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Fourth Congress on Intelligent Systems : CIS 2023, Volume 2
| Fourth Congress on Intelligent Systems : CIS 2023, Volume 2 |
| Autore | Kumar Sandeep |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (480 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
BalachandranK
KimJoong Hoon BansalJagdish Chand |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9990-40-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Comparative Study of Various Machine Learning Techniques for Parkinson Disease Detection Based on Handwriting -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Acquisition and Collection -- 3.2 Feature Extraction from Images -- 3.3 Machine Learning for Classification -- 4 Results and Discussion -- 4.1 Metrics -- 5 Conclusion -- References -- A Systematic Review of Air Pollution and Weather Parameters Detection Methods in Satellite Remote Sensing -- 1 Introduction -- 2 Air Pollutants -- 2.1 Carbon Monoxide (CO) -- 2.2 Carbon Dioxide (CO2) -- 2.3 Nitrogen Compounds (NO) -- 2.4 Sulfur Dioxide (SO2) -- 2.5 Ozone (O3) -- 2.6 Particulate Matter (PM) -- 3 Methodology -- 4 Review Analysis -- 5 Conclusion and Future -- References -- Fingerprint-Based Asymmetric Bio-Cryptographic Key Generation Using Convolution Network -- 1 Introduction -- 2 Literature Review -- 3 Proposed Method -- 3.1 Work Flow -- 3.2 Preprocessing and Image Splitting -- 3.3 Image Shuffling -- 3.4 Template Generation -- 3.5 Large Number Generation -- 3.6 Prime Numbers Generation -- 3.7 Public-Private Key Generation -- 4 Results and Discussion -- 4.1 Data Set -- 4.2 Execution Time -- 4.3 Key Generation Range -- 4.4 Security Analysis -- 5 Conclusion -- References -- Comparison of Brain Tumor Detection Techniques by Using Different Machine Learning YOLO Algorithms -- 1 Introduction -- 2 Methodology -- 2.1 Data Preprocessing -- 2.2 Proposed MRI Brain Tumor Detection Model and Detection Unit -- 2.3 Evaluation Matrix -- 3 Experimental Result and Discussion -- 3.1 Results After Preprocessing -- 3.2 Overall Performance -- 4 Conclusion -- References -- Media Steganography Using CNN with Blockchain-Enabled Secure File Transfer -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion.
References -- Diagnosing ADHD and Personality Disorders as Per DSM-5 Using Novel APK, PDPK, and DDPK Machine Learning Algorithms -- 1 Introduction -- 1.1 Developmental Psychology -- 1.2 Developmental Disorder -- 1.3 Psychopathology -- 1.4 Diagnosing Developmental Disorders as Per DSM-5 -- 1.5 Significance of Accurate Diagnosis of Developmental Disorders -- 1.6 Objectives of the Research Work -- 2 ML Approach to Psychopathology -- 3 Review of Literature -- 4 Methodology -- 4.1 APK Unsupervised ML Algorithm -- 4.2 PDPK Unsupervised ML Algorithm -- 4.3 DDPK Unsupervised ML Algorithm -- 5 Results -- 5.1 APK ML Algorithm Diagnosing the Prevalence or the Onset of ADHD -- 5.2 PDPK Algorithm Diagnosing the Prevalence of Personality Disorders -- 5.3 DDPK Algorithm for the Differential Diagnosis of Personality Disorder -- 6 Discussion -- 7 Conclusions -- 8 Limitations of the Research -- 9 Future Enhancements -- References -- Inception Time Model for Structural Damage Detection Using Vibration Measurements -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Inception Time Model -- 3 Data Set Description -- 3.1 Shear Frame Structure -- 3.2 ASCE Benchmark Structure -- 3.3 Generation of Data Set -- 4 Results and Analysis -- 4.1 Performance Measure -- 4.2 Analysis of Results for Shear Frame Structure -- 4.3 Analysis of Results for ASCE Benchmark Structure -- 5 Conclusion -- References -- Exploring Challenges and Innovations in E-Commerce Recommendation Systems: A Comprehensive Review -- 1 Introduction -- 2 Background Knowledge -- 2.1 Collaborative Filtering (CF) -- 2.2 Content-Based Filtering (CBF) -- 3 Studies on Recommendation Systems -- 3.1 Importance of Personalised Recommendation -- 3.2 Combination of Collaborative Filtering and Other Approaches -- 3.3 Handling Problems in Recommendation -- 3.4 Different Approaches for Recommendations. 