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Design of GaN Buck Converter using Geometric Programming

Design of GaN Buck Converter using Geometric Programming

引用

2024 international conference on Control, automation and Diagnosis, ICCAD 2024

作者： Lambada, Puneeth Raj Wang, Xin Southern Illinois University Electrical and Computer Engineering EdwardsvilleIL62026 United States

ISBN: (纸本)9798350361025

This paper delves into the design of a Gallium Nitride (GaN) based medium-frequency synchronous buck converter employing geometric programming (GP). GaN Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) are chosen for this configuration due to their minimized switching losses. The optimization process encompasses various constraints, such as current and voltage ripples, bandwidth, inductor dimensions, temperature, and magnetic flux density. The cost function is defined as total losses. The inductor utilized in this design features a homothetic shape and incorporates an air gap. The utilization of GP is advantageous for efficiently addressing problems with numerous variables, ensuring that the solution obtained is the global optimum if it exists. The paper aims to determine the values of the operating frequency, capacitor, inductor, and the dimensions of the inductor within this context. © 2024 IEEE.

关键词： Gallium nitride

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Enhancing the Recommender System Algorithm's Quality Through the Utilization of Affinity Analysis 16

Enhancing the Recommender System Algorithm's Quality Through...

引用

16th IEEE international Scientific and Technical conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Stubarev, Igor M. Alsova, Olga K. Yakimenko, Alexander A. Novosibirsk State Technical University Faculty of Automation and Computer Engineering FB Consult Novosibirsk Russia Novosibirsk State Technical University Faculty of Automation and Computer Engineering Novosibirsk Russia Novosibirsk State Technical University Faculty of Automation and Computer Engineering Institute of Computational Mathematics and Mathematical Geophysics SB RAS Laboratory of Geophysical Informatics Novosibirsk Russia

ISBN: (纸本)9798350330885

The demand for auxiliary systems that utilize methods and technologies of intellectual data analysis and machine learning is increasing in the CRM system development field. These systems are capable of generating valuable insights from vast amounts of data collected in CRM. The article shows the results of the development and study of the CRM system using the methods of affinity analysis. Earlier, the authors developed and implemented the base version of the recommender algorithm based on the use of cluster data analysis and collaborative filtration [1, 2]. The new version of the algorithm additionally uses affinity analysis methods to form recommendations for the selection of products, which made it possible to increase the accuracy of the recommendation system (service) by metrics F2 on average from 67.98% to 81.24% with an increase in the time for issuing recommendations (On average by 2.47 ms). The study and comparison of the basic and modified versions of the algorithm were executed using data sourced from insurance companies, furnished by "FB Consult". © 2023 IEEE.

关键词： Collaborative filtering

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Deep learning solutions for pneumonia detection: performance comparison of custom and transfer learning models

Deep learning solutions for pneumonia detection: performance...

引用

2024 international conference on automation and Intelligent Technology, ICAIT 2024

作者： Zhong, Yihao Liu, Yanan Gao, Erdi Wei, Changsong Wang, Zhuoyue Yan, Chao Courant Institute of Mathematical Sciences New York University New York United States Research and Development Department Suzhou Liangchuang Hongzhi Intelligent Technology Co. Ltd. Kunshan China Tandon School of Engineering New York University New York United States Digital Financial Information Technology Co.LTD Chengdu China Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA United States Department of Electrical and Computer Engineering Northeastern University Sunnyvale United States

ISBN: (数字)9781510685819

ISBN: (纸本)9781510685802

Pneumonia is one of the leading causes of illness and death worldwide. In clinical practice, Chest X-ray imaging is a common method used to diagnose pneumonia. However, traditional pneumonia diagnosis through X-ray analysis requires manual annotation by healthcare professionals which delays diagnosis and treatment. This study aimed to investigate and compare three different deep learning methodologies for classifying pneumonia to detect the disease in patients. These advanced models have the potential to overcome the challenges of reliability and accessibility of diagnostic practices. The methodologies evaluated included a custom convolutional neural network (CNN), a transfer learning approach as well as a fine-tuning strategy based on ResNet152V2. The models were rigorously assessed and compared across various metrics, including testing accuracy, loss, precision, F1 score, and recall. The comparative analysis shows that the fine-tuning strategy outperforms the other methods in terms of operational effectiveness, with the custom CNN being the next most effective, and the transfer learning method ranking last. The study also highlights that false negatives can have more serious consequences than false positives, even without specialized medical knowledge. © The Authors.

