Intelligent Systems Design and Applications

Name: Intelligent Systems Design and Applications | 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 1
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22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 1

Ajith Abraham Sabri Pllana Gabriella Casalino Kun Ma Anu Bajaj(Herausgeber*in)

Springer (Verlag)

Erschienen am 30. Mai 2023

XV, 577 Seiten

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978-3-031-27440-4 (ISBN)

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Intro
Preface
ISDA 2022-Organization
Contents
KMetaTagger: A Knowledge Centric Metadata Driven Hybrid Tag Recommendation Model Encompassing Machine Intelligence
1 Introduction
2 Related Work
3 Proposed Work
4 Results and Performance Evaluation
5 Conclusion
References
KCReqRec: A Knowledge Centric Approach for Semantically Inclined Requirement Recommendation with Micro Requirement Mapping Using Hybrid Learning Models
1 Introduction
2 Related Works
3 Proposed System Architecture
4 Implementation and Performance Evaluation and Results
5 Conclusion
References
Object Classification Using ECOC Multi-class SVM and HOG Characteristics
1 Introduction
1.1 Background
1.2 Research Objectives
1.3 Paper Organization
2 Proposed Scheme for Object Classification
3 System Description
3.1 Image Datasets
3.2 ECOC Based Multi-class SVM
3.3 Appropriate Cell Size Selection for HOG Feature
4 Results and Discussions
5 Conclusion
References
GA Evolved Configuration Data for Embryonic Architecture with Built-in Self-test
1 Introduction
2 Embryonic Digital Circuit Architecture Using CGP Data
3 Novel Parallel GA Design for CGP Configuration Data Generation
3.1 Optimum Individual Monogenetic GA-OIMGA
3.2 Parallel HsClone GA
4 Embryonic Cells with Built-in Self-Test Design
5 Embryonic Adder and Comparator Cell Fault Detection
6 Conclusion and Scope for Future Work
References
A Multi-layer Deep Learning Model for ECG-Based Arrhythmia Classification
1 Introduction
2 Related Work
3 Material and Method
3.1 Dataset
3.2 Methodology
4 Results and Discussion
5 Conclusion
References
Analyzing Electoral Data Using Partitional and Hierarchical Clustering Algorithms
1 Introduction
2 The Municipal Human Development Index (MHDI)
3 Data Used in the Experiments
4 Methodology and Experiments
5 Conclusions
References
Medical Decision Making Based 5D Cardiac MRI Segmentation Tools
1 Introduction
2 Methods and Materials
3 Theory
3.1 Concept of the 5D Segmentation and Medical Issue
3.2 Goals and Contributions
4 Results
5 Discussion
6 Conclusion
References
India Post Service Facility Layout Design Selection and Evaluation Using MCDM Approach
1 Introduction
2 Literature Support
3 Research Methodology
4 Application - NSH Mangalore
5 Results
5.1 Finding the Weightage Criteria
5.2 Calculation Method
6 Conclusions
References
Weighted Pathfinding in the Paparazzi Problem with Dynamic Obstacles
1 Introduction
2 Problem Statement
3 Background Information
3.1 A* Algorithm
3.2 Extended A* Algorithm
3.3 Heuristics
3.4 Dynamic Obstacles
4 Implementation and Testing
4.1 Code Structure
4.2 Pathfinding
5 Results and Discussion
5.1 Data Distribution
5.2 Pathfinding
5.3 Diagonal Movement
5.4 Overall Heuristic Performance
6 Conclusions
References
A Rapid Review on Ensemble Algorithms for COVID-19 Classification Using Image-Based Exams
1 Introduction
2 Ensemble Algorithms
3 Methodology
3.1 Inclusion Criteria
3.2 Exclusion Criteria
4 Results and Discussion
4.1 Q1 - Ensemble Technique
