دانلود کتاب Intelligent Computing: Proceedings of the 2022 Computing Conference, Volume 2

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Editor’s Preface
Contents
An Adaptive Geometry and Dual Graph Approach to Sign Prediction for Weighted and Signed Networks
1 Introduction
2 Dual Graphs
3 Neighborhoods of Nodes in Dual Graphs
4 Predictive Models for Sign Prediction
4.1 Embedded SVM Method
5 Experimental Results for Real Datasets
References
A Stochastic Modified Limited Memory BFGS for Training Deep Neural Networks
1 Introduction
2 An Overview on the L-BFGS Update
2.1 The BFGS Update
2.2 The L-BFGS Update and Its Compact Form
2.3 The Initialization of the L-BFGS Update
3 A Modified L-BFGS Update
3.1 Sign Correction
3.2 A New Modified Secant Condition
4 The Modified L-BFGS Trust Region Method
5 Stochastic M-LBFGS-TR
6 Experiments
7 Conclusions
References
Enhanced Deep Learning Framework for Fine-Grained Segmentation of Fashion and Apparel
1 Introduction
2 Related Work
3 Method
3.1 Network Structure
3.2 Feature Extraction Module: Inception V3 and Mask RCNN
4 Experiments
4.1 Datasets
5 Conclusions
References
Towards Tackling QSAT Problems with Deep Learning and Monte Carlo Tree Search
1 Introduction
2 Related Work
3 Preliminaries
3.1 Neural Monte Carlo Tree Search
3.2 QSAT Problems and QSAT Games
3.3 Gated Graph Neural Networks
4 Implementation
4.1 QBF Graphs
4.2 Architecture
5 Experiment
5.1 Experiment Setup
5.2 Performance Measurement
5.3 General Result
5.4 Two Examples
6 Discussion
6.1 Exploration vs. Exploitation
6.2 State Space Coverage
6.3 Limitation
7 Conclusion
References
Laplacian Pyramid-like Autoencoder
1 Introduction
2 Related Works
2.1 Autoencoder
2.2 Network Acceleration
2.3 Single Image Super-Resolution
3 Laplacian Pyramid in Neural Network
3.1 Idea and Structure of LP
3.2 Strengths of LP and Applications on Neural Net
4 Laplacian Pyramid-Like Autoencoder
4.1 Proposed Model
4.2 Loss for LPAE
4.3 Image Classification Problem
4.4 Applications to Super-Resolution Problem
4.5 Details on Experiments
5 Experimental Results
5.1 Autoencoder
5.2 Classification
5.3 Super-Resolution
6 Conclusion and Future Works
References
Autonomous Vision-Based UAV Landing with Collision Avoidance Using Deep Learning
1 Introduction
2 Proposed Method
2.1 Estimation of Position
2.2 YoloV4 Dataset Cloud Training
2.3 Collision Avoidance
3 Experiment
4 Conclusion
5 Future Study
References
The Current State of the Art in Deep Learning for Image Classification: A Review
1 Introduction
2 Transformer-Based Networks
3 Transformer/Convolution Hybrid Networks
4 EfficientNet Networks
5 Using Neither Transformers nor Convolutions
6 Teacher-Student Networks
7 Innovations Related to Training Procedures
8 Conclusion
References
Deep Convolutional Neural Networks for COVID-19 Detection from Chest X-Ray Images Using ResNetV2
1 Introduction
2 Related Work
3 Dataset
4 Architecture and Methods
4.1 Proposed Model
5 Results
6 Discussion
7 Conclusion
References
Deep Neural Networks for Remote Sensing Image Classification
1 Introduction
2 ReCaS-Bari Cloud Infrastructure: The HPC Cluster
3 Method
4 Land Cover Classification Results Using Deep Neural Networks
5 Conclusions
References
Linear Block and Convolutional MDS Codes to Required Rate, Distance and Type
1 Introduction
1.1 Motivation, Summary
1.2 Background, Notation
1.3 Abbreviations
2 Summary of Design Methods
2.1 Linear Block MDS
