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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Vakil, Ardavan Faezipour, Miad School of Engineering Technology Electrical & Computer Engineering Technology Purdue University West LafayetteIN United States

ISBN: (纸本)9798350327595

Deep brain stimulation (DBS) is a device that relies on methods to desynchronize adverse neurodegenerative activities within the brain. It is a well-known treatment method for people diagnosed with Parkinson's disease (PD). The adjustment of a precise definition of DBS signal parameters is critical to breaking the synchrony and burst of the increased neuronal activity, while preventing tissue or electrode damage, and also considering reducing the energy consumption for prolonging the battery life of the DBS device. In this research in progress, we study a pulse DBS waveform with delay between its cathodic and anodic parts to disrupt and desynchronize the firing/bursting patterns of Parkinsonian neuronal cell activities. We use a hyperbolic neuronal spiking pattern model to represent the signal activity of the brain. Specifically, we model a neuron infected with bursting behavior similar to that of PD, and apply DBS current to observe the effect, computationally. The expected output of applying the proposed pulse delayed DBS waveform is to break the bursting pattern and convert the bursting spike into a regular tonic spike. In addition, the promising results of pulse delayed waveforms in terms of eliciting action potential, desynchronization of the bursting behavior, and reduced energy consumption, can potentially enhance the performance of the applied DBS. © 2023 IEEE.

关键词： deep brain stimulation hyperbolic model neuronal spiking pattern Parkinson's Disease pulse delayed wave-form

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A Simple Analysis and Discussion of Poland Longwave Broadcasting Station Antenna

A Simple Analysis and Discussion of Poland Longwave Broadcas...

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2024 International Symposium on Antennas and Propagation, ISAP 2024

作者： Wu, Chao Qiu, Shuang Qiu, Jinghui Denisov, Olensandr Molebny, Vasyl Department of Microwave Engineering Harbin Institute of Technology Harbin China Department of Electrical and Computer Engineering University of Macau China

ISBN: (纸本)9798350364774

With the profound and complex changes of the international situation, the longwave communication has more and more important application value and strategic significance. And longwave can realize a large range of communication and even global communication at the low end of longwave frequency because of its advantages of low propagation loss, strong diffraction ability, etc. Therefore, longwave is widely used in a lot of fields, such as sea navigation, underground communication, underwater submarine communication, and so on. As one of the most important components of the longwave communication system, the performance of longwave antennas (LWAs) play a decisive role. In recent years, the research of LWAs mainly focuses on mechanical antenna and the traditional antenna form is less studied. In this paper, the world's most famous Poland longwave broadcasting station antenna is briefly discussed and analyzed and the development direction of the traditional longwave antenna is proposed. © 2024 IEEE.

关键词： Broadcasting antennas

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Efficient Brain Tumor Classification through Transfer Learning Models 26

Efficient Brain Tumor Classification through Transfer Learni...

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Mehemud, Md. Yusuf Binte Kibria, Hafsa Salam, Abdus Rajshahi University of Engineering & Technology Department of Electrical & Computer Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350359015

One of the most dangerous diseases, brain tumors need a quick and accurate method of detection. Wide-ranging symptoms can be caused by brain tumors, and both diagnosing and treating them can be difficult. Neurologists and radiologists occasionally fail to find the brain tumor. The American Brain Tumor Association says, about 700,000 people are coping with brain tumors. Each year, more than 80,000 new cases are diagnosed. The goal of this work is to identify brain tumors from MRI images in order to prevent earlier death. Brain image classification is done using the DenseNet121 and EfficientNetB0 pretrained transfer learning model. DenseNet121 and EfficientNetB0 have been selected for brain tumor classification because of their robust performance in image analysis tasks, their pretrained knowledge from extensive datasets like ImageNet, and their computational efficiency. The experimental result shows that the proposed model performs better than the previous work model VGG16, Support Vector Machine (SVM), Discrete Wavelet Transform (DWT), Gray Level Co-occurrence Matrix(GLCM), Hidden Markov Model (HMM), and Convolution Neural Network (CNN). These previous models' classification accuracy ranges from 94% to 96%, while the suggested model where we used 80% data for training and 20% data used for testing and average accuracies are 97.09% for DenseNet121 and 98.32% for EfficientNetB0. Also, the purpose of this work to categorize 4 classes in these 3 classes for tumor and 1 class for non tumor. Additionally, the proposed model's precision, recall, and F1-score are all 97% and 98%, indicating very good performance. However, these techniques have shown a significant potential for improving the diagnosis and treatment of brain tumors by providing a quick, accurate, and non-invasive way to categorize different types of tumors. © 2023 IEEE.

