Proceedings of World Conference on Artificial Intelligence : Wcaiaa 2023

• Autore: Tripathi Ashish Kumar
• Pubblicazione: Singapore : , : Springer Singapore Pte. Limited, , 2023; ©2023
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (543 pages)
• Altri autori: AnandDarpan NagarAtulya K
• Nota di contenuto: Intro -- Preface -- Contents -- About the Editors -- 1 A Pragmatic Study of Machine Learning Models Used During Data Retrieval: An Empirical Perspective -- 1 Introduction -- 2 Literature Review -- 3 Pragmatic Analysis and Comparison -- 4 Conclusion and Future Scope -- References -- 2 Smart Knowledge Management for IT Services -- 1 Introduction -- 2 Literature Review -- 3 Objective -- 4 Methodology -- 4.1 Business Understanding -- 4.2 Problem Description -- 4.3 Proposed Solution -- 5 Data Understanding and Preparation -- 6 Data Modeling and Evaluation -- 6.1 Modeling -- 6.2 Evaluation -- 7 Deployment, Analysis, and Results -- 8 Conclusion and Future Scope -- References -- 3 Patient-Centric Electronic Health Records Management System Using Blockchain Based on Liquid Proof of Stake -- 1 Introduction -- 1.1 Blockchain -- 1.2 Cryptography -- 1.3 InterPlanetary File System (IPFS) -- 2 Literature Review -- 3 Proposed Model -- 4 Conclusion -- References -- 4 AI Driving Game Changing Trends in Project Delivery and Enterprise Performance -- 1 Introduction -- 2 Motivation of the Study -- 3 Organization Trends -- 4 Contribution of AI -- 5 Literature Review -- 6 Areas of Application of AI in Project Management -- 7 Conceptual Framework -- 8 Methodology -- 8.1 Hypothesis -- 8.2 Analysis and Discussion -- 8.3 Limitations of the Study -- 9 Impact on Project Managers -- 10 Conclusion -- References -- 5 Prediction of Children Age Range Based on Book Synopsis -- 1 Introduction -- 2 Review of Literature -- 3 Proposed System -- 3.1 Data Collection -- 3.2 Data Cleaning -- 3.3 Splitting of Dataset -- 3.4 Feature Extraction -- 3.5 Classification Models -- 4 Results -- 4.1 KNN -- 4.2 SVM -- 4.3 XGBoost -- 4.4 MLP -- 5 Conclusion and Future Recommendations -- References. ; 6 Predicting Credit Card Churn Using Support Vector Machine Tuned by Modified Reptile Search Algorithm -- 1 Introduction -- 2 Background and Related Works -- 2.1 Support Vector Machine (SVM) -- 2.2 Swarm Intelligence -- 3 Proposed Method -- 3.1 Original Reptile Search Algorithm -- 3.2 Modified RSA -- 4 Experiments and Discussion -- 4.1 Dataset Description -- 4.2 Experimental Setup and Solutions Encoding -- 4.3 Results and Discussion -- 5 Conclusion -- References -- 7 Comparison of Deep Learning Approaches for DNA-Binding Protein Classification Using CNN and Hybrid Models -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Classification Models -- 4 Result and Discussion -- 5 Conclusion -- References -- 8 Exploring Jaccard Similarity and Cosine Similarity for Developing an Assamese Question-Answering System -- 1 Introduction -- 2 Related Study -- 3 Background -- 3.1 Tokenization -- 3.2 Stop Word Removal -- 3.3 Cosine Similarity -- 3.4 Jaccard Similarity -- 4 Proposed Work -- 5 Pre-processing -- 6 Establishment of Relationship -- 6.1 Jaccard Similarity -- 6.2 Cosine Similarity -- 7 Experiments -- 7.1 Data Preparation -- 7.2 Experimental Setup -- 7.3 Result and Analysis -- 7.4 Comparison Between English Chatbot and AQAS -- 8 Conclusion and Future Work -- References -- 9 Artificial Neural Network Modelling for Simulating Catchment Runoff: A Case Study of East Melbourne -- 1 Introduction -- 2 Study Area -- 3 Methodology -- 3.1 Description of Datasets -- 3.2 Datasets Preprocessing -- 3.3 Data Normalisation -- 3.4 Development of ANN Model -- 4 Results and Discussion -- 5 Future Works -- 6 Conclusion -- References -- 10 Effective Decision Making Through Skyline Visuals -- 1 Introduction -- 2 Related Work -- 3 Visualizing the Skyline -- 3.1 Skyline Visuals -- 3.2 Creating the Skyline Visuals. ; 4 Conclusion and Future Scope -- References -- 11 A Review Paper on the Integration of Blockchain Technology with IoT -- 1 Introduction -- 2 Literature Review -- 3 Background -- 3.1 Internet of Things -- 3.2 Architecture of IoT -- 3.3 Applications of IoT -- 3.4 Security Aspects of IoT -- 3.5 Attacks and Vulnerabilities in IoT -- 4 Blockchain Technology -- 4.1 Types of Blockchain -- 4.2 Structure of Blockchain -- 5 Integration of Blockchain and IoT -- 5.1 Blockchain Solution to IoT -- 5.2 Blockchain Scalability to IoT -- 5.3 Security in Blockchain and IoT -- 5.4 A Comparative Study -- 6 Conclusion -- References -- 12 Survey and Analysis of Epidemic Diseases Using Regression Algorithms -- 1 Introduction -- 2 Literature Review -- 2.1 Dengue -- 2.2 Influenza -- 2.3 Malaria -- 2.4 COVID-19 -- 2.5 Impact of Dengue, Malaria, and Influenza on COVID-19 -- 3 Data and Methods -- 4 Conclusion and Future Work -- References -- 13 Hybrid Pre-trained CNN for