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Proceedings of World Conference on Artificial Intelligence : Wcaiaa 2023
Proceedings of World Conference on Artificial Intelligence : Wcaiaa 2023
Autore Tripathi Ashish Kumar
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2023
Descrizione fisica 1 online resource (543 pages)
Altri autori (Persone) AnandDarpan
NagarAtulya K
Collana Algorithms for Intelligent Systems Series
Soggetto topico Artificial intelligence
Machine learning
ISBN 9789819958818
9819958814
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNINA-9910760291403321
Tripathi Ashish Kumar  
Singapore : , : Springer Singapore Pte. Limited, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Proceedings of World Conference on Artificial Intelligence: Advances and Applications : WCAIAA 2024 / / edited by Ashish Kumar Tripathi, Darpan Anand, Atulya K. Nagar
Proceedings of World Conference on Artificial Intelligence: Advances and Applications : WCAIAA 2024 / / edited by Ashish Kumar Tripathi, Darpan Anand, Atulya K. Nagar
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (469 pages)
Disciplina 006.3
Collana Algorithms for Intelligent Systems
Soggetto topico Computational intelligence
Artificial intelligence
Natural language processing (Computer science)
Data mining
Computational Intelligence
Artificial Intelligence
Natural Language Processing (NLP)
Data Mining and Knowledge Discovery
ISBN 981-9744-96-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1: A Novel Meta-Analysis and Classification of Herbal Medicinal Plant Raw Materials for Food Consumption Prediction Using Hybrid Deep Learning Techniques Based on Augmented Reality in Computer Vision -- Chapter 2: SoWhat: Real-Time Crop and Fertilizer Predictor -- Chapter 3: Access Control in IoT: A Comprehensive Survey of Challenges, Approaches, and Future Directions -- Chapter 4: Unveiling the Influential Dynamics: Personal Innova-tion and Word of Mouth in Shaping Online Pharmacy Adoption -- Chapter 5: A Novel Method of Enhancing Skin Lesion Diagnosis Using Attention Mechanisms and Weakly-Supervised Learning -- Chapter 6: Fully Homomorphic Encryption for Embedded Systems: IP Core Design and Implementation -- Chapter 7: Financial Time Series Forecasting Using Hybrid Evolutionary Extreme Learning Machine -- Chapter 8: Enhancing Childbirth Delivery Mode Prediction: A Machine Learning Hybrid Ensemble Approach -- Chapter 9: Exploring the Efficiency of Vedic Mathematics on FPGA and ASIC: A Performance Analysis -- Chapter 10: A Novel Approach For Energy Efficient Clustering Using NWOT-TCHE For Trust Based Cluster Head Election In Wireless Sensor Networks. etc.
Record Nr. UNINA-9910890186803321
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui