Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Advances in Engineering Design [[electronic resource] ] : Select Proceedings of FLAME 2022 / / edited by Rohit Sharma, Ravindra Kannojiya, Naveen Garg, Sachin S. Gautam
| Advances in Engineering Design [[electronic resource] ] : Select Proceedings of FLAME 2022 / / edited by Rohit Sharma, Ravindra Kannojiya, Naveen Garg, Sachin S. Gautam |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (816 pages) |
| Disciplina | 929.374 |
| Collana | Lecture Notes in Mechanical Engineering |
| Soggetto topico |
Engineering design
Computer-aided engineering Mechanics, Applied Solids Engineering Design Computer-Aided Engineering (CAD, CAE) and Design Solid Mechanics |
| ISBN | 981-9930-33-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Estimation of Lacunar Permeability in Anatomical Regions of Femoral Cortex: Endocortical vs. Periosteal -- Design of Efficient Finite Elements using Deep Learning Approach -- Design of Efficient Quadrature Scheme in Finite Element Using Deep Learning -- Accelerating Finite Element Assembly on a GPU -- Design and Optimization of Path Planning Bot Based on ROS -- Design and Fabrication of PLA Printed Wearable Exoskeleton with 7 DOF for Upper Limb Physiotherapy Training and Rehabilitation -- Framework for Design and Control of Automatic Stone - Glass Separator -- Buckling Analysis of Piston Rod for Hydraulic Cylinder of Cotton Bale Press Machine -- Manufacturing Process Related Challenges of Additive Manufactured Parts: A Review -- Modelling of Kinematic Chains and Mechanisms with Special Emphasis on Multi-linked Jointed Chain Mechanisms -- Design And Analysis of a Spherical Joint Mechanism for Robotic Manipulators. |
| Record Nr. | UNINA-9910741145103321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Analytics for Smart Grids Applications--A Key to Smart City Development
| Data Analytics for Smart Grids Applications--A Key to Smart City Development |
| Autore | Kumar Sharma Devendra |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (466 pages) |
| Altri autori (Persone) |
SharmaRohit
JeonGwanggil KumarRaghvendra |
| Collana | Intelligent Systems Reference Library |
| ISBN | 3-031-46092-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- About This Book -- Key Features -- Contents -- About the Editors -- 1 Data Analytics for Smart Grids and Applications-Present and Future Directions -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 Smart Grid Infrastructure -- 1.4 Data Analytics in Smart Grids -- 1.4.1 Data Pre Processing Techniques in Smart Grids -- 1.4.2 Case Study of Data Analytics in Smart Grids -- 1.5 Artificial Intelligence in Smart Grids -- 1.5.1 Event Detection Using Data Analytics and Cloud Computing for Intelligent IoT System -- 1.6 Conclusion -- References -- 2 Design, Optimization and Performance Analysis of Microgrids Using Multi-agent Q-Learning -- 2.1 Introduction -- 2.2 Literature Review -- 2.3 Proposed Model -- 2.4 Experiments -- 2.5 Conclusion -- References -- 3 Big Data Analytics for Smart Grid: A Review on State-of-Art Techniques and Future Directions -- 3.1 Introduction -- 3.2 State-of-Art Techniques for Big Data Analytics in Smart Grids -- 3.3 Challenges in Big Data Analytics for Smart Grids -- 3.4 Big Data Analytics for Smart Grids -- 3.5 Applications of Big Data Analytics in Smart Grids -- 3.6 Challenges and Future Directions for Big Data Analytics in Smart Grids -- 3.7 Case Studies of Big Data Analytics in Smart Grids -- 3.7.1 Case Study 1: Duke Energy's Grid Modernization Program -- 3.7.2 Case Study 2: National Grid's Smart Grid Program -- 3.7.3 Case Study 3: ENEL's Smart Grid Program -- 3.8 Future Directions for Big Data Analytics in Smart Grids -- 3.9 Real-Time Big Data Analytics for Smart Grids -- 3.10 Conclusion -- References -- 4 Smart Grid Management for Smart City Infrastructure Using Wearable Sensors -- 4.1 Introduction -- 4.1.1 Smart Grid Versus Traditional Electricity Grids -- 4.1.2 Why Do We Need Smart Grids? -- 4.1.3 Smart Grid Features -- 4.1.4 Smart Grid Technologies -- 4.1.5 Smart Grid Approaches.