Multi-classification of Rice Plants -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Dataset Description -- 3.2 Preprocessing -- 3.3 Classification -- 4 Results and Discussions -- 5 Conclusion -- References -- 14 Cauliflower Plant Disease Prediction Using Deep Learning Techniques -- 1 Introduction -- 2 Study on Plant Disease Prediction -- 3 Merits and Demerits of an Existing Method -- 4 Analysis and Performance Comparisons -- 5 Conclusion -- References -- 15 Disease Detection and Prediction in Plants Through Leaves Using Convolutional Neural Networks -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 4 Implementation -- 5 Experiments and Results -- 6 Conclusion -- References -- 16 Classification of Breast Cancer Using Machine Learning: An In-Depth Analysis -- 1 Introduction -- 2 Several Levels of Classification. ; 2.1 Data Acquisition: Techniques for the Accumulation of Information -- 2.2 Data Preprocessing or Image Preprocessing -- 2.3 Segmentation -- 3 Features Extraction and Selection -- 3.1 Features Selection -- 3.2 Classification Using Machine Learning Algorithms -- 4 Literature Review -- 5 Conclusion and Discussion -- References -- 17 Prediction of Age, Gender, and Ethnicity Using Haar Cascade Algorithm in Convolutional Neural Networks -- 1 Introduction -- 2 Method -- 2.1 VGG Model -- 2.2 CNN Model -- 3 Proposed System -- 3.1 Implementation -- 3.2 Preprocessing -- 3.3 System Architecture -- 4 Results and Discussion -- 4.1 Transfer Learning Using VGG Face Model -- 4.2 Three Convolution Layer Model -- 4.3 Four Convolution Layer Model -- 4.4 Five Convolution Layer Model -- 4.5 Output Images and Classification -- 5 Conclusion -- References -- 18 Augmentation of Green and Clean Environment by Employing Automated Solar Lawn Mower for Exquisite Garden Design -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Introduction -- 4 Components Used -- 5 Results and Discussion -- 5.1 Implementation Process -- 6 Results -- 6.1 Comparative Study -- 7 Conclusion and Recommendation -- 7.1 Conclusion -- 7.2 Future Scope -- References -- 19 A Lightweight Solution to Intrusion Detection and Non-intrusive Data Encryption -- 1 Introduction -- 2 Methodology -- 2.1 Proposed System -- 2.2 Used Dataset and Preprocessing -- 2.3 Feature Extraction -- 2.4 Model Training -- 2.5 ECC Encryption -- 3 Result Analysis -- 4 Conclusion -- References -- 20 Efficiency of Cellular Automata Filters for Noise Reduction in Digital Images -- 1 Introduction -- 2 Cellular Automata -- 3 Noise and Its Types -- 4 Noise Reduction Techniques -- 4.1 Linear and Nonlinear Filters -- 4.2 Cellular Automata-Based Noise Reduction Filters -- 5 Methodology for Output Image Analysis. ; 6 Result and Discussion -- 7 Conclusion -- References -- 21 Effective Mutants' Classification for Mutation Testing of Smart Contracts -- 1 Introduction -- 1.1 Organization of Paper -- 2 Background -- 2.1 Smart Contract Features -- 2.2 Software Testing and Mutation Testing -- 2.3 Smart Contract Testing -- 2.4 Prioritizing Mutants in Mutation Testing -- 3 Problem Statement -- 4 Proposed Methodology -- 4.1 Mutant Classification -- 4.2 Dataset -- 4.3 Machine Learning-Based Evaluation of the Utility of Mutants -- 4.4 Features Selection for Characterizing Mutants -- 5 Results and Discussion -- 5.1 Feature Importance -- 5.2 Machine Learning Approach -- 5.3 Classification Report -- 6 Conclusion -- References -- 22 Scheming of Silver Nickel Magnopsor for Magneto-Plasmonic (MP) Activity -- 1 Introduction -- 2 Design Logic of the Device -- 3 Results and Discussion -- 4 Conclusion -- 5 Competing Interests -- References -- 23 Heart Stroke Prediction Using Different Machine Learning Algorithms -- 1 Introduction -- 2 Methodology -- 2.1 Proposed Method for Prediction -- 2.2 Input Data -- 2.3 Data Pre-processing -- 2.4 Split Data -- 2.5 Train Data -- 2.6 Test Data -- 2.7 Algorithms -- 3 Result Analysis -- 3.1 Precision -- 3.2 Recall -- 3.3 F-Measure -- 3.4 Accuracy -- 4 Conclusion -- References -- 24 Credit Card Fraud Detection Using Hybrid Machine Learning Algorithm -- 1 Introduction -- 2 Problem Statement -- 3 Related Work -- 4 Material and Methods -- 4.1 Decision Tree Algorithm -- 4.2 Random Forest Algorithm -- 4.3 Honey Bee Algorithm -- 4.4 Synthetic Minority Oversampling Technique (SMOTE) -- 4.5 Confusion Matrix and Related Metrics -- 5 Proposed Model -- 5.1 Credit Card Fraud Detection Using Hybrid Machine Learning Algorithm -- 6 Results and Discussion -- 7 Conclusions and Future Work -- References. ; 25 Smart Air Pollution Monitoring System for Hospital Environment Using Wireless Sensor and LabVIEW.
• Titolo autorizzato: Proceedings of World Conference on Artificial Intelligence
• ISBN: 981-9958-81-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910760291403321
• Lo trovi qui: Univ. Federico II
• Serie: Algorithms for Intelligent Systems Series