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Artificial Intelligence : Proceedings of AITA 2023, Volume 2
| Artificial Intelligence : Proceedings of AITA 2023, Volume 2 |
| Autore | Sharma Harish |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (531 pages) |
| Altri autori (Persone) |
ChakravortyAntorweep
HussainShahid KumariRajani |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9984-79-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| 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. |
| Record Nr. | UNINA-9910799221503321 |
Sharma Harish
|
||
| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence : Proceedings of AITA 2023, Volume 1
| Artificial Intelligence : Proceedings of AITA 2023, Volume 1 |
| Autore | Sharma Harish |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (495 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ChakravortyAntorweep
HussainShahid KumariRajani |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9984-76-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Control Techniques for Vision-Based Autonomous Vehicles for Agricultural Applications: A Meta-analytic Review -- 1 Introduction -- 2 State-of-The Art Studies -- 2.1 Target Detection in Autonomous Vehicle System -- 2.2 Vision-Based System -- 3 Mathematical Modeling of Autonomous System -- 4 Conclusion -- References -- Co-GA: A Bio-inspired Semi-supervised Framework for Fake News Detection on Scarcely Labeled Data -- 1 Introduction -- 2 Related Work -- 2.1 Supervised Fake News Detection Using Linguistic Content -- 2.2 Semi-supervised Fake News Detection Using Linguistic Content -- 2.3 Metaheuristics-Based Approaches for Feature Selection -- 2.4 Metaheuristics-Based Fake News Detection -- 3 Data -- 4 Proposed Methodology -- 4.1 Pre-processing -- 4.2 Feature Extraction -- 4.3 Bio-inspired Feature Selection -- 4.4 Multi-view Co-training Model -- 5 Results and Analysis -- 6 Future Research Directions -- 7 Conclusion -- References -- Kernel Methods for Conformal Prediction to Detect Botnets -- 1 Introduction -- 2 Related Works -- 2.1 Signature-Based and Heuristic-Based Botnet Detection -- 2.2 Machine Learning for Botnet Detection -- 2.3 Kernel Methods -- 2.4 Conformal Prediction -- 2.5 Deep Learning and Graph-Based Approaches -- 2.6 Challenges and Limitations -- 2.7 Motivation for the Proposed Approach -- 2.8 Emerging Trends and Research Directions -- 3 Methodology -- 3.1 Kernel Methods -- 3.2 Conformal Prediction -- 3.3 Proposed Approach: Kernel Methods for Conformal Prediction -- 3.4 Evaluation Metrics -- 3.5 Experimental Setup -- 4 Results -- 4.1 Dataset Description -- 4.2 Experimental Setup -- 4.3 Experimental Results -- 4.4 Analysis of Results -- 5 Conclusion -- References -- Biogas Generation from Animal Waste: A Case Study of Village Wazirpur -- 1 Introduction.
2 Biogas Production from Animal Waste -- 2.1 Factors Affecting Biogas Production -- 2.2 Sensors for Determining the Parameters Affecting Biogas Production -- 3 Area Under Study -- 4 Cost Analysis and Electricity Production -- 5 Conclusion -- References -- Volume of Imbalance Container Prediction using Kalman Filter and Long Short-Term Memory -- 1 Introduction -- 2 Problem Statement -- 3 Research Questions -- 4 KALSTM: A Hybrid Model -- 5 Results and Limitations -- 6 Conclusion -- References -- Modelling Stock Prices Prediction with Long Short-Term Memory (LSTM): A Black Box Approach -- 1 Introduction -- 2 Methodology Based on LSTM -- 3 Description of Datasets -- 4 Results and Discussions -- 5 Conclusion and Future Work -- References -- Agricultural Crop Yield Prediction for Indian Farmers Using Machine Learning -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Dataset -- 3.2 Methodology -- 4 Architecture -- 5 Result Analysis -- 6 Conclusion -- References -- Application of Artificial Intelligence on Camera-Based Human Pose Prediction for Yoga: A Methodological Study -- 1 Introduction -- 1.1 Scope -- 1.2 Challenges -- 1.3 Impact of Yoga [1] -- 2 Literature Review -- 3 Methodology -- 3.1 Research Process -- 3.2 Key Point Detection Methods -- 3.3 Implementation Methodology [12, 13] -- 4 Datasets and Metrics -- 5 Results -- 6 Conclusion -- 7 Future Potential Development -- References -- Predicting of Credit Risk Using Machine Learning Algorithms -- 1 Introduction -- 2 Review of Literature -- 2.1 Machine Learning Algorithms -- 2.2 Development of Credit Risk Model -- 3 Data and Methodology -- 3.1 Data -- 3.2 Variables -- 3.3 Machine Learning Models and Evaluation Parameters -- 3.4 Evaluation Parameters -- 3.5 Methodology -- 4 Empirical Findings -- 5 Conclusions and Implications -- References -- Study of Various Text Summarization Methods. 