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6th Computational Methods in Systems and Software, CoMeSySo 2022

作者： Jicinsky, Pavel Mares, Jan Department of Process Control Faculty of Electrical Engineering and Informatics University of Pardubice Pardubice Czech Republic

ISBN: (纸本)9783031214349

Rehabilitation in orthopedics is one of the most important processes that influence the patient’s quality of life. In today’s practice, the orthopedic assessments still depend mainly on subjective view of physician. To further objectify the results, a wearable electronic device was developed based on inertial sensors. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： IMU Motion analysis Orthopedics Signal acquisition and processing

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ELCD-NSC2: a novel early lung cancer detection and non-small cell classification framework

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Neural Computing and Applications 2024年第24期36卷 15149-15164页

作者： Helaly, Hadeer A. Badawy, Mahmoud El-Gendy, Eman M. Haikal, Amira Y. Electrical Engineering Department Faculty of Engineering Damietta University Damietta Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Department of Computer Science and Informatics Taibah University Medina Saudi Arabia

The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the lung cancer diagnosis, the higher the survival rate. For radiologists, recognizing malignant lung nodules from computed tomography (CT) scans is a challenging and time-consuming process. As a result, computer-aided diagnosis (CAD) systems have been suggested to alleviate these burdens. Deep-learning approaches have demonstrated remarkable results in recent years, surpassing traditional methods in different fields. Researchers are currently experimenting with several deep-learning strategies to increase the effectiveness of CAD systems in lung cancer detection with CT. This work proposes a deep-learning framework for detecting and diagnosing lung cancer. The proposed framework used recent deep-learning techniques in all its layers. The autoencoder technique structure is tuned and used in the preprocessing stage to denoise and reconstruct the medical lung cancer dataset. Besides, it depends on the transfer learning pre-trained models to make multi-classification among different lung cancer cases such as benign, adenocarcinoma, and squamous cell carcinoma. The proposed model provides high performance while recognizing and differentiating between two types of datasets, including biopsy and CT scans. The Cancer Imaging Archive and Kaggle datasets are utilized to train and test the proposed model. The empirical results show that the proposed framework performs well according to various performance metrics. According to accuracy, precision, recall, F1-score, and AUC metrics, it achieves 99.60, 99.61, 99.62, 99.70, and 99.75%, respectively. Also, it depicts 0.0028, 0.0026, and 0.0507 in mean absolute error, mean squared error, and root mean square error metrics. Furthermore, it helps physicians effectively diagnose lung cancer in its early stages and allows spe

关键词： Image classification

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Triple Parallel LSTM Networks for Classifying the Gait Disorders Using Kinect Camera and Robot Platform During the Clinical Examination

Triple Parallel LSTM Networks for Classifying the Gait Disor...

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2023 International Conference on electrical, Computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Shayestegan, Mohsen Zalabsky, Tomas Mareš, Jan University of Pardubice Pardubice Faculty of Electrical Engineering and Informatics Czech Republic Research Center University of Pardubice Pardubice Faculty of Electrical Engineering and Informatics Czech Republic University of Pardubice Pardubice Faculty of Electrical Engineering and Informatics Department of Process Control Czech Republic

ISBN: (纸本)9798350322972

This paper presents a new methodology for the data processing and classification method for gait disorders, which is observed with a Kinect camera. The study of gait and motion stability in gait disorders is one of the most interesting research areas in the field. The patient and the physician must monitor the progress of the rehabilitation process before and after surgery to obtain an objective view of the rehabilitation process. In this study, the patient is scanned with the Kinect camera placed on a mobile robotic platform. For feature extraction and feature analysis, the exercises (three walking exercises) frames are collected and saved in data folders. This study uses 84 measurements of 37 patients with complex observations based on the physician's opinion in a clinical setting to address classification problems. In the analysis of gait disorders, motion data play an essential role. Furthermore, it reduces the selection of helpful body features for assessing gait disorders. The proposed system uses a key-point detector that computes body landmarks and classifies gait disorders using triple-parallel long short-term memory (LSTM) networks. The present study demonstrates the success of the method in classification evaluation when combined with the state-of-the-art pose estimation method. Around 81 percent accuracy was achieved for given sets of individuals using velocity-based, angle-based, and position-based features. © 2023 IEEE.

