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25th IEEE International Conference on Industrial technology, ICIT 2024

作者： Zar, Abu Nawazish Ali, S.M. Jalili, Mahdi School of Electrical Engineering and Computer Science National University of Sciences and Technology IslamabadH-12 Pakistan School of Electrical Engineering RMIT University Victoria3001 Australia

In response to the escalating impact of the greenhouse effect on Earth's climate, electric vehicles (EVs) have emerged as a pivotal solution for sustainable transportation. This research addresses a critical challenge to the widespread EV adoption, focusing on the efficient integration of EV chargers with existing electricity grids. A novel robust 'Terminal Conditioned Super-Twisting Sliding Mode Controller' (TC-ST-SMC) is proposed for the control of the power flow in bidirectional EV charging modes from grid to vehicle (G2V) and vehicle to grid (V2G). The novel contribution lies in tuning these controllers using a reinforcement learning (RL) based Deep Q-Network (DQN) agent. The global asymptotic stability of the proposed mathematical framework is validated using Lyapunov stability criteria which presents a significant step forward in achieving efficient and robust control for EV chargers. The proposed mathematical model of EV charger and its controller design underwent tuning and simulation in MATLAB/Simulink® (2023b) environment. Finally, hardware-in-loop (HIL) based experimental results verify the proposed framework and its realtime control. © 2024 IEEE.

关键词： Sliding mode control

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Unveiling Sentiments: Exploring Tweet and Text Analysis for Deeper Insights

Unveiling Sentiments: Exploring Tweet and Text Analysis for ...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Ranjan, Ritik Karthik, N. Vani, V. National Institute of Technology Puducherry Department of Electrical and Electronics Engineering Karaikal India National Institute of Technology Puducherry Department of Computer Science and Engineering Karaikal India

ISBN: (数字)9798331540685

ISBN: (纸本)9798331540685

This work presents a comprehensive exploration of sentiment analysis on social media data, with a specific focus on Twitter. The study evaluates three state-of-the-art classifiers-Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF)-to categorize sentiments (positive, negative, neutral) based on specific criteria. Data cleansing and classification methods are applied to extract meaningful insights from unstructured social media data. Results show that SVM achieves the highest accuracy (92.67%) among the classifiers. It also discusses the strengths and limitations of each classifier in capturing the nuances of sentiment expressions. This work contributes to the understanding of sentiment analysis techniques on social media platforms © 2024 IEEE.

关键词： Tweets

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Real Eventual Exponential Positivity of Complex-valued Laplacians: Applications to Consensus in Multi-agent Systems 10

Real Eventual Exponential Positivity of Complex-valued Lapla...

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10th Indian Control Conference, ICC 2024

作者： Saxena, Aditi Tripathy, Twinkle Anguluri, Rajasekhar The Department of Electrical Engineering Indian Institute of Technology Kanpur India The Department of Computer Science and Electrical Engineering University of Maryland Baltimore CountyMD85281 United States

ISBN: (纸本)9798331517212

In this paper, we explore the property of eventual exponential positivity (EEP) in complex matrices. We show that this property holds for the real part of the matrix exponential for a certain class of complex matrices. Next, we present the relation between the spectral properties of the Laplacian matrix of an unsigned digraph with complex edge-weights and the property of real EEP. Finally, we show that the Laplacian flow system of a network is stable when the negated Laplacian admits real EEP. Numerical examples are presented to demonstrate the results. © 2024 IEEE.

关键词： Multi agent systems

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Impact of Lightning Impulse on the Performance of Microgrid and Low-voltage AC Distribution Network 13

Impact of Lightning Impulse on the Performance of Microgrid ...

