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Advances in Computing Applications / / edited by Amlan Chakrabarti, Neha Sharma, Valentina Emilia Balas
| Advances in Computing Applications / / edited by Amlan Chakrabarti, Neha Sharma, Valentina Emilia Balas |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (290 pages) |
| Disciplina | 004 |
| Soggetto topico |
Computers
Optical data processing Management information systems Computer science Information Systems and Communication Service Computer Imaging, Vision, Pattern Recognition and Graphics Management of Computing and Information Systems |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Wait Event Tuning in Database Engine -- 2. Machine Learning using k-Nearest Neighbor for Library Resources Classification in Agent based Library Recommender System -- 3. An Efficient Dynamic Scheduling of Tasks for Multi-Core Real Time Systems -- 4. Model based approach for Shadow Detection of Static Images -- 5. Light Fidelity (Li-Fi): In Mobile Communication and Ubiquitous Computing Applications -- 6. Performance Analysis of De Noising Filters MR Images -- 7. A Detailed View on SecureString 3.0 -- 8. Performance Comparison for EMD based Classification of Unstructured Acoustic Environments using GMM and K-NN Classifiers -- 9. Performance of Multimodal Biometric System Based on Level and Method of Fusion -- 10. A DSK based Authentication Technique for Secure Smart Grid Wireless Communication -- 11. A Smart Security Framework for High Risk Locations Using Wireless Authentication by Smart Phone -- 12. High Performance Computation Analysis for Medical Images using High Computational Methods -- 13. Terrorist Scanner Radar and Multiple Object Detection System -- 14. Inexact Implementation of Wavelet Transform and its Performance Evaluation through Bit Width Reduction -- 15. A Vulnerability Analysis Mechanism Utilizing Avalanche Attack Model for Dependency Based Systems -- 16. Performance of Statistical and Neural Network Method for Prediction of Survival of Oral Cancer Patients. |
| Record Nr. | UNINA-9910160700103321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Management, Analytics and Innovation : Proceedings of ICDMAI 2024, Volume 2 / / edited by Neha Sharma, Amol C. Goje, Amlan Chakrabarti, Alfred M. Bruckstein
| Data Management, Analytics and Innovation : Proceedings of ICDMAI 2024, Volume 2 / / edited by Neha Sharma, Amol C. Goje, Amlan Chakrabarti, Alfred M. Bruckstein |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (459 pages) |
| Disciplina | 005.74 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Engineering - Data processing Big data Computational Intelligence Data Engineering Big Data |
| ISBN |
9789819732456
9789819732449 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Comprehensive Survey of Nonverbal Emotion Recognition Techniques -- 1 Introduction -- 2 Applications Based on Understanding Nonverbal Emotion -- 3 Machine/Deep Learning Methods for Recognition of Nonverbal Emotion -- 3.1 Facial Expressions Recognition Machine/deep Learning Methods -- 3.2 Hand Gestures Recognition Machine/Deep Learning Methods -- 3.3 Body Language Recognition Machine/Deep Learning Methods -- 4 Findings -- 5 Conclusion -- References -- A Two-Stage CNN Based Satellite Image Analysis Framework for Estimating Building-Count in Residential Built-Up Area -- 1 Introduction -- 2 Review of the Relevant Research Work -- 3 Background Study -- 3.1 Mask R-CNN -- 3.2 Regression Using CNN -- 4 Proposed Methodology -- 4.1 Overview of Proposed Methodology -- 4.2 Mask R-CNN Top-Down Approach for Segmentation of Built Up Area -- 4.3 CNN Based Regression Model to Estimate Building-Count Within Segmented Built-Up Area -- 5 Experimental Evaluation of the Proposed Framework -- 5.1 Dataset Used -- 5.2 Experimental Setup -- 5.3 Experimental Evaluation Metric -- 5.4 Experimental Results and Discussion -- 6 Conclusion -- References -- Forecast of Energy Demand Using Temporal Fusion Transformer -- 1 Introduction -- 2 Survey of Literature -- 3 Proposed Work -- 3.1 Data Collection and Preprocessing -- 3.2 TFT Model Architecture -- 3.3 Training and Validation -- 4 Results -- 4.1 Forecasts -- 4.2 Interpreting the Seasonality -- 4.3 Detecting Some Accidental or Extreme Events -- 4.4 Ranking the Features -- 5 Conclusion -- References -- Mental Health Prediction Using Artificial Intelligence -- 1 Introduction -- 2 Literature Survey -- 3 Design -- 4 Methodology -- 5 Results -- 6 Future Directions and Limitations -- 7 Conclusion -- References.
