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Computational Intelligence in Healthcare Informatics
Computational Intelligence in Healthcare Informatics
Autore Acharjya D. P
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2024
Descrizione fisica 1 online resource (401 pages)
Altri autori (Persone) MaKun
Collana Studies in Computational Intelligence Series
ISBN 981-9988-53-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- Editors and Contributors -- Acronyms -- Theoretical Foundation of Computational Intelligence Techniques -- Refining Metabolic Network by Fuzzy Matching of Metabolite Names for Improving Metabolites Ranking Toward the Diseases -- 1 Introduction -- 2 Literature Survey -- 3 Materials and Methods -- 3.1 Pairwise Disease Similarity -- 3.2 Threshold Matching Based Metabolite Name Mapping -- 3.3 Fuzzy Matching Based Metabolite Name Matching Algorithm -- 3.4 Pairwise Metabolite Similarity -- 3.5 Identification and Ranking of Disease-Related Metabolites -- 4 Result Analysis -- 4.1 Performance Measures of Threshold and Fuzzy Matching -- 5 Conclusion -- References -- Learning from Imbalanced Data in Healthcare: State-of-the-Art and Research Challenges -- 1 Introduction -- 2 Literature Review of Imbalance Healthcare Data -- 2.1 Imbalanced Cancer Data Diagnosis -- 2.2 Prediction of Imbalanced Covid-19 Data -- 2.3 Drug Prediction with Imbalanced Data -- 2.4 Imbalance Classification of Diabetes -- 2.5 Rare Disease Prediction with Imbalanced Data -- 2.6 Depression and Suicidal Detection with Imbalanced Data -- 3 Methodologies for Handling Imbalance Data in Healthcare -- 3.1 Algorithm Approach -- 3.2 Data-Level Approach -- 3.3 Cost-Sensitive Approach -- 3.4 Multiple Classifier Ensemble Approach -- 4 Source of Imbalanced Healthcare Data -- 5 Conclusions and Future Aspects -- References -- A Review on Metaheuristic Approaches for Optimization Problems -- 1 Introduction -- 2 Metaheuristic Approach and Types -- 2.1 Swarm Intelligence Algorithms -- 2.2 Evolutionary Algorithm -- 2.3 Bio Inspired Algorithms -- 2.4 Physics and Chemistry Based Algorithms -- 2.5 Other Algorithms -- 3 Category Wise Representatives of Metaheuristic Approaches -- 3.1 Cuckoo Search Algorithm -- 3.2 Genetic Algorithm -- 3.3 Harmony Search.
3.4 Biogeography Based Optimization -- 4 Conclusion and Future Scope -- References -- Diabetes Prediction: A Comparison Between Generalized Linear Model and Machine Learning -- 1 Introduction -- 2 Data Mining Process -- 2.1 Classification -- 2.2 Types of Classification Techniques -- 2.3 Major Classification Algorithms -- 3 Related Research Work -- 4 Computational Methodology -- 4.1 Data Pre-processing -- 4.2 Application of Classification Techniques -- 5 Experimental Results and Discussion -- 5.1 Binary Logistics Regression -- 5.2 Support Vector Machine -- 6 Conclusion -- References -- Prediabetes Prediction Using Response Surface Methodology and Probabilistic Neural Networks Model in an Ethnic South Indian Population -- 1 Introduction -- 2 Brief Introduction to Prediabetes -- 3 Materials and Methods -- 3.1 Clinical Study -- 3.2 Biochemical Study -- 4 Computational Intelligence Techniques in Prediabetes Prediction -- 4.1 Pearson Correlation -- 4.2 Response Surface Methodology -- 4.3 Artificial Neural Network -- 4.4 Probabilistic Neural Networks -- 5 Results and Analysis -- 5.1 Pearson Correlation Analysis -- 5.2 Response Surface Methodology Analysis -- 5.3 Artificial Neural Networks -- 5.4 Probabilistic Neural Networks -- 6 Discussion -- 6.1 Residual Plots for Predicted Glycemic Levels Using RSM -- 6.2 Regression Plot for Prediabetes Prediction Using ANN -- 7 Conclusion -- References -- Localization and Classification of Brain Tumor Using Multi-layer Perceptron -- 1 Introduction -- 2 Background Literature -- 3 Foundations of Neural Network -- 3.1 Feed-Forward Networks -- 3.2 Recurrent Networks -- 3.3 Radial Basis Network -- 3.4 Multi-layer Perceptron -- 4 Phases of Brain Tumor Detection -- 5 Experimental Results -- 6 Conclusion -- References -- Computational Intelligence in Analyzing Health Data.
