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检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

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A Survey on data Security using Reversible Cellular Automata

A Survey on Data Security using Reversible Cellular Automata

引用

2023 international conference on Computer Communication and Informatics, ICCCI 2023

作者： Degala, Divya Priya Athithan, Senthil Chinnasamy, P. KL University Department of Computer Science and Engineering Vijayawada India MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350348217

Now a days, without network and advanced computer technologies we can't able to transfer data among users. Among this the security is the biggest issue with the CPS system. The major issue is figuring out how to increase these systems' security while still doing it effectively. In order to overcome the issues this survey proposes several techniques for providing security of cyber-physical systems using reversible computing and cellular automata. A Cyber-Physical System(CPS) is an intelligent system used for data storing, transferring and protecting. To protect data, many machine(ml) and deep learning(dl) algorithms have been designed, which require more computation, dissipating more *** solve this, we are offering an public key encryption using reversible cellular automata to enhance the security of data in Cyber-Physical Systems © 2023 IEEE.

关键词： Cyber Physical System

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Urban Traffic Accident Factor Analysis, Risk Prediction and Early Warning Based on Big data Technology 23

Urban Traffic Accident Factor Analysis, Risk Prediction and ...

引用

9th international conference on computing and Artificial Intelligence, ICCAI 2023

作者： Hou, Xuehui Faculty of Information Security and Engineering Xinjiang Police College China

ISBN: (纸本)9781450399029

Urban road traffic safety has become a social problem related to people’s life safety, the main factors affecting the occurrence and severity of road traffic accidents are human factors, time, month, vehicle conditions, lighting, road conditions, weather conditions, visibility, etc. Using descriptive and predictive modeling, descriptive modeling is based on Hive database software to analyze the full sample data or Pyechart to visualize the data, the model studies and charts on historical data to obtain corresponding data regularity. Predictive models use machine learning algorithms, accident severity is taken as the target variable, through data cleaning, PCA was used for dimension reduction, RobustScaler data normalization and other processing, select the feature variables, Random forest algorithm or Xgboost algorithm was used to analyze the importance of characteristic variables that affect the severity of accidents. So as to find out the rules, in order to take preventive measures, reduce traffic accidents, to ensure people’s safety. © 2023 Copyright held by the owner/author(s).

关键词： Risk analysis

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FBI-Net: Frequency Band Integration Network for Infrared Small Target Segmentation

FBI-Net: Frequency Band Integration Network for Infrared Sma...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Xin, Biqiao Li, Qiang Mao, Qianchen Wang, Jinbao Wang, Bingshu School of Software Northwestern Polytechnical University Xi'an China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

ISBN: (纸本)9798350368741

Small targets in infrared imagery exhibit challenging characteristics due to their minimal semantic information and the extremely imbalanced distribution between the targets and the background. In this paper, we propose a frequency band integration network to extract salient features of infrared small targets in both the spatial and frequency domains. To excavate the high-frequency features of the small targets, we propose a frequency decoupling-fusion module. To decrease the semantic loss that occurs in deep networks, we propose a semantic injection mechanism to assist in retaining critical information from shallow layers. Experimental results show that our proposed method reaches higher prediction accuracy and robustness in the infrared small target segmentation task compared with other state-of-the-art approaches. © 2025 IEEE.

关键词： Feature Fusion Infrared Small Target Segmentation Semantic Injection Wavelet Transformation

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MODELING HIERARCHICAL TOPOLOGICAL STRUCTURE IN SCIENTIFIC IMAGES WITH GRAPH NEURAL NETWORKS 30

MODELING HIERARCHICAL TOPOLOGICAL STRUCTURE IN SCIENTIFIC IM...

引用

30th IEEE international conference on Image processing (ICIP)

作者： Leventhal, Samuel Gyulassy, Attila Pascucci, Valerio Heimann, Mark Univ Utah Salt Lake City UT 84112 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA

ISBN: (纸本)9781728198354

Topological analysis reveals meaningful structure in data from a variety of domains. Tasks such as image segmentation can be effectively performed on an image's topological connectivity using graph neural networks (GNNs). We propose two methods for using GNNs to learn from the hierarchical information captured by complexes at multiple levels of topological persistence: one modifies the training procedure of an existing GNN, and one extends the message passing across all levels of the complex. Experiments on real-world data from three domains show the performance benefits to GNNs from using a hierarchical topological structure.

