Proceedings of International Conference on Artificial Intelligence and Communication Technologies (ICAICT 2023): Artificial Intelligence and Wireless ... Innovation, Systems and Technologies, 368)

Preface
Contents
About the Editors
Part I Remote Sensing and Machine Learning
1 Multi-objective Dynamic Optimization Scheme for Unmanned Aerial Vehicles
	1.1 Introduction
	1.2 Analysis of UAV Position
		1.2.1 Triangulation Method on UAV Positioning
		1.2.2 Three-Target Bearings-Only Triangulation on UAV Positioning
	1.3 The Establishment and Solution of Model
		1.3.1 Multi-objective Dynamic Scheduling Model
		1.3.2 The Solution of Model
	1.4 Conclusions
	References
2 Extraction and Fusion of Geographic Information from Multi-source Remote Sensing Images Based on Artificial Intelligence
	2.1 Introduction
	2.2 Methodology
		2.2.1 Basic Theory of Multi-source Data Fusion
		2.2.2 Geographic Information Extraction and Fusion Algorithm of RS Image
	2.3 Result Analysis and Discussion
	2.4 Conclusions
	References
3 Architecture Simulation of Unmanned Lunar Exploration Platform Based on Modelica
	3.1 Introduction
	3.2 Overall Model Architecture
		3.2.1 System Composition of Unmanned Lunar Exploration Platform
		3.2.2 System Simulation Model Architecture
		3.2.3 Operation Process
	3.3 Multi-domain Modeling Method
		3.3.1 Common Function Modeling of Multi-module
		3.3.2 Mobile Detection Module Modeling
		3.3.3 Energy Supply Module Modeling
		3.3.4 Lunar Communication Module Modeling
		3.3.5 Modeling of Command Center Module
	3.4 Mission-Oriented Integrated Simulation Applications
		3.4.1 Example Description
		3.4.2 Simulation Model Integration
		3.4.3 Simulation Solution and Visualization Analysis
	3.5 Conclusion
	References
4 Trajectory Optimization Control System of Intelligent Robot Based on Improved Particle Swarm Optimization Algorithm
	4.1 Introduction
	4.2 Research on Trajectory Planning of Intelligent Robots Based on Improved Particle Swarm Optimization Algorithm
		4.2.1 Trajectory Optimization Control System
		4.2.2 Optimization Goal Establishment
		4.2.3 Particle Velocity and Position Updates
	4.3 Simulation Experiment and Result Analysis
		4.3.1 Simulation Conditions and Parameter Settings
		4.3.2 Simulation Result
	4.4 Conclusions
	References
5 Design of Remote Sensing Image Processing Algorithm Based on Machine Learning
	5.1 Introduction
	5.2 Methodology
		5.2.1 Characterization of RS Data Characteristics
		5.2.2 RS Image Processing Algorithm
	5.3 Result Analysis and Discussion
	5.4 Conclusions
	References
6 Design of Hovering Orbit and Fuel Consumption Analysis for Spacecraft Considering J2 Perturbation
	6.1 Introduction
	6.2 Hovering Control Considering J2 Perturbation
	6.3 Numerical Example
		6.3.1 Variation of Spacecraft Hovering Control Under Different Orbital Elements
		6.3.2 Research on Fuel Consumption in Hovering Orbits
	6.4 Conclusions
	References
7 3D Scene Modeling and Real-Time Infrared Simulation Technology Based on Artificial Intelligence Algorithm
	7.1 Introduction
	7.2 Methodology
		7.2.1 Application of AI in Infrared Image Processing
		7.2.2 3D Scene Modeling Algorithm of Infrared Image
	7.3 Result Analysis and Discussion
	7.4 Conclusion
	References
8 Simulation of Vehicle-Scheduling Model in Logistics Distribution Center Based on Artificial Intelligence Algorithm
	8.1 Introduction
	8.2 Model Building
		8.2.1 Model Hypothesis
		8.2.2 Modeling
	8.3 Optimization Objectives for Logistics Delivery Vehicle Scheduling
	8.4 Simulation Experiment
	8.5 Conclusions
	References
9 Construction of Intelligent Recognition System of Automobile State Based on Digital Image Processing
	9.1 Introduction
	9.2 Methodology
	9.3 Result Analysis and Discussion
	9.4 Conclusions
	References
10 A Survey of Target Orientation Detection Algorithms Based on GPU Parallel Computing
	10.1 Introduction