2.2 Convolutional MDS
2.3 Characteristic 2 and Prime Fields
2.4 Examples
3 Constructions
4 Specify the Codes
4.1 Matrices to Work and Control
5 Algorithms
5.1 QECC Hermitian
5.2 Higher Memory
5.3 DC LCD Convolutional
5.4 Addendum
References
A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications
1 Introduction
2 Unsupervised Machine Learning and Deep Learning
2.1 Restricted Boltzmann Machines
2.2 Autoencoders
2.3 Recurrent Neural Networks
2.4 Deep Learning
3 Unsupervised Machine Learning Frameworks for Anomaly Detection
3.1 Unsupervised Machine Learning for Anomaly Detection in Electrical Substation Circuits
3.2 Unsupervised Machine Learning System for the Detection of Cyber Based Attacks in Smart Grids
3.3 Unsupervised Machine Learning for Anomaly Detection in Network Centric Architecture Based on IoT
3.4 Unsupervised Anomaly for the Detection and Diagnosis in Multivariate Time Series Data
3.5 Unsupervised Machine Learning for Anomaly Detection in Unmanned Aerial Vehicles
3.6 Unsupervised Machine Learning Algorithm for Anomaly Detection in Real-Time Video Surveillance
3.7 Unsupervised Machine Learning Approach for Anomaly Detection in Hyperspectral Imaging
4 Future Directions
5 Conclusions
References
Causal Probabilistic Based Variational Autoencoders Capable of Handling Noisy Inputs Using Fuzzy Logic Rules
1 Introduction
2 Related Works
3 Fuzzy Cevae
3.1 Fuzzy Causal Effect Variational Autoencoder (FCEVAE-V1) First Architecture
3.2 Fuzzy Causal Effect Variational Autoencoder (FCEVAE-V2) Second Architecture
3.3 Second Architecture’s Experiments
4 Conclusion
References
Multi-Object On-Line Tracking as an Ill-Posed Problem: Ensemble Deep Learning at the Edge for Spatial Re-identification
1 Research Innovation and Objective(s)
2 Introduction
3 Method
3.1 Ensemble Training
3.2 RE-ID Occlusion Use Case
4 Results and Discussion
4.1 Transfer Learning
4.2 Baseline Tracker
4.3 Ensemble Re-identification
References
An Ensemble-Based Machine Learning for Predicting Fraud of Credit Card Transactions
1 Introduction
1.1 Credit Card Fraud
1.2 Ensemble Learning
2 Literature Review
3 Proposed Method
3.1 CCFD System
3.2 Datasets and Features Extractions
3.3 Machine Learning and Ensemble Techniques
4 Results Assessment and Performance Evaluation
5 Conclusion
6 Future Work
References
Unsupervised Machine Learning Methods for City Vitality Index
1 Introduction
2 The Proposed Method for the Vitality Index
2.1 Selected Features
2.2 Framework Design to Predict Vitality Index
2.3 Unsupervised Learning – k-Means Clustering
2.4 Genetic Algorithms
2.5 Feature-Weighted Inputs
2.6 Linear Regression to Predict VI
3 Results Applied on the First Belt Districts in Trois-Rivières City
3.1 Features Distribution and Representation
3.2 Vitality Index
3.3 Clustering
3.4 Weighting the Features
3.5 Predicting Vitality Indexes
4 Discussions
5 Conclusion
References
Machine Learning of a Pair of Charged Electrically Particles Inside a Closed Volume: Electrical Oscillations as Memory and Learning of System
1 Introduction
2 The Physics Model
2.1 The Electric Field
2.2 The Usage of Divergence Theorem
3 The Machine Learning Implementation
3.1 Task
3.2 Performance
3.3 Experience
3.4 Electrical Oscillations
4 Conclusion
References
Marlo’s Networks of Expectations
1 Presence and Absence of Resources and Threats as the Basis for Decisions
2 Combinatorics as the Basis of Tree Diagrams: Representation of Simple and Complex Propositions
