Proceedings of the Seventh International Scientific Conference Intelligent Information Technologies for Industry (IITI'23) : Volume 1

• Record Nr.: UNINA9910746282603321
• Autore: Kovalev Sergey
• Pubbl/distr/stampa: Cham : , : Springer, , 2023; ©2023
• ISBN: 9783031437892; 3031437896
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (444 pages)
• Collana: Lecture Notes in Networks and Systems Series ; ; v.776
• Altri autori (Persone): KotenkoIgor; SukhanovAndrey
• Soggetti: Artificial intelligence; Automation
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Invited Papers -- Intelligent Interfaces and Systems for Human-Computer Interaction -- 1 Introduction -- 2 Intelligent Synthesis -- 2.1 Video Modality -- 2.2 Audio Modality -- 2.3 Text Modality -- 2.4 Multimodality -- 3 Intelligent Analysis -- 3.1 Video Modality -- 3.2 Audio Modality -- 3.3 Text Modality -- 3.4 Multimodality -- 4 Conclusions -- References -- Three Knowledge Sources and Three Constituents of Artificial Intelligence Foundation -- 1 Introduction -- 2 Data vs. Knowledge -- 3 Data Science -- 4 From Knowledge Engineering to Knowledge Science: A Perspective -- 5 Digital Twin As a Source of Various Knowledge -- 6 Discussion: Integration and Interaction of Knowledge from Different Types of Sources -- 7 Conclusion -- References -- Machine Learning and Its Applications -- Comparative Analysis of Data Synthesis Methods for Prognostic Models Development in Cardiology -- 1 Introduction -- 2 Related works -- 3 Methods and materials -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Artificial Intelligence Approach to Palladium Nanocatalysts Diagnostics Automation -- 1 Introduction -- 2 Model-Based Training DRL Agents -- 3 Optimal Control Algorithms and Spectral Profile Analysis -- 4 Conclusion -- ; References -- Methodology for Detecting and Feature Selection of an Information Attack in the Process of Mediatization -- 1 Introduction -- 2 Related Work -- 3 Methodology for Detection and Feature Selection -- 3.1 Information Attack Model -- 3.2 Approach to Detection and Feature Selection -- 4 Case Study -- 5 Conclusion -- References -- Planning Maneuvers for Autonomous Driving Based on Offline Reinforcement Learning: Comparative Study -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Offline RL -- 3.2 Conservative Q-learning -- 4 Approach -- 4.1 CommonRoad Scenarios.; 4.2 Trajectories Generation -- 5 Experiments -- 6 Conclusion -- References -- Big Five: What User Posts Say? -- 1 Introduction -- 1.1 Prerequisites for Research -- 1.2 Big Five -- 1.3 Related Work -- 2 Problem Statement -- 3 Methods -- 3.1 Description Dataset -- 3.2 Data Preprocessing -- 3.3 Used Models -- 3.4 Methodology for Evaluating the Results of Experiments -- 3.5 Results -- 4 Discussion -- 5 Conclusion -- References -- Gated Recurrent Unit Autoencoder for Fault Detection in Penicillin Fermentation Process -- 1 Introduction -- 2 Literature Review -- 3 Domain Adaptation -- 4 Deep Learning Models -- 4.1 Gated Recurrent Unit -- 4.2 GRU Based Autoencoder -- 4.3 GRU-AE Based Fault Detection -- 5 Experiments and Results -- 5.1 Dataset -- 5.2 Data Preprocessing -- 5.3 Model Training -- 5.4 Results -- 6 Conclusion -- References -- Resume Recommendation using RNN Classification and Cosine Similarity -- 1 Introduction -- 2 Related Works -- 2.1 Resume Classifier Related Works -- 2.2 Resume Recommender Related Works -- 3 The Proposed Two-Fold Algorithm Approach -- 3.1 Resume Classification -- 3.2 Experimental Results and Evaluation -- 4 Resume Recommendation -- 