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Artificial Intelligence and Digital Twin Technology : 1st International Conference, IconAIDTT 2023, Sivakasi, India, April 26-28, 2023, Proceedings
| Artificial Intelligence and Digital Twin Technology : 1st International Conference, IconAIDTT 2023, Sivakasi, India, April 26-28, 2023, Proceedings |
| Autore | K Valarmathi |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (173 pages) |
| Altri autori (Persone) |
ARamathilagam
SeeniSankarganesh KoseUtku HungBui Thanh KottursamyKottilingam |
| Collana | Communications in Computer and Information Science Series |
| ISBN |
9783031777998
3031777999 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910918590803321 |
K Valarmathi
|
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| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fuzzy Computing in Data Science : Applications and Challenges
| Fuzzy Computing in Data Science : Applications and Challenges |
| Autore | Mohanty Sachi Nandan |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2022 |
| Descrizione fisica | 1 online resource (363 pages) |
| Altri autori (Persone) |
ChatterjeePrasenjit
HungBui Thanh |
| Collana | Smart and Sustainable Intelligent Systems Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-394-15688-X
1-394-15687-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Dedication Page -- Contents -- Preface -- Acknowledgement -- Chapter 1 Band Reduction of HSI Segmentation Using FCM -- 1.1 Introduction -- 1.2 Existing Method -- 1.2.1 K-Means Clustering Method -- 1.2.2 Fuzzy C-Means -- 1.2.3 Davies Bouldin Index -- 1.2.4 Data Set Description of HSI -- 1.3 Proposed Method -- 1.3.1 Hyperspectral Image Segmentation Using Enhanced Estimation of Centroid -- 1.3.2 Band Reduction Using K-Means Algorithm -- 1.3.3 Band Reduction Using Fuzzy C-Means -- 1.4 Experimental Results -- 1.4.1 DB Index Graph -- 1.4.2 K-Means-Based PSC (EEOC) -- 1.4.3 Fuzzy C-Means-Based PSC (EEOC) -- 1.5 Analysis of Results -- 1.6 Conclusions -- References -- Chapter 2 A Fuzzy Approach to Face Mask Detection -- 2.1 Introduction -- 2.2 Existing Work -- 2.3 The Proposed Framework -- 2.4 Set-Up and Libraries Used -- 2.5 Implementation -- 2.6 Results and Analysis -- 2.7 Conclusion and Future Work -- References -- Chapter 3 Application of Fuzzy Logic to the Healthcare Industry -- 3.1 Introduction -- 3.2 Background -- 3.3 Fuzzy Logic -- 3.4 Fuzzy Logic in Healthcare -- 3.5 Conclusions -- References -- Chapter 4 A Bibliometric Approach and Systematic Exploration of Global Research Activity on Fuzzy Logic in Scopus Database -- 4.1 Introduction -- 4.2 Data Extraction and Interpretation -- 4.3 Results and Discussion -- 4.3.1 Per Year Publication and Citation Count -- 4.3.2 Prominent Affiliations Contributing Toward Fuzzy Logic -- 4.3.3 Top Journals Emerging in Fuzzy Logic in Major Subject Areas -- 4.3.4 Major Contributing Countries Toward Fuzzy Research Articles -- 4.3.5 Prominent Authors Contribution Toward the Fuzzy Logic Analysis -- 4.3.6 Coauthorship of Authors -- 4.3.7 Cocitation Analysis of Cited Authors -- 4.3.8 Cooccurrence of Author Keywords.
4.4 Bibliographic Coupling of Documents, Sources, Authors, and Countries -- 4.4.1 Bibliographic Coupling of Documents -- 4.4.2 Bibliographic Coupling of Sources -- 4.4.3 Bibliographic Coupling of Authors -- 4.4.4 Bibliographic Coupling of Countries -- 4.5 Conclusion -- References -- Chapter 5 Fuzzy Decision Making in Predictive Analytics and Resource Scheduling -- 5.1 Introduction -- 5.2 History of Fuzzy Logic and Its Applications -- 5.3 Approximate Reasoning -- 5.4 Fuzzy Sets vs Classical Sets -- 5.5 Fuzzy Inference System -- 5.5.1 Characteristics of FIS -- 5.5.2 Working of FIS -- 5.5.3 Methods of FIS -- 5.6 Fuzzy Decision Trees -- 5.6.1 Characteristics of Decision Trees -- 5.6.2 Construction of Fuzzy Decision Trees -- 5.7 Fuzzy Logic as Applied to Resource Scheduling in a Cloud Environment -- 5.8 Conclusion -- References -- Chapter 6 Application of Fuzzy Logic and Machine Learning Concept in Sales Data Forecasting Decision Analytics Using ARIMA Model -- 6.1 Introduction -- 6.1.1 Aim and Scope -- 6.1.2 R-Tool -- 6.1.3 Application of Fuzzy Logic -- 6.1.4 Dataset -- 6.2 Model Study -- 6.2.1 Introduction to Machine Learning Method -- 6.2.2 Time Series Analysis -- 6.2.3 Components of a Time Series -- 6.2.4 Concepts of Stationary -- 6.2.5 Model Parsimony -- 6.3 Methodology -- 6.3.1 Exploratory Data Analysis -- 6.3.1.1 Seed Types-Analysis -- 6.3.1.2 Comparison of Location and Seeds -- 6.3.1.3 Comparison of Season (Month) and Seeds -- 6.3.2 Forecasting -- 6.3.2.1 Auto Regressive Integrated Moving Average (ARIMA) -- 6.3.2.2 Data Visualization -- 6.3.2.3 Implementation Model -- 6.4 Result Analysis -- 6.5 Conclusion -- References -- Chapter 7 Modified m-Polar Fuzzy Set ELECTRE-I Approach -- 7.1 Introduction -- 7.1.1 Objectives -- 7.2 Implementation of m-Polar Fuzzy ELECTRE-I Integrated Shannon's Entropy Weight Calculations. 