Intelligent Systems and Applications

Name: Intelligent Systems and Applications | Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 3
Brand: Springer
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Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 3

Kohei Arai(Editor)

Springer (Publisher)

Published on 6. August 2021

XII, 887 pages

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978-3-030-82199-9 (ISBN)

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Content

Intro
Editor's Preface
Contents
LexDivPara: A Measure of Paraphrase Quality with Integrated Sentential Lexical Complexity
1 Introduction
2 Method
2.1 Data Collection
2.2 Feature Engineering
2.3 Learning to Rank Paraphrase Quality
2.4 Label Smoothing Regularization
2.5 Augmenting Semantic Similarity
3 Results
4 Discussion
5 Conclusion
References
The Potential of Machine Learning Algorithms for Sentiment Classification of Students' Feedback on MOOC
1 Introduction
2 Related Work
3 Experimental Settings
3.1 Dataset
3.2 Preprocessing
3.3 Model Architectures and Parameter Settings
4 Results and Discussion
4.1 Aspect Category Classification
4.2 Aspect Sentiment Classification
5 Conclusion
References
Towards an Automated Language Acquisition System for Grounded Agency
1 Introduction
2 Lessons
2.1 Lesson I: Entities
2.2 Lesson II: Entities and Attributes
2.3 Lesson III: Composed Imagery, Attributes and Relations
2.4 Lesson IV: Entity Modes, Affordances and Actions
2.5 Lesson V: Behavior
3 Conclusions
References
Text-Based Speaker Identification for Video Game Dialogues
1 Introduction
2 Related Works
3 Datasets
3.1 Dragon Age: Origins Dialogue Dataset
3.2 LIGHT Research Platform Dataset
4 Methods
4.1 K-Nearest Neighbors
4.2 Convolutional Neural Network
4.3 Convolutional Neural Network with Utterance Concatenation
4.4 BERT
5 Experiments
6 Discussion
7 Conclusion and Future Work
References
Automatic Monitoring and Analysis of Brands Using Data Extracted from Twitter in Romanian
1 Introduction
2 Recent Works
3 Methodology
3.1 Data Collection
3.2 Data Labelling
3.3 Balancing Data and Creating the Final Set of Training Data
3.4 Data Preprocessing
4 Experiments and Results
4.1 Datasets Exploration
4.2 Transfer Learning Experiment
4.3 Training Supervised Machine Learning Models
4.4 Comparison Between Models on Different Preprocessing Pipelines
5 Brand Analysis Framework
5.1 eReputationScore Calculation
5.2 Analysis Reports
6 Discussions and Future Works
7 Conclusions
References
Natural Language Processing in the Support of Business Organization Management
1 Introduction
2 Characteristics of Natural Language Processing
3 Selected Areas of NLP Business Applications: Review of Research and Practical Examples
4 Survey Research Results
5 Conclusion
References
Discovering Influence of Yelp Reviews Using Hawkes Point Processes
1 Introduction
2 Literature Review
3 Data Description
3.1 Raw Data
3.2 Features
3.3 Variables
4 Methodology
4.1 Lasso Regression Model
4.2 Lasso Regression Model with Hawkes Features (Variables)
4.3 Simulation Using Multinomial Logistic Regression Model
4.4 Lasso Regression Modeling on Simulated Data
5 Results
5.1 Lasso Regression Modeling on Processed Yelp Data with Hawkes Features (Variables)
5.2 Generate Simulated Data Through Multinomial Logistic Regression
5.3 Lasso Regression Modeling on Simulated Review Star-Ratings and Hawkes Features (Variables)
5.4 Verification Through Logistic Regression Model
6 Discussion
7 Conclusion
8 Appendix
8.1 B-Spline Basis Function
