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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2022年第2期84卷 45-62页

作者： Ismail, Laith S. Lupu, Ciprian Alshareefi, Hamid Luu, Duc Lich Dept. of Automatic Control University POLITEHNICA of Bucharest Romania Computer Technology Engineering Department Al Turath University Collage Baghdad Iraq Faculty of Mechanical Dynamics Vinh University of Technology Education Nghe an Viet Nam

This paper presents a dynamic model of a magnetic levitation system (Maglev) and suggests a Fuzzy Tuning of a proportional—integral--derivative controller (PID) that uses a fuzzy approach system to determine the PID controller's settings. The controller allows a steel ball to be suspended in free fall in the chosen position in reference to the electromagnet bottom end. The electromagnet levitation system can be controlled with a traditional PID controller, however because of the highly nonlinear of this system, it is unpredictable in the case of load and air gap changes. The fuzzy rules are developed to fuzzy tune PID while considering the control response and behavior of the system to find a solution to this problem. This paper shows excellent stability, rising time, settling time overshoot, and robust response results. The results reveal that this fuzzy PID controller solution can stabilize the ball's location and has strong disturbance rejection. The real time platform is designed for educational laboratory and test all the proposed control systems. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： controllers

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Representation of Coherent Structures from Volume Data Using Quality-oriented Features and Genetic optimization

Representation of Coherent Structures from Volume Data Using...

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

作者： Marius Gavrilescu Florin Leon Sabina-Adriana Floria Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iasi Romania

Representing relevant information from volume data sets is a problem often faced in visualization. Generating meaningful images from highly-complex volume data sets is a challenging, tedious task requiring specialized knowledge of the distribution and properties of the data. Traditionally, this task has been carried out manually via specialized user interfaces. We propose a volume visualization pipeline which facilitates the automatic generation of high-quality images from volume data sets. Our method involves a direct volume renderer which generates images from volume data based on visual mappings provided by a transfer function. Central to our approach is a quality-focused descriptor which exploits the properties of the distribution of gradient orientations of an alpha-bounded surface within the volume. This feature is useful for determining transfer functions that result in the rendering of corresponding images depicting various details from the volume. We show that by using this feature as an optimization objective, the generation of high quality images can be automated. Using simple genetic algorithms, we can automatically generate sets of images illustrating coherent, easily-distinguishable and high-quality surfaces of relevant structures from volume data.

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Efficient Deep Learning Models Based on Tension Techniques for Sign Language Recognition

SSRN

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SSRN 2023年

作者： Attia, Nehal F. Faheem Said Ahmed, Mohamed T. Alshewimy, Mahmoud A.M. Computer and Automatic Control Dept. Faculty of Engineering Tanta University Tanta Egypt

Among the various ways of self-expression and communication between people, communication by speaking prevails. Speech presents a significant challenge for some disabled people, such as the deaf, hearing impaired, wordless, and dumb persons. Therefore, these people rely on the use of sign language to interact with others. Sign language is a system of movements and visual messages that ensure the integration of these individuals into groups that communicate vocally. On the other side, it is necessary to understand the gestures and linguistic semantics of these individuals. The main objective of this study is to establish a new model that enhances the performance of the existing paradigms in use for the recognition of American Sign Language (ASL). Therefore, three enhanced deep-learning models of YOLOv5 for recognizing the alphabetic and numeric information conveyed by hand motions are presented in this paper. These models depend on using different attention approaches. The suggested models were evaluated using the MU HandImages ASL dataset. The proposed models yielded superior results compared to those achieved by the initial version of YOLOv5. The modified models have reached their maximum accuracy of 98.9%, maximum recall of 97.5%, maximum mAP 0.5 of 99.2%, and maximum mAP 0.5:0.95 of 98.9%. © 2023, The Authors. All rights reserved.

关键词： computer vision

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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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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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An OpenStack Cloud Solution for a Community Database with Handwritten Characters Used in Developing OCR Algorithms 27

An OpenStack Cloud Solution for a Community Database with Ha...

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27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Pavăl, Mihaela-Irina Alexandrescu, Adrian Archip, Alexandru Directorate of Informatization and Digital Communications "Gheorghe Asachi" Technical University of Iaşi Iaşi Romania Faculty of Automatic Control and Computer Engineering "Gheorghe Asachi" Technical University of Iaşi Iaşi Romania

ISBN: (纸本)9798350337983

Most research addressing OCR through machine learning techniques is focused on the actual algorithms and on using the MNIST data set as the de facto benchmark. Little effort was made to extend the data set or to build an entirely new one. Furthermore, support for characters other than English ones is mostly limited. This paper presents an OpenStack based approach that aims to overcome this last limitation by providing a community-oriented solution for developing and maintaining richer, language agnostic, community-shared data sets for OCR based applications. The proposed architecture is integrated with OpenStack services and relies on new Cloud perspectives, such as Function-as-a-Service (FaaS), to achieve a greater degree of flexibility. The included modules allow users to upload their own data sets, select or fine-tune their desired pre-processing methods, and derive the required features for their target character set. Both the input and the output data are stored using OpenStack specific data services and are shared for all the users of the Cloud deployment. An interesting feature is that the underlying FaaS functionality would also allow interested parties to upload their own pre-processing and feature extraction stages. © 2023 IEEE.