Information Retrieval from Healthcare Information System -- 1 Introduction -- 2 Challenges of Information Retrieval in Health Care -- 2.1 The Medical Healthcare Benefits and Challenges -- 2.2 IoT-Based Medical Services Data Model -- 2.3 Frequently Attainable Metadata Model for IoT Data -- 3 UDA-IoT Ubiquitous Data Accessing for Information System -- 3.1 Accessing UDA-IoT Data and Cloud Platform -- 4 A Case Study on UDA-IoT Methodology -- 4.1 Emergency Medical DSS Ubiquitous Data Accessing Implementation -- 4.2 Discussion -- 5 Conclusion -- References -- Association Rule Mining for Healthcare Data Analysis -- 1 Introduction -- 2 Related Works -- 2.1 Liver Diseases -- 2.2 Heart Diseases -- 2.3 Kidney Diseases -- 3 Association Rule Mining -- 4 Measures Used in Association Rule Mining -- 5 Experimental Analysis and Results -- 6 Conclusion and Future Direction -- References -- Feature Selection and Classification of Microarray Cancer Information System: Review and Challenges -- 1 Introduction -- 2 Background Study -- 2.1 Fundamentals of Feature Selection -- 2.2 Fundamental Classification Techniques -- 3 Related Research Work -- 4 Result and Analysis -- 4.1 Analysis Based on Feature Selection -- 4.2 Analysis Based on Dataset -- 4.3 Analysis Based on Classifier -- 5 Conclusion -- References -- Early Detection of Osteoporosis and Osteopenia Disease Using Computational Intelligence Techniques -- 1 Introduction -- 2 Methods of Computational Intelligence -- 2.1 Artificial Neural Networks for Osteoporosis Classification -- 2.2 Extreme Learning Machine in Osteoporosis Classification -- 3 A General Evaluation Scheme with a Block Diagram -- 4 Findings and Evaluation -- 5 Conclusion -- References -- Pathway to Detect Cancer Tumor by Genetic Mutation -- 1 Introduction -- 2 Background Study -- 2.1 Literature Survey -- 3 System Modeling -- 4 Materials and Methods.
4.1 Stacking Model -- 4.2 K-Nearest Neighbor -- 4.3 Linear Support Vector Machines -- 5 Experiment and Result Analysis -- 5.1 Dataset -- 5.2 Performance Analysis -- 5.3 Machine Learning Model Implementations -- 5.4 Comparison of Machine Learning Models -- 6 Conclusion and Future Scope -- References -- A Knowledge Perception: Physician and Patient Toward Telehealth in COVID-19 -- 1 Introduction -- 2 Review of Telehealth and Telemedicine Services -- 3 Methodology -- 4 Results Analysis -- 4.1 Patient's Perception of Telehealth -- 4.2 Physician's Perception of Telehealth -- 4.3 Data Interpretation on Patient's Response -- 4.4 Data Interpretation on Physician's Response -- 5 Conclusion -- References -- Computational Intelligence in Electronic Health Record -- Classification of Cardiovascular Disease Information System Using Machine Learning Approaches -- 1 Introduction -- 2 Machine Learning for Cardiovascular Disease Classification -- 3 Cardiovascular Disease Information System -- 4 Exploratory Data Analysis -- 5 Performance Measures -- 6 Conclusion -- References -- Automatic Edge Detection Model of MR Images Based on Deep Learning Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 Fuzzy Logic Approach -- 2.2 Neuro-Fuzzy Approach -- 3 Proposed Research Design Workflow -- 4 Experimental Results and Analysis -- 5 Conclusions -- References -- Lung Disease Classification Based on Lung Sounds-A Review -- 1 Introduction -- 2 Natural Ways to Recognize Symptoms -- 3 Clinical Process to Recognize Pneumonia -- 4 Data Availability -- 5 Computational Intelligence in Lung Sound Classification -- 5.1 Feature Extraction Methods and the Classification -- 5.2 Miscellaneous Methods -- 6 Conclusion -- References -- Analysis of Forecasting Models of Pandemic Outbreak for the Districts of Tamil Nadu -- 1 Introduction -- 2 Literature Survey.