References
AIRM: A New AI Recruiting Model for the Saudi Arabia Labor Market
1 Introduction
2 Background Research
3 Data Lake and AI Model
3.1 Data Lake
3.2 Algorithms
4 Proposed Solution
4.1 Initial Screening Layer
4.2 Mapping Layer
4.3 Preferences Layer
5 Future Work
6 Conclusion
References
Chat-XAI: A New Chatbot to Explain Artificial Intelligence
1 Introduction
2 Chatbot Explanation Framework
2.1 Design Principles
2.2 Chatbot Implementation
3 Field Deployment and Preliminary Evaluation
3.1 Findings
4 Discussion and Future Work
References
Global Postal Automation
1 Introduction
2 Background
2.1 History of Postal Automation
2.2 A New Field Theory Approach to Postal Automation
2.3 Introduction to Optical Character Recognition
2.4 Hand-Written Address Interpretation Technology
3 Overview of the Postal Mail Process in the United States
3.1 Mail Classification
3.2 Handling Process
4 Global Postal Automation
4.1 Automation in India
4.2 Automation in China
4.3 Automation in Japan
5 Future of Postal Automation
6 The COVID-19 Pandemic
7 Conclusion
References
Automated Corpus Annotation for Cybersecurity Named Entity Recognition with Small Keyword Dictionary
1 Introduction
2 Background
2.1 BERT
3 Proposed Method
3.1 Category Classification for Ambiguous Meaning Keywords
4 Experimental Evaluation
4.1 Data
4.2 Results
5 Analysis and Discussion
5.1 Analysis: Auto-labeled Data
5.2 Analysis: Sec_col Data
5.3 Discussion
6 Conclusion
References
Text Classification Using Neural Network Language Model (NNLM) and BERT: An Empirical Comparison
1 Introduction
2 Related Works
2.1 Neural Network Language Model (NNLM)
2.2 Word2Vec: Continuous Bag of Words (CBOW)
2.3 Word2Vec: Skip Gram
2.4 Global Vectors for Word Representation (GloVe)
2.5 fastText
2.6 Embeddings from Language Models (ELMo)
2.7 Transformer
2.8 Generative Pre-Training (GPT)
2.9 Bidirectional Encoder Representations from Transformers
2.10 BERT Improvements
2.11 Others
3 Experiments
3.1 Data Set
3.2 Tools and Frameworks
3.3 Data Analysis and Processing
3.4 Experiment
3.5 Evaluation
4 Conclusion
References
Past, Present, and Future of Swarm Robotics
1 Introduction
2 The History of Swarm Robotics
3 Swarm Robotics: An Initial Approach
3.1 Swarm-Types in Science
3.2 Properties
3.3 Advantages and Issues
3.4 Task Areas and Tasks for Swarm Robotic Systems
3.5 Application Fields
3.6 Swarm Robotic Systems and Other Robotic Systems
3.7 Swarm Robotics Classification
4 The Present State
4.1 Projects
4.2 Simulators
4.3 Real Life Applications
5 The Future
5.1 Hardware and Software Issues
5.2 Possible Future Applications
6 Related Surveys
7 Conclusion
References
Flow Empirical Mode Decomposition
1 Introduction
2 Related Work
2.1 Empirical Mode Decomposition
2.2 Electrocardiogram
3 Flow Empirical Mode Decomposition
3.1 Sliding Window Wave
3.2 Flow Empirical Mode Decomposition Algorithm
4 ECG-HR Analyzes Using FEMD
4.1 ECG QRS Peak
4.2 ECG Results
5 Conclusions
References
Cost-Effective 4DoF Manipulator for General Applications
1 Introduction
2 Manipulator Features
3 Kinematics
3.1 Forward Kinematics
3.2 Inverse Kinematics
3.3 Inverse Position
4 Hardware Architecture
5 Software Architecture
5.1 Control Loop
5.2 Initialization Loop
5.3 Data Sharing Packet Protocol
6 Driver Development
7 Experiment and Results
8 Conclusion and Future Work
References
Design of a Granular Jamming Universal Gripper
1 Introduction
1.1 Background
1.2 Problem Formulation
1.3 Related Work
2 Design of the Universal Gripper
2.1 Design
