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[null,null,"Titolo",null,"Data Science and Security : Proceedings of IDSCS 2023 / / edited by Samiksha Shukla, Hiroki Sayama, Joseph Varghese Kureethara, Durgesh Kumar Mishra"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"981-9709-75-X"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (568 pages)"]
[null,null,"Collana",null,"Lecture Notes in Networks and Systems, , 2367-3389 ; ; 922"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence - Data processing"]
[{"$nulls":4},"Data protection"]
[{"$nulls":4},"Computer networks - Security measures"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Data Science"]
[{"$nulls":4},"Data and Information Security"]
[{"$nulls":4},"Mobile and Network Security"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Contents -- Fear and Finance: An Unsupervised Machine Learning Study on Credit-Averse Households in the U.S -- 1 Introduction -- 1.1 Background on Credit Fear and Its Impact on Households -- 1.2 Purpose of the Research -- 1.3 Overview of the Methodology and Data Sources -- 2 Literature Review -- 2.1 Previous Research on Credit Fear and Credit Constraints -- 2.2 Overview of the Survey of Consumer Finances (SCF) -- 2.3 Overview of Unsupervised Machine Learning Method with Clustering -- 3 Methodology -- 3.1 K-means Clustering -- 4 Analysis and Results -- 4.1 Data Preparation -- 4.2 Feature Selection Approach -- 4.3 Principal Component Analysis -- 5 Conclusions -- 5.1 Limitations and Future Research Directions -- References -- OGIA: Ontology Integration and Generation Using Archaeology as a Domain -- 1 Introduction -- 2 Related Works -- 3 Proposed System Architecture -- 4 Results and Performance Evaluation -- 5 Conclusions -- References -- Data: A Key to HR Analytics for Talent Management -- 1 Introduction -- 2 Conventional Talent Management Techniques -- 2.1 Comparison Between the Traditional Performance Management System "]
[{"$nulls":4},"and the Unconventional Performance Management System -- 3 Framework for Data-Driven Talent Management -- 4 Parameters Used in HR Analytics -- 5 Tools Used for HR Analytics -- 6 Challenges of Conventional Talent Management Techniques -- 7 Importance of Data and HR Analytics in Workforce Planning -- 7.1 Analyzing Workforce Turnover Patterns Using Data Analytics: A Case Study -- 8 Application of Data-Oriented HR Analytics -- 8.1 Healthcare Sector -- 8.2 Academics -- 8.3 IT Sector -- 9 Limitations -- 10 Conclusion and Future Recommendations -- References -- An Early Lumpy Skin Disease Detection System Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Data Collection -- 3.1 Data Pre-processing."]
[{"$nulls":4},"4 Model Training -- 4.1 Decision Tree -- 4.2 Random Forest -- 4.3 Logistic Regression -- 4.4 Support Vector Machine -- 4.5 KNN -- 5 Results and Discussion -- 6 Conclusion -- References -- Extracting Network Structures from Corporate Organization Charts Using Heuristic Image Processing -- 1 Introduction -- 2 Dataset -- 3 Method -- 4 Results -- 5 Conclusions -- References -- Generating Equations for Mathematical Word Problems Using Multi-head Attention Transformer -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Preprocessing -- 3.2 Baseline Model (Bi-LSTM Model with Attention Layers) -- 3.3 Transformer Model with Attention -- 4 Results and Conclusions -- 5 Future Scope -- References -- Autonomous System Enabling Node and Edge Detection, Path Optimization, and Effective Color-Coded Box Management in Diverse Robotic Environments -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Extracting Necessary Features and Information from the Given Image -- 3.2 Path Planning and Navigation -- 4 Implementation Using LiDAR -- 5 Comparative Study -- 6 Results -- 7 Future Scope and Conclusion -- References -- GLANCE-Guided Language Through Autoregression Establishing Natural and Classifier-Free Editing -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Scene Tokenizing and Representation -- 3.2 Prioritizing Human Attention in Tokenization -- 3.3 Vector Quantization of Faces -- 3.4 Enhancing Facial Emphasis Within the Scene Context -- 3.5 Object Vector Quantization -- 3.6 Transformer-Scene Based -- 3.7 Pioneering Classifier-Free Transformer Guidance -- 4 Results -- 4.1 Dataset -- 4.2 Metrics -- 4.3 Previous Work Comparison -- 4.4 Experimental Setting with Result Analysis for Storytelling -- 5 Conclusion -- References -- Method for Design of Magnetic Field Active Silencing System Based on Robust Meta Model -- 1 Introduction."]