7.2.1 The m-Polar Fuzzy ELECTRE-I Integrated Shannon's Entropy Weight Calculation Method -- 7.3 Application to Industrial Problems -- 7.3.1 Cutting Fluid Selection Problem -- 7.3.2 Results Obtained From m-Polar Fuzzy ELECTRE-I for Cutting Fluid Selection Problem -- 7.3.3 FMS Selection Problem -- 7.3.4 Results Obtained From m-Polar Fuzzy ELECTRE-I for FMS Selection -- 7.4 Conclusions -- References -- Chapter 8 Fuzzy Decision Making: Concept and Models -- 8.1 Introduction -- 8.2 Classical Set -- 8.3 Fuzzy Set -- 8.4 Properties of Fuzzy Set -- 8.5 Types of Decision Making -- 8.5.1 Individual Decision Making -- 8.5.2 Multiperson Decision Making -- 8.5.3 Multistage Decision Making -- 8.5.4 Multicriteria Decision Making -- 8.6 Methods of Multiattribute Decision Making (MADM) -- 8.6.1 Weighted Sum Method (WSM) -- 8.6.2 Weighted Product Method (WPM) -- 8.6.3 Weighted Aggregates Sum Product Assessment (WASPAS) -- 8.6.4 Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) -- 8.7 Applications of Fuzzy Logic -- 8.8 Conclusion -- References -- Chapter 9 Use of Fuzzy Logic for Psychological Support to Migrant Workers of Southern Odisha (India) -- 9.1 Introduction -- 9.2 Objectives and Methodology -- 9.2.1 Objectives -- 9.2.2 Methodology -- 9.3 Effect of COVID-19 on the Psychology and Emotion of Repatriated Migrants -- 9.3.1 Psychological Variables Identified -- 9.3.2 Fuzzy Logic for Solace to Migrants -- 9.4 Findings -- 9.5 Way Out for Strengthening the Psychological Strength of the Migrant Workers through Technological Aid -- 9.6 Conclusion -- References -- Chapter 10 Fuzzy-Based Edge AI Approach: Smart Transformation of Healthcare for a Better Tomorrow -- 10.1 Significance of Machine Learning in Healthcare -- 10.2 Cloud-Based Artificial Intelligent Secure Models -- 10.3 Applications and Usage of Machine Learning in Healthcare. 10.3.1 Detecting Diseases and Diagnosis -- 10.3.2 Drug Detection and Manufacturing -- 10.3.3 Medical Imaging Analysis and Diagnosis -- 10.3.4 Personalized/Adapted Medicine -- 10.3.5 Behavioral Modification -- 10.3.6 Maintenance of Smart Health Data -- 10.3.7 Clinical Trial and Study -- 10.3.8 Crowdsourced Information Discovery -- 10.3.9 Enhanced Radiotherapy -- 10.3.10 Outbreak/Epidemic Prediction -- 10.4 Edge AI: For Smart Transformation of Healthcare -- 10.4.1 Role of Edge in Reshaping Healthcare -- 10.4.2 How AI Powers the Edge -- 10.5 Edge AI-Modernizing Human Machine Interface -- 10.5.1 Rural Medicine -- 10.5.2 Autonomous Monitoring of Hospital Rooms-A Case Study -- 10.6 Significance of Fuzzy in Healthcare -- 10.6.1 Fuzzy Logic-Outline -- 10.6.2 Fuzzy Logic-Based Smart Healthcare -- 10.6.3 Medical Diagnosis Using Fuzzy Logic for Decision Support Systems -- 10.6.4 Applications of Fuzzy Logic in Healthcare -- 10.7 Conclusion and Discussions -- References -- Chapter 11 Video Conferencing (VC) Software Selection Using Fuzzy TOPSIS -- 11.1 Introduction -- 11.2 Video Conferencing Software and Its Major Features -- 11.2.1 Video Conferencing/Meeting Software (VC/MS) for Higher Education Institutes -- 11.3 Fuzzy TOPSIS -- 11.3.1 Extension of TOPSIS Algorithm: Fuzzy TOPSIS -- 11.4 Sample Numerical Illustration -- 11.5 Conclusions -- References -- Chapter 12 Estimation of Nonperforming Assets of Indian Commercial Banks Using Fuzzy AHP and Goal Programming -- 12.1 Introduction -- 12.1.1 Basic Concepts of Fuzzy AHP and Goal Programming -- 12.2 Research Model -- 12.2.1 Average Growth Rate Calculation -- 12.3 Result and Discussion -- 12.4 Conclusion -- References -- Chapter 13 Evaluation of Ergonomic Design for the Visual Display Terminal Operator at Static Work Under FMCDM Environment -- 13.1 Introduction -- 13.2 Proposed Algorithm. 