3 Integration
3.1 Integration with a Syringe Actuator
3.2 Integration with a Vacuum Pump
4 Testing
4.1 Integration of the Gripper with a 6 d.o.f. Robotics Arm
4.2 Experiments with Daily Life Objects
5 Conclusion
References
Benchmarking Virtual Reinforcement Learning Algorithms to Balance a Real Inverted Pendulum
1 Introduction
2 Literature Review
2.1 Reinforcement Learning
2.2 Virtual Training
3 Methodology
3.1 Preliminaries
3.2 Rewards
3.3 Policy Gradient
3.4 Actor-Critic
3.5 Proximal Policy Optimization
4 Results
5 Discussion
6 Conclusion
References
Configuring Waypoints and Patterns for Autonomous Arduino Robot with GPS and Bluetooth Using an Android App
1 Introduction
1.1 Specifying a Previously Stored Waypoint
1.2 Replaying a Previously Stored Pattern
2 System Architecture
2.1 User Interface Layer
2.2 Robot Control Layer
2.3 Robot Physical Layer
3 Android App Design and Programming
3.1 Communication Protocol
3.2 Storage
3.3 Remote Control
3.4 Move to Waypoint
3.5 Replay Pattern
4 Robot Design and Programming
4.1 Arduino
4.2 Bluetooth
4.3 GPS
4.4 Compass
4.5 microSD
4.6 Motor Controllers
4.7 Program Flow
5 Results
5.1 Remote Control
5.2 Move to Waypoint
5.3 Replay Pattern
5.4 Improvements
5.5 Overall
References
Small Scale Mobile Robot Auto-parking Using Deep Learning, Image Processing, and Kinematics-Based Target Prediction
1 Introduction
2 Background and Related Research
2.1 Related Research
2.2 Transfer Learning with AlexNet
2.3 The Hough Transform
3 Hardware and Software Setup
3.1 Hardware Setup
3.2 Software Setup
4 The Four-Step Auto-parking Process
4.1 Identification of Available Parking Space
4.2 Determination of Parking Slot Boundaries
4.3 Kinematics-Based Target Prediction
4.4 Motion Control
5 Conclusions and Future Directions
References
Local-Minimum-Free Artificial Potential Field Method for Obstacle Avoidance
1 Introduction
2 State of the Art
3 Problem Formulation
3.1 Local Minima Problem
3.2 The Modified APF
4 Simulation Results
5 Conclusion
References
Digital Transformation of Public Service Delivery Processes in a Smart City
1 Introduction
2 State of the Art
3 The Formal Model and System Objectives
4 Methodology
5 Processes Verification and Evaluation
6 Implementation and Tests
7 Conclusion
References
Prediction of Homicides in Urban Centers: A Machine Learning Approach
1 Introduction
2 Related Work
3 Crime Understanding
4 Machine Learning Approach
4.1 The Data
4.2 Pre-process
4.3 Analyzed Algorithms
5 Discussion
5.1 Performance Analysis
5.2 Statistical Analysis
6 Conclusion
References
Experimental Design of Artificial Neural-Network Solutions for Traffic Sign Recognition
1 Introduction
2 Designing a Solution
2.1 Artificial Neural Network
2.2 Principal Component Analysis
2.3 Simulated Annealing
2.4 Convolutional Neural Networks
2.5 Proposed Solution
3 Experiments
3.1 Method
3.2 Experiments
3.3 Alternative Solutions
4 Results and Discussions
5 Conclusions and Future Work
References
Potholes Detection Using Deep Learning and Area Estimation Using Image Processing
1 Introduction
2 Related Works
3 Theoretical Overview of the Architectures
3.1 YOLOv5
3.2 Faster RCNN
4 Experimental Setup and Results
4.1 Setup
4.2 Performance Evaluation Metrics
4.3 Object Detection Result and Discussion
4.4 Area Estimation
5 Conclusion and Future Work
References
Exploiting Deep Learning Algorithm to Understand Buildings' Façade Characteristics
1 Introduction
2 Background
2.1 Urban Heat Island
2.2 Building Facades' Impact on UHI
2.3 Building Facade Material