4.1.6 Smart Meters and Home EMS -- 4.1.7 Smart Appliances -- 4.1.8 Home Power Generation -- 4.1.9 Machine Learning for Data Analytics in Smart Grids and Energy Management -- 4.1.10 Security for Industrial Control Systems in Smart Grids -- 4.1.11 Power Flow Modelling and Optimization in Smart Grids -- 4.1.12 Grid Stability and Security in Smart Grids -- 4.1.13 Integration of Renewable Energy Sources in Smart Grid Management -- 4.1.14 Demand Response Strategies for Efficient Smart Grid Management -- 4.1.15 Cybersecurity Measures for Smart Grid Management -- 4.1.16 Energy Storage Systems and Their Role in Smart Grid Management -- 4.1.17 Data Analytics and Artificial Intelligence in Smart Grid Management -- 4.1.18 Smart Grid Communication Protocols and Infrastructure -- 4.1.19 Advantages of Smart Grids -- 4.1.20 Disadvantages of Smart Grids -- 4.2 Conclusion -- References -- 5 Studies on Conventional and Advanced Machine Learning Algorithm Towards Framing of Robust Data Analytics for the Smart Grid Application -- 5.1 Introduction -- 5.2 Review of Different Smart Grid Based Approaches -- 5.3 Smart Grid Model -- 5.3.1 Smart Grids as Coordinators for Data Flow and Energy Flow -- 5.3.2 Big Data -- 5.4 Features of Big Data to Be Integrated into the Smart Grid -- 5.5 Contribution of the Smart Grid as Data Source -- 5.6 Smart Grid in Supply of Data Gathering -- 5.6.1 Data Transmission Methodology -- 5.6.2 Data Analysis Methodology -- 5.6.3 Data Extraction from Smart Grid -- 5.6.4 Grid for Production of Renewable Source of Energy -- 5.6.5 Big Data in Smart Grid -- 5.6.6 Machine Learning Approach to the Data Grid -- 5.6.7 Application of IOT to the Smart Grid Technology -- 5.7 IOT Based Solutions Towards Grid Problems -- 5.7.1 Stability of IOT Based Connection -- 5.7.2 Cost Effectiveness in Implementation -- 5.7.3 Security to the Information. 5.8 Application of Data Grid in Mobile Sink Based Wireless Sensor Network -- 5.8.1 Assumptions of Network Characteristics -- 5.9 Virtual Grid Architecture -- 5.9.1 Different Structures of Virtual Grids -- 5.9.2 Virtual Grid Construction Cost -- 5.9.3 Reading of the Smart Meter Data and Its Analysis by the Smart Grid with Future Prediction -- 5.9.4 Prediction Analysis of Smart Meter Data -- 5.10 Future Research Direction -- 5.11 Conclusion -- References -- 6 Prediction and Classification for Smart Grid Applications -- 6.1 Introduction -- 6.2 Smart Grid -- 6.3 Predictive and Classification Models in Smart Grid Applications -- 6.4 Predictive Modeling -- 6.5 Classification Modeling -- 6.6 Smart Grid Management -- 6.7 Intelligent Data Collection Devices -- 6.8 Data Science Pertaining to Smart Grid Analytics -- 6.9 Machine Learning for Data Analytics -- 6.10 Data Security for Smart Grid Applications -- 6.11 Conclusion -- References -- 7 A Review on Smart Metering Using Artificial Intelligence and Machine Learning Techniques: Challenges and Solutions -- 7.1 Introduction -- 7.1.1 Trends of the Smart Metering Systems -- 7.1.2 Challenges of Smart Meters -- 7.1.3 Key Elements of Smart Meter -- 7.1.4 IoT in Smart Metering -- 7.1.5 Integration of IoT with AI and Machine Learning for Smart Meter -- 7.1.6 Artificial Intelligence Techniques -- 7.2 Conclusion -- References -- 8 Machine Learning Applications for the Smart Grid Infrastructure -- 8.1 Introduction -- 8.2 IoT in Distribution System -- 8.3 Techniques Using Machine Learning -- 8.4 Conclusion -- References -- 9 A Privacy Mitigating Framework for the Smart Grid Internet of Things Data -- 9.1 Introduction -- 9.1.1 Overview of the Smart Grid and Its Significance in Modern Energy Systems -- 