4.1 Similarity Function -- 4.2 Computing Similarity Function -- 5 Discussion and Conclusion -- References -- Machine Learning for Adaptive Analysis and Evaluation of Soil Slopes -- 1 Introduction -- 2 Background -- 3 Method -- 3.1 The Model of Cluster Analysis -- 3.2 BCubed Clustering Quality Metric -- 3.3 Agglomerative Clustering Algorithm -- 4 Results -- 4.1 Pre-processing of the Data Frame -- 4.2 Field Segmentation -- 4.3 Formation of ``Winners'' and ``Losers'' -- 4.4 Clustering -- 4.5 Angle Calculation -- 4.6 Quality Assessment -- 5 Proposed Decision -- 6 Conclusion and Future Work -- References.; Research on Video Pedestrian Tracking Based on the Combination of Optical Flow Method and Target Tracking Network -- 1 Introduction -- 1.1 Tracking Model Based on Traditional Methods -- 1.2 Tracking Model Based on Deep Learning Methods -- 2 Related Work -- 2.1 Siamese-Based Tracking Model -- 2.2 Self-attention -- 2.3 Variational Optical Flow Method -- 3 Transformer-Based Target Tracking Model -- 3.1 Overall Framework of SiamSA Tracking Model -- 3.2 Variational Optical Flow Model Based on Deep Learning Priors -- 3.3 Optical Flow Vector Correction Search Area -- 4 Experiments -- 4.1 Effect of Self-attention -- 4.2 Improved Optical Flow Model -- 4.3 Effect of Search Area Update Model -- 5 Conclusion -- References -- Development and Testing Intelligent Video Surveillance Systems Based on the CNN Algorithm -- 1 Introduction -- 2 Analog Overview -- 2.1 Solutions Based on OpenCV Methods -- 2.2 Convolutional Neural Network Models -- 2.3 Determining the Accuracy of Forecast Data -- 3 Suggested Solutions -- 3.1 Object Detection Based on OpenCV and Convolution Neural Network -- 3.2 Tracking and Dynamic Identity Stack Creation Algorithm -- 4 Computer Simulation Scenarios as Datasets -- 5 Experimental Results -- 5.1 Testing the Object Detection Algorithm -- 5.2 Testing the Tracking Algorithm -- 6 Conclusion -- References -- Impact of Loss Functions on the Training of LiDAR-based Place Recognition Models -- 1 Introduction -- 2 ; Related Work -- 2.1 LiDAR-based Place Recognition Methods -- 2.2 Loss Functions in Place Recognition -- 3 Methodology -- 3.1 Loss Function -- 3.2 Methods -- 3.3 Training Details -- 4 Experiments -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Neural Attention Forests: Transformer-Based Forest Improvement -- 1 Introduction -- 2 Preliminaries.; 2.1 Nadaraya-Watson Regression and Attention -- 2.2 Attention-based Random Forest -- 3 The Neural Attention Forest Architecture -- 4 The Neural Attention Forest as a Transformer -- 5 Numerical Experiments -- 6 Concluding Remarks -- References -- Audio-Visual Multi-modal Meeting Recording System -- 1 Introduction -- 1.1 Background -- 1.2 Main Contribution -- 1.3 Paper Structure -- 2 Training Strategy -- 2.1 Contrast Learning -- 2.2 Domain Generalization -- 3 Dataset -- 3.1 Dataset of AVSR -- 3.2 Dataset of SPR -- 4 Models -- 4.1 AVSR Model -- 4.2 SPR Model -- 5 Experiment -- 5.1 AVSR Model Training -- 5.2 SPR Model Training -- 5.3 Test -- 6 System Deployment -- 6.1 User Interface -- 6.2 Function Realization -- 7 Conclusion -- References -- Evolutional Modeling -- Studying the Efficiency of Parameter Scaling in Optimal Control Problems with Parallel Memetic Algorithm -- 1 Introduction -- 2 Problem Formulation -- 3 Gasoline's Catalytic Reforming Reaction -- 4 Memetic Parallel Mind Evolutionary Computation Algorithm -- 5 Computational Experiments -- 5.1 Study of the Parameter Scaling Efficiency -- 5.2 Analysis from the Chemical Perspective -- 5.3 Analysis from the Optimization Perspective -- 6 Conclusions -- References -- Canonical Representation of Transport Networks and Their Identification Based on Evolutionary Modeling -- 1 Introduction -- 2 Operations on Basic Structures of Transport Networks -- 2.1 Serial Connection -- 2.2 Adding a Feedback Loop -- 2.3 Parallel Connection -- 3 Model Parameter Identification Method -- 4 Learning Theory Methods in Transport Network Identification -- 5 Conclusion -- References -- Modified Adaptive Particle Swarm Algorithm -- 1 Introduction -- 2 Approach to the Representation of Solutions in an Algorithm based on Swarm Intelligence -- 3 Modified Algorithm for the Adaptive Behavior of a Bee Colony.; 4 Hybridization of the Structure of Swarm Intelligence -- 5 Experimental Studies -- 6 Conclusion -- References -- Development and Research of Algorithms for the Synthesis of Combinational Logic Circuits Based on the Evolutionary Approach -- 1 Introduction -- 2 Problem Statement -- 3 Evolutionary Algorithm for Synthesizing Combinational Circuits -- 4 Results of Computational Experiments -- 5 Conclusions -- References -- Fuzzy Models -- Co-active of Fuzzy Temporal Ontological Models and Fuzzy Temporal Cognitive Models for the Analysis and Forecasting of Complicated Systems -- 1 Introduction -- 2 Fuzzy Temporal Ontological Model -- 3 Fuzzy Relational Temporal Cognitive Model -- 4 Forecast Assessment of the Condition and Risks of the IEMS Malfunction -- 5 Conclusion -- References -- Synthesis of Intelligent Tracking Filter with Fuzzy for Parameter Setting in Problems of Air Traffic Management Automation -- 1 Introduction -- 2 Formulation of the Problem -- 3 Construction of the Equation of the Target Motion Based on the Condition for the Maximum of the Generalized Power Function for a Discrete Time Setting -- 4 The Synthesis of the Intelligent Tracking Filter -- 5 Mathematical Simulation -- 6 Conclusion -- References -- Intelligent Decision-Making -- Making Diagnostic Decisions Based on the Assessment of Mixed Production Rules -- 1 Introduction -- 2 Development of Mixed Production Rules -- 3 Application of a Complex Approach to MPR for Diagnosing the Asynchronous Electric Motor -- 4 Conclusion -- References -- ; Ontology-Based Methodology for Knowledge Maps Design -- 1 Introduction -- 2 Knowledge Maps: Short Overview -- 3 Ontologies as a Conceptual Skeleton of a Knowledge Domain -- 4 Four Meta-steps to Create a Knowledge Map -- 5 Conclusion -- References -- Operating with Fuzzy Cases in Distributed Intelligent Systems -- 1 Introduction.; 2 Searching for a Decision Based on Cases.
• Sommario/riassunto: This volume is part of the Lecture Notes in Networks and Systems series and presents the proceedings of the Seventh International Scientific Conference on Intelligent Information Technologies for Industry (IITI'23). Held in September 2023 in Saint Petersburg, Russia, the conference gathered international experts to discuss advancements in intelligent information technologies and their applications in various industries. The collection features research on automation, artificial intelligence, and the integration of these technologies in industrial contexts. Renowned speakers presented on topics such as machine learning, data science, intelligent interfaces, and edge computing. The conference aims to foster collaboration and innovation by connecting researchers and practitioners from around the globe, contributing to the development and understanding of intelligent systems in industrial settings.