2.4 Building Facade Color
2.5 Other Parameters
2.6 Image Classification
2.7 Convolutional Neural Network
3 Methods and Tools
3.1 CNN Architecture
4 Results
4.1 Evaluation of the Network
5 Discussion
6 Conclusion
References
An On-Device Deep Learning Framework to Encourage the Recycling of Waste
1 Introduction
2 Related Work
3 Methodology
4 Design Specification
4.1 Deep Learning Image Classification Model
4.2 Gamification Elements
5 Implementation
6 Results and Discussion
7 Conclusion and Future Work
References
Spatial Modelling and Microstructural Modulation of Porous Pavement Materials for Seepage Control in Smart Cities
1 Introduction
2 Variable with Their Correlation Selection
3 Structural Optimization and Its Analysis
3.1 Optimal Design of Composition
3.2 Construction and Evaluation of Strength Model
3.3 Structural Optimization of Framework and Matrix Based on Contact Point
4 Conclusion
References
Deep Learning-Based Vehicle Direction Detection
1 Introduction
2 Problem Statement
3 Approach
4 Deep Learning Techniques
5 MATLAB Program for Deep Learning
6 Results
6.1 Training Progress
6.2 Confusion Chart
6.3 Learning Progress with Epochs
7 Conclusion
References
EMG Controlled Electric Wheelchair
1 Introduction
2 Preprocessing
3 Feature Extraction
4 Classification Using Artificial Neural Networks
5 Hardware Components
6 Results
7 Conclusions
8 Limitations of the Current Project
9 Future Work
References
A Low-Cost Human-Robot Interface for the Motion Planning of Robotic Hands
1 Introduction
2 System Design
2.1 Selection of the Parts
2.2 Requirements and Specifications
3 Design
4 Software Integration
5 Testing
6 Discussion and Conclusion
References
Ensemble UNet++ for Locating the Exponential Growth Virus Samples
1 Introduction
2 Background
2.1 Phylogenitic Tree
2.2 Wright-Fisher Model
2.3 UNet++
2.4 Loss Function
3 Experiments and Results
3.1 UNet++ for Large Exponential Block Samples
3.2 UNet++ for Small Exponential Block Samples
3.3 Ensemble UNet++
4 Conclusion
References
ViewClassifier: Visual Analytics on Performance Analysis for Imbalanced Fatal Accident Data
1 Introduction
2 Data Description
3 Design Goals of ViewClassifier
4 Related Work
4.1 Visual Analytics for Machine Learning
4.2 Visualization for Traffic Accident Data
5 The Proposed Visualization Tool
5.1 Simulating Negative Samples with Feature Distribution
5.2 Displaying of Overall Classification Results
5.3 Computational Modeling
5.4 Class and Instance-Level Performance Visualization
5.5 Providing Interactivity to Users
6 Case Studies
6.1 Case Study I: US Fatal Accident Data
6.2 Case Study II: UK Fatal Accident Data
7 Discussion
8 Conclusion
References
Comparative Analysis of Machine Learning Algorithms Using COVID-19 Chest X-ray Images and Dataset
1 Introduction
2 Background
2.1 Problem Definition
2.2 Discussion of Related Work
2.3 Machine Learning Algorithms
3 Research Methodology
3.1 Data Sources
3.2 Preprocessing
3.3 Applying Machine Learning Algorithms
3.4 Results and Analysis
3.5 Discussion of Results
References
A Critical Evaluation of Machine Learning and Deep Learning Techniques for COVID-19 Prediction
1 Introduction
2 Related Work
2.1 Deep Learning Studies
2.2 Machine Learning Studies
2.3 Deep Learning and Machine Learning Combine Model Studies
3 Framework for Covid-19 Detection
3.1 Data Gathering
3.2 Data Preprocessing
3.3 Feature Extraction and Selection
3.4 Model Building
3.5 Model Building
4 Critical Evaluation
4.1 COVID-19 Detection Techniques