关键词： Long short-term memory

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Path Planning for Data Collection Multiagent System with Priority and Moving Nodes in a Sensing Field with Obstacles

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2024年第3期68卷 309-318页

作者： Szénási, Sára Harmati, István Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok körútja 2 Budapest1117 Hungary

Nowadays there is a more and more common need for one-off data collection in a specified area. For example, in case of searching for the survivors of disasters or wars, or for skiers who get into trouble. The simplest way of collecting such data is using wireless sensor network (WSN). However, data transmission within the network uses great amount of energy that may significantly reduce the lifetime and operation time of the battery-operated sensors. For this reason, the data transfer between the given sensor nodes is carried out by robots. In order to minimize the latency of data collection, it is possible to use cooperating robots. It frequently occurs that one of the nodes requires more urgent visit than the other ones, for example, the serious injuries require urgent medical attendance. The sensor nodes can also be moved to collect more usable data in a larger field. To solve this, path planning for data collection from priority and moving nodes are also presented here. The algorithm developed here to perform the one-off data collection operates so that the agents start from preliminary determined or random points and then visit all the sensor nodes, download the data from these nodes and after this arrive at a designated point where they upload the collected information. The goal here is the minimization of cost that include not only the walk-through time but also the consequences of the late visit of the higher priority nodes. The optimization is solved using the ant colony optimization. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Motion planning

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Algorithmic Decomposition of Railway Objects for Distributed Interlocking System

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica electrical engineering and Computer Science 2024年第4期68卷 319-326页

作者： Arató, Péter Markovits, Tibor Gergely Rácz, György Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok krt. 2. BudapestH-1117 Hungary

Railway interlocking systems can be implemented as distributed systems, where each part of a station is handled by a separate logical unit. The logical units of such systems form a network and communicate by interchanging messages. Such distributed architectures are well known in large industrial control systems. There are several design practices and also algorithmic task partitioning methods that are applicable in distributed control systems. Some of such methods can also be adapted in designing of railway interlocking systems as well. In the case of such systems, the communication time between components must be kept low. Namely each separate controller in a given route must be able to exchange their internal state within a limited time in order to permit the train movement authorization. This limitation could cause high traffic load, if every logical unit would be interconnected with each other. Therefore, the main goal of the minimization is to reduce the number of connections between logical units. This can achieved by distributing and assigning the topological railway objects to certain logical units. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Distributed parameter control systems

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Robust Trajectory Tracking control of a Differentially Flat Overhead Crane Using Sliding Mode

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2024年第2期68卷 213-221页

作者： Finta, Barnabás Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics University Műegyetem rkp. 3. BudapestH-1111 Hungary

The control of overhead cranes is a benchmark problem, since it is an underactuated mechanism and its mathematical model is nonlinear. During operation the mass of the load is unknown, representing an uncertainty in the inertial parameters, which requires robustness of the controlled system. Our paper proposes a novel robust control method, that combines the differentially flat property of the dynamics with the robustness of the sliding mode control. The sliding surface is constructed to ensure the tracking of the configuration variables whose accelerations is calculated using the flatness property of the dynamic model. This formulation also allows achieving the matching conditions of the parameter uncertainties. Considering a simplified overhead crane model where the load motion is restricted in a vertical plane, two sliding surfaces are defined for the rope angle and rope length, since the cart position can be calculated from the previous two. The suggested control method is successfully validated in simulations as well as using a reduced-size overhead crane. For the real crane, the rope angle was estimated by utilizing the dynamical model, which uses the estimated cart acceleration. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Acceleration

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Stability and bifurcation analysis of delayed tri-trophic food chain model in poisoned environment with fear effect and additional food

Stability and bifurcation analysis of delayed tri-trophic fo...

