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Blockchain Applications in Healthcare : Innovations and Practices
| Blockchain Applications in Healthcare : Innovations and Practices |
| Autore | Choudhury Tanupriya |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2023 |
| Descrizione fisica | 1 online resource (254 pages) |
| Altri autori (Persone) |
KhannaAbhirup
ChatterjeePrasenjit UmJung-Sup BhattacharyaAbhishek |
| ISBN |
1-394-22951-8
1-394-22949-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Foreword -- Preface -- Acknowledgments -- Chapter 1. Framework for Blockchain in Healthcare -- 1.1. Concept of Blockchain -- 1.2. Blockchain as distributed database -- 1.3. Architecture of Blockchain in healthcare -- 1.4. Development of Blockchain: A state of art -- 1.5. Information distribution in Blockchain -- 1.6. The growing anticipation of Blockchain -- 1.6.1. Challenges faced by Blockchain -- 1.7. The benefits of Blockchain in healthcare -- 1.8. Open issues related to Blockchain -- 1.9. Future trends of Blockchain -- 1.10. References -- Chapter 2. Role of Smart Contracts in Blockchain -- 2.1. Introduction to Blockchain -- 2.1.1. Types of Blockchain -- 2.1.2. Characteristics of Blockchain -- 2.2. Smart contracts -- 2.2.1. Operating mechanism of smart contracts -- 2.2.2. Applications of smart contracts -- 2.2.3. Programming languages and platforms -- 2.3. Quantitative analysis -- 2.3.1. Results -- 2.4. Role of smart contracts in healthcare -- 2.4.1. Health Insurance -- 2.4.2. Healthcare -- 2.4.3. Telemedicine -- 2.5. Example of smart contracts -- 2.5.1. Simple open auction -- 2.5.2. Voting -- 2.5.3. Patient record -- 2.6. Challenges related to smart contracts -- 2.6.1. Contract vulnerabilities -- 2.6.2. Privacy and legal issues -- 2.6.3. Immutability issue -- 2.7. Conclusion -- 2.8. References -- Chapter 3. Blockchain-based Platforms for the Healthcare Industry -- 3.1. Introduction -- 3.2. Literature review -- 3.3. Blockchain technology -- 3.3.1. Uses of Blockchain in the healthcare sector -- 3.4. Blockchain applications that can be useful for treating the medical sector problems -- 3.4.1. Smart contracts -- 3.4.2. Fraud detection -- 3.4.3. Identity verification -- 3.5. Examples of healthcare platforms using Blockchain -- 3.5.1. Data sharing using Gem Health Network -- 3.5.2. MeDshare.
3.5.3. OmniPHR -- 3.6. Blockchain during the Covid-19 pandemic -- 3.7. Conclusion -- 3.8. References -- Chapter 4. Analyzing and Modeling the Challenges Faced by the Healthcare Sector in the Adoption Process of Blockchain Technologies -- 4.1. Introduction -- 4.2. Literature review -- 4.2.1. Blockchain in healthcare -- 4.3. Challenges of Blockchain in healthcare -- 4.3.1. Technical challenges (TC) -- 4.3.2. Social challenges (SC) -- 4.3.3. Organizational challenges (OC) -- 4.4. Research methodology -- 4.5. Data analysis -- 4.6. Discussion -- 4.7. Conclusion -- 4.8. References -- Chapter 5. Blockchain as an Effective Technology in Maintaining Electronic Health Record Systems -- 5.1. Introduction -- 5.2. Background concepts on Blockchain technology -- 5.2.1. Consensus algorithms -- 5.2.2. Types of Blockchain -- 5.2.3. Smart contracts -- 5.2.4. Features of Blockchain -- 5.2.5. Applications of Blockchain technology -- 5.3. Blockchain in healthcare -- 5.4. Electronic health records using Blockchain -- 5.5. Quantitative analysis -- 5.5.1. Results -- 5.6. Proposed framework for the EHRs using Blockchain -- 5.6.1. System workflow -- 5.7. Issues in Blockchain-based EHRs -- 5.8. Case studies -- 5.8.1. MedRec -- 5.8.2. AI-based solution for EHRs -- 5.8.3. Improving medical record keeping with Blockchain -- 5.9. Conclusion -- 5.10. References -- Chapter 6. An Optimistic Approach to Share Private Health Records Using Blockchain Technology -- 6.1. Introduction -- 6.2. Related work -- 6.2.1. Process of storing larger healthcare data -- 6.3. Blockchain-based EHR system -- 6.3.1. Sharing of data -- 6.3.2. Interoperability -- 6.3.3. A distributed network -- 6.3.4. Shared ledger -- 6.3.5. Digital transactions -- 6.4. Blockchain in healthcare -- 6.4.1. On-chain storage -- 6.4.2. Off-chain storage -- 6.4.3. Trust issues in the context of health information exchange (HIE). 6.5. Conclusion and future scope -- 6.6. References -- Chapter 7. Patient Data Privacy Using Blockchain -- 7.1. Introduction -- 7.2. Threat modeling - digitalization in the healthcare industry -- 7.2.1. Data flow diagram (DFD) -- 7.2.2. Threat analysis -- 7.3. Privacy versus security -- 7.3.1. Privacy in Blockchain -- 7.3.2. Process flow -- 7.4. Regulatory compliance requirements -- 7.4.1. HIPAA, HITRUST, HITECH and GDPR -- 7.4.2. Blockchain as a savior -- 7.5. Differential privacy -- 7.5.1. Local differential privacy versus global differential privacy -- 7.5.2. Quantification of privacy and mathematical form of differential privacy -- 7.5.3. Advantages of using differential privacy in Blockchain -- 7.6. Privacy by Design -- 7.7. Conclusion -- 7.8. References -- Chapter 8. Decentralized Smart Healthcare Systems Using Blockchain and AI -- 8.1. Introduction to the healthcare system -- 8.1.1. Introduction to AI -- 8.1.2. Introduction to Blockchain -- 8.2. Use of AI in healthcare systems -- 8.3. Use of Blockchain in healthcare systems -- 8.4. History of medical care -- 8.4.1. Health claims -- 8.4.2. Interoperability -- 8.4.3. Exposure to healthcare -- 8.4.4. Supply chains -- 8.5. Literature review -- 8.6. Bringing intelligence to medical devices and machines -- 8.7. Using artificial intelligence to transform clinical decision-making in hospitals -- 8.7.1. Advantages of Blockchain in healthcare systems -- 8.8. Results of existing models -- 8.9. Conclusion -- 8.10. References -- Chapter 9. Component-based Healthcare Software Application Using Blockchain -- 9.1. Introduction -- 9.2. Literature review -- 9.3. Software development models -- 9.3.1. Traditional software development methodologies -- 9.3.2. Modern software development methodologies -- 9.4. Proposed model -- 9.4.1. Component-based software development life-cycle. 9.4.2. Component development life-cycle -- 9.5. Comparison among different software development life-cycle models -- 9.6. Conclusion and future works -- 9.7. References -- Chapter 10. The Role of Smart Contracts and Blockchain Technology in Healthcare and Other Use Cases -- 10.1. Introduction -- 10.1.1. Comparison between traditional contracts and smart contracts -- 10.2. Ethereum: Generation Two of Blockchain technology -- 10.2.1. History of Ethereum -- 10.3. Smart contracts -- 10.3.1. How smart contracts work -- 10.3.2. Benefits of smart contracts -- 10.3.3. Roles of smart contracts -- 10.4. Use of smart contracts in healthcare, patient monitoring, and other use cases -- 10.4.1. Transparency in supply chain -- 10.4.2. Electronic health records on the Blockchain -- 10.4.3. Use of smart contracts for insurance and billing in supply chain management -- 10.4.4. Verification of medical personnel's identity cards -- 10.4.5. IoT security for remote patient monitoring -- 10.5. Building smart contracts on the Ethereum Blockchain -- 