关键词： Convolutional neural networks

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Two-Operation Buffering based on Dynamic Optical RAM 17

Two-Operation Buffering based on Dynamic Optical RAM

引用

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

作者： Semenov, Andriy Tsyrulnyk, Serhii Baraban, Serhii Semenova, Olena Rudyk, Andrii Khloba, Anton Vinnytsia National Technical University Faculty of Information Electronic Systems Vinnytsia Ukraine Vinnytsia National Agrarian University Department of Computer Sciences and Digital Economy Vinnytsia Ukraine Poznan University of Technology Faculty of Computing and Telecommunications Poznan Poland National University of Water and Environmental Engineering Department of Automation Electrical Engineering and Computer-Integrated Technologies Rivne Ukraine

ISBN: (纸本)9798331520564

The authors of this paper propose a block diagram for a dual-operating buffer on a dynamic optical RAM. The buffer consists of two dynamic optical RAMs, each controlled separately to allow for simultaneous writing and reading of data, thereby improving performance. This setup enables data to be read from the buffer while new data is being written to it. Implementing a dual-operating buffer on a dynamic optical RAM has the potential to enhance the performance of high-speed data transmission in telecommunications networks. The authors conducted numerical calculations to compare failure probabilities between single-operation and dual-operation buffers on dynamic optical RAM. The results indicated that using a dual-operating buffer significantly reduces the probability of failure with the same buffer memory capacity compared to a single-operating buffer. Additionally, the authors analyzed the effectiveness of the proposed dual-operating buffer. The analysis confirmed that exploiting dynamic optical memory for buffering enhances data transfer speed and efficiency due to the inherent properties of optical data transfer, such as high bandwidth and low latency. © 2024 IEEE.

关键词： Dynamic random access storage

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Design of an intelligent temperature-controlled fan based on STM32 6

Design of an intelligent temperature-controlled fan based on...

引用

6th international conference on Information Science, Electrical, and automation engineering, ISEAE 2024

作者： Sun, Yu Zheng, Junyuan Fu, Wenting Li, Rihui Zhou, Fangyu Guan, Jiayang Chen, Lei School of Optical and Electronic Information Suzhou City University Suzhou215104 China Suzhou Key Laboratory of Biophotonics Suzhou215104 China

ISBN: (纸本)9781510682924

This study designs an intelligent fan system based on the STM32 embedded processor. The core components of the system include keyboard module, motor drive module, temperature-illuminance sensor module, fan module, and serial communication. The system collects real-time environmental temperature data through a thermistor and transmits the data to the main control chip for processing. Based on the preset temperature settings, the main control chip automatically adjusts the fan speed using an algorithm to maintain a comfortable indoor temperature. Meanwhile, users can manually adjust the set temperature through buttons or PC software for personalized control, achieving intelligent energy saving to meet the diverse needs of different users. © 2024 SPIE.

关键词： computer keyboards

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Enhanced Supply Chain Management using IoT based Predictive Analysis 15

Enhanced Supply Chain Management using IoT based Predictive ...

引用

15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Jagadeesan, Arunkumar Gowrishankar, Vigneshwaran Yesodha, Karthik Raj Kumar Yuvaraj, N. PLM Engineering Campfire Interactive Inc. 2211 Old Earhart Rd Suite 175 Ann ArborMI48105 United States Advanced Manufacturing Canoo 19951 Mariner Ave TorranceCA90503 United States Supplier Quality and Planning Caterpillar Inc. 3000 N St DecaturIL62526 United States Sri Shakthi Institute of Engineering & Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350370249

Predictive analytics and automation with net of factors (IoT) is an rising fashion in supply chain management as the generation permits for price-efficient operations and permits organizations to higher reveal and control their deliver chain systems. The combination of predictive analytics algorithms and automatic structures can offer insights into deliver chain operations and expect adjustments in patron demands and allow agencies to better plan and put together for the future. IoT can also be used to screen supply chain techniques, become aware of regions for development and proactively manipulate potential disruptions. By means of utilizing IoT-based analytics and automation, advantages which includes increased visibility in supply chain operations, elevated customer satisfaction, and price-effective deliver chain processes may be done. Furthermore, predictive analytics and automation also can help improve choice-making with actual-time records insights and make certain that everyone tactics are being optimized for optimum performance. © 2024 IEEE.

