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检索条件"任意字段=International Conference on Computer Engineering and Technology"

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A Comparative Study of CNN and Transformer Models for Image Recognition in Autonomous Driving 2

A Comparative Study of CNN and Transformer Models for Image ...

引用

2nd international conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Gupta, Rahul Singh, Shashank Yadav, Vandana Dhanda, Namrata Sharma, Pakhi Monad University U.P. Hapur India Department of Computer Science & Engineering S.R. Institute of Management & Technology Lucknow India Department of Computer Science & Engineering Amity University U.P. Lucknow India

ISBN: (纸本)9798331530389

An autonomous driving system requires efficient image recognition to interpret the environment, detect obstacles, and make real-time decisions. This study compares Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) for image recognition tasks in autonomous driving. CNNs achieve higher accuracy (92.5% vs. 91.2%) and faster inference times (25ms vs. 35ms), making them more suitable for real-time applications. ViTs, however, perform better in challenging conditions, such as low lighting and occlusions, by capturing detailed information across entire images. The findings suggest that both architectures offer distinct advantages and could be combined to enhance the reliability and efficiency of autonomous driving systems. © 2025 IEEE.

关键词： Convolutional neural networks

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Research on Remaining Lifetime Prediction of IGBT Using LSTM Neural Network Optimized by an Improved Snake Optimization Algorithm 24

Research on Remaining Lifetime Prediction of IGBT Using LSTM...

引用

8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Guo, Yuyang Du, Xianjun Lanzhou University of Technology Gansu Lanzhou China

ISBN: (纸本)9798400710094

This paper proposes a novel method for predicting the remaining lifetime of IGBT based on the publicly available NASA dataset. This approach utilizes the collector-emitter blocking voltage as a failure parameter and constructs a prediction model utilizing a Long Short-Term Memory (LSTM) neural network. To enhance the prediction performance, the snake optimization algorithm is introduced, and an improved method is proposed, which incorporates a K-means++ initialization strategy to initialize the population and introduces a non-uniform mutation strategy to address its limitations. Experimental results demonstrate that the improved model achieves high accuracy in predicting the remaining lifetime of IGBT, outperforming the other three comparison models. This study provides a new perspective for the field of IGBT remaining lifetime prediction, offers valuable insights for the stable operation of power electronic systems, and looks forward to further exploring and optimizing this model in future work. © 2024 Copyright held by the owner/author(s).

关键词： Insulated gate bipolar transistors (IGBT)

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Overview of spatial data management methods based on digital twins for airport construction 24

Overview of spatial data management methods based on digital...

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8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Sang, Hongxia Liang, Congshan Nie, Liangxue Zhao, Zihan Wang, Han Academy of Military Sciences Beijing China Geovis Technology Co. Ltd. Beijing China 93125 troops of PLA Jiangsu Xuzhou China

ISBN: (纸本)9798400710094

The command and resource scheduling capabilities of the airport serve as crucial support for rapid take-off and landing, as well as efficient aircraft operations, the future intelligent airport scheduling poses new requirements for airport construction, it is necessary to effectively manage and analyze the vast and complex airport spatial data. To this end, the digital twin spatial data management methods for airport construction are comprehensively studied, and three different types of storage systems, general parallel computing framework, multi source data association algorithm and real time data processing engine have developed in this article, that can realize the whole time and space multi-dimensional data fusion management and the association and fusion between multi-source heterogeneous data entities, solve the problem of managing and analyzing the huge spatial data of the airport, to provide technical support for space-air big data analysis and mining. © 2024 Copyright held by the owner/author(s).

关键词： Data fusion

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Patient-Centric Skill Evaluation in IoT-Based Surgical Training with Naive Bayes Algorithm for Personalized Feedback 2

Patient-Centric Skill Evaluation in IoT-Based Surgical Train...

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2nd international conference on computer, Communication and Control, IC4 2024

作者： Gopi, B. Ashfaqul Hasan, M.D. Kumar, G. Sivakumar, S. Raju, M. Janardhana Malathi, N. Department of Electronics and Communication Engineering Rasipuram Tamil Nadu India Narsampet Telangana Warangal India Malla Reddy Institute of Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad India Srm Institute of Science and Technology Faculty of Management Studies Kattankulathur Chenagalpattu Tamil Nadu Chennai India Department of Computer Science Tamil Nadu Perambalur India Siddartha Institute of Science and Technology Narayanavanam Andhra Pradesh Puttur India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387933