VGGish Deep Learning Model: Audio Feature Extraction and Analysis -- 1 Introduction -- 1.1 Feature Extraction -- 1.2 Dataset -- 2 Related Work -- 3 Proposed System -- 3.1 Preprocessing -- 3.2 Feature Extraction -- 3.3 Feature Concatenation and Selection -- 3.4 Classification -- 3.5 Output -- 4 Proposed Algorithm -- 4.1 Initialization -- 5 Results -- 6 Conclusion -- References -- Stacking Ensemble-Based Approach for Sarcasm Identification with Multiple Contextual Word Embeddings -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Preprocessing -- 3.2 Contextual Word Embeddings -- 3.3 Proposed Model -- 4 Materials and Methods -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Results and Analysis -- 5 Conclusion -- References -- Trigger-Based Pothole Detection, and Warning System with RQ and PHR Mapping -- 1 Introduction -- 2 Related Work and Comparative Study -- 3 Methodology -- 4 Flowcharts -- 5 Result and Discussions -- 6 Conclusion -- References -- Blending Motion Capture and 3D Human Reconstruction Techniques for Enhanced Character Animation -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Technologies Used for 3D Model Building -- 3.2 Technology Used for MoCap -- 3.3 Integration of the Technologies Used -- 3.4 Constraints of the Proposed System -- 4 Result -- 5 Future Scope -- References -- A Comprehensive Survey of Regression-Based Loss Functions for Time Series Forecasting -- 1 Introduction -- 2 Time Series Data -- 3 Regression Loss Functions -- 3.1 Mean Absolute Error (MAE) -- 3.2 Mean Squared Error (MSE) -- 3.3 Mean Bias Error (MBE) -- 3.4 Relative Absolute Error (RAE) -- 3.5 Relative Squared Error (RSE) -- 3.6 Mean Absolute Percentage Error (MAPE) -- 3.7 Root Mean Squared Error (RMSE) -- 3.8 Mean Squared Logarithmic Error (MSLE) -- 3.9 Root Mean Squared Logarithmic Error (RMSLE). 3.10 Normalized Root Mean Squared Error (NRMSE) -- 3.11 Relative Root Mean Squared Error (RRMSE) -- 3.12 Huber Loss -- 3.13 Log-Cosh Loss -- 3.14 Quantile Loss -- 4 Experiments -- 4.1 Datasets -- 4.2 Performance Metrics -- 5 Conclusion -- References -- Diabetic Retinopathy Detection Using Real-World Datasets of Fundus Images -- 1 Introduction -- 1.1 Diabetic Retinopathy -- 1.2 Severity and Stages -- 2 Literature Review -- 2.1 Research Gaps -- 3 The Dataset -- 3.1 Retinal Image Collection -- 4 Related Work -- 5 Methodology -- 5.1 Data Distribution of Retinal Image Collection -- 5.2 Filtering Out Images with Noise -- 5.3 Image Cropping for Removal of Unnecessary Content -- 6 Model Architecture -- 7 Experimental Analysis -- 8 Results and Discussion -- 8.1 Deep Learning Models Overview -- 8.2 Diagnosis & -- Preventative Measures -- 9 Comparative Analysis -- 10 Future Scope -- 11 Conclusion -- References -- Deep Learning for MRI-Based Brain Tumour Identification and Classification -- 1 Introduction -- 1.1 Viewing Brains -- 1.2 PET Scans -- 1.3 CGI -- 1.4 MRI -- 1.5 Diffusion Scaling Imaging -- 2 Literature Survey -- 3 Proposed Method -- 3.1 Pre Processing -- 3.2 Classification -- 3.3 Characterisation -- 3.4 Grouping -- 3.5 Convolution Neural Network -- 4 Results and Discussion -- 5 Conclusion -- References -- Preserving Tamil Brahmi Letters on Ancient Inscriptions: A Novel Preprocessing Technique for Diverse Applications -- 1 Introduction -- 2 Literature Review -- 3 Methodology for Inscription Translation -- 3.1 Image Blurring -- 3.2 Binarization -- 3.3 Edge Detection -- 4 Results and Discussion -- 5 Conclusion -- References -- Analysis of Regular Machine Learning and Ensemble Learning Approaches for Term Insurance Prediction in Banking Data -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Acquisition of Data -- 3.2 Analysis. 