10.5.1. Ethereum virtual machine (EVM) -- 10.5.2. Gas -- 10.5.3. Solidity -- 10.6. Real-time use cases of smart contracts -- 10.6.1. Smart contracts and insurance -- 10.6.2. Smart contracts in an electric vehicle -- 10.6.3. Smart contracts in the energy sector -- 10.6.4. Intellectual property rights -- 10.6.5. Stock trading -- 10.7. Six companies using smart contracts in real-world applications -- 10.7.1. Slock.It -- 10.7.2. Fizzy AXA -- 10.7.3. Etherparty -- 10.7.4. Propy -- 10.7.5. Populous -- 10.7.6. PolySwarm -- 10.8. Challenges -- 10.9. Historical attacks and issues with smart contracts -- 10.10. Conclusion -- 10.11. References -- Chapter 11. Healthcare Research Using Blockchain Technology: A Future Perspective -- 11.1. Introduction -- 11.2. Benefits of using Blockchain in the healthcare industry. 11.3. Application of Blockchain in the healthcare industry -- 11.4. Merging of Blockchain with artificial intelligence in healthcare -- 11.5. Drawbacks of using Blockchain in the healthcare industry -- 11.6. Conclusion and future scope -- 11.7. References -- List of Authors -- Index -- EULA. |
| Record Nr. | UNINA-9910830701403321 |
Choudhury Tanupriya
|
||
| Newark : , : John Wiley & Sons, Incorporated, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Blockchain Applications in Healthcare : Innovations and Practices
| Blockchain Applications in Healthcare : Innovations and Practices |
| Autore | Choudhury Tanupriya |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2023 |
| Descrizione fisica | 1 online resource (254 pages) |
| Altri autori (Persone) |
KhannaAbhirup
ChatterjeePrasenjit UmJung-Sup BhattacharyaAbhishek |
| ISBN |
1-394-22951-8
1-394-22949-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Foreword -- Preface -- Acknowledgments -- Chapter 1. Framework for Blockchain in Healthcare -- 1.1. Concept of Blockchain -- 1.2. Blockchain as distributed database -- 1.3. Architecture of Blockchain in healthcare -- 1.4. Development of Blockchain: A state of art -- 1.5. Information distribution in Blockchain -- 1.6. The growing anticipation of Blockchain -- 1.6.1. Challenges faced by Blockchain -- 1.7. The benefits of Blockchain in healthcare -- 1.8. Open issues related to Blockchain -- 1.9. Future trends of Blockchain -- 1.10. References -- Chapter 2. Role of Smart Contracts in Blockchain -- 2.1. Introduction to Blockchain -- 2.1.1. Types of Blockchain -- 2.1.2. Characteristics of Blockchain -- 2.2. Smart contracts -- 2.2.1. Operating mechanism of smart contracts -- 2.2.2. Applications of smart contracts -- 2.2.3. Programming languages and platforms -- 2.3. Quantitative analysis -- 2.3.1. Results -- 2.4. Role of smart contracts in healthcare -- 2.4.1. Health Insurance -- 2.4.2. Healthcare -- 2.4.3. Telemedicine -- 2.5. Example of smart contracts -- 2.5.1. Simple open auction -- 2.5.2. Voting -- 2.5.3. Patient record -- 2.6. Challenges related to smart contracts -- 2.6.1. Contract vulnerabilities -- 2.6.2. Privacy and legal issues -- 2.6.3. Immutability issue -- 2.7. Conclusion -- 2.8. References -- Chapter 3. Blockchain-based Platforms for the Healthcare Industry -- 3.1. Introduction -- 3.2. Literature review -- 3.3. Blockchain technology -- 3.3.1. Uses of Blockchain in the healthcare sector -- 3.4. Blockchain applications that can be useful for treating the medical sector problems -- 3.4.1. Smart contracts -- 3.4.2. Fraud detection -- 3.4.3. Identity verification -- 3.5. Examples of healthcare platforms using Blockchain -- 3.5.1. Data sharing using Gem Health Network -- 3.5.2. MeDshare.