	10.2 Development Status of Narrowband Beamforming and Realization Technology
	10.3 Development Status of Broadband Beamforming and Realization Technology
	10.4 Overseas and Domestic Research Status of GPU Parallel Computing
	10.5 Conclusion
	References
Part II Intelligent Image and Data Processing
11 Optimal Design of Hydrodynamic Journal Bearing Based on BP Neural Network Optimized by Improved Particle Swarm Algorithm
	11.1 Introduction
	11.2 Hydrodynamic Journal Bearing Lubrication Analysis
		11.2.1 Reynolds Equation
		11.2.2 Oil Film Thickness Equation
		11.2.3 Bearing Oil Film Counterforce
		11.2.4 Discharge Flow
		11.2.5 Friction Power Loss
		11.2.6 Solution Method
	11.3 Mathematical Model for Optimal Design of Hydrodynamic Journal Bearing
		11.3.1 Bearing Minimum Oil Film Thickness hmin Constraint
		11.3.2 Bearing Width-to-Diameter Ratio Λ
		11.3.3 Average Specific Pressure of the Bearing overlinep
		11.3.4 Bearing Clearance Ratio Ψ Constraint
		11.3.5 Bearing Lubricant Flow Q Constraint
		11.3.6 Bearing Lubricant Temperature Rise Δt
		11.3.7 Bearing Load Capacity F
	11.4 Hydrodynamic Journal Bearing Algorithm Coupling
		11.4.1 Particle Swarm Algorithm
		11.4.2 Neural Network Modeling Framework
	11.5 Calculation Examples
		11.5.1 Verify the Accuracy of the Calculation
		11.5.2 Validate Computational Efficiency
	11.6 Conclusion
	References
12 The Intelligent Human–Computer Interaction Method for Application Software of Electrical Energy Metering Based on Deep Learning Algorithm
	12.1 Introduction
	12.2 Composition and Function of Energy Metering APP
	12.3 Main Methods of Man–Machine Interaction of Energy Metering APP
		12.3.1 Classical Human–Computer Interaction Method
		12.3.2 Intelligent Human–Computer Interaction Method
	12.4 Intelligent Human–Computer Interaction Principle of APP Based on Deep Learning
		12.4.1 Neural Network Structure Types of Deep Learning
		12.4.2 Deep Learning Principle Based on Convolutional Neural Network
		12.4.3 Implementation Process of Deep Learning Algorithm Based on Convolutional Neural Network
	12.5 Principle of APP Fingerprint Recognition Human–Computer Interaction Based on Deep Learning
		12.5.1 Deep Learning of Fingerprint Recognition Principle
	12.6 Results of Fingerprint Recognition Simulation Based on Deep Learning
		12.6.1 Fingerprint Identification Simulation
	12.7 Summary
	References
13 Short Text Classification of Invoices Based on BERT-TextCNN
	13.1 Introduction
	13.2 Related Research
	13.3 Research Methodology
		13.3.1 BERT
		13.3.2 TextCNN
	13.4 Experiment
		13.4.1 Experimental Environment and Data Set
		13.4.2 Experimental Setup
		13.4.3 Evaluation Indicators
		13.4.4 Analysis of Experimental Results
	13.5 Conclusion
	References
14 Design of Fully Automatic Calibration Scheme for Load Box Based on Visual Recognition
	14.1 Introduction
	14.2 Technical Proposal
		14.2.1 Overall Design Plan
		14.2.2 Load Output Control System
	14.3 Hardware Composition
		14.3.1 Pin Automatic Insertion Power Supply Device
		14.3.2 Visual Inspection System
		14.3.3 Motor Control System
	14.4 Module Functions
		14.4.1 CCD Detection
		14.4.2 Identification Scheme
		14.4.3 Real-Time Alarm
	14.5 Algorithm Design
		14.5.1 Image Preprocessing
		14.5.2 Image Preprocessing
	14.6 Software Design
	14.7 Conclusion
	References
15 DeepScan: Revolutionizing Garbage Detection and Classification with Deep Learning
	15.1 Introduction
	15.2 Theory of Convolutional Neural Networks
		15.2.1 Traditional Neural Networks
		15.2.2 Convolutional Neural Network
		15.2.3 Image Classification Networks
	15.3 Proposed Methodology
		15.3.1 Image Processing Based on Keras
		15.3.2 Sequential Model Training and Optimization
	15.4 Model Training
	15.5 Conclusion and Future Work
	References
16 Research on Portable Methane Telemetry System Based on TDLAS
	16.1 Introduction
	16.2 Working Principle of Telemetry System