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13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024

作者： Kaushal, Jitender Basak, Prasenjit Apex Institute of Technology Chandigarh University Department of Computer Science Punjab Mohali India Thapar Institute of Engineering and Technology Department of Electrical and Instrumentation Engineering India

ISBN: (纸本)9798350305463

A photovoltaic (PV) generator integrated low voltage (LV) distribution system may be affected by lightning strikes due to thunderstorms. In this paper, a PV generatorintegrated LV distribution network is considered to analyse the effect of lightning causing the generation of a travelling wave. The lightning impulse is modelled and simulated at various locations of the proposed model. The voltage and current profiles due to the injection of lightning impulse have been analysed. The variations in frequency causing changes in impedance are also observed in the proposed model simulated using MATLAB-Simulink software. In addition, it is observed that the nominal voltage and current waveforms at different buses are affected by the lightning impulse voltage, and the impact of lightning voltage gradually decreases as the distance of the line from the point of lightning increases. This kind of simulation work of lightning impulse and its effect on power systems will be beneficial for the power system engineers/researchers at the level of research and development of protection systems of AC distribution networks/microgrids. The proposed methodology is reproducible for the analysis of lightning effects on grid-connected LV microgrid systems for any other models, irrespective of the nature of resources and their geographical locations. © 2024 IEEE.

关键词： Electric power distribution

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Retinal Blood Vessel Tracking and Diameter Estimation via Gaussian Process With Rider Optimization Algorithm

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IEEE Journal of Biomedical and health Informatics 2024年第3期28卷 1173-1184页

作者： Ahmad, Nehal Lai, Kuan-Ting Tanveer, M. Indian Institute of Technology Indore Simrol Department of Mathematics Indore453552 India National Taipei University of Technology Department of International Program of Electrical Engineering and Computer Science Taipei106 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei106 Taiwan

Retinal blood vessels structure analysis is an important step in the detection of ocular diseases such as diabetic retinopathy and retinopathy of prematurity. Accurate tracking and estimation of retinal blood vessels in terms of their diameter remains a major challenge in retinal structure analysis. In this research, we develop a rider-based Gaussian approach for accurate tracking and diameter estimation of retinal blood vessels. The diameter and curvature of the blood vessel are assumed as the Gaussian processes. The features are determined for training the Gaussian process using Radon transform. The kernel hyperparameter of Gaussian processes is optimized using Rider Optimization Algorithm for evaluating the direction of the vessel. Multiple Gaussian processes are used for detecting the bifurcations and the difference in the prediction direction is quantified. The performance of the proposed Rider-based Gaussian process is evaluated with mean and standard deviation. Our method achieved high performance with the standard deviation of 0.2499 and mean average of 0.0147, which outperformed the state-of-the-art method by 6.32%. Although the proposed model outperformed the state-of-the-art method in normal blood vessels, in future research, one can include tortuous blood vessels of different retinopathy patients, which would be more challenging due to large angle variations. We used Rider-based Gaussian process for tracking blood vessels to obtain the diameter of retinal blood vessels, and the method performed well on the 'STrutred Analysis of the REtina (STARE) Database' accessed on Oct. 2020 (https://***/~ahoover/stare/). To the best of our knowledge, this experiment is one of the most recent analysis using this type of algorithm. © 2013 IEEE.

关键词： Blood vessels

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COMPARATIVE STUDY OF MECHANICAL PERFORMANCE OF MICROWAVE-CURED AND AUTOCLAVE-CURED CARBON/EPOXY COMPOSITES 10

COMPARATIVE STUDY OF MECHANICAL PERFORMANCE OF MICROWAVE-CUR...

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10th Composites and Advanced Materials Expo, CAMX 2024

作者： Pundhir, N. Heskin, M. Luo, W. Chandrashekhara, K. Wilcox, L. Donnell, K. Department of Mechanical and Aerospace Engineering Missouri University of Science and Technology RollaMO65409 United States Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

