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Biblioteca

MARC Lista (tabellare)
Advances and trends in artificial intelligence : from theory to practice : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings, part II / / Hamido Fujita [and three others] editors
Advances and trends in artificial intelligence : from theory to practice : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings, part II / / Hamido Fujita [and three others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (644 pages)
Disciplina 006.3
Collana Lecture Notes in Computer Science
Soggetto topico Artificial intelligence
ISBN 3-030-79463-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910495203903321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances and trends in artificial intelligence : artificial intelligence practices : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings. Part I / / Hamido Fujita [and three others] editors
Advances and trends in artificial intelligence : artificial intelligence practices : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings. Part I / / Hamido Fujita [and three others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (640 pages)
Disciplina 006.3
Collana Lecture Notes in Computer Science
Soggetto topico Artificial intelligence
ISBN 3-030-79457-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910495204403321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances and trends in artificial intelligence : from theory to practice : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings, part II / / Hamido Fujita [and three others] editors
Advances and trends in artificial intelligence : from theory to practice : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings, part II / / Hamido Fujita [and three others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (644 pages)
Disciplina 006.3
Collana Lecture Notes in Computer Science
Soggetto topico Artificial intelligence
ISBN 3-030-79463-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464395503316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances and trends in artificial intelligence : artificial intelligence practices : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings. Part I / / Hamido Fujita [and three others] editors
Advances and trends in artificial intelligence : artificial intelligence practices : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26-29, 2021 : proceedings. Part I / / Hamido Fujita [and three others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (640 pages)
Disciplina 006.3
Collana Lecture Notes in Computer Science
Soggetto topico Artificial intelligence
ISBN 3-030-79457-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464401403316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances and Trends in Artificial Intelligence. Theory and Applications [[electronic resource] ] : 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Shanghai, China, July 19–22, 2023, Proceedings, Part II / / edited by Hamido Fujita, Yinglin Wang, Yanghua Xiao, Ali Moonis
Advances and Trends in Artificial Intelligence. Theory and Applications [[electronic resource] ] : 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Shanghai, China, July 19–22, 2023, Proceedings, Part II / / edited by Hamido Fujita, Yinglin Wang, Yanghua Xiao, Ali Moonis
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (430 pages)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Artificial Intelligence
ISBN 3-031-36822-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Classification and Case-Based Reasoning -- Computer Vision -- Decision Making -- E-Learning -- Information Fusion -- Knowledge Graph and Link Prediction -- Machine Learning Theory -- Pattern Recognition -- Industrial Applications -- Natural Language Processing -- Optimization -- Prediction -- Reinforcement Learning -- Security -- Various Applications.
Record Nr. UNISA-996542666503316
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances and Trends in Artificial Intelligence. Theory and Applications : 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Shanghai, China, July 19–22, 2023, Proceedings, Part II / / edited by Hamido Fujita, Yinglin Wang, Yanghua Xiao, Ali Moonis
Advances and Trends in Artificial Intelligence. Theory and Applications : 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Shanghai, China, July 19–22, 2023, Proceedings, Part II / / edited by Hamido Fujita, Yinglin Wang, Yanghua Xiao, Ali Moonis
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (430 pages)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Artificial Intelligence
ISBN 3-031-36822-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Classification and Case-Based Reasoning -- Computer Vision -- Decision Making -- E-Learning -- Information Fusion -- Knowledge Graph and Link Prediction -- Machine Learning Theory -- Pattern Recognition -- Industrial Applications -- Natural Language Processing -- Optimization -- Prediction -- Reinforcement Learning -- Security -- Various Applications.
