Advances and trends in artificial intelligence. Theory to practice : 35th international conference on industrial, engineering and other applications of applied intelligent systems, IEA/AIE 2022, Kitakyushu, Japan, July 19-22, 2022, proceedings / / Hamido Fujita, [and three others], editors

• Record Nr.: UNISA996485665103316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2022]; ©2022
• ISBN: 3-031-08530-2
• Descrizione fisica: 1 online resource (932 pages)
• Collana: Lecture notes in computer science. Lecture notes in artificial intelligence
• Disciplina: 006.3
• Soggetti: Artificial intelligence; Artificial intelligence - Industrial applications
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Includes index.
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Industrial Applications -- Comparative Study of Methods for the Real-Time Detection of Dynamic Bottlenecks in Serial Production Lines -- 1 Introduction -- 1.1 On the Dynamic Nature of Bottlenecks -- 1.2 The Need for Real-Time Bottleneck Detection -- 2 Related Work on Bottleneck Detection -- 2.1 Detection Using Bottleneck Walk with Buffer Levels -- 2.2 Detection Using Active Period Method with Machine States -- 2.3 Detection Using Interdeparture Time Variance with Process Times -- 3 Design of the Comparative Study for Bottleneck Detection -- 4 Detection Results using BNW, APM and ITV -- 4.1 Bottleneck Detection with Bottleneck Walk -- 4.2 Bottleneck Detection Using the Active Period Method -- 4.3 Bottleneck Detection Using Interdeparture Time Variances -- 5 Comparison -- 5.1 Comparison of 20%-Bottleneck Results -- 5.2 Results for Varying Bottleneck Process Times (10% to 100%) -- 6 Conclusion -- References -- Ultra-short-Term Load Forecasting Model Based on VMD and TGCN-GRU -- 1 Introduction -- 2 Methodology -- 2.1 Variational Mode Decomposition -- 2.2 Temporal Graph Convolution Network -- 2.3 VTGG Model -- 3 ; Experiments and Discussions -- 3.1 Data -- 3.2 Evaluation Method -- 3.3 Contrast Experimental Model -- 3.4 Experimental Environment and Parameter Settings -- 3.5 Experimental Results -- 4 Conclusion -- References -- Learning to Match Product Codes -- 1 Introduction -- 2 Related Work -- 3 Data Wrangling -- 4 Approximate String Matching -- 5 Deep Learning -- 6 System Structure Design -- 7 Experiments and Results -- 7.1 Exploratory Data Analysis -- 7.2 Comparison of Approximate String Matching Methods -- 7.3 Comparison of Deep Learning Methods -- 8 Conclusion and Future Work -- References -- ResUnet: A Fully Convolutional Network for Speech Enhancement in Industrial Robots -- 1 Instruction.; 2 Related Work -- 2.1 U-Net -- 2.2 ResNet -- 2.3 Huber Loss Function -- 3 The Proposed Method -- 3.1 Overview of the Proposed Method -- 3.2 Structure of Res-Unet -- 3.3 Optimization Function -- 4 Experimental Methods -- 4.1 Dataset -- 4.2 Feature Transformation -- 4.3 Training Schemes -- 4.4 Evaluation Score -- 5 Experimental Results -- 6 Conclusion -- References -- Surface Defect Detection and Classification Based on Fusing Multiple Computer Vision Techniques -- 1 Introduction -- 2 Technical Framework -- 3 Online Defect Detection -- 3.1 Defect Detection Based on Conventional CV Technology -- 3.2 Defect Detection Based on CNN -- 3.3 Detection Result Fusion -- 4 Offline Defect Classification -- 5 Case Study and Experiment -- 5.1 Overall System Architecture -- 5.2 Data Acquisition -- 5.3 Online Defect Detection -- 6 Conclusion -- References -- Development of a Multiagent Based Order Picking Simulator for Optimizing Operations in a Logistics Warehouse -- 1 Introduction -- 2 Order Picking Simulator -- 2.1 Setting of Simulator -- 2.2 Cart Behavior Decision Algorithm -- 3 Experiments for Simulator Performance Evaluation -- 3.1 Experimental Setting -- 3.2 Results -- 4 Discussion -- 5 Conclusion -- References -- Health Informatics -- Predicting Infection Area of Dengue Fever for Next Week Through Multiple Factors -- 1 Introduction -- 2 Related Work -- 2.1 Study on the Factor of Dengue Fever Model -- 3 Research Methodology -- 3.1 Research Characteristics -- 3.2 Model Scoring -- 4 Research Experiment -- 4.1 Data Collection -- 4.2 Data Preprocessing -- 4.3 Model Parameter Adjustment -- 4.4 Experimental Results and Analysis -- 4.5 Important Characteristics of the Model -- 4.6 Adjusted Model Results and Analysis -- 5 Conclusion and Future Research -- References.; Hospital Readmission Prediction via Personalized Feature Learning and Embedding: A Novel Deep Learning Framework -- 1 Introduction -- 2 Basic Notation and Problem Definition -- 3 The Proposed Framework -- 3.1 Personalized Feature Learning and Embedding -- 3.2 Personalized Prediction -- 4 Experimental Setup -- 4.1 Dataset Description -- 4.2 Data Preprocessing -- 4.3 Baseline Approaches -- 4.4 Implementation Details and Evaluation Strategies -- 5 Results and Discussion -- 5.1 Performance Evaluation -- 5.2 Clinical Feature Interdependencies -- 6 Conclusion -- References -- Intelligent Medical Interactive