3.5.3. OmniPHR -- 3.6. Blockchain during the Covid-19 pandemic -- 3.7. Conclusion -- 3.8. References -- Chapter 4. Analyzing and Modeling the Challenges Faced by the Healthcare Sector in the Adoption Process of Blockchain Technologies -- 4.1. Introduction -- 4.2. Literature review -- 4.2.1. Blockchain in healthcare -- 4.3. Challenges of Blockchain in healthcare -- 4.3.1. Technical challenges (TC) -- 4.3.2. Social challenges (SC) -- 4.3.3. Organizational challenges (OC) -- 4.4. Research methodology -- 4.5. Data analysis -- 4.6. Discussion -- 4.7. Conclusion -- 4.8. References -- Chapter 5. Blockchain as an Effective Technology in Maintaining Electronic Health Record Systems -- 5.1. Introduction -- 5.2. Background concepts on Blockchain technology -- 5.2.1. Consensus algorithms -- 5.2.2. Types of Blockchain -- 5.2.3. Smart contracts -- 5.2.4. Features of Blockchain -- 5.2.5. Applications of Blockchain technology -- 5.3. Blockchain in healthcare -- 5.4. Electronic health records using Blockchain -- 5.5. Quantitative analysis -- 5.5.1. Results -- 5.6. Proposed framework for the EHRs using Blockchain -- 5.6.1. System workflow -- 5.7. Issues in Blockchain-based EHRs -- 5.8. Case studies -- 5.8.1. MedRec -- 5.8.2. AI-based solution for EHRs -- 5.8.3. Improving medical record keeping with Blockchain -- 5.9. Conclusion -- 5.10. References -- Chapter 6. An Optimistic Approach to Share Private Health Records Using Blockchain Technology -- 6.1. Introduction -- 6.2. Related work -- 6.2.1. Process of storing larger healthcare data -- 6.3. Blockchain-based EHR system -- 6.3.1. Sharing of data -- 6.3.2. Interoperability -- 6.3.3. A distributed network -- 6.3.4. Shared ledger -- 6.3.5. Digital transactions -- 6.4. Blockchain in healthcare -- 6.4.1. On-chain storage -- 6.4.2. Off-chain storage -- 6.4.3. Trust issues in the context of health information exchange (HIE). 6.5. Conclusion and future scope -- 6.6. References -- Chapter 7. Patient Data Privacy Using Blockchain -- 7.1. Introduction -- 7.2. Threat modeling - digitalization in the healthcare industry -- 7.2.1. Data flow diagram (DFD) -- 7.2.2. Threat analysis -- 7.3. Privacy versus security -- 7.3.1. Privacy in Blockchain -- 7.3.2. Process flow -- 7.4. Regulatory compliance requirements -- 7.4.1. HIPAA, HITRUST, HITECH and GDPR -- 7.4.2. Blockchain as a savior -- 7.5. Differential privacy -- 7.5.1. Local differential privacy versus global differential privacy -- 7.5.2. Quantification of privacy and mathematical form of differential privacy -- 7.5.3. Advantages of using differential privacy in Blockchain -- 7.6. Privacy by Design -- 7.7. Conclusion -- 7.8. References -- Chapter 8. Decentralized Smart Healthcare Systems Using Blockchain and AI -- 8.1. Introduction to the healthcare system -- 8.1.1. Introduction to AI -- 8.1.2. Introduction to Blockchain -- 8.2. Use of AI in healthcare systems -- 8.3. Use of Blockchain in healthcare systems -- 8.4. History of medical care -- 8.4.1. Health claims -- 8.4.2. Interoperability -- 8.4.3. Exposure to healthcare -- 8.4.4. Supply chains -- 8.5. Literature review -- 8.6. Bringing intelligence to medical devices and machines -- 8.7. Using artificial intelligence to transform clinical decision-making in hospitals -- 8.7.1. Advantages of Blockchain in healthcare systems -- 8.8. Results of existing models -- 8.9. Conclusion -- 8.10. References -- Chapter 9. Component-based Healthcare Software Application Using Blockchain -- 9.1. Introduction -- 9.2. Literature review -- 9.3. Software development models -- 9.3.1. Traditional software development methodologies -- 9.3.2. Modern software development methodologies -- 9.4. Proposed model -- 9.4.1. Component-based software development life-cycle. 