4.2 Q2 - Number of Classes
4.3 Q3 - Machine Learning Algorithms and Models
4.4 Q4 - Datasets
5 Conclusions
References
Indian Postal Service Quality Assessment Using Graph Theoretic Approach - A Quantitative Decision-Making Tool
1 Introduction
1.1 Importance of the Study
2 Literature Review
2.1 Graph Theoretical (GT) Model
3 Research Methodology
3.1 Graph-Theoretic Model Approach
4 Analysis and Results
4.1 Graph Theory Calculation
5 Conclusions
References
Analyzing the Critical Success Factors of Lean System Implementation in India Post Using DEMATEL Method
1 Introduction
1.1 Rationale of the Study
2 Literature Support
3 Research Methodology
3.1 Steps for DEMATEL Method
4 Case Application: Indian Postal NSH Mangalore, India
5 Conclusions
References
Application of Artificial Intelligence in Mental Health
1 Introduction to Artificial Intelligence in Healthcare
2 Mental Health
2.1 AI in Healthcare
2.2 Ethics and AI Mental Health Research
2.3 AI Research on the Involvement of Patient and Public Mental Health
2.4 Well-Being and Educational Performance
2.5 Internet-Based Mental Health Care
2.6 Mental Healthcare Chatbots
3 Literature Survey
4 Constraints of AI and Mental Health Care Research
5 Statistics Scenario in the Area of AI in Mental Health Care Research
6 Conclusion
References
Cold Rolling Mill Energy Consumption Prediction Using Machine Learning
1 Introduction
2 Cold Rolling Mill and Energy Consumption
3 Proposed Approach
4 Results and Analysis: Model Training and Energy Prediction
5 Conclusions and Future Work
References
Virtual Reconstruction of Adaptive Spectral and Spatial Features Based on CNN for HSI Classification
1 Introduction
2 Proposed Approach
2.1 Extraction of Spectral Data Vectors and Fusions of Pixels to Obtain a Single Spatial-Spectral Band
2.2 Apply Five Algorithms to Create Five Virtual Layers
2.3 3D Image Reconstruction
2.4 Edge-Adaptive Spatial Data Extraction
2.5 Convolution and Processing of Each Block Until Recognition of the pixel
2.6 Placing Pixels in Their Positions, Merging the Five Spectral Bands and Labeling
3 Experiences and Results
3.1 Tests
3.2 Results and Discussions
4 Conclusion
References
Enhancing Rental Bike Count and Availability Prediction Using Regression Modelling
1 Introduction
2 Literature Review
3 Methodology
3.1 Multiple Linear Regression
3.2 Polynomial Regression
4 Results
5 Conclusion and Fututre Enhancement
References
Application of WASPAS Method for the Evaluation of Tamil Nadu Private Travels
1 Introduction
2 Literature Support
3 Research Methods
4 Case Study - Chennai, Tamilnadu, Southern India
4.1 Application of WASPAS Method
5 Comparative Study
6 Conclusion
References
Time Series Forecast Applied to Electricity Consumption
1 Introduction
2 Related Work
3 BackGround of Study
3.1 Definitions
3.2 Machine Learnings Models
4 Material and Methods
4.1 Dataset Description
4.2 Performance Indices
5 Simulation Results
5.1 Regression Models - Data with Daily Periodicity
5.2 Regression Models - Data with Daily Periodicity (Outlier Removal)
5.3 Regression Models - Data with Monthly Periodicity
5.4 Regression Models - Data with Daily Periodicity (Outlier Removal) - Moving Average
5.5 Multi Layer Perceptron (MLP) - Data with Monthly Periodicity
5.6 Recurrent Neural Network (RNR) - Data with Monthly Periodicity
6 Conclusions
References
A Survey on Text Processing Using Deep Learning Techniques
1 Introduction
2 Sentiment Analysis is Divided into Numerous Categories
2.1 Sentiment with a Finer Granularity
