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检索条件"任意字段=3rd International Conference on Computer Science and Management Technology, ICCSMT 2022"

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Proceedings - 2022 3rd international conference on computer science and management technology, iccsmt 2022

Proceedings - 2022 3rd International Conference on Computer ...

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3rd international conference on computer science and management technology, iccsmt 2022

ISBN: (纸本)9798350320404

The proceedings contain 111 papers. The topics discussed include: design of food safety management information system for western restaurant;research on enterprises’ response to emergencies based on machine learning;design and application of crop variety recommendation and production decision system in agricultural production;research on network structure analysis of English learning in social media;research on the prediction of e-commerce platform user churn based on random forest model;gazetteer enhanced named entity recognition for musical user-generated content;an application study of stochastic service systems based on operations search;risk early warning and response of PPP projects in characteristic towns based on fuzzy group decision- making and matter-element model;design and realization of an online examination system based on maven framework;design and implementation of dynamic interactive e-book system;optimization method for cloud service composition of machine tools under multiple constraints;application of environmental monitoring and control system in agricultural production;and design and implementation of warehouse management system based on Vuetify 3.0 framework.

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An Empirical Study of Supply Chain Finance Promoting Logistics Industry Development under Digital technology Innovation 24

An Empirical Study of Supply Chain Finance Promoting Logisti...

引用

5th international conference on computer science and management technology, iccsmt 2024

作者： Liu, Jian Liu, Qi Guangdong University of Science and Technology Guangdong Dongguan China

ISBN: (纸本)9798400709999

This study uses the intermediary effect model to make an empirical analysis of the relationship between digital economy, supply chain finance and logistics industry. The results show that the digital economy has significantly promoted the development of logistics industry through supply chain finance. Specifically, supply chain finance has significant effects in promoting logistics enterprises' financing, reducing operating costs and improving service efficiency. Through data analysis and model validation, the study confirms the key role of supply chain finance in capital liquidity and supply chain management. The paper puts forward policy suggestions such as strengthening digital infrastructure, enhancing financial support mechanisms, promoting digital literacy and skills development, encouraging innovation and adoption of digital technologies. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Decentralized finance

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Influence analysis and price prediction of digital asset social network based on graph neural network 24

Influence analysis and price prediction of digital asset soc...

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5th international conference on computer science and management technology, iccsmt 2024

作者： Yang, Wenfang Luo, Fu Guangdong University of Science and Technology Guangdong Dongguan China

ISBN: (纸本)9798400709999

As a crucial component of the digital economy, the market price fluctuations of Non-Fungible Tokens (NFTs) are influenced by various factors, making accurate prediction extremely important. This paper leverages a Graph Neural Network (GNN) model to analyze features such as user interaction frequency, user influence, and the popularity of discussion topics within social networks, aiming to predict the volatility of NFT market prices. Experimental results demonstrate that the GNN model achieves a prediction accuracy of 92%, significantly outperforming traditional time series models and linear regression models in key metrics like Mean Squared Error (MSE), Mean Absolute Error (MAE), and R2. The study finds that high-influence users and trending discussion topics in social networks are the primary drivers of price volatility. This research not only validates the effectiveness of the GNN model in processing complex social network data but also provides new theoretical insights and practical references for understanding and predicting market behaviors in the digital asset space. The findings offer a solid foundation for the design and optimization of price prediction models in the future digital economy. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Prediction models

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Research on Dietary Intake Monitoring and Nutrition Assessment System for Dialysis Patients Combined with computer Vision technology 24

Research on Dietary Intake Monitoring and Nutrition Assessme...

引用

3rd international conference on Public Health and Data science, ICPHDS 2024

作者： Yao, Lu Che, Xing The 83rd Group Army Hospital of People's Liberation Army Henan Xinxiang China China Research Institute of Radiowave Propagation Henan Xinxiang China

ISBN: (纸本)9798400711671

This study proposes a dietary intake monitoring and nutrition assessment system for dialysis patients based on computer vision technology, aiming to achieve automatic monitoring of dietary intake and accurate nutritional analysis of dialysis patients. This study introduces a deep learning convolutional neural network (CNN) for image feature extraction and uses transfer learning to enhance the model's generalization ability on various food data sets. In the simulation stage, the system is tested on the dietary images of actual dialysis patients. The results show that the system's accuracy in food recognition reaches 92.5%, and the error in nutrient estimation is controlled within 5%. The experimental data fully proves the effectiveness and reliability of the system, which can provide a scientific basis for the dietary management of dialysis patients. At the same time, this system has the advantages of high efficiency and low cost and is suitable for broad application in clinical environments. This study provides a new method for personalized nutritional assessment of dialysis patients and provides a theoretical basis and technical support for developing health management systems based on computer vision. © 2024 Copyright held by the owner/author(s).

