Proceedings of Data Analytics and Management : ICDAM 2023, Volume 4

• Autore: Swaroop Abhishek
• Pubblicazione: Singapore : , : Springer Singapore Pte. Limited, , 2024; ©2023
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (550 pages)
• Disciplina: 005.7565
• Altri autori: PolkowskiZdzislaw CorreiaSérgio Duarte VirdeeBal
• Nota di contenuto: Intro -- ICDAM 2023 Steering Committee Members -- Preface -- Contents -- Editors and Contributors -- Deep Spectral Feature Representations Via Attention-Based Neural Network Architectures for Accented Malayalam Speech-A Low-Resourced Language -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Accented Model Construction -- 3.4 Conclusion -- References -- Improving Tree-Based Convolutional Neural Network Model for Image Classification -- 1 Introduction -- 1.1 Contribution of the Research Work -- 2 Literature Review -- 2.1 Previous Work -- 2.2 Contribution -- 3 Methodology -- 3.1 Overview -- 3.2 Dataset -- 3.3 1D Convolutions and Strides -- 3.4 Removal of Max Pooling -- 3.5 Leaky ReLU -- 3.6 Model Architecture -- 4 Results and Conclusion -- References -- Smartphone Malware Detection Based on Enhanced Correlation-Based Feature Selection on Permissions -- 1 Introduction -- 1.1 Motivation -- 1.2 Contributions -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Datasets -- 3.2 Feature Extraction -- 3.3 Feature-Feature Correlation with ENMRS -- 3.4 Feature-Class Correlation Measure: crRelevance -- 3.5 Proposed Feature Selection Technique: ECFS -- 3.6 Machine Learning Techniques Used -- 4 Results and Discussion -- 4.1 n 1 equals 0.1n1=0.1 and n 1 equals 0.9n1=0.9 -- 4.2 n 1 equals 0.2n1=0.2 and n 2 equals 0.8n2=0.8 -- 4.3 n 1 equals 0.3n1=0.3 and n 2 equals 0.7n2=0.7 -- 4.4 n 1 equals 0.4n1=0.4 and n 2 equals 0.6n2=0.6 -- 4.5 n 1 equals 0.5n1=0.5 and n 2 equals 0.5n2=0.5 -- 4.6 n 1 equals 0.6n1=0.6 and n 2 equals 0.4n2=0.4 -- 4.7 n 1 equals 0.7n1=0.7 and n 2 equals 0.3n2=0.3 -- 4.8 n 1 equals 0.8n1=0.8 and n 2 equals 0.2n2=0.2 -- 4.9 n 1 equals 0.9n1=0.9 and n 2 equals 0.1n2=0.1 -- 5 Conclusion -- References -- Fake News Detection Using Ensemble Learning Models -- 1 Introduction -- 2 Related Works. ; 3 Proposed Methodology -- 3.1 Dataset Description and Data Preprocessing -- 3.2 Feature Extraction -- 3.3 Algorithms -- 3.4 Evaluation Metrics -- 3.5 Web Application -- 4 Results and Discussion -- 5 Conclusion -- References -- Ensemble Approach for Suggestion Mining Using Deep Recurrent Convolutional Networks -- 1 Introduction -- 2 Related Work -- 3 Proposed Architecture -- 4 Experiments -- 4.1 Dataset and Pre-processing -- 4.2 Experimental Setup -- 5 Results and Discussion -- 6 Limitations -- 7 Conclusion -- References -- A CNN-Based Self-attentive Approach to Knowledge Tracing -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Architecture for the Proposed Model -- 4 Experimentations -- 4.1 Dataset -- 4.2 Evaluation Methodology -- 5 Results and Discussion -- 6 Conclusion and Future Work -- References -- LIPFCM: Linear Interpolation-Based Possibilistic Fuzzy C-Means Clustering Imputation Method for Handling Incomplete Data -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 4 Experimental Framework -- 4.1 Dataset Description -- 4.2 Missing Value Simulation -- 4.3 Evaluation Criteria -- 5 Experimental Results and Discussion -- 6 Conclusion and Future Work -- References -- Experimental Analysis of Two-Wheeler Headlight Illuminance Data from the Perspective of Traffic Safety -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Methodology -- 3.2 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Detecto: The Phishing Website Detection -- 1 Introduction -- 2 Literature Review -- 2.1 Methodologies for Phishing Website Detection -- 2.2 Dataset -- 2.3 Feature Extraction -- 2.4 Machine Learning Algorithm -- 3 Result -- 4 Limitation -- 5 Conclusion -- References -- Synergizing Voice Cloning and ChatGPT for Multimodal Conversational Interfaces -- 1 Introduction. ; 2 Related Works -- 3 The Proposed System -- 3.1 Voice-Enabled ChatGPT -- 3.2 Voice Cloning Model -- 4 Methodology -- 4.1 Voice-Enabled ChatGPT -- 5 Voice Cloning -- 6 Result and Discussion -- 7 Conclusion -- 8 Future Scope -- References -- A Combined PCA-CNN Method for Enhanced Machinery Fault Diagnosis Through Fused Spectrogram Analysis -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Dataset -- 2.2 Data Preprocessing -- 2.3 Fusion -- 2.4 CNN -- 3 Results and Discussion -- 4 Conclusion -- References -- FPGA-Based Design of Chaotic Systems with Quadratic Nonlinearities -- 1 Introduction -- 2 Design Methodology -- 2.1 Mathematical Representation -- 3 Results -- 3.1 Synthesis Results -- 3.2 Simulation Results -- 4 Conclusion -- References -- A Comprehensive Survey on Replay Strategies for Object Detection -- 1 Introduction -- 2 Object Detectors -- 3 Continual Learning and Catastrophic Forgetting -- 4 Replay