Advances in electronics, communication and computing : select proceedings of ETAEERE 2020 / / Pradeep Kumar Mallick [and three others], editors |
Edizione | [1st ed. 2021.] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (XX, 675 p. 350 illus., 250 illus. in color.) |
Disciplina | 621.3 |
Collana | Lecture notes in electrical engineering |
Soggetto topico |
Electrical engineering
Telecommunication systems Computer networks |
ISBN | 981-15-8752-3 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Realization of Security System Using Facial Recognition and Arduino Keypad Door Lock System -- Analysis of t-distribution in Variable Step Size Firefly Algorithm in the Applications of Machine Learning -- Detecting Vulnerabilities of Web Application using Penetration Testing and Prevent using Threat Modeling -- Analysis and Comparison of Credit Card Fraud Detection Using Machine Learning -- Data Hiding Technique using Di erential Evolution -- Intelligent Baby Monitoring System using Blynk -- Implementation of Dual Image Watermarking for Copyright Protection -- Biswaranjan Acharya, Roshan Gupata, Shankey Garg, Jitendra Kumar Rout and Niranjan Ray -- Bengali spoken numerals recognition by MFCC and GMM technique -- Chittaranjan Pradhan Detection and Evaluation of Chronic Kidney Disease using Different Regression and Classification Algorithms in Machine Learning -- Analysis and Prevention Of Road Accidents. . |
Record Nr. | UNINA-9910483570603321 |
Singapore : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Advances in electronics, communication and computing : select proceedings of ETAEERE 2020 / / Pradeep Kumar Mallick [and three others], editors |
Edizione | [1st ed. 2021.] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (XX, 675 p. 350 illus., 250 illus. in color.) |
Disciplina | 621.3 |
Collana | Lecture notes in electrical engineering |
Soggetto topico |
Electrical engineering
Telecommunication systems Computer networks |
ISBN | 981-15-8752-3 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Realization of Security System Using Facial Recognition and Arduino Keypad Door Lock System -- Analysis of t-distribution in Variable Step Size Firefly Algorithm in the Applications of Machine Learning -- Detecting Vulnerabilities of Web Application using Penetration Testing and Prevent using Threat Modeling -- Analysis and Comparison of Credit Card Fraud Detection Using Machine Learning -- Data Hiding Technique using Di erential Evolution -- Intelligent Baby Monitoring System using Blynk -- Implementation of Dual Image Watermarking for Copyright Protection -- Biswaranjan Acharya, Roshan Gupata, Shankey Garg, Jitendra Kumar Rout and Niranjan Ray -- Bengali spoken numerals recognition by MFCC and GMM technique -- Chittaranjan Pradhan Detection and Evaluation of Chronic Kidney Disease using Different Regression and Classification Algorithms in Machine Learning -- Analysis and Prevention Of Road Accidents. . |
Record Nr. | UNISA-996464406803316 |
Singapore : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Cognitive informatics and soft computing : proceeding of CISC 2020 / / editors, Pradeep Kumar Mallick [and three others] |
Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (960 pages) |
Disciplina | 006.3 |
Collana | Advances in intelligent systems and computing |
Soggetto topico |
Soft computing
Informàtica tova Intel·ligència artificial |
Soggetto genere / forma |
Congressos
Llibres electrònics |
ISBN | 981-16-1056-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Editorial Board Members -- Preface -- Contents -- About the Editors -- A Hybrid Face Recognition Scheme in a Heterogenous and Cluttered Environment -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 4 Dataset Descriptions -- 5 Result Analysis -- 6 Conclusion and Future Works -- References -- Smart Critical Patient Care System with Doctor and Bystander Support with Wireless Sensor Network Using IoT and Intelligent Recommender Algorithm -- 1 Introduction -- 1.1 Related Work -- 2 Problem Identification -- 3 Methodology -- 4 Result and Discussion -- 5 Conclusion and Future Work -- References -- IoT-Enabled Toxic Gas Detection and Alarming System Using Wireless Sensor Network with TAGDS Smart Algorithm -- 1 Introduction -- 1.1 Related Work -- 2 Problem Identification -- 3 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- A Deep Neural Network Model for Effective Diagnosis of Melanoma Disorder -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Sentiment Analysis and Evaluation of Movie Reviews Using Classifiers -- 1 Introduction -- 2 Literature Review -- 3 Proposed Model -- 4 Result Analysis -- 5 Conclusion -- References -- Risk Factors Analysis for Real Estate Price Prediction Using Regression Approach -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Result and Analysis -- 4.1 Implementation of Multiple Regression -- 4.2 Implementation of Stepwise Regression -- 4.3 Implementation of Support Vector Regression -- 5 Parameter for Performance Analysis -- 6 Conclusion -- References -- A Support Vector Machine Approach for Effective Bicycle Sharing in Urban Zones -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Pre-processing -- 4 Proposed Prediction Model.