3 Research Methodology -- 3.1 SIR Model -- 3.2 ARIMA Model -- 3.3 Forecasting -- 4 Results and Discussions -- 5 Conclusion -- References -- Suppression of Artifacts from EEG Recordings Using Computational Intelligence -- 1 Introduction -- 2 Computational Intelligence -- 2.1 Evolutionary Computing -- 2.2 Swarm Intelligence -- 3 Characteristics of the EEG Signal -- 3.1 Types of Artifacts -- 4 Artifact Removal Techniques -- 4.1 Filtering Methods -- 4.2 Regression Methods -- 4.3 Wavelet Transform -- 4.4 Blind Source Separation -- 4.5 Mode Decomposition Methods -- 5 Performance Evaluation and Discussion -- 6 Conclusion -- References -- Rough Computing in Healthcare Informatics -- 1 Introduction -- 2 Information System -- 3 Rough Computing -- 3.1 Rough Set -- 3.2 Fuzzy Rough Set -- 3.3 Rough Set on Fuzzy Approximation Space -- 3.4 Rough Set on Intuitionistic Fuzzy Approximation Space -- 4 Hybridized Rough Computing -- 5 Healthcare Informatics -- 5.1 Feature Selection -- 5.2 Classification -- 5.3 Clustering -- 5.4 Decision Support System -- 6 Healthcare Applications -- 7 Conclusion -- References -- Computational Intelligence in Ethical Issues in Healthcare -- Ethical Issues on Drug Delivery and Its Impact in Healthcare -- 1 Introduction -- 2 Review of Literature -- 3 Rudiments of Genetic Algorithm -- 3.1 Fitness Function -- 3.2 Selection -- 3.3 Crossover -- 3.4 Mutation -- 4 Problem Formulation -- 4.1 Modeling of the Problem -- 5 Methodology -- 5.1 Complete Elitist Genetic Algorithm -- 6 Results and Discussions -- 6.1 Experimental Results -- 6.2 Analysis of the Findings -- 6.3 Comparative Study -- 7 Conclusion and Future Extensions -- References -- Privacy-Preserving Deep Learning Models for Analysis of Patient Data in Cloud Environment -- 1 Introduction -- 2 Medical Data, Deep Learning, and Cloud Computing -- 2.1 Medical Data and Secondary Usage.
2.2 Deep Learning.
Record Nr. UNINA-9910841858203321
Acharjya D. P  
Singapore : , : Springer Singapore Pte. Limited, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Hybrid Intelligent Systems [[electronic resource] ] : 22nd International Conference on Hybrid Intelligent Systems (HIS 2022), December 13–15, 2022 / / edited by Ajith Abraham, Tzung-Pei Hong, Ketan Kotecha, Kun Ma, Pooja Manghirmalani Mishra, Niketa Gandhi
Hybrid Intelligent Systems [[electronic resource] ] : 22nd International Conference on Hybrid Intelligent Systems (HIS 2022), December 13–15, 2022 / / edited by Ajith Abraham, Tzung-Pei Hong, Ketan Kotecha, Kun Ma, Pooja Manghirmalani Mishra, Niketa Gandhi
Autore Abraham Ajith
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (1380 pages)
Disciplina 006.3
Altri autori (Persone) HongTzung-Pei
KotechaKetan
MaKun
Manghirmalani MishraPooja
GandhiNiketa
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Artificial intelligence
Computational Intelligence
Artificial Intelligence
Soggetto non controllato Artificial Intelligence
Engineering
Computers
Technology & Engineering
ISBN 3-031-27409-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910728399503321
Abraham Ajith  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Innovations in bio-inspired computing and applications : proceedings of the 10th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2019) ; Gunupur, Odisha, India ; December 16-18, 2019 / / editors, Ajith Abraham [et al.]
Innovations in bio-inspired computing and applications : proceedings of the 10th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2019) ; Gunupur, Odisha, India ; December 16-18, 2019 / / editors, Ajith Abraham [et al.]
Edizione [1st edition 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (398 pages)
Disciplina 006
Collana Advances in Intelligent Systems and Computing
Soggetto topico Natural computation
Neural networks (Computer science)
Soft computing
ISBN 3-030-49339-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Towards the speed enhancement of Association rule mining algorithm for Intrusion Detection System -- Image Retrieval using Bat Optimization and Image Entropy -- Logistic Regression on Hadoop using PySpark -- Analysis of Pre-processing Techniques for Odia Character Recognition -- Cluster-based Under-Sampling using Farthest Neighbour Technique for Imbalanced Datasets -- Vehicle Detection and Classification: A Review -- Methods for Automatic Gait Recognition: A review -- Comparative Performance Exploration and prediction of Fibrosis, Malign Lymph, Metastases, Normal Lymphogram using Machine Learning Method -- Decision Forest classifier with flower search optimization algorithm for efficient detection of BHP flooding attacks in Optical Burst Switching Network.