9.1.2 Introduction to the IoT and Its Integration with the Smart Grid -- 9.1.3 Importance of Privacy in Smart Grid IoT Data. 9.2 Privacy Challenges in Smart Grid IoT Data -- 9.3 Privacy Mitigation Techniques -- 9.4 Privacy Mitigation Framework for Smart Grid -- 9.4.1 Privacy Monitoring Engine Description -- 9.5 Results -- 9.6 Conclusion -- References -- 10 Protecting Future of Energy: Data Security and Privacy for Smart Grid Applications Using MATLAB -- 10.1 Introduction -- 10.1.1 Data Security and Privacy Threats -- 10.1.2 Data Security and Privacy Solutions -- 10.1.3 MATLAB Solution -- 10.1.4 Key Features and Capabilities -- 10.2 MATLAB Tools and Inbuilt Functions for Data Security in Applications of Smart Grid -- 10.3 MATLAB Functions for Data Security and Privacy in Smart Grid Applications Include -- 10.4 MATLAB Techniques for Data Security and Privacy in Smart Grid Applications -- 10.5 Matlab Algorithm for Privacy-Preserving Data Mining for Smart Grid Applications -- 10.6 Threats to Data Security and Privacy in Smart Grid Applications -- 10.6.1 Preventive Measures -- 10.7 Case Studies and Practical Implementations of Data Security and Privacy in Smart Grid Applications -- 10.7.1 Case Study 1: Securing Smart Meters Using Blockchain -- 10.7.2 Case Study 2: Machine Learning-Based Anomaly Detection in Power Grids -- 10.7.3 Case Study 3: Privacy-Preserving Data Aggregation in Smart Grids -- 10.7.4 Case Study 4: Secure Data Sharing in Smart Grids Using Homomorphic Encryption -- 10.7.5 Case Study 5: Anomaly Detection in Smart Grids Using Machine Learning (ML) with Matlab -- 10.8 Conclusion -- References -- 11 Revolutionizing Smart Grids with Big Data Analytics: A Case Study on Integrating Renewable Energy and Predicting Faults -- 11.1 Introduction -- 11.2 Current Trends in Smart Grid Based Big Data Analytics -- 11.2.1 There is a Notable Surge in Speculation in Smart Grid Projects and, Consequently, Smart Grid Analytics [9-11]. 11.2.2 Smart Grid Analytics Effectively Handle Real-Time Data Despite the Increased Speed and Diverse Requirements -- 11.2.3 Digital Technologies and Cloud Computing Will Continue to Improve, Facilitating Enhanced Data Computation Capabilities -- 11.2.4 Smart Grid and Its Benefits for Renewable Energy -- 11.3 Challenges of Smart Grid Analytics -- 11.3.1 Benefits of Analytics in Smart Grid -- 11.3.2 Trends in the Utility Industry -- 11.4 Technologies for Smart Grid Analytics and Its Importance -- 11.4.1 Business Intelligence (BI) and Data Analysis -- 11.4.2 Other Framework Technologies-Databases Such as Apache Hadoop, MapReduce, and SQL -- 11.4.3 The Significance of Big Data in Smart Grid Analytics -- 11.5 Gaining Perceptions Through a Smart Grid and Big Data: A Case Study -- 11.5.1 Case Studies in Focus -- 11.5.2 Smart Grid Based Data Analytics Use-Cases in Europe -- 11.6 Future and Scope of Big Data Analytics in Smart Grids -- 11.6.1 Customer Acceptance and Engagement -- 11.6.2 Regulatory Policies -- 11.6.3 Innovative Structures -- 11.7 Conclusion -- References -- 12 Fake User Account Detection in Online Social Media Networks Using Machine Learning and Neural Network Techniques -- 12.1 Introduction -- 12.1.1 Statistics of Social Media Usage -- 12.1.2 Why Are Fake Profiles Created? -- 12.2 Literature Review -- 12.3 Proposed System for Detecting Fake Accounts on Twitter Using AI -- 12.3.1 Artificial Neural Network (ANN) -- 12.3.2 Support Vector Machine (SVM) -- 12.3.3 Random Forest (RF) -- 12.4 Findings and Discussions -- 12.5 Conclusion -- References -- 13 Data Analytics for Smart Grids Applications to Improve Performance, Optimize Energy Consumption, and Gain Insights -- 13.1 Introduction -- 13.2 Leveraging Smart Grids for Predictive Energy Analytics -- 13.3 Big Data Analytics for Grid Resiliency and Security. 13.4 Machine Learning Techniques for Smart Grid Optimization. |