5 Conclusion and Future Work -- References -- Biosensor for Stress Detection Using Machine Learning -- 1 Introduction -- 1.1 Brief About Biosensors -- 1.2 Objectives of the Study -- 1.3 Applications of Biosensors and Types of Biosensors -- 1.4 Advantages and Disadvantages of Biosensors -- 2 Stress Detection Using Biosensors and Other Applications: Literature Review -- 2.1 Stress Detection: Aspects and Its Use -- 2.2 Related Work and Case Studies About Stress Detection Using Biosensors -- 3 Machine Learning Model Used in Biosensor Design -- 3.1 Data Pre-processing -- 3.2 Feature Extraction and Dimension Reduction -- 3.3 Feature Subset Selection -- 4 Various Challenges of Using ML in Biosensor Design -- 5 Conclusion and Future Work -- References -- An Accurate Automatic Traffic Signal Detector Using CNN Model -- 1 Introduction -- 2 Literature Survey -- 3 Dataset Description -- 4 Proposed Work/model with Description -- 4.1 Preparing the Training Dataset -- 4.2 Proposed Machine Learning Model -- 5 Result and Analysis -- 6 Conclusion -- References -- Classification of Arrhythmia Through Heart Rate Variability Using Logistic Regression -- 1 Introduction -- 2 Materials and Methods -- 2.1 ECG Database -- 2.2 Plotting -- 2.3 Preprocessing -- 2.4 Thresholding -- 2.5 Peak Points Detection in Ecg Signal -- 2.6 Feature Extraction -- 2.7 HRV Analysis -- 3 Classification -- 4 Conclusion -- References -- U-INS: An Android-Based Navigation System -- 1 Introduction -- 2 Related Works -- 3 Proposed System -- 4 Result and Discussion -- 5 Conclusion and Future Work -- References -- LSTM-Based Cardiovascular Disease Detection Using ECG Signal -- 1 Introduction -- 2 Research Gap, Motivation and Objectives -- 2.1 Research Gap -- 2.2 Motivation -- 2.3 Objective -- 2.4 Organization -- 3 Source and Details of the Data -- 4 Development of the Proposed LSTM Detection Method. 5 Simulation-Based Experimental Results and Discussion -- 6 Conclusion -- References -- Network Intrusion Detection Using Genetic Algorithm and Predictive Rule Mining -- 1 Introduction -- 2 Related Work -- 3 Intrusion Detection System -- 3.1 Drawbacks of the Existing System -- 4 Proposed Work: IDS Using Genetic Algorithm and Predictive Rule Mining -- 4.1 NSL-KDD Dataset -- 4.2 Feature Selection and Predictive Rule Mining -- 4.3 Data Representation -- 4.4 Evaluation Function -- 4.5 Genetic Operators -- 5 Implementation and Testing -- 6 Results and Discussion -- 6.1 Comparative Analysis -- 7 Conclusion and Future Work -- References -- A Comparison of Different Methodologies for Predicting Forest Fires -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Comparison of Results -- 5 Conclusion and Future Scope -- References -- Isolated Converters as LED Drivers -- 1 Introduction -- 2 Literature Survey -- 3 Specifications of LED Down Light -- 4 Mathematical Modeling of Flyback Converter -- 4.1 Calculation of Inductance and Capacitance -- 5 Closed Loop Operation -- 6 Mathematical Modeling of Forward Converter -- 6.1 Calculation of Inductance and Capacitance -- 7 Closed Loop Operation of Forward Converter -- 8 Results and Conclusion -- 9 Recommendation for Further Research -- References -- Fractional Order Elliptic Filter Implemented