Record Nr. UNINA-9910484606803321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 3 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 3 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Autore Abraham Ajith
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (602 pages)
Disciplina 006.3
Altri autori (Persone) PllanaSabri
CasalinoGabriella
MaKun
BajajAnu
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Artificial intelligence
Computational Intelligence
Artificial Intelligence
Soggetto non controllato Science
ISBN 3-031-35501-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910728946403321
Abraham Ajith  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 2 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 2 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Autore Abraham Ajith
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (614 pages)
Disciplina 006.3
Altri autori (Persone) PllanaSabri
CasalinoGabriella
MaKun
BajajAnu
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Artificial intelligence
Computational Intelligence
Artificial Intelligence
Soggetto non controllato Science
ISBN 3-031-35507-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910728934703321
Abraham Ajith  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 1 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 1 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Autore Abraham Ajith
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (592 pages)
Disciplina 006.3
Altri autori (Persone) PllanaSabri
CasalinoGabriella
MaKun
BajajAnu
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Artificial intelligence
Computational Intelligence
Artificial Intelligence
Soggetto non controllato Artificial Intelligence
Engineering
Computers
Technology & Engineering
ISBN 3-031-27440-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- ISDA 2022-Organization -- Contents -- KMetaTagger: A Knowledge Centric Metadata Driven Hybrid Tag Recommendation Model Encompassing Machine Intelligence -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Results and Performance Evaluation -- 5 Conclusion -- References -- KCReqRec: A Knowledge Centric Approach for Semantically Inclined Requirement Recommendation with Micro Requirement Mapping Using Hybrid Learning Models -- 1 Introduction -- 2 Related Works -- 3 Proposed System Architecture -- 4 Implementation and Performance Evaluation and Results -- 5 Conclusion -- References -- Object Classification Using ECOC Multi-class SVM and HOG Characteristics -- 1 Introduction -- 1.1 Background -- 1.2 Research Objectives -- 1.3 Paper Organization -- 2 Proposed Scheme for Object Classification -- 3 System Description -- 3.1 Image Datasets -- 3.2 ECOC Based Multi-class SVM -- 3.3 Appropriate Cell Size Selection for HOG Feature -- 4 Results and Discussions -- 5 Conclusion -- References -- GA Evolved Configuration Data for Embryonic Architecture with Built-in Self-test -- 1 Introduction -- 2 Embryonic Digital Circuit Architecture Using CGP Data -- 3 Novel Parallel GA Design for CGP Configuration Data Generation -- 3.1 Optimum Individual Monogenetic GA-OIMGA -- 3.2 Parallel HsClone GA -- 4 Embryonic Cells with Built-in Self-Test Design -- 5 Embryonic Adder and Comparator Cell Fault Detection -- 6 Conclusion and Scope for Future Work -- References -- A Multi-layer Deep Learning Model for ECG-Based Arrhythmia Classification -- 1 Introduction -- 2 Related Work -- 3 Material and Method -- 3.1 Dataset -- 3.2 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- Analyzing Electoral Data Using Partitional and Hierarchical Clustering Algorithms -- 1 Introduction -- 2 The Municipal Human Development Index (MHDI).
3 Data Used in the Experiments -- 4 Methodology and Experiments -- 5 Conclusions -- References -- Medical Decision Making Based 5D Cardiac MRI Segmentation Tools -- 1 Introduction -- 2 Methods and Materials -- 3 Theory -- 3.1 Concept of the 5D Segmentation and Medical Issue -- 3.2 Goals and Contributions -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- India Post Service Facility Layout Design Selection and Evaluation Using MCDM Approach -- 1 Introduction -- 2 Literature Support -- 3 Research Methodology -- 4 Application - NSH Mangalore -- 5 Results -- 5.1 Finding the Weightage Criteria -- 5.2 Calculation Method -- 6 Conclusions -- References -- Weighted Pathfinding in the Paparazzi Problem with Dynamic Obstacles -- 1 Introduction -- 2 Problem Statement -- 3 Background Information -- 3.1 A* Algorithm -- 3.2 Extended A* Algorithm -- 3.3 Heuristics -- 3.4 Dynamic Obstacles -- 4 Implementation and Testing -- 4.1 Code Structure -- 4.2 Pathfinding -- 5 Results and Discussion -- 5.1 Data Distribution -- 5.2 Pathfinding -- 5.3 Diagonal Movement -- 5.4 Overall Heuristic Performance -- 6 Conclusions -- References -- A Rapid Review on Ensemble Algorithms for COVID-19 Classification Using Image-Based Exams -- 1 Introduction -- 2 Ensemble Algorithms -- 3 Methodology -- 3.1 Inclusion Criteria -- 3.2 Exclusion Criteria -- 4 Results and Discussion -- 4.1 Q1 - Ensemble Technique -- 4.2 Q2 - Number of Classes -- 4.3 Q3 - Machine Learning Algorithms and Models -- 4.4 Q4 - Datasets -- 5 Conclusions -- References -- Indian Postal Service Quality Assessment Using Graph Theoretic Approach - A Quantitative Decision-Making Tool -- 1 Introduction -- 1.1 Importance of the Study -- 2 Literature Review -- 2.1 Graph Theoretical (GT) Model -- 3 Research Methodology -- 3.1 Graph-Theoretic Model Approach -- 4 Analysis and Results -- 4.1 Graph Theory Calculation.
