| Pubbl/distr/stampa |
Singapore : , : Springer, , [2023]
|
| Descrizione fisica |
1 online resource (899 pages)
|
| Disciplina |
929.605
|
| Collana |
Algorithms for Intelligent Systems
|
| Soggetto topico |
Computational intelligence
|
| ISBN |
981-19-6004-6
|
| Formato |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione |
eng
|
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- 1 Modeling Müller-Lyer Illusion Using Information Geometry -- 1 Introduction -- 2 Method -- 3 Information Geometric Measure of Distance -- 4 Computational Method and Results -- 5 Discussion -- References -- 2 Building up a Categorical Sentiment Dictionary for Tourism Destination Policy Evaluation -- 1 Introduction -- 2 MCST Questionnaires for Selecting Evaluation Categories -- 2.1 Categories and Questions of MCST and Keywords Associated to the Categories -- 2.2 Incorporating the Questionnaire-Based Evaluation into Sentiment Analysis Based on Text Mining -- 3 Additional Information Required from Authors -- 3.1 Model Architecture -- 3.2 Data -- 3.3 Text Cleaning and Preprocessing -- 3.4 Extracting Category-Specific Tokens Using CTF-IDF -- 3.5 Logistic Regression for Extracting Sentiment Words -- 3.6 Human Evaluation on Sentiment Words in a Category -- 3.7 Matching -- 4 Results -- 5 Conclusion -- References -- 3 Statistical Analysis of Stress Prediction from Speech Signatures -- 1 Introduction -- 2 Methodology -- 3 Database Collection -- 4 Results and Analysis -- 5 Discussion -- 6 Conclusion -- References -- 4 DermoCare.AI: A Skin Lesion Detection System Using Deep Learning Concepts -- 1 Introduction -- 2 Theory -- 2.1 Survey of Existing Systems -- 2.2 Limitations Found in Existing Systems -- 3 Proposed Work -- 3.1 Data Set -- 3.2 Pre-processing -- 3.3 CNN Architecture -- 4 Results and Discussion -- 4.1 Evaluation Measures -- 4.2 Multi-class Classification -- 4.3 Benign/Malignant Classification -- 4.4 Integrating Models into a Web Application -- 5 Conclusion and Future Scope -- References -- 5 Analysis of Phishing Base Problems Using Random Forest Features Selection Techniques and Machine Learning Classifiers -- 1 Introduction -- 2 Research Background -- 3 Methodology -- 3.1 Data Description.
3.2 Features Selection Method -- 3.3 Algorithms Description -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- 6 Cost Prediction for Online Home-Based Application Services by Using Linear Regression Techniques -- 1 Introduction -- 1.1 Motivation -- 2 Problem Statement -- 3 Literature Survey -- 3.1 Domestic Android Application for Home Services [9] -- 3.2 An Online System for Household Services [10] -- 3.3 E-commerce and Its Impact on Global Trade and Market [11] -- 3.4 Examining the Impact of Security, Privacy, and Trust, on the TAM and TTF Models for E-commerce Consumers [12] -- 3.5 A Research Study on Customer Expectation and Satisfaction Level of Urban Clap in Beauty Services with Special Reference to Pune [13] -- 3.6 Timesaverz-First of Its Kind On-Demand Home Service Provider, India [14] -- 4 Proposed System and Architecture Diagram -- 4.1 Registration Module -- 4.2 Login Module -- 4.3 Feedback Module -- 4.4 Admin Module -- 5 Project Scope -- 6 Prototype Model -- 6.1 Feature Value (Target Value) and Linear Regression -- 6.2 Cost Prediction -- 6.3 Three-Step Verification -- 6.4 Feedback -- 7 Users' Classes and Features -- 8 Applications -- 8.1 Home and Cleaning Service Industry -- 8.2 Health Care -- 8.3 Repair and Maintenance Service Industry -- 8.4 Home Renovation/Shifting -- 8.5 Home Construction and Design -- 8.6 Businesses -- 9 Future Scope -- 10 Conclusion -- References -- 7 Convolutional Neural Network Based Intrusion Detection System and Predicting the DDoS Attack -- 1 Introduction -- 2 Related Works -- 3 System Model -- 3.1 Image Conversion Algorithm from KDD Dataset to Gray Scale -- 3.2 Feature Selection Algorithm -- 3.3 CNN Algorithm -- 4 Performance Evaluation -- 4.1 Number of Convolution Layers -- 4.2 Kernel Size -- 5 Conclusion -- References -- 8 BERT Transformer-Based Fake News Detection in Twitter Social Media.