| Record Nr. | UNINA-9910767529203321 |
Kumar Sharma Devendra
|
||
| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
ICMETE 2018 : 2nd International Conference on Micro-Electronics and Telecommunication Engineering : proceedings : Ghaziabad, India, 20-21 September 2018 / / edited by Devendra Kumar Sharma, Rohit Sharma ; technically sponsored by Institute of Electrical and Electronics Engineers
| ICMETE 2018 : 2nd International Conference on Micro-Electronics and Telecommunication Engineering : proceedings : Ghaziabad, India, 20-21 September 2018 / / edited by Devendra Kumar Sharma, Rohit Sharma ; technically sponsored by Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 |
| Descrizione fisica | 1 online resource (352 pages) |
| Disciplina | 621.381 |
| Soggetto topico |
Microelectronics
Telecommunication |
| ISBN | 1-5386-6918-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910330360203321 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
ICMETE 2018 : 2nd International Conference on Micro-Electronics and Telecommunication Engineering : proceedings : Ghaziabad, India, 20-21 September 2018 / / edited by Devendra Kumar Sharma, Rohit Sharma ; technically sponsored by Institute of Electrical and Electronics Engineers
| ICMETE 2018 : 2nd International Conference on Micro-Electronics and Telecommunication Engineering : proceedings : Ghaziabad, India, 20-21 September 2018 / / edited by Devendra Kumar Sharma, Rohit Sharma ; technically sponsored by Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 |
| Descrizione fisica | 1 online resource (352 pages) |
| Disciplina | 621.381 |
| Soggetto topico |
Microelectronics
Telecommunication |
| ISBN | 1-5386-6918-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996577842203316 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Micro-Electronics and Telecommunication Engineering [[electronic resource] ] : Proceedings of 7th ICMETE 2023 / / edited by Devendra Kumar Sharma, Sheng-Lung Peng, Rohit Sharma, Gwanggil Jeon
| Micro-Electronics and Telecommunication Engineering [[electronic resource] ] : Proceedings of 7th ICMETE 2023 / / edited by Devendra Kumar Sharma, Sheng-Lung Peng, Rohit Sharma, Gwanggil Jeon |
| Autore | Sharma Devendra Kumar |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (811 pages) |
| Disciplina | 621.382 |
| Altri autori (Persone) |
PengSheng-Lung
SharmaRohit JeonGwanggil |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Signal processing Electronics Technology - Sociological aspects Information technology Communications Engineering, Networks Electronic Circuits and Systems Signal, Speech and Image Processing Electronics and Microelectronics, Instrumentation Information and Communication Technologies (ICT) |
| ISBN | 981-9995-62-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Transportation in IoT-SDN Using Vertical Handoff Scheme -- 1 Introduction -- 2 Related Work -- 3 IoT Evolution -- 4 IoT with Transportation -- 4.1 IoT in Transportation: Applications -- 5 Intelligent Transportation Using a Vertical Handoff Method Based on Software-Defined Networks -- 6 Brief Analysis of Various Proposed Schemes and Results -- 7 Conclusion -- References -- MLP-Based Speech Emotion Recognition for Audio and Visual Features -- 1 Introduction -- 2 Review of Literature Research -- 3 Problem Statement -- 3.1 Dataset Description -- 3.2 Dataset