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检索条件"任意字段=3rd International Conference on Signal and Data Processing, ICSDP 2023"

共 2953 条记录，以下是281-290 订阅

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Design and Performance Analysis of 3-Fin 08 nm Physical Gate Length SOI FinFETs Employing Gate Stacked High-K Dielectrics 3

Design and Performance Analysis of 3-Fin 08 nm Physical Gate...

引用

3rd IEEE international conference on Applied Electromagnetics, signal processing, and Communication, AESPC 2023

作者： Nanda, Swagat Kumari, Sapna Dhar, Rudra Sankar National Institute of Technology Department of Electronics and Communication Engineering Mizoram Aizawl India

ISBN: (纸本)9798350358742

The continuation of the scaling of FinFETs in the nano regime guaranteed the continuance of semiconductor industry with the fabrication of reliable, high performance and low power devices. The Short Channel Effects (SCEs) were effectively suppressed by these Trigate FinFETs while lowering the leakage currents further. However, as the FinFETs were scaled below 22 nm gate lengths, the SCEs amplified. The gate oxide thickness was reduced to suppress the SCEs but the leakage currents deteriorated. Therefore, to reduce the leakage currents along with improved SCEs, the replacement of the gate oxide with high permittivity dielectrics like Zirconium Dioxide, Hafnium Oxide, Aluminum Oxide and Silicon Nitrate were needed. The motivation of this paper is the development a 3 Fin SOI FinFET at a physical gate length of 08 nm where the gate oxide of each fin consists of a stacked combination of 0.5 nm of high-k dielectrics atop a 0.5 nm layer of SiO2 to control the leakage currents and other SCEs. The use of 3-Fin structures significantly enhances the drain current while the gate stack high-k materials reduce leakage currents leading to higher switching speeds for faster CMOS fabrication and optimized device performance. © 2023 IEEE.

关键词： Leakage currents

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Research on Intelligent Operation and Maintenance System of Power Distribution Automation Terminal under Computer Big data 3

Research on Intelligent Operation and Maintenance System of ...

引用

3rd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Han, Lu Xing, Zhenhua Wang, Shuyuan Qiao, Dongwei Xie, Yumeng Sun, Peng State Grid tai'An Power Supply Company Tai'an271000 China

ISBN: (纸本)9798350398410

This paper uses the combination of computer Internet of things information processing and configuration of distribution automation terminal operation and maintenance system to carry out innovative design. Then in this paper, the power mobile communication data are accurately collected, processed and configured through the Internet of Things mobile operation and maintenance system, so as to realize the effective association between the power intelligent communication operation and maintenance system and the Internet of Things data configuration and processing platform. The system uses the STX-NUCLEO-6180XA1VL6180X sensor to sense the surrounding environment information. Then use HZ-JK02B model DC power screen monitoring equipment to add a centralized expansion unit. RS485 interface communication to realize branch insulation monitoring. Experiments show that the designed platform has a higher pass rate of operation and maintenance management function, a lower resource occupancy and a better performance. © 2023 IEEE.

关键词： Internet of things

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Design of real time monitoring and intelligent analysis system for fiber optic sensor networks driven by big data 3

Design of real time monitoring and intelligent analysis syst...

引用

3rd international conference on Electronic Information Engineering and data processing, EIEDP 2024

作者： Gang, Huang Like, Pan Chengzhang, He Chengfeng, Yang Zhong, Li Xiuyi, Pan Yongjia County Electric Power Industry Co. Ltd. Zhejiang Wenzhou325100 China State Grid Yongjia County Power Supply Co. Ltd. Zhejiang Wenzhou325100 China

ISBN: (纸本)9781510680531

This article explores the application of big data technology in the design of real-time monitoring and intelligent analysis systems for fiber optic sensor networks (FOSN). An analysis was conducted on the limiting factors of current FOSN, such as cross sensitivity, data processing speed, signal-to-noise ratio, etc. This paper proposes an advanced data analysis engine based on CNN (Convolutional Neural Network) algorithm model and artificial intelligence to overcome these challenges. In the real-time data processing capability experiment, the average time for processing 10000 pieces of data based on CNN algorithm system was only 0.05 seconds, while the time for processing 100000 pieces of data was controlled within 0.5 seconds, demonstrating the efficiency of processing large-scale data. In the accuracy verification experiment of monitoring, the average error of the CNN algorithm system for 1000 data is only 0.03, indicating the high accuracy performance of the system in real-time monitoring. © 2024 SPIE.