Record Nr. UNINA-9910734862603321
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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
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
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (932 pages)
Disciplina 006.3
Collana Lecture notes in computer science. Lecture notes in artificial intelligence
Soggetto topico Artificial intelligence
Artificial intelligence - Industrial applications
ISBN 3-031-08530-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNINA-9910590055603321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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
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
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (932 pages)
Disciplina 006.3
Collana Lecture notes in computer science. Lecture notes in artificial intelligence
Soggetto topico Artificial intelligence
Artificial intelligence - Industrial applications
ISBN 3-031-08530-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNISA-996485665103316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in Engineering Research and Application : Proceedings of the International Conference, ICERA 2018 / / edited by Hamido Fujita, Duy Cuong Nguyen, Ngoc Pi Vu, Tien Long Banh, Hermann Horst Puta
Advances in Engineering Research and Application : Proceedings of the International Conference, ICERA 2018 / / edited by Hamido Fujita, Duy Cuong Nguyen, Ngoc Pi Vu, Tien Long Banh, Hermann Horst Puta
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (xi, 603 pages)
Disciplina 620
Collana Lecture Notes in Networks and Systems
Soggetto topico Applied mathematics
Engineering mathematics
Artificial intelligence
Mathematical and Computational Engineering
Artificial Intelligence
ISBN 3-030-04792-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910337615103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Information and Database Systems : 16th Asian Conference, ACIIDS 2024, Ras Al Khaimah, UAE, April 15-18, 2024, Proceedings, Part I
Intelligent Information and Database Systems : 16th Asian Conference, ACIIDS 2024, Ras Al Khaimah, UAE, April 15-18, 2024, Proceedings, Part I
Autore Nguyen Ngoc Thanh
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer, , 2024
Descrizione fisica 1 online resource (342 pages)
Altri autori (Persone) ChbeirRichard
ManolopoulosYannis
FujitaHamido
HongTzung-Pei
NguyenLe Minh
WojtkiewiczKrystian
Collana Lecture Notes in Computer Science Series
ISBN 9789819749829
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Advanced Data Analysis Methods -- Continual AE-WGAN for Unsupervised Anomaly Detection in Streaming Data -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Overview -- 3.2 Learning Step 1: Autoencoder Training -- 3.3 Learning Step 2: WGAN-GP Training -- 3.4 Anomaly Score-Based Prediction -- 4 Experimental Results -- 4.1 Experiment Setup -- 4.2 Comparing Methods -- 4.3 Ablation Study -- 5 Conclusion -- References -- Energy Measurement System for Data Lake: An Initial Approach -- 1 Introduction -- 2 Related Work -- 3 Power Measurement Model -- 4 Energy Measuring System for a Data Lake -- 5 Experimental Evaluation -- 5.1 AUDAL Datalake and DLBench+ -- 5.2 System Setup and Experimental Methodology -- 5.3 Energy Measurement Results -- 6 Conclusions and Future Work -- References -- CDER: Collaborative Evidence Retrieval for Document-Level Relation Extraction -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 Encoder Module -- 3.3 Document-Level Bipartite Graph -- 3.4 Entity Pair-Aware GATs -- 3.5 Evidence Prediction -- 3.6 Training Objective -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Results -- 4.3 Ablation Study -- 5 Conclusion -- References -- Stochastic Approaches for Criteria Weight Identification in Multi-criteria Decision Analysis -- 1 Introduction -- 2 Preliminaries -- 2.1 Particle Swarm Optimization -- 2.2 The Characteristic Objects Method -- 2.3 Stochastic IdenTification of Weights -- 3 Study Case -- 4 Conclusions -- References -- Exploring Data Preparation Modules by Examples -- 1 Introduction -- 2 Background -- 2.1 Data Example Generation -- 2.2 Related Work and Scope of Our Work -- 3 Module Discovery -- 3.1 Feedback-Driven Module Discovery -- 3.2 Incremental Ranking of Candidate Modules -- 4 Evaluation.