2.2 Sentiment Analysis for Emotion Identification
2.3 Analyses Based on Aspects
2.4 Sentiment Analysis Based on Intent
3 Approaches to Sentiment Analysis
3.1 Rule-Based Approach
3.2 Machine Learning Approach
3.3 Lexicon Based Approach
4 All Approaches Advantages and Limitations
5 Text-Based Emotion Detection (TBED)
5.1 Datasets for Text-Based ED (Emotion Detection) Research
6 Feature Set
6.1 Extraction of Feature
6.2 Feature Selection
7 Comparison Analysis
7.1 Lexicon Based Approach
7.2 Dictionary-Based Classification
7.3 Corpus-Based Classification
7.4 Machine Learning Based Classification
7.5 Support Vector Machine
7.6 Comparative Table for Different Classification Algorithm
7.7 Naïve Bayes
7.8 K-Nearest Neighbor
7.9 Maximum Entropy
7.10 Decision Tree Learning
7.11 Semantic Orientation Approach
7.12 Keyword-Based Classification
7.13 Emotions Based Classifications
8 Issues in Text Sentiment Analysis
9 Conclusion
References
RePI: Research Paper Impact Analysis
1 Introduction
2 Literature Survey
2.1 Previous Works
2.2 Impact Metrics
2.3 Keyword Extraction
3 Dataset Creation
4 Methodology and Architecture
5 Design and API Integration
5.1 RAKE
5.2 Implementation
6 Impact Metric Calculation
7 Results
7.1 Visualizations
7.2 Impact Metric Ratio
8 Conclusion
References
Human-Centred Artificial Intelligence in Sound Perception and Music Composition
1 Introduction
2 Melody and Musical Grammar
3 Formalization of Musical Grammar Rules
4 Obtained Results
5 Discussion and Conclusions
References
Multi-objective Optimization for Sensor Networks Based Smart Parking Systems
1 Introduction
2 Related Works
3 Real Time Smart Parking System Description
4 Mathematical Formulation
4.1 Poisson Process
4.2 Linear Programming Formulation
5 Performance Evaluation
6 Open Research Issue: Sensor Networks and Artificial Neural Networks (ANN)
7 Conclusion
References
Process Automation with Digital Robots Under Smart University Concept
1 Introduction
2 Literature Review
3 Digital Transformation of Processes
3.1 Digital Transformation
3.2 Process Automation
3.3 Human Path and Robot Path
4 Case Study
4.1 Current Situation Analysis
4.2 Automating the Process
4.3 Improved Situation Analysis
4.4 What-If Analysis
5 Conclusion
References
Performance Evaluation of Manufacturing Product Layout Design Using PROMETHEE II - MCDM Method
1 Introduction
2 Literature Background
3 Research Methodology
4 Case Problem: Product Layout, Coimbatore, India
5 Results and Findings
6 Conclusion
References
An Ergonomics Assessment in India Post Manual Sorting Centre Using EDAS - A MCDM Approach
1 Introduction
2 Literature Support
3 Research Methodology
4 Case Study - Indian Postal Service, Mangalore, Karnataka
4.1 Cognitive Workload Assessment
5 Results of EDAS Method
6 Discussions
7 Conclusion
References
A Concept for QoS Management in SOA-Based SoS Architectures
1 Introduction
2 Related Work
3 Methodology
3.1 Environment
3.2 Arrowhead Framework
4 Scenarios
4.1 Scenario: AHF's Current QoS
4.2 Scenario: Performance Based QoS
4.3 Scenario: Availability and Reliability Based QoS
4.4 Scenario: Service Cost Based QoS
4.5 Scenario: Privacy Based QoS
5 Requirements for an SOA-Based SoS QoS System
6 Results and Discussion
7 Future Work
References
Comparative Data Oversampling Techniques with Deep Learning Algorithms for Credit Card Fraud Detection
1 Introduction
2 Literature Review
2.1 Review of Data Oversampling Techniques
3 Methodology
3.1 Dataset Collection
3.2 Dataset Pre-processing
3.3 Data Splitting
3.4 Data Resampling