5 Conclusions -- References -- Analyzing the Critical Success Factors of Lean System Implementation in India Post Using DEMATEL Method -- 1 Introduction -- 1.1 Rationale of the Study -- 2 Literature Support -- 3 Research Methodology -- 3.1 Steps for DEMATEL Method -- 4 Case Application: Indian Postal NSH Mangalore, India -- 5 Conclusions -- References -- Application of Artificial Intelligence in Mental Health -- 1 Introduction to Artificial Intelligence in Healthcare -- 2 Mental Health -- 2.1 AI in Healthcare -- 2.2 Ethics and AI Mental Health Research -- 2.3 AI Research on the Involvement of Patient and Public Mental Health -- 2.4 Well-Being and Educational Performance -- 2.5 Internet-Based Mental Health Care -- 2.6 Mental Healthcare Chatbots -- 3 Literature Survey -- 4 Constraints of AI and Mental Health Care Research -- 5 Statistics Scenario in the Area of AI in Mental Health Care Research -- 6 Conclusion -- References -- Cold Rolling Mill Energy Consumption Prediction Using Machine Learning -- 1 Introduction -- 2 Cold Rolling Mill and Energy Consumption -- 3 Proposed Approach -- 4 Results and Analysis: Model Training and Energy Prediction -- 5 Conclusions and Future Work -- References -- Virtual Reconstruction of Adaptive Spectral and Spatial Features Based on CNN for HSI Classification -- 1 Introduction -- 2 Proposed Approach -- 2.1 Extraction of Spectral Data Vectors and Fusions of Pixels to Obtain a Single Spatial-Spectral Band -- 2.2 Apply Five Algorithms to Create Five Virtual Layers -- 2.3 3D Image Reconstruction -- 2.4 Edge-Adaptive Spatial Data Extraction -- 2.5 Convolution and Processing of Each Block Until Recognition of the pixel -- 2.6 Placing Pixels in Their Positions, Merging the Five Spectral Bands and Labeling -- 3 Experiences and Results -- 3.1 Tests -- 3.2 Results and Discussions -- 4 Conclusion -- References.
Enhancing Rental Bike Count and Availability Prediction Using Regression Modelling -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Multiple Linear Regression -- 3.2 Polynomial Regression -- 4 Results -- 5 Conclusion and Fututre Enhancement -- References -- Application of WASPAS Method for the Evaluation of Tamil Nadu Private Travels -- 1 Introduction -- 2 Literature Support -- 3 Research Methods -- 4 Case Study - Chennai, Tamilnadu, Southern India -- 4.1 Application of WASPAS Method -- 5 Comparative Study -- 6 Conclusion -- References -- Time Series Forecast Applied to Electricity Consumption -- 1 Introduction -- 2 Related Work -- 3 BackGround of Study -- 3.1 Definitions -- 3.2 Machine Learnings Models -- 4 Material and Methods -- 4.1 Dataset Description -- 4.2 Performance Indices -- 5 Simulation Results -- 5.1 Regression Models - Data with Daily Periodicity -- 5.2 Regression Models - Data with Daily Periodicity (Outlier Removal) -- 5.3 Regression Models - Data with Monthly Periodicity -- 5.4 Regression Models - Data with Daily Periodicity (Outlier Removal) - Moving Average -- 5.5 Multi Layer Perceptron (MLP) - Data with Monthly Periodicity -- 5.6 Recurrent Neural Network (RNR) - Data with Monthly Periodicity -- 6 Conclusions -- References -- A Survey on Text Processing Using Deep Learning Techniques -- 1 Introduction -- 2 Sentiment Analysis is Divided into Numerous Categories -- 2.1 Sentiment with a Finer Granularity -- 2.2 Sentiment Analysis for Emotion Identification -- 2.3 Analyses Based on Aspects -- 2.4 Sentiment Analysis Based on Intent -- 3 Approaches to Sentiment Analysis -- 3.1 Rule-Based Approach -- 3.2 Machine Learning Approach -- 3.3 Lexicon Based Approach -- 4 All Approaches Advantages and Limitations -- 5 Text-Based Emotion Detection (TBED) -- 5.1 Datasets for Text-Based ED (Emotion Detection) Research -- 6 Feature Set.
6.1 Extraction of Feature -- 6.2 Feature Selection -- 7 Comparison Analysis -- 7.1 Lexicon Based Approach -- 7.2 Dictionary-Based Classification -- 7.3 Corpus-Based Classification -- 7.4 Machine Learning Based Classification -- 7.5 Support Vector Machine -- 7.6 Comparative Table for Different Classification Algorithm -- 7.7 Naïve Bayes -- 7.8 K-Nearest Neighbor -- 7.9 Maximum Entropy -- 7.10 Decision Tree Learning -- 7.11 Semantic Orientation Approach -- 7.12 Keyword-Based Classification -- 7.13 Emotions Based Classifications -- 8 Issues in Text Sentiment Analysis -- 9 Conclusion -- References -- RePI: Research Paper Impact Analysis -- 1 Introduction -- 2 Literature Survey -- 2.1 Previous Works -- 2.2 Impact Metrics -- 2.3 Keyword Extraction -- 3 Dataset Creation -- 4 Methodology and Architecture -- 5 Design and API Integration -- 5.1 RAKE -- 5.2 Implementation -- 6 Impact Metric Calculation -- 7 Results -- 7.1 Visualizations -- 7.2 Impact Metric Ratio -- 8 Conclusion -- References -- Human-Centred Artificial Intelligence in Sound Perception and Music Composition -- 1 Introduction -- 2 Melody and Musical Grammar -- 3 Formalization of Musical Grammar Rules -- 4 Obtained Results -- 5 Discussion and Conclusions -- References -- Multi-objective Optimization for Sensor Networks Based Smart Parking Systems -- 1 Introduction -- 2 Related Works -- 3 Real Time Smart Parking System Description -- 4 Mathematical Formulation -- 4.1 Poisson Process -- 4.2 Linear Programming Formulation -- 5 Performance Evaluation -- 6 Open Research Issue: Sensor Networks and Artificial Neural Networks (ANN) -- 7 Conclusion -- References -- Process Automation with Digital Robots Under Smart University Concept -- 1 Introduction -- 2 Literature Review -- 3 Digital Transformation of Processes -- 3.1 Digital Transformation -- 3.2 Process Automation -- 3.3 Human Path and Robot Path.
