Intelligent Systems and Machine Learning: First EAI International Conference, ICISML 2022, Hyderabad, India, December 16-17, 2022, Proceedings, Part ... and Telecommunications Engineering, 471)

This two-volume set constitutes the refereed proceedings of the First EAI International Conference on Intelligent Systems and Machine Learning, ICISML 2022, held in Hyderabad, India, in December 16-17,2022. The 75 full papers presented were carefully reviewed and selected from 209 submissions. The conference focuses on Intelligent Systems and Machine Learning Applications in Health care; Digital Forensic & Network Security; Intelligent Communication Wireless Networks; Internet of Things (IoT) Applications; Social Informatics; and Emerging Applications. Preface Conference Organization Contents – Part II Contents – Part I Emerging Applications A Model for Engineering, Procurement, and Construction (EPC) Organizations Using Vendor Performance Rating System 1 Introduction 2 Literature Review 3 Objectives of the Study 4 Research Methodology 5 Importance of Vender Management 6 Conclusion 7 Future Implications References F2PMSMD: Design of a Fusion Model to Identify Fake Profiles from Multimodal Social Media Datasets 1 Introduction 2 Related Work 3 Data Set Description 4 Design of the Proposed Fusion Model to Identify Fake Profiles from Multimodal Social Media Datasets 5 Results and Discussion 6 Conclusion and Future Scope References A Novel Model to Predict the Whack of Pandemics on the International Rankings of Academia 1 Introduction 2 Overview of the Related Work 3 Proposed Methodology and Design 3.1 Loading the Dataset 3.2 Splitting the Dataset 3.3 Data Pre-processing: Checking for Missing Data 3.4 Data Pre-processing: Data Normalization 3.5 Data Pre-processing: Handling Imbalanced Data 3.6 Deploying the Proposed Model 3.7 Make Predictions 3.8 Model Comparison with Other Models 3.9 Evaluate the Model 4 Empirical Setup with Implementation Details 5 Collating with State-of-Art 6 Deductions and Subsequent Work References Credit Risk Assessment - A Machine Learning Approach 1 Introduction 2 Understanding the Concept of Credit Risk and Machine Learning Algorithms 2.1 What is Credit Risk? 2.2 What is Machine Learning? 3 Literature Review 4 Research Problem or Gap 5 Objectives of Study 6 Research Methodology 7 Experimental results 8 Result Analysis 9 Conclusion References Development of Analytical DataMart and Data Pipeline for Recruitment Analytics 1 Introduction 1.1 Recruitment Process 2 Literate Review 2.1 HR DataMart by Ralph Kimball 2.2 HR DataMart by Oracle 3 Methodology 3.1 Load the Data 3.2 ETL and Finding Fact and Dimension Tables 3.3 Star Schema DataMart 3.4 Creating Analytical Dashboards 3.5 Model Building 3.6 Deployment 4 Results and Discussion 5 Conclusion and Future Scope References Data Homogeneity Dependent Topic Modeling for Information Retrieval 1 Introduction 2 Review of Related Literature 2.1 Prevalence of Topic Modeling in Scientific and Corporate Settings 2.2 Homogeneity and Heterogeneity 2.3 Preprocessing Techniques 2.4 Modeling Techniques 2.5 Evaluation Metrics 3 Experimental Setup 3.1 Data Source 3.2 Methodology 4 Results and Discussion 4.1 Outcome of Experiments 4.2 Recommended Data Homogeneity Dependent Topic Modeling Process 5 Conclusion References Pattern Discovery and Forecasting of Attrition Using Time Series Analysis 1 Introduction 2 Literature Review 3 Problem Statement 4 Methodology 4.1 Business Understanding 4.2 Data Understanding 4.3 Data Preparation 4.4 Modeling 4.5 Model Evaluation 5 Analysis and Results 6 Conclusions and Recommendations for Future Work References Resume Shortlisting and Ranking with Transformers 1 Introduction 2 State of Art 3 Problem Definition 4 Proposed Method 5 Modeling 6 Analysis and Results 7 Conclusion and Future Works References Hybrid Deep Learning Based Model on Sentiment Analysis of Peer Reviews on Scientific Papers 1 Introduction 2 Literature Review 3 Proposed Method 4 Methodology 4.1 Dataset Description 4.2 Pre-processing 4.3 Implementation 5 Results Analysis 6 Conclusion and Future Work References Artificial Intelligence Based Soilless Agriculture System Using Automatic Hydroponics Architecture 1 Introduction 2 Background of