关键词： Sensor networks

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ML Based Automated Assistance System for Efficient Crowd Control A detailed investigation 3

ML Based Automated Assistance System for Efficient Crowd Con...

引用

3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Kumar, Ashwini Parikh, Swapnil Arka Jain University Department of Engineering& It Jharkhand Jamshedpur India Pit Parul University Department of Cse Gujarat Vadodara India

ISBN: (纸本)9798350399264

This section covers ML and automated assistance systems for crowd control. ML-based artificial intelligence (AI) lets software programmes enhance prediction accuracy without being designed to. ML techniques forecast correct output using past data. The next step towards truly automated beings is to develop methods for understanding and managing the currently pervasive community info gadgets since data is so important. In this part, we'll discuss ML's automatic crowd control. data availability is expanding learning for application across sectors. Computer vision has helped medical diagnosis, data presentation and processing, science, and research. Computer hardware, electronics, internet content, and cyber security have used these methods. The machine learning-based automatic assistance system for efficient cored management can now be concluded. © 2023 IEEE.

关键词： data acquisition

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Enhancement of data Security Scheme with Cryptography Training System in Smart Grid Network 3

Enhancement of Data Security Scheme with Cryptography Traini...

引用

3rd IEEE Applied signal processing conference, ASPCON 2023

作者： Chatterjee, Tirtharaj Biswas, Subrata Shil, Sayan Purkait, Prithwiraj Ghosh, Poulami St. Thomas' College of Engineering and Technology Electrical Engineering Department Kolkata India Netaji Subhash Engineering College Electrical Engineering Department Kolkata India Jadavpur University Power Engineering Department Kolkata India

ISBN: (纸本)9798350325881

Smart grid security is a crucial aspect of protecting the electrical grid that employs advanced technologies, including digital communication, sensors, and automation, to enhance the efficiency and dependability of power distribution. As the adoption of these technologies continues to increase, it is imperative to safeguard smart grid systems against potential cyber-attacks, which could result in power outages, financial losses, and public safety threats. Smart grid security measures encompass encryption, access control, intrusion detection, as well as training and awareness programs for both employees and consumers. By ensuring a secure smart grid system, risks can be mitigated and the resilience of the power infrastructure can be maintained. This Paper represents a scheme to secure the smart grid. In this scheme HMAC (Hashed-Based Message Authentication Code) is used to decrypt the message along with SKDP (Secure Key Distribution Protocol) which secures the from UKS (Unknown Share Key Attack). © 2023 IEEE.

关键词： Smart power grids

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Design of Financial data Evaluation System under Neural Network Algorithm 3

Design of Financial Data Evaluation System under Neural Netw...

引用

3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Feng, Yuchen Newcastle Business School The University of Newcastle Australia Singapore

ISBN: (纸本)9798350317022

Financial data evaluation plays a crucial role in enterprise decision-making and investment. Traditional financial analysis methods are often influenced by subjective judgment and uncertainty, so more scientific and accurate methods are needed to evaluate the financial situation of enterprises. With the help of machine learning technology, it is possible to overcome the limitations of traditional financial analysis methods and achieve accurate prediction of financial conditions through data collection, cleaning, and model processing. According to the experimental data, it can be seen that the number of satisfied individuals in the two traditional system experiments ranged from 95 to 127 and from 29 to 39, respectively. The number of satisfied individuals in the financial data evaluation system of the two neural network algorithms ranged from 207 to 215 and from 86 to 91, respectively. From this, it can be seen that the application of this method marks a significant improvement in the objectivity and reliability of financial evaluation, and has a positive promoting effect on the future development of enterprises. © 2023 IEEE.

关键词： data analysis enterprise finance neural network algorithm system architecture system design

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Transformer-based Context Aware Morphological Analyzer for Telugu 3

Transformer-based Context Aware Morphological Analyzer for T...