13.3 An Illustrative Example on Ergonomic Design Evaluation -- 13.4 Conclusions -- References -- Chapter 14 Optimization of Energy Generated from Ocean Wave Energy Using Fuzzy Logic -- 14.1 Introduction -- 14.2 Control Approach in Wave Energy Systems -- 14.3 Related Work -- 14.4 Mathematical Modeling for Energy Conversion from Ocean Waves -- 14.5 Proposed Methodology -- 14.5.1 Wave Parameters -- 14.5.2 Fuzzy-Optimizer -- 14.6 Conclusion -- References -- Chapter 15 The m-Polar Fuzzy TOPSIS Method for NTM Selection -- 15.1 Introduction -- 15.2 Literature Review -- 15.3 Methodology -- 15.3.1 Steps of the mFS TOPSIS -- 15.4 Case Study -- 15.4.1 Effect of Analytical Hierarchy Process (AHP) Weight Calculation on the mFS TOPSIS Method -- 15.4.2 Effect of Shannon's Entropy Weight Calculation on the m-Polar Fuzzy Set TOPSIS Method -- 15.5 Results and Discussions -- 15.5.1 Result Validation -- 15.6 Conclusions and Future Scope -- References -- Chapter 16 Comparative Analysis on Material Handling Device Selection Using Hybrid FMCDM Methodology -- 16.1 Introduction -- 16.2 MCDM Techniques -- 16.2.1 FAHP -- 16.2.2 Entropy Method as Weights (Influence) Evaluation Technique -- 16.3 The Proposed Hybrid and Super Hybrid FMCDM Approaches -- 16.3.1 TOPSIS -- 16.3.2 FMOORA Method -- 16.3.3 FVIKOR -- 16.3.4 Fuzzy Grey Theory (FGT) -- 16.3.5 COPRAS -G -- 16.3.6 Super Hybrid Algorithm -- 16.4 Illustrative Example -- 16.5 Results and Discussions -- 16.5.1 FTOPSIS -- 16.5.2 FMOORA -- 16.5.3 FVIKOR -- 16.5.4 Fuzzy Grey Theory (FGT) -- 16.5.5 COPRAS-G -- 16.5.6 Super Hybrid Approach (SHA) -- 16.6 Conclusions -- References -- Chapter 17 Fuzzy MCDM on CCPM for Decision Making: A Case Study -- 17.1 Introduction -- 17.2 Literature Review -- 17.3 Objective of Research -- 17.4 Cluster Analysis -- 17.4.1 Hierarchical Clustering -- 17.4.2 Partitional Clustering -- 17.5 Clustering. 17.6 Methodology. |
| Record Nr. | UNINA-9910632499103321 |
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Mohanty Sachi Nandan
|
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| Newark : , : John Wiley & Sons, Incorporated, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fuzzy computing in data science : applications and challenges / / edited by Sachi Nandan Mohanty, Prasenjit Chatterjee and Bui Thanh Hung
| Fuzzy computing in data science : applications and challenges / / edited by Sachi Nandan Mohanty, Prasenjit Chatterjee and Bui Thanh Hung |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023] |
| Descrizione fisica | 1 online resource (363 pages) |
| Disciplina | 511.313 |
| Collana | Smart and sustainable intelligent systems |
| Soggetto topico |
Fuzzy logic
Fuzzy systems Data mining |
| ISBN |
1-394-15688-X
1-394-15687-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Dedication Page -- Contents -- Preface -- Acknowledgement -- Chapter 1 Band Reduction of HSI Segmentation Using FCM -- 1.1 Introduction -- 1.2 Existing Method -- 1.2.1 K-Means Clustering Method -- 1.2.2 Fuzzy C-Means -- 1.2.3 Davies Bouldin Index -- 1.2.4 Data Set Description of HSI -- 1.3 Proposed Method -- 1.3.1 Hyperspectral Image Segmentation Using Enhanced Estimation of Centroid -- 1.3.2 Band Reduction Using K-Means Algorithm -- 1.3.3 Band Reduction Using Fuzzy C-Means -- 1.4 Experimental Results -- 1.4.1 DB Index Graph -- 1.4.2 K-Means-Based PSC (EEOC) -- 1.4.3 Fuzzy C-Means-Based PSC (EEOC) -- 1.5 Analysis of Results -- 1.6 Conclusions -- References -- Chapter 2 A Fuzzy Approach to Face Mask Detection -- 2.1 Introduction -- 2.2 Existing Work -- 2.3 The Proposed Framework -- 2.4 Set-Up and Libraries Used -- 2.5 Implementation -- 2.6 Results and Analysis -- 2.7 Conclusion and Future Work -- References -- Chapter 3 Application of Fuzzy Logic to the Healthcare Industry -- 3.1 Introduction -- 3.2 Background -- 3.3 Fuzzy Logic -- 3.4 Fuzzy Logic in Healthcare -- 3.5 Conclusions -- References -- Chapter 4 A Bibliometric Approach and Systematic Exploration of Global Research Activity on Fuzzy Logic in Scopus Database -- 4.1 Introduction -- 4.2 Data Extraction and Interpretation -- 4.3 Results and Discussion -- 4.3.1 Per Year Publication and Citation Count -- 4.3.2 Prominent Affiliations Contributing Toward Fuzzy Logic -- 4.3.3 Top Journals Emerging in Fuzzy Logic in Major Subject Areas -- 4.3.4 Major Contributing Countries Toward Fuzzy Research Articles -- 4.3.5 Prominent Authors Contribution Toward the Fuzzy Logic Analysis -- 4.3.6 Coauthorship of Authors -- 4.3.7 Cocitation Analysis of Cited Authors -- 4.3.8 Cooccurrence of Author Keywords.