3.5 Coupon Usage in Recommendation -- 4 Conclusion -- References -- Enhanced Ensemble Classifiers for Heart Disease Prediction -- 1 Introduction -- 2 State of Art Related to Heart Disease Prediction -- 3 Proposed Methodology -- 3.1 Input Dataset and Feature Selection Process -- 3.2 Novel Enhanced Ensemble Classifiers (EEC) -- 3.3 Ensemble Classifier Training -- 3.4 Ensemble Classifier Training -- 3.5 Building Enhanced Ensemble Classifier (EEC) Models -- 4 Experimental Result of EEC Model -- 4.1 Discussions -- 5 Conclusion -- References -- Study of RNN with Its CNN-Based Hybridization for Temporal Remote Sensing Data Processing to Map Rabi Crops -- 1 Introduction -- 2 Recurrent Neural Networks -- 3 Convolutional Neural Networks -- 4 Hybridization of RNN with CNN Models -- 5 Area of Study and Dataset Used -- 5.1 Study Area -- 5.2 Utilized Dataset -- 6 Methodology -- 7 Results and Discussion -- 8 Conclusion -- References -- Safeguarding Healthcare: Leveraging Machine Learning for Enhanced Cybersecurity in the Internet of Medical Things -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Preprocessing and Encoding -- 3.2 Dataset Partitioning and Scaling -- 3.3 Model Design and Training -- 4 Experimental Results -- 4.1 Training and Validation -- 4.2 Performance Analysis -- 4.3 Evaluation -- 5 Discussion and Future Work -- 6 Conclusion -- References -- BIMA: Blockchain-Enabled Fog Computing for Intensive Medical Assistance to Elder Patients -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Priority Setting for Incoming Tasks -- 3.2 Task Allocation Using Adaptive Learning -- 3.3 Miner Selection Using Fuzzy System -- 3.4 Proof of Analysis (PoA): An Energy Efficient Consensus Mechanism for Validation of Block -- 4 Performance Evaluation -- 5 Conclusion -- References. On Some Graphs Whose Domination Number Is the Perfect Italian Domination Number -- 1 Introduction -- 2 Main Results -- 2.1 Characterising Graphs with gamma Subscript upper I Superscript p Baseline left parenthesis upper G right parenthesis equals gamma left parenthesis upper G right parenthesisγIp(G)=γ(G) -- 2.2 Bounds on StartAbsoluteValue upper V left parenthesis upper G right parenthesis EndAbsoluteValue|V(G)|, gamma left parenthesis upper G right parenthesis equals gamma Subscript upper I Superscript p Baseline left parenthesis upper G right parenthesisγ(G)=γIp(G) -- 2.3 gamma Subscript upper I Superscript p Baseline left parenthesis upper G right parenthesisγIp(G) in terms of gamma left parenthesis upper G right parenthesisγ(G) -- 3 Conclusion -- References -- Role of Convolutional Neural Networks in Hyperspectral Imaging Applications: A Review -- 1 Introduction -- 2 Fundamentals of HSI -- 2.1 Structure of Hyperspectral Image -- 2.2 Components of HSI System -- 3 Introduction to ML -- 4 Introduction to Deep Learning and Convolutional Neural Network -- 4.1 DL -- 4.2 CNN -- 4.3 Remote Sensing -- 4.4 Food Quality Assessment -- 4.5 Agriculture and Horticulture -- 4.6 Medical Imaging -- 5 Conclusion -- References -- VARUNA: The Remote-Controlled Fire Fighter Robot -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Block Diagram -- 3.2 Components -- 3.3 Working -- 3.4 CAD Models -- 4 Results and Discussion -- 5 Conclusion -- References -- Investigations on Deep Learning Pre-trained Model Inception-V3 Using Transfer Learning for Remote Sensing Image Classification on Benchmark Datasets -- 1 Introduction -- 2 Pre-trained Models Employed with Transfer Learning -- 3 Overview of Inception-V3 -- 4 Experimental Setup for Remote Sensing Image Classification Using Pre-trained Model Inception-V3 -- 4.1 Datasets Description. 