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International Conference on Modern Electrical and Energy Systems (MEES)

作者： Simona Kirešová Milan Guzan Branislav Sobota Viacheslav Melnykov Rostyslav Yatsiuk Bohdan Peryvertailo Dept. of Theoretical and Industrial Electrical Engineering Technical University of Košice Košice Slovakia Dept. of Computers and Informatics Technical University of Košice Košice Slovakia Dept. of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Dept. of Computer Engineering and Electronics Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

This paper deals with the design of an Android mobile application and visualization of the measured values of particulate matter and meteorological factors from the measurement stations. The application can in principle be effectively used in any field of data visualization. The architecture of the mobile application, the security, the use of AWS services to access the data in the InfluxDB databases, as well as the user interface and graphical visualizations of the measured data are described and illustrated. The application is user tested and the paper documents their first experiences using the mobile application.

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Client-server Mobile System for Diagnosis of Asynchronous Motors 4

Client-server Mobile System for Diagnosis of Asynchronous Mo...

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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Chorna, Olha Kurliak, Petro Busher, Victor Chornyi, Oleksii Tytiuk, Valerii Zachepa, Iurii Institute of Education and Science in Electrical Engineering and Information Technologies Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Department of Electrical Power Engineering Electrical Engineering And Electromechanics Ivano-Frankivsk National Technical University of Oil and Gas Ivano-Frankivsk Ukraine Dept. of Electrical Engineering and Electronics National University "Odessa Maritime Academy" Odessa Ukraine Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

ISBN: (纸本)9798350395532

This paper presents client-server mobile system for diagnosis of asynchronous motors. The system is created as a mobile application for smartphones and tablets. The system provides processing of the measured values of the currents and voltages of the stator phases of the asynchronous motor. According to the processing results, the results of diagnostics and forecasting of the current state of asynchronous motors are calculated. The software runs on the Android OS. The main purpose is to predict the current state of AD, which has a parametric electromagnetic asymmetry of the stator phases. © 2023 IEEE.

关键词： Induction motors

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A Comparative Study of Three Meta-Heuristic MPPT Techniques for PV Systems Under Complex Partial Shading Conditions

A Comparative Study of Three Meta-Heuristic MPPT Techniques ...

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Australasian Universities Power engineering Conference, AUPEC

作者： Abdulbari Talib Naser Karam Khairullah Mohammed Nur Fadilah Ab Aziz Karmila Binti Kamil Saad Mekhilef Dept. of Electrical and Electronic Engineering University Tenaga Nasional Selangor Malaysia Dept. Control and Mechatronics Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia Institute of Power Engineering (IPE) University Tenaga Nasional Selangor Malaysia School of Science Computing and Engineering Technologies University of Technology Melbourne VIC Australia

The energy generation performance of solar panels can be greatly influenced by partial shading conditions (PSCs). The phenomenon is ascribed to the presence of several maximum power points (MPPs) evident on the characteristic curves of power-voltage (P-V). These MPPs encompass diverse local peaks (LPs) along with a solitary global peak (GP). Traditional (MPPT) techniques fall short in precisely tracing the GP owing to the complex and nonlinear features of PV characteristic curves during instances of PSC. Hence, the adoption of MPPT techniques based on artificial intelligence (AI) becomes essential to effectively track the GP. In this research endeavor, three metaheuristic approaches for MPPT are investigated, namely the Team Game Algorithm (TGA), Gray Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). These algorithms are practically implemented, and their efficacy is experimentally validated while considering different solar irradiation levels while keeping the temperature constant. The experimental evaluation aims to compare the dynamic behavior of the photovoltaic (PV) array under various weather conditions. In contrast to other approaches, the TGA technique offers outstanding convergence capabilities, as shown by the experimental tests carried out in this study.

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Modeling and Analysis of Electric Field Variation across Insulation System of a MV power Cable 3

Modeling and Analysis of Electric Field Variation across Ins...

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3rd International Conference on Electrical, Communication and Computer engineering, ICECCE 2021

作者： Musa, Umar Mati, Abdullahi A. Mas'ud, Abdullahi A. Shehu, Gaddafi S. Albarracin-Sanchez, Ricardo Rodriguez-Serna, Johnatan M. Ahmadu Bello University Dept. of Electrical Engineering Zaria Nigeria Center for Energy Research Training Ahmadu Bello University Zaria Nigeria Jubail Industrial College Dept. of Electrical and Electronic Engineering Jubail Saudi Arabia School of Industrial Design and Engineering Universidad Politécnica de Madrid Dept. of Electrical and Electronic Engineering Automatic Control and Applied Physics Spain

ISBN: (纸本)9781665438971

Cross-linked polyethylene (XLPE) has found wide application in high-and medium-voltage power distribution and transmission systems. Owing to its excellent properties, XLPE is highly deployed for insulation purposes in underground power cables. The presence of defects across the insulation systems serves as field enhancement and partial discharge initiation sites that may lead to equipment failure. In this paper, the finite element modeling of electric field variation across the insulation system of an XLPE medium-voltage (MV) power cable has been presented. A cross-section of the cable sector has been modeled in COMSOL without and with a single spherical cavity. Electric field strength analyses are performed for the healthy and defected cable, and their results are compared. The simulation results showed that the presence of the cavity has risen the electric field strength magnitude by 27.1 % as compared to the original value (without cavity). © 2021 IEEE.