4.4 Bibliographic Coupling of Documents, Sources, Authors, and Countries -- 4.4.1 Bibliographic Coupling of Documents -- 4.4.2 Bibliographic Coupling of Sources -- 4.4.3 Bibliographic Coupling of Authors -- 4.4.4 Bibliographic Coupling of Countries -- 4.5 Conclusion -- References -- Chapter 5 Fuzzy Decision Making in Predictive Analytics and Resource Scheduling -- 5.1 Introduction -- 5.2 History of Fuzzy Logic and Its Applications -- 5.3 Approximate Reasoning -- 5.4 Fuzzy Sets vs Classical Sets -- 5.5 Fuzzy Inference System -- 5.5.1 Characteristics of FIS -- 5.5.2 Working of FIS -- 5.5.3 Methods of FIS -- 5.6 Fuzzy Decision Trees -- 5.6.1 Characteristics of Decision Trees -- 5.6.2 Construction of Fuzzy Decision Trees -- 5.7 Fuzzy Logic as Applied to Resource Scheduling in a Cloud Environment -- 5.8 Conclusion -- References -- Chapter 6 Application of Fuzzy Logic and Machine Learning Concept in Sales Data Forecasting Decision Analytics Using ARIMA Model -- 6.1 Introduction -- 6.1.1 Aim and Scope -- 6.1.2 R-Tool -- 6.1.3 Application of Fuzzy Logic -- 6.1.4 Dataset -- 6.2 Model Study -- 6.2.1 Introduction to Machine Learning Method -- 6.2.2 Time Series Analysis -- 6.2.3 Components of a Time Series -- 6.2.4 Concepts of Stationary -- 6.2.5 Model Parsimony -- 6.3 Methodology -- 6.3.1 Exploratory Data Analysis -- 6.3.1.1 Seed Types-Analysis -- 6.3.1.2 Comparison of Location and Seeds -- 6.3.1.3 Comparison of Season (Month) and Seeds -- 6.3.2 Forecasting -- 6.3.2.1 Auto Regressive Integrated Moving Average (ARIMA) -- 6.3.2.2 Data Visualization -- 6.3.2.3 Implementation Model -- 6.4 Result Analysis -- 6.5 Conclusion -- References -- Chapter 7 Modified m-Polar Fuzzy Set ELECTRE-I Approach -- 7.1 Introduction -- 7.1.1 Objectives -- 7.2 Implementation of m-Polar Fuzzy ELECTRE-I Integrated Shannon's Entropy Weight Calculations. 7.2.1 The m-Polar Fuzzy ELECTRE-I Integrated Shannon's Entropy Weight Calculation Method -- 7.3 Application to Industrial Problems -- 7.3.1 Cutting Fluid Selection Problem -- 7.3.2 Results Obtained From m-Polar Fuzzy ELECTRE-I for Cutting Fluid Selection Problem -- 7.3.3 FMS Selection Problem -- 7.3.4 Results Obtained From m-Polar Fuzzy ELECTRE-I for FMS Selection -- 7.4 Conclusions -- References -- Chapter 8 Fuzzy Decision Making: Concept and Models -- 8.1 Introduction -- 8.2 Classical Set -- 8.3 Fuzzy Set -- 8.4 Properties of Fuzzy Set -- 8.5 Types of Decision Making -- 8.5.1 Individual Decision Making -- 8.5.2 Multiperson Decision Making -- 8.5.3 Multistage Decision Making -- 8.5.4 Multicriteria Decision Making -- 8.6 Methods of Multiattribute Decision Making (MADM) -- 8.6.1 Weighted Sum Method (WSM) -- 8.6.2 Weighted Product Method (WPM) -- 8.6.3 Weighted Aggregates Sum Product Assessment (WASPAS) -- 8.6.4 Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) -- 8.7 Applications of Fuzzy Logic -- 8.8 Conclusion -- References -- Chapter 9 Use of Fuzzy Logic for Psychological Support to Migrant Workers of Southern Odisha (India) -- 9.1 Introduction -- 9.2 Objectives and Methodology -- 9.2.1 Objectives -- 9.2.2 Methodology -- 9.3 Effect of COVID-19 on the Psychology and Emotion of Repatriated Migrants -- 9.3.1 Psychological Variables Identified -- 9.3.2 Fuzzy Logic for Solace to Migrants -- 9.4 Findings -- 9.5 Way Out for Strengthening the Psychological Strength of the Migrant Workers through Technological Aid -- 9.6 Conclusion -- References -- Chapter 10 Fuzzy-Based Edge AI Approach: Smart Transformation of Healthcare for a Better Tomorrow -- 10.1 Significance of Machine Learning in Healthcare -- 10.2 Cloud-Based Artificial Intelligent Secure Models -- 10.3 Applications and Usage of Machine Learning in Healthcare. 