关键词： computer vision

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A Named Entity Recognition Model for Threat Intelligence Based on Similar Semantic Space Construction 24

A Named Entity Recognition Model for Threat Intelligence Bas...

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5th international conference on computer science and management technology, iccsmt 2024

作者： Chen, Long Zhao, Chong Liu, Ziqi Wang, Hongyun School of Electronic Information Engineering China West Normal University Sichuan Nanchong China School of Computer Science China West Normal University Sichuan Nanchong China China Tobacco Sichuan Industrial Co. Ltd. Sichuan Chengdu China

ISBN: (纸本)9798400709999

Extracting cybersecurity entities from unstructured web text is an important part of security *** BERT-based entity extraction models rely on a single semantic expression generated by the model, however, these models do not take into account the polysemous information that exists for entities in the intelligence domain, thus limiting the performance of traditional models for extracting ***, this paper proposes a Semantic Enhancement Model (SEM) for named entities based on similar semantic space ***, the input text goes into BERT and CNN to get word-level word embeddings and character-level word embeddings respectively, and then merges them into mixed feature word embedding to enhance the robustness of the *** the same time, SEM computes the set of similar words S-SET for the input text sequentially by the Similar Word Sense Matching Algorithm, and then uses the self-attention mechanism to compute the semantic relevance weights among the S-SET elements, so as to get the word embeddings with similar *** mixed feature word embeddings and similar semantic word embeddings are used to calculate the similarity between the embedding vectors at different semantic levels through a multi-head attention mechanism, and then fused to construct an integrated semantic expression of the entity;thereby enriching the semantic expression of the entity and increasing the probability of the entity being predicted ***, the integrated semantic expression is input into CRF for entity *** experimental outcomes demonstrate that our proposed model outperforms existing baseline approaches on the network security datasets DNRTI and Bridge. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Semantics

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Research on Pulse Feature Point Identification Based on Differential Threshold 24

Research on Pulse Feature Point Identification Based on Diff...

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3rd international conference on Signal Processing, computer Networks and Communications, SPCNC 2024

作者： Chen, Likai Zheng, Gaofeng Zeng, Ziyue Li, Haonan Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen University Fujian Xiamen China

ISBN: (纸本)9798400710834

Accurate recognition of pulse signal characteristics is the key to disease diagnosis, the existing methods cannot adapt to the identification of sudden pulse cycles. The dynamic threshold method is used to locate all the starting point of the ascending branch and pulse cycle. The single-cycle segmentation of the entire pulse cycle can be achieved. The results show that the starting point and the peak point of all pulse data can be identified by this method. The segment of single pulse signal and recognition of feature points can also be realized through this method. The recognition accuracy of the tidal wave points and the dichotomous wave point reaches 92.6%;it can be basically completed. The identification of characteristic points provides the basis for the analysis and digitization of traditional Chinese medicine. © 2024 Copyright held by the owner/author(s).

关键词： Diagnosis

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A Hybrid Blockchain Framework for Secure, Scalable, and Energy-Efficient Digital Identity management with Token-based Selective Disclosure 3

A Hybrid Blockchain Framework for Secure, Scalable, and Ener...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Velmurugan, M. Shinzeer, C.K. Maya, G. Ramya, R. Kanimozhi, R. Lathif, Syed Ismail Abdul Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science And Technology Department Of Computer Science & Engineering Chennai600 062 India Lovely Professional University Department of School of Computer Applications Punjab Phagwara144411 India Srm Institute of Science and Technology Faculty of Management Kattankulathur603 203 India K.Ramakrishnan College of Engineering Department of Electronics and Communication Engineering Samayapuram621112 India Muthayammal Engineering College Computer Science and Engineering Rasipuram637408 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India

ISBN: (纸本)9798331509675

Data breaches, identity theft, and the lack of user control within traditional digital identity management systems, it begs a more secure and decentralized alternative. In this study we propose a blockchain based digital identity management framework that implements privacy, security and transparency by employing distributed ledger technology. To provide tamper proof identity storage and automated verification, the proposed model uses cryptographic hashing and smart contracts. The use of a novel token-based access mechanism enables users to safely share their identity data with third parties, while keeping sensitive information out of sight. Security metrics are enhanced by 30% for data integrity with 45% reduction in unauthorized access attempts all through simulations. The framework also achieves improved efficiency reducing identity verification time by 40 percent compared to traditional systems. It offers a promising approach to address important vulnerabilities in centralized identity management in line with the development of marketable and user-friendly digital identity solutions. © 2025 IEEE.

