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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

共 4197 条记录，以下是61-70 订阅

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Aspect-based Sentiment Analysis with External Knowledge Embedding and Syntactic information 7

Aspect-based Sentiment Analysis with External Knowledge Embe...

引用

7th international conference on Electronic information technology and computer Engineering (EITCE)

作者： Zhang, Fan Zheng, Wenbin Chengdu Univ Informat Technol Sch Software Engn Chengdu 610225 Peoples R China

ISBN: (纸本)9798400708305

Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis. the current research mainly focuses on context-based and syntactic dependency-based approaches. However, they only consider the inherent syntactic connections and linguistic properties within the sentence, and much additional knowledge is not considered or utilized. To handle this concern, we propose a knowledge embedding and syntactic information enhancement network (KESE). KESE aims to fully utilize syntactic dependency and introduce external knowledge for assisting in mining the connection between aspect and sentiment words. We utilize an aspect-oriented attention mechanism to capture aspect features and enhance them with syntactic masking networks and graph convolutional networks. Furthermore, we embed knowledge graphs to improve the recognition of aspects and sentiments. We conduct experiments on several publicly accessible ABSA datasets, and the results demonstrate the effectiveness of our proposed KESE.

关键词： Sentiment Analysis Syntactic information Knowledge Graph

来源：评论

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Predicting Chargeback Fraud Using Data Mining Techniques 7

Predicting Chargeback Fraud Using Data Mining Techniques

引用

7th international conference on Signal processing and information Security, ICSPIS 2024

作者： Doodipala, Shreya Rahate, Mrudula Jothi, J. Angel Arul Birla Institute of Technology and Science Pilani Department of Computer Science Dubai Campus United Arab Emirates

ISBN: (纸本)9798350368673

Chargeback fraud, commonly known as friendly fraud, is committed intentionally or unintentionally by consumers who make online transactions using their credit card and later dispute the charge with the credit card company. Chargeback fraud can have serious implications depending on the extent of the financial losses suffered by the business, the possible damage to their reputation, and the overall burden it puts on the smooth functioning and trustworthiness of the entire payment system. this paper aims to identify the best algorithm to detect fraudulent activities in financial transactions by applying data mining techniques. the proposed work includes preprocessing, feature engineering and comparative analysis of 6 algorithms on 3 variants of an unbalanced dataset of credit card transactions. From the result it is observed that XGBoost has the best performance, with an accuracy of 98% and F1 score of 84% on the dataset. © 2024 IEEE.

关键词： binary classification chargeback fraud data mining SMOTE-NC XGBoost

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UNet-AFF: U-Net based on attention feature fusion for COVID-19 focus segmentation 7

UNet-AFF: U-Net based on attention feature fusion for COVID-...

引用

7th international conference on computer information Science and Application technology, CISAT 2024

作者： Ye, Xi Yang, Zhihong Zhang, Zhiwei Zhang, Quanxin Institute of Intelligent Manufacturing Jianghan University Wuhan China Institute of Computer Science and Technology Wuhan University of Bioengineering Wuhan China

ISBN: (纸本)9798350375107

In response to the limitations of conventional U-Net in fusing high- and low-level features in automatic segmentation of neocoronal pneumonia foci, this paper proposes an attention feature fusion-based segmentation model for U-Net pneumonia foci. the model incorporates an attention feature fusion module in the decoding stage of the network for the purpose of integrating high- and low-level features. the attention feature fusion module is designed to focus on and emphasise the effective expression of features when they are fused through the attention mechanism. this helps the network to integrate the semantic information and spatial details of features at different layers, thereby improving the accuracy of the network's decoding. Finally, this paper presents experimental results on the COVID19 CT lung infection segmentation dataset with new crown pneumonia foci. the results demonstrate that the improved segmentation model in this paper can effectively improve the segmentation performance for new crown pneumonia foci. © 2024 IEEE.

关键词： Semantics

来源：评论

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Development Of Data Collection And Data processing In Hospital Asset Position Mapping Applications 7

Development Of Data Collection And Data Processing In Hospit...

