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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Priya, r. Krishna Aanandha Saravanan, K. Gadgil, Aashish A. Sabarmathi, K.r. Niranjanamurthy, M. Azarudeen, K. Department of Engineering-Electrical section College of Engineering and Technology University of Technology and Applied Sciences Shinas Oman Department of ECE Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and technology Chennai India Department of ECE KLS GOGTE institute of Technology Karnataka Belagavi India Department of Information Technology Bannari Amman Institute of Technology Tamilnadu Sathyamangalam India Department of AI and ML BMS Institute of Technology and Management Avalahalli. Karnataka Bangalore India Department of Computer Science and Engineering Velammal College of Engineering and Technology Madurai India

ISBN: (纸本)9798350305418

With the popularity of languages and the increasing demand for language translation, the optimization of artificial intelligence scoring algorithm for English translation has become the urgent need of the translation market. Based on the deep neural network(dNN) algorithm, it continuously integrates modern technology to realize information collection, storage, analysis and application, which promotes the deep integration of the dNN algorithm in the field of intelligent identification and expands the application scope of artificial intelligence identification technology. This paper focuses on how to efficiently optimize the model of English translation artificial intelligence scoring algorithm by dNN, specifically studying the dNN model, by studying the mathematical model and algorithm flow of the dNN optimization algorithm, and the basic principle of the dNN model;Based on the dNN model, a learning ability analysis model of English translation algorithm is proposed. Experiments show that this model can optimize the artificial intelligence scoring algorithm of English translation. © 2023 IEEE.

关键词： Artificial intelligence scoring algorithm dNN English translation

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deep Learning for Ocular disease Classification: A Study on OdIr-5K dataset

Deep Learning for Ocular Disease Classification: A Study on ...

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Artificial Intelligence, Applications, Innovation and Ethics (AI2E), International Conference for

作者： Suresh rasappan S. Ahamed Nishath Sathish Kumar Kumaravel regan Murugesan Kala raja Mohan Nagadevi Bala Nagaram Mathematics Department University of Technology and Applied Sciences-Ibri Ibri Sultanate of Oman Information Technology Department College of Computing and Information Sciences University of Technology and Applied Sciences-Ibri Ibri Sultanate of Oman Department of Mathematics Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Mathematics Panimalar Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798331513733

ISBN: (纸本)9798331513740

This research investigates the utilization of deep learning methodologies for classifying ocular dis-eases using the OdIr-5K dataset. A tailored convolutional neural network (CNN) architecture is developed to categorize fundus images into five distinct classes: diabetes, glaucoma, cataract, age-related macular de-generation, and normal. Notably, experimental outcomes achieve a 96.32 % accuracy rate, underscoring the effi-cacy of deep learning in ocular disease diagnosis.

关键词： deep learning Glaucoma Technological innovation Accuracy Systematics Feature extraction Convolutional neural networks Medical diagnosis Optimization diseases

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Comparative study of Mechanical and Electrical Characteristics on High-Strength Steel and Conventional Steel for EV Traction High-Speed Multilayer IPMSM Using rare-Earth Free PM

Comparative study of Mechanical and Electrical Characteristi...

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Magnetic Conference - Short Papers (INTErMAG Short Papers), IEEE International

作者： Ki-O Kim Young-Hoon Jung Jin-Cheol Park Myung-Seop Lim Department of Automotive Engineering Hanyang University Seoul Republic of Korea R&D Division Hyundai Motor Company Hwaseong Republic of Kores Robot Business Team Samsung Electronics Co. Ltd. Suwan-si Republic of Korea

In this article, the electrical and mechanical characteristics are compared with multilayer IPMSM (ML-IPMSM) using ferrite permanent magnet (PM) when driven at high-speed according to electrical steel. In high-speed operation, in the case of ML-IPMSM, the mechanical and electrical characteristics change depending on the number of PM layers, PM shape, the number of bridges, and bridge thickness. In addition, ferrite PM has a lower coercive force than Nd PM, therefore irreversible demagnetization (Id) must be considered, and it is affected by the number of layers and PM shape of ML-IPMSM. Therefore, when designing a multilayer IPMSM using ferrite PM for electrical vehicle (EV) traction, all the characteristics must be considered. Compared to conventional electrical steel (CES), High-strength electrical steel (HSES) has advantages in mechanical properties, allowing the ML shape to be relatively free. Accordingly, it is possible to design a shape that is advantageous in electrical performance compared to CES by adjusting ML shape. In this article, all characteristics of each ML-IPMSM applied with HSEC and CES are reviewed through finite element analysis (FEA), and the advantages of HSEC applied motors for high-speed driving motors are presented. To verify the validity of the review contents of this article, experiments are conducted on the manufactured motor, FEA results are compared with the test results.

