Recent Advances in Intelligent Engineering: Volume Dedicated to Imre J. Rudas’ Seventy-Fifth Birthday (Topics in Intelligent Engineering and Informatics, 18)

The book publishes new developments and advances in the various areas of computational intelligence―quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics, and life science, as well as the methodologies behind them. The book contains monographs, lecture notes, and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution―this permits a rapid and broad disseminational of research results. Soft computing, as a collection of techniques exploiting approximation and tolerance for imprecision and uncertainty in traditionally intractable problems, has become very effective and popular especially because of the synergy derived from its components. The integration of constituent technologies provides complementary methods that allow developing flexible computing tools and solving complex problems. A wide area of natural applications of soft computing techniques consists of the control of dynamic systems, including robots. Loosely speaking, control can be understood as driving a process to attain a desired goal. Intelligent control can be seen as an extension of this concept, to include autonomous human-like interactions of a machine with the environment. Intelligent robots can be characterized by the ability to operate in an uncertain, changing environment with the help of appropriate sensing. They have the power to autonomously plan and execute motion sequences to achieve a goal specified by a human user without detailed instructions. In this book leading specialists address various theoretical and practical aspects in soft computing, intelligent robotics, and control. The problems discussed are taken from fuzzy systems, neural networks, interactive evolutionary computing, intelligent mobile robotics, and intelligent control of linear and nonlinear dynamic systems. Preface Contents STAM-SNN: Spatio-Temporal Associative Memory in Brain-Inspired Spiking Neural Networks: Concepts and Perspectives 1 Introduction 2 Spatio-Temporal Associative Memory (STAM) Based on NeuCube 3 Experimental Case Studies 4 Discussions and Conclusions References Fast Multi-scale Batch-Learning Growing Neural Gas 1 Introduction 2 Related Works 3 Fast Learning for Multi-scale Batch-Learning Growing Neural Gas 3.1 Multi-scale Batch-Learning Procedure 3.2 Growing Procedure 4 Computational Experiments 4.1 Experimental Conditions 4.2 Experimental Results 5 Discussions 6 Conclusions References Conversion Between Denavit-Hartenberg and Hayati Conventions for Calibration and Forward Kinematics of Manipulators 1 Introduction 2 Basic Concepts 2.1 Conventional Denavit-Hartenberg (DH) Parameters 2.2 Hayati Parameters 3 Main Results 3.1 DHSubscript ii-DHSubscript i plus 1i+1 to HayatiSubscript ii-DHSubscript i plus 1i+1 Conversion 3.2 HayatiSubscript ii-DHSubscript i plus 1i+1 to DHSubscript ii-DHSubscript i plus 1i+1 Conversion 4 Numerical Results 4.1 Using only DH Modeling and Local Optimization 4.2 Using Mixed DH-Hayati Modeling 4.3 Using Mixed DH-Hayati Modeling with Decreased Measurement Noise Level 5 Conclusion References Stability and Stabilization Conditions for Switching Positive T-S Fuzzy Interval Observes 1 Introduction 2 Positive T-S Fuzzy Observers 3 Switching Metzler-Takagi-Sugeno Interval Observers 4 Enhanced Design Conditions 5 Illustrative Example 6 Concluding Remarks References Surgical Data Science: Emerging Trends and Future Pathways 1 Introduction 2 SDS Directions 2.1 Phase Recognition 2.2 Surgical Image Segmentation 2.3 Surgical Process Modeling, Ontology Development, Workflow Analysis 2.4 Surgical Skill Assessment 2.5 SDS Clinical Success 3 Datasets in Surgical Data Science 4 Annotation Tools in Surgical Data Science 5 Data Acquisition in Surgical Data Science 6 Surgical Procedures within SDS 7 Processing Techniques in SDS 8 Discussion and Future Directions in SDS 9 Conclusion References Which Random-Set Representation of a Fuzzy Set Is the Simplest? 