of the complex features and the heterogeneous state noise. Because of no explicit human knowledge about the characteristic representation of the classes, classical feature generation is impossible. A new approach by generation of a concept for neural networks and realization by especially convolutional networks shows the power of technical sound classification methods. After the concept finding a parametrized network model is devised and realized. First results show the power of the RNNs and CNNs. Dependent on the parametrized configuration of the net architecture and the training sets an enhancement of the sound event classification is possible. © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved

关键词： Recurrent neural networks

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Tracking of non-stationary biological signals with utilizing of adaptive filtering method 20

Tracking of non-stationary biological signals with utilizing...

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20th International Conference on Process Control, PC 2015

作者： Honek, Marek Malinovský, Ľudovít Ondrejkovič, Karol Rohaľ-Ilkiv, Boris Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9781467366274

This paper presents an approach intended for tracking of biological non-stationary signals. The proposed approach utilizes a Kalman filter autoregressive model together with a method for estimation of covariance matrices of the uncorrelated process noise and measurement noise. The method was tested in simulations, where the ability of tracking of a class of time varying autoregressive processes was the subject of our interest. The obtained results are promising in the meaning that the suggested algorithm is suitable to track the time varying autoregressive processes with sufficient accuracy. © 2015 IEEE.

关键词： Adaptive filtering

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Light-Field Camera Based Spatial Multiple Small Particle Tracking with Post-processing

Light-Field Camera Based Spatial Multiple Small Particle Tra...

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International Symposium on automation, Mechanical and Design Engineering, SAMDE 2021

作者： Zhang, Miao Matthes, Jörg Aleksandrov, Krasimir Gehrmann, Hans-Joachim Vogelbacher, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Institute for Technical Chemistry Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9783031099083

Multi-object detection and tracking is one of the most significant tasks in computer vision, which has been widely applied in various fields, such as biomedicine, automatic driving, and video surveillance. In our project, we aim to investigate the flight behavior of different small refuse-derived fuel particles (e.g., plastic, wood, paper, etc.) with sizes around 5 to 30 mm, which are blown into a combustion chamber (rotary kiln) via a lance, by detecting and tracking the particles. By utilizing a calibrated light-field camera, both 2D gray value images and 3D information, including the depth of the scene, are available for investigation. To obtain particle trajectories, accurate temporal localization of the particles is necessary. Thus, we perform an approach combining a 2D detection method and a 3D clustering method for precise detection of the particles at first. Subsequently, the temporal 2D particle localizations are associated into tracklets based on the Kalman filter state estimator and the global nearest neighbor algorithm. Owing to the wrong and incomplete tracklets caused by several inaccurate detections, we present a post-processing method to enhance the tracking performance in the paper. Finally, the optimized 2D particle trajectories are converted into 3D trajectories, and these obtained 3D particle trajectories are analyzed by a polynomial regression for further analysis of the particle flight behavior. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cameras

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Classification of Bundle Branch Blocks with QRS Templates Extracted from 12-lead ECGs

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Current Directions in Biomedical Engineering 2021年第2期7卷 582-585页

作者： Welle, Hannes Nagel, Claudia Loewe, Axel Mikut, Ralf Dössel, Olaf Institute of Biomedical Engineering KIT Fritz-Haber-Weg 1 Karlsruhe Germany Institute for Automation and Applied Informatics KIT Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen Germany

Being non-invasive, cheap and widely available, the 12-lead electrocardiogram (ECG) is a standard method to assess cardiac function. Still, its reliable interpretation requires specialized knowledge and experience, rendering a second opinion valuable. We evaluated the performance of machine learning based classification of 11,705 healthy and bundle branch block 12-lead ECGs from 3 open databases. For each lead of the ECG signal, a representative QRS-complex template was extracted automatically. Principal component analysis (PCA) was applied to the concatenated, normalized and rescaled QRS signals to reduce their dimensionality. Multilayer perceptron and support-vector machine classifiers were trained using the principal components of weighted and non-weighted QRS template signals as input data. Classifiers achieved F1 scores between 0.92 and 0.96 on the test set for different input configurations. Anomaly based weighting slightly improved the performance of the classifiers. Neither class-wise PCA for feature extraction nor adding information on sex, gender and electrical heart axis to the input data yielded considerable improvement of the F1 scores. The achieved classification accuracy is similar to deep learning classifier performances and should generalize robustly to other ECG datasets. Our results suggest that this simple and well interpretable approach based on morphological signal characteristics is suitable for automatically and non-invasively identifying bundle branch block pathologies in clinical or smart electronics contexts. © 2021 by Walter de Gruyter Berlin/Boston.

关键词： Electrocardiograms

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