3 Solved Exercises in a Simple Version of the Network
4 The Alpha System
5 Linguistic Ensembles of Cognitive Cells
6 Principles of the Propagation of Truth and Falsehood
7 Some Exercises Solved Using the Expectations Network
8 Limits of the Work and Conclusions
References
Complete Blood Analysis: An Android OCR-Based Interpretation
1 Introduction
2 Related Works
2.1 Blood Test Guide
2.2 Smart Blood Pressure (SmartBP) BP Tracker
2.3 iCare Health Monitor
2.4 Medical Lab Tests
2.5 Lab Tests Online Website
3 Methodology
3.1 Agile Model
3.2 Conceptual System Components
4 Experimental Evaluation
4.1 Techniques Used to Collect Requirements
4.2 Interviews
4.3 Survey
4.4 Experimental Results
5 Conclusion
References
Refined Optimal Control Problem and Its Solution Using Symbolic Regression
1 Introduction
2 A Refined Optimal Control Problem
2.1 Classical Formulation of the Optimal Control Problem
2.2 Refined Formulation of the Optimal Control Problem
3 A Synthesized Optimal Control
3.1 Maximum Principle for Synthesized Control
4 The Optimal Control Problem with Bottleneck Phase Constraints
5 An Example
6 Conclusions
References
Influences of Coating and Spandex Compositions of Conductive Textiles Used as Strain Sensors Using an Automated Test System
1 Introduction
2 Related Work
2.1 Smart Textiles
2.2 Textile Testsystems
2.3 Applications
3 Automated Testing System
3.1 Test System
3.2 Test Scenarios
4 Test Samples
4.1 Patches
4.2 EeonTex
4.3 Ideal Behavior
5 Test Results
5.1 Patches
5.2 EeonTex
5.3 Comparison
6 Conclusion
References
Problem Structuring Combined with Sentiment Analysis to Product-Service System Performance Management
1 Introduction
1.1 Text Analytics and Sentiment Analysis
1.2 Aspect-Based Sentiment Analysis (ABSA)
1.3 Problem Structuring Method (PSM)
1.4 Soft System Methodology (SSM)
2 Research Methodology
2.1 SLR on Performance of PSS in CE
2.2 SLR on Text Analytics Uses Focused on Improving Decision Making and Performance Management
2.3 Research Gap Identified and Addressed by this Article Proposition
3 A Framework to Integrate ABSA and SSM to Support Identification of Improvement Opportunities
4 Discussion
References
Texture Transfer Attention for Realistic Image Completion
1 Introduction
2 Related Work
3 Approach
3.1 The Overall Pipeline
3.2 Texture Transfer Attention
3.3 Similarity Weight Texture Synthesis
3.4 Training Objective
4 Experiment Results
4.1 Quantitative Results
4.2 Qualitative Results
5 Conclusion
References
Examining Correlation Between Trust and Transparency with Explainable Artificial Intelligence
1 Introduction
2 Experimental Design
2.1 Similarities Between Surveys
2.2 Differences Between Surveys
2.3 Distribution of Survey
3 Evaluation of Survey Results
3.1 Splitting the Data
3.2 Comparing the Data
4 Results
4.1 Model Influence Metric Results
4.2 Trust Evaluation Results
4.3 Discussion and Conclusion
References
Utilizing AI in Test Automation to Perform Functional Testing on Web Application
1 Introduction
2 Related Work
3 Methodology
3.1 Data Generation and Collection
3.2 Data Evaluation Using Fuzzy Inference System
3.3 Alternative Data Evaluation Layer
3.4 Implementation
4 Result
4.1 Compare the Different Approaches for Data Generation
4.2 Self-hEALING TEST Automation
4.3 Data Collection by Extracting Search Endpoint
4.4 Data Evaluation
4.5 Detecting Failure’s Layer
4.6 Challenges and Limitation
5 Conclusions
References