1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Dataset -- 4 Results and Discussion -- 5 Conclusion -- References -- 9 The Facial Expression Recognition Using Deep Neural Network -- 1 Introduction -- 2 Related Work -- 2.1 Literature Review -- 2.2 Dataset -- 3 Proposed Model -- 3.1 Model Architecture -- 4 Experiment -- 4.1 Experimental Design -- 4.2 Experimental Results and Evaluation -- 5 Conclusion -- References -- 10 New IoT-Based Portable Microscopic Somatic Cell Count Analysis -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Performance Analysıs -- 5 Conclusion -- References -- 11 A Survey on Hybrid PSO and SVM Algorithm for Information Retrieval -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Analysis -- 4 Results and Discussion -- 4.1 Ranking Models and Experiments with These Models -- 4.2 The Vector Space Mode -- 4.3 Positioning Based on Document Structure -- 4.4 Adjustments and Enhancements to the Basic Indexing and Search Processes -- 5 Conclusion -- References -- 12 Metric Effects Based on Fluctuations in Values of k in Nearest Neighbor Regressor -- 1 Introduction -- 2 Methodology -- 2.1 Euclidean Distance -- 2.2 Manhattan Distance -- 2.3 Hamming Distance -- 2.4 Regressor -- 2.5 Dataset -- 3 Results -- 3.1 Root Mean Squared Error -- 3.2 Goodness of Fit -- 4 Conclusion -- References -- 13 An Ensemble Approach to Recognize Activities in Smart Environment Using Motion Sensors and Air Quality Sensors -- 1 Introduction -- 2 Literature Review -- 3 Proposed Work -- 4 Experimental Analysis -- 4.1 Phase 1-Activity Recognition Using Motion Sensors Data -- 4.2 Phase 2-Activity Recognition Using Air Quality Sensors -- 5 Results -- 6 Conclusion -- References -- 14 Generalization of Fingerprint Spoof Detector -- 1 Introduction -- 2 Literature Survey -- 3 Working Principle -- 3.1 Dataset.
3.2 Training and Validation of Our Proposed CNN Model -- 4 Conclusion -- References -- 15 Applied Deep Learning for Safety in Construction Industry -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Description -- 3.2 Convolutional Neural Network Model -- 3.3 VGG16 Model -- 3.4 System Architecture -- 4 Discussion -- 4.1 Technologies Required -- 4.2 Convolutional Neural Network -- 4.3 VGG16 Model -- 5 Results -- 5.1 Classification Performance -- 5.2 Pre-processed Image Dataset -- 5.3 Equipment Classification -- 5.4 Result Comparison -- 6 Conclusion -- References -- 16 Deep Learning-Based Quality Inspection System for Steel Sheet -- 1 Introduction -- 2 Literature Survey -- 3 Existing System -- 4 Proposed Work -- 5 Architecture Diagram -- 6 System Design -- 6.1 Analysis of Experimental Data -- 6.2 Building Model -- 6.3 System Training and Testing Procedures -- 6.4 User Interface -- 7 Results -- 8 Conclusion -- 9 Future Scope -- References -- 17 Forecasting Prediction of Covid-19 Outbreak Using Linear Regression -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Dataset Description -- 3.2 Data Pre-processing -- 3.3 Training and Testing -- 3.4 Classification -- 4 Result -- 5 Conclusion -- References -- 18 Proctoring Solution Using AI and Automation (Semi) -- 1 Introduction -- 2 Project Plan and Schedule -- 3 Literature Survey -- 4 System Requirements -- 4.1 Hardware Requirement -- 4.2 Software Requirements -- 5 Proposed System -- 6 System Design and Working -- 6.1 Proctor Module -- 6.2 Student Module -- 6.3 Examiner Module -- 7 Implementation -- 8 Results -- 9 Advantages -- 10 Disadvantages -- 11 Conclusion -- 12 Future Enhancements -- References -- 19 Apple Leaf Disease Prediction Using Deep Learning Technique -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 4 Proposed System -- 5 Results.
6 Conclusion -- References -- 20 Sentimental Analysis and Classification of Restaurant Reviews -- 1 Introduction -- 2 Literature Survey -- 3 Existing Methodology -- 4 Sentiment Analysis of Restaurant Reviews -- 5 Sentimental Analysis -- 6 Proposed Methodology -- 6.1 Data Collection -- 6.2 Data Preprocessing -- 6.3 Stop-Word Elimination -- 6.4 Stemming -- 6.5 Bag-of-Words Model -- 6.6 Data Classification -- 6.7 Splitting Dataset -- 7 Splitting -- 8 Naive Bayes -- 9 Logistic Regression -- 10 Result -- 11 Conclusion -- 12 Future Work -- References -- 21 A Controllable Differential Mode Band Pass Filter with Wide Stopband Characteristics -- 1 Introduction -- 2 Filter Design -- 3 Current Distributions -- 4 Conclusion -- References -- 22 Design and Analysis of Conformal Antenna for Automotive Applications -- 1 Introduction -- 2 Antenna Design Process -- 2.1 Bending Analysis -- 3 Results and Analysis -- 4 Conclusions -- References -- 23 An Improved Patch-Group-Based Sparse Representation Method for Image Compressive Sensing -- 1 Introduction -- 1.1 Research Motivation and Contribution -- 2 Related Work and Challenges -- 3 Proposed Work -- 3.1 Phase-1: Patch-Based Adaptive Sparsifying Learning (PASL) -- 3.2 Phase-2: Constrained Group Sparse Representation -- 4 Result and Discussion -- 5 Conclusion -- References -- 24 Comparative Analysis of Stock Prices by Regression Analysis and FB Prophet Models -- 1 Introduction -- 2 Dataset Used for Research Evaluation -- 3 Comparative Analysis of Linear Regression and FB Prophet Models -- 3.1 Linear Regression Model -- 3.2 FB Prophet Model -- 4 Metric Used for Evaluation of Comparative Analysis of Models -- 5 Result and Discussion -- 5.1 Comparative Study -- 6 Conclusion and Future Scope -- References -- 25 g POD-Dual Purpose Device (Dustbin and Cleaning) -- 1 Introduction -- 2 Brief Overview of Dual Purpose Device.
2.1 Robot Vacuum Cleaner Base.
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| Record Nr. | UNINA-9910633930203321 |
Info
Data intelligence and cognitive informatics : proceedings of ICDICI 2022 / / edited by I. Jeena Jacob, Selvanayaki Kolandapalayam Shanmugam, Ivan Izonin