4.1 Assessing the Performance Using a Synthetic Dataset -- 4.2 Discovering Real-World Scientific Modules -- 4.3 Efficiency -- 5 Conclusions -- References -- A Novel Approach to the Use of Explainability to Mine Network Intrusion Detection Rules -- 1 Introduction -- 2 Related Work -- 3 Background and Dataset -- 3.1 Explainable Artificial Intelligence -- 3.2 Random Forest Algorithm -- 3.3 Dataset Description -- 4 Proposed Method for SIEM Rules Enhancement -- 4.1 Definition of Static SIEM Rules -- 4.2 Novel Method for SIEM Rules Mining via xAI -- 5 Experiments and Results -- 6 Discussion -- 7 Conclusion -- References -- AI-Driven Cybersecurity and Medical Solutions -- IDRF: An Improved Dynamic Random Forest Approach for Blockchain Time Series Data Classification -- 1 Introduction -- 1.1 Contributions -- 1.2 Paper Organization -- 2 Related Work -- 3 Classification Approaches -- 3.1 Baseline Approach: Random Forest Tree -- 3.2 Dynamic Random Forest (DRF) -- 3.3 Proposed Improved Dynamic Random Forest (IDRF) -- 4 Experimental Results -- 4.1 Dataset Description -- 4.2 Root Main Square Error (RMSE) -- 4.3 Accuracy -- 4.4 Execution Time -- 5 Conclusion -- References -- Oral Diseases Recognition Based on Photographic Images and Dental Decay Diagnosis -- 1 Introduction -- 2 Literature Review -- 3 Data Material and Methodology -- 4 The Results -- 5 Conclusion -- References -- Multifaceted ECG Feature Extraction for AFIB Detection: Using Traditional Machine Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 The Method for Processing of ECG Data to Detect AFIB -- 3.1 Data Preprocessing -- 3.2 Feature Extraction -- 3.3 Training Model -- 3.4 Evaluation -- 4 Experimental Results -- 5 Conclusion and Future Works -- References -- Automation of the Analysis of Medical Interviews to Improve Diagnoses Using NLP for Medicine -- 1 Introduction -- 2 Related Works.
3 Proposed Approach -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Results of Experiments -- 5 Discussion -- 6 Conclusions -- References -- Application of Generative Models -- FramedTruth: A Frame-Based Model Utilising Large Language Models for Misinformation Detection -- 1 Introduction -- 2 Related Works -- 3 FramedTruth Model -- 4 Experiments and Results -- 4.1 Datasets and Generation -- 4.2 Experiment 1: Performance Comparison -- 4.3 Experiment 2: Ablation Study -- 4.4 Experiment 3: Case Study -- 5 Conclusion and Future Work -- References -- Named Entity Recognition Model for Polish Books -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 NER Definition for Books -- 3.2 PoLitBert -- 4 Experiments and Results -- 4.1 Named Entity Extraction Evaluation -- 4.2 Prediction Time Evaluation -- 5 Conclusion -- References -- Building the ArabNER Corpus for Arabic Named Entity Recognition Using ChatGPT and Bard -- 1 Introduction -- 2 Related Work -- 3 Methodology for Building ArabNER Corpus -- 3.1 Overview -- 3.2 Web Scraping -- 3.3 Data Generation -- 3.4 Pre-processing -- 3.5 Annotation Method -- 4 Evaluation -- 5 Conclusion -- References -- Professionally Diverse: AI-Generated Faces for Targeted Advertising -- 1 Introduction -- 2 Evolution of Generative Adversarial Networks for Image Synthesis -- 3 Data Collection and Preparation -- 4 Experiments with Generating Images -- 5 Conclusions -- References -- Optimizing Neural Topic Modeling Pipelines for Low-Quality Speech Transcriptions -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Embedding Models -- 3.2 Dimensionality Reduction Methods -- 3.3 Clustering Methods -- 3.4 Topic Representation -- 3.5 Data -- 3.6 Evaluation Metrics -- 3.7 Experiment Setup -- 4 Results -- 5 Conclusions -- References -- OrphaGPT: An Adapted Large Language Model for Orphan Diseases Classification.