On the Modelling of Species Distribution: Logistic Regression Versus Density Probability Function
1 Introduction
2 Background and Related Work
2.1 SDSim
3 Methods
3.1 First Case Study: Strawberry Tree
3.2 Second Case Study - Apis Mellifera Honeybee
4 Discussion
5 Conclusion
References
Artificial Intelligence Tools for Actuator Fault Diagnosis of an Unmanned Underwater Vehicle
1 Introduction
2 Process Model and Control Scheme
3 Perturb and Observe Algorithm
4 Conclusion
References
Applying the Delphi Method to Measure Enterprise Content Management Workflow System Performance
1 Introduction
2 Background
2.1 The Delphi Method and Business Process Management
2.2 The Delphi Method and CERT Values
2.3 CERT Values and Enterprise Content Management System Performance
2.4 The Delphi Method and Workflow Information Systems
3 The Delphi Method
3.1 The Delphi Method as a Research Study Framework
3.2 The Delphi Method Reliability
3.3 The Delphi Method Validity
4 Delphi Results
4.1 The Relationship between the Delphi Method and CERT Values
4.2 Delphi Results
4.3 Finding Key Performance Indicators
5 Conclusion
References
A Fuzzy Epigenetic Model for Representing Degradation in Engineered Systems
1 Introduction
2 Background
2.1 Epigenetics and Methylation
2.2 Foundational Formal Model
3 Disease Process Model
3.1 Failure Modes
3.2 Methylation as a Failure Model
3.3 Model Postulates for Methylation
4 Fuzzy Model
4.1 Fuzzy Representations of Impact and Methylation
4.2 Example of the Fuzzy Set Model
5 Conclusion and Future Work
References
A Voting Ensemble Technique for Gas Classification
1 Introduction
2 Experimental Setup
2.1 Data Collection
2.2 Classification Algorithm
2.3 Ensemble Learning
3 Results and Discussion
4 Conclusion
References
Neural Networks with Superexpressive Activations and Integer Weights
1 Introduction
2 An Effective Kronecker\'s Theorem
3 Network Selection and Approximation
4 Application to Nonparametric Regression
5 Conclusion
References
Mask Compliance Detection on Facial Images
1 Introduction
2 Related Work
3 Data
3.1 Description
3.2 MaskedFace-Net
3.3 Preprocessing
4 Model Experimentation
4.1 Training and Validation
4.2 Model A
4.3 Model B
4.4 Model C
5 Application
6 Results
6.1 Real-Time Classifier
7 Discussion
8 Conclusion and Further Work
References
Urban Tree Detection and Species Classification Using Aerial Imagery
1 Introduction
2 Dataset Generator Framework
3 Tree Species Classification
3.1 VGG19 Model
3.2 ResNet50 Model
3.3 DenseNet121 Model
3.4 InceptionV3 Model
4 Results and Discussion
5 Conclusion
References
Rectifying Homographies for Stereo Vision: Analytical Solution for Minimal Distortion
1 Introduction
1.1 Background
1.2 Previous Work
2 Setting the Problem
2.1 Pinhole Cameras and Epipolar Geometry
2.2 Rectification
2.3 Perspective Distortion
2.4 Distortion Metric
3 Geometric Interpretation and Analytical Derivation of the Minimum
3.1 Geometric Interpretation
3.2 Analytic Derivation of the Minimising Rectification
4 Algorithm Summary
5 Discussion
5.1 Rectification Examples
6 Conclusions
References
Statistical Analysis of Electroencephalographic Signals in the Stimulation of Energy Data Visualizations
1 Introduction
2 Related Work
3 Proposed System
4 Data Analysis
5 Discussion
6 Conclusion
References
GCANet: A Cross-Modal Pedestrian Detection Method Based on Gaussian Cross Attention Network
1 Introduction
2 Related Work
2.1 Multispectral Pedestrian Detection