Hydroponics 2.1 Introduction to Hydroponics 2.2 Advantages of Hydroponics to Conventional Soil Agriculture 2.3 Types of Hydroponic Systems 3 Design Overview 3.1 Nutrient Film Technique 3.2 Nutrient Solution Mixture 3.3 Plant Reservoir 3.4 Submersible Pumps 3.5 EC Sensor 3.6 pH Sensor 3.7 Oxygenation of the Nutrient Solution 3.8 Air Pumps and Air Stones 4 Process Flow of the NFT System 4.1 Control Unit 4.2 Display Unit (16 × 2 LCD) 4.3 Mixture Types 4.4 Developed Software 4.5 Arduino Compiler 4.6 Proteus 8 Professional 4.7 Simulation 4.8 Brief on How the Simulation Works 5 Conclusion 6 Limitation and Recommendation References Mining Ancient Medicine Texts Towards an Ontology of Remedies – A Semi-automatic Approach 1 Introduction 2 Ontologies, Methodologies and Applications 3 Ontology Learning Processes 4 An Ontology for Ancient Remedies 4.1 The Application Case 4.2 Extracting the Ontology 5 Conclusions and Future Work References A Novel Oversampling Technique for Imbalanced Credit Scoring Datasets 1 Introduction 2 Literature Review 3 Proposed Model 3.1 Elimination of Noise Points from Minority Instances 3.2 Determine the Weights of the Informative Minority Instances 3.3 The Synthetic Instance Generation Phase 4 Experimental Study 4.1 Datasets 4.2 Experimental Design 5 Results Analysis 6 Conclusion and Future Work References A Blockchain Enabled Medical Tourism Ecosystem 1 Introduction 2 Literature Review 3 E-Healthcare or Telemedicine System 3.1 A. Significance of Cloud Computing in E-Healthcare 3.2 Significance of Machine Learning in E-Healthcare 4 Medical Tourism 5 Blockchain Technology Potentials in the Field of Medical Tourism 6 Digitalization and Interoperability Improvement 6.1 Electronic Health Records (EHRs) 6.2 Methods/Services Offered by Blockchain in Medical Tourism 7 Challenges 8 Conclusion References Measuring the Impact of Oil Revenues on Government Debt in Selected Countries by Using ARDL Model 1 Introduction 1.1 Theoretical Side 1.2 Practical Side 1.3 Econometric Side 1.4 Discussion 2 Conclusion 3 Recommendation Appendix (1) Appendix (2) Appendix (3) Appendix (4) Appendix (5) References Diagnosis of Plant Diseases by Image Processing Model for Sustainable Solutions 1 Introduction 2 Literature Survey 3 Proposed Model Architecture 3.1 System Architecture 3.2 Model Engine Architecture 4 Algorithm of the Model 5 Results and Discussion 6 Conclusion References Face Mask Detection: An Application of Artificial Intelligence 1 Introduction 2 Problem Identification 3 Working of Face Mask Detection 3.1 Gathering the Dataset 3.2 Processing the Data 3.3 Classification Using MobileNetV2 Architecture 4 Implementation and Result Discussion 4.1 Training and Testing the CNN Model 4.2 Making Predictions and Visualizing Results 4.3 Training Loss and Accuracy on Dataset 4.4 Predictions and Analyzing Accuracy 5 Conclusion and Future Enhancements References A Critical Review of Faults in Cloud Computing: Types, Detection, and Mitigation Schemes 1 Introduction 1.1 Taxonomy of Faults in CC 1.2 Fault Tolerance and Mitigation Techniques in CC 2 Literature Work 2.1 ML-Based Fault Detection Techniques for Fault Detection 2.2 Some Other Noteworthy Works 3 Conclusion References Video Content Analysis Using Deep Learning Methods 1 Introduction 2 Related Work 2.1 Review on Feature Extraction Techniques for Video Content Dataset 2.2 Reviews of Video Segmentation Methods 2.3 Reviews of Video Content Classification Algorithms 3 Experimental Results 3.1 Accuracy 3.2 Precision 3.3 Sensitivity 3.4 Specificity 3.5 False Discovery Rate 3.6 False Alarm Rate 4 Conclusion References Prediction of Cochlear Disorders Using Face Tilt Estimation and Audiology Data 1 Introduction 2 Background Study 3 Proposed Methodology 3.1 Data Preprocessing and Feature Engineering 3.2 Model Development 3.3 Face Tilt Value Collection 3.4 Deployment Procedure 4 Results and Discussion 5 Conclusion and Future Works References Quantum Data Management and Quantum Machine Learning for Data Management: State-of-the-Art and Open Challenges 1 Introduction 2 Quantum Data Management 2.1 Quantum Machine Learning 2.2 Quantum Computing for Data Management 2.3 Data Management for Quantum Computing 3 Summary and Conclusions References Multivariate