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作者： Ramasamy, Sivasamy Banjerdpongchai, David Park, PooGyeon Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Electrical Engineering Pohang University of Science and Technology Pohang Korea Republic of

One of the most important goals of theoretical ecologists is to find a strategy for controlling the chaos in ecological models to maintain healthy ecosystems. We investigate the influence of fear and the supply of additional food to predators in a delayed tri-trophic food chain model, where interference among the species is determined by Holling type-II functional response. The proposed model incorporates the fact that the growth rates of prey and middle predators are decreased due to the fear of middle and special predators, respectively. The additional food is supplied to both predators by either nature or external agencies. Furthermore, the poisoned prey in the predator's environment is taken into account. In the proposed model, we use two time delays: one for the growth term of the middle predator and another for the gestation delay of the special predator. We determine the conditions for the existence of ecologically feasible equilibrium points and their local and global stability. In addition, we establish the conditions for the existence of Hopf bifurcation around interior equilibrium to seek periodic behavior in nondelayed and delayed models. Numerical investigations are performed to justify the proposed theoretical findings through phase portraits, time series of solutions, and bifurcation diagrams. We observe that the chaotic dynamics of a tri-trophic food chain model can be controlled by the proper choice of the fear effect and by supplying additional food parameters. As a result, our findings provide more ecological insights into the dynamics of the delayed tri-trophic food chain model with the fear effect and additional food supply. © 2023 John Wiley & Sons, Ltd.

关键词： Hopf bifurcation

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Analysis of selected dielectric parameters of insulating liquids 23

Analysis of selected dielectric parameters of insulating liq...

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23rd International Scientific Conference on Electric Power engineering, EPE 2023

作者： Pluzek, Aleksandra Nagi, Lukasz Koziol, Michal Zygarlicka, Malgorzata Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Electrical Power and Renewable Energy Opole Poland Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Computer Science Opole Poland

ISBN: (纸本)9798350335934

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength. © 2023 IEEE.

关键词： Nanoparticles

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Formation control Design of Fixed-wing UAVs Based on Model Reference Adaptive control

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica electrical engineering and Computer Science 2025年第1期69卷 43-52页

作者： Lantos, Bela Kimathi, Stephen Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Department of Electrical and Electronic Engineering Dedan Kimathi University of Technology P.O.B. 10143 Dedan Kimathi Nyeri10100 Kenya

Formation control is currently a popular field of research due to the increasing application areas of unmanned aerial vehicles. Of concern is the stability of unmanned aerial vehicles (UAVs) formation while tracking especially under the influence of disturbances, and model parameter uncertainty. Since formation of the UAV formation while tracking, especially flying involves a mutual cooperation, consensus-based techniques are more suited such that a group of UAVs are collectively coordinated to perform some tasks. In this paper, a leader–follower formation control of homogeneous fixed wing UAVs based on model reference adaptive control with an integral error control compensation is presented. Model reference adaptive control is powerful and effective for handling uncertain and varying dynamics. This proposed distributed composite control strategy with a directed graph topology, although model-dependent can be effective to suppress disturbances affecting the vehicles, while achieving consensus-based tracking of a reference path. The numerical simulation results given show the applicability of this proposed control strategy. © 2025 Budapest University of Technology and Economics. All rights reserved.

关键词： Directed graphs

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Parameter estimation in solar power plant systems: a comparative study of recursive and iterative techniques

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Sustainable Energy Research 2024年第1期11卷 1-12页

作者： Sadeghi, Kiavash Hossein Shafikhah, Mahmood Marashian, Arash Roshandel, Emad Razminia, Abolhassan Department of Electrical Engineering Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran Process Control Laboratory Faculty of Natural Sciences and Engineering Åbo Akademi University Turku Finland College of Science and Engineering Flinders University Adelaide Australia

The development of a dynamic model for a popular implemented solar power plant is a critical task for power engineers aiming to enhance the plant’s performance and reliability. In this study, we utilized the prediction error method (PEM), a robust algorithm for system identification, to capture the plant’s operational characteristics with precision. Additionally, we employed both recursive and hierarchical algorithms to identify the system parameters effectively. The results from each identification method are rigorously quantified and analyzed, allowing for a detailed comparison of their performance. This comprehensive evaluation not only highlights the strengths and weaknesses of each approach, but also provides valuable insights into their practical applications in the context of solar power systems. © The Author(s) 2024.

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