9.4.2. Component development life-cycle -- 9.5. Comparison among different software development life-cycle models -- 9.6. Conclusion and future works -- 9.7. References -- Chapter 10. The Role of Smart Contracts and Blockchain Technology in Healthcare and Other Use Cases -- 10.1. Introduction -- 10.1.1. Comparison between traditional contracts and smart contracts -- 10.2. Ethereum: Generation Two of Blockchain technology -- 10.2.1. History of Ethereum -- 10.3. Smart contracts -- 10.3.1. How smart contracts work -- 10.3.2. Benefits of smart contracts -- 10.3.3. Roles of smart contracts -- 10.4. Use of smart contracts in healthcare, patient monitoring, and other use cases -- 10.4.1. Transparency in supply chain -- 10.4.2. Electronic health records on the Blockchain -- 10.4.3. Use of smart contracts for insurance and billing in supply chain management -- 10.4.4. Verification of medical personnel's identity cards -- 10.4.5. IoT security for remote patient monitoring -- 10.5. Building smart contracts on the Ethereum Blockchain -- 10.5.1. Ethereum virtual machine (EVM) -- 10.5.2. Gas -- 10.5.3. Solidity -- 10.6. Real-time use cases of smart contracts -- 10.6.1. Smart contracts and insurance -- 10.6.2. Smart contracts in an electric vehicle -- 10.6.3. Smart contracts in the energy sector -- 10.6.4. Intellectual property rights -- 10.6.5. Stock trading -- 10.7. Six companies using smart contracts in real-world applications -- 10.7.1. Slock.It -- 10.7.2. Fizzy AXA -- 10.7.3. Etherparty -- 10.7.4. Propy -- 10.7.5. Populous -- 10.7.6. PolySwarm -- 10.8. Challenges -- 10.9. Historical attacks and issues with smart contracts -- 10.10. Conclusion -- 10.11. References -- Chapter 11. Healthcare Research Using Blockchain Technology: A Future Perspective -- 11.1. Introduction -- 11.2. Benefits of using Blockchain in the healthcare industry. 11.3. Application of Blockchain in the healthcare industry -- 11.4. Merging of Blockchain with artificial intelligence in healthcare -- 11.5. Drawbacks of using Blockchain in the healthcare industry -- 11.6. Conclusion and future scope -- 11.7. References -- List of Authors -- Index -- EULA. |
| Record Nr. | UNINA-9910877387403321 |
|
Choudhury Tanupriya
|
||
| Newark : , : John Wiley & Sons, Incorporated, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Geo-Environmental Hazards Using AI-Enabled Geospatial Techniques and Earth Observation Systems
| Geo-Environmental Hazards Using AI-Enabled Geospatial Techniques and Earth Observation Systems |
| Autore | Choudhury Tanupriya |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (318 pages) |
| Altri autori (Persone) |
KoleyBappaditya
NathAnindita UmJung-Sup PatidarAtul Kumar |
| Collana | Advances in Geographic Information Science Series |
| ISBN |
9783031537639
9783031537622 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- An Introduction to Artificial Intelligence and Its Applications Towards Remote Sensing -- 1 Introduction -- 2 Machine Learning Algorithms -- 3 ML Applications in Remote Sensing -- 4 Deep Neural Network in Remote Sensing -- 5 Conclusion and Future Work -- References -- GIS and Remote Sensing Application for Vegetation Mapping -- 1 Introduction -- 2 Literature Review -- 3 Methodology Used -- 4 GIS and Remote Sensing Application -- 4.1 Agriculture -- 4.2 Natural Resource Management -- 4.3 Disaster Management -- 4.4 Urban Planning -- 4.5 Environmental Monitoring -- 4.6 Defense and Security -- 4.7 Climate Change -- 5 Various Ways GIS Can Be Used for Vegetation Mapping -- 6 Why Sensors Used for Vegetation Mapping -- 7 Case Study -- 8 Discussion of Case Study -- 9 Result and Discussion -- 10 Conclusion and Future Scope -- References -- Spatiotemporal Trends of Tropical Cyclones in Bay of Bengal Basin, India -- 1 Introduction -- 2 Characteristics of the Study Region -- 3 Material and Methods -- 3.1 Data Collection -- 3.2 Data Analysis -- 4 Result and Discussion -- 4.1 Spatiotemporal Distribution of Tropical Cyclones -- 4.1.1 Spatial Trend in Tropical Cyclone -- 4.1.2 Temporal Trend in Tropical Cyclone -- 5 Conclusions -- References -- Application of Geospatial Technologies and AHP Technique in the Identification of Soil Erosion-Prone Zones in the Rift Valley, Southern Ethiopia -- 1 Introduction -- 2 Materials and Methods -- 2.1 Description of the Study Area -- 2.2 Data Collection and Preparation of Nine Thematic Layers -- 2.3 Analytical Hierarchy Process (AHP) Method -- 3 Results and Discussions -- 3.1 Impact of Selected Nine Conditioning Thematic Layers on Soil Erosion -- 3.2 Soil Erosion-Prone Zone Identification -- 3.3 Result Validation -- 4 Conclusions -- References.
