Advances and Trends in Artificial Intelligence. Theory and Applications : 37th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2024, Hradec Kralove, Czech Republic, July 10-12, 2024, Proceedings

• Autore: Fujita Hamido
• Pubblicazione: Singapore : , : Springer Singapore Pte. Limited, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (525 pages)
• Altri autori: CimlerRichard Hernandez-MatamorosAndres AliMoonis
• Nota di contenuto: Intro -- Preface -- Organization -- Keynote Speeches -- The Application of Value Analysis in Large Language Models, Intelligent Services, and Other Aspects -- Behavior Understanding and Embodied Intelligence -- Contents -- Computer Vision -- Boundary-Focused Semantic Segmentation for Limited Wafer Transmission Electron Microscope Images -- 1 Introduction -- 2 Proposed Method -- 3 Experiments -- 3.1 Data Acquisition and Experimental Configurations -- 3.2 Results -- 4 Conclusion -- References -- A Robust Component-Based Template Matching Approach Using Document Layout Graph for Extracting Information -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Overview -- 3.2 Problem Formulation -- 3.3 Graph Construction -- 3.4 Sub-graph Mining -- 3.5 Sub-graph Matching Procedure -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Datasets -- 4.3 Experimental Results -- 4.4 Effectiveness of Softmax to Binary Transition -- 5 Conclusion -- References -- Classifying Endangered Species in High-Risk Areas Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Dataset Creation -- 3.2 Data Augmentation -- 3.3 Transfer Learning -- 3.4 Wildlife Classification -- 4 Experiments and Results -- 4.1 Impact of Data Augmentation -- 5 Conclusions -- References -- Super-Resolution Methods for Wafer Transmission Electron Microscopy Images -- 1 Introduction -- 2 Method -- 3 Experiments -- 3.1 Datasets and Implementation -- 3.2 Results -- 4 Conclusion -- References -- Cyber Security -- Sandbox Environment for Offensive and Defensive Training in Smart Metering -- 1 Introduction -- 1.1 BUTCA Platform -- 1.2 DATEL -- 2 Background and Related Work -- 2.1 Smart Metering -- 2.2 Related Work -- 3 Offensive and Defensive Training -- 3.1 Offensive Scenario -- 3.2 Defensive Scenario -- 4 Sandbox Environment -- 4.1 Sandbox Definition. ; 4.2 Sandbox Deployement -- 5 Testing and Evaluation -- 6 Conclusions and Future Work -- References -- Training Scenario for Security Testing of the Kerberos Protocol -- 1 Introduction -- 2 Background and Related Work -- 2.1 Kerberos Authentication Process -- 2.2 Related Work -- 3 Training Scenario -- 3.1 Sandbox Environment -- 3.2 Pass-the-Ticket Scenario -- 3.3 Golden Ticket Scenario -- 3.4 Silver Ticket Scenario -- 3.5 Testing Security Configuration -- 4 Conclusions and Future Work -- References -- HERMES DXP: An Approach to Military and Non-military Cyber Threat Intelligence Sharing -- 1 Introduction and Context of the HERMES Research -- 2 Current Cyber Security Situation -- 2.1 Key Market Drivers -- 2.2 Key Challenges Faced by the European Defence Industry -- 2.3 Related Scientific Work and the Current Market Situation -- 3 HERMES Approach, Objectives and Contribution -- 4 Proposed High-Level Architecture of HERMES Data Exchange Platform -- 4.1 System Domains -- 4.2 Exchange Registries -- 4.3 Management -- 4.4 Node Block Diagram -- 5 Conclusions and Future Work -- References -- Classification of Datasets Used in Data Anonymization for IoT Environment -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Collecting Datasets -- 3.2 Classifying Datasets -- 4 Results -- 4.1 Limitations of the Research -- 5 Conclusion -- References -- Utilization of Artificial Intelligence for the SIEM Logging Architecture Design in the Context of Smart City -- 1 Introduction -- 2 SMC Data Model -- 2.1 Data Classification -- 3 SIEMs Logging Architecture -- 3.1 Logging Levels -- 3.2 Logging Formats -- 3.3 Collection Methods -- 3.4 Architecture Aspects -- 4 Utilization of AI Tools for SIEM Logging Architecture Design in the Context of Smart City -- 4.1 A Cybersecurity Assets and Risks Model Classification in AI Language Models -- 5 Conclusion -- References. ; Data Mining -- Work in Progress Prediction for Business Processes Using Temporal Convolutional Networks -- 1 Introduction -- 2 Preliminaries -- 2.1 Event Log -- 2.2 Models -- 3 Proposed Approach -- 3.1 Dataset -- 3.2 WiP Attributes of an Event -- 3.3 WiP Time Series Generation -- 3.4 Data Split -- 3.5 Architecture -- 4 Evaluation -- 4.1 Helpdesk -- 4.2 BPIC 2013 Incidents -- 5 Conclusion -- References -- Explainable Machine Learning for Intrusion Detection -- 1 Introduction -- 2 Related Work -- 3 Proposed Improved Explainable Machine Learning Model -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Machine Learning Algorithms -- 3.4 Expalinability Using SHAP and LIME -- 4 Experiments and Results -- 4.1 Machine Learning Results -- 4.2 Explainability Results -- 5 Conclusion and Future Work -- References -- Enhancing False-Sentence Pairs of BERT-Pair for