3.5 Distributions of Training and Testing Data
3.6 Deep Learning Models
3.7 Performance Evaluation Metrics
4 Experimental Results
5 Conclusion
References
An Error Sensitive Fuzzy Clustering Technique for Mammogram Image Segmentation
1 Introduction
2 Proposed Methodology
3 Results and Discussion
4 Conclusion
References
A Sustainable Green Supplier Selection Using CRITIC Method
1 Introduction
2 Literature Support
3 Research Methodology
3.1 CRITIC Method - Step by Step Procedure
4 Case Study - ABC, Chennai, Tamil Nadu
4.1 Application of CRITIC Method
5 Results and Discussions
6 Conclusion
References
Apartment Waste Disposal Sustainable Facility Location Using ENTROPY Method
1 Introduction
2 Literature Support
3 Research Methodology
4 Case Study - Park Avenue Apartments, Chennai, Tamil Nadu
5 Application of ENTROPY Method
6 Results and Discussions
7 Conclusion
References
Prediction of Stock Price Direction Combining Volatility Indicators with Machine Learning Algorithms
1 Introduction
2 Related Works
3 Methodology
3.1 Data Collection
3.2 Weighting Data
3.3 Feature Extraction
3.4 Training Model with Random Forest and SVM
3.5 Evaluate Predictions
4 Results and Discussion
5 Conclusion
References
Integration of Text and Graph-Based Features for Depression Detection Using Visibility Graph
1 Introduction
2 Related Work
2.1 Text-Based Depression Detection
2.2 Voice-Based Depression Detection
2.3 Multi-modal Voice and Text Approaches
3 Proposed Method
3.1 Mapping of Signals to Graphs
3.2 Overall Process
3.3 Scalable Depression Prediction
4 Experiments
4.1 Dataset
4.2 Preprocessing
4.3 Text-Based Detection
4.4 Voice-Based Detection
5 Conclusion
References
Application of VIKOR Method for Green Postal Sustainable Service Design
1 Introduction
2 Literature Support
3 Research Methodology
4 Case Study - Indian Postal Service, South India
5 Application of VIKOR Method
5.1 Results and Discussions
6 Conclusion
References
Automotive Stamping Process Optimization Using Machine Learning and Multi-objective Evolutionary Algorithm
1 Introduction
2 Theoretical Background
2.1 Automotive Stamping
2.2 Multi-objective Optimization and NSGA-II Algorithm
3 Related Work
4 Proposed Model
5 Experiments, Results, and Analysis
6 Conclusion and Future Work
References
Augmented Reality in Marketing Sector: Viewpoint of XR the Moroccan Association Experts
1 Introduction
2 AR Marketing
3 Research Methodology
3.1 SWOT Analysis
4 Discussion
4.1 Strengths
4.2 Weaknesses
4.3 Opportunities
4.4 Threats
5 Conclusion
References
Improving MIL Video Anomaly Detection Concatenating Deep Features of Video Clips
1 Introduction
2 Related Work
3 Methodology
3.1 Data Organization
3.2 Data Windowing Procedure
3.3 Modeling and Evaluation
4 Results and Discussion
5 Conclusion
References
Moroccan Stock Price Prediction Using Trend Technical Indicators: A Comparison Study
1 Introduction
2 Related Works
3 Methodology
3.1 Features
3.2 LSTM and RF Models
4 Results and Discussion
5 Conclusion and Future Works
References
A Review on Cloud-Based Smart Applications
1 Introduction
2 Fundamentals of IoT
3 Overview of Cloud Computing
3.1 Cloud as a Service
3.2 Cloud-Based Smart Applications
3.3 Relationship Between IoT and Cloud Computing
3.4 Cloud-Based Internet of Things (Cloud of Things)
4 Literature Survey
5 Challenges
5.1 Security and Privacy
5.2 Heterogeneity
5.3 Performance
5.4 Legal Aspects
5.5 Monitoring
6 New Research Initiatives
7 Conclusion
References
Territorial Design and Vehicle Routing Problem Applied to the Population Census as a Case Study
