Big Data and Security : 5th International Conference, ICBDS 2023, Nanjing, China, December 22-24, 2023, Revised Selected Papers, Part I

• Autore: Tian Yuan
• Pubblicazione: Singapore : , : Springer, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (258 pages)
• Altri autori: MaTinghuai KhanMuhammad Khurram
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Big Data and New Method -- Recurrent Age Recognition Based on Manifold Learning -- 1 Introduction -- 2 Related Work -- 3 The Proposed Methodology MLPAP -- 3.1 Improved Age Label Distribution -- 3.2 Personal Aging Pattern -- 3.3 MLPAP -- 4 Experiment -- 4.1 Dataset -- 4.2 Evaluation Criteria -- 4.3 Network Initialization and Training -- 4.4 Experimental Results and Analysis -- 5 Conclusion -- References -- A Three Layer Chinese Sentiment Polarity Detection Framework with Case Study -- 1 Introduction -- 2 Related Work -- 3 A Specialized Framework -- 3.1 Module 1-3: Sentence Collector, Corpora Learner and Basic Lexicons -- 3.2 Module 4: Lexicon Producer -- 3.3 Module 5: Vector Transformer and New Corpora -- 4 Experimental Analysis -- 5 Conclusion -- References -- Big Data Intelligence Empowered Specialized Disciplines Development Pattern Recognition in Power Industry Universities -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Source -- 3.2 Research Design -- 4 Results -- 4.1 Characteristics of Disciplinary Development of NCEPU -- 4.2 Characteristics of Disciplinary Development of SUEP -- 4.3 Characteristics of Disciplinary Development of CSUST -- 4.4 Characteristics of Disciplinary Development of NJIT -- 5 Conclusion and Discussion -- 5.1 Highly Interdisciplinary Integration -- 5.2 Multidisciplinary Collaborative Innovation -- 5.3 Deepening Disciplinary Culture Construction -- References -- A Survey on Real-Time Semantic Segmentation Based on Deep Learning -- 1 Introduction -- 2 Real-Time Semantic Segmentation Network -- 2.1 Single-Branch Network -- 2.2 Double-Branch Network -- 2.3 Three-Branch Network -- 3 Feature Fusion Module -- 3.1 Serial Connection Structure -- 3.2 Parallel Multi-branch Structure -- 4 Model Performance Evaluation. ; 4.1 Datasets -- 4.2 Metrics -- 4.3 Model Comparison -- 5 Future Research Trends and Conclusions -- References -- A Clustering Method for Distribution Network Load Curve Based on Fast DDTW -- 1 Introduction -- 2 Dynamic Time Warping Algorithm -- 2.1 DTW Algorithm -- 2.2 The Necessity of Using DTW for Similarity Measurement -- 2.3 The "Singularity" Problem of Dynamic Time Planning -- 3 K-Medoids Clustering Method Based on Fast DDTW -- 3.1 Derivative Dynamic Time Warping -- 3.2 Fast DDTW Clustering Algorithm -- 3.3 Gaussian Filter -- 3.4 K-Medoids Clustering -- 4 Calculation Example Analysis -- 4.1 Data Preprocessing -- 4.2 Clustering Quality Evaluation Index -- 4.3 Algorithm Evaluation -- 5 Conclusion -- References -- Object Detection Model Based on Attention Mechanism -- 1 Introduction -- 2 Relevant Technology -- 2.1 Introduction to YOLO Series Models -- 2.2 Attention Mechanism -- 2.3 Data Set Introduction -- 3 The Object Detection Method Based on Attention Mechanism -- 3.1 YOLOv7 Network Structure -- 3.2 Network Architecture Design -- 4 Experimental Results and Analysis -- 4.1 Experimental Environment -- 4.2 Training Parameters -- 4.3 Experimental Dataset -- 4.4 Evaluation Metrics -- 4.5 Comparative Experiments -- 5 Conclusion -- References -- Gas Pressure Prediction and Application with Missing Data Imputation Techniques for Gas Regulator Data -- 1 Introduction -- 2 Methodology -- 2.1 Imputation -- 2.2 Prediction -- 3 Dataset Introduction and Processing -- 3.1 Dataset -- 3.2 Data Characteristics -- 3.3 Data Preprocessing -- 4 Result -- 4.1 Evaluation Method -- 4.2 Gas Pressure Imputation -- 4.3 Gas Pressure Prediction -- 4.4 Implementation of Gas Pressure Prediction Models -- 4.5 Result of Gas Pressure Prediction -- 5 Conclusion -- References. ; Advances, Patterns and Future Potential of Big Data Technology Research for New Energy Sources and Energy Storage Systems -- 1 Introduction -- 2 Advancements in the Research of BD Technology for NEP and ESS -- 3 Research Trends of BD Application in NEP and ESS -- 3.1 Multidimensional Data Analysis -- 3.2 Provision of Historical Data Services -- 3.3 Expanded Usage Scenarios -- 3.4 Comprehensive Monitoring and Management -- 4 Future Research Directions in NEP and ESS Based on BD Technology -- 5 Conclusion -- References -- Construction of Enterprise Capital Allocation Efficiency Model Based on Fuzzy Clustering Algorithm -- 1 Introduction -- 2 Methodology -- 2.1 Theoretical Analysis of Enterprise Financial Management -- 2.2 Enterprise Capital Allocation Efficiency Model -- 3 Result Analysis and Discussion -- 4 Conclusions -- References -- Artificial Intelligence and Machine Learning -- Analysing Potential of ResNet for Transfer Learning with Stochastic Depth -- 1 Introduction -- 2 Related Work -- 2.1 Dropout -- 2.2 Transfer Learning -- 2.3 Deep Residual Network and Stochastic Depth -- 3 Methodology -- 4 Experiment and Results -- 4.1 CIFAR-10 -- 4.2 OXFORD-IIIT PET -- 5 Conclusion -- References -- A Survey of Research Progresses on Instance Segmentation Based on Deep Learning -- 1 Introduction -- 2 DL-BASED Instance Segmentation Methods -- 2.1 Fully Supervised Learning -- 2.2 Semi-supervised Learning Method -- 2.3 Unsupervised Learning Method -- 3 Datasets and Experimental Evaluation -- 3.1 MS COCO Dataset -- 3.2 Cityscapes Dataset -- 3.3 Other Special Scenario Datasets -- 4 Application -- 4.1 Intelligent Driving Field -- 4.2 Face Recognition Field -- 4.3 Medical Field -- 4.4 Industrial Manufacturing Field -- 4.5 Agricultural Field -- 5 Prospect and Conclusion -- References. ; Charting the Landscape of Multi-view Stereo: An In-Depth Exploration of Deep Learning Techniques -- 1 Introduction -- 2 Background -- 3 Depth Map-Based Approaches -- 4 Volumetric Approaches -- 5 Semi-supervised and Unsupervised Approaches -- 6 MVS Benchmarks -- 7 Conclusion -- References -- A Survey of Federated Learning: Review, Attacks, Defenses -- 1 Introduction -- 2 Overview of FL -- 2.1 Federated Learning -- 2.2 Types of FL -- 3 Poisoning Attacks and Defenses of FL -- 3.1 Data Poisoning Attacks -- 3.2 Model Poisoning Attacks -- 3.3 Defenses -- 4 Summary -- References -- ROMA: Reverse Model-Based Data Augmentation for Offline Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 2.1 Offline RL -- 2.2 Data Augmentation (DA) -- 3 Trajectory Augment by Reversed Model -- 3.1 Preliminaries -- 3.2 Constructing the Virtual Transition Dataset -- 3.3 Training the Reverse Model -- 3.4 Improving Trajectory Quality by Splicing -- 3.5 Combination with Model-Free Algorithms -- 4 Experiments -- 4.1 Simple Environment -- 4.2 Continuous Environment -- 5 Discussion -- 6 Conclusion -- References -- Application Research of Digital Intelligence Technology in Mining Electric Power Equipment Fault Cases: Taking Text Mining Technology as an Example -- 1 Introduction -- 2 Overview of Text Mining -- 2.1 Development Process of Text Mining -- 2.2 Difficulties in Text Mining -- 3 Text Mining Framework Construction for Typical Fault Cases of Power Equipment -- 4 Text Mining Application for Typical Fault Cases of Electric Power Equipment -- 4.1 Power Equipment Fault Name Entity Recognition -- 4.2 Power Equipment Fault Entity Relationship Extraction -- 4.3 Construction of Knowledge Graph for Fault Power Equipment -- 4.4 Automatic Evaluation of Power Equipment Health Status -- 5 Prospect of Text Mining for Typical Failure Cases of Electric Power Equipment -- 6 Conclusion. ; References -- Deep Learning-Based Attribute Graph Clustering: An Overview -- 1 Introduction -- 2 Related Work -- 2.1 Notations -- 2.2 Data Augmentation -- 2.3 Pretraining -- 3 Overview of Recent Graph Clustering Methods -- 3.1 Generation Method -- 3.2 Adversarial Method -- 3.3 Contrastive Method -- 3.4 Network-Assisted Loss -- 4 Experiments -- 4.1 Experimental Result -- 4.2 Dataset -- 5 Conclusion -- References -- Construction of Demand Forecasting Model of Human Resources Professional Structure Based on Deep Learning -- 1 Introduction -- 2 Research Method -- 3 Result Analysis -- 4 Conclusions -- References -- Financial Management and Early Warning System of Non-profit Organizations Based on Artificial Neural Network -- 1 Introduction -- 2 Financial Management and Early Warning of Non-profit Organizations -- 2.1 Overview of Financial Management of Nonprofit Organizations -- 2.2 Procedures of Financial Risk Management -- 2.3 Research Background and Significance -- 3 Non-profit Organization Financial Management and Early Warning System Based on Artificial Neural Network -- 3.1 Problems Existing in Non-profit Financial Management -- 3.2 Countermeasures for Financial Risk Control of Non-profit Organizations -- 4 Conclusions -- References -- Author Index.
• Titolo autorizzato: Big Data and Security
• ISBN: 9789819743872; 9789819743865
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910874681403321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science Series