ISBN: (纸本)9781934551462

The unique combination of properties offered by carbon fiber-reinforced polymer composites has led to their widespread adoption in aerospace, automotive, and other industries due to their high specific stiffness and strength properties. The present study investigates the potential of vacuum-assisted microwave curing for carbon fiber-reinforced polymer composites which presents several advantages over traditional autoclave curing methods. Microwave curing offers reduced cycle times, volumetric heating, enhanced safety, and lower energy consumption. This comprehensive approach evaluates the feasibility and efficacy of vacuum-assisted microwave curing for carbon fiber-reinforced polymer composites by comparing the manufactured composites against traditional autoclave composites. Mechanical properties and microstructural characteristics were measured and examined to accomplish this. In the present work, industrially available IM7/Cycom 5320-1 unidirectional prepreg with 33% resin by weight and a fiber area weight of 145 g/m2 is employed to manufacture the laminated composite. A sixteen-layer symmetric cross-ply ([00/900]4s) and quasi-isotropic ([450/900/-450/00]2s) laminated composites are manufactured using a custom-built microwave curing chamber. Mechanical characterization of the microwave-cured composite is conducted through uniaxial tensile and flexural tests, with subsequent comparison to autoclave-cured samples. Optical microscopy is employed to estimate the quality of the manufactured samples. The results obtained from this study support advancements in composite manufacturing processes, particularly in the aerospace and automotive sectors. Copyright 2024. Used by CAMX – The Composites and Advanced Materials Expo.

关键词： Laminated composites

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Active terahertz beam steering based on mechanical deformation of liquid crystal elastomer metasurface

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Light(science & Applications) 2023年第1期12卷 118-127页

作者： Xiaolin Zhuang Wei Zhang Kemeng Wang Yangfan Gu Youwen An Xueqian Zhang Jianqiang Gu Dan Luo Jiaguang Han Weili Zhang Center for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronic Information TechnologyMinistry of EducationTianjin University300072 TianjinChina Department of Electrical and Electronic Engineering Southern University of Science and Technology518055 ShenzhenChina School of Electrical and Computer Engineering Oklahoma State UniversityStillwaterOK 74078USA

Active metasurfaces are emerging as the core of next-generation optical devices with their tunable optical responses and flat-compact *** for the terahertz band,active metasurfaces have been developed as fascinating devices for optical chopping and compressive sensing ***,performance regulation by changing the dielectric parameters of the integrated functional materials exhibits severe limitations and parasitic ***,we introduce a C-shape-split-ring-based phase discontinuity metasurface with liquid crystal elastomer as the substrate for infrared modulation of terahertz ***-focused infrared light is applied to manipulate the deflection of the liquid crystal elastomer substrate,enabling controllable and broadband wavefront steering with a maximum output angle change of 22°at *** as another control method is also investigated and compared with infrared *** further demonstrate the performance of liquid crystal elastomer metasurface as a beam steerer,frequency modulator,and tunable beam splitter,which are highly desired in terahertz wireless communication and imaging *** proposed scheme demonstrates the promising prospects of mechanically deformable metasurfaces,thereby paving the path for the development of reconfigurable metasurfaces.

关键词： tunable modulator beam

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A Comparative Study of DeepLabCut and Other Open-Source Pupillometry Data Analysis Algorithms – Which to Choose?

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Machine Graphics and Vision 2024年第2期33卷 77-90页

作者： Badkul, Amitesh Mishra, Sonakshi Kommajosyula, Srinivasa P. Department of Electrical & Electronics Engineering Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Department of Pharmacy Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Ph.D. Program in Computer Science The Graduate Center The City University of New York New YorkNY United States

Pupillometry measures pupil size, and several open-source algorithms are available to analyse pupillometry data. However, only a few studies compared these algorithms’ accuracy and computational resources. This study aims to compare the accuracy of computer vision-based algorithms (Swirski, Starburst, PuRe, ElSe, ExCuSe algorithms) and the machine learning algorithm, DeepLabCut, to the double-blinded human examiners (gold-standard). Training of DeepLabCut with different architectures and a variable number of markers (2-9 markers) was done on an open-source dataset. The duration of training was statistically longer for the ResNet152 model compared to the MobileNet model. The pupil diameters in computer vision-based software such as PuRe, Starburst, and Swirski were statistically different from human measurements. MobileNet 2 and 3 marker models were the closest to the human measurements. In conclusion, this work highlights the efficiency of lower marker models based on MobileNet architecture in DeepLabCut, which consumes fewer computational resources and is more accurate. © 2024 Institute of Information technology, Warsaw University of Life sciences - SGGW. All rights reserved.