引用

3rd Workshop on Speech and Language Technologies for Dravidian Languages, DravidianLangTech 2023

作者： Dasari, Priyanka Chelpuri, Abhijith Vuppala, Nagaraju Marreddy, Mounika Krishnamurthy, Parameswari Mamidi, Radhika International Institute of Information Technology Hyderabad India

ISBN: (纸本)9789544520854

This paper addresses the challenges faced by Indian languages in leveraging deep learning for natural language processing (NLP) due to limited resources, annotated datasets, and Transformer-based architectures. We specifically focus on Telugu and aim to construct a Telugu morph analyzer dataset comprising 10,000 sentences. Furthermore, we assess the performance of established multilingual Transformer models (m-Bert, XLM-R, IndicBERT) and mono-lingual Transformer model BERT-Te (trained from scratch on an extensive Telugu corpus comprising 80,15,588 sentences). Our findings demonstrate the efficacy of Transformer-based representations pre-trained on Telugu data improved the performance of the Telugu morph analyzer, surpassing existing multi-lingual approaches. This highlights the necessity of developing dedicated corpora, annotated datasets, and machine learning models in a mono-lingual setting. Using our dataset, we present benchmark results for the Telugu morph analyzer achieved through simple fine-tuning on BERT-Te. The morph analyzer dataset1 and codes are open-sourced and available here. © DravidianLangTech 2023 - 3rd Workshop on Speech and Language Technologies for Dravidian Languages, associated with 14th international conference on Recent Advances in Natural Language processing, RANLP 2023 - Proceedings.

关键词： Deep learning

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data processing Optimization of Power Grid Dispatching Control Cloud Based on Edge-Cloud Collaborative Computing 3

Data Processing Optimization of Power Grid Dispatching Contr...

引用

3rd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2023

作者： Sheng, Lei Wang, Chunying Liu, Yan Zhang, Ningning Wang, Zhaohe State Grid Henan Electric Power Company Information & Telecommunication Company Zhengzhou China

ISBN: (纸本)9781665472784

Cloud computing technology is widely used in power grid systems. In response to the data with strict delay requirements and a large amount of data generated by the operation of the power grid system. New challenges are raised to the delay of business processing. In order to achieve the goal of minimizing the system average latency time of task processing, based on the power grid dispatching cloud architecture, a delay optimization method based on SDN edge-cloud collaborative computing is proposed. The goal is to minimize the system average delay of task processing. Introduce continuously variable edge and cloud and task distribution coefficients. The delay optimization problem is transformed into the task allocation coefficient optimization problem. And finally get the task allocation optimization strategy based on the model calculation. The experimental results show that when the edge node tasks are reasonably loaded into the cloud center for processing, the system delay of the business can be effectively reduced. Compared with the previous methods, the edge-cloud collaborative computing method proposed in this paper reduces the system delay and utilizes the control mechanism of SDN that can coordinate cloud computing and edge computing. The algorithm can be used in the power system cloud platform system based on SDN. © 2023 IEEE.

关键词： Edge computing

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2023 3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

2023 3rd International Conference on Smart Generation Comput...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

ISBN: (纸本)9798350319125

The proceedings contain 441 papers. The topics discussed include: evaluating the impact of image restoration on digital image processing using compression technique;blockchain's transcendent evolution: uncovering its impact across industries and cutting-edge applications;analysis of the construction of digital education resource sharing in universities from the perspective of blockchain;examining the impact of data mining on decision-making processes;the synchronous dislocation scheduling algorithm: cloud-based performance improvement;the multicarrier NOMA- assisted full duplex IoT networks for robust resource allocation using lightweight secure transmission;research on English teaching quality evaluation based on fuzzy comprehensive evaluation based on k-means clustering algorithm;and predicting life expectancy using machine learning approach through linear regression and decision tree classification techniques.

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Research on Power System Load Clustering based on signal Analysis and K-Prototypes 3

Research on Power System Load Clustering based on Signal Ana...

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3rd international conference on Electrical Engineering and Control Science, IC2ECS 2023

作者： Peng, Bo Liu, Yuhui Qinghai University Faculty of Energy and Electrical Engineering Xining China School of Mathematics and Physics Qinghai University Xining China

ISBN: (纸本)9798350382426

Based on the K-prototypes algorithm, this study discusses the method of load clustering in power system. After the data is acquired, the outliers are processed, and then the data is filtered and analyzed using the Butterworth higher-order filter. Then, the feature engineering project is carried out to extract the representative features in the time domain and frequency domain, and a mixed-attribute clustering model is constructed, which organically combines numerical attributes and categorical attributes. This model is designed to fully exploit the latent information in the load data and more accurately characterize the load. Through this model, we can realize the fine division of load data and provide more detailed and effective information for power system management, which provides new ideas and methods for power system load management, and has certain theoretical and practical value. © 2023 IEEE.

关键词： Butterworth filter K-prototypes mixed-attribute clustering power system load time-frequency analysis

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