Using Optimization Technique -- 1 Introduction -- 1.1 Literature Review -- 1.2 The Objective of the Proposed Work -- 2 Optimization of Proposed Filter -- 3 Sensitivity and Stability Analysis -- 4 Simulink Simulations -- 5 Comparative Analysis -- 6 Analog Realization of Proposed Filter -- 7 Conclusion -- References -- Energy-Efficient MPLS-MANET Using Ant Colony Optimization and Harmony Search Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Multi-Protocol Local Switching -- 4 ACO-HSA Methodology. 4.1 Deployment of Routers -- 4.2 Optimal Paths Selection Using Ant Colony Optimization -- 4.3 Path Optimization Using Harmony Search Algorithm -- 4.4 Derivation of Fitness Function -- 5 Results and Discussion -- 5.1 Performance Analysis -- 5.2 Comparative Analysis -- 6 Conclusion -- References -- Performance Evaluation of Novel Feature Selection Method for Classification of Diabetic Drugs Based on Twitter Data Using SVM Algorithm -- 1 Introduction -- 2 Related Works -- 3 Feature Selection: An Overview -- 3.1 Genetic Algorithm (GA) -- 3.2 Particle Swarm Optimization (PSO) -- 3.3 Glowworm Swarm Optimization (GSO) Algorithm -- 4 Classification: SVM -- 5 Results and Discussions -- 5.1 Dataset -- 5.2 Experiments and Results -- 5.3 Evaluation Accuracy -- 5.4 Time Analysis -- 5.5 Summary of Related Articles with Social Media, Feature Selection and Classification Algorithm -- 6 Conclusion -- References -- Enhancing Periodic Storage Performance in IoT-Based Waste Management -- 1 Introduction -- 2 Related Works -- 3 Methodology and Materials -- 3.1 Block Diagram -- 3.2 Hardware Components -- 3.3 Software Tools -- 3.4 Interface -- 3.5 K-Means -- 3.6 Optimizing Periodic Clean-Ups and Dustbin Placement -- 4 Results and Analysis -- 4.1 Standard Deviation -- 4.2 Range -- 4.3 Levels of Result -- 5 Conclusion -- References -- Oil Spill Detection and Confrontation Using Instance Segmentation and Swarm Intelligence -- 1 Introduction -- 1.1 Preface -- 1.2 Problem Definition -- 2 Literature Survey -- 3 Methodology -- 3.1 Design -- 3.2 Implementation -- 3.3 Specifications -- 3.4 Working -- 4 Results -- 5 Conclusion -- References -- Impact of a Parameter Selection Using eARIMA and Ensemble by SKMC in Time Series Data Analysis -- 1 Introduction -- 2 Literature Review -- 3 Time Series Analysis -- 4 Methodology -- 4.1 eARIMA Weightage Index. 4.2 Segment K-Means Cluster Algorithm -- 5 Result and Discussion -- 6 Conclusion -- References -- Secure Transfer of Images Using Pixel-Level and Bit-Level Permutation Based on Knight Tour Path Scan Pattern and Henon Map -- 1 Introduction -- 2 Related Work -- 2.1 Knight Tour Path -- 2.2 Mutation Rule -- 2.3 Henon Map -- 2.4 Tent Map -- 2.5 Knight Travel Path Based Pixel Permutation -- 3 Proposed Method -- 4 Performance Analysis of Proposed Scheme -- 5 Discussion -- 6 Conclusion -- References -- Performance Analysis of Irregular Shaped MEMS Switch with Gold and Aluminum as Composite Cantilever Beam Material -- 1 Introduction -- 2 Switch Design and Description -- 3 Simulation Results -- 3.1 Effect of Varying Irregular Shaped Cantilever Thickness on the Pull-in Voltage -- 3.2 Effect of Varying Cantilever Length Between the Upper Cantilever and Bottom Electrode