Details -- 4 Proposed System -- 4.1 Data Exploration -- 4.2 Feature Extraction -- 5 Classifiers -- 5.1 Multi-layer Perceptron -- 5.2 Support Vector Machine -- 5.3 Random Forest Classifier -- 5.4 Decision Tree -- 6 Experimental Results -- 7 Conclusion -- References -- Drain Current and Transconductance Analysis of Double-Gate Vertical Doped Layer TFET -- 1 Introduction -- 2 Schematics of VDL-TFET -- 3 Simulations and Result -- 4 Conclusion -- References -- OpenFace Tracker and GoogleNet: To Track and Detect Emotional States for People with Asperger Syndrome -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Data Preprocessing -- 3.2 Cues Generation -- 3.3 Training Step -- 4 Results and Discussions -- 5 Conclusion -- References -- Vehicle Classification and License Number Plate Detection Using Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Proposed Model -- 4 Result -- 5 Conclusion -- References -- Car Price Prediction Model Using ML -- 1 Introduction -- 2 Literature Review -- 3 Proposed Model -- 3.1 Algorithm -- 4 Result -- 5 Conclusion -- 6 Future Scope -- References -- Effects of Material Deformation on U-shaped Optical Fiber Sensor -- 1 Introduction -- 2 Theory -- 3 Design Considerations and Results.
3.1 Sensor Characteristics -- 3.2 Evanescent Wave Absorbance -- 3.3 Sensitivity -- 4 Conclusion -- References -- Classification of DNA Sequence for Diabetes Mellitus Type Using Machine Learning Methods -- 1 Introduction -- 2 Related Works -- 3 Proposed System -- 4 Dataset -- 5 Data Preprocessing -- 5.1 Handle Missing Values -- 5.2 List to String -- 5.3 K-mer -- 5.4 Oversampling -- 5.5 Ordinal Encoding -- 5.6 Min-Max Normalization -- 6 Feature Selection -- 6.1 ANOVA -- 6.2 F-Regressor -- 6.3 Mutual Information -- 7 Classification -- 7.1 Random Forest -- 7.2 Gaussian NB -- 7.3 Support Vector Machine -- 7.4 Decision Tree -- 8 Results and Discussion -- 9 Conclusion -- References -- Unveiling the Future: A Review of Financial Fraud Detection Using Artificial Intelligence Techniques -- 1 Introduction -- 2 Literature Review -- 2.1 Machine Learning Techniques for Financial Fraud Detection -- 2.2 Deep Learning for Financial Fraud Detection -- 2.3 Ensemble Methods for Financial Fraud Detection -- 2.4 Unsupervised and Semi-supervised Learning for Financial Fraud Detection -- 2.5 Explainable AI for Financial Fraud Detection -- 2.6 Feature Selection and Feature Engineering -- 3 Models and Methodologies -- 3.1 FDS of Bayesian Learning and Dempster-Shafer Theory -- 3.2 The Evolutionary-Fuzzy System -- 3.3 Deep Artificial Neural Networks -- 3.4 BLAST-SSAHA Hybridization -- 3.5 Decision Tree -- 4 Conclusion -- References -- Remodeling E-Commerce Through Decentralization: A Study of Trust, Security and Efficiency -- 1 Introduction -- 2 Background and Related Work -- 3 Research Approach -- 3.1 Study Design -- 3.2 Proposed System Architecture -- 3.3 Implementation Methodology -- 4 Result -- 4.1 Gas Fees and Time Cost Analysis -- 4.2 Reliability Analysis -- 5 Conclusions and Future Scopes -- 5.1 Conclusions -- 5.2 Future Scopes -- References. Estimation of Wildfire Conditions via Perimeter and Surface Area Optimization Using Convolutional Neural Network -- 1 Introduction -- 2 Existing Systems -- 3 Proposed System Architecture -- 4 Module Implementation -- 4.1 Collection of Data -- 4.2 Preprocessing the Data -- 4.3 Extraction of Features -- 4.4 Evaluating the Model -- 5 Result Analysis -- 6 Conclusion -- 7 Future Enhancements -- References -- A Framework Provides Authorized Personnel with Secure Access to Their Electronic Health Records -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Security