3.3 Data Preprocessing -- 3.4 Training and Analysis of Models -- 4 Results -- 5 Conclusion -- References -- Platform Independent Satellite Image Processing Using GPGPU -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Operating System Portability and Hardware Independence -- 3.2 GPU Detection and Parallel Computing -- 3.3 Change Detection -- 3.4 Algorithms -- 4 Results and Discussions -- 4.1 Evaluation Environment -- 4.2 Evaluation Result -- 5 Conclusion -- 6 Future Scope -- References -- Blending Psychological Models with Modern HCI Techniques to Develop Artificial Emotional Intelligent "Affective" Systems -- 1 Introduction -- 1.1 Understanding Affective Computing -- 1.2 Human Emotions -- 1.3 Paper Organization -- 2 Literature Review -- 3 HCI Techniques for Utilizing Emotion Models -- 3.1 HCI Background -- 3.2 Modern HCI Systems & -- Interaction Modalities -- 4 Blending HCI Approaches with Psychological Models and ML Techniques -- 5 Conclusion -- 5.1 Future Scope -- References -- An Enhanced Deep Learning Method to Generate Synthetic Images with Features That are Comparable to Original Images Using Neural Style Transfer -- 1 Introduction -- 2 Network Architecture -- 2.1 Loss -- 2.2 Content Loss -- 2.3 Style Loss -- 3 Results -- 3.1 Comparative Evaluation -- 4 Conclusion -- References -- Improving Sentiment Analysis by Handling Negation on Twitter Data Using Deep Learning Approaches -- 1 Introduction -- 1.1 Contributions -- 1.2 Organization -- 2 Related Work -- 3 Proposed Methodology -- 3.1 WordNet -- 3.2 Preprocessing -- 3.3 Negation Handling -- 3.4 Classification -- 4 Results -- 4.1 Dataset Description -- 4.2 Experimental Results -- 5 Conclusion -- References -- Comparative Analysis of Deep Learning Models for Car Part Image Segmentation -- 1 Introduction -- 2 Related Works -- 3 Dataset Description -- 4 Methodology. 4.1 YOLOv8 Segmentation Model -- 4.2 Detectron2 Mask R-CNN Resnet 101 FPN -- 4.3 Detectron 2 Mask R-CNN ResNeXt 101 32×8d FPN -- 5 Experimental Results and Observations -- 6 Conclusion -- References -- Boosting Tiny Object Detection in Complex Backgrounds Through Deep Multi-Instance Learning -- 1 Introduction -- 2 Literature Survey -- 2.1 Multi Instance Metric Learning and Bags -- 3 Methodology -- 3.1 Dataset Preparation -- 3.2 Experimental Design -- 4 Results and Discussion -- 4.1 Experimental Setup -- 5 Conclusion -- References -- Driver Drowsiness Detection System Using YoloV5 -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Technology Used -- 4.1 Design and Analysis -- 5 Result and Experiment -- 5.1 Design and Analysis -- 5.2 Preprocessing -- 5.3 Performance of the Model -- 5.4 Result and Discussion -- 6 Future Scope -- 7 Conclusion -- References -- Shift of Customer from Unorganised to Organised Sector in Retail: Is Adoption of Technology a Catalyst -- 1 Introduction -- 1.1 Background of the Problem -- 1.2 Research Problem and Relevance -- 2 Theoretical Framework and Hypothesis Development -- 3 Research Methodology -- 4 Result and Analysis -- 5 Findings and Discussions -- 6 Conclusion -- 6.1 Usage and Limitations -- References -- E-CNN-FFE: An Enhanced Convolutional Neural Network for Facial Feature Extraction and Its Comparative Analysis with FaceNet, DeepID, and LBPH Methods -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Implementation -- 5 Conclusion -- References -- A Graphical Neural Network-Based Chatbot Model for Assisting Cancer Patients with Dietary Assessment in their Survivorship -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Material -- 3.2 Software and Hardware Requirements -- 3.3 Method -- 4 Results and Discussion -- 4.1 Time Complexity -- 5 Conclusion -- References. Plant Identification and Disease Detection System Using Deep Convolutional Neural Networks. |
| Record Nr. | UNINA-9910878050703321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data management, analytics and innovation . Volume 2 : proceedings of ICDMAI 2020 / / Neha Sharma [and three others], (editors)