2.2 Fusion with Attention
3 Method
3.1 Overview of GCANet
3.2 Backbone
3.3 Gaussian Transformer Encoder
3.4 Detection Head
3.5 Loss Function
4 Experiments
4.1 Dataset and Evaluation Metrics
4.2 Implementation Details
4.3 Comparisons with State-of-the-Art
4.4 Ablation Study
5 Conclusion
References
Automatic Classification of Felsic, Mafic, and Ultramafic Rocks in Satellite Images from Palmira and La Victoria, Colombia
1 Introduction
2 Theoretical Foundation
3 Related Work
4 Methodology
4.1 Acquiring Raw and Infrared Satellite Images
4.2 Preparing and Processing the Data
5 Results
6 Discussion
7 Conclusions and Future Work
References
SHAQ: Single Headed Attention with Quasi-recurrence
1 Introduction
1.1 Background and Motivation
1.2 ENWIK8 Dataset
2 Architecture Overview
2.1 SHA-RNN
3 Approach
4 Experiment and Results
4.1 Boom
4.2 Alternate-Attention Head Experiments
4.3 Layer-Attention Analysis
4.4 QRNN
5 SHAQ
6 Conclusion
References
Dynamic Topic Modeling Reveals Variations in Online Hate Narratives
1 Introduction
2 Data and Machine Learning Methods
3 Results and Discussion
4 Limitations of the Study
5 Conclusion
References
An Improved Bayesian TRIE Based Model for SMS Text Normalization
1 Introduction
2 Background
2.1 Design of the TRIE
2.2 TRIE Probability of a Word
3 The Improved Trie
4 Error Checking Algorithm
4.1 The Bayesian Approach
4.2 Character Bigram
5 Simulations
5.1 Almost Sure Convergence
5.2 Equality of Expectation
5.3 Comparison
5.4 Error Correction
6 Conclusions
References
Dialog Act Segmentation and Classification in Vietnamese
1 Introduction
2 Related Work
3 Proposed Methods
3.1 Dialog Segmentation
3.2 Dialog Act Classification
3.3 Joint Learning Architecture
4 Corpus Construction
4.1 Collecting Raw Dialogues
4.2 Designing Label Sets
4.3 Annotating the Corpus
4.4 Double-Checking and Correcting the Corpus
5 Experiments
5.1 Experimental Setups
5.2 Network Training
5.3 Experimental Results
6 Conclusion
References
ConDef: Automated Context-Aware Lexicography Using Large Online Encyclopedias
1 Introduction
2 Lexicography Dataset Construction
2.1 Data Harvesting
2.2 Data Cleaning and Sampling
2.3 Data Augmentation
3 Training, Tuning, and Validation
4 Results
5 Conclusion
References
On Sensitivity of Deep Learning Based Text Classification Algorithms to Practical Input Perturbations
1 Introduction
2 Related Work
3 Experimental Setup
3.1 Dataset Description
3.2 Models
3.3 Methodology
3.4 Proposed Approach
4 Results
4.1 Addition of Tokens
4.2 Removal of Tokens
4.3 Addition of OOV Tokens
5 Conclusion
References
A Survey of Artificial Intelligence Techniques for User Perceptions’ Extraction from Social Media Data
1 Introductions
2 Background
2.1 Machine Learning (ML)
2.2 Deep Learning (DL)
2.3 Natural Language Processing (NLP)
3 State-of-the-Art Studies of AI Techniques for Analyzing Social Media Data
3.1 Machine Learning (ML)
3.2 Deep Learning (DL)
3.3 Natural Language Processing (NLP)
4 Findings from State-of-the-art Studies
5 Conclusion
References
Social Media Self-expression as Form of Coping During the 2020 Pandemic Lockdown
1 Introduction
2 Literature Review
2.1 Stress and Coping
2.2 Social Media, Coping and Well-Being
3 Theoretical Framework
3.1 Stressor
3.2 Coping Antecedents
3.3 Mediating Process – Appraisal
3.4 Mediating Process – Social Media Coping Expression
3.5 Coping Outcome
4 Methodology
4.1 Data Gathering
4.2 Survey Questionnaire