4.2 Evaluation Metrics Used for Model Assessment in Image Classification -- 5 Investigations on Test Accuracy and Test Loss on Benchmark Datasets Using Inception-V3 -- 6 Results Depicted Through Experimentation -- 7 Conclusion and Future Directions -- References -- Review of the Deep Learning Models for Anomaly Detection-Based Video Scrutiny System -- 1 Introduction -- 2 Related Work -- 3 Overview of Surveillance -- 3.1 Anomaly Detection -- 4 Proposed Methodology -- 4.1 Deep Learning Models -- 4.2 Restricted Boltzmann Machine -- 4.3 Auto-encoders -- 4.4 Convolution Neural Network Model -- 5 Limitations -- 6 Conclusion -- References -- Survey on Non-fungible Tokens in Blockchain with Attacks and Challenges -- 1 Introduction -- 2 Literature Review -- 3 NFT Methodology -- 4 Attacks on NFT -- 5 NFT Challenges -- 6 Conclusion and Future Work -- References -- Spatial Co-location Pattern Mining-A Survey of Recent Trends -- 1 Introduction -- 2 Basic Concept -- 3 Multilevel-Global and Local Patterns -- 4 Approaches to Co-location Pattern Mining -- 5 Recent Trends in Spatial Co-location Pattern Mining -- 6 Conclusion and Open Challenges -- References -- A Survey on Anomaly Detection in Network with ML Techniques -- 1 Introduction -- 1.1 Classification of Anomalies -- 2 Machine Learning for Anomaly Detection -- 2.1 Evaluation Index -- 3 Related Work -- 3.1 Anomaly Detection in Various Networks Using Supervised Machine Learning -- 3.2 Anomaly Detection in Various Networks Using Unsupervised Machine Learning -- 3.3 Anomaly Detection in Various Networks Using Semi-supervised Machine Learning -- 3.4 Anomaly Detection in Various Networks Using Reinforcement Learning -- 4 Challenges in Various Networks with ML Technique via DoS and DDoS -- 5 Conclusion and Future Work -- References. Chaos Control in a Time Delayed Phytoplankton-Zooplankton System with Harvesting of Zooplankton. |
| Record Nr. | UNINA-9910847072003321 |
Kumar Sandeep
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| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Third Congress on Intelligent Systems : Proceedings of CIS 2022, Volume 2 / / edited by Sandeep Kumar, Harish Sharma, K. Balachandran, Joong Hoon Kim, Jagdish Chand Bansal
| Third Congress on Intelligent Systems : Proceedings of CIS 2022, Volume 2 / / edited by Sandeep Kumar, Harish Sharma, K. Balachandran, Joong Hoon Kim, Jagdish Chand Bansal |
| Autore | Kumar Sandeep |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (850 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
SharmaHarish
BalachandranK KimJoong Hoon BansalJagdish Chand |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Robotics Computational Intelligence Artificial Intelligence |
| Soggetto non controllato | Science |
| ISBN |
9789811993794
9789811993787 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Patch Extraction and Classifier for Abnormality Classification in Mammography Imaging -- Improving the Performance of Fuzzy Rule Based Classification Systems using Particle Swarm Optimization -- Tuning Extreme Learning Machine by Hybrid Planet Optimization Algorithm: An Application for Diabetes Classification -- Towards Computation Offloading Approaches in IoT-Fog-Cloud Environment: Survey on Concepts, Architectures, Tools and Methodologies -- Prediction of COVID-19 Pandemic spread using Graph Neural Networks -- Event Based Time-To-Contact Estimation with Depth Image Fusion -- mCD and Clipped RBM based DBN for Optimal Classification of Breast Cancer -- Digital Disruption in Major Ports with Special Reference to Chennai Port, Kamarajar Port and Tuticorin Port -- SmartTour: A Blockchain-based Smart Tourism Platform using Improvised SHA -- Detection of Starch in Turmeric using Machine Learning Methods -- A study of Crypto-Ransomware using Detection Techniques for Defence Research -- Internet of Things (IOT) Based Smart Agriculture System Implementation and Current Challenges -- Physical Unclonable Function and Smart Contract based Authentication Protocol for Medical Sensor Network -- Developing Prediction Model for Hospital Appointment No-Shows using Logistic Regression. |
| Record Nr. | UNINA-9910734096103321 |
|
Kumar Sandeep
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||