关键词： Brain tumor Classification CNN DenseNet121 EfficientNetB0 F1-score MRI

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A Frog-Shaped UWB MIMO Antenna Design for 5G

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Progress in Electromagnetics Research C 2025年 151卷 101-112页

作者： Yao, Shanhua Yang, Tianchu Qiu, Xiaorong Li, Xiang School of Electrical and Information Engineering Anhui University of Science and Technology Huainan232001 China School of Computer Science Huainan Normal University Huainan232001 China

In this paper, a frog-shaped ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna is proposed for 5G applications in the n77, n78, n79, and 6 GHz bands with a compact antenna structure of 31 × 55 × 1.5 mm3. The designed antenna consists of two frog-shaped monopole antennas and a floor from which a part has been removed, and the operating bandwidths range from 3.05 to 13.38 GHz, which meets the design criteria for UWB. The T-shaped floor with two T-shaped slots impedes the flow of coupling currents and improves the isolation of the antenna. This results in an isolation of less than −17 dB over the entire operating bandwidth and less than −20 dB in the 5G band. In addition, the envelope correlation coefficient (ECC) is less than 0.007, the diversity gain (DG) more than 9.96, the total active reflection coefficient (TARC) less than −30 dB, and the channel capacity loss (CCL) less than 0.34 bit/s/Hz. The measured and simulated results agree with each other, demonstrating the antenna’s potential application in 5G communication systems. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Bandwidth

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Electrostatic tapering for efficient generation of radiation

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Physical Review E 2022年第2期105卷 L023201-L023201页

作者： Miron Voin Levi Schächter Department of Electrical and Computer Engineering Technion—Israel Institute of Technology Haifa 32000 Israel

We demonstrate the feasibility of electrostatic (dc) tapering such that the net average force of the electromagnetic (ac) field is compensated by a dc field, which at resonance may be interpreted as “direct” energy transfer from the dc to the ac field. This combination persists in all three components of the setup—e-gun, resonant zone, and collector, in each one playing a different role. In equilibrium, the two field components field-emit at the cathode a density modulated cylindrical beam which is accelerated along the e-gun by the dc field; the latter also focuses the e-beam. Radiation confinement perpendicular to the e-beam is ensured by an array of dielectric Bragg-mirrors and an array of metallic hollow electrodes impose synchronous bunches and wave. This double periodic structure ensures the coexistence of dc and ac fields in the same volume. Numerical simulations demonstrate the feasibility of generation of order of 1[W] power at 1 THz from a volume on a scale of few mm3 with efficiency of the order of 25%.

关键词： Electromagnetism Low-energy multiple-particle dynamics

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Thermal Model of a Soldering Iron 33rd

Thermal Model of a Soldering Iron

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33rd International Conference on Organization and technology of Maintenance, OTO 2024

作者： Barić, Tomislav Glavaš, Hrvoje Dubravac, Anto Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Osijek Croatia

ISBN: (纸本)9783031805967

Soldering irons are a hand tool that is indispensable in the process of making small series of electronic devices. Soldering irons have evolved from very simple devices without temperature control to devices with complex temperature control. The implementation of temperature control is based on the knowledge of the thermal models of the soldering iron. Thermal models of soldering irons are based either on the theory of thermal fields or on the theory of equivalent Kirchhoff thermal circuits. The theory of thermal fields is applied for very accurate modeling. In doing so, the finite element method (FEM) is used. For the above, it is necessary to use software packages based on FEM. Unlike FEM-based modeling, thermal circuit modeling does not require specialized software tools. It is also possible to derive analytical expressions that describe the thermal process of the soldering iron. In this paper, a thermal model of a soldering iron based on equivalent Kirchhoff thermal circuits is presented. Analytical expressions were derived to describe the thermal transient. The validity of the theoretical model is supported by measurement. Measurements were carried out on two soldering irons from different manufacturers. The measurement results were analyzed. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Hand tools

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Voltage Sag Investigation for Induction Motor Startup in Distribution Systems using Solid State Transformer 15

Voltage Sag Investigation for Induction Motor Startup in Dis...

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15th International Renewable Energy Congress, IREC 2025

作者： Ghambirlou, Khaled Abosnina, Adel Ali Moschopoulos, Gerry Western University Dept. Electrical and Computer Engineering London Canada College of Electrical and Electronics Technology Benghazi Libya

ISBN: (纸本)9798331516772

Dealing with voltage sags during motor startup is crucial because they can delay power restoration and lead to widespread failures for industrial loads and distribution systems. A novel approach is introduced to investigate voltage sag in distribution networks using solid-state transformers (SSTs) instead of traditional ones. The induction motor startup model is employed to simulate voltage sags, accurately representing the characteristics influenced by conventional industrial loads. The inherent capabilities of SSTs are leveraged to mitigate these voltage sag issues effectively. This study focuses on analyzing voltage sags caused by the activation of induction motors in power systems, with particular emphasis on SST technology, which actively regulates voltage during motor starting by controlling reactive power. The selected distribution system is implemented and tested using MATLAB/Simulink. The results will be compared with previous research on voltage sag during motor startup, demonstrating the improvements and effectiveness of using SSTs in managing power quality issues. This study emphasizes the potential of SSTs to improve the stability and reliability of power systems during the challenging conditions of motor startup. © 2025 IEEE.