关键词： Data integrity

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Role of IoT in Smart Cities: A Review, Applications, Open Challenges and Solutions 3

Role of IoT in Smart Cities: A Review, Applications, Open Ch...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Vivek, Kolla Swetha, Gurrala Kumar M, V. T. Ram Pavan Veni, Anusuri Krishna Praveen, Neti Kale, Masthan Rao Dept. of Cse Andhra Pradesh Ongole India Dept. of Cse Telangana India Kakaraparti Bhavanarayana College Dept. of Computer Science Andhra Pradesh Vijayawada India Madanapalle Institute of Technology & Science Dept. of Computer Science & Engineering - Data Science Andhra Pradesh Madanapalle517325 India Srkr Engineering College Dept. of Computer Science and Design Andhra Pradesh Bhimavaram India Dept. of Cse Andhra Pradesh Ongole India

ISBN: (纸本)9798331509675

Smart cities have emerged as a response to the fast expansion of metropolitan areas;these places strive to improve the lives of their residents while simultaneously promoting environmentally responsible growth. To maximize urban services, the Internet of Things (IoT) is an essential technology that allows for the seamless integration of sensors, devices, and systems. This allows smart cities to become a reality. With an emphasis on smart transportation, energy management, healthcare, environmental monitoring, and public safety, this paper explores the critical role of IoT in smart cities. Data security, privacy, scalability, and interoperability are some of the problems that arise when smart cities use IoT, despite the revolutionary potential it has. These obstacles are thoroughly examined in this work, along with possible solutions to these problems. This study gives a thorough overview of the IoT and its impact on smart city development, innovation, and urban resilience by focusing on the present situation, applications, and unanswered questions. © 2025 IEEE.

关键词： Digital technology Drainage Monitoring Fire detection Smart City Waste management

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Digital Evidence management: Modern Techniques in Digital Forensics 3

Digital Evidence Management: Modern Techniques in Digital Fo...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Venkataramanan, N. Jayalakshmi, V. Anitha, S. Ganesan, R. Jenifer, V. Drbccc Hindu College Department of Computer Applications Pattabiram Chennai600072 India Department of Computer Science and Applications Ramapuram600089 India Anna University St. Joseph's College of Engineering Department of Artificial Intelligence and Machine Learning Chennai600119 India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai600062 India Department of Computer Science and Applications Ramapuram Campus 600089 India

ISBN: (纸本)9798331509675

This research study reviews the significance of digital forensic analysis in modern criminal investigations, highlighting the way it complements conventional methods of inquiry and the difficulties it encounters in the information era. To solve crimes effectively, investigators must combine digital knowledge with traditional forensic techniques. This will enable them to use evidence from many different types of digital and physical sources. The specific intricacies of digital crime scenes need specialized methods for the proper storage and analysis of digital evidence to identify criminal intent and patterns of conduct. To propose Modern Techniques for Digital Evidence management [MT-DEM] based Digital Forensics Service. Multidisciplinary teams and cutting-edge technology are becoming necessities in digital forensic investigation as the field adjusts to new threats like data encryption and massive amounts of data. The admissibility of evidence in the legal world depends on digital forensic procedures being transparent and adhering to set criteria. Digital forensic analysis has become an indispensable tool for contemporary investigators with the rise of digital evidence. © 2025 IEEE.

关键词： Forensic science

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A Skin Disease Classification Model Combining CAFormer and Curriculum Learning 24

A Skin Disease Classification Model Combining CAFormer and C...

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3rd international conference on Algorithms, Data Mining, and Information technology, ADMIT 2024

作者： He, Xingguang Chen, Yide University of Electronic Science and Technology of China China University of Electronic Science and Technology of China China

ISBN: (纸本)9798400718120

Skin diseases represent a significant challenge to human health, affecting individuals across various demographics and potentially leading to severe complications if left untreated. The landscape of skin diseases is diverse, encompassing a wide range of conditions, each necessitating specific and tailored treatment approaches. Given this complexity, the prompt and precise identification of the type of skin disease becomes essential not only for effective management but also for improving patient outcomes. This paper introduces the CAFormer model and curriculum learning to the problem of skin disease classification for the first time. This combination achieves outstanding results compared to other models in this classification task. This combination achieved the best Top-1 accuracy of 75.31%, along with a Top-5 accuracy and Macro F1 Score of 91.50% and 0.7233, respectively. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive Learning

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