关键词： Partial discharges

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Identification of Low Order Systems in a Loewner Framework 1

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IFAC-PapersOnLine 2024年第15期58卷 199-204页

作者： Arya Honarpisheh Rajiv Singh Jared Miller Mario Sznaier ECE Dept. Northeastern University Boston MA 02115 USA The MathWorks Inc. 1 Apple Hill Drive Natick MA 01760 USA Automatic Control Laboratory (IfA) Department of Information Technology and Electrical Engineering (D-ITET) ETH Zürich Physikstrasse 3 8092 Zürich Switzerland

This paper considers the problem of non-parametric identification of low-order models from time-domain experimental data using a combination of Caratheodory Fejer and Loewner-based interpolation, followed by a Loewner matrix Balanced Reduction (LBR) step. As we show in the paper, the Loewner matrix is an estimator for the trace norm of a system, playing a role similar to the one played by the Hankel matrix. However, utilizing Zolotarev numbers to establish decay rate bounds for singular values reveals that the decay of singular values in the Loewner matrix is considerably faster than that in the Hankel matrix. Thus, Loewner-based methods yield lower order systems, with the same error bound, than comparable ones based on Hankel matrices. The effectiveness of our method is demonstrated through a numerical example.

关键词： Low-rank Approximation Loewner Matrix Hankel Matrix Balanced Reduction Subspace Methods Linear Systems

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Compensation’s Method of Collector Load’s Parasitic Components in SiGe and SOI Cascode Amplifiers Operating at High Temperatures

Compensation’s Method of Collector Load’s Parasitic Compon...

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IEEE International Conference on Electrical engineering and Photonics (EExPolytech)

作者： Anna V. Bugakova Ilya V. Frolov Yuri I. Ivanov Nadezhda A. Dmitrienko Dept. Scientific Research Dept. Information Systems and Radio Engineering Don State Technical University Rostov-on-Don Russia Lab. Solid-State Electronics Opto- and Nanoelectronics Ulyanovsk Branch of the Kotelnikov Institute of Radioengineering and Elecronics of Russian Academy of Science Ulyanovsk Russia Dept. Automatic Control Systems Southern Federal University Rostov-on-Don Russia Dept. Foreign Languages Institute of Service and Business (branch) DSTU in Shakhty Shakhty Russia

ISBN: (数字)9798350388879

ISBN: (纸本)9798350388886

This paper considers the circuit method for neutralizing the effect of parasitic components of the collector load in silicon-germanium (SiGe) and silicon-on-insulator (SOI) classical cascade amplifiers and common-base stages on their voltage gain (Gain). The article demonstrates that the incorporation of a dedicated compensating circuit into the original circuits enables the enhancement of their upper frequency limit or gain by a factor of 5 to 10. The conditions for mitigating the impact of resistor parasites, which contribute to losses in planar inductance, on the Q-factor of the RLC-circuit of the selective amplifier are established. It is recommended that the proposed circuit solutions be employed in practical applications involving SiGe and SOI analog chips operating at elevated temperatures.

关键词： Resistors Resistance Q-factor Inductance Temperature distribution Transfer functions Silicon-on-insulator Voltage Transistors Silicon germanium

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A Machine Learning Approach to Classify Network Traffic 13

A Machine Learning Approach to Classify Network Traffic

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13th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2021

作者： Jadav, Nilesh Dutta, Nitul Sarma, Hiren Kumar Deva Pricop, Emil Tanwar, Supeep Marwadi University Dept. of Computer Engineering Rajkot India Sikkim Manipal Inst. of Technology Dept. of Information Technology Majitar India Petroleum-Gas University of Ploiesti Automatic Control Comp and Elect. Dept Ploiesti Romania Nirma University Dept. of Computer Science and Eng. Ahmedabad India

ISBN: (纸本)9781665425346

There is a significant increase of cloud and networking-enabled applications, leading to an exponential growth of network traffic. Monitoring all these applications and their generated traffic is a challenging and complex task, especially in regard to anonymous networks used to access the Dark Web or darknet. Manual investigation of the network traffic to determine patterns of malicious activity is a very difficult task and the results might not be satisfactory. The usage of machine learning is the most viable approach for the classification of the traffic as normal or malign activity. This paper analyzes CIC-Darknet 2020 dataset to classify the benign and darknet traffic. Before applying any classifiers to our dataset, we have balanced it using Synthetic Minority Oversampling Technique (SMOTE). We have applied PCA to reduce dimensionality, furthermore, ensemble techniques, logistic classifiers, tree-classifiers, and Naive Bayes have been compared and evaluated thoroughly with various evaluation metrics Accuracy, Precision, Recall, F1-Score, and Mathew's Correlation Coefficient (MCC). © 2021 IEEE.