关键词： Adversarial machine learning

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SCCNet: An Improved Multi-Class Skin Cancer Classification Network using Deep Learning 3

SCCNet: An Improved Multi-Class Skin Cancer Classification N...

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3rd International Conference on Advancement in electrical and Electronic engineering, ICAEEE 2024

作者： Ahmed, Tanvir Mou, Farzana Sharmin Hossain, Amran Dhaka University of Engineering & Technology Department of Computer Science and Engineering Gazipur Bangladesh Brunel University Department of Electronic and Electrical Engineering London United Kingdom

ISBN: (纸本)9798350388282

Skin cancer is the most prevalent type of cancer worldwide, and detecting it early is crucial to a successful course of treatment. In recent years, machine learning methods have demonstrated great potential for making skin cancer detection simpler. Using a model of the fine-tuned Skin Cancer Classification Network (SCCNet) based on deep learning, we proposed a unique method for classifying skin cancer into multiple categories in this research, which is comprised of the Xception deep learning model and additional four types of fine-tuned layers. The proposed model was trained by the publicly available skin cancer dataset ISIC-2018. The dataset consists of seven classes and 21,000 images after data augmentation, with 3,000 images in each class. The proposed model achieved an accuracy, precision, recall, and F1-score of 95.20%, 95.14%, 95.00%, and 95.14% respectively, for seven-class classification. The proposed SCCNet model, achieved an impressive accuracy of 95.20% in the classification of multiple skin cancer classes, outperforms several state-of-the-art approaches, demonstrating its potential to enhance dermatological diagnostics and guide effective therapeutic interventions for patients with skin cancer. © 2024 IEEE.

关键词： Diseases

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Machine Translation for Morphologically Rich Low-Resourced South African Languages 4

Machine Translation for Morphologically Rich Low-Resourced S...

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4th International Multidisciplinary Information technology and engineering Conference, IMITEC 2024

作者： Masethe, Hlaudi Daniel Mothapo, Lawrence M Ojo, Sunday O. Owolawi, Pius A. Masethe, Mosima Anna Giunchigilia, Fausto Tshwane University of Technology Department of Data Science South Africa Durban University of Technology Department of Information Technology South Africa Tshwane University of Technology Department of Computer Engineering South Africa Sefako Makgatho Health Sciences University Department of Computer Science and Information Technology South Africa University of Trento Department of Information Engineering and Computer Science Italy

ISBN: (纸本)9798350387988

In the context of machine translation, many of South Africa's languages are categorized as low-resourced, despite the country's vast linguistic diversity. Creating efficient multilingual translation systems that can support languages like Afrikaans, Sesotho sa Leboa (Sepedi), isiNdebele, Setswana, isiXhosa, Xitsonga, siSwati and isiZulu are severely hampered by the lack of high-quality training data. Low translation accuracy and fluency are the result of existing translation models' frequent inability to perform well in these languages. As a result, speakers of these languages encounter difficulties using increasingly accessible online resources for information and services. By utilizing the MarianMT model to create a reliable multilingual machine translation system, this work seeks to address these issues by enhancing the quality of translation for South African languages with limited resources. This study presents a comprehensive approach to multilingual machine translation focused on low-resourced South African languages, utilizing the MarianMT model. Our objective was to enhance translation quality for languages with limited training data, including Afrikaans, Sesotho sa Leboa (Sepedi), isiNdebele, Setswana, IsiXhosa, Xitsonga, siSwati and isiZulu. We conducted extensive experiments, resulting in a BLEU score of 62%, indicating a significant improvement in translation. Our evaluation metrics demonstrated strong performance, with precision at 78%, recall at 81%, F1 score at 79%, and overall accuracy at 82%. © 2024 IEEE.

关键词： Neural machine translation

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