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14th International Conference ELEKTRO, ELEKTRO 2022

作者： Radil, Roman Bajtos, Marek Carnecka, Lucia Hargasova, Klaudia Kamencay, Patrik University of Zilina Department of Electromagnetic and Biomedical Engineering Zilina Slovakia Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Systems Biology and Engineering Gliwice Poland

ISBN: (纸本)9781665467261

The article is focused on design of specific electromagnetic coil system using numerical modelling and simulation methods. The proposed solution would be capable of delivering magnetic field of desired strength/ flux density and homogeneity within the specific area to affect the cultivation process of single cells in lab on chip experiments. © 2022 IEEE.

关键词： Numerical models

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Analog, Programmable Switched Capacitor FIR Filter Based on Rotator Architecture Implemented in CMOS Technology 26

Analog, Programmable Switched Capacitor FIR Filter Based on ...

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26th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Pawlowski, Pawel Dlugosz, Rafal Radkowski, Marek Watly, Mateusz Dabrowski, Adam Poznań University of Technology Division of Signal Processing and Electronic Systems Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznań60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350304985

The paper presents project and its verification of a prototype integrated circuit containing an analog, programmable finite impulse response (FIR) filter, implemented in CMOS 350 nm technology. The structure of the filter is based on the switched capacitor technique. In circuits of this type, one of main challenges is an efficient implementation of filter coefficients, which result from several factors described in this work. When implementing such filters as programmable circuits, the values of their coefficients have to be limited to a selected range, i.e. a given resolution in bits. In the implemented prototype filter, the filter coefficients are represented by 6 bits in sign-magnitude notation, so they can take 63 different values only. In such filters, it is not possible to directly implement any frequency response of the filter. Each time, it is necessary to properly round the theoretical values of the coefficients so that they fit into the available range of discrete values resulting from the implementation. The authors of the work designed an algorithm that allows such matching. The paper also presents results of measurements of the prototype chip. © 2023 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： FIR filters

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4K Video Coding Efficiency in UAV Systems 45

4K Video Coding Efficiency in UAV Systems

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Benjak, J. Hofman, D. Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia

ISBN: (纸本)9789532331035

With increasing requirements for high quality, low bandwidth video transmission systems, comes a demand for more ad hoc video encoders. Unmanned Aerial Vehicles (UAVs), or just drones, have recently grown in popularity and use. Therefore, in this paper, we provide an efficiency comparison of the two most popular video encoders in a First-person view (FPV) drone piloting system. We film all the test sequences ourselves, using a drone with an attached 4K camera. Each sequence captures a scene with different spatiotemporal characteristics. Because video encoders are sensitive to video content or scene complexity, instead of doing a comprehensive comparison of all sequences at once, we first classify all the sequences into four groups. Finally, we examine the compression efficiency by varying the parameters with the highest impact on encoder operation. The quality of compressed footage is determined using four objective video quality measures. Due to high computational complexity, tests were performed on several nodes of a supercomputer and the relative encoding times were also considered. © 2022 Croatian Society MIPRO.

关键词： Antennas

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ORB-Net: End-to-end Planning Using Feature-based Imitation Learning for Autonomous Drone Racing 56

ORB-Net: End-to-end Planning Using Feature-based Imitation L...

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56th International Symposium on Robotics, ISR Europe 2023

作者： Pham, Huy Xuan Heiß, Micha Tran, Dung Nguyen, Minh Anh Nguyen, Anh Quang Kayacan, Erdal Department of Electrical and Computer Engineering Aarhus University Aarhus C8000 Denmark Hanoi Viet Nam Automatic Control Group Department of Electrical Engineering and Information Technology Paderborn University Paderborn Germany

ISBN: (纸本)9783800761418

Deep learning-based methods have enhanced the performance of many robot applications thanks to their superior ability to robustly extract rich high-dimensional features. However, it comes with a high computational cost that often increases the latency of the overall system. On the other hand, traditional feature extraction methods, such as oriented FAST and rotated BRIEF (ORB), can be computed efficiently and remains the backbone of some critical robot algorithms, e.g. ORB-SLAM for robot state estimation. In this work, the usefulness of the aforementioned features for a robot navigation task is investigated. The features are experimentally incorporated with a deep-learning method, called ORB-Net1, which allows an agile aerial robot to learn a motion policy to complete a racing track in an autonomous drone racing context. The experimental studies demonstrate that it can be beneficial to reuse these computed features for end-to-end motion planning for the agile quadrotor, as the proposed method using combined input of ORB feature position and RGB images outperforms the baseline methods which use only RGB images. © VDE VERLAG GMBH Berlin Offenbach.

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Smooth Motion Planning of an Omnidirectional Mobile Robot in Dynamic Environments

Smooth Motion Planning of an Omnidirectional Mobile Robot in...

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2022 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Šelek, Ana Seder, Marija Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

In this paper, a real-time smooth motion planning method for a four mecanum wheeled omnidirectional mobile robot in dynamic environments that generates a smooth collision-free trajectory is proposed. The method employs a graph-search-based path planning algorithm and a smoothing technique based on clothoids. It is suitable for real-time operation due to its computational simplicity and allows fast path replanning in case the robot encounters unknown and dynamic obstacles. Such a path is feasible for holonomic mobile robots since it does not contain sharp turns so the energy consumption is reduced. Our method is compared to the reactive model predictive control scheme in simulations. The comparison showed advantages of the proposed method in the reduced task execution time, path length, cumulative replanning time, and smooth velocity profile. © 2022 IEEE.