4.2 Machine Learning and Deep Learning Techniques
4.3 Dataset Evaluation
5 Analysis, Limitations, and Challenges
6 Conclusion and Future Work
References
Automatic Estimation of Fluid Volume Intake
1 Introduction
2 Material and Methods
2.1 Preliminary Datasets Collection
2.2 FxTVI
2.3 FxSVI
3 Experimental Results
3.1 FXTVI
3.2 FXSVI
4 Discussion
5 Conclusion
References
A Deep Learning-Based Tool for Automatic Brain Extraction from Functional Magnetic Resonance Images of Rodents
1 Introduction
2 Related Works
3 Methods
3.1 Image Acquisition
3.2 Dataset Production and Watershedding-Based Brain Segmentation
3.3 Deep Learning-Based Segmentation
3.4 Data Augmentation and Training
4 Results
5 Discussion
References
Classification of Computed Tomography Images with Pleural Effusion Disease Using Convolutional Neural Networks
1 Introduction
1.1 Objective
2 Materials and Methods
2.1 Materials
2.2 Methods
3 Experimental Results
3.1 Inception-V3
3.2 ResNet50 Results
4 Conclusions
References
Creating a Robot Brain with Object Recognition Using Vocal Control, Text-to-Speech Support and a Simple Webcam
1 Introduction
2 Problem Formulation
3 Problem Solution
3.1 The Algorithm
3.2 Software Implementation
4 Conclusion
References
Detection of Health-Preserving Behavior Among VK.com Users Based on the Analysis of Graphic, Text and Numerical Data
1 Introduction
2 Background
3 Survey Data of Social Network Users
4 Social Network Data
5 Building Image Descriptors
6 List of Generated Datasets, Machine Learning Methods Used
7 Results of User Classification
8 Discussion of the Results
9 Conclusions
References
WearMask in COVID-19: Identification of Wearing Facemask Based on Using CNN Model and Pre-trained CNN Models
1 Introduction
2 Literature Review
3 Dataset Explanation
4 Methodology
4.1 Image Pre-processing
4.2 CNN Architecture with Fully Connected Deep Neural Network
4.3 Pre-trained Models
4.4 Training Detail
5 Experimental Results
5.1 Accuracy and Loss vs Number of Epochs
5.2 Classification Metrics
5.3 Comparative Analysis
6 Conclusion and Future Works
References
Predicting Falls in Older Adults Aged 65 and up Based on Fall Risk Dataset
1 Introduction
2 Background
2.1 Related Work
2.2 Relevant Machine Learning Algorithms
3 Methodology
3.1 Fall Risk Dataset
3.2 Data Pre-processing and Preparation for Training and Testing
4 Results
5 Conclusion
6 Future Work
References
Detection of the Inflammatory Bowel Diseases via Machine Learning Methods
1 Introduction
2 Methods
3 Results
3.1 Metabolic Pathways
3.2 Integrative Analysis of Networks
3.3 Machine-Learning Analysis via MLP Classifier
3.4 Machine-Learning Analysis
4 Conclusion
References
An Attention-Based Deep Learning Model with Interpretable Patch-Weight Sharing for Diagnosing Cervical Dysplasia
1 Introduction
2 Related Work
3 Data
4 Method
4.1 Proposed Model for Cervical Cancer Diagnosis
4.2 Loss Weighting Guidance
5 Results
6 Conclusion and Future Work
References
Towards a Computational Framework for Automated Discovery and Modeling of Biological Rhythms from Wearable Data Streams
1 Introduction
2 Related Work
3 Methods
3.1 Periodicity Detection
3.2 Changing Point Detection in Cycles
4 Experiment
4.1 Periodicity Detection
4.2 Changing Point Detection in Cycles
5 Implications and Conclusion
References
Towards a Novel Architecture of Smart Campuses Based on Spatial Data Infrastructure and Distributed Ontology
1 Introduction
2 Related Works
3 General Architecture of the Smart Campus
4 Distributed Ontology and SOA-Based Approach: Linking Spatial Objects and Their Features