Shoreline Changes Along Bhitarkanika Sanctuary, North Odisha Coast, India -- 1 Introduction -- 2 Study Area -- 3 Data and Methods -- 3.1 Data Acquisition -- 3.2 Preliminary Analysis -- 3.3 Shoreline Extraction -- 3.4 Shoreline Change Analysis (DSAS Model) -- 4 Results -- 4.1 Shoreline Changes -- 4.1.1 Short-Term Changes/Decadal Changes -- 4.1.2 Long-Term Changes -- 5 Conclusion -- References -- One-Dimensional Shoreline Evolution Modeling at Sea Turtle Nesting Ground Near the Rushikulya Estuary, Southern Odisha Coast, India -- 1 Introduction -- 2 Study Area -- 3 Data and Methods -- 3.1 Sediment Transport and Shoreline Evolution Modeling -- 4 Results and Discussion -- 4.1 Longshore Sediment Transport -- 4.2 Shoreline Evolution -- 5 Conclusion -- References -- Analysis of Sea Surface Temperature and Chlorophyll-a Concentration Along the Coastline of the Indian Peninsula Using Remote Sensing Data -- 1 Introduction -- 2 Study Area -- 3 Methodology -- 3.1 Theoretical Background -- 3.2 Data Acquisition -- 4 Results and Discussion -- 4.1 Preliminary Analysis -- 4.1.1 Sea Surface Temperature (SST) -- 4.2 Chlorophyll-a Concentration -- 4.3 Trend Analysis -- 4.4 Effect of the Pandemic -- 5 Conclusion -- References -- Landslide Susceptibility Mapping Through Hyperparameter Optimized Bagging and Boosting Ensembles: Case Study of NH-10, West Bengal, India -- 1 Introduction -- 1.1 Related Literature -- 2 Study Area -- 2.1 Geological Perspective -- 2.2 Landslide Inventory -- 3 Materials and Methodology -- 3.1 Causative Factors for Landslides -- 3.2 Applied Models -- 4 Results and Exhibits -- 4.1 Spatial Association Between the Causal Factors with the Model Predictions -- 4.2 Susceptibility Maps Prepared by the Proposed Models -- 4.3 Accuracy Assessment -- 5 Conclusion and Future Scope -- References -- Flash Flood Assessment in Hilly Regions -- 1 Introduction. 1.1 Background -- 1.2 Literature Review -- 1.3 Case Study -- 2 Methodology and Methods -- 2.1 Identification of Flood Assessment Parameters -- 2.2 Mapping of Flood Assessment Parameters -- 2.2.1 Rainfall -- 2.2.2 Morphometric Analysis -- 2.2.3 Elevation -- 2.2.4 Relative Relief -- 2.2.5 Slope -- 2.2.6 Soil -- 2.2.7 LULC -- 2.3 Results and Discussion -- 3 Conclusion -- References -- Mapping Flood Hazard in Marinduque, Philippines, Using Maximum Entropy Approach -- 1 Introduction -- 1.1 Floods -- 1.2 Flood Hazard Mapping -- 1.3 Study Site -- 1.4 Objectives -- 2 Methodology -- 2.1 Flood Event Data -- 2.2 Geo-Environmental Data -- 2.3 Maximum Entropy Modeling -- 3 Results and Discussion -- 3.1 MaxEnt Modeling -- 3.2 Flood Hazard Map -- 4 Conclusion -- References -- GIS Mapping and Groundwater Quality Assessment Near Solid Waste Dump Site -- 1 Introduction -- 2 Methodology -- 2.1 Study Area -- 2.2 Water Quality Parameters -- 2.3 GIS -- 3 Results -- 4 Discussion of Results -- 5 Conclusions -- References -- Assessment of Groundwater Potential Using an Integrated Approach of GIS, Fuzzy AHP, and Remote Sensing: A Case Study of Madurai City in India -- 1 Introduction -- 2 Study Area -- 3 Materials and Methods -- 3.1 Creation of Thematic Maps -- 3.2 Fuzzy AHP Approach to Calculate Feature Weights -- 3.3 Assessment of Groundwater Potential Zone (GWPZ) -- 3.4 Validation of Results -- 4 Results and Discussion -- 4.1 Slope -- 4.2 Curvature -- 4.3 Roughness -- 4.4 Drainage Density -- 4.5 Geology -- 4.6 Geomorphology -- 4.7 Land Use/Land Cover (LU/LC) -- 4.8 Soil -- 4.9 Lineament Density -- 4.10 Topographic Wetness Index -- 4.11 Groundwater Potential Zones by FAHP Method -- 4.12 Validation of Groundwater Potential Zones -- 5 Conclusion -- References -- Developing Sustainable Livelihood Index for the Coastal Belt of Indian Sundarbans -- 1 Introduction. 