4.3 Data Analysis
5 Result
5.1 Social Media Self-expression Versus Appraisal and Subjective Well-Being
5.2 Influence of Coping Antecedents on Appraisal, Coping Expression, and Outcome
6 Discussion
7 Limitations
8 Conclusions
References
Building Wikipedia N-grams with Apache Spark
1 Introduction
2 Related Works
3 Apache Spark
3.1 Resilient Distributed Datasets (RDD)
3.2 Apache Spark Architecture
4 Experiment
4.1 Data Set
4.2 Cluster Setup
4.3 Data Processing
4.4 Run Time Evaluation
5 Conclusion
References
Selecting NLP Classification Techniques to Better Understand Causes of Mass Killings
1 Introduction
1.1 Triggers of Mass Killings (ToMK)
2 Related Work
2.1 Overview of Machine Learning Tools: SVMs and Neural Networks
2.2 Use of SVMs and Neural Networks for Classification in Related Case Studies
2.3 Comparison of SVMs and NNs
3 ToMK Classification Framework
3.1 Visualize Corpus, Preprocess Text, Encode Labels, and Extract Features
3.2 Machine Learning Model
3.3 Hyperparameter Tuning
3.4 Production Phase
4 Comparative Analysis
4.1 Accuracy of Machine Learning Models
4.2 Number of Articles Classified as a Coup Event
4.3 Similarity Percentage Between Models
4.4 Resource Restraints
4.5 Interpretability
5 Conclusion
References
Sentiment Analysis on Citizenship Amendment Act of India 2019 Using Twitter Data
1 Introduction
1.1 Motivation
1.2 Research Objectives and Approach
1.3 Methodology
2 Data and Preprocessing
2.1 Dataset and Variables
2.2 Data Preprocessing
3 Sentiment Analysis
3.1 NLTK (Natural Language Toolkit)
3.2 Semantic Lexicons
4 Methods
4.1 Machine Learning Models
4.2 Deep Learning Methods
4.3 Evaluation Parameters
5 Results
5.1 Statistical Analysis
6 Conclusions and Future Work
References
Sentiment Analysis on Depression Detection: A Review
1 Introduction
2 Sentiment Analysis: An Overview
3 Application of Sentiment Analysis
4 Discussion
5 Conclusion
References
Supervised Negative Binomial Classifier for Probabilistic Record Linkage
1 Introduction
1.1 Contributions
2 Probabilistic Record Linkage
2.1 Error Distribution
2.2 Limitations
3 Supervised Negative Binomial Classifier
3.1 Matching of Records
4 Experiments
4.1 Performance on the Test Data
5 Conclusion and Future Work
References
A Recipe for Low-Resource NMT
1 Introduction
2 Data Sources
3 Subword Splitting
4 A Recipe for Low-Resource NMT
5 Multilingual Translation
6 Conclusion
References
Natural Language Processing Using Database Context
1 Introduction
1.1 Problem Definition
1.2 NLP Explanation
1.3 Technical Environment
2 Methodology
2.1 Pre-processing
3 Query Parsing
3.1 Removing of Stop Words
3.2 Edit Distance Algorithm for Incorrect Words
3.3 Grammar Parsing
4 Creating the Table Query
5 Results
5.1 Future Developments
6 Conclusion
References
Enriching Contextualized Representations with Biomedical Ontologies: Extending KnowBert to UMLS
1 Introduction
2 Related Work
3 KnowBert-UMLS
3.1 Pretrained BERT
3.2 Ontology and Candidate Generator
3.3 KAR
3.4 Training
4 Preliminary Experiments
4.1 Masked LM and Next Sentence Prediction
4.2 NER
5 Conclusions
References
One Step Beyond: Keyword Extraction in German Utilising Surprisal from Topic Contexts
1 Introduction
2 Related Work
3 Methods
3.1 Text Corpus
3.2 TextRank
3.3 Topic Context Model
3.4 Recurrent Neural Network
4 Results
5 Conclusion and Outlook
References
Language Use and Susceptibility in Online Conversation
1 Introduction
2 Related Work