Internet of Things (IoT) technology has established essential in advancing surgical training, enabling more individualized and patient-centric methods. This paper proposes a unique framework for skill assessment in surgical training, concentrating on individualized feedback using the Naive Bayes algorithm. With the use of IoT technology, surgical simulators can now collect real-time data on trainee performance while also communicating patient-centric factors into account. The data is analyzed using the suggested Naive Bayes Algorithm, which places an emphasis on providing personalized feedback to individuals. The objective of this method is to improve surgical outcomes while simultaneously increasing surgeons' technical competence. The trainee's abilities are evaluated in a variety of ways by the algorithm, which takes into account accuracy, recall, and other metrics. It provides to the continuing attempts to establish more efficient and individualized training procedures using IoT-based surgical training combined with machine learning approaches. These results demonstrate the promise of the Naive Bayes algorithm for improving surgical outcomes via the delivery of actionable, personalized feedback to surgeons. © 2024 IEEE.

关键词： Internet of things

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Particle swarm optimised fuzzy PID control method for hybrid magnetic bearings 3

Particle swarm optimised fuzzy PID control method for hybrid...

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3rd international conference on Intelligent Mechanical and Human-computer Interaction technology, IHCIT 2024

作者： Xiong, Feng Han, Jinchang Xu, Wenhao Li, Yan Institute of Noise & vibration Naval University of Engineering Wuhan430033 China National Key Laboratory on Ship Vibration & Noise Wuhan China Science and Technology on System Design Technology Laboratory Nuclear Power institute of China Chengdu610213 China

ISBN: (纸本)9781510683105

To enhance the control effectiveness of hybrid magnetic bearings (HMBs), this paper proposes a PSO-based fuzzy PID control algorithm. The algorithm optimizes the fuzzy controller's output parameters using the Particle Swarm Optimization technique, effectively addressing the limitations caused by fixed parameters and improving control accuracy. The effectiveness of the PSO algorithm optimization is verified through simulations of a hybrid magnetic bearing system built in Simulink. Compared to the fuzzy PID control algorithm, this method demonstrates a faster response and smaller overshoot, achieving better results in controlling the vibration displacement of rotors supported by hybrid magnetic bearings. © 2024 SPIE.

关键词： Particle swarm optimization (PSO)

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E-Auction System of Agricultural Products Using Blockchain technology 4

E-Auction System of Agricultural Products Using Blockchain T...

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4th international conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Makka, Shanthi Reddy, S. Bharath Rautela, Kundan Singh Kaushal, Rajesh Kumar Charan, Vankadaru Vardhaman College of Engineering Computer Science and Engineering Telangana Hyderabad501218 India Kg Reddy College of Engineering and Technology Computer Science and Engineering Telangana India Computer Science and Engineering 201310 India Chitkara University Computer Science and Engineering Punjab India Vardhaman College of Engineering Information Technology Hyderabad India

ISBN: (纸本)9798350364729

Products generated by agricultural industries are bought and sold in the Agricultural Auction System. An online auction is a procedure where buyers and sellers may interact on a single platform and place bids within a certain time limit. Currently, Blockchain is quite popular technology due to its decentralized nature. Applications of Blockchain are widely used in industries ranging from Agriculture to Medical. Blockchain can be used to make the food supply chain transparent. By eliminating third party intervention, the decentralized Blockchain based electronic auction system improves the auction process while enhancing security and efficiency. Building trust between vendors, buyers, and auctioneers is challenging in centralized auctions, where websites or platforms collect bids and determine auction results. These systems demonstrate a lack of transparency and anonymity, making them unreliable. In order to perform the transactions between the seller and the buyers safely and securely and without the involvement of unreliable third parties, a broad architecture for decentralized auctions that is utilized to track and trace bids is required. In this paper, we provide an extensive review of Blockchain based auction systems and a framework is designed for privacy preserving auction system using solidity based smart contracts implemented on Ethereum test network. This method, known as "Agro auction system using Blockchain,"improves the supply, trading, and security of agricultural products. This effort creates the groundwork for future studies to develop all encompassing, end-to-end agricultural auction solution. © 2024 IEEE.

关键词： Smart contract

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Anomalous Magnetoresistance of Polysilicon Films in SemOI-Structures 17

Anomalous Magnetoresistance of Polysilicon Films in SemOI-St...

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17th IEEE international conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Lisnykh, Demian Khoverko, Yuriy Druzhinin, Anatoly Kogut, Igor Lviv Polytechnic National University Department of semiconductor electronics Lviv Ukraine Vasyl Stefanyk Precarpathian National University Department of Computer Engineering and Electronics Ivano-Frankivsk Ukraine

ISBN: (纸本)9798331520564

The paper analyzes the experimental data on the magnetic transport properties of polycrystalline silicon in silicon-on-insulator structures at cryogenic temperatures in strong magnetic fields up to 14 T. The peculiarities of the behavior of the magnetoresistance of SemOI structures depending on the concentration of the main charge carriers, which is in the range from 2.4 × 1018 to 1.7 × 1020 cm-3, covering the interval of the metal-dielectric phase transition in silicon, are established. Taking into account the contribution of intergranular boundaries as a paramagnetic component, the regularities of the electrophysical characteristics of poly-Si in the presence of spin moment at grain boundaries are determined, which is manifested in an anomalous positive magnetoresistance within the polarization conductivity, which reaches ≈20% without saturation with increasing magnetic field induction to 14T. © 2024 IEEE.