关键词： Machine learning

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Learning Goal-based Movement via Motivational-based Models in Cognitive Mobile Robots

arXiv

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arXiv 2023年

作者： Berto, Letícia Costa, Paula Simões, Alexandre Gudwin, Ricardo Colombini, Esther Laboratory of Robotics and Cognitive Systems Institute of Computing University of Campinas Brazil Dept. of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas Brazil Dept. of Control and Automation Engineering Institute of Science and Technology São Paulo State University Sorocaba Brazil University of Campinas Brazil

Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action’s perceived pleasure, which is susceptible to changes over time. This makes decision-making more complex, requiring learning to balance needs and preferences according to the context. To understand how this process works and enable the development of robots with a motivational-based learning model, we computationally model a motivation theory proposed by Hull. In this model, the agent (an abstraction of a mobile robot) is motivated to keep itself in a state of homeostasis. We added hedonic dimensions to see how preferences affect decision-making, and we employed reinforcement learning to train our motivated-based agents. We run three agents with energy decay rates representing different metabolisms in two different environments to see the impact on their strategy, movement, and behavior. The results show that the agent learned better strategies in the environment that enables choices more adequate according to its metabolism. The use of pleasure in the motivational mechanism significantly impacted behavior learning, mainly for slow metabolism agents. When survival is at risk, the agent ignores pleasure and equilibrium, hinting at how to behave in harsh scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Metabolism

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A Computer Vision-Based Solution for Assessing Prosthetic Leg Length Discrepancy

A Computer Vision-Based Solution for Assessing Prosthetic Le...

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E-Health and Bioengineering Conference (EHB)

作者： Otilia Zvorişteanu Dimitrie-Cristian Fodor Vasile-Ion Manta Neculai-Eugen Seghedin Ştefan-Daniel Achirei Dragoş-Florin Chitariu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania “Dr. Iacob Czihac” Military Emergency Clinical Hospital Iaşi Dept. of Digital Production Systems Faculty of Machine Manufacturing and Industrial Management “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

This paper presents a novel computer vision-based approach for assessing leg length discrepancy (LLD) in individuals with prosthetic limbs. The proposed solution uses image processing techniques to detect markers placed on the patient's knee, prosthesis, and a reference wall, allowing for precise measurement of limb alignment. Through a comparative analysis of the initial reference position, set by a specialist, and the current limb positioning, the algorithm identifies discrepancies in leg length. The system employs a non-invasive methodology, utilizing an IP camera to capture images and communicate them via Wi-Fi to a computing unit for further analysis. Experimental validation, conducted on simulated LLDs ranging from 1mm to 10mm, demonstrates the system's high sensitivity and accuracy in detecting subtle changes in limb alignment. This approach offers a scalable, automated alternative to traditional manual methods, improving both the reliability and ease of prosthetic adjustments.

关键词： Legged locomotion Wireless communication Limbs Prosthetic limbs Current measurement Manuals Cameras Reliability IP networks Wireless fidelity

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MCU-MixQ: A HW/SW Co-optimized Mixed-precision Neural Network Design Framework for MCUs

arXiv

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arXiv 2024年

作者： Gong, Junfeng Liu, Cheng Cheng, Long Li, Huawei Li, Xiaowei SKLP Institute of Computing Technology Chinese Academy of Sciences Beijing China Dept. of Computer Science University of Chinese Academy of Sciences Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

Mixed-precision neural network (MPNN) that utilizes just enough data width for the neural network processing is an effective approach to meet the stringent resources constraints including memory and computing of MCUs. Nevertheless, there is still a lack of sub-byte and mixed-precision SIMD operations in MCU-class ISA and the limited computing capability of MCUs remains underutilized, which further aggravates the computing bound encountered in neural network processing. As a result, the benefits of MPNNs cannot be fully unleashed. In this work, we propose to pack multiple low-bitwidth arithmetic operations within a single instruction multiple data (SIMD) instructions in typical MCUs, and then develop an efficient convolution operator by exploring both the data parallelism and computing parallelism in convolution along with the proposed SIMD packing. Finally, we further leverage Neural Architecture Search (NAS) to build a HW/SW co-designed MPNN design framework, namely MCUMixQ. This framework can optimize both the MPNN quantization and MPNN implementation efficiency, striking an optimized balance between neural network performance and accuracy. According to our experiment results, MCU-MixQ achieves 2.1× and 1.4× speedup over CMix-NN and MCUNet respectively under the same resource constraints. © 2024, CC BY-SA.

关键词： Convolution

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