4 Case Study.
Record Nr. UNINA-9910728933403321
Abraham Ajith  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 4 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Intelligent Systems Design and Applications [[electronic resource] ] : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 4 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
Autore Abraham Ajith
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (631 pages)
Disciplina 006.3
Altri autori (Persone) PllanaSabri
CasalinoGabriella
MaKun
BajajAnu
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Artificial intelligence
Computational Intelligence
Artificial Intelligence
Soggetto non controllato Science
ISBN 3-031-35510-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- ISDA 2022-Organization -- Contents -- Machine Learning Approach for Detection of Mental Health -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Proposed Model -- 5 Results and Discussion -- 6 Conclusion and Future Scope -- References -- U-Net as a Tool for Adjusting the Velocity Distributions of Rheomagnetic Fluids -- 1 Introduction -- 2 Theoretical Basics -- 2.1 Physics-Based Loss -- 2.2 Rheomagnetic Fluids -- 3 Simulation Modeling -- 4 Results and Discussion -- 5 Conclusions -- References -- Detection of Similarity Between Business Process Models with the Integration of Semantics in Similarity Measures -- 1 Introduction -- 2 Similarity Measures -- 2.1 Syntactic Measures -- 2.2 Semantic Measures -- 2.3 Structural Measures -- 2.4 Behavioral Measures -- 3 Problem Illustration -- 3.1 Similarity Measures -- 3.2 Dimensions of Semantic Similarity -- 3.3 Cardinality Problem -- 3.4 Genetic Algorithm -- 4 Related Work -- 5 Our Approach -- 5.1 Steps of Genetic Algorithm -- 6 Conclusion -- References -- Efficient Twitter Sentiment Analysis System Using Deep Learning Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Proposed Method -- 3.1 Pre-processing -- 3.2 User-Mention -- 3.3 EMOJ Positive and Negative -- 3.4 Feature Selection -- 3.5 Classification -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- An Efficient Deep Learning-Based Breast Cancer Detection Scheme with Small Datasets -- 1 Introduction -- 1.1 Contributions -- 2 Proposed Method -- 2.1 Preprocessing -- 2.2 CNN Architecture -- 3 Datasets -- 4 Results and Discussion -- 5 Conclusion -- References -- Comparative Analysis of Machine Learning Models for Customer Segmentation -- 1 Introduction -- 2 Problem Statement -- 3 Literature Review -- 4 Algorithms for Customer Segmentation -- 4.1 Customer Segmentation Using K-Means.
4.2 Customer Segmentation Using DBSCAN -- 4.3 Agglomerative Clustering (Using PCA) -- 4.4 K-Means Using PCA -- 5 Results and Discussion -- 5.1 K-Means Model -- 5.2 DBSCAN -- 5.3 Agglomerative Clustering with PCA -- 5.4 Kmeans with PCA -- 6 Conclusion -- References -- An Intelligent Approach to Identify the Eggs of the Insect Bemisia Tabaci -- 1 Introduction -- 2 Overview of Proposed Approach -- 2.1 Deep Learning Algorithm -- 2.2 Auto-encoder -- 2.3 Stacked Auto-encoder for Egg Classification -- 3 Results and Discussion -- 3.1 Databases Used -- 3.2 Result -- 3.3 Test Phase -- 4 Conclusion -- References -- Overview of Blockchain-Based Seafood Supply Chain Management -- 1 Introduction -- 2 Blockchain Technology: Overview and Adoption in Supply Chains Management -- 3 An Overview of Blockchain Based Seafood Supply Chain Management Systems -- 4 Discussion and Research Challenges -- 5 Conclusion -- References -- Synthesis of a DQN-Based Controller for Improving Performance of Rotor System with Tribotronic Magnetorheological Bearing -- 1 Introduction -- 2 System Description and Modeling -- 2.1 Rotor Model -- 2.2 Bearing Model -- 3 Model Verification -- 4 Designing a DQN Controller -- 5 Results and Discussion -- 6 Conclusion -- References -- Card-Not-Present Fraud Detection: Merchant Category Code Prediction of the Next Purchase -- 1 Introduction -- 2 State of the Art -- 2.1 What is a Card-Not-Present Transaction? -- 2.2 Card not Present Fraud Scenario -- 2.3 What is the Merchant Category Code? -- 2.4 Prediction of Merchant Category Code for the Next Buy -- 3 Related Works -- 3.1 Online Payment Fraud Detection AI Proposals -- 4 Conclusion -- References -- Fast Stroke Lesions Segmentation Based on Parzen Estimation and Non-uniform Bit Allocation in Skull CT Images -- 1 Introduction -- 2 Related Works: classical and Deep Learning Approaches.