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A Study of Stochastic Ecological Model with Prey Harvesting as a Tool of disease Control 1

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1st International Conference on Mathematical Modeling and Computational Science, ICMMCS 2020

作者： Vijaya Lakshmi, G.M. rasappan, Suresh rajan, Pugalarasu Department of Mathematics Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi Tamil Nadu600062 India Department of Information Technology University of Technology and Applied Sciences - Ibri Ibri Oman

ISBN: (数字)9789813343894

ISBN: (纸本)9789813343887

This study explores the hierarchical dynamics of a predator model in which the population of prey is comprised of two classes: susceptible and infected (SI) prey including the non-selective prey harvesting. The system’s points of equilibrium are found. The model’s stability properties were tested by both locally and globally. Next, we have implemented the stochastic perturbations and indicated that the deterministic model of stochastic perturbations is robust. The stochastic perturbations effects on the dynamics were discussed via simulations. The deterministic method results in a stochastic system with an effect of atmospheric random noise were presented. That is, we have explored the SI prey–predator model’s stability incorporating prey harvesting by introducing stochastic perturbations that were not previously studied. Finally, some numerical examples and diagrams help our complex dynamics of our model using time series diagrams and phase portraits which supports our theoretical results. Parallel to this, we presented the time series diagram and phase portraits for the stochastic perturbation system. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： disease control

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Business Process Automation using robotic Process Automation (rPA) and AI Algorithm's on Various Tasks 8

Business Process Automation using Robotic Process Automation...

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8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： dandale, M.N. Mazharunnisa daniel, d. J. Joel devadass Priya, r. Sathya Walid, Md. Abul Ala Thulasimani, T. Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities Maharashtra Nagpur India Koneru Lakshmaiya Educational Foundation Kl University Kl Business School Vijayawada Andhra Pradesh Vaddeswaram India VelTech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Tamilnadu Chennai India Knowledge Institute of Technology Department of Cse Tamilnadu Salem India Department of Computer Science and Engineering Bangladesh Bannari Amman Institute of Technology Mathematics Tamilnadu Erode India

ISBN: (纸本)9798350396638

robotic Process Automation (rPA) bots automate mundane, rules-based operations, allowing workers more time to focus on high-level, strategic projects. Meanwhile, AI be used to analyze data and spot trends, resulting in better choices and increased productivity for enterprises. Previous researches are less efficient, slowly working algorithms when classification is performed in a large set of databases. The existing methods could be doing better while comparing the error factors, and in the cross-verification process, they have made inappropriate results, leading to wrong classifications. robotic Process Automation (rPA) bots automate mundane, rules-based operations, allowing workers more time to focus on high-level, strategic projects. Meanwhile, AI be used to analyze data and spot trends, resulting in better choices and increased productivity for enterprises. Previous research on email automation and invoice process automation have needed to improve classification model efficiency and they have less efficient, slowly working algorithms when doing classification in a large set of databases. In this work, the random Forest algorithm is used for classification, and the Quest method is used to segment texts in emails and invoices, both of which can be automated more effectively. The results of existing categorization algorithms have been less than ideal, especially when used to huge datasets, and are often completely inaccurate. The suggested method outperforms previous ML/AI approaches because it produces highly accurate outcomes with little resource investment. There are a number of benefits to utilizing rPA with AI, such as cost reduction, increased output, and streamlined operations. The advantages of this automation, challenges that must be met, and potential answers to those questions are discussed in this study. © 2023 IEEE.

关键词： Support vector machines

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Wireless Simulator: Empowering remote Operations By demystifying Modulation Techniques

Wireless Simulator: Empowering Remote Operations By Demystif...