1 Formulation of the Problem 2 Definitions and the Main Results 3 Proof References The Basic Design Space of Out-of-Order Execution in CPU Cores 1 Introduction 2 Design Aspects of Register Renaming Impacting the Layout of Out-of-Order Execution in CPU Cores 2.1 Overview 2.2 Types of Rename Buffers 2.3 Register Mapping Methods 3 Design Aspects of Scheduling Policies Impacting the Layout of Out-of-Order CPU Cores 3.1 Overview 3.2 Implementation Alternatives of Scheduling Buffers 3.3 Implementation Alternatives of Operand Fetching 4 Instruction Reordering 5 The Basic Design Space of Out-of-Order Execution of CPU Cores 6 The Most Advantageous Alternative of Implementing Out-of-Order Execution of CPU Cores 7 Preferred Design Options of Out-of-Order Execution in Earlier and Recent Processors 8 Conclusion References Tensor-Based Approach to Diagnostic Causal Network Modeling 1 Introduction 2 Tensor Approach to Model the Diagnostic Causal Network 3 The Proposed Algorithm 4 Example 5 Conclusions References Modeling of a Microgrid and Its Time-Series Analysis Using the Prophet Model 1 Introduction 1.1 Microgrid System Market, Policy Development, and COVID-19 Impact 1.2 Rise of Clean Microgrid 1.3 Microgrid as Energy Price Managers 1.4 Policies for MG Design in Different Countries 1.5 International Renewable Energy Agency 1.6 Global Microgrid Market Forecast 2 Microgrids’ Role in Net Zero Emission 2.1 Overview of Renewable Power Generation Costs Across the Globe 2.2 Related Works 2.3 Research Focus 2.4 Materials and Methods 3 Methodology for Optimal Configuration Determination 3.1 Software Selection 3.2 Location and Modeling 3.3 Power Outages and Simulation Inputs 3.4 Overall Best Configurations in the HOMER Grid 3.5 Economic Impact 4 Conclusion References Muscle Atrophy Monitoring Using Machine Learning and Surface Electromyography 1 Introduction 2 Literature Review 2.1 sEMG Signal-Based Gesture Recognition Using Deep Learning 2.2 Deep Learning for Human Activity Recognition 2.3 Data Fusion Approaches 2.4 Deep Learning for Atrophy-Based Concerns 2.5 Monitoring via Contemporary Gesture Classifier 3 Research Proposal 3.1 Training Strategy and Data Collection 3.2 Data Pre-processing and Feature Extraction 3.3 Classification and Training 4 Experimental Setup and Results 4.1 Experimental Setup 4.2 Experimental Implementation and Initial Results 5 Conclusion and Further Work 5.1 Increase Numeric Sensor Count 5.2 Transfer Learning Applicability 5.3 Data Fusion with Accelerometer Sensing 5.4 Closing Remarks References Frequency-Dependent Feedback in Fixed Point Iteration-Based Adaptive Control 1 Introduction 2 Definition of the Concept of ``Dynamics-Dependence'' in the Time Domain 3 Simulations for a 3 DoF Rotary Robot Arm Model 3.1 Extremely Low Velocity of Motion 3.2 Low Velocity of Motion 3.3 High Velocity of Motion 4 Conclusions References BlackAnt—High Available Micro-Service Based Cloud Platform with Dynamical Scaling 1 Introduction 2 Related Work 2.1 Container 2.2 Docker Swarm 2.3 Docker Compose 2.4 Scalability 2.5 High Availability (HA) 3 BlackAnt Overview 3.1 BlackAnt Deployment Architecture 3.2 Authentication and Role Handling 3.3 Task Creation 3.4 Service Implementation 3.5 Scheduler State Machine 3.6 Monitoring 3.7 Dynamic Scaling 3.8 Infrastructure 4 Effectiveness of BlackAnt 4.1 Ansible Deployment 4.2 Development Speed 4.3 Integration Support 5 Further Possible research and Development Directions 5.1 More Language Support 5.2 Kubernetes Migration 5.3 Workflow Support 5.4 Getting Involved in Education 6 Conclusion References Cyber-Medical Systems in Chemotherapy Treatment Optimization 1 Introduction 2 Modeling 2.1 In Vivo Tumor Model 2.2 In Vitro Tumor Model 3 Parametric Identification 3.1 Parametric Identification with Mixed-Effects Models 3.2 Tumor Dynamics Clustering 3.3 Noise Model for Calipter Measurements in Animal Experiments 4 Therapy Optimization 4.1 Therapy Optimization Based on Pharmacodynamics and Pharmacokinetics 4.2 Fuzzy System Estimation and Model Predictive Control 4.3 Population-Based Optimization Using Genetic Algorithm 5 Conclusion References Obtaining Visual and Audio Information Based on Artificial Intelligence 1 Introduction 2 Creating an Artificial Virtual Environment 3 Software Development 4 Dynamic Analysis of the 3-Dimensional Model 5 The Method of Classification of Information Objects 6 Conclusions References Spectrum Analyzer with FPAA 1 Introduction 2 FPAA and Microcontroller as an Embedded Hybrid Cell 3 Results, Further Work References The Importance of Resilience in Engineering Education 1 Introduction 2 Literature Review 3 Participants, Methods, and Instruments 4 Results 4.1 Findings from the Evaluation of the Resilience Test 4.2 Study-Related Correlations Between Resilience and Internet Use 4.3 Gender and Generational Correlations Between Resilience and Internet Use 4.4 Correlations Between Residence and Parental Education Between Resilience and Internet Use 5 Discussion and Conclusion References Application of the Inventory Method to Estimate the Inertia of the Hungarian Power System 1 The Inertia 2 The Correct Inertia Response 3 Various Methods for Calculating and Estimating System Inertia 4 Estimation of Inertia Capacity of the Domestic System 5 Conclusion References