Educational System for Cardiovascular Disease -- 1 Introduction -- 2 Materials and Methods -- 2.1 Medical Teaching Materials -- 2.2 Patient-Orient Healthcare Documents -- 2.3 System Design -- 2.4 DAG Structure -- 2.5 Keyword Statistics Architecture -- 3 Result and Discussion -- 3.1 Develop a Patient-Centered Educational Interaction System -- 3.2 Evaluation of Cardiovascular Health Education Data -- 4 Future Work -- References -- Evolutionary Optimization for CNN Compression Using Thoracic X-Ray Image Classification -- 1 Introduction -- 2 Related Work -- 2.1 CNN for Xray Images Classification -- 2.2 Channel Pruning -- 3 Proposed Method -- 3.1 Compression-CNN-XRAY -- 4 ; Experiments -- 4.1 Experiment Configuration and Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- An Oriented Attention Model for Infectious Disease Cases Prediction -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 4 The Proposed OAM -- 4.1 Oriented Attention Unit (OAU) -- 4.2 Temporal Fusion Layer -- 5 Experiments -- 5.1 Settings -- 5.2 Study on Attention Combinations -- 5.3 Performance Comparisons -- 6 Conclusions -- References -- The Differential Gene Detecting Method for Identifying Leukemia Patients -- 1 Introduction -- 2 Proposed Method.; 3 Experiments and Results -- 4 Conclusions -- References -- Epidemic Modeling of the Spatiotemporal Spread of COVID-19 over an Intercity Population Mobility Network -- 1 Introduction -- 2 The Proposed Approach -- 2.1 SEIR Model (Single-Network) -- 2.2 M-Urb-SEIR (Urban Network Epidemic Framework) -- 2.3 Addressing the Challenges of a Deterministic Epidemic Model -- 3 Experimental Settings -- 3.1 Datasets -- 3.2 Competitors -- 3.3 Evaluation Metrics -- 4 Experimental Results -- 5 Conclusion -- References -- Skin Cancer Classification Using Different Backbones of Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Model Configuration -- 5 Experimental Results -- 6 Conclusion and Future Work -- References -- Cardiovascular Disease Detection on X-Ray Images with Transfer Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Data Pre-processing -- 3.2 Proposed Model for Cardiovascular Disease Detection -- 4 Experiments -- 4.1 Data Set -- 4.2 Evaluation Methods and Baselines -- 4.3 Experimental Results -- 4.4 Discussion on Experimental Results -- 5 Conclusion -- References -- Causal Reasoning Methods in Medical Domain: A Review -- 1 Introduction -- 2 Probability-Based Reasoning Methods -- 2.1 Causal Bayesian Networks -- 2.2 Causal Graph -- 2.3 Probability Tree -- 3 Model-Based Reasoning Methods -- 3.1 SCM -- 3.2 RCM -- 3.3 MSM -- 4 Regression-Based Reasoning Methods -- 4.1 Granger Causality Test -- 5 Balancing-Based Reasoning Methods -- 5.1 Propensity Score Matching -- 5.2 Re-weighting -- 5.3 Confounder Balancing -- 6 Conclusion and Discussion -- References -- Optimization -- Enhancing a Multi-population Optimisation Approach with a Dynamic Transformation Scheme -- 1 Introduction -- 2 Related Work -- 2.1 The Original AMPO Algorithm -- 2.2 Other Metaheuristic Algorithms -- 3 The Enhanced Search Framework.; 4 The Empirical Evaluation -- 5 Concluding Remarks -- References -- A Model Driven Approach to Transform Business Vision-Oriented Decision-Making Requirement into Solution-Oriented Optimization Model -- 1 Introduction -- 2 Past Related Studies -- 2.1 Theorical Foundation of MDE -- 2.2 Previous Experiences in M2M -- 3 MDE for Decision-Making Process Design -- 3.1 Cognitive Process for Decision-Making System -- 3.2 Cognitive Process-Based Model Driven Architecture -- 4 PIM to PSM Transformation Applied to TSP -- 4.1 Specification of Solution-Oriented Mathematical Meta-model (SMM) -- 4.2 Transformation Process -- 5 Case Study -- 6 Conclusion and Research Perspectives -- References -- A Hybrid Approach Based on Genetic Algorithm with Ranking Aggregation for Feature Selection -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 The Filter Based Ranking Aggregation -- 3.2 The RA-GA Algorithm -- 4 Empirical Settings -- 5 Experimental Results -- 5.1 RQ1: How Does the Proposed Approach Perform Comparing with Some State-of-the-Art Methods? -- 5.2 RQ2: What is the Impact of the Subset's Size Produced by RA-GA? -- 6 Conclusion -- References -- A Novel Type-Based Genetic Algorithm for Extractive Summarization -- 1 Introduction -- 2 Our Proposed Type-Based GA for Extractive Summarization -- 2.1 ; Chromosome Encoder -- 2.2 Fitness Function -- 2.3 The Proposed Type-Based GA -- 3 Related Works -- 4 Empirical Settings -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Tuning Parameters -- 5 Results -- 6 Conclusion -- References -- Dragonfly Algorithm for Multi-target Search Problem in Swarm Robotic with Dynamic Environment Size -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Simulation Parameters Setup -- 3.2 Environment Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- Video and Image Processing.; Improved Processing of Ultrasound Tongue Videos by Combining ConvLSTM and 3D Convolutional Networks.