3 Materials and Methods -- 3.1 Level Set -- 3.2 Parzen Window -- 3.3 Non-uniform Bit Allocation: -law and A-law Algorithms -- 3.4 Datasets and Evaluation Metrics -- 4 LSBRD: An Approach Based on Parzen Estimation and Non-uniform Bit Allocation via -law and A-law -- 5 Results and Discussions -- 5.1 Algorithm Performance Analysis -- 6 Conclusion and Future Works -- References -- Methods for Improving the Fault Diagnosis Accuracy of Rotating Machines -- 1 Introduction -- 2 Intellectual Diagnostic Methods -- 2.1 Fully Connected Neural Networks -- 2.2 Generative Adversarial Network -- 3 Results and Discussion -- 3.1 Data Collection -- 3.2 Fully Connected Neural Networks to Rotor Diagnostic Defects -- 3.3 Generative Adversarial Network to Increasing the Volume and Variety of Training Data -- 4 Conclusion -- References -- Heuristics Assisted by Machine Learning for the Integrated Production Planning and Distribution Problem -- 1 Introduction -- 2 Problem Definition -- 3 Proposed Algorithms -- 3.1 Decoding Algorithms -- 3.2 Initial Solution -- 3.3 Neighborhood Search Heuristics -- 3.4 Framework -- 4 Computational Experiments -- 4.1 Computational Results -- 5 Conclusions -- References -- LSTM-Based Congestion Detection in Named Data Networks -- 1 Introduction -- 2 Background and Related Works -- 2.1 Long Short Term Memory Background -- 2.2 Related Works -- 3 LSTM-Based Congestion Detection -- 4 Performance Evaluation -- 5 Conclusion -- References -- Detection of COVID-19 in Computed Tomography Images Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Image Acquisition -- 3.2 Pre-processing -- 3.3 Data Augmentation -- 3.4 Evaluated Architectures -- 3.5 Proposed Method -- 4 Experimental Results -- 4.1 Transfer Learning Results -- 4.2 Fine-Tuning Results -- 5 Discussion -- 6 Conclusion -- References.
Abnormal Event Detection Method Based on Spatiotemporal CNN Hashing Model -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Spatiotemporal Stream -- 3.2 Network Architecture -- 4 Experiments Results -- 4.1 Network Architecture -- 4.2 Datasets -- 4.3 Evaluation -- 5 Conclusion -- References -- A Multi-objective Iterated Local Search Heuristic for Energy-Efficient No-Wait Permutation Flowshop Scheduling Problem -- 1 Introduction -- 2 Problem Description -- 3 Multi-objective Iterated Local Search Heuristic -- 3.1 Multi-objective Local Search and Perturbation -- 4 Computational Experiments -- 4.1 Obtained Results -- 5 Conclusions -- References -- An Elastic Model for Virtual Computing Labs Using Timed Petri Nets -- 1 Introduction -- 2 Cloud Computing -- 2.1 Cloud Service Models -- 2.2 Cloud Deployement Models -- 2.3 Benefits and Challenges of Cloud Computing -- 3 Related Works -- 4 Background -- 4.1 Timed and Colored Petri Nets -- 4.2 Cloud Elasticity -- 5 Proposed Approach -- 5.1 The Challenge for Moving to VCL -- 5.2 Model Description -- 5.3 Vertical Elasticity Algorithm -- 5.4 Proposed Solution -- 5.5 Support Tools -- 6 Conclusion -- References -- A Decision Support System Based Vehicle Ontology for Solving VRPs -- 1 Introduction -- 2 Literature Review -- 2.1 Classification of Vehicle Routing Problems -- 2.2 Ontologies for Vehicle Domain -- 3 Decision Support System -- 4 Proposed VRP-Vehicle Ontology -- 5 Conclusion -- References -- Web API Service to RDF Mapping Method for Querying Distributed Data Sources -- 1 Introduction -- 2 Related Work -- 2.1 Smart City Platforms -- 2.2 Relational Databases -- 3 Accident Card Analysis System -- 3.1 R2RML Mapping -- 3.2 Data Quality -- 4 Web API Service to RDF Mapping Method Description -- 4.1 Weather Data Sources Specific -- 4.2 W2RML Scheme -- 5 Conclusion -- References.