1 Introduction
2 The Territorial Design Problem and Geographical Units Partitioning
2.1 Modeling in Geographic Partitioning
3 Partitioning Algorithm in Territorial Design with Tabu Search
3.1 Tabu Search Algorithm in Partitioning
3.2 Tabu Search Algorithm in Partitioning
3.3 Parameters Description
3.4 Parameters Description
4 Territorial Design and Vehicle Routing Problem Applied to the Metropolitan Area of Valle de Toluca
5 Vehicle Routing Problem Model
6 Conclusions
References
A Unified Framework for Knowledge Inference Based on Heterogeneous Graph Neural Networks
1 Introduction
2 Related Work
2.1 Knowledge Inference Based on Knowledge Graph
2.2 Heterogeneous Diagram
3 Background
3.1 Heterogeneous Graph Neural Networks in Recommender Systems
3.2 Heterogeneous Graph Neural Networks in Knowledge Graph Inference
3.3 Comparative Analysis
4 Experiment Setup
4.1 Dataset and Evaluation Indicators
4.2 Comparison of Results
5 Discussion and Conclusion
References
Evaluation of Convolution Primitives for Embedded Neural Networks on 32-Bit Microcontrollers
1 Introduction
2 Background
2.1 Preliminaries and Notation
2.2 Convolution Primitives
2.3 Neural Network Library for Cortex-M MCU
3 Implementation
3.1 Quantization
3.2 Batch Normalization Folding
3.3 Im2col Algorithm with SIMD Instructions
4 Experimental Characterisations
4.1 Influence of the Primitive Parameters
4.2 Influence of Other Factors
5 Conclusion
References
On a Structure of an Automated Differential Equation Solver Based on Machine Learning Methods
1 Introduction
2 Related Work
3 State of Neural Network Differential Equation Solvers
4 Proposed Architecture
4.1 Equation Module
4.2 Solution and Solver Module
4.3 Cache Module
5 Conclusion
References
Stack Tag - Predicting the Stack Overflow Questions' Tags Using Gated Recurrent Unit Networks
1 Introduction
2 Technologies Employed
2.1 Deep Learning
2.2 Recurrent Neural Networks
2.3 Long Short Term Memory
2.4 Gated Recurrent Unit Networks
2.5 Natural Language Processing
3 Related Work
3.1 SCC++: Predicting the Programming Language of Questions and Snippets of Stack Overflow
3.2 SOTagger - Towards Classifying Stack Overflow Posts Through Contextual Tagging
3.3 Predicting the Programming Language: Extracting Knowledge from Stack Overflow Posts
3.4 Predicting Tags for Stack Overflow Posts
3.5 Predicting Tags for Stack Overflow Posts
3.6 Prediction of Relatedness in Stack Overflow: Deep Learning vs. SVM: A Reproducibility Study
4 Proposed Methodology
4.1 Dataset
4.2 Data Cleaning and Preprocessing
5 Experiments and Results
5.1 Model Summary
5.2 Evaluation Parameters
6 Conclusion and Future Scope
References
A Rapid Review on the Application of Unmanned Aerial Vehicles in Construction Safety
1 Introduction
2 Research Method
3 Results and Discussion
3.1 Overview of the Related Documents
3.2 Advantages of UAV in Construction Safety
3.3 Barriers and Hazards in the Utilization of UAVs
4 Future Directions
5 Summary and Conclusion
References
Retail Demand Forecasting for 1 Million Products
1 Introduction
2 Related Work
3 System Architecture
4 Experimental Evaluation
4.1 Basic Model Architecture
4.2 AutoML
4.3 Case Study
5 Conclusions
References
Intelligent Mapping of Virtualized Services on Multi-domain Networks
1 Introduction
2 Related Work
3 Genetic Service Mapping
3.1 GeSeMa's Request Model
3.2 The Proposed Genetic Multi-domain Mapping Method
4 Experimental Evaluation
5 Conclusion
References
Fundus Eye Image Classification and Interpretation for Glaucoma Diagnosis
