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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 | ||
| ||
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 | ||
| ||
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
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||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 | ||
| ||
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 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||