		16.2.1 Beer–Lambert Law
		16.2.2 Selection of CH4 Absorption Line
	16.3 Detection System Design
	16.4 Optical System Design and Simulation
		16.4.1 Optical Component Design
		16.4.2 Simulation and Verification of Optical Systems
	16.5 Methane Concentration Detection Experiments
		16.5.1 Measurement Calibration
		16.5.2 Gas Measurement Accuracy Experiments
	16.6 Summary
	References
17 Recommendation Algorithm Based on Wide&Deep and FM
	17.1 Introduction
	17.2 Related Work
	17.3 Preliminary Knowledge
		17.3.1 Wide&Deep Model
		17.3.2 FM Model
	17.4 Recommendation Model
	17.5 Experiments
		17.5.1 Datasets
		17.5.2 Evaluation Protocols
		17.5.3 Baseline Algorithms
		17.5.4 Experimental Results
	17.6 Conclusion
	References
18 Simulation of E-Commerce Big Data Classification Model Based on Artificial Intelligence Algorithm
	18.1 Introduction
	18.2 Research Method
		18.2.1 Classification of DM
		18.2.2 E-Commerce BD Classification
	18.3 Simulation Analysis
	18.4 Conclusion
	References
19 Research and Implementation of Data Feature Extraction Technology for Multisource Heterogeneous Data in Electric Distribution Network
	19.1 Introduction
	19.2 Related Work
	19.3 Research on Data Feature Extraction Technology for Multisource Heterogeneous Data in Electric Distribution Network
		19.3.1 Fusion of Electric Power Multisource Heterogeneous Data
		19.3.2 Data Feature Extraction Technology for Electric Industry Data
	19.4 Implementation of Data Feature Extraction Technology for Multisource Heterogeneous Data in Electric Distribution Network
		19.4.1 Access and Governance of Electric Data Resources
		19.4.2 Implementation of Feature Extraction Technology for Electric Data
	19.5 Application Results
	References
20 Design and Optimization of Business Decision Support System Based on Deep Learning
	20.1 Introduction
	20.2 Research Method
		20.2.1 Structural Design of Commercial DSS
		20.2.2 System Optimization
	20.3 System Test
	20.4 Conclusion
	References
21 Performance Evaluation of Container Identification Detection Algorithm
	21.1 Introduction
	21.2 Related Work
	21.3 IdentificationText Dataset
		21.3.1 Dataset Description
		21.3.2 Annotation Method
		21.3.3 Downstream Application of IdentificationText Dataset
	21.4 Benchmark
		21.4.1 Experimental Setup
		21.4.2 Evaluation Metric
		21.4.3 Result and Analysis
	21.5 Conclusion
	References
22 Application and Prospect of Deep Learning and Machine Learning Technology
	22.1 Introduction
	22.2 Relationship Between Deep Learning and Machine Learning
	22.3 Comparative Analysis of Machine Learning and Deep Learning
		22.3.1 Comparison of the Required Data Quantity
		22.3.2 Comparison of Data Processing Processes
		22.3.3 Hardware Dependency Comparison
		22.3.4 Comparison of Time Required for Algorithm Model Training
		22.3.5 Comparison of Learning Algorithm Types
	22.4 Prospects
	References
23 Simulation of Intelligent Image Processing Model Based on Machine Learning Algorithm
	23.1 Introduction
	23.2 Research Method
		23.2.1 Medical Image Segmentation Method
		23.2.2 Improved FCM Intelligent Image Processing
	23.3 Simulation Analysis
	23.4 Conclusion
	References
Part III Health Systems and Security
24 Design and Implementation of a Health Monitoring Management Platform Based on IoT and DL
	24.1 Introduction
	24.2 Functional Conception and Structural Design of HMMP
		24.2.1 Health Monitoring
		24.2.2 Management Services
		24.2.3 Functional Design
		24.2.4 Platform Construction
	24.3 HMMP Design Implementation and Function Inspection
		24.3.1 HMMP
		24.3.2 Health Management Indicators
		24.3.3 Platform Function Module Design
		24.3.4 Research on DL Algorithm
	24.4 Experimental Results and Discussion of HMMP
	24.5 Conclusion
	References
25 Design of Hospital Equipment Information Management System Based on Computer Vision Technology
	25.1 Introduction
	25.2 Research Method