Analysis and Comparison of Machine Learning Algorithms: A Case Study of Cereals of America 1 Introduction 2 Related Work 3 Methodology 3.1 Comparative Analysis 4 Results and Discussion 4.1 Data Analysis and Visualization 4.2 Comparative Analysis of Machine Learning Models 4.3 Challenges 5 Conclusion References Competitive Programming Vestige Using Machine Learning 1 Introduction 2 Related Work 3 Proposed Approach 3.1 Data Set 3.2 Preprocessing 3.3 Supervised Learning 4 Proposed Model 4.1 Experimental Setup 4.2 Proposed Algorithm 4.3 Proposed Model Objectives 4.4 Proposed Model Outcomes 5 Results and Discussion 6 Conclusions References Machine Learning Techniques for Aspect Analysis of Employee Attrition 1 Introduction 2 Related Work 3 Methodology 4 Result and Discussion 4.1 Aspect Analysis Using Visualization 4.2 Comparative Analysis of Various Machine Learning Models 5 Conclusion References AI-Enabled Automation Solution for Utilization Management in Healthcare Insurance 1 Introduction 2 Literature Review 3 Methodology 4 Software Design 5 Implementation 5.1 TF-IDF 5.2 Universal Sentence Encoder 6 Analysis and Results 6.1 TF-IDF 6.2 Universal Sentence Encoder 7 Conclusion References Real-Time Identification of Medical Equipment Using Deep CNN and Computer Vision 1 Introduction 2 Methodology 2.1 Data Collection 2.2 Training Data 2.3 Data Preprocessing 2.4 Compiling CNN 3 Results and Discussion 4 Conclusion References Design of a Intelligent Crutch Tool for Elders 1 Introduction 2 Literature Survey 3 Methodology 4 Result and Discussion 5 Conclusion References An Approach to New Technical Solutions in Resource Allocation Based on Artificial Intelligence 1 Introduction 2 System Model Resource Allocation in Heterogeneous Distributed Platforms 2.1 The Application 2.2 Wait–For–Graph (WFG) 2.3 The Algorithms Distributed System Resources Detection 2.4 Algorithmic Approach to Deadlock Detection 3 Our Algorithm to Prevention Deadlock 4 Experiments and Results 5 Conclusion References Gesture Controlled Power Window Using Deep Learning 1 Introduction 2 Related Works 3 Proposed Method 4 Methodology 4.1 Image Acquisition 4.2 Dataset Preparation 4.3 CNN Model Development 4.4 Python Arduino Interfacing 4.5 Testing and Validating 5 Result and Discussion 6 Conclusions and Future Scope References Novel Deep Learning Techniques to Design the Model and Predict Facial Expression, Gender, and Age Recognition 1 Introduction 1.1 Problem Definition 2 Literature Review 3 Methodology 3.1 Convolutional Neural Network 3.2 Haar Cascade Classifier 3.3 Model 3.4 Applications 4 Results 5 Conclusion and Futurework References A Comprehensive Review on Various Data Science Technologies Used for Enhancing the Quality of Education Systems 1 Introduction 2 Related Works 3 Data Science Methodologies 3.1 Data Mining Techniques used in Education System 3.2 Big Data Models 3.3 Data Warehousing Models 3.4 Business Intelligence Models 4 Results and Discussion 5 Conclusion References AI/ML Based Sensitive Data Discovery and Classification of Unstructured Data Sources 1 Introduction 1.1 Data Protection Laws and Regulations 1.2 Data Discovery and Classification 1.3 Data Protection Lifecycle 1.4 Types of Sensitive Data 2 Literature Review 3 Problem Statement 4 Proposed Solution 4.1 Detect Sensitive Elements 4.2 Rule Based Document Risk Categorization 4.3 Document Classification 4.4 Data Modelling Results 5 Conclusion and Future Scope References Bias Analysis in Stable Diffusion and MidJourney Models 1 Introduction 2 Overview of Bias Detection in Pre-trained Models 2.1 Where Does Bias Come From? 3 Previous Work 3.1 Reducing Bias in DALL-E 3.2 Detecting Bias in Pre-trained NLP Models 4 Results of Bias Analysis in Art Generating Models 4.1 Gender Bias Inequality 4.2 Racial Inequality 5 The Potential Impact of Applying Unfiltered Pre-trained Models 6 Potential Solutions 6.1 Fine-Tuning 6.2 Filtering 7 Conclusion and Future Work References Machine Learning Based Spectrum Sensing for Secure Data Transmission Using Cuckoo Search Optimization 1 Introduction 2 Design Methodology 2.1 Support Vector Machines 2.2 K-Nearest Neighbors (KNN) 2.3 Cuckoo Search Optimization Algorithm (CSO) 3 Results and Conclusions References Author Index