2 Characteristics of the Study Area -- 3 Data and Methodology -- 4 Construction of Sustainable Livelihood Index -- 5 Stepwise Regression Model -- 6 Results and Analysis -- 7 Concluding Remarks -- References -- A Geospatial Approach for the Development of Sustainable Watershed Management -- 1 Introduction -- 1.1 Study Area -- 2 Methodology -- 2.1 Data Collection -- 2.2 Database Creation -- 2.2.1 Spatial Database -- 2.2.2 Attribute Database -- 3 Results and Discussion -- 3.1 Elevation of the Study Area -- 3.2 Land Use/Land Cover of the Study Area -- 3.3 Structures of the Study Area -- 3.4 Electrical Resistivity of the Area -- 3.5 Geology of the Study Area -- 3.6 Velchal Watershed Developmental Map -- 4 Conclusions -- References -- An Efficient Image Compression Algorithm Using Neural Networks -- 1 Introduction -- 2 Methods -- 3 Feed-Forward Framework -- 4 Results -- 4.1 Description -- 5 Conclusion -- References -- Computer Vision-Based Autonomous Underwater Vehicle with Robotic Arm for Garbage Detection and Cleaning -- 1 Introduction -- 2 Background -- 2.1 Object Detection Using Deep Learning -- 2.2 Autonomous Underwater Vehicle (AUV) -- 3 Materials and Methods -- 3.1 Proposed System Architecture -- 3.2 Proposed System Design -- 3.3 Proposed System Components -- 4 Results and Discussion -- 5 Application and Future Work -- 5.1 Applications -- 5.2 Future Work -- 5.3 Challenges in Underwater Processing -- 6 Conclusions -- References -- Visual Media Super-Resolution Using Super-Resolution Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Architecture -- 3.1.1 The Architecture of Generator -- 3.1.2 Discriminator Architecture -- 3.2 Loss Function -- 3.3 Video Description -- 3.4 API -- 4 Analysis Framework -- 4.1 Generator -- 4.2 Discriminator -- 4.3 Video -- 4.4 API Flow -- 5 Results and Discussions -- 5.1 Dataset. 5.2 Training and Validation -- 5.3 Final Results (Figs. 7, 8 and 9) -- 5.4 End Product -- 5.5 Evaluation and Analysis -- 5.6 Qualitative Analysis -- 6 Conclusion -- References -- Index. |
| Record Nr. | UNINA-9910864190103321 |
|
Choudhury Tanupriya
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Intelligence and Data Science Applications : Proceedings of MIDAS 2022 / / edited by Amar Ramdane-Cherif, T. P. Singh, Ravi Tomar, Tanupriya Choudhury, Jung-Sup Um
| Machine Intelligence and Data Science Applications : Proceedings of MIDAS 2022 / / edited by Amar Ramdane-Cherif, T. P. Singh, Ravi Tomar, Tanupriya Choudhury, Jung-Sup Um |
| Autore | Ramdane-Cherif Amar |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (559 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
SinghT. P
TomarRavi ChoudhuryTanupriya UmJung-Sup |
| Collana | Algorithms for Intelligent Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Quantitative research Machine learning Computational Intelligence Artificial Intelligence Data Analysis and Big Data Machine Learning |
| ISBN | 981-9916-20-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Blockchain-supported Sustainable Supply Chain in Industry 4.0 -- COVID 19 Cases In India: A Study on the effect of Weather Factors and Building the Forecast Model -- A Review On Scheduling in Cloud Fog Computing Environments -- Simplifying Handwritten Medical Prescription: OCR Approach. |
| Record Nr. | UNINA-9910743681303321 |
|
Ramdane-Cherif Amar
|
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||