Details

Subject(s)

• Artificial intelligence [Browse]
• Artificial intelligence—Congresses [Browse]
• Deep learning (Machine learning) [Browse]
• Computational intelligence [Browse]
• Computer vision [Browse]
• Image processing—Digital techniques [Browse]

Editor

• Shakya, Subarna [Browse]
• Du, K.-L. [Browse]
• Ntalianis, Klimis [Browse]

Series

• Advances in intelligent systems and computing ; Volume 1432. [More in this series]
• Advances in Intelligent Systems and Computing Series ; Volume 1432

Bibliographic references

Includes bibliographical references and index.

Source of description

Description based on print version record.

Contents

• Intro
• Preface
• Contents
• About the Editors
• Ranking Roughly Tourist Destinations Using BERT-Based Semantic Search
• 1 Introduction
• 2 Semantic Search with SBERT
• 2.1 Semantic Search with SBERT
• 2.2 Extracting a Boundary by Applying Different Thresholds
• 3 System Architecture
• 3.1 Data
• 3.2 Text Cleaning and Pre-processing
• 3.3 Embeddings
• 3.4 Similarity Measure
• 3.5 Ranking Algorithm
• 4 Result of Ranking System
• 4.1 Result of Ranking System
• 4.2 Evaluation of Result
• 5 Discussion and Conclusion
• References
• A New Image Encryption Technique Built on a TPM-Based Secret Key Generation
• 1.1 Neural Network and Tree Parity Machine (TPM)
• 2 Methodology
• 2.1 Traditional Method of Generating Secret Key Using Tree Parity Machine
• 2.2 Proposed Rule with Algorithm
• 3 Results and Discussion
• 3.1 Performance Parameters
• 3.2 Security Parameters
• 4 Conclusion
• Application Prototypes for Human to Computer Interactions
• 2 Related Work
• 2.1 Methodology
• 2.2 Literature Review
• 3 Conclusion
• Feature Selection-Based Spam Detection System in SMS and Email Domain
• 2 Literature Review
• 2.1 Phase 1
• 2.2 Phase 2
• 2.3 Phase 3
• 3 Classification Methods Used for Spam Detection in SMS and Email Domains
• 3.1 Phase 1
• 3.2 Phase 2
• 3.3 Phase 3
• 4 Experiment and Result
• 4.1 Data-sets Used
• 5 Conclusions and Future Work
• Discerning the Application of Virtual Laboratory in Curriculum Transaction of Software Engineering Lab Course from the Lens of Critical Pedagogy
• 2 Motivation for This Work
• 3 Objectives and Scope of This Research
• 3.1 Specific Objectives of the Research
• 3.2 Scope of the Research
• 4 Organization of This Research Paper
• 5 Virtual or Online Learning.
• 6 Traditional Versus Virtual Laboratory
• 7 Critical Pedagogy Theory
• 8 Instructional Design Delivery (IDD)
• 9 Students' Learning Outcomes (LO)
• 10 Assessments (ASS)
• 11 Students' Empowerment (EM)
• 12 Critical Thinking (CT)
• 13 Social Presence (SP)
• 14 Alignment (AL)
• 15 Approaches to Virtual Laboratories and Software Engineering Virtual Laboratory
• 16 Synthesis of Related Work and Concluding Remarks
• 17 Educational Implications
• 18 Limitations
• 19 Conclusion and Way Forward
• 19.1 Design Software Engineering Virtual Lab
• 19.2 CP-VLLM: Development of a Virtual Learning Measurement Tool
• 19.3 Evaluation of Students' Learning Performance in a Virtual Laboratory Learning Environment
• 19.4 Directions for Future Research
• Chrome Extension for Text Sentiment Analysis
• 2 Related Works
• 3 Proposed Model
• 3.1 Sentiment Analysis
• 3.2 Chrome Extension
• 4 Experimental Analysis and Results
• 4.1 Dataset Description
• 4.2 Performance Evaluation
• 5 Conclusion
• Performance of RSA Algorithm Using Game Theory for Aadhaar Card
• 3 RSA Algorithm
• 4 Proposed GT-RSA Algorithm and Analysis
• 4.1 Game Theory
• 4.2 Games Are Classified in Several Ways
• 4.3 Pure Strategy Characteristics of a Two-Person, Zero-Sum Game
• 4.4 Pure Strategy Problems
• 4.5 GT-RSA
• 5 Experimental Results
• 5.1 Encryption Time
• 5.2 Decryption Time
• 5.3 Execution Time
• 5.4 Encryption Throughput
• 5.5 Decryption Throughput
• 5.6 Execution Throughput
• 5.7 Power Consumption
• 5.8 Avalanche Effect
• 6 Conclusion
• Drought Prediction Using Recurrent Neural Networks and Long Short-Term Memory Model
• 1.1 Literature Review
• 2.1 Read the Data
• 2.2 Data Cleaning.
• 2.3 Data Preparation and Visualization
• 2.4 Applying RNN and LSTM
• 3 Results
• 3.1 Experimental Methodology
• 3.2 Results
• Recogn-Eye: A Smart Medical Assistant for Elderly
• 2 Literature Survey
• 3 Problem Statement
• 4 Proposed Method
• 5 Project Demonstration
• 6 Results and Discussions
• 7 Conclusion
• Lossless Image Compression Using Machine Learning