1 Introduction -- 2 Literature Review -- 3 Overview of Proposed Model -- 3.1 Proposed Methodology -- 3.2 Design of Model Architecture -- 3.3 Model Evaluation -- 4 Results -- 5 Conclusion -- References -- Investigations on Deep Learning Pre-trained Model VGG-19 Using Transfer Learning for Remote Sensing Image Classification on Benchmark Datasets -- 1 Introduction -- 2 Literature Review -- 3 Comparison of Performance Metrics of Machine Learning Methods on the PatterNet Dataset -- 4 Utilizing Pre-trained Models for Transfer Learning -- 5 Transfer Learning with Pre-trained Models Based on the Baseline ImageNet Dataset -- 6 Overview of VGG-19 -- 7 Enabling Efficient Feature Reuse and Information Flow in Deep Neural Networks for Superior Performance -- 8 Deep Learning Surpassing Traditional Machine Learning Techniques -- 9 Setting Up Experiments: Feature Extraction and Classification for Remote Sensing Images with a Pre-trained VGG-19 Model -- 9.1 Dataset Description -- 9.2 Assessment Metrics Utilized for Model Evaluation in Image Classification and Retrieval -- 9.3 Research Findings: Investigating Test Accuracy and Test Loss Scores on Benchmark Datasets Using VGG-19 Pre-trained Model -- 10 Summarizing the Feature Extraction with Transfer Learning Approach in Deep Learning -- References -- Complexity Analysis of Legal Documents -- 1 Introduction -- 2 Related Works -- 2.1 NER for Indian Legal Documents -- 2.2 Information Extraction -- 2.3 Summarising in Legal Domain -- 2.4 Complexity of Legal Documents -- 3 Methodology -- 3.1 Proposed Model -- 3.2 Analysis of Complexity -- 4 Result Analysis -- 5 Conclusion and Future Works -- References -- Predicting Virality of Tweets Using ML Algorithms and Analyzing Key Determinants of Viral Tweets -- 1 Introduction -- 2 Theoretical Background and Related Work -- 3 Methodology -- 4 Results and Discussion. 5 Conclusion, Limitations, and Future Scope -- References -- Review of Classification and Detection for Insects/Pests Using Machine Learning and Deep Learning Approach -- 1 Introduction -- 1.1 Pictorial Representation of Classification and Detection of Pests and Comparison Between ML and DL -- 2 Material -- 2.1 Dataset Collection -- 3 Literature Work -- 3.1 Review of Different Machine Learning and Deep Learning Techniques for the Classification of Pests -- 4 Conclusion -- References -- Sentiment Analysis of Product Reviews Using Deep Learning and Transformer Models: A Comparative Study -- 1 Introduction -- 2 Literature Review -- 3 Sentiment Analysis -- 3.1 Sentiment Analysis Based on Machine Learning -- 3.2 Sentiment Analysis Based on Deep Learning -- 3.3 Sentiment Analysis Based on Transformer-Based Models -- 4 Implementation -- 4.1 Dataset -- 4.2 Data Pre-processing -- 4.3 Classification Models -- 5 Results and Discussions -- 5.1 Hyper Parameters Used -- 5.2 Performance Evaluation -- 6 Conclusion -- References -- Effect of Variation in Pause Times Over MANET Routing Protocols -- 1 Introduction -- 2 MANET Routing Protocols and Literature Review -- 3 Environment Setup -- 4 Performance Metrics -- 5 Conclusions and Future Scope -- References -- DDCMR2: A Deep Detection and Classification Model with Resizing and Rescaling for Plant Disease -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology and Implementation -- 3.1 Data Collection -- 3.2 Data Cleaning, Preprocessing, and Visualization -- 3.3 Cache, Shuffle, and Prefetch -- 3.4 Model Building -- 3.5 Hyperparameters Choice -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Leveraging Natural Language Queries for Effective Video Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology and Models -- 3.1 Uni-Modal Encoder -- 3.2 Cross-Modal Encoder. 3.3 Query Generator -- 3.4 Query Decoder -- 4 Experimental Analysis and Outcomes -- 5 Conclusion -- References -- An Experimental Study to Perform Bioinformatics Based on Heart Disease Case Study Using Supervised Machine Learning -- 1 Introduction -- 2 Preliminaries -- 2.1 Machine Learning -- 2.2 Logistic Regression -- 2.3 Decision Tree -- 2.4 Support Vector Machine -- 3 Experimentation -- 3.1 Data Provenance -- 3.2 Flow Diagram of This Study -- 3.3 Correlation Matrix -- 3.4 Logistic Regression -- 3.5 Support Vector Machine (SVM) -- 3.6 Decision Tree -- 4 Results and Analysis -- 5 Conclusion -- References -- Empirical Analysis of Denoising Algorithms for CCTV Face Images -- 1 Introduction -- 2 Related Work -- 3 BM3D (Block-Matching and 3D Filtering) -- 3.1 Collaborative Filtering: It Takes Four Steps -- 3.2 Aggregation -- 3.3 Wiener Filtering Step -- 4 KSVD (k-Singular Value Decomposition) -- 5 WNNM (Weighted Nuclear Norm Minimization) -- 6 Results and Discussion -- 7 Conclusion -- References -- Content-Based Tagging and Recommendation System for Tamil Songs Based on Text and Audio Input -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Music Segmentation -- 3.2 Instrument Recognition -- 3.3 Lyric Collection and Translation -- 3.4 Lyric Tagging -- 3.5 Audio Prompt -- 3.6 Similarity-Based Retrieval -- 4 Datasets -- 4.1 MUSDB18 Dataset -- 4.2 Tamil Songs -- 4.3 AudioSet -- 5 Outcomes -- 5.1 Metrics for Evaluation -- 5.2 Summary of Metrics -- 6 Conclusions and Future Work -- References -- Multimodal Face and Ear Recognition Using Feature Level and Score Level Fusion Approach -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Preprocessing -- 3.2 Feature Extraction (BSIF) -- 3.3 Feature Level Fusion -- 3.4 Score Level Fusion -- 4 Experimental Results and Discussion -- 4.1 GTAV Dataset. 4.2 FEI Face Database. |
| Record Nr. | UNINA-9910841868303321 |
|
Sharma Harish
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||