Framework -- 4 Key Features of the Proposed Security Framework -- 5 Experimental Results and Discussion -- 6 Conclusion and Future Enhancement -- References -- Explainable Artificial Intelligence for Deep Learning Models in Diagnosing Brain Tumor Disorder -- 1 Introduction -- 2 Literature Review -- 3 XAI Approaches -- 3.1 Local Interpretable Model-Agnostic Explanations (LIMEs) -- 3.2 SHapley Additive ExPlanations (SHAPs) -- 3.3 Integrated Gradients -- 3.4 Gradient-Weighted Class Activation Mapping (Grad-CAM) -- 4 Results and Discussion -- 5 Conclusion -- References -- Pioneering a New Era of Global Transactions: Decentralized Overseas Transactions on the Blockchain -- 1 Introduction -- 2 Existing Solution -- 2.1 International Wire Transfer -- 2.2 Transactions via Cryptocurrency -- 3 Proposed Solution by Conversion of Fiat Currency -- 3.1 A Unified Payment Interface Decentralized Finance App Works Globally -- 4 Conclusion -- References -- A Perspective Review of Generative Adversarial Network in Medical Image Denoising -- 1 Introduction -- 2 Related Works -- 3 Various Types of Image-Denoising Methods Using GAN -- 4 Performance Metrics -- 5 Significance of Image Denoising Utilizing GAN -- 6 Conclusion -- References -- Osteoporosis Detection Based on X-Ray Using Deep Convolutional Neural Network. 1 Introduction -- 2 Related Works -- 3 Proposed System -- 4 Methodology -- 4.1 Preprocessing -- 4.2 Smudging -- 4.3 Deep Convolutional Neural Network (DCNN) -- 5 Result Analysis and Discussion -- 6 Conclusion -- References -- Fault Prediction and Diagnosis of Bearing Assembly -- 1 Introduction -- 2 Hardware Designing -- 2.1 AC Motor -- 2.2 T-Coupling -- 2.3 Setup Holding Base -- 2.4 Ball Bearing -- 2.5 Shaft -- 2.6 Pulley and Belt -- 2.7 Load Controller -- 2.8 Electronic Weight Machine -- 2.9 NI DAQ Card -- 2.10 Vibration Sensor -- 3 Experimental Procedure -- 4 Simulation for Fault Diagnosis -- 4.1 Parameter and Operating Conditions -- 5 Result -- 5.1 Plots for Different Loads -- 6 Conclusion -- 7 Summary -- 8 Future Scope -- References -- Bearing Fault Diagnosis Using Machine Learning Models -- 1 Introduction -- 2 Methodology -- 2.1 SVM -- 2.2 SVM Kernels -- 2.3 KNN -- 2.4 Decision Tree -- 2.5 Random Forest -- 2.6 Regression -- 3 Methodology of Machine Learning Model -- 4 Techniques for Extracting and Selecting Features from Data -- 5 Relationship Between the Statistical Features -- 6 Data Description -- 7 Comparative Study of Statistical Features -- 8 Result -- 9 Conclusion -- 10 Summary -- 11 Future Scope -- References -- A High-Payload Image Steganography Based on Shamir's Secret Sharing Scheme -- 1 Introduction -- 2 Related Work -- 3 Proposed Steganography Technique -- 3.1 Secret Distributing Scheme (SDS) -- 3.2 Shamir's Secret Sharing (SSS) Scheme for Protecting Hidden Secret Information -- 3.3 Proposed PVD-Based Steganography Method -- 4 Results and Experimental Findings -- 4.1 Robustness and Varying Embedding Capacity -- 4.2 Comparative Analysis -- 5 Conclusion -- References -- Design and Comparison of Various Parameters of T-Shaped TFET of Variable Gate Lengths and Materials -- 1 Introduction -- 2 Device Structure and Simulation. 