| Data management, analytics and innovation . Volume 2 : proceedings of ICDMAI 2020 / / Neha Sharma [and three others], (editors) |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XII, 462 p. 225 illus., 171 illus. in color.) |
| Disciplina | 005.74 |
| Collana | Advances in intelligent systems and computing |
| Soggetto topico |
Quantitative research
Database management Big data |
| ISBN | 981-15-5619-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automatic Standardization of Data based on Machine Learning and Natural Language Processing -- Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network.-APPLICATION OF BAYESIAN AUTOMATED HYPERPARAMETER TUNING ON CLASSIFIERS PREDICTING CUSTOMER RETENTION IN BANKING INDUSTRY -- Quantum Machine Learning: A Review and Current Status -- Survey of Transfer Learning and a Case Study of Emotion Recognition using Inductive Approach -- An Efficient Algorithm for Complete Linkage Clustering with a Merging Threshold. |
| Record Nr. | UNINA-9910483147403321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Management, Analytics and Innovation : Proceedings of ICDMAI 2020, Volume 2 / / edited by Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic
| Data Management, Analytics and Innovation : Proceedings of ICDMAI 2020, Volume 2 / / edited by Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Springer Singapore, 2021 |
| Descrizione fisica | 1 online resource (XII, 462 p. 225 illus., 171 illus. in color.) |
| Disciplina | 005.74 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Telecommunication Big data Artificial intelligence—Data processing Artificial intelligence Computational Intelligence Communications Engineering, Networks Big Data Data Science Artificial Intelligence |
| ISBN | 981-15-5619-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automatic Standardization of Data based on Machine Learning and Natural Language Processing -- Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network.-APPLICATION OF BAYESIAN AUTOMATED HYPERPARAMETER TUNING ON CLASSIFIERS PREDICTING CUSTOMER RETENTION IN BANKING INDUSTRY -- Quantum Machine Learning: A Review and Current Status -- Survey of Transfer Learning and a Case Study of Emotion Recognition using Inductive Approach -- An Efficient Algorithm for Complete Linkage Clustering with a Merging Threshold. |
| Record Nr. | UNINA-9910863125003321 |
| Springer Singapore, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Management, Analytics and Innovation : Proceedings of ICDMAI 2020, Volume 1 / / edited by Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic
| Data Management, Analytics and Innovation : Proceedings of ICDMAI 2020, Volume 1 / / edited by Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (471 pages) : illustrations |
| Disciplina | 005.7565 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Telecommunication Big data Artificial intelligence—Data processing Artificial intelligence Computational Intelligence Communications Engineering, Networks Big Data Data Science Artificial Intelligence |
| ISBN | 981-15-5616-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Improving Microblog Clustering: Tweet Pooling Schemes -- An IoT based parking framework for smart cities -- Open Source Challenges & Opportunities -- Empirical study on the perception of accounting professionals towards awareness and adoption of IFRS in India -- On Readability Metrics of Goal Statements of Universities and Brand-promoting Lexicons for Industries -- An Efficient Recommendation System on E-Learning Platform by Query Lattice Optimization -- DengueCBC: Dengue EHR Transmission using Secure Consortium Blockchain Enabled Platform -- Online Credit Card Fraud Analytics using Machine Learning Techniques -- Identifying Major Critical Factors Faced by Tourism Industry Using Apriori Algorithm. |