引用

7th international conference of computer and Informatics Engineering, IC2IE 2024

作者： Widyadhari, Dinda Putri Suakanto, Sinung Hamami, Faqih Nuryatno, Edi Telkom University Faculty of Industrial Engineering Department of Information System Bandung Indonesia The University of Western Australia Uwa Centre for Medical Research Perth Australia

ISBN: (纸本)9798331505530

Efficient management of hospital assets is essential for optimal operations and quality health services. Problems that often occur when recording and managing assets in hospitals are done manually which causes data errors, data mismatches, and asset data is only known by asset managers without being explicitly stated. this research develops an automation system for collecting and processing hospital asset data using YOLO model reading technology and database. this system consists of several stages such as detection and identification of assets with the YOLO model, storing detection data in SQLite3, sending data to the central server via API, and post-processing data on the server to select data with the highest confidence score and then save it to the MySQL database. the implementation of this system can reduce manual recording time, improve asset visibility and optimize the use of resources, thereby contributing to improving the efficiency and quality of health services. © 2024 IEEE.

关键词： Data collection

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AI-Powered Cybersecurity: Enhancing threat Detection and Defense in the Digital Age 7

AI-Powered Cybersecurity: Enhancing Threat Detection and Def...

引用

7th IEEE international conference on Electronic information and Communication technology, ICEICT 2024

作者： Zhang, Xianni Wang, Pengfei Jia, Haonan Huang, Zhen Zhao, Runfeng College of Information Engineering Beijing Polytechnic College Department of New Generation Information Technology Beijing100042 China Beijing University of Technology School of Mechanical and Energy Engineering Beijing100000 China Huizhou University School of Computer Science and Engineering 516007 China

ISBN: (纸本)9798350384437

information technology's swift progression has rendered network security a critical component of modern infrastructure. Artificial Intelligence (AI) has revolutionized network security, particularly in threat detection and defense mechanisms. Leveraging its advanced data processing and pattern recognition capabilities, AI can forecast and counter potential network threats with enhanced precision and efficiency. the burgeoning global AI market reflects its expansive potential in bolstering network security. By emulating the neural networks of the human brain, AI bolsters threat detection rates, dynamically refines security strategies, and enables automated response and recovery from cyber-attacks. Studies suggest that AI's integration can markedly diminish the risk of network breaches and fortify the reliability of security *** the cyber landscape grows more intricate and threats evolve, ongoing innovation in AI is imperative for future advancements. the anticipation is that AI will assume an increasingly pivotal role in network security, offering robust defense against the escalating complexity of cyber threats. © 2024 IEEE.

关键词： Cyber attacks

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Research on multimodal human-computer interaction technology based on audiovisual fusion 7

Research on multimodal human-computer interaction technology...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Jiao, Zhinan School of Art and Design Hubei University of Technology China

ISBN: (纸本)9781665478571

With the improvement of information technology, service robots are becoming more and more deeply involved in our work and life, and provide a wider variety of services. How to make robots communicate with humans more intelligently and understand and accomplish people's task needs has become a current research hotspot. In this paper, we propose a multimodal human-robot interaction technique with D-S evidence theory for fusion of audiovisual information, and a multimodal interaction system with speech and gesture interaction to improve the performance of human-robot interaction. © 2022 IEEE.

关键词： Human robot interaction

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A Chinese Sentiment Analysis Model Incorporating Knowledge Graph and Deep Learning 7

A Chinese Sentiment Analysis Model Incorporating Knowledge G...

引用

7th international conference on Electrical, Mechanical and computer Engineering, ICEMCE 2023

作者： Zhao, Shengping Chen, Jinlong Qin, Xingguo School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China School of Computer Science and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guangxi Guilin541004 China

ISBN: (纸本)9798350382877

With the rapid growth of social media and e-commerce, users are generating large amounts of textual review data on these platforms. Analyzing and mining these comment data is important for governments, enterprises, and consumers to make decisions. therefore, sentiment analysis, especially for Chinese comments, has become an area of wide interest in industry and academia. Aiming at the characteristics of Chinese online reviews, this paper applies the techniques of knowledge graph and deep learning around sentence-level sentiment analysis and designs a sentiment analysis model that integrates different information such as sentiment knowledge graph and serialized annotation in a deep learning model to improve the accuracy and effectiveness of sentiment analysis of Chinese online reviews. this is important for improving products and services, understanding user needs, and making more informed business and policy decisions. © 2023 IEEE.