1 Introduction
2 Theoretical Background
2.1 Glaucoma Disease and Eye Fundus Image
2.2 Convolutional Neural Networks and Model Interpretability
3 Related Works
4 Proposed Model
5 Experiments, Results, and Analysis
6 Conclusion and Future Work
References
Ensemble Learning Based Big Data Classification for Intrusion Detection
1 Introduction
2 Related Works
3 Existing Techniques
3.1 Classifications of an IDS for Network Analysis
3.2 Ensemble Learning
4 Proposed Techniques
4.1 Classification Using Big Data Techniques
4.2 Evaluation Method
5 Conclusion
References
Application of Combined SWOT and AHP Analysis to Assess the Virtual Reality and Select the Priority Factors for Education
1 Introduction
2 Related Works
2.1 Virtual Reality Technology
2.2 Virtual Reality in Education
3 Methodology
3.1 SWOT Analysis
3.2 AHP Approach
3.3 A'WOT Methodology
4 Results and Discussion
5 Conclusion
References
Prediction of Colon Cancer Related Tweets Using Deep Learning Models
1 Introduction
2 Related Work
3 The Proposed System
3.1 Data Collection and Preprocess Stage
3.2 Feature Extraction
3.3 Labeling
4 Results and Discussion
5 Comparison with Other Related Works
6 Conclusions
References
A Combinatorial Approach: Datamining and an Efficient Deep Neural Network for Heart Disease Prediction
1 Introduction
2 Related Work
3 Proposed Method
3.1 Preprocess the Data
3.2 Normalization and Split Data
3.3 Designing Neural Networks
4 Experiments and Results
4.1 Metrics
4.2 Dataset
4.3 Results
4.4 Comparative Study
5 Result Analysis and Discussion
6 Conclusion
7 Future Direction
References
High-Performance Computation in Big Data Analytics
1 Introduction
2 Characteristics of Big Data
3 Big Data and Cloud Computing
4 Big Data and Deep Learning
4.1 Semantic Indexing
4.2 Statistical Modelling
5 Challenges of Deep Learning in Big Data
5.1 Utilization of Incremental Learning Data that is not Stationary
5.2 High-Dimensional Data
5.3 Large Scale Models
5.4 Future of Deep Learning in Big Data
5.5 Application of Machine Learning Algorithm
6 Parallel Computation in Big Data
6.1 What is Parallel Computation?
6.2 Parallel Computation Models of Data Analysis
6.3 Hadoop MapReduce
7 Issues of Parallelism
7.1 Fault-Tolerance
7.2 Memory Model
7.3 Storage and I/O
8 Conclusion
References
Evaluation of Semantic Parsing Frameworks for Automated Knowledge Base Construction
1 Introduction
2 Related Works
3 Methodology
4 Semantic Representation Frameworks
4.1 Abstract Meaning Representations
4.2 Universal Conceptual Cognitive Annotation
4.3 Universal Dependencies
4.4 Elementary Dependency Structures
4.5 Prague Tectogrammatical Graphs
4.6 Discourse Representation Structures
4.7 Universal Decompositional Semantics
5 Results and Evaluation
5.1 Test Corpus
5.2 Frameworks, Tools, Models
5.3 Parse Output
5.4 Results and Evaluation
6 Discussion
7 Conclusions
References
Performing Systematic Review on Personalized Menu Scheduling Using PRISMA Guidelines
1 Introduction
2 Carrying Out the SLR on MPP
3 Planning the Review (Phase 1)
3.1 Research Key Terms: PICO Search Tool
3.2 Research Equation
3.3 Electronic Sources and Search Grid
4 Conducting the Review (Phase 2)
4.1 Study Selection
4.2 Data Extraction Strategy: PRISMA Flowchart
5 Reporting the Review (Phase 3)
5.1 Synthesis of Results (Meta-analysis)
5.2 Discussion
6 Conclusion
References
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Intelligent Systems Design and Applications

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