		25.2.1 System Structure Design
		25.2.2 Implementation of Key Technologies of the System
	25.3 System Test
	25.4 Conclusion
	References
26 Design and Implementation of an Internet of Things-Based Real-Time Five-Layer Security Surveillance System
	26.1 Introduction
	26.2 Related Work
	26.3 Proposed Architecture
	26.4 Hardware Implementation
		26.4.1 Significance of Arduino Mega
	26.5 System Architecture
		26.5.1 System Experimental
		26.5.2 Face Recognition
		26.5.3 Voice Recognition
		26.5.4 Fingerprint
		26.5.5 Radio Frequency Identification
	26.6 Implementation and Results
		26.6.1 Identification of User
		26.6.2 User not Identified
		26.6.3 Wrong Entry of Password
	26.7 Conclusion and Future Scope
	References
27 Logistics Security Integrated Communication System Under the Background of 5G Artificial Intelligence
	27.1 Introduction
	27.2 Logistics Security Integrated Communication System Under the Background of 5G Artificial Intelligence
	27.3 Overall System Architecture
		27.3.1 The Architecture Design of the System is Divided into Three Logical Layers
		27.3.2 Five Modules
		27.3.3 Hardware Device Environment Deployment
		27.3.4 The Main Results Achieved
		27.3.5 Market Outlook
	27.4 System Development Platform and Tools
	27.5 External Cooperation Situation
	27.6 Suggestions and Prospects
	27.7 Conclusions
	References
28 Deep Learning Unveiled: Investigating Retina Eye Segmentation for Glaucoma Diagnosis
	28.1 Introduction
	28.2 Methodology
		28.2.1 Datasets
		28.2.2 Deep Neural Network Architectures
		28.2.3 Performance Measures
	28.3 Experimental Results and Discussions
	28.4 Conclusion
	References
Part IV Intelligent Teaching Applications
29 Computer Physical Education Teaching Model Based on Deep Learning
	29.1 Introduction
	29.2 PE Resource Recommendation Model Based on DL
		29.2.1 The Role of Multimedia-Assisted Teaching in PE Teaching
		29.2.2 Construction of PE Instructional Resource Model and Learner Model
	29.3 Results Analysis and Discussion
	29.4 Conclusions
	References
30 Research on the Art Design of Green Clothing Based on Image Restoration Technology
	30.1 Introduction
	30.2 Methodology
		30.2.1 Application of Green Design Concept in Clothing Design
		30.2.2 Restoration Algorithm of Green Clothing Image Information
	30.3 Result Analysis and Discussion
	30.4 Conclusions
	References
31 Research on Teaching Reform of Digital Signal Processing Course Based on Python
	31.1 Introduction
	31.2 Teaching Status
	31.3 The Specific Application of Python in Teaching
		31.3.1 Application in Classroom Teaching and Experimental Teaching
		31.3.2 The Application of Python in Course Design
	31.4 Teaching Reform in Practice
	31.5 Conclusions
	References
32 Visual Analysis of Multi-source Temporal Data for Online Learning
	32.1 Introduction
	32.2 Related Work
		32.2.1 Time Series Data Study
		32.2.2 Visualization Methods Study
	32.3 Experiment Method
		32.3.1 Multi-source Time Series Data Fusion
		32.3.2 Visualization Method
	32.4 Experiment and Analysis
		32.4.1 Experiment Preparing
		32.4.2 Experiment Plan
		32.4.3 Experiment Visualization Results
	32.5 Conclusion
	References
33 Application of Deep Learning Technology in College Teaching
	33.1 Introduction
	33.2 The Important Role of Deep Learning in College Chinese Teaching
		33.2.1 Improve Learning Objectives
		33.2.2 Optimize the Teaching Process
		33.2.3 Create a Learning Atmosphere
		33.2.4 Improve Learning Efficiency
	33.3 Material and Methods
		33.3.1 Integration of Deep Learning and Flipped Classroom
		33.3.2 Data Filtering Method
	33.4 Results
		33.4.1 A Survey of College Chinese Learning Methods
		33.4.2 A Survey of the Mode of Listening to College Chinese Classes
	33.5 Discussion
		33.5.1 Curriculum Design and Application
		33.5.2 The Construction of Deep Learning in College Chinese Teaching
	33.6 Conclusion
	References
Author Index