Artificial Intelligence : Proceedings of AITA 2023, Volume 2

• Autore: Sharma Harish
• Pubblicazione: Singapore : , : Springer Singapore Pte. Limited, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (531 pages)
• Altri autori: ChakravortyAntorweep HussainShahid KumariRajani
• Nota di contenuto: Intro -- Preface -- Contents -- Editors and Contributors -- Spam Email Image Detection Using Convolution Neural Network and Convolutional Block Attention Module -- 1 Introduction -- 2 Related Works -- 3 Convolution Neural Network -- 4 Convolutional Block Attention Model -- 5 Experimental Result -- 5.1 Dataset -- 5.2 Evaluation Metrics -- 5.3 Discussion -- 6 Conclusion -- References -- Identifying Fake Twitter Trends with Deep Learning -- 1 Introduction -- 2 Related Work -- 2.1 PolitiFact Dataset -- 2.2 PHEME Dataset -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Modeling -- 3.4 Experiments -- 4 Results and Analysis -- 5 Conclusion and Future Work -- References -- An Intelligent Agent Framework for Resilient Deployment in the Internet of Things Environment -- 1 Introduction -- 2 Intelligent Agent Framework -- 3 Proposed Deployment Algorithm -- 4 Results and Discussion -- 5 Conclusions -- References -- The Impact of Financial Ratios and Pandemic on Firm Performance: An Indian Economic Study -- 1 Introduction -- 2 Literature Review and Hypotheses Development -- 2.1 Debt and Firm Performance -- 2.2 Working Capital and Firm Performance -- 2.3 Financial Autonomy and Firm Performance -- 2.4 Quick Ratio and Firm Performance -- 3 Sample -- 4 Research Methodology -- 5 Results -- 5.1 Trend Analysis -- 5.2 Regression Results -- 6 Conclusion -- References -- An Enhanced BERT Model for Depression Detection on Social Media Posts -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Enhanced BERT Classical -- 4 Results and Discussion -- 4.1 Dataset -- 4.2 Comparison with the Existing System -- 5 Conclusion -- References -- Quality Prediction of a Stack Overflow Question Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Techniques -- 3.1 Naïve Bayes (NB) -- 3.2 Support Vector Classifier (SVC). ; 3.3 Decision Tree (DT) -- 3.4 Logistic Regression (LR) -- 3.5 K-Nearest Neighbors (KNN) -- 3.6 Random Forest (RF) -- 3.7 Natural Language Processing (NLP) -- 3.8 Bag of Words (BoW) -- 3.9 Word Cloud Analysis -- 4 Proposed Methodology and Implementation -- 4.1 Importing Libraries -- 4.2 Description of Dataset -- 4.3 Cleaning Textual Data -- 4.4 Tokenization, Lemmatization, and PoS Tagging -- 4.5 Lexicon-Based Sentiment Analysis -- 4.6 Word Embedding -- 4.7 Splitting the Dataset -- 4.8 Model Building and Performance Evaluation -- 5 Experimental Results and Analysis -- 6 Conclusion -- References -- Decision-Making Framework for Supplier Selection Using an Integrated Approach of Dempster-Shafer Theory and Maximum Entropy Principle -- 1 Introduction -- 2 Preliminaries -- 2.1 Dempster-Shafer Evidence Theory -- 2.2 Cobb-Douglas Utility Function -- 2.3 Maximum Entropy Method -- 3 Proposed Methodology -- 3.1 Evaluate Criteria Weights -- 3.2 Evaluate Alternative Ranking -- 4 Numerical Example -- 4.1 Problem Description -- 4.2 Evaluation of Criteria Weights -- 4.3 Ranking of Alternatives -- 5 Comparative Analysis and Discussions -- 5.1 Comparative Analysis of Weight Determination Method -- 5.2 Comparative Analysis of Ranking Method -- 6 Sensitivity Analysis -- 7 Conclusions -- References -- Improved Accuracy of Robotic Arm Using Virtual Environment -- 1 Introduction -- 2 Literature Review and Related Work -- 3 Proposed Method, Tools, and Techniques Used -- 3.1 Forward Kinematics -- 3.2 Inverse Kinematics -- 3.3 Technique -- 4 Methodology -- 4.1 Design of the Robotic Arm -- 4.2 Addition of Revolute Joints -- 4.3 Importing the Model to MATLAB -- 4.4 Defining the Robot Environment -- 4.5 Defining the Desired Trajectory -- 4.6 Working of Inverse Kinematic Block -- 4.7 Working of Forward Kinematic Block -- 4.8 Data Collection and Analysis -- 5 Result -- 6 Conclusion. ; References -- Human Activity Recognition a Comparison Between Residual Neural Network and Recurrent Neural Network -- 1 Introduction -- 2 HAR Using ResNet50 -- 3 HAR Using RNN -- 4 Conclusion -- References -- Using AI Planning to Automate Cloud Infrastructure -- 1 Introduction -- 2 Related Work -- 2.1 Cloud Infrastructure -- 2.2 Prototype Model -- 3 Problem Formulation -- 4 Proposed Solution -- 5 Testing and Result Evaluations -- 5.1 Test Case 1: Empty Environment -- 5.2 Test Case 2: No Application Module -- 5.3 Test Case 3: Neither the Database nor the Application Module -- 5.4 Test Case 4: Inconsistent Database -- 5.5 Test Case 5: Application Module in Unhealthy Status -- 5.6 Test Case 6: Application Out of Capacity -- 6 Conclusions and Future Scope -- References -- Using Historical Trip Information to Determine the Waiting Time Required for Taxi Services -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Proposed