10.3.1 Detecting Diseases and Diagnosis -- 10.3.2 Drug Detection and Manufacturing -- 10.3.3 Medical Imaging Analysis and Diagnosis -- 10.3.4 Personalized/Adapted Medicine -- 10.3.5 Behavioral Modification -- 10.3.6 Maintenance of Smart Health Data -- 10.3.7 Clinical Trial and Study -- 10.3.8 Crowdsourced Information Discovery -- 10.3.9 Enhanced Radiotherapy -- 10.3.10 Outbreak/Epidemic Prediction -- 10.4 Edge AI: For Smart Transformation of Healthcare -- 10.4.1 Role of Edge in Reshaping Healthcare -- 10.4.2 How AI Powers the Edge -- 10.5 Edge AI-Modernizing Human Machine Interface -- 10.5.1 Rural Medicine -- 10.5.2 Autonomous Monitoring of Hospital Rooms-A Case Study -- 10.6 Significance of Fuzzy in Healthcare -- 10.6.1 Fuzzy Logic-Outline -- 10.6.2 Fuzzy Logic-Based Smart Healthcare -- 10.6.3 Medical Diagnosis Using Fuzzy Logic for Decision Support Systems -- 10.6.4 Applications of Fuzzy Logic in Healthcare -- 10.7 Conclusion and Discussions -- References -- Chapter 11 Video Conferencing (VC) Software Selection Using Fuzzy TOPSIS -- 11.1 Introduction -- 11.2 Video Conferencing Software and Its Major Features -- 11.2.1 Video Conferencing/Meeting Software (VC/MS) for Higher Education Institutes -- 11.3 Fuzzy TOPSIS -- 11.3.1 Extension of TOPSIS Algorithm: Fuzzy TOPSIS -- 11.4 Sample Numerical Illustration -- 11.5 Conclusions -- References -- Chapter 12 Estimation of Nonperforming Assets of Indian Commercial Banks Using Fuzzy AHP and Goal Programming -- 12.1 Introduction -- 12.1.1 Basic Concepts of Fuzzy AHP and Goal Programming -- 12.2 Research Model -- 12.2.1 Average Growth Rate Calculation -- 12.3 Result and Discussion -- 12.4 Conclusion -- References -- Chapter 13 Evaluation of Ergonomic Design for the Visual Display Terminal Operator at Static Work Under FMCDM Environment -- 13.1 Introduction -- 13.2 Proposed Algorithm. 13.3 An Illustrative Example on Ergonomic Design Evaluation -- 13.4 Conclusions -- References -- Chapter 14 Optimization of Energy Generated from Ocean Wave Energy Using Fuzzy Logic -- 14.1 Introduction -- 14.2 Control Approach in Wave Energy Systems -- 14.3 Related Work -- 14.4 Mathematical Modeling for Energy Conversion from Ocean Waves -- 14.5 Proposed Methodology -- 14.5.1 Wave Parameters -- 14.5.2 Fuzzy-Optimizer -- 14.6 Conclusion -- References -- Chapter 15 The m-Polar Fuzzy TOPSIS Method for NTM Selection -- 15.1 Introduction -- 15.2 Literature Review -- 15.3 Methodology -- 15.3.1 Steps of the mFS TOPSIS -- 15.4 Case Study -- 15.4.1 Effect of Analytical Hierarchy Process (AHP) Weight Calculation on the mFS TOPSIS Method -- 15.4.2 Effect of Shannon's Entropy Weight Calculation on the m-Polar Fuzzy Set TOPSIS Method -- 15.5 Results and Discussions -- 15.5.1 Result Validation -- 15.6 Conclusions and Future Scope -- References -- Chapter 16 Comparative Analysis on Material Handling Device Selection Using Hybrid FMCDM Methodology -- 16.1 Introduction -- 16.2 MCDM Techniques -- 16.2.1 FAHP -- 16.2.2 Entropy Method as Weights (Influence) Evaluation Technique -- 16.3 The Proposed Hybrid and Super Hybrid FMCDM Approaches -- 16.3.1 TOPSIS -- 16.3.2 FMOORA Method -- 16.3.3 FVIKOR -- 16.3.4 Fuzzy Grey Theory (FGT) -- 16.3.5 COPRAS -G -- 16.3.6 Super Hybrid Algorithm -- 16.4 Illustrative Example -- 16.5 Results and Discussions -- 16.5.1 FTOPSIS -- 16.5.2 FMOORA -- 16.5.3 FVIKOR -- 16.5.4 Fuzzy Grey Theory (FGT) -- 16.5.5 COPRAS-G -- 16.5.6 Super Hybrid Approach (SHA) -- 16.6 Conclusions -- References -- Chapter 17 Fuzzy MCDM on CCPM for Decision Making: A Case Study -- 17.1 Introduction -- 17.2 Literature Review -- 17.3 Objective of Research -- 17.4 Cluster Analysis -- 17.4.1 Hierarchical Clustering -- 17.4.2 Partitional Clustering -- 17.5 Clustering. 17.6 Methodology. |
| Record Nr. | UNINA-9910830507603321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The Impact of Algorithmic Technologies on Healthcare
| The Impact of Algorithmic Technologies on Healthcare |
| Autore | Dubey Parul |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (394 pages) |
| Disciplina | 621.382 |
| Altri autori (Persone) |
MadankarMangala
DubeyPushkar HungBui Thanh |
| Collana | Machine Learning in Biomedical Science and Healthcare Informatics Series |
| Soggetto topico | Artificial intelligence - Medical applications |
| ISBN |
9781394305476