关键词： graph neural networks topological data analysis image segmentation persistence Morse-Smale complex

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Congestion-aware Optimal data rate Selection for Efficient Routing in Wireless Rechargeable Sensor Network 3

Congestion-aware Optimal Data rate Selection for Efficient R...

引用

3rd international conference on Advances in computing, Communication, Embedded and Secure Systems, ACCESS 2023

作者： Susan T, Siron Anita Nithya, B. Ameen, Abdulla Rajkumar, Sarvesh National Institute of Technology Computer Science and Engineering Tiruchirappalli India

ISBN: (纸本)9798350346169

Wireless Rechargeable Sensor Nodes (WRSNs) are widely used to sense, collect, and process data or signals transmitted among people, the environment, and computer systems. However, it faces severe threats such as congestion, resource deprivation, security risk, limited communication speed, high cost, limited bandwidth, and so on. To address some of these issues and to improve the QoS, this paper proposes an Adaptive Rate Determined Congestion Management (ARDCM) approach. It adopts a feedback-based system in which the incoming data rate is managed to increase when congestion is low and decrease when congestion is high. It guarantees congestion free data flow between upstream and downstream in data communication by controlling the data rate and buffer occupancy. The proposed approach is simulated on NS2 with varying numbers of active nodes in a simulated environment. The proposed model's performance is evaluated by comparing the Packet Delivery Ratio(PDR), Packet Loss Ratio(PLR), delay, and throughput to the existing algorithms. © 2023 IEEE.

关键词： Sensor nodes

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A Security Verification System Based on Bilinear Maps in the Multi-cloud Environment 4

A Security Verification System Based on Bilinear Maps in the...

引用

2023 4th international conference on Computer Engineering and Intelligent Control, ICCEIC 2023

作者： Yue, Ruiqing Yang, Guangcan Li, Peixuan Xie, Jiaqi Jiao, Feipeng Zhan, Ling North China University of Technology School of Information Science and Technology Beijing China

ISBN: (纸本)9798350308877

As cloud computing continues to grow, an increasing amount of sensitive data is migrated to the cloud for storage and processing. However, sensitive data is usually stored in a single cloud environment, which poses several risks such as data leakage and a single point of failure. To address the above issues, a security verification system based on bilinear maps in the multi-cloud environment (i.e. SVS-BM) is proposed. In the paper, bilinear mapping technology is used to ensure the integrity and authenticity of user data during transmission and processing in the multi-cloud. Moreover, trusted middleware connects the terminal to multiple cloud service providers, which ensures efficient management and security verification of user data by segmenting and merging user data. Experimental results and performance analysis show that the system can effectively guarantee user data integrity and security in the multi-cloud environment. © 2023 IEEE.

关键词： Sensitive data

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Weather Report Analysis Prediction using Machine Learning and data Analytics Techniques

Weather Report Analysis Prediction using Machine Learning an...

引用

2023 international conference on data Science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Nagaraj, P. Prabhu, M. Chaithanya Venkata Sai Kumar, B. Yasaswitha, Ch. Mohana, K. Jahnavi, C. Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Virudhunagar Krishnankoil India

ISBN: (纸本)9798350348910

Accurate and dependable forecasts are necessary for weather prediction, which is essential to many industries and everyday activities. This paper investigates the use of gradient-boosting algorithms in weather report analysis and prediction by utilizing the capabilities of data science approaches. The gradient boosting model is trained using features that include temperature, humidity, wind speed, and atmospheric pressure, all of which are derived from historical weather data. Since atmospheric conditions are chaotic, it is difficult to make precise predictions in this environment. Nevertheless, gradient-boosting algorithms are quite good at identifying complex relationships in the data. The key phases of this process - data collection, preprocessing, and feature engineering - are highlighted in this paper. The paper provides a thorough approach to developing algorithms with an emphasis on algorithm selection, hyperparameter adjustment, and thorough assessment. strong forecasting models. Additionally discussed are the function of ensemble methods and model generalization, emphasizing the need for constant upkeep and monitoring to ensure peak performance. The results highlight how gradient-boosting algorithms might improve the precision of weather forecasts. Additionally, the incorporation of data science techniques demonstrates a methodical approach to deriving significant insights from intricate meteorological data. This research adds to a better knowledge of how to combine cutting-edge machine learning algorithms and domain expertise to address the complexities of weather report processing and prediction, as weather-related difficulties continue to arise. © 2023 IEEE.