2.1 Language Use and Persuasion
2.2 Persuasion in Online Discussions
2.3 Online Persuasion in One-To-One Setting
3 Research Methodology
4 Results
4.1 Language Use in Discussions
4.2 Dynamics in Type B Discussions
4.3 Language Use in Individual Comments
5 Discussion
6 Conclusion
References
How Does the Thread Level of a Comment Affect its Perceived Persuasiveness? A Reddit Study
1 Introduction
2 Related Work
3 Research Methodology
3.1 Dataset
3.2 Delta Awarded Comments on the Trees: Our Observation and Hypotheses
3.3 Hypothesis Testing: Our Results
4 Discussion
5 Conclusion
References
Ultra-Low-Power Range Error Mitigation for Ultra-Wideband Precise Localization
1 Introduction
2 Methodology
2.1 Network Design
2.2 Network Optimization and Quantization Techniques
3 Experiments and Results
3.1 The DeepUWB Dataset
3.2 Experimental Setting
3.3 Quantitative Results
4 Conclusions
References
The Pareto-Frontier-Based Stiffness of a Controller: Trade-off Between Trajectory Plan and Controller Design
1 Introduction
2 Dynamics and Task Allocation
2.1 Planar UAV Dynamics
2.2 Task Allocation
3 Controller and Trajectory Trade-off Scheme
3.1 Altitude Controller
3.2 Attitude and Position Controller
3.3 Trajectory Design
3.4 Experiments and Testbed
4 Solver Setup
5 Results
6 Stiffness of the Controller
7 Conclusions and Discussions
References
Remote Manipulation of a Robotic Arm with 6 DOF via IBSV Using a Raspberry Pi and Machine Vision
1 Introduction
1.1 Manipulator Robot
1.2 Servo Vision (VS)
2 Materials and Methods
2.1 Materials
2.2 Method
2.3 Machine Vision System
3 Results and Discussion
4 Conclusions
References
Dynamic Analysis and Modeling of DNN-Based Visual Servoing Systems
1 Introduction
2 Related Work
3 Effect of DNNs on Controllers
4 Experimental Setup
4.1 DNN and Communication Protocol
5 Model
5.1 Definition of the System with Detection Loss
5.2 Delay
6 Discussion
7 Conclusion
References
Implementation of a Balanced and Fluid Movement Six-Legged Spider Robot
1 Introduction and Implementation Description
2 Related Work
3 Analysis and Design Details
4 Design Component
4.1 Ping Sensor
4.2 Hi-Tec Servo
4.3 SSC-32U Servo Controller
4.4 Botboarduino
5 Discussion
6 Conclusion
References
The Applying of Low Order Frequency-Dependent Components in Signal Processing of Autonomous Mobile Robotic Platforms
1 Introduction
2 The Description of Low Order Frequency-Dependent Components
3 The Models of Low Order Frequency-Dependent Components
4 The Transfer Function Coefficients Calculation
4.1 The First Order Low Filters and First Order High Filters
4.2 The First Order Bandpass Filters and First Order Stopband Filters
5 The Additional Facilities in Using the Low Order Filters
6 Conclusions
References
Run-Time Dependency Graph Models for Independently Developed Robotic Software Components
1 Introduction
2 The SmartDG Methodology
3 SmartDG Toolchain in Action
4 SmartDG @ Run.time
4.1 Causal Connection
4.2 Modularity
4.3 Distribution
4.4 Co-evolution
5 Conclusions and Future Works
References
A Raspberry Pi Computer Vision System for Self-driving Cars
1 Introduction
1.1 Outline of the Field of Work
1.2 Ethics of the System
2 Materials and Equipment
2.1 Hardware
2.2 Software
3 Methods and Results
3.1 Basic Requirements
3.2 Implementation – Image Processing
3.3 Implementation – Line Definitions
3.4 Implementation – Steering and Self-driving
4 Discussion
5 Conclusion
References
Author Index