5 Conclusion
References
Course Recommendation System for a Flexible Curriculum Based on Attribute Selection and Regression
1 Introduction
2 State of the Art
3 Description of the Curriculum
4 Description of the Data
4.1 Data Preprocessing
5 System Architecture
5.1 Operation of Module 1
5.2 Experiments and Results for the Operation of Module 1
5.3 Operation of Module 2
5.4 Experiments and Results for the Operation of Module 2
5.5 System Evaluation
6 Conclusions and Future Work
References
Advancing Adaptive Learning via Artificial Intelligence
1 Adaptive Education
2 Seeking Intelligent and Adaptive Learning
3 Survey of Educational Adaptive Engines
3.1 McGraw Hill SIMnet
3.2 McGraw Hill Connect/ConnectMaster
3.3 Pearson MyITLab
3.4 Realizeit
3.5 Smart Sparrow
3.6 Cerego
3.7 MindTap (by Cengage)
3.8 Acrobatiq
3.9 Fishtree
3.10 Drillster
3.11 Waymaker
3.12 ScootPad
3.13 Knewton Alta
3.14 Inspark
4 Analysis
5 Conclusion
6 Future Study
Appendix
References
Technology of Creation and Functioning of a Multimedia Educational Portal for Distance Learning of School Children in the Republic of Kazakhstan Under Pandemic Conditions
1 Introduction
2 Portal Creation and Functioning Technology
3 Filling the Portal with Content
4 Conclusion
References
Detecting CAN Bus Intrusion by Applying Machine Learning Method to Graph Based Features
1 Introduction
2 Background and Related Work
2.1 CAN Bus
2.2 Related Work
2.3 Attack Model
3 Methodology
3.1 Overview of the IDS
3.2 Conversion of CAN Bus Message to Graph
3.3 Graph Properties as Features
3.4 Classification Step
4 Performance Evaluation
4.1 Description of the Dataset
4.2 Validation Metrics
4.3 Simulation Result
4.4 Comparison with the State of the Art
5 Conclusion and Future Work
References
Information Security Awareness Evaluation Framework and Exploratory Study
1 Introduction
2 State-of-the-Art and Security-Related Competencies
2.1 Outline of the Questionnaire
2.2 Respondents' Profiles
3 Degree of Awareness of Respondents in the Area of Information Security
3.1 Degree of Awareness in the Technological Aspects of Information Security
3.2 Degree of Awareness in the Legal Aspects of Information Security
3.3 Degree of Awareness in the Economic Aspects of Information Security
4 Conclusion and Future Work
References
Multilayer Security for Facial Authentication to Secure Text Files
1 Introduction
2 Methodology
2.1 Encryption and Embedding
2.2 Extraction and Decryption
3 Analysis of Findings and Results
3.1 Accuracy of the Face Authentication
3.2 Runtime Execution
3.3 Resistance of the Ciphertext to Brute Force Attack
3.4 Imperceptibility of the Stego-Image Using MSE and PSNR
4 Conclusions and Recommendations
References
sBiLSAN: Stacked Bidirectional Self-attention LSTM Network for Anomaly Detection and Diagnosis from System Logs
1 Introduction
2 Related Work
3 Dataset
3.1 Simulated Network Traffic Dataset
3.2 Real-Life Server Log Dataset
4 Methods
4.1 LSTM-AD: LSTM-Based Anomaly Detection
4.2 Stacked LSTM Based Model
4.3 Stacked Bidirectional LSTM Based Model
4.4 Attention Mechanism
4.5 Self-attention
4.6 Stacked Bidirectional LSTM Based Model with Self-Attention
4.7 Data Processing
4.8 Experimental Setup
4.9 Evaluation Metrics
5 Experimental Results
5.1 Simulated Network Traffic Dataset
5.2 Real-Life Server Log Dataset
6 Conclusion
References
A Multi-agent System with Smart Agents for Resource Allocation Problem Solving
1 Introduction
2 Test Problem
3 Proposed Algorithm