| Record Nr. | UNINA-9910483964003321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Suicide Among Diverse Youth : A Case-Based Guidebook / / edited by Andres J Pumariega, Neha Sharma
| Suicide Among Diverse Youth : A Case-Based Guidebook / / edited by Andres J Pumariega, Neha Sharma |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIV, 248 p. 8 illus., 5 illus. in color.) |
| Disciplina | 618.9289 |
| Soggetto topico |
Child psychiatry
General practice (Medicine) Child and Adolescent Psychiatry General Practice / Family Medicine |
| ISBN | 3-319-66203-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Foreword -- 1. Cultural Aspects of Suicidality Among Youth -- 2. Culturally Informed Treatment of Suicidality with Diverse Youth: General Principles -- 3. Suicide Among African-American and Other African-Origin Youth -- 4. Suicide Among American Indian, Alaskan Native, and Native Hawaiian Pacific Islander Youth: An Unrealized Future -- 5. Suicide Among Latino Youth -- 6. Suicide Among South Asian Youth in America -- 7. Suicide Among South East Asian Youth -- 8. Suicide Among East Asian Youth -- 9. Suicide Among Turkish American Youth -- 10. Suicide Among Youth of Middle Eastern Origin -- 11. Suicide Among Eastern European Immigrant Youth -- 12. Suicide Among Youth of Soviet Jewish Origin -- 13. Suicide and Self-Harm Among Sexual and Gender Minority Youth: Resilience, Coping, and Despair -- 14. Family and Community Intervention in Suicide Prevention and Management. |
| Record Nr. | UNINA-9910300262303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
World of business with data and analytics / / edited by Neha Sharma, Mandar Bhatavdekar
| World of business with data and analytics / / edited by Neha Sharma, Mandar Bhatavdekar |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (211 pages) |
| Disciplina | 260 |
| Collana | Studies in Autonomic, Data-Driven and Industrial Computing |
| Soggetto topico | Business - Data processing |
| ISBN | 981-19-5689-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 2 Cognitive Models to Predict Pipeline Leaks and Ruptures -- 1 Introduction -- 2 Literature Review -- 3 Material and Methodology -- 3.1 Defining the Solution Using Data and Analytics -- 4 Results -- 5 Conclusion -- References -- 3 Network Optimization of the Electricity Grid to Manage Distributed Energy Resources Using Data and Analytics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Defining a Network Optimization Solution to Build an Agile Grid -- 3.2 Defining the Problem -- 3.3 Defining a Solution for the Problem -- 4 Results -- 5 Conclusion -- References -- 4 Enhancing Market Agility Through Accurate Price Indicators Using Contextualized Data Analytics -- 1 Introduction -- 2 Literature Review -- 3 Data-Flow in Utility Value Chain -- 4 Handaling Market data Volatility and Coherency -- 5 Leveraging Data Analytics in Improving Accuracy of Price-Prediction Models -- 6 Data-Reliant Congestion Management -- 7 Unlocking Techno Commercial Benefits to Utility -- 8 Conclusion -- References -- 5 Infrastructure for Automated Surface Damage Classification and Detection in Production Industries Using ResUNet-based Deep Learning Architecture -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Methodology -- 4.1 Two-Phase Learning Approach -- 5 Results -- 6 Conclusion -- References -- 6 Cardiac Arrhythmias Classification and Detection for Medical Industry Using Wavelet Transformation and Probabilistic Neural Network Architecture -- 1 Introduction -- 2 Literature Review -- 3 The Solution -- 3.1 Discrete Wavelet Transformation -- 3.2 Probabilistic Neural Network.