[{"$nulls":4},"1.1 Introduction to the Problem -- 1.2 Contribution -- 1.3 Paper Organization -- 2 Related Works -- 3 Exact Model Design -- 4 Robust Meta Model Design -- 5 Active Silencing Robust System Design -- 6 Games Solutions Calculation -- 7 Numerical Study -- 8 Experimental Study -- 9 Conclusions -- References -- Ontology Integration for Cultural Landscape Management Using ML and Assistive Artificial Intelligence -- 1 Introduction -- 2 Related Works -- 3 Proposed System Architecture -- 4 Performance Evaluation and Results -- 5 Conclusion -- References -- Early Phase Detection of Bacterial Blight in Pomegranate Using GAN Versus Ensemble Learning -- 1 Introduction -- 2 Literature Review -- 2.1 Comparison Table of Previous Existing Techniques and Methods -- 3 Methodology -- 3.1 Steps Involved -- 3.2 Cycle-GAN Generated Images of Different Classes -- 3.3 Ensemble Learning Model -- 4 Graphs -- 5 Results -- 6 Conclusion -- References -- Classification of Diseased Leaves in Plants Using Convolutional Neural Networks -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 4 Data Analysis -- 5 Results, Discussion, and Conclusion -- References -- Brain Tumor Localization "]
[{"$nulls":4},"Using Deep Ensemble Classification and Fast Marching Segmentation -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Dataset -- 3.2 Experimental Setup -- 3.3 MobileNet-V3 -- 3.4 EfficientNetV2L -- 3.5 The Ensemble Model -- 3.6 Fast Marching Segmentation -- 4 Results and Discussions -- 4.1 MobileNetV3L -- 4.2 EfficientNetV2 -- 4.3 Ensemble Model -- 4.4 Segmentation -- 5 Conclusion -- References -- Spectrum and Energy of the Mobius Function Graph of Finite Cyclic Groups -- 1 Introduction -- 2 Preliminaries -- 3 Adjacency Spectrum of upper M left parenthesis normal upper G right parenthesis M(G)."]
[{"$nulls":4},"4 Laplacian Spectrum of upper M left parenthesis normal upper G right parenthesis M(G) -- 5 Energy of upper M left parenthesis normal upper G right parenthesis M(G)  and the Laplacian Energy of upper M left parenthesis normal upper G right parenthesis M(G) -- 6 Conclusion -- References -- Analysis of Multinomial Classification for Legal Document Categorization -- 1 Introduction -- 2 Dataset Preparation and Methodology -- 2.1 Dataset Preprocessing -- 2.2 Methodology -- 3 Discussions -- 4 Conclusion -- References -- Pioneering Image Analysis with Hybrid Convolutional Neural Networks and Generative Adversarial Networks for Enhanced Visual Perception -- 1 Introduction -- 1.1 Scope -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Problem Definition -- 3.2 Data Acquisition and Pre-processing -- 3.3 Hybrid Deep CNN Architecture -- 3.4 GAN Architecture -- 3.5 Hybrid Integration -- 3.6 Training -- 3.7 Evaluation -- 4 Result and Discussion -- 4.1 Accuracy -- 4.2 Loss -- 5 Conclusion -- References -- Enhancing Medical Decision Support Systems with the Two-Parameter Logistic Regression Model -- 1 Introduction -- 2 Methodology -- 3 Empirical Study -- 4 Conclusion -- 5 Future Research -- References -- BI-RADS Score Prediction Using AI for Breast Cancer Screening -- 1 Introduction -- 2 Literature Survey -- 3 Materials and Methods -- 3.1 Collection of Mammograms -- 3.2 Data Pre-processing -- 3.3 Transforming DICOM -- 3.4 DICOM Annotation -- 3.5 Model Building -- 4 Results and Discussion -- 5 Conclusion -- References -- Modeling and Analysis of the Lead-Lag Network of Economic Indicators -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion and Limitations -- References -- Predictive Maintenance Model for Industrial Equipment -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Result and Discussion -- 5 Conclusion -- References."]
[{"$nulls":4},"Taming the Complexity of Distributed Lag Models: A Practical Approach to Multicollinearity, Outliers, and Auto-Correlation in Finance -- 1 Introduction -- 2 Methodology -- 3 Empirical Application -- 4 Conclusions -- 5 Future Scope -- References -- Algorithm of Robust Control for Multi-stand Rolling Mill Strip Based on Stochastic Multi-swarm Multi-agent Optimization -- 1 Introduction -- 1.1 Introduction to the Problem -- 1.2 Contribution -- 1.3 The Organization of the Paper -- 2 Literature Review and Problem Statement -- 3 Design of an Exact Model of the Random Processes of the Longitudinal Variation in Strip Thickness -- 4 Design of a Robust Meta-Model of the Random Processes of the Longitudinal Variation in Strip Thickness -- 5 Model Description for Multi-stand Rolling Mill -- 6 Robust System Design -- 7 Calculation of Vector Games Solutions -- 8 Simulation Results -- 9 Conclusions -- References -- Emoji Sentiment Analysis of User Reviews on Online Applications Using Supervised Machine Learning -- 1 Introduction -- 2 Related Work -- 2.1 Inference from Literature Review -- 3 The Materials and the Method -- 3.1 Data Set -- 3.2 Data Preprocessing -- 3.3 Experimental Setup -- 3.4 Data Exploration and Analysis -- 3.5 Machine Learning Models for Data "]
[{"$nulls":4},"Classification -- 3.6 Performance Evaluation -- 4 Research Results and Discussions -- 5 Conclusion -- References -- An Enhanced Power Management and Prediction for Smart Grid Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Comfort Level Prediction -- 4 Proposed Algorithm -- 5 Simulation and Experimental Result -- 5.1 Simulation Analysis -- 6 Conclusion -- References -- Feature Reduction Set for the Prediction of Renal Disease Using Ensemble Methods and Optimal Hyperplane Algorithms -- 1 Introduction -- 2 Literature Survey -- 3 Data Pre-processing -- 4 Data Reduction."]
[{"$nulls":4},"5 Supervised and Ensemble Learning Approach."]
[null,null,null,"Sommario/riassunto","This book presents best-selected papers presented at the International Conference on Data Science for Computational Security (IDSCS 2023), organized by the Department of Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, India, from 02–04 November, 2023. The proceeding targets the current research works in the areas of data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithms design, computer networking, data mining, big data, text mining, knowledge representation, soft computing, and cloud computing."]