Low-Frequency Aspect Category Detection -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 BERT-Pair -- 3.2 Our Proposed Methods -- 4 Experiment -- 4.1 Experimental Setup -- 4.2 Results -- 5 Discussion -- 5.1 Effect on Low-Frequency Aspect Categories -- 5.2 Possible Mechanism -- 6 Conclusion -- References -- e-Applications -- A Method for Integrating of Knowledge Model and Functional Component and Application in Intelligent Problem Solver -- 1 Introduction -- 2 Related Work -- 3 Integration of Ontology Rela-Model and Functional Component -- 3.1 Ontology Rela-Model -- 3.2 Integration Ontology Rela-Model and the Knowledge of Functions -- 4 Rela-Funcs Model -- 5 Algorithms for Solving Problems on Rela-Funcs Model -- 5.1 Model of Problems on Rela-Funcs Model -- 6 Algorithms for Solving Problems -- 7 Design an IPS in 2D-Analytic Geometric in High-School -- 7.1 Designing a Knowledge-Based System -- 7.2 Design the Inference Engine of the Application -- 7.3 Testing -- 8 Conclusion and Future Work. ; References -- A Comparative Study of Transfer Learning on CNN-Based Models for Fault and Anomaly Detection in Industrial Processes -- 1 Introduction -- 2 Background -- 3 Literature Review -- 4 Research Framework -- 5 Case Study -- 5.1 Experimental Setting -- 5.2 Fault Detection During 3D Printing Process -- 5.3 Corrosion Detection on Equipment -- 5.4 Application of TL Technique -- 6 Results and Discussions -- 6.1 Fault Detection During 3D Printing Process -- 6.2 Corrosion Detection in Industrial Plants -- 7 Conclusions -- References -- A Computer Vision Based Approach for Energy-Efficient Air Conditioner Control -- 1 Introduction -- 2 Related Works -- 2.1 Human Detection -- 2.2 Smart Air Conditioner -- 2.3 Challenges and Considerations -- 3 Methodology -- 3.1 Dataset -- 3.2 Object Detector -- 3.3 Training Setup -- 4 Experiment -- 4.1 Transfer Learning in Training -- 4.2 Deployment -- 4.3 Results and Discussion -- 5 Conclusion and Future Works -- References -- Verifying Autoencoders for Anomaly Detection in Predictive Maintenance -- 1 Introduction -- 2 Background -- 2.1 Neural Networks -- 2.2 Verification -- 3 Case Study -- 4 Experimental Setup -- 4.1 Models and Training -- 4.2 Property Specification and Verification -- 5 Experimental Results -- 6 Conclusions and Future Work -- References -- Fog-Based Ransomware Detection for Internet of Medical Things Using Lighweight Machine Learning Algorithms -- 1 Introduction -- 2 Related Research -- 2.1 Internet of Things -- 2.2 Deep Learning Architectures -- 3 Proposed Methodology -- 3.1 Dataset -- 3.2 Implementation -- 3.3 Model Training and Evaluation -- 3.4 Result -- 4 Conclusion -- References -- Machine Learning -- Live Product Line Engineering Using Density-Based Clustering of CAD Models -- 1 Introduction -- 2 Related Works -- 3 Problem Definition and Available Data -- 4 Approach. ; 4.1 Live Product Line Approach -- 4.2 Feature Extraction and Preprocessing -- 4.3 Clustering -- 4.4 Validation -- 5 Experimental Findings -- 5.1 Baseline Scenario -- 5.2 Principal Component Analysis (PCA) -- 5.3 Hyperparameter Optimization -- 5.4 Manual Validation -- 6 Summary and Outlook -- References -- Evaluation Techniques for Long Short-Term Memory Models: Overfitting Analysis and Handling Missing Values -- 1 Introduction -- 2 Background and Related Studies -- 3 Proposed Approach -- 3.1 Long Short-Term Memory and Teacher Forcing -- 3.2 Overfitting Tests -- 3.3 Missing Values -- 4 Experimental Assessment -- 4.1 The Tennessee Eastman Process Dataset -- 4.2 Architecture, Hyperparameters and Additional Parameters -- 5 Experimental Results -- 5.1 Overfitting Tests -- 5.2 Missing Values -- 6 Discussions and Conclusions -- References -- Representation and Generation of Music: Incorporating Composers' Perspectives into Deep Learning Models -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 PreProcessing Data -- 3.2 OrchNet -- 3.3 CompoNet -- 3.4 Implementation Tools and Environment -- 3.5 Post-processing Results -- 4 Human-Subject Evaluation -- 4.1 Test Design -- 4.2 Conducting the Test and Demography of Respondents -- 4.3 Test Results -- 5 Conclusion -- References -- Causal Deep Q Networks -- 1 Introduction -- 2 Related Works -- 3 Causal DQN (C-DQN) -- 3.1 Probabilistic Easy variational Causal Effect (PEACE) -- 3.2 C-DQN Architecture -- 4 Results -- 5 Conclusion and Future Works -- References -- Towards Addressing an Open Problem in Coupled Matrix Tensor Factorization for Satellite Imagery Data Using Human-in-Loop -- 1 Introduction -- 2 Related Work -- 2.1 Image Processing Approaches for Imputation -- 2.2 Tensor Completion -- 3 Background and Notations -- 4 CMTF4SI -- 5 Experiments -- 5.1 Datasets and Setup. ; 5.2 Evaluation of CMTF4SI Against CMTF-OPT.
• Titolo autorizzato: Advances and Trends in Artificial Intelligence. Theory and Applications
• ISBN: 981-9746-77-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910872191003321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science Series