1394305478 9781394305483 1394305486 9781394305490 1394305494 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- 1 Introduction to Algorithmic Health: Exploring Healthcare Through Digital Twins 1 A.S. Vinay Raj, N. Gopinath, R. Anandh, M. Mohammed Jalaluddin and Lyndsay R. Buckingham -- 1.1 Introduction -- 1.2 Related Works -- 1.3 Hardware Description -- 1.4 Methodology -- 1.5 Performance Analysis -- 1.6 Conclusion -- 2 The Digital Revolution in Healthcare 27 Devanand Bhonsle, Rama Shukla, Deepshikha Sahu, Tanuja Kashyap, Monika Dewangan and Seema Mishra -- 2.1 Introduction -- 2.2 Digital Technologies in the Healthcare Sector -- 2.3 Evolution of Digitalization in Business -- 2.4 Role of IoMT in Healthcare -- 2.5 Internet of Medical Things Devices -- 2.6 Security and Privacy in the Healthcare Sector -- 2.7 Eliminating Security and Privacy Concerns of Digitalization of the Healthcare Sector -- 2.8 Discussion -- 2.9 Future Works -- 2.10 Conclusion -- 3 Data-Driven Diagnostics: Deep Learning for Brain Tumor Classification 45 Astha Pathak and Lalita Panika -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Methodology -- 3.4 Result Analysis -- 3.5 Conclusion -- 4 Predictive Analysis in Patient Care 61 Bolukonda Prashanth, Bandi Krishna, Rakesh Nayak, Umashankar Ghugar and Arunakranthi Godishala -- 4.1 Introduction -- 4.2 Review of Predictive Analysis -- 4.3 Conclusion and Future -- 5 Leveraging Predictive Analytics: Enhancing Brain Tumor Classification with XGBoost 85 Katakam Hemanvitha and Vikram Dhiman -- 5.1 Introduction -- 5.2 Literature Review -- 5.3 Methodology -- 5.4 Results and Discussion -- 5.5 Conclusion -- 6 Machine Learning in Medical Imaging Revolutionizing Lung Cancer Diagnosis: A Comparative Analysis of Convolutional Neural Networks and Vision Transformers in Medical Imaging 103 Priya Parkhi, Bhagyashree Hambarde, Himesh Gangwani, Rupali Vairagade and Fred Kalombo -- 6.1 Introduction -- 6.2 Literature Review -- 6.3 Description of Model -- 6.4 Methodology -- 6.5 Results -- 6.6 Conclusion -- 7 Innovations in AI and ML for Medical Imaging: An Extensive Study with an Emphasis on Face Spoofing Detection and Snooping 127 Aparna Pandey, Arvind Kumar Tiwari, Harsha Nishad and Siji A. Thomas -- 7.1 Introduction -- 7.2 Artificial Intelligence as Well as Device Understandings -- 7.3 Assaults Through Entrance Spoofing -- 7.4 A Case Study with Real-Time Narrative: Identifying Face Spoofing in Medical Imaging -- 7.5 Moral Factors to Consider -- 7.6 Discussion -- 7.7 Summary -- 8 Progressive Growing of Generative Adversarial Networks (PGGAN) Approach to Synthesize Medical Images 157 Vishal V. Raner, Amit D. Joshi, Suraj T. Sawant and Tamizharasan P. S. -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Methodology -- 8.4 Results and Discussion -- 8.5 Conclusions -- 9 Revolutionizing Healthcare Through Optimized Video Retrieval 177 Pratibha Singh and Alok Kumar Singh Kushwaha -- 9.1 Introduction -- 9.2 Literature Review -- 9.3 Methodology -- 9.4 Results and Discussion -- 9.5 Conclusion -- 10 Multiclass Classification of Oral Diseases Using Deep Learning Models 189 Mohammed Zubair Hussain, Shrey Gupta, Bhagyashree Hambarde, Priya Parkhi and Zafar Karimov -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 Methodology -- 10.4 Results -- 10.5 Conclusion -- 11 Smart Wearable Devices for Remote Patient Monitoring in Healthcare 209 Ravi Mishra, Swati Chaitandas Hadke, Devanand Bhonsle, Priti Nilesh Bhagat, Anupama Mahabansi and Sheetal Mungale -- 11.1 Introduction -- 11.2 Wearable Devices for Remote Monitoring -- 11.3 Communication Technologies for Remote Healthcare Monitoring -- 11.4 Proposed Methodology -- 11.5 Conclusion -- 12 Efficient IoT Solutions for Remote Health Monitoring 225 Vijayakumar S., N. Sheik Hameed, Kanchan S. Tiwari, A. Allwyn Sundarraj, N. Gopinath and Lyndsay R. Buckingham -- 12.1 Introduction -- 12.2 Related Works -- 12.3 Methodology -- 12.4 Discussion -- 12.5 Conclusion -- 13 Smart Medication Dispensing: IoT Innovations in Drug Development 255 Sapna Singh Kshatri, Mukesh Kumar Chandrakar, Devanand Bhonsle, Manjushree Nayak, Prashant