关键词： Adjustments Development Disruptions Elevated Processes Visibility

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Intelligent Pick-Up of Drilling Logs Based on NLP Technology 2

Intelligent Pick-Up of Drilling Logs Based on NLP Technology

引用

2nd IEEE international conference on Image Processing and computer Applications, ICIPCA 2024

作者： Yunyi, Mei Ziyu, Song Xiaoyan, Shi Yanlong, Zhang Yong, Ji China National Petroleum Corporation Engineering Technology Research Institute Co. Ltd National Engineering Research Center for Oil and Gas Drilling and Completion Technology Beijing China Hiroshima University Hiroshima City Japan

ISBN: (纸本)9798350360240

Drilling logs are crucial documents in petroleum engineering that record geological information, operational parameters, and technical data. They contain a wealth of unstructured textual information, which is essential for optimizing drilling strategies, evaluating production potential, and ensuring operational safety. However, manually interpreting these documents is time-consuming, laborious, and prone to subjective bias. This paper proposes an NLP-based method for automatic analysis of drilling operation efficiency, exploring how to intelligently extract key useful information, identify critical geological features by training models, evaluate drilling efficiency, and predict drilling accident complexity through automation. Experimental results demonstrate that NLP achieves a recognition rate of 99.8% in the intelligent extraction technology of drilling logs, filling a domestic gap and having broad development prospects. © 2024 IEEE.

关键词： Petroleum geology

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Research on Semantic SLAM Algorithm Based on Deep Learning 4

Research on Semantic SLAM Algorithm Based on Deep Learning

引用

4th international conference on computer Vision and Pattern Analysis, ICCPA 2024

作者： Wang, Xiulian Shi, Zihao College of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China

ISBN: (纸本)9781510682528

In practical applications, mobile robots or UAVs often need to navigate and locate in a dynamic environment, but traditional SLAM algorithms often perform poorly in the face of dynamic environments. Therefore, dynamic SLAM has become one of the research hotspots. In order to solve the problems of low positioning accuracy and poor robustness of traditional visual SLAM in dynamic scenes. In this paper, an improved algorithm based on ORBSLAM3 is proposed. Under the condition of keeping the original framework unchanged, the algorithm adds a new semantic thread, combines Mask R-CNN to segment the image frame, extracts the keyframes for optimization, removes the feature points of the dynamic object, and retains the feature points of the original static object. Finally, comparative experiments are carried out based on the TUM dataset, and the final results show that the proposed algorithm is superior to the existing algorithms, and the positioning accuracy and robustness are improved. © 2024 SPIE.

关键词： SLAM robotics

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Creating an Experimental Setup in Mininet for Traffic Flow Collection During DDoS Attack 8

Creating an Experimental Setup in Mininet for Traffic Flow C...

引用

8th IEEE international conference on Computing, Communication, Control and automation, ICCUBEA 2024

作者： Jare, Shreya Abraham, Jibi Coep Technological University Department of Computer Engineering Pune India

ISBN: (纸本)9798350391770

The proliferation of network-enabled devices and the increasing reliance on digital services have underscored the importance of effective network monitoring and security measures. DDoS attacks continue to pose significant threats to network availability and performance, targeting critical infrastructure and disrupting business operations. This research paper presents a detailed methodology for constructing an experimental setup using Mininet to simulate and collect traffic flow data during Distributed Denial of Service (DDoS) attacks. The paper outlines the steps involved in setting up the network environment, configuring traffic generation, launching DDoS attacks, and collecting traffic flow data for analysis. The proposed setup provides researchers with a controlled environment to study DDoS attack behaviors and evaluate mitigation strategies. © 2024 IEEE.

关键词： Denial-of-service attack

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Application of Artificial Intelligence to Deep Learning in Vocational Education

Application of Artificial Intelligence to Deep Learning in V...

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2023 IEEE international conference on Electrical, automation and computer engineering, ICEACE 2023

作者： Ran, Qin Han, Dan Wuhan Railway Vocational College of Technology Wuhan China

ISBN: (纸本)9798350309614

The model of vocational education resource metadata management platform is designed and the metadata in teaching resource library is described. The paper proposes a technology to realize the automatic transformation of XML information. Using the specification of teaching data metadata, the format of other data is converted into XML file. The information exchange and sharing mechanism of multiple teaching resource libraries is established. At the same time, this paper proposes a deep learning vocational teaching design framework based on four aspects: 'teaching objectives', 'teaching strategies', 'teaching process' and 'teaching evaluation'. A multi-dimensional vocational education data collection index for deep learning is constructed based on adjoint evaluation and multi-modal data technology. The system can support multi-modal data-driven deep learning implementation. © 2023 IEEE.

关键词： Artificial intelligence computer system deep learning metadata vocational education XML

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