Solution: Design and Implementation -- 5 Results' Evaluation -- 6 Conclusions and Future Scope -- References -- The Impact of Cesarean Section Trends and Associated Complications in the Current World: A Comprehensive Analysis Using Machine Learning Techniques -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Decision Tree (DT) -- 3.2 Random Forest (RF) -- 3.3 K-Nearest Neighbour (KNN) -- 3.4 Support Vector Machine (SVM) -- 3.5 AdaBoost (AB) -- 4 Results -- 4.1 Decision Tree -- 4.2 Random Forest -- 4.3 K-Nearest Neighbour -- 4.4 Support Vector Machine -- 4.5 AdaBoost -- 5 Conclusion -- References -- Novel Hybrid Methods for Journal Article Summarization Combining Graph Method and Rough Set TFIDF Method with Pegasus Model -- 1 Introduction -- 2 Related Works and Summarization Datasets -- 3 Motivation and Challenges in Article Summarization -- 4 Methodology -- 4.1 Extractive Summarization Methods. ; 4.2 Abstractive Summarization Methods -- 4.3 Hybrid Summarization Methods -- 5 Results and Discussion -- 5.1 Rouge Score for Word Overlap over Annotated Summary -- 5.2 BERT Score for Similarity Score -- 6 Conclusion and Future Scope -- References -- Differential Evolution Wrapper-Based Feature Selection Method for Stroke Prediction -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Proposed System -- 4 Result Analysis -- 5 Discussion -- 6 Conclusion -- References -- Parkinson's Disease Identification from Speech Signals Using Machine Learning Models -- 1 Introduction -- 2 Literature Review -- 2.1 Machine Learning and Neural Network Techniques for PD Classification -- 2.2 Hybrid Models with Machine Learning Techniques and Neural Network -- 3 System Architecture -- 3.1 Dataset Details -- 3.2 Proposed Approach -- 4 Results and Discussions -- 4.1 Performance Matrices -- 4.2 Experimental Analysis -- 5 Conclusion -- References -- Performance Analysis of Deep CNN, YOLO, and LeNet for Handwritten Digit Classification -- 1 Introduction -- 2 Literature Review -- 3 Objective, Motivation and Challenges -- 4 Methodology -- 4.1 Dataset Description -- 5 Implementation -- 5.1 Convolution Neural Network -- 5.2 Convolutional Layer -- 5.3 Pooling Layer -- 5.4 Fully Connected Layer -- 5.5 Creating a CNN Model -- 5.6 You Only Look Once (YOLO) -- 5.7 LeNet -- 6 Result and Discussion -- 7 Conclusions -- References -- Data-Driven Decision Support Systems in E-Governance: Leveraging AI for Policymaking -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Research Objectives -- 3.2 Research Methodology -- 3.3 Proposed Contributions -- 4 Experimental Results -- 4.1 Accuracy -- 4.2 Precision -- 4.3 Recall (Sensitivity) -- 4.4 F1 Score -- 4.5 Mean Absolute Error (MAE) -- 4.6 Root Mean Square Error (RMSE) -- 5 Conclusions. ; References -- The Infrastructure Development of Contemporary Medical Devices Based on Internet of Things Technology -- 1 Introduction -- 2 IoT Infrastructure in Health Care -- 3 IoT Wireless Standards -- 4 IoT Network Architecture -- 4.1 Availability -- 4.2 Scalability -- 4.3 Network Performance -- 4.4 Manageability -- 4.5 Affordability -- 4.6 Adaptability -- 4.7 Usability -- 5 Cloud Computing in IoT -- 6 Contemporary Applications of IoT -- 6.1 Smart IoT Sensors -- 6.2 Smart Pill Containers -- 6.3 Smart Hospital Beds -- 6.4 Temperature Sensors -- 6.5 Wearable Devices -- 6.6 Future of IoT Medical Instruments -- 7 Conclusions -- References -- Business Intelligence System Adoption Project in the Area of Investments in Financial Assets -- 1 Introduction -- 2 Understanding the Significance and Functionality of Business Intelligence Systems -- 3 Review of Business Intelligence Literature -- 4 Traditional Information Systems on Investments in Financial Assets -- 5 Business Intelligence for Investments in Financial Assets-The Case of an IT Industry Organization -- 5.1 Preliminary Information -- 5.2 Original Business Intelligence System Employed in the Organization -- 6 Conclusions -- References -- Feature Selection Techniques to Enhance Prediction of Clinical Appointment No-Shows Using Neural Network -- 1 Introduction -- 2 Related Studies -- 3 Model Development -- 4 Analysis of Performance Measures -- 5 Conclusion -- References -- A Simple Recommendation Model Using the Item's Global Popularity and Frequency-Based User Preference -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Formalizations -- 3.2 Model -- 4 Experimental Results -- 5 Conclusion -- References -- An Early Detection of Autism Spectrum Disorder Using PDNN and ABIDE I& -- II Dataset -- 1 Introduction. ; 2 The Next Step in Comprehending the Brain and Psychiatric Diseases is Machine Learning, Deep Learning, and Predicting Disease States.
• Titolo autorizzato: Artificial Intelligence
• ISBN: 981-9984-79-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910799221503321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Networks and Systems Series