3 Comparative Analysis on Devices and Discussion -- 3.1 ON Current and OFF Current -- 3.2 Subthreshold Swing (SSavg) -- 3.3 Transconductance (gm) -- 4 Results -- 4.1 Transfer Characteristics of Device -- 4.2 Transconductance Analysis (gm) -- 4.3 Band-to-Band Tunneling -- 4.4 Electric Field -- 4.5 Surface Potential -- 5 Conclusion -- References -- Experiment to Find Out Suitable Machine Learning Algorithm for Enzyme Subclass Classification -- 1 Introduction -- 2 Background -- 3 Brief Description of Methods Used in the Study -- 3.1 Experiment Using Logistic Regression Model -- 3.2 Experiment Using SVM -- 3.3 Experiment Using Random Forest -- 4 Computational Procedure -- 5 Data -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- Iris Recognition Method for Non-cooperative Images -- 1 Introduction -- 2 Structure of Iris -- 3 Iris Segmentation -- 4 Literature Review -- 5 Methodology -- 5.1 Image Acquisition -- 5.2 Segmentation -- 5.3 Iris Normalization -- 5.4 Features Extraction (Iris Code) -- 5.5 Matching -- 6 Results -- 7 Conclusions -- References -- An Exploration: Deep Learning-Based Hybrid Model for Automated Diagnosis and Classification of Brain Tumor Disorder -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- Recognition of Apple Leaves Infection Using DenseNet121 with Additional Layers -- 1 Introduction -- 2 DenseNet with Additional Layers -- 2.1 Preprocessing -- 2.2 Architecture -- 3 Dataset -- 4 Results -- 5 Conclusion -- References -- Techniques for Digital Image Watermarking: A Review -- 1 Introduction -- 2 Watermarking Techniques -- 3 Foundations of Presented Work -- 4 Process of Watermarking -- 5 Characteristics of Watermarking -- 6 Parameters of Quality Evaluation -- 7 Applications of the Image Watermarking -- 8 Conclusion -- References. Improved Traffic Sign Recognition System for Driver Safety Using Dimensionality Reduction Techniques. |
| Record Nr. | UNINA-9910845496103321 |
|
Sharma Devendra Kumar
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Micro-Electronics and Telecommunication Engineering [[electronic resource] ] : Proceedings of 3rd ICMETE 2019 / / edited by Devendra Kumar Sharma, Valentina Emilia Balas, Le Hoang Son, Rohit Sharma, Korhan Cengiz
| Micro-Electronics and Telecommunication Engineering [[electronic resource] ] : Proceedings of 3rd ICMETE 2019 / / edited by Devendra Kumar Sharma, Valentina Emilia Balas, Le Hoang Son, Rohit Sharma, Korhan Cengiz |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XVI, 735 p. 413 illus., 305 illus. in color.) |
| Disciplina | 621.381 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Electronics
Microelectronics Power electronics Electrical engineering Artificial intelligence Electronics and Microelectronics, Instrumentation Power Electronics, Electrical Machines and Networks Communications Engineering, Networks Artificial Intelligence |
| ISBN | 981-15-2329-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Radio Direction Finding techniques for an Unmanned Aerial Vehicle -- Translation into Pali language from Brahmi Script -- A Fractal Boundary Wideband Antenna with DGS for X-Band Application -- An Approach to Automated Spam Detection Using Deep Neural Network and Machine Learning Classifiers -- Handling Sparsity in Cross Domain Recommendation Systems: Review -- Daily Rainfall Prediction Using Nonlinear Autoregressive Neural Network -- Adiabatic Design Implementation of Digital Circuits for Low Power Applications -- Parametric Classification of Dynamic Community Detection Techniques -- Survey on the Impact of FSM Design for High-performance Architecture Evaluation -- Design of Configurable Analog Block based Oscillator and Possible Applications -- Classification of Pre-diabetes and Healthy Subjects in Plantar Infrared Thermal Imaging Using Various Machine Learning Algorithms. |
| Record Nr. | UNINA-9910383834003321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multimedia technologies in the Internet of things environment . Volume 3 / / edited by Raghvendra Kumar, Rohit Sharma, and Prasant Kumar Pattnaik