关键词： Platform as a Service (PaaS)

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A Plagiarism Detection Architecture Based on OpenStack Services 27

A Plagiarism Detection Architecture Based on OpenStack Servi...

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27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Vodă, Georgian Alexandrescu, Adrian Directorate of Informatization and Digital Communications "Gheorghe Asachi" Technical University of Iaşi Iaşi Romania Faculty of Automatic Control and Computer Engineering "Gheorghe Asachi" Technical University of Iaşi Iaşi Romania

ISBN: (纸本)9798350337983

Plagiarism is a well-known problem that impacts the academic community. The escalation of source code plagiarism affects the quality of computer science and technology education. This article approaches a novel architecture for an academic plagiarism detection system focused on projects and source code. A part of the detection process is based on a few already existing open-source tools. All the system components use the OpenStack Cloud platform services for scalability, parallel processing of files, and load balancing. The solution also integrates with an identity and access management system, which contains users, roles, and cohorts. The proposed solution is an efficient approach for both organizing assignments at which students upload projects and for detecting plagiarism in all the submitted assignments. © 2023 IEEE.

关键词： Cloud computing architecture

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RISC-V Extension for Optimized PWM control

RISC-V Extension for Optimized PWM Control

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

作者： Cosmin-Andrei Popovici Andrei Stan Vasile-Ion Manta Department of Computer Engineering Faculty of Automatic Control and Computer Engineering Technical University “Gheorghe Asachi” Iași România

This paper proposes a RISC-V extension, named SigWavy, meant to optimize the PWM control for general purpose or application specific designs. The RISC-V extension named above is a PWM control Unit with a dedicated ISA extension set designed for configuring and driving up to 32 PWM signals. The extension is integrated into RiscPwm, an updated version of our previous work, the RisCanFd SoC, for taking advantage of CAN-FD, a massively used protocol in the areas of automation and mobility. Being configured with the dedicated ISA extension or with parameters directly extracted from CAN-FD commands, the proposed solution manages to configure/reconfigure PWM channels between 4.79x and 9.18x times faster than an ARM Cortex-M7 processor, although our SoC operates with a 6x lower frequency.

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Real-Time Communication Model for IoT Systems

Real-Time Communication Model for IoT Systems

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Federated Conference on computer Science and Information Systems (FedCSIS)

作者： Stanisław Deniziak Mirosław Płaza Łukasz Arcab Faculty of Electrical Engineering Automatic Control and Computer Science Kielce University of Technology Kielce Poland

Internet of Things solutions typically involve interaction between sensors, actuators, the cloud, embedded systems and user applications. Often in such cases, there are time constraints specifying the maximum response time to a request. This time depends on the calculation time and transmission time. Existing Internet communication solutions do not ensure the implementation of transmissions in a way that guarantees meeting the set time constraints. This paper proposes a new model of Internet communication dedicated to real-time Internet of Things systems, which includes a communication protocol, as well as a transmission scheduling and routing method. The protocol takes into account information about transmission time constraints, which is used for packet scheduling by routers, allowing to increase quality of service. In addition, the proposed static routing mechanism makes it possible to parallelize transmissions if time constraints are still exceeded. Also presented are preliminary results of experiments showing to what extent the proposed methods allow improving the quality of service in real-time Internet of Things systems.

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Follow me droney! Will UWB technology do it right? 12

Follow me droney! Will UWB technology do it right?

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12th Asia Conference on Mechanical and Aerospace engineering, ACMAE 2021

作者： Hanzel, Krzysztof Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

Object tracking for consumer drones is currently a rapidly developing technology. Its implementation is currently carried out with the use of object-in-image detection, which often limits the latest possibilities of this technology. The disadvantage of such a solution is also the increase in energy demand and the need to provide additional computing power, or delays resulting from the transfer of this operation to the control device. The proposed solution to this problem in this article is the use of UWB (Ultra-wideband) technology, which is increasingly appearing in consumer devices. The possible yield related to the accuracy of determining the position of the object as well as the experimentally determined frequency of receiving information about the position was presented. Additional advantages, such as resistance to NLOS (non-line of sight) conditions, were also presented. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

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