关键词： Silicon on insulator technology

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Thai Herbs Recommendation Model 9

Thai Herbs Recommendation Model

引用

Joint 9th international conference on Digital Arts, Media and technology with 7th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Kantawong, Krittika Yaibuates, Mayoon Sookying, Sontaya Pravesjit, Sakkayaphop University of Phayao School of Information and Communication Technology Phayao Thailand Chiang Rai Rajabhat University Faculty of Digital Technology Chiang Rai Thailand University of Phayao School of Pharmaceutical Sciences Phayao Thailand

ISBN: (纸本)9798350318241

This work proposes a Thai herbs recommendation model to recommend appropriate Thai herbs to users. Herbs data was collected from available data sources including books, websites, and publication documents. All data were integrated, cleaned, and transformed before transfer to the herbs database. The rule-based was produced based on herbs properties for various symptoms. Then, the best Thai herbs were given based on the specific condition of the user. The overall model evaluation was compared with solutions from the National List of Essential Drugs A.D. 1999 (List of herbal medicine products) given 0.77 precision, 1.00 recall, and 0.87 F-measure. © 2024 IEEE.

关键词： Recommender systems

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Low Voltage Feedback Based Folded Flipped Source Follower for Wide Operating Range

Low Voltage Feedback Based Folded Flipped Source Follower fo...

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2024 IEEE international Women in engineering (WIE) conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Dadheech, Astha Raj, Nikhil Rawal, Divyang The Lnm Institute of Information Technology Department of Ece Jaipur India

ISBN: (纸本)9798331535476

In this paper, a novel cascoded-based folded flipped source follower (CFFSF) with a super transistor stage is presented. The CFFSF circuit demonstrates excellent DC transfer characteristics, with the output voltage accurately tracking the input voltage over a specified range. A folded transistor provides an alternative path for sourcing current, enabling the achievement of the desired low output resistance. The inclusion of the super transistor stage enhances both the input and output voltage swing of 0.42V and 0.278V while significantly reducing output resistance of 166Ω. The presented CFFSF architecture has been designed in Cadence Virtuoso Analog Design Environment (ADE) using United Microelectronics Corporation (UMC) 180 nm Complementary MOS technology with a dual power supply voltage of ±0.5V. © 2024 IEEE.

关键词： Cascode amplifiers

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Adversarial Attacks and Defenses Using Machine Learning for Cybersecurity in Corporates

Adversarial Attacks and Defenses Using Machine Learning for ...

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2024 international conference on Distributed Systems, computer Networks and Cybersecurity, ICDSCNC 2024

作者： Gopinath, R. Sathiyamoorthy, C. Sugumaran, D. Giriprasath, K.S. Tripathi, Neha Arif, Mohammad K S.Rangasamy College of Technology Department of Computer Science and Engineering Tamil Nadu India Saveetha College of Liberal Arts and Sciences Department of Commerce Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Information Technology Tamil Nadu Chennai India Psg Institute of Technology and Applied Research Department of Computer Science and Engineering Tamil Nadu Coimbatore India Graphic Era Deemed to Be University Uttarakhand Dehradun India Vellore Institute of Technology School of Computer Science & Engineering Tamil Nadu Vellore India

ISBN: (纸本)9798350375442

This article suggests a novel method for protecting corporate cybersecurity systems from malevolent attacks, based on Capsule Networks (CapsNets). The enhancement of hierarchical feature learning by Capital Networks is a critical component of its capacity to differentiate between authentic and fraudulent data. Robust optimization techniques and adversarial training are implemented to develop a model. The training seeks to be more resilient and beneficial in a larger environment by introducing perturbations one capsule at a time. CapsNets executed an effective operation, achieving 95% accuracy and 97% precision. In terms of managing adversarial assaults, CapsNets outperform baseline models greatly. The proposed approach exhibits potential as an improved cybersecurity defense method, as a result of its exceptional resilience and precision. This study demonstrates the efficacy of CapsNets in improving cybersecurity and also offers a glimpse into the adversarial defenses used in enterprise machine learning applications. © 2024 IEEE.

关键词： Adversarial machine learning

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