on the Pull-in Voltage -- 3.3 Effect of Varying Airgap on the Pull-in Voltage -- 3.4 Effect of Perforations on Pull-in Voltage -- 4 Conclusion -- References -- Gesture-Controlled System Using Convolutional Neural Network -- 1 Introduction -- 2 Literature Survey -- 3 System Model -- 3.1 Methodology -- 3.2 Flowchart -- 3.3 Proposed Work -- 4 Applications -- 5 Results and Discussion -- 6 Conclusion -- References -- A Survey on Security and Safety in Vehicular Ad hoc Networks (VANETs) Cloud -- 1 Introduction -- 2 VANET Cloud Architecture -- 3 Application of VANET Cloud -- 4 Issues in VANET Cloud -- 4.1 Architecture Creation of VANET Cloud -- 4.2 Issues in Privacy and Security of VANET Cloud -- 4.3 Issues in Policy and Operational Management -- 5 Security Challenges in VANET Cloud -- 6 Safety Challenges in VANET Cloud -- 7 Discussion -- 8 Conclusion -- References -- Overview and Analysis of RPL Protocol Objective Functions -- 1 Introduction -- 2 Related Works -- 3 An Overview of RPL. 3.1 Control Messages. |
Record Nr. | UNINA-9910488701903321 |
Gateway East, Singapore : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Electronic systems and intelligent computing : proceedings of ESIC 2020 / / Pradeep Kumar Mallick [and three others] editors |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2020] |
Descrizione fisica | 1 online resource (XXVI, 1154 p. 690 illus., 495 illus. in color.) |
Disciplina | 006.3 |
Collana | Lecture Notes in Electrical Engineering |
Soggetto topico |
Artificial intelligence
Computer networks |
ISBN | 981-15-7031-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | A Reliable and Secure Wireless Network for VoIP Application -- Interdisciplinary Approaches Incorporating Computational Intelligence in Modern Pharmacognosy to Address Biological Problems -- Solar Power Plant Site Selection: A Systematic Literature Review on MCDM Techniques Used -- Biometrics Based Pig Identification: From Invention to Commercialisation -- Optimal Placement of FACTS Devices in the Power System Using ANN to Increase the System Loadability -- Impact of Noise Levels on SVM-GMM based Speaker Recognition System -- Implementation of Perturbation Based MPPT Technique Using Model Based Design -- Modified Aggressive Packet Combining Scheme with Repetition Code for Throughput Enhancement in High Error Rate Channel -- Development of Image Based Disease Scale of Phoma Blight of Potato using K-means Clustering. |
Record Nr. | UNINA-9910427685103321 |
Singapore : , : Springer, , [2020] | ||
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Lo trovi qui: Univ. Federico II | ||
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Electronic systems and intelligent computing : proceedings of ESIC 2020 / / Pradeep Kumar Mallick [and three others] editors |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2020] |
Descrizione fisica | 1 online resource (XXVI, 1154 p. 690 illus., 495 illus. in color.) |
Disciplina | 006.3 |
Collana | Lecture Notes in Electrical Engineering |
Soggetto topico |
Artificial intelligence
Computer networks |