Tamrakar and Pramisha Sharma -- 13.1 Introduction -- 13.2 Problem Identification -- 13.3 Proposed Method -- 13.4 Applications -- 13.5 Use of ATMEGA328P Using Arduino -- 13.6 Software Used -- 13.7 Result and Discussion -- 13.8 Conclusion -- 14 Telemedicine and Virtual Health: Pioneering Innovation and Future Frontiers in Personalized Patient Care 279 R. Rahul, R. Raghul Jayaprakash, M. Shibhi Varmaah and S. Velmurugan -- 14.1 Introduction to Telemedicine and Virtual Health -- 14.2 Challenges in Telemedicine -- 14.3 Artificial Intelligence in Telemedicine -- 14.4 Neurofeedback and Brain-Computer Interfaces (BCIs) in Telemedicine -- 14.5 Blockchain Technology in Virtual Healthcare -- 14.6 Telemedicine for Personalized Patient Care -- 14.7 Future Directions of Telemedicine in Healthcare -- 15 Blockchain Algorithm: Revolutionizing Healthcare Systems 313 Ritika Awasthi and Arvind Tiwari -- 15.1 Introduction -- 15.2 How Blockchain can Relate to Healthcare -- 15.3 Literature Review -- 15.4 Features of Blockchain -- 15.5 Blockchain Algorithms -- 15.6 Network Model in Blockchain Algorithm -- 15.7 Data Collection and Storage -- 15.8 Diversity in Blockchain Technology -- 15.9 Limitations of Blockchain -- 15.10 Conclusion -- 15.11 Future Work -- 16 Enhancing Cyber-Physical System Security in Healthcare Through Ensemble Learning, Blockchain and Multi-Attribute Feature Selection 349 Jagdish Pimple and Avinash Sharma -- 16.1 Introduction -- 16.2 Literature Survey -- 16.3 Identification of the Problem -- 16.4 Objectives -- 16.5 Proposed Methodology -- 16.6 Result and Discussion -- 16.7 Conclusion and Future Work -- 17 Digitizing Wellness: A Deep Dive Into EHR/EMR Systems 375 Parul Dubey, Anansingh Thinakaran and Rajendra Motiramji Rewatkar -- 17.1 Introduction -- 17.2 Literature Review -- 17.3 AWS and Healthcare Solutions -- 17.4 AWS Services for Healthcare -- 17.5 Building EHR/EMR Solutions on AWS -- 17.6 Innovating with AI and Analytics -- 17.7 Case Studies -- 17.8 Proposed Architecture Overview -- 17.9 Conclusion -- 18 Harmony in Healthcare: Implementing an AI-Powered Biometric System 397 S. Sharmila, M. Nirmala, Somasundaram Devaraj and M. Menagadevi -- 18.1 Introduction to Biometric System -- 18.2 Types of Biometric Systems -- 18.3 Biometrics in Healthcare Application -- 18.4 Biometric System for Monitoring and Disease Diagnosis -- 18.5 Future Direction of Biometrics in Personalized Care -- 19 Investigating the Revolution of Healthcare Application with Intense Comparisons and Case Study 421 Amudhavalli P., S. Urmela, Vishnupriya G., N. Gopinath, R. Anandh and Lyndsay R. Buckingham -- 19.1 Introduction -- 19.2 Digital Twin -- 19.3 Case Study--Healthcare Applications -- 19.4 Future Research Ideas -- 19.5 Conclusion -- References -- Index. |
| Record Nr. | UNINA-9911020179303321 |
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Dubey Parul
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of Second International Conference on Intelligent System : ICIS 2023 / / edited by João Manuel R. S. Tavares, Souvik Pal, Vassilis C. Gerogiannis, Bui Thanh Hung
| Proceedings of Second International Conference on Intelligent System : ICIS 2023 / / edited by João Manuel R. S. Tavares, Souvik Pal, Vassilis C. Gerogiannis, Bui Thanh Hung |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (XII, 518 p. 271 illus., 218 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Algorithms for Intelligent Systems |
| Soggetto topico |
Computational intelligence
Telecommunication Quantitative research Data protection Computational Intelligence Communications Engineering, Networks Data Analysis and Big Data Data and Information Security |
| ISBN |
9789819989768
9819989760 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Deep Convolutional Neural Networks for Brain Tumor Image Segmentation -- A Comparison and Evaluation of Handwritten Digit Recognition (HDR) Algorithms -- An Analysis of Machine Learning Algorithms for AQI Prediction -- Application of The Harmonic Runge-Kutta with Forward-Backward Technique by Parallelism -- A preconditioned conjugate gradient multigrid method for multi-material topology optimization -- Generated Graph for Text Encryption Algorithm Based on BRHC Curve -- Issues and Challenges of Digital Banking System -- Impact of COVID-19 Pandemic on Assessment Process of Technical Education System-Analysis and Critical Review -- Ensuring Energy Efficiency using AI and Nudge Theory to Reach Sustainable Development Goals: A Research Framework -- Configuration and Evaluation of Models for Ecological Systems the case of distribution of Koala -- Design and Experiments of a Manta-Ray Robot for STEM Education -- Price forecast for Imbalanced Label Data by Meta Heuristic model -- Unmanned Aerial Vehicles(UAVs): Performance Analysis of Routing Protocols for Optimized Operations -- Processing the missing value based on the linear regression approach -- Comparative Analysis for Test Case Prioritization using Particle Swarm Optimization Firefly Algorithm -- Improving object detection versatility with 6G in VANETS -- Analysis of Human Behavior on Movie Review -- Artificial Intelligence (ΑΙ) in Education-Current Trends -- The Study of Randomness Properties Exhibited by LAO-3D Lightweight Block Cipher Algorithm -- Association Rule Mining Based Food Preferences Analysis Using FP-Growth Method -- Studies on potential conflicts of network densification in 6G -- Machine Learning Framework for Detecting Fake News over Social Media Platforms -- Analysis and Detection of Political Fake News Using Deep Learning With High-Performance Hybrid-Model -- Wasserstein barycenters over Heisenberg group -- BlockChain Technology with High Performance Via Parallel Processing -- Customer Churn Prediction Model using Deep Learning -- Artificial Intelligence Use in Maritime And Ports Industry as Smart Multimodal Hubs - Emerging Trends -- On-line wear measurement for micro turning round tip tool based on machine vision -- Logistic Regression based Legal Prediction Model -- A Comprehensive Approach for Predicting Different Types of Retinal Detachment with ML algorithms -- Diabetic Retinopathy Automatic Detection and Classification in fundus Images using Modified Residual Convolutional neural networks (CNN) with improved accuracy -- Properties of Idealization Graph over a Ring -- Research Arima Model Forecasts Student's Graduation Rate -- A Home LPM System Based on WSN -- Privacy Preservation Using Network Coding Against Traffic Analysis in Wireless Network -- Optimized Back Propagation based Deep residual Learning Network Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus images -- Use Data Augmentation Model in Image Segmentation -- A prototype for Lung Cancer Forecasting Using Convolution Neural Network Method -- Utilizing Blockchain Technology for Farmer Identity Management and Land Registry Systems in Agriculture -- IoT and Big Data Analytics for Smart Healthcare 4.0 Applications -- 5G Networks with Mm Wave Communications For Enhanced Communication Range. -- Dynamic Load Balancing Schemes for Software Defined Networking (SDN) -- Symmetric Encryption Scheme Based on Fuzzy Graph -- MED-H: Smart Healthcare System Based on IoT and Rule Set -- Landscape View of Hyperparameter Optimization Cybersecurity by Using Bio-inspired Algorithm -- A Multi-hop routing with energy efficient using agglometrive hierarchical clustering using wireless sensor networks in SIOT -- A Study in Understanding the Role of Key Measures in Applying Machine Learning Models for Effective Risk Management in Banking Industry With Focus on Private Banks In India. -- A Converter Tool to Transform the Android Mobile Application into Java Codes for Software Testing -- Genetic Algorithm based Neural Network for Vegetable Price Forecasting on E-Commerce Platform: A Case Study in Malaysia -- A System for Biomedical Image Processing of Brain Tumor via Segmentation and Pattern Recognition. |
| Record Nr. | UNINA-9910847596903321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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