关键词： Distribution transformers

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A Machine Learning Approach for Distribution Transformer Fault Detection 10

A Machine Learning Approach for Distribution Transformer Fau...

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10th IEEE International Conference on Power Systems, ICPS 2023

作者： Jyoti, Oishi Kibria, Hafsa Binte Hossain, Md. Munawar Rajshahi University of Engineering & Technology Department of Electrical & Computer Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350318739

A distribution transformer fault refers to a malfunction or abnormal condition that occurs in a distribution transformer, which is a vital component in electrical power distribution systems. Distribution transformers lower high transmission voltage for use in homes and businesses. In this study, we address the critical challenge of transformer fault detection by employing a comprehensive approach that harnesses the power of advanced machine-learning techniques. We conducted extensive experiments utilizing a diverse dataset to predict and classify four distinct types of transformer faults. Leveraging the capabilities of twelve different classification algorithms, such as - SVM, DecisionTree(DT), AdaBoost, RandomForest(RF), ExtraTrees(ET), GradientBoosting(GB), MultipleLayerPerceptron(MLP), KNeighbors, LogisticRegression(LR), LinearDiscriminantAnalysis, XGBoost, and LGBM, we implemented a robust methodology that outperformed prior results, achieving a significantly higher accuracy rate. Key to our success is the integration of cross-validation, ensuring the reliability and generalization of our predictive models. This research advances the field of transformer fault prediction, offering a more accurate and dependable framework for identifying and mitigating critical issues in power distribution systems. The results hold substantial promise for enhancing the reliability and safety of transformer operations, with far-reaching implications for the energy industry. © 2023 IEEE.

关键词： Adaptive boosting

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High-Performance Face Identification Using Randomly Selected Channels from Hyperspectral Images

High-Performance Face Identification Using Randomly Selected...

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2024 IEEE International Conference on Imaging Systems and Techniques, IST 2024

作者： Furusawa, Sota Premachandra, Chinthaka Graduate School of Engineering and Science Shibaura Institute of Technology Dept. of Electrical Engineering and Computer Science Tokyo Japan

ISBN: (纸本)9798350378214

With the recent development of information technology, the importance of protecting personal information has increased. Because of the vulnerability in passwords, biometric authentication is now being used as a method of personal information protection. However, biometric authentication has the possibility of malicious authentication due to the emergence of technology that can generate biometric data that is difficult to duplicate. Therefore, this study aimed to solve the security problems posed by Generative Adversarial Networks (GANs) in biometric authentication by using Hyperspectral Images (HSI). We searched for solutions to the problems identified in previous studies, such as the inability to correctly identify individuals who have not been previously learned and the length of time required for identification. In this paper, we used three channels of data randomly selected from hyperspectral face images for learning to identify individuals by binary classification into 'learned subject (class)' and 'unlearned subjects (classes)'. In this case, discriminators based on the least-squares generative adversarial network (LSGAN) model was developed for each class using three randomly selected channels of data from the HSI for two class classification. The proposed method significantly reduced the identification time and achieved very high discrimination accuracy in all classes. In addition, the results showed high accuracy throughout multiple face identification experiments. © 2024 IEEE.

关键词： Generative adversarial networks

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Best Linear Controllers for Decentralized Linear Quadratic Systems

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Journal of Systems Science & Complexity 2025年第1期38卷 210-237页

作者： AFSHARI Mohammad MAHAJAN Aditya Institute for Robotics and Inteligent Machines Georgia Institute of TechnologyAtlanta 30332-0530USA Department of Electrical and Computer Engineering McGill UniversityMontreal H3A 0G4Canada

In this paper,the authors revisit decentralized control of linear quadratic(LQ)*** of imposing an assumption that the process and observation noises are Gaussian,the authors assume that the controllers are restricted to be *** authors show that the multiple decentralized control models,the form of the best linear controllers is identical to the optimal controllers obtained under the Gaussian noise *** main contribution of the paper is the solution ***,optimal controllers for decentralized LQ systems are identified using dynamic programming,maximum principle,or spectral *** authors present an alternative approach which is based by combining elementary building blocks from linear systems,namely,completion of squares,state splitting,static reduction,orthogonal projection,(conditional)independence of state processes,and decentralized estimation.

关键词： Decentralized estimation decentralized stochastic control linear quadratic systems team theory

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