Strategies for Object Detection -- 5 Conclusions -- References -- Investigation of Statistical and Machine Learning Models for COVID-19 Prediction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Performance Metrics -- 4 Algorithms Used -- 4.1 Statistical Model -- 4.2 Machine Learning Algorithms -- 5 Result Analysis -- 6 Conclusion -- References -- SONAR-Based Sound Waves' Utilization for Rocks' and Mines' Detection Using Logistic Regression -- 1 Introduction -- 2 Literature Review -- 3 Proposed Work -- 4 Implementation Analysis -- 5 Conclusion and Future Scope -- References -- A Sampling-Based Logistic Regression Model for Credit Card Fraud Estimation -- 1 Introduction -- 2 Literature Review -- 3 Proposed Model -- 4 Result Analysis and Discussion -- 5 Conclusion and Future Scope -- References -- iFlow: Powering Lightweight Cross-Platform Data Pipelines -- 1 Introduction. ; 2 Literature Review -- 3 Proposed Methodology -- 4 Result Analysis and Discussion -- 5 Conclusion and Future Work -- References -- Developing a Deep Learning Model to Classify Cancerous and Non-cancerous Lung Nodules -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset -- 3.2 Model Architecture -- 4 Results and Discussion -- 5 Conclusion -- References -- Concrete Crack Detection Using Thermograms and Neural Network -- 1 Introduction -- 1.1 Related Work -- 2 Experiment Design -- 2.1 Simulation Dataset Creation -- 2.2 Camera and Concrete Blocks Specifications -- 2.3 Compression-Exposed Concrete Data Collection -- 2.4 Simulation Dataset Model -- 2.5 Laboratory Dataset Model -- 3 Results and Analysis -- 3.1 Simulation Dataset Model Results -- 3.2 Laboratory Dataset Model Results -- 3.3 The Challenges of Using Thermal Images -- 4 Conclusion -- References -- Wind Power Prediction in Mediterranean Coastal Cities Using Multi-layer Perceptron Neural Network -- 1 Introduction -- 2 Material and Method -- 2.1 Study Area and Dataset -- 2.2 MLPNN Model -- 2.3 Statistical Indices (SI) -- 3 Results and Discussions -- 4 Conclusions -- References -- Next Generation Intelligent IoT Use Case in Smart Manufacturing -- 1 Introduction -- 2 Literature Review -- 2.1 Research Objectives of This Study -- 2.2 Research Methodology -- 3 Next Generation Technology Development -- 4 Defining '4*S Model' -- 4.1 Conceptualization of '4*S Model' -- 5 Challenges in Smart Manufacturing -- 6 Advantages in Smart Manufacturing -- 6.1 Direct Cost Savings -- 6.2 Indirect Cost Savings -- 7 Limitations of This Study -- 8 Conclusion -- References -- Forecasting Financial Success App: Unveiling the Potential of Random Forest in Machine Learning-Based Investment Prediction -- 1 Introduction -- 2 Literature Review -- 3 Concept -- 3.1 Financial Investment -- 3.2 Machine Learning. ; 4 Methodology -- 5 Results -- 6 Discussions -- 7 Limitations -- 8 Conclusion and Future Scope -- References -- Integration of Blockchain-Enabled SBT and QR Code Technology for Secure Verification of Digital Documents -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Performance Analysis -- 4.1 Time -- 4.2 Scalability -- 4.3 Authentication and Security -- 4.4 Automation -- 5 Conclusion and Future Scope -- References -- Time Series Forecasting of NSE Stocks Using Machine Learning Models (ARIMA, Facebook Prophet, and Stacked LSTM) -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Data Preparation -- 5 Assessment Metric -- 6 Models -- 6.1 ARIMA -- 6.2 Facebook Prophet -- 6.3 LSTM -- 7 Proposed Methodology -- 8 Observations and Results -- 9 Result Analysis -- 10 Limitations -- 11 Conclusion -- 12 Social Impact -- 13 Future Scope -- References -- Analysis of Monkey Pox (MPox) Detection Using UNETs and VGG16 Weights -- 1 Introduction -- 2 Previous Works -- 3 Methodology -- 3.1 VGG16 -- 3.2 CNN -- 3.3 Custom CNN -- 3.4 UNET -- 4 Implementation Analysis -- 4.1 Data Preprocessing -- 4.2 Extracting Features -- 4.3 Measures of Performance -- 5 Discussion -- 6 Conclusion -- 7 Future Enhancement -- References -- Role of Robotic Process Automation in Enhancing Customer Satisfaction in E-commerce Through E-mail Automation -- 1 Introduction -- 2 Review of Literature -- 3 The E-learning Environment -- 4 Need for Robotic Process Automation -- 5 RPA Implementation -- 5.1 Payment Management -- 5.2 Moodle Account Creation -- 5.3 E-mail Automation -- 6 Discussions -- 7 Conclusion -- References -- Gene Family Classification Using Machine Learning: A Comparative Analysis -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Machine Learning in Bioinformatics -- 1.3 Motivation -- 2 Literature Survey -- 3 Proposed Work -- 3.1 Architecture. ; 3.2 Implementation of Machine Learning Algorithms.
• Titolo autorizzato: Proceedings of Data Analytics and Management
• ISBN: 981-9965-53-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910799251203321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Networks and Systems Series