关键词： Sentiment analysis

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Research and Application of Controllable AIGC technology in Architectural Renderings Generation 24

Research and Application of Controllable AIGC Technology in ...

引用

2024 7th international conference on computer information Science and Artificial Intelligence, CISAI 2024

作者： Liu, Xiaohu Guo, Yutang Department of Information Engineering Anhui Lvhai Vocational College of Business Anhui Hefei China

ISBN: (纸本)9798400707254

With the wide application of AIGC image technology in the production of architectural renderings, how to generate more accurate and clear architectural renderings has become a research hotspot in the industry. Aiming at this problem, this paper designs a system framework for controllable AI-generated architectural renderings, which has the Features of strong scalability and smooth processing flow. this paper also proposes a three-category combination method of text-to-image prompt words to effectively design prompt words. At the same time, this paper designs and implements a three-stage AI generation algorithm for architectural renderings, conducts theoretical analysis on the complexity of the algorithm, and tests and compares the generation effects through experiments. the research results of this paper can effectively realize controllable AI-generated architectural renderings and have good application effects and promotion significance. © 2024 Copyright held by the owner/author(s).

关键词： Rendering (computer graphics)

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Design and Optimization of Quad-Band Qing-Shaped Patch Antenna Using CMA-Surrogate Model 7

Design and Optimization of Quad-Band Qing-Shaped Patch Anten...

引用

7th IEEE international conference on Electronic information and Communication technology, ICEICT 2024

作者： Pei, Yingqi Chung, Kwok L. Li, Caiying Wu, Zhipan Lai, Guoming Huizhou University School of Computer Science and Engineering Huizhou516007 China

ISBN: (纸本)9798350384437

this paper introduces a novel surrogate model based on characteristic mode analysis, applied in the design and optimization of a distinctive Qing-shaped patch antenna printed in LiShu format, a style of Chinese calligraphy. the optimized results demonstrate that the L-probe excited antenna achieves quad impedance bandwidths at 1.67, 2.13, 2.6, and 3.0 GHz, with an average broadside gain of 8 dBi. through optimization, the overall patch size is determined to be 88 mm in width, 59 mm in length, and 16 mm in height. © 2024 IEEE.

关键词： Microstrip antennas

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Stealthy False Data Injection Attack Using Improved Singular Value Decomposition in Smart Grid 7

Stealthy False Data Injection Attack Using Improved Singular...

引用

7th international conference on information and computer Technologies, ICICT 2024

作者： Yang, Liqun Li, Chunan Wei, Chaoren Yang, Jian Qu, Gang Zhang, Liang Zhang, Yipeng Li, Tongliang Beihang University School Of Cyber Science And Technology Beijing China Beihang University School Of Computer Science And Engineering Beijing China State Grid Corporation Of China East China Branch Shanghai China North China University Of Technology School Of Information Science And Technology Beijing China Beijing Information Science And Technology University Computer School Beijing China

ISBN: (纸本)9798350385625

Smart grid is a crucial Cyber-Physical system and is prone to cyber-attacks. In this paper, we propose a novel false data injection attack (FDIA) construction mechanism. Firstly, the measurements are preprocessed to eliminate the outliers caused by the system failure, communication failure and data missing. then, the preprocessed measurements are decomposed into a multiplication of the unitary matrixes by the proposed improved Singular Value Decomposition (SVD) algorithm. To achieve more accurate decomposed matrix, we introduce the regularization constraints into the objective of SVD. At last, the FDIA is constructed based on the decomposed matrix in a sparse way. We assess the performance of the proposed FDIA with comprehensive simulations on IEEE 14- and 118-bus systems. the results indicate that the proposed FDIA can be performed in a stealthy and sparse way. © 2024 IEEE.

关键词： State estimation

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