关键词： Motion planning

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Radial basis function network-based optimization of the hard self-propelled rotary turning titanium

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Neural Computing and Applications 2025年第7期37卷 5607-5634页

作者： Nguyen, Trung-Thanh Dang, Xuan-Ba Faculty of Mechanical Engineering Le Quy Don Technical University 236 Hoang Quoc Viet Hanoi100000 Viet Nam Department of Automatic Control Ho Chi Minh City University of Technology and Education 1 Vo Van Ngan Ho Chi Minh City70000 Viet Nam

Machining of difficult-to-cut materials such as high-temperature metals is challenging due to their low machinability resulting in reduced productivity and high manufacturing cost. This investigation develops and optimizes the hard self-propelled rotary turning (HSPRT) operation, in which an efficient self-propelled rotary tool is proposed and fabricated. The HSPRT responses (total carbon emission—TC, machined roughness—MR, and noise emission—EN) are minimized using optimal process variables (inclination angle—A, turning depth—D, turning speed—V, and rake angle—R). The TC, MR, and EN models are developed in terms of the HSPRT inputs using the radial basis function network and response surface method, while the weights were computed using the removal effects of criteria, EQUAL, and rank order centroid methods. The improved quantum-behaved particle swarm optimization algorithm and method based on the multi-attributive border approximation area comparison were applied to produce feasible solutions and select the best optimal point. The optimization findings of the V, D, f, and R were 32 deg., 0.2 mm, 137 m/min, and 20 deg., while the TC, MR, and EN were saved by 42.8%, 24.1%, and 20.0%, respectively. The HSPRT performances were primarily affected by the turning depth and speed, respectively. The valuable outcomes could be applied to the practice to boost HSPRT performances, while the developed HSPRT operation could be utilized for machining alloys and hardened steels. The technique could be applied to treat optimization problems for other rotary turning processes. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Particle swarm optimization (PSO)

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Towards experimental insight into magnetic flux distribution within the air gap of permanent magnet synchronous drive

Towards experimental insight into magnetic flux distribution...

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

作者： Hubert Milanowski Adam Krzysztof Piłat Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics AGH University of Krakow Krakow Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

This report explores the experimental identification of magnetic flux density within the motor air gap, focusing on the development of a robot-based approach to automate the scanning procedure. Emphasis is placed on analyzing the distribution of magnetic flux within the motor’s spatial air gap, as well as the amplification of harmonics resulting from changes in air gap orientation. Drawing upon experimental findings, a model is proposed to illustrate the three-dimensional distribution of magnetic flux within the gap.

关键词： Solid modeling Magnetic flux density Automation Atmospheric modeling Air gaps Rotors Drives

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Artificial Intelligence Based Employee Attrition Analysis and Prediction 6

Artificial Intelligence Based Employee Attrition Analysis an...

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6th International Conference on Computing and Informatics, ICCI 2024

作者： Ozakca, Nazli Sila Bulus, Ali Cetin, Aydin Havelsan Inc.Command Control and Defence technologies Ankara Turkey Computer Engineering Department Gazi University Faculty of Technology Ankara Turkey

ISBN: (纸本)9798350373875

The use of classification models to predict the probability of an employee leaving the job can greatly improve the ability of human resources to intervene in a timely manner and rectify the situation to prevent attrition. After the so-called "The Great Resignation", which took place after the pandemic period, studies on attrition have increased in order to regain the lost workforce and increase the loyalty of existing employees. In Turkey, however, studies in this field remain insufficient. The aim of this study is to predict the possible loss of employees, to take relevant measures and to reduce the financial losses of companies. The study was made available as SaaS (Software as a Service) based in order to facilitate accessibility to the target audience. For the analysis phase, the columns in the data set were analyzed with Pandas and Scikit-Learn library. Exploratory Data Analysis was performed by visualizing the analyzed data with Plotly and Seaborn libraries. Various insights were obtained with these inferences. The data was subjected to pre-processing stages such as cleaning, missing data completion, scaling, feature selection, data set balancing, dimension reduction, etc. to make it useful. Logistic Regression, KNN, SVM, Desicion Tree, Random Forest, ADABoost and Naive Bayes were used to train the model. In order to enrich the data set and increase the efficiency of the model, artificial intelligence-based synthetic data generation (Data Augmentation) was performed. In case of missing columns in the trained model, KNN-Data Imputation, one of the missing data completion methods, was used. In the optimization process of the model, hyperparameter optimizations were performed to achieve maximum efficiency with improvements. 5-fold cross-validation prevented the model from over-learning. Performance was analyzed on the basis of Accuracy, Recall, Precision and F1-score metrics and the success criterion was determined as F1-Score. The model was presented as a web se

关键词： Efficiency

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Comparative study of deep learning models for action recognition based on skeleton data

Comparative study of deep learning models for action recogni...

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2023 International Conference on computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2023

作者： Liang, Zhanhao Kudayberdievna, Kadyrkulova Kyial Isakunovich, Batyrkanov Jenish Liang, Zhantu Department of Automatic Control Kyrgyz State Technical University after Named I.Razzakov Bishkek Kyrgyzstan Faculty of Engineering Science and Technology Infrastructure University Kuala Lumpur Kajang Malaysia

ISBN: (纸本)9781510677685

In this study, we conducted a comparative analysis of three deep learning models - CNNs (90% accuracy), LSTMs (92% accuracy), and RNNs (95% accuracy) - for skeleton-based action recognition. The research focused on evaluating each model's ability to accurately classify a variety of human actions using a Kaggle dataset. Our findings revealed CNNs' strength in spatial recognition, LSTMs' proficiency in temporal dynamics, and RNNs' overall superiority in sequential processing. The study emphasizes the importance of model selection in action recognition tasks and lays groundwork for future exploration into hybrid models. © 2024 SPIE.

关键词： Classification (of information)

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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