4 Algorithm Properties
4.1 Experiment 1: Trucks Accumulate Experience While Repeatedly Starting the Same Factory
4.2 Experiment 2: Studying the Effect of Increasing the Success Assessment on the Total Mileage of All Trucks When Starting a Set of Factories
4.3 Experiment 3: Comparison with Linear Programming Solution of Transportation Problem
5 Conclusion
References
Search Methods in Motion Planning for Mobile Robots
1 Introduction
1.1 Robotic Paths in Motion Planning Problems
1.2 Background on Contexts and Applications
1.3 Search Methods in This Study
2 Deployment of DFS in Robotic Paths
2.1 The Depth-First Search Method
2.2 Implementation of Depth-First Search in Robotic Motion Planning
3 BFS and Its Application to Robotic Paths
3.1 The Breadth-First Search Method
3.2 How Breadth-First Search Applies to Robots Finding Paths
4 A* Search Method and Its Robotic Path Adaptation
4.1 The A* Search Method
4.2 Adaptation of A* Search for Navigating Robotic Paths
5 Results and Discussion
5.1 Highlights of Experiments
5.2 Potential Applications of this Study
6 Related Work
7 Conclusions
References
Application of Adversarial Domain Adaptation to Voice Activity Detection
1 Introduction
1.1 Background
1.2 Purpose
2 Methodology
2.1 Adversarial Domain Adaptation between Clean and Noise Distribution
2.2 Voice Activity Detector
3 Experiments
4 Results and Discussion
4.1 Effect of Adversarial Domain Adaptation
4.2 Comparison to Models Learned Hand-Crafted Feature
5 Conclusions
References
More Than Just an Auxiliary Loss: Anti-spoofing Backbone Training via Adversarial Pseudo-depth Generation
1 Introduction
2 Related Work
3 Proposed Method
3.1 Pre-processing
3.2 Pseudo-Depth GAN
4 Experiment Setting
4.1 Experiment Types
4.2 Evaluation Metrics
5 Experiment Results
5.1 Intra Dataset Experiment
5.2 Inter Dataset Experiment
5.3 Embedding Space Visualization
6 Conclusion
References
Emergence and Solidification-Fluidisation
1 Introduction
2 Emergence Theorem
2.1 System Ordering Processes
2.2 6th Main Sentence of Thermodynamics
2.3 Freedom and Safety
3 Solidification-Fluidisation Theorem
3.1 Socio Cultural Ordering Process
3.2 Osmotic Paradigm
4 Hybridisation
5 Conclusion and Outlook
References
Prediction of Isoflavone Content in Soybeans with Sentinel-2 Optical Sensor Data by Means of Regressive Analysis
1 Introduction
2 Proposed Method
3 Experiment
3.1 Experimental Method and Data Acquisition
3.2 Estimation of Isoflavone Content using Sentinel-2 of Satellite Imagery Data
4 Conclusion
5 Future Works
References
A Neuro-Fuzzy Model for Fault Detection, Prediction and Analysis for a Petroleum Refinery
1 Introduction
2 Artificial Neural Networks
3 Fuzzy Logic
4 Neuro-Fuzzy System
5 Data Collection and Feature Extraction
6 Method
7 Results
8 Conclusion
References
Impact of Interventional Policies Including Vaccine on COVID-19 Propagation and Socio-economic Factors: Predictive Model Enabling Simulations Using Machine Learning and Big Data
1 Introduction
2 Methods
2.1 Data Sources
2.2 Machine Learning Pipeline and Architecture
3 Results
4 Discussion
5 Multimedia Appendix 1
6 Multimedia Appendix 2
References
Correction to: Automatic Monitoring and Analysis of Brands Using Data Extracted from Twitter in Romanian
Correction to: Chapter "Automatic Monitoring and Analysis of Brands Using Data Extracted from Twitter in Romanian" in: K. Arai (Ed.): Intelligent Systems and Applications, LNNS 296, https://doi.org/10.1007/978-3-030-82199-9_5
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