| Multimedia technologies in the Internet of things environment . Volume 3 / / edited by Raghvendra Kumar, Rohit Sharma, and Prasant Kumar Pattnaik |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (237 pages) |
| Disciplina | 004.678 |
| Collana | Studies in Big Data |
| Soggetto topico |
Artificial intelligence
Internet of things Multimedia systems |
| ISBN | 981-19-0924-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910558489003321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multimedia technologies in the internet of things environment / / edited by Raghvendra Kumar, Rohit Sharma, Prasant Kumar Pattnaik
| Multimedia technologies in the internet of things environment / / edited by Raghvendra Kumar, Rohit Sharma, Prasant Kumar Pattnaik |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XVIII, 208 p. 88 illus., 57 illus. in color.) |
| Disciplina | 929.605 |
| Collana | Studies in Big Data |
| Soggetto topico |
Multimedia systems
Big data Computational intelligence |
| ISBN | 981-15-7965-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Smart Control and Monitoring of Irrigation System using Internet of Things -- Chapter 2. Blockchain-based Cyber Threat Mitigation Systems for Smart Vehicles and Industrial Automation -- Chapter 3. IT Convergence related Security Challenges for Internet of Things and Big Data -- Chapter 4. Applicability of Industrial IoT in Diversified Sectors: Evolution, Applications and Challenges -- Chapter 5. Recent emergine for inteliigent learning and analytics in Big data -- Chapter 6. Real Time Health System (RTHS) centered Internet of Things (IoT) in healthcare industry: benefits, use cases and advancements in 2020 -- Chapter 7. Building intelligent Integrated Development Environment for IoT in the context of Statistical modeling for Software Source code -- Chapter 8. Visualization of COVID-19 Pandemic: an Analysis through Machine Intelligent Technique towards Big Data Paradigm -- Chapter 9.Multimedia Security and Privacy on Real Time Behavioral Monitoring in Machine Learning IoT Application using Big Data Analytics Chapter 10. A robust approach with text analytics for bengalir digit recgnition using mechine learning -- Chapter 11. Internet of Things Based Security Model and Solutions for Educational Systems. |
| Record Nr. | UNINA-9910484574303321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multimedia Technologies in the Internet of Things Environment, Volume 2
| Multimedia Technologies in the Internet of Things Environment, Volume 2 |
| Autore | Kumar Raghvendra |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
| Descrizione fisica | 1 online resource (242 pages) |
| Altri autori (Persone) |
SharmaRohit
PattnaikPrasant Kumar |
| Collana | Studies in Big Data Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-16-3828-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910497102903321 |
|
Kumar Raghvendra
|
||
| Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
New trends and applications in Internet of things (IoT) and big data analytics / / Rohit Sharma, Dilip Kumar Sharma, editors
| New trends and applications in Internet of things (IoT) and big data analytics / / Rohit Sharma, Dilip Kumar Sharma, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (278 pages) |
| Disciplina | 004.678 |
| Collana | Intelligent Systems Reference Library |
| Soggetto topico |
Big data - Economic aspects
Internet of things |
| ISBN | 3-030-99329-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910568299603321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