4 Experimental Outcome -- 5 Results and Discussion -- 6 Conclusion -- References -- 7 Investor Behavior Towards Mutual Fund -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Results and Discussions -- 6 Conclusion and Future Scope -- References -- 8 iMask-An Artificial Intelligence Based Redaction Engine -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 9 Intrusion Detection System Using Signature-Based Detection and Data Mining Technique -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Conclusion -- References -- 10 Cloud Cost Intelligence Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Results and Recommendations -- 5 Conclusion -- References -- 11 Mining Deeper Insights from Texts Using Unsupervised NLP -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Result -- 5 Conclusion -- References -- 12 Explainable AI for ML Ops -- 1 Introduction -- 1.1 ML and The "Last Mile" Problem -- 1.2 Keeping Tabs on the Model -- 1.3 Explainable AI for Model Monitoring -- 2 Literature Review -- 2.1 AI/ML Maturity -- 2.2 Rise of ML Ops -- 2.3 ML Ops in Postproduction -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Explainable AI 101 -- 3.3 Explainability and ML Monitoring -- 4 Exploratory Data Analysis -- 5 Experimental Analysis -- 6 Results -- 6.1 SOLUTION 1: Local Explanation with One Particular Observation -- 6.2 SOLUTION 2: Global Monitoring: Iterating the Model 100 Times, Introduce the Manipulation from the 30th Iteration -- 7 Conclusion -- References. |
| Record Nr. | UNISA-996490358303316 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
World of business with data and analytics / / edited by Neha Sharma, Mandar Bhatavdekar
| World of business with data and analytics / / edited by Neha Sharma, Mandar Bhatavdekar |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (211 pages) |
| Disciplina | 260 |
| Collana | Studies in Autonomic, Data-Driven and Industrial Computing |
| Soggetto topico | Business - Data processing |
| ISBN | 981-19-5689-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 2 Cognitive Models to Predict Pipeline Leaks and Ruptures -- 1 Introduction -- 2 Literature Review -- 3 Material and Methodology -- 3.1 Defining the Solution Using Data and Analytics -- 4 Results -- 5 Conclusion -- References -- 3 Network Optimization of the Electricity Grid to Manage Distributed Energy Resources Using Data and Analytics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Defining a Network Optimization Solution to Build an Agile Grid -- 3.2 Defining the Problem -- 3.3 Defining a Solution for the Problem -- 4 Results -- 5 Conclusion -- References -- 4 Enhancing Market Agility Through Accurate Price Indicators Using Contextualized Data Analytics -- 1 Introduction -- 2 Literature Review -- 3 Data-Flow in Utility Value Chain -- 4 Handaling Market data Volatility and Coherency -- 5 Leveraging Data Analytics in Improving Accuracy of Price-Prediction Models -- 6 Data-Reliant Congestion Management -- 7 Unlocking Techno Commercial Benefits to Utility -- 8 Conclusion -- References -- 5 Infrastructure for Automated Surface Damage Classification and Detection in Production Industries Using ResUNet-based Deep Learning Architecture -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Methodology -- 4.1 Two-Phase Learning Approach -- 5 Results -- 6 Conclusion -- References -- 6 Cardiac Arrhythmias Classification and Detection for Medical Industry Using Wavelet Transformation and Probabilistic Neural Network Architecture -- 1 Introduction -- 2 Literature Review -- 3 The Solution -- 3.1 Discrete Wavelet Transformation -- 3.2 Probabilistic Neural Network.
4 Experimental Outcome -- 5 Results and Discussion -- 6 Conclusion -- References -- 7 Investor Behavior Towards Mutual Fund -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Results and Discussions -- 6 Conclusion and Future Scope -- References -- 8 iMask-An Artificial Intelligence Based Redaction Engine -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 9 Intrusion Detection System Using Signature-Based Detection and Data Mining Technique -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Conclusion -- References -- 10 Cloud Cost Intelligence Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Results and Recommendations -- 5 Conclusion -- References -- 11 Mining Deeper Insights from Texts Using Unsupervised NLP -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Result -- 5 Conclusion -- References -- 12 Explainable AI for ML Ops -- 1 Introduction -- 1.1 ML and The "Last Mile" Problem -- 1.2 Keeping Tabs on the Model -- 1.3 Explainable AI for Model Monitoring -- 2 Literature Review -- 2.1 AI/ML Maturity -- 2.2 Rise of ML Ops -- 2.3 ML Ops in Postproduction -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Explainable AI 101 -- 3.3 Explainability and ML Monitoring -- 4 Exploratory Data Analysis -- 5 Experimental Analysis -- 6 Results -- 6.1 SOLUTION 1: Local Explanation with One Particular Observation -- 6.2 SOLUTION 2: Global Monitoring: Iterating the Model 100 Times, Introduce the Manipulation from the 30th Iteration -- 7 Conclusion -- References. |
| Record Nr. | UNINA-9910616374303321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||