ISBN | 981-15-7031-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | A Reliable and Secure Wireless Network for VoIP Application -- Interdisciplinary Approaches Incorporating Computational Intelligence in Modern Pharmacognosy to Address Biological Problems -- Solar Power Plant Site Selection: A Systematic Literature Review on MCDM Techniques Used -- Biometrics Based Pig Identification: From Invention to Commercialisation -- Optimal Placement of FACTS Devices in the Power System Using ANN to Increase the System Loadability -- Impact of Noise Levels on SVM-GMM based Speaker Recognition System -- Implementation of Perturbation Based MPPT Technique Using Model Based Design -- Modified Aggressive Packet Combining Scheme with Repetition Code for Throughput Enhancement in High Error Rate Channel -- Development of Image Based Disease Scale of Phoma Blight of Potato using K-means Clustering. |
Record Nr. | UNISA-996465468703316 |
Singapore : , : Springer, , [2020] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Hybrid artificial intelligence and IoT in healthcare / / edited by Akash Kumar Bhoi, Pradeep Kumar Mallick, Mihir Narayana Mohanty |
Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (341 pages) |
Disciplina | 060 |
Collana | Intelligent Systems Reference Library |
Soggetto topico |
Internet of things
Artificial intelligence - Medical applications Intel·ligència artificial en medicina Internet de les coses |
Soggetto genere / forma | Llibres electrònics |
ISBN | 981-16-2972-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Hybrid Cloud/Fog Environment for Healthcare: An Exploratory Study, Opportunities, Challenges, and Future Prospects -- 1 Introduction -- 2 Applications of Cloud Computing in Smart Healthcare System -- 3 Applications of Fog Computing in Smart Healthcare System -- 4 Challenges of Cloud and Fog Computing in Smart Healthcare System -- 5 The Future Prospects of Cloud and Fog Computing -- 6 Conclusion and Future Research Directions -- References -- Hybrid Intelligent System for Medical Diagnosis in Health Care -- 1 Introduction -- 1.1 Intelligent Systems -- 1.2 Hybrid Intelligent System -- 1.3 Health Care -- 2 Need for Health Care's Intelligent Infrastructure for Medical Diagnosis -- 2.1 Basic Algorithm -- 2.2 Applications in Diagnosis -- 3 Hybrid Intelligent Medical Diagnosis System -- 3.1 Adaptive Neuro-Fuzzy Inference Systems (ANFIS) -- 3.2 Ensemble Approaches -- 3.3 Evolutionary Artificial Neural Network -- 3.4 Application of Hybrid Intelligent System in Health Care -- 4 Need of Hybrid Intelligent System in Medical Diagnosis -- 5 Conclusion -- References -- Remote Patient Monitoring Using IoT, Cloud Computing and AI -- 1 Cloud-Oriented IoT Using AI -- 1.1 Introduction to Internet of Things -- 1.2 Cloud Computing (CC) -- 1.3 Artificial Intelligence (AI) -- 1.4 Deep Learning Architecture -- 2 Wireless Body Networks (WBN) -- 2.1 Overview -- 2.2 Architecture and Applications -- 2.3 Hybrid Sensor-Based Healthcare Systems -- 3 Cloud Infrastructure and Processing -- 3.1 Overview -- 3.2 Topology and Network Protocol for Remote Monitoring -- 3.3 Cloud Infrastructure -- 3.4 Cloud Computing Components and Characteristics -- 4 Challenges in Cloud and AI-Based IoT on Remote Monitoring -- 4.1 Overview -- 4.2 Accessing Cloud with Validation -- 4.3 Block Chain-Oriented Healthcare Records.