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International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)

作者： d Ferlin deva Shahila Joel Livin P Aruna Jeyanthy Valantina Stephen Yarragolla Venkata Sai Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India University of Technology and Applied Sciences Sultanate of Oman Department of EEE Kalasalingam Academy of Research and Education Tamil Nadu India Department of EEE Saveetha School of Engineering Thandalam Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

Light Emitting diodes (LEds), which are extremely efficient and long-lasting, have been created as a result of technological developments in solid-state lighting. Along with becoming increasingly popular for use in traditional lighting, these LEds are also being investigated for a cutting-edge use in Visible Light Communication (VLC). Utilising a VLC transmission system, VLC has the potential to be a practical access technique for vehicular networking. The GNU radio framework, which was used to build Universal Software radio Peripheral software-defined radios, serves as the system's foundation. With a photodiode serving as the receiver and a conventional automobile lamp acting as the sender. Applications for vehicle networking can greatly benefit from the many features that VLC offers. Our system also accommodates a number of modulation techniques, such as OOK (On-Off Keying), ASK (Amplitude Shift Keying), FSK (Frequency Shift Keying), and PSK (Phase Shift Keying). Modelling of the system's performance has shown outstanding distance dependability independent of the time of day in terms of Signal-to-Noise ratio (SNr) and Bit Error rate (BEr).

关键词： Wireless communication Phase shift keying System performance Bit error rate Amplitude shift keying Frequency shift keying Light emitting diodes Visible light communication Software radio Signal to noise ratio

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GLOBAL SOLUTIONS ANd UNIFOrM CONVErGENCE STABILITY FOr COMPrESSIBLE NAVIEr-STOKES EQUATIONS WITH OLdrOYd-TYPE CONSTITUTIVE LAW

arXiv

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arXiv 2024年

作者： Boyaval, Sebastien Hu, Yuxi Wang, Na School of Applied Science Beijing Information Science and Technology University Beijing100192 China Ecole des Ponts ParisTech EDF R&D Chatou & Matherials Inria Paris France Department of Mathematics China University of Mining and Technology Beijing100083 China

We consider one dimensional isentropic compressible Navier-Stokes equations with Oldroyd-type constitutive law. By establishing uniform a priori estimates (with respect to relaxation time), we show global existence of smooth solutions with small initial data. Moreover, we get global-in-time convergence of the system towards the classical isentropic compressible Navier-Stokes equations. Copyright © 2024, The Authors. All rights reserved.

关键词： Viscous flow

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Future Prospects of Large Language Models: Enabling Natural Language Processing in Educational robotics

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2024年第23期18卷 85-97页

作者： Vinoth Kumar, S. Saroo raj, r.B. Praveenchandar, J. Vidhya, S. Karthick, S. Madhubala, r. Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of IT Rajalakshmi Engineering College Tamil Nadu Chennai India Tamil Nadu Coimbatore India Department of Information Science and Engineering The Oxford College of Engineering Karnataka Bangaluru India Information Technology Department University of Technology and Applied Sciences Shinas Oman

Large language models (LLMs) have recently shown considerable promise in educational robotics by offering generic knowledge necessary in situations when prior programming is not possible. In general, mobile education robots cannot perform tasks like navigation or localization unless they have a working knowledge of maps. In this letter, we tackle the issue of making LLMs more applicable in the field of mobile education robots by helping them to understand Space Graph, a text-based map description. This study, which focuses on LLMs, is divided into several sections. It explores basic natural language processing (NLP) techniques and highlights how they can help create smooth education discussions. Examining the development of LLMs inside NLP systems, the paper explores the benefits and implementation issues of important models utilized in the education sector. Applications useful in educational discussions are described in depth, ranging from patient-focused tools like diagnosis and treatment recommendations to systems that support education providers. We provide thorough instructions and real-world examples for quick engineering, making LLM-based educational robotics solutions more accessible to novices. We demonstrate how LLM-guided upgrades can be easily included in education robotics applications using tutorial-level examples and structured prompt creation. This survey provides a thorough review and helpful advice for leveraging language models in automation development, acting as a road map for researchers navigating the rapidly changing field of LLM-driven educational robotics. © 2024 by the authors of this article.

