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[null,null,"Titolo",null,"Artificial Intelligence: Theory and Applications : Proceedings of AITA 2023, Volume 2 / / edited by Harish Sharma, Antorweep Chakravorty, Shahid Hussain, Rajani Kumari"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"981-9984-79-3"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (531 pages)"]
[null,null,"Collana",null,"Lecture Notes in Networks and Systems, , 2367-3389 ; ; 844"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Big Data"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Contents -- Editors and Contributors -- Spam Email Image Detection Using Convolution Neural Network and Convolutional Block Attention Module -- 1 Introduction -- 2 Related Works -- 3 Convolution Neural Network -- 4 Convolutional Block Attention Model -- 5 Experimental Result -- 5.1 Dataset -- 5.2 Evaluation Metrics -- 5.3 Discussion -- 6 Conclusion -- References -- Identifying Fake Twitter Trends with Deep Learning -- 1 Introduction -- 2 Related Work -- 2.1 PolitiFact Dataset -- 2.2 PHEME Dataset -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Modeling -- 3.4 Experiments -- 4 Results and Analysis -- 5 Conclusion and Future Work -- References -- An Intelligent Agent Framework for Resilient Deployment in the Internet of Things Environment -- 1 Introduction -- 2 Intelligent Agent Framework -- 3 Proposed Deployment Algorithm -- 4 Results and Discussion -- 5 Conclusions -- References -- The Impact of Financial Ratios and Pandemic on Firm Performance: An Indian Economic Study -- 1 Introduction -- 2 Literature Review and Hypotheses Development -- 2.1 Debt and Firm Performance -- 2.2 Working Capital and Firm Performance -- 2.3 Financial Autonomy and Firm Performance -- 2.4 Quick Ratio and Firm Performance -- 3 Sample -- 4 Research Methodology -- 5 Results -- 5.1 Trend Analysis "]
[{"$nulls":4},"-- 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)."]
[{"$nulls":4},"3.3 Decision Tree (DT) -- 3.4 Logistic Regression (LR) -- 3.5 K-Nearest Neighbors (KNN) -- 3.6 Random Forest (RF) -- 3.7 Natural Language Processing (NLP) -- 3.8 Bag of Words (BoW) -- 3.9 Word Cloud Analysis -- 4 Proposed Methodology and Implementation -- 4.1 Importing Libraries -- 4.2 Description of Dataset -- 4.3 Cleaning Textual Data -- 4.4 Tokenization, Lemmatization, and PoS Tagging -- 4.5 Lexicon-Based Sentiment Analysis -- 4.6 Word Embedding -- 4.7 Splitting the Dataset -- 4.8 Model Building and Performance Evaluation -- 5 Experimental Results and Analysis -- 6 Conclusion -- References -- Decision-Making Framework for Supplier Selection Using an Integrated Approach of Dempster-Shafer Theory and Maximum Entropy Principle -- 1 Introduction -- 2 Preliminaries -- 2.1 Dempster-Shafer Evidence Theory -- 2.2 Cobb-Douglas Utility Function -- 2.3 Maximum Entropy Method -- 3 Proposed Methodology -- 3.1 Evaluate Criteria Weights -- 3.2 Evaluate Alternative Ranking -- 4 Numerical Example -- 4.1 Problem Description -- 4.2 Evaluation of Criteria Weights -- 4.3 Ranking of Alternatives -- 5 Comparative Analysis and Discussions -- 5.1 Comparative Analysis of Weight Determination Method -- 5.2 Comparative Analysis of Ranking Method -- 6 Sensitivity Analysis -- 7 Conclusions -- References -- Improved Accuracy of Robotic Arm Using Virtual Environment -- 1 Introduction -- 2 Literature Review and Related Work -- 3 Proposed Method, Tools, and Techniques Used -- 3.1 Forward Kinematics -- 3.2 Inverse Kinematics -- 3.3 Technique -- 4 Methodology -- 4.1 Design of the Robotic Arm -- 4.2 Addition of Revolute Joints -- 4.3 Importing the Model to MATLAB -- 4.4 Defining the Robot Environment -- 4.5 Defining the Desired Trajectory -- 4.6 Working of Inverse Kinematic Block -- 4.7 Working of Forward Kinematic Block -- 4.8 Data Collection and Analysis -- 5 Result -- 6 Conclusion."]
[{"$nulls":4},"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 "]
[{"$nulls":4},"(RF) -- 3.3 K-Nearest Neighbour (KNN) -- 3.4 Support Vector Machine (SVM) -- 3.5 AdaBoost (AB) -- 4 Results -- 4.1 Decision Tree -- 4.2 Random Forest -- 4.3 K-Nearest Neighbour -- 4.4 Support Vector Machine -- 4.5 AdaBoost -- 5 Conclusion -- References -- Novel Hybrid Methods for Journal Article Summarization Combining Graph Method and Rough Set TFIDF Method with Pegasus Model -- 1 Introduction -- 2 Related Works and Summarization Datasets -- 3 Motivation and Challenges in Article Summarization -- 4 Methodology -- 4.1 Extractive Summarization Methods."]
[{"$nulls":4},"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."]
[{"$nulls":4},"References -- The Infrastructure Development of Contemporary Medical Devices Based on Internet of Things Technology -- 1 Introduction -- 2 IoT Infrastructure in Health Care -- 3 IoT Wireless Standards -- 4 IoT Network Architecture -- 4.1 Availability -- 4.2 Scalability -- 4.3 Network Performance -- 4.4 Manageability -- 4.5 Affordability -- 4.6 Adaptability -- 4.7 Usability -- 5 Cloud Computing in IoT -- 6 Contemporary Applications of IoT -- 6.1 Smart IoT Sensors -- 6.2 Smart Pill Containers -- 6.3 Smart Hospital Beds -- 6.4 Temperature Sensors -- 6.5 Wearable Devices -- 6.6 Future of IoT Medical Instruments -- 7 Conclusions -- References -- Business Intelligence System Adoption Project in the Area of Investments in Financial Assets -- 1 Introduction -- 2 Understanding the Significance and Functionality of Business Intelligence Systems -- 3 Review of Business Intelligence Literature -- 4 Traditional Information Systems on Investments in Financial Assets -- 5 Business Intelligence for Investments in Financial Assets-The Case of an IT Industry Organization -- 5.1 Preliminary Information -- 5.2 Original Business Intelligence System Employed in the Organization -- 6 Conclusions -- References -- Feature Selection Techniques to Enhance Prediction of Clinical Appointment No-Shows Using Neural Network -- 1 "]
[{"$nulls":4},"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&amp -- II Dataset -- 1 Introduction."]
[{"$nulls":4},"2 The Next Step in Comprehending the Brain and Psychiatric Diseases is Machine Learning, Deep Learning, and Predicting Disease States."]
[null,null,null,"Sommario/riassunto","This book features a collection of high-quality research papers presented at International Conference on Artificial Intelligence: Theory and Applications (AITA 2023), held during 11–12 August 2023 in Bengaluru, India. The book is divided into two volumes and presents original research and review papers related to artificial intelligence and its applications in various domains including health care, finance, transportation, education, and many more."]