关键词： Decision trees

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Learning tool of chemical molecules for healthcare students based on 3D visualizations, Large Language Models and Linked Open data 7

Learning tool of chemical molecules for healthcare students ...

引用

7th international conference on Education and E-Learning (ICEEL)

作者： Lorena Prieto, Maria Fuencisla Gilsanz, Maria Puertas, Enrique European Univ Madrid Madrid Spain

ISBN: (纸本)9798400708732

This paper presents a software tool designed to assist healthcare students and teachers in applying case-based learning methodologies for studying chemical compounds and their structures in a three-dimensional (3D) space. The tool utilizes natural language processing algorithms based on Large Language Models (LLM) to extract chemical entities from biomedical text documents. The tool provides students with a starting point for their research in a case-based learning exercise, and by using Large Language Models and Linked Open data, it shows them a path to follow. The system shows a description of the molecules, a 3D view, a 2D structure information, and a panel with scientific articles about the selected chemical compound obtained from the Scielo portal, a repository of scientific publications. The application has a modular architecture that allows for easy addition of new functionalities in the future. The web interface let users to input the text of the clinical case for processing and studying. The functionality of querying scientific articles can be expanded with new modules to obtain information from other repositories. Overall, this software tool provides a comprehensive and innovative approach to learning chemical molecules for healthcare students, which can help them develop the necessary skills to tackle real-life problems as healthcare professionals.

关键词： chatbot large language models learning management system artificial intelligence learning bots e-learning

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Research on Cloud Security Power Grid Model Simulation System Based on Computer Big data Technology 3

Research on Cloud Security Power Grid Model Simulation Syste...

引用

2023 IEEE 3rd international conference on data Science and Computer Application, ICDSCA 2023

作者： Xi, Wang Ming, Chen Shuang, Yang Dingwen, Zhang Yibin, Zhao Conghui, Xing China of Limited Company of Jilin Province Power Communication Company Changchun130021 China State Grid Jilin Electric Power Company Limited Changchun130021 China State Grid Info-Telecom Greate Power Science and Technology Co. Ltd Fuzhou350003 China

ISBN: (纸本)9798350341546

In this paper, a model of active distribution network safety monitoring system based on big data mining platform is established. This model combines multiple detection techniques and uses three-stage detection methods in the analysis equipment engine. A fuzzy encryption processing model of power flow information is proposed, which can improve the computing efficiency of static security analysis of power system under cloud computing environment on the premise of ensuring power flow information security. Through the simulation analysis of the fault diagnosis example, the results show that the proposed fault diagnosis algorithm is fast, accurate and effective. © 2023 IEEE.

关键词： Big data Cloud Security Computer Power Grid Model Simulation System

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Research on Key technologies of Internet of Things data Terminal and Integrated Management System for Power mobile devices 3

Research on Key technologies of Internet of Things Data Term...

引用

3rd international conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2023

作者： Hu, Haoqing Xiang, Yingyu Zeng, Cheng Chen, Boxi Hou, Jianxun Kunming Power Supply Bureau of Yunnan Power Grid Corporation Kunming China

ISBN: (纸本)9798350303698

With the development of information technology, China has launched various business processes of power informatization equipment in distribution or transmission grid informatization construction, laying the intelligent foundation of China's current power business informatization. Automatically mining and identifying performance degradation evolution patterns from the massive operation process data of complex equipment which is used to analyze the dynamic health status of equipment and guide equipment maintenance has become a research hotspot in the field of safety and reliability. Our research takes Yunnan Power Grid Company's power mobile equipment Internet of Things (IOT) data terminal and data center in integrated management system as the research object. We analyzes its construction method, data storage and processing, optimization algorithm and application advantages based on big data background. It carries out integrated power system management, provides good data interaction guarantee and achieves the overall goal of digital construction and transformation of power grid construction. The use of the latest technology platform, and combined with intelligent algorithms, the development of powerful computing power mobile equipment IoT data terminals and integrated management system has become a strategic trend of the current layout of China's power industry. © 2023 IEEE.

关键词： Informatization

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