• 3 Image Representation
• 4 Problem Statement
• 5 Clustering Techniques
• 6 Image Compression Techniques
• 6.1 Generative Adversarial Networks
• 6.2 Gaussian Mixture Models
• 7 Methodology
• 8 Lossless and Lossy
• 9 Implementation
• 10 Experimental Results
• 11 Conclusion
• An Energy-Efficient Approach to Transfer Data from WSN to Mobile Devices
• 3 Proposed Architecture
• 4 Wireless XML Stream
• 4.1 G-Node (G-N)
• 4.2 Lineage Code
• 5 Query Processing
• 5.1 Simple Query Processing
• 5.2 Twig Pattern Query Processing
• 6 Simulation Result
• 6.1 Query Processing Time with Lineage Encoding
• 6.2 Maximum Residual Energy
• 6.3 Maximum Number of Sensor Nodes with Optimum Energy
• 7 Conclusion and Future Work
• Worker Safety Helmet
• 3 Methodologies
• 4 Architecture Diagram
• 5 Prototype Implementation
• 6 Testing and Evaluation
• Using IT in Descriptive Statistics and Way ANOVA Analysis to Assessment Development in Some Anthropometric Indicators of Thai Ethnic Students Born Between 2003 and 2006 in Thuan Chau District, Son La Province, Vietnam
• 3.1 Standing Height of Thai Ethnic Students
• 3.2 The Weight of Thai Students by Age and Sex.
• 3.3 BMI of Thai Students by Age and Sex
• LSTM-Based Deep Learning Architecture for Recognition of Human Activities
• 3 Proposed System
• 4 LSTM Architecture
• 5 Methodology
• 6 Results
• A Deep Learning Framework for Classification of Hyperspectral Images
• 3 Proposed Methodology
• 4 Experimental Results
• Improved Security on Mobile Payments Using IMEI Verification
• 4 Implementation and Result Analysis
• 5 Conclusions
• Evaluating the Effectiveness of Classification Algorithms for EEG Sentiment Analysis
• 1.1 Background
• 1.2 Motivation
• 1.3 Objective
• 2 Methods
• 2.1 Dataset
• 2.2 Preprocessing
• 2.3 Feature Extraction
• 2.4 Machine Learning Algorithms
• 2.5 Deep Learning Algorithms
• 2.6 Data Preparation
• 2.7 Evaluation Metrics
• 3 Results and Discussions
• 4 Conclusion and Future Research Direction
• 5 Data and Code Availability
• Analytics and Data Computing for the Development of the Concept Digitalization in Business and Economic Structures
• 1 Introduction, Background, Motivation and Objective
• 2 Methods the Implementing Digital HR Capabilities
• 2.1 Implementation of Statistical Assessment of Functional Interactions of Users of Social and Economic Phenomena and Processes
• 2.2 Influence of Enterprise Corporate Culture Components on Individual Components of Enterprise Personnel Motivation
• 3 The Results of the Analysis the Components of Corporate Culture Motivation for Personnel
• 4 Discussions
• The Social Hashtag Recommendation for Image and Video Using Deep Learning Approach.
• 2.1 Tag Recommendation for Micro-video
• 2.2 Social Tag Recommendation for Images
• 2.3 Social Tag Recommendation for Micro-video
• 2.4 Social Tag Recommendation for Image
• 3 Filtering Methods for Hashtag Recommendation
• 3.1 Collaborative Filtering
• 3.2 Content-Based Filtering
• 3.3 Filtering Based on Hybrids Approach
• 3.4 Social Popularity Prediction
• 3.5 Technique for Tag Recommendation for Images/Videos
• 4 Evaluation Parameter
• 5 Conclusion and Future Scope
• Smart Door Locking System Using IoT-A Security for Railway Engine Pilots
• 3 Methodology
• 4 Results and Implementation
• AdaSmooth: An Adaptive Learning Rate Method Based on Effective Ratio
• 1.1 Gradient Descent
• 2.1 Momentum
• 2.2 AdaGrad
• 2.3 AdaDelta
• 3 AdaSmooth Method
• 3.1 Effective Ratio (ER)
• 3.2 AdaSmooth
• 3.3 AdaSmoothDelta
• 4 Experiments
• 4.1 Experiment: Multi-layer Perceptron
• 4.2 Experiment: Convolutional Neural Networks
• 4.3 Experiment: Logistic Regression
• Designing and Implementing a Distributed Database for Microservices Cloud-Based Online Travel Portal
• 3 Problem Definition
• 3.1 Why Distributed Database?
• 3.2 DDB Systems Types
• 3.3 Advantages of Distributed Database System
• 3.4 Limitations of Relational Database
• 3.5 Major Characteristics of RDBMS
• 3.6 Why Microservice Architecture?
• 4 Methodology
• 4.1 System Design
• 4.2 Data Collection Methods
• 4.3 Database Design
• 4.4 Data Analysis Tools
• 5 Results and Discussions
• A Comparative Study of a New Customized Bert for Sentiment Analysis
• 2 Proposed Sentiment Analysis Framework.
• 2.1 Proposed Model.

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ISBN

981-19-5443-7

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