4.4 Reliability and Complexity in Computational Intelligence -- 5 Case Studies -- 5.1 IoT-Based Remote Pain Monitoring System: From Device to Cloud Platform [27] -- 5.2 Internet of Things Sensor Assisted Security and Quality Analysis for Healthcare Datasets Using Artificial Intelligent-Based Heuristic Health Management System [28] -- 5.3 A Survey on Deep Transfer Learning to Edge Computing for Mitigating the COVID-19 Pandemic [29] -- References -- An Analytical Study of the Role of M-IoT in Healthcare Domain -- 1 Introduction to IoT and Healthcare -- 2 Integration of M-IOT in Healthcare -- 3 Working Principle of M-IOT in Healthcare -- 4 Comparative Analysis of Existing M-IoT Technologies -- 5 Applications of M-IOT Devices in Healthcare -- 6 Benefits of M-IoT -- 7 Challenges of M-IoT -- 8 Relevant Studies on M-IoT in Healthcare -- 9 Discussion of the Use M-IoT in Cancer Detection -- 10 M-IoT in Blood Pressure Measurement from Heart Rate -- 11 Conclusion and Future Scope -- References -- Hybrid AI and IoT Approaches Used in Health Care for Patients Diagnosis -- 1 Introduction -- 2 Methodology Used -- 3 Conclusion -- References -- RADIoT: The Unifying Framework for IoT, Radiomics and Deep Learning Modeling -- 1 Introduction -- 2 The Internet of Things (IoT) in smart healthcare system -- 2.1 Internet of Things (IoT) for Radiomics -- 3 The Radiomics -- 3.1 Dataset Acquisition -- 3.2 Volume of Interests (VOIs) Segmentation -- 3.3 Feature Mining -- 3.4 Feature Selection -- 3.5 Model Development -- 4 Machine Learning Models for Radiomics -- 4.1 Traditional ML Models -- 4.2 Deep Learning (DL) Models -- 4.3 Performance Indicators for ML Models -- 5 Challenges, Open Issues and Opportunities -- 5.1 Challenges of Handicraft Radiomics -- 5.2 Challenges of Deep Learning for Radiomics Analysis -- 5.3 Challenges of IoT in Radiomics. 5.4 Open Issues and Opportunities -- 6 Implementation -- 6.1 The RADIoT Unifying Radiomics Framework -- 6.2 Feature Selection -- 6.3 Classification Results and Discussion -- 7 Conclusion and Future Research Directions -- References -- Hybrid Artificial Intelligence and IoT in Health care for Cardiovascular Patient in Decision-Making System -- 1 Introduction -- 1.1 Comprehensive Health Care Systems -- 1.2 Connected eHealth Mobile Applications -- 1.3 Artificial Intelligence -- 2 Data Source -- 2.1 Analysis of Data -- 3 Materials and Methods -- 3.1 Data Gathering -- 3.2 Feature Selection -- 3.3 Classification -- 4 Various Machine Learning Algorithms -- 4.1 Logistic Regression -- 4.2 Naïve Bayes -- 4.3 Random Forest -- 4.4 Support Vector Machine -- 4.5 Gradient Boosting -- 4.6 Accuracy Module -- 5 Results and Discussion -- 6 Conclusion -- References -- A Smart Assistive System for Visually Impaired to Inform Acquaintance Using Image Processing (ML) Supported by IoT -- 1 Introduction -- 2 Related Work -- 3 System Design -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Internet of Things in Health Care: A Survey -- 1 Introduction -- 2 Classification and Overview -- 2.1 Based on Privacy and Security Techniques -- 2.2 Based on e-Health and m-Health -- 2.3 Based on Cloud, Fog, and Evolutionary Computing -- 2.4 Based on Network and Communication Techniques -- 2.5 Based on System Design and Architecture -- 3 Classification Based on Optimization Goal and Evaluation Platform -- 4 IoT Techniques -- 4.1 Access and Authentication -- 4.2 Compression and Encryption -- 4.3 E-health and M-health -- 4.4 Big Data and Cloud Computing -- 4.5 Evolutionary Computing Algorithms -- 4.6 Fog and Cloud Computing -- 4.7 Network and Communication -- 4.8 System Design and Architecture -- 5 Conclusion and Future Outlook -- References. Disease Diagnosis System for IoT-Based Wearable Body Sensors with Machine Learning Algorithm -- 1 Introduction -- 2 The