1 Introduction -- 2 Related Work -- 2.1 Large Language Model for Orphan Diseases -- 2.2 Orphan Disease Identification Using Artificial Intelligence -- 3 Methodology -- 3.1 Data Collection and Preprocessing -- 3.2 Fine-Tuning the Language Model -- 3.3 Hyperparameter Tuning -- 3.4 Deployment and Accessibility -- 4 Performance Analysis -- 4.1 Accuracy -- 4.2 Cohen's Kappa Coefficient -- 4.3 Fine-Tuning Time(s) -- 5 Result and Discussion -- 6 Conclusions and Future Work -- References -- Computational Intelligence -- A Novel Dynamic Programming Method for Non-parametric Data Discretization -- 1 Introduction -- 2 Proposed Approach -- 2.1 Problem Formulation -- 2.2 Partial Correlation over Intervals -- 2.3 Proposed Dynamic Programming Algorithm -- 3 Experimental Settings -- 3.1 Benchmark Datasets -- 3.2 Evaluation Plan -- 4 Results and Discussion -- 4.1 RQ1: How Effective is Our Proposed Approach Compared to State-of-the-Art Baselines on Data Discretization? -- 4.2 RQ2: How Does the Degree of Variability of Continuous Variables Impact the Performance of Our Proposed Approach? -- 5 Conclusion -- References -- Framework to Merge Possibilistic Belief Bases -- 1 Introduction -- 2 Related Works -- 2.1 Bargaining Game with Integrity Constraint -- 2.2 Belief Merging by Social Contraction Function -- 3 Framework for Merging Possibilistic Belief Bases -- 3.1 Axiomatic Model -- 3.2 Constructive Model -- 3.3 Logical Properties -- 4 Conclusions and Discussion -- References -- Game-Theory Based Voting Schemas for Ensemble of Classifiers -- 1 Introduction -- 2 Classification and Ensemble Methods -- 3 Game Theory -- 4 Proposed Approach -- 5 Numerical Experiments -- 6 Conclusions -- References -- RECALL: Towards Generalized Representations in Unsupervised Federated Learning Under Non-IID Conditions -- 1 Introduction -- 2 Related Works -- 2.1 Federated Learning Algorithm.
2.2 Non-IID Solutions -- 3 Non-IID Solution for Unsupervised Federated Learning -- 3.1 Problem Definition -- 3.2 Analysis of Supervised and Unsupervised Learning -- 3.3 Intuition -- 3.4 Method -- 4 Experimental Result -- 4.1 Experimental Setting -- 4.2 Non-IID Issue Under Unsupervised Learning Task -- 4.3 The Effectiveness of Proposed RECALL -- 5 Conclusion -- References -- Predicting Epidemic Outbreak Using Climatic Factors -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Models -- 3.2 Geospatial Analysis Using ArcGIS (Analytic Hierarchy Process Model) -- 3.3 Datasets -- 3.4 Evaluation Metrics -- 4 Results and Analysis -- 5 Conclusion and Future Directions -- References -- A Novel Approach Utilizing Local Criteria Weights for Multi-criteria Evaluation Within the SPOTIS Method -- 1 Introduction -- 2 Preliminaries -- 2.1 Identification of the Local Weights -- 2.2 Stable Preference Ordering Towards Ideal Solution -- 3 Proposed Approach -- 4 Study Case -- 5 Conclusions -- References -- Masked Face-Landmark Prediction with Mask-Coefficient -- 1 Introduction -- 2 Related Work -- 3 Face-Landmark Prediction -- 3.1 Overall Architecture -- 3.2 Image-Augmentation Module -- 3.3 Mask-Coefficient-Calculation Module -- 3.4 Loss Function with M -- 4 Experiment -- 4.1 Experimental Data -- 4.2 Experimental Measures -- 4.3 Experimental Results -- 4.4 Illustrative Resulting Examples -- 5 Conclusion -- References -- Federated Erasable-Itemset Mining with Quasi-Erasable Itemsets -- 1 Introduction -- 2 Review of Related Works -- 2.1 Erasable-Itemsets Mining -- 2.2 Prelarge Itemsets Mining -- 2.3 Federated Learning -- 3 Federated Erasable-Itemset Mining -- 3.1 Problem Analysis -- 3.2 Problem Description -- 3.3 Definitions -- 3.4 Algorithm Framework -- 4 Experimental Results -- 5 Conclusion and Future Work -- References.
An Optimization Approach for Finding Diverse Trading Strategy Portfolio Using the Memetic Algorithm.
Record Nr. UNINA-9910874691003321
Nguyen Ngoc Thanh  
Singapore : , : Springer, , 2024
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