关键词： Motion planning

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Smart Soft Sensor for Froth flotation quality monitoring using pre-trained feature extractor and Vision Transformer ViT 17

Smart Soft Sensor for Froth flotation quality monitoring usi...

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17th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2023

作者： Hasidi, Oussama Bendaouia, Ahmed Abdelwahed, El Hassan Abdellah, El Alaoui-Chrifi Moulay Boussetta, Abdelmalek Benzakour, Intissar Bourzeix, Francois Oubouhss, Kaotar Mohammed Vi Polytechnic University Lisi Laboratory Computer Science Departement Uca Analytics Lab Marrakech Morocco Cadi Ayyad University Lisi Laboratory Computer Science Departement Marrakech Morocco Reminex Managem Group R&d and Engineering Center Marrakech Morocco Mohammed Vi Polytechnic University Analytics Lab Rabat Morocco National School of Applied Science Uae Department of Electrical and Industrial Engineering Tangier Morocco

ISBN: (纸本)9798350370911

Smart sensor technologies have gained prominence in the field of machine vision-based applications. Within this context, the utilization of machine vision systems for monitoring and controlling flotation plants has become increasingly prevalent. This paper addresses the critical need for accurate froth image classification in the development of an online machine vision-based control system. This paper explores the recent advancements in machine learning, with a focus on deep learning techniques. Specifically, it introduces the application of a Vision Transformer (VIT) model as an alternative to the traditional Convolutional Neural Network (CNN) for classifying froth images collected from an industrial lead flotation circuit. The results of this research demonstrate the remarkable performance of the ViT model, achieving an impressive overall accuracy rate of 96% when combined with pre-trained feature extractor models. This achievement surpasses the capabilities of conventional artificial neural network (CNN) classifiers of the state of art in terms of both accuracy and computational efficiency. These findings underscore the promising potential of deep learning neural networks in froth image analysis, highlighting their significance in the advancement of smart sensor-based machine vision systems within the field of flotation plant control. © 2023 IEEE.

关键词： Computer vision

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The effect of TiO2 film on the surface roughness and optical properties of Mo/Si periodic films by atomic layer deposition

The effect of TiO2 film on the surface roughness and optical...

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International Conference on Extreme Ultraviolet Lithography 2024

作者： Lee, Chao-Te Cho, Wen-Hao Chen, Wei-Chun Shew, Bor-Yuan Chen, Hung-Pin Jaing, Cheng-Chung Lee, Chien-Lin Tsai, Kuen-Yu Taiwan Instrument Research Institute National Applied Research Laboratories 20 R&D Rd. VI Hsinchu Science Park Hsinchu300092 Taiwan National Synchrotron Radiation Research Center 101 Hsin-Ann Road Hsinchu Science Park Hsinchu30076 Taiwan Department of Semiconductor and Electro-Optical Technology Minghsin University of Science and Technology 1 Xinxing Rd. Xinfeng Township Hsinchu30401 Taiwan Department of Electrical Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei106319 Taiwan

ISBN: (数字)9781510681569

ISBN: (纸本)9781510681552

In this work, the TiO2 film was deposited on periodic Mo/Si bilayer at various temperatures (70~90 oC) by atomic layer deposition (ALd). The H2O and Tetrakis(dimethylamino)titanium (TdMAT) were be used for precursors. Effects of substrate temperature and thickness of TiO2 film on the microstructure, surface roughness, and optical properties were investigated by field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), high resolution transmission electron microscope (HrTEM), and extreme ultraviolet (EUV) spectrometer, respectively. It was found that the surface roughness of the TiO2 film at substrate temperature 70 oC was obviously larger than the others. The surface roughness of TiO2 film was under 0.2 nm at the substrate temperature was above 80 oC. The reflectivity of periodic Mo/Si bilayer was 66% by EUV spectrometer. We found that the reflectivity of Mo/Si/TiO2 films was decreased with increased the thickness of TiO2 film. The reflectivity of the films was maintain 65.97% as the TiO2 film was 1.8 nm. However, the reflectivity of the films was decreased to 59.27% when the TiO2 film was 3nm. Based on the results of the reflectivity investigation, the TiO2 thin film by ALd as the protective film for highly reflective EUV mirror was been confirmed. © 2024 SPIE.

关键词： Field emission microscopes

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