General Overview of IoT-Based Applications in Smart Healthcare System -- 3 The Applications of Wearable Body Sensors in Smart Healthcare System -- 4 IoT-Wearable Body Sensors-Based Framework with Machine Learning Algorithm for Disease Diagnosis -- 5 The Application of Machine Learning for the Diagnosis of Heart Diseases as Case Study -- 5.1 The Heart Disease Dataset Characteristics -- 5.2 Performance Evaluation Metrics -- 6 Results and Discussion -- 6.1 The Precision-Recall Curve (PRC) -- 6.2 Confusion Matrix -- 7 Conclusion and Future Research Directions -- References -- Integration of Machine Learning and IoT in Healthcare Domain -- 1 Healthcare Viewpoint -- 1.1 Machine Learning in Health Care -- 1.2 IoT in Health Care -- 2 Renowned Machine Learning Application in the Field of Health Care -- 2.1 Identifying Disease and Diagnosis -- 2.2 Machine Learning in Radiology -- 2.3 Clinical Trial and Research -- 2.4 Outbreak Prediction -- 3 Internet of Things (IoT) Applications in Clinical Domain -- 3.1 Depression Monitoring Apple Watch App -- 3.2 Coagulation Testing -- 3.3 Medical Information Distribution -- 3.4 Emergency Care -- 4 A General Architecture for IoMT Systems -- 5 Various Extensive Studies Conducted -- 6 Review of IoMT Monitoring Solutions -- 6.1 Physiological Analysis -- 6.2 IoMT Solutions in Rehabilitation Systems -- 6.3 Assessing of Diet Intake and Skin Pathology -- 6.4 Treatments Pertaining to the Spread of Epidemics and Their Diagnosis -- 6.5 Diagnosis and Treatment of Diabetes -- 7 Trends and Discussions About Applications -- 8 A Smart Predictive Framework for Disease Risk Factors Detection -- 9 Summary -- References -- Managing Interstitial Lung Diseases with Computer-Aided Visualization -- 1 Introduction. 2 ILD Diagnosis -- 2.1 HRCT Patterns -- 2.2 ILD Diagnosis Summary -- 2.3 ILD Treatment Algorithms -- 3 Computer-Aided Techniques -- 3.1 Regression -- 3.2 Hidden Markov Models -- 3.3 Neural Networks -- 3.4 Complex Networks -- 3.5 Layout Algorithm Selection -- 4 Conclusion -- References -- Use of Machine Learning Algorithms to Identify Sleep Phases Starting from ECG Signals -- 1 Introduction -- 2 Related Works -- 3 The Database -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Numerical Results -- 4.3 Statistical Analysis -- 5 Summary/Conclusion -- References -- Emerging Technologies for Pandemic and Its Impact -- 1 Introduction -- 2 Surveillance -- 2.1 Location Data -- 2.2 Health Tracking Mobile Applications -- 2.3 Robotic Diagnostic System -- 2.4 Robotic Patrolling System -- 3 Healthcare -- 3.1 3D Printing Supplies -- 3.2 Advanced Isolation Cubicles with Automation -- 3.3 Autonomous Vehicles -- 3.4 Cobotics for Treatment -- 4 Economy -- 4.1 3D Remote Work with XR (AR or VR) -- 4.2 Sanitization Systems for Essential Workers -- 5 Lockdown -- 5.1 Drones -- 5.2 AI Based Entertainment Streaming -- 5.3 Automation and Innovation in Cleaning -- 6 Education -- 6.1 Interactive Mixed Reality (MR) Classrooms -- 6.2 AI for Analyzing Student Mental Health -- 7 Conclusion -- References -- Impact of Artificial Intelligence in Health care: A Study -- 1 Introduction -- 1.1 Autonomous Vehicles -- 1.2 Cybersecurity -- 1.3 Agriculture -- 1.4 Social Media and Gaming -- 1.5 Military -- 1.6 Finance and Business -- 2 AI in Health care -- 3 Existing Applications Integrating AI in the Healthcare Sector -- 3.1 Virtual Nurses and Digital Consultation -- 3.2 Robots -- 3.3 Cybersecurity -- 3.4 Administration and Workflow -- 3.5 Dosage and Treatment Design -- 3.6 Fraud Detection -- 3.7 Health Monitoring -- 3.8 Drug Creation and Clinical Trial Participation. 3.9 Treatment Design and Precision Medicine. |
Record Nr. | UNINA-9910495204203321 |
Singapore : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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