Risk Management in the Clinical Pathology Laboratory: A Bayesian Network Approach -- 1 Introduction -- 2 Research Design -- 3 Results -- 3.1 Literature Review -- 3.2 Risk Model -- 4 Conclusions -- References -- Leveraging Sequence Mining for Robot Process Automation -- 1 Introduction -- 2 Related Works -- 3 The Proposed Approach -- 3.1 FEM-M: Frequent Episode Miner -- 3.2 TEF-M: Target Episode Finder -- 4 Experimental Results -- 5 A Case Study -- 6 Conclusions -- References -- Intelligent Agents System for Intention Mining Using HMM-LSTM Model -- 1 Introduction and Motivation -- 2 Related Works -- 3 Architecture of Multi Intelligent Agents System Approach -- 3.1 Description of Agents -- 3.2 Hybrid Model -- 4 Experimentation and Validation -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Result -- 5 Conclusion -- References -- Unsupervised Manipulation Detection Scheme for Insider Trading -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Feature Characterisation -- 3.2 Kernel Principal Component Analysis (KPCA) -- 4 Results and Discussion -- 5 Conclusion -- References -- A Comparative Study for Modeling IoT Security Systems -- 1 Introduction -- 1.1 Originality and Objectives -- 1.2 Outline -- 2 IoT and Modeling Languages -- 2.1 IoT Background -- 2.2 Overview of UML -- 2.3 Overview of SysML -- 3 Related Works -- 4 Proposed New IoT Security Modeling -- 4.1 IoT Architecture and Security Requirements -- 4.2 Modeling the Security of the Physical Layer and the Network Layer of IoT Systems with UML Language: Use Case Diagram -- 4.3 Modeling IoT Security Systems Using SysML Language: Requirement Diagram -- 5 Analysis and Discussion -- 6 Conclusion -- References -- Improving the Routing Process in SDN Using a Combination of the Evidence Theory and ML -- 1 Introduction -- 2 Related Work -- 3 Overview of the Trust-Based Routing Scheme.
4 Global Trust (GT) Vector Computation.
Record Nr. UNINA-9910728932903321
Abraham Ajith  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
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Lo trovi qui: Univ. Federico II
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Intelligent Systems Design and Applications [[electronic resource] ] : 19th International Conference on Intelligent Systems Design and Applications (ISDA 2019) held December 3-5, 2019 / / edited by Ajith Abraham, Patrick Siarry, Kun Ma, Arturas Kaklauskas
Intelligent Systems Design and Applications [[electronic resource] ] : 19th International Conference on Intelligent Systems Design and Applications (ISDA 2019) held December 3-5, 2019 / / edited by Ajith Abraham, Patrick Siarry, Kun Ma, Arturas Kaklauskas
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (679 pages)
Disciplina 006.33
Collana Advances in Intelligent Systems and Computing
Soggetto topico Computational intelligence
Artificial intelligence
Computational Intelligence
Artificial Intelligence
ISBN 3-030-49342-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Data Jackets as Communicable Metadata for Potential Innovators – Toward Opening to Social Contexts -- A Proposal Based on Instance Typicality for Dealing with Nominal Attribute Values in Instance-Based Learning Environments -- Dataset for Intrusion Detection in Mobile Ad-Hoc Networks -- Visual Password Scheme Using Bag Context Shape Grammars -- Peak detection enhancement in autonomous wearable Fall Detection -- Automated detection of tuberculosis from sputum smear microscopic images using transfer learning techniques -- Comparative Performance Analysis of Neural Network Base Training Algorithm and Neuro-Fuzzy System with SOM for the Purpose of Prediction of the Features of Superconductors.
Record Nr. UNINA-9910484516903321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
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Next Generation Information Processing System : Proceedings of ICCET 2020, Nanded, India, 9-11 January 2020 . Volume 2 / / editors, Prachi Deshpande [et al.]
Next Generation Information Processing System : Proceedings of ICCET 2020, Nanded, India, 9-11 January 2020 . Volume 2 / / editors, Prachi Deshpande [et al.]
Edizione [1st edition 2021.]
Pubbl/distr/stampa Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (xii, 344 pages)
Disciplina 621.382
Collana Advances in Intelligent Systems and Computing
Soggetto topico Electrical engineering
Information technology
Mobile communication systems
Telecommunication
Wireless communication systems
ISBN 981-15-4851-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto UAV Communication in FANETs using Metaheuristic Techniques -- On-demand joint predictive Flooding in Vehicular Adhoc Networks -- Entity-Centric Combined Trust (ECT) algorithm to detect packet dropping attack in vehicular ad-hoc networks (VANETs) -- Optimized Low Energy Adaptive Clustering Hierarchy in Wireless Sensor Network -- QoS in Vertical Handoff for Wireless network using Hungarian model and Data Parceling technique.
Record Nr. UNINA-9910484384303321
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021
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Lo trovi qui: Univ. Federico II
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