Recent Advancements in Artificial Intelligence

Name: Recent Advancements in Artificial Intelligence | Proceedings of ICRAAI 2023
Brand: Springer
Price: 319.93 EUR
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Proceedings of ICRAAI 2023

Richi Nayak Namita Mittal Manoj Kumar Zdzislaw Polkowski Ajay Khunteta(Herausgeber*in)

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Erschienen am 1. Mai 2024

XX, 406 Seiten

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Dr. Richi Nayak is a professor of computer science at the Queensland University of Technology (QUT), Brisbane Australia. Her current research interests include machine learning, text mining, personalization, automation, and social network analysis. She was awarded the 2016 WiT (Women in Technology) Infotech Outstanding Achievement Award for exemplary service to the field of data analytics. With a proven track record, she has successfully overseen and delivered over 30 industry-related projects, attracting a total income of over $15 million. She has an extensive portfolio of more than 250 refereed publications, attracting over 4,200 citations, with an h-index of 33 and an i10-index of 115 as of June 2023. She received the Masters in Engineering degree from the Indian Institute of Technology, Roorkee, India, and the PhD degree in computer science from the Queensland University of Technology.

Dr. Namita Mittal is working as Associate Professor of in Department of ComputerScience and Engineering at MNIT Jaipur and currently also holds the position of Head of the Department and coordinator, ISRO RACS at MNIT Jaipur. She is a recipient of Career Award for Young Teachers (CAYT) by AICTE. Her Current research areas are Data Science, Information Retrieval, Data Mining and NLP. She has published several research papers in reputed international conferences and journals, and two books in Springer Publication. She is also a member of review committees for Refereed journals/ conferences. She has been granted one patent of "The Smart Gait Analyzer". She is Senior Member of IEEE, Member of ACM, CCICI, and SCRS. She has conducted various FDPs/Conferences/Workshops like Ph.D. Colloquium FIRE 2017, GIAN Course on Advances on Data and Web Analytics 2017 and AI and Information Retrieval 2022., International Workshop on Text analytics and Retrieval (WI 2018), and WIRe (FIRE Track 2020). She is guiding 7 PhD students currently and 8 PhD have been awarded under her guidance. One PhD scholar is receiving prestigious PMRF scholarship.

Dr. Manoj Kumar completed his Ph.D. from The Northcap University and M.Sc. (Information Security and Digital Forensics) from Technological University Dublin, Ireland in 2013. He received fully-funded scholarship for his M.Tech and M.Sc. program from Irish Government. Dr. Kumar have more than 13 years of research, teaching, and corporate experience. He is currently working on the post of Associate Professor-Cyber Security in the University of Wollongong in Dubai, UAE and Research Head for Network and Cyber Security Cluster. His specializations are Digital Forensics, Machine Learning, Information Security, Image Processing, IOT and Computer Networking. He has published over 140 articles in International refereed journals and conferences. Dr. Kumar is member of numerous renowned professional bodies including IEEE, ACM, IAENG, ISTS and UACEE and many more.He delivered several guest lectures, seminars and chaired the session at various reputed international conferences. He published three textbooks and eight edited books for the most famed publishers like Springer, CRC Press, IOP, Bentham Science, Taylor & Francis, and Elsevier, etc. He is an associate editor, Guest editor, and editorial board member of various journals of repute. Dr. Kumar received the Best Researcher Award in 2020, an outstanding Scientist Award in 2021, and a Young Researcher Award in 2021 from recognized international professional bodies. He published over 10 patents and delivered three international research funded projects.

Dr. Zdzislaw Polkowski is professor of UJW at Faculty of Social and Technical Sciences and Rector's Representative for International Cooperation and Erasmus+ Program at the Jan Wyzykowski University Polkowice and professor of WSG University Bydgoszcz, Poland. Also Since 2019 he is also Adjunct Professor in Department of Business Intelligence in Management, Wroclaw University of Economics and Business and The Karkonosze University of Applied Sciences in Jelenia Góra Poland. Moreover, he is visiting professor in University of Pitesti, Romania, Swami Sahajanand School of Management, Bhavnagar and adjunct professor in Marwadi University, Rajkot, India. He is the former dean of the Technical Sciences Faculty during the period 2009 -2012 at UZZM in Lubin. He holds a PhD degree in Computer Science and Management from Wroclaw University of Technology, Post Graduate degree in Microcomputer Systems in Management from University of Economics in Wroclaw and Post Graduate degree IT in Education from Economics University in Katowice. He obtained his Engineering degree in Computer Systems in Industry from Technical University of Zielona Gora. He has published more than 159 papers in journals, 35 conference proceedings, including more than 65 papers in journals indexed in the Web of Science, Scopus, IEEE. Dr. Polkowski is co-editor of 29 books which have been published in Springer, IGI and CRC Press Taylor & Francis. He served as a member of Technical Program Committee and the member of the editorial board in many International conferences, journals in Poland, India, China, Iran, Iraq, Syria, United Kingdom, Romania, Turkey, Indonesia, Philippines, Vietnam, Malaysia and Bulgaria. Till date he has delivered over 85 invited talks at different international conferences across various countries. He is also the member of the Board of Studies and expert member of the doctoral research committee in many universities in India. His area of interests includes IT in Business, IoT in Business and Education Technology. He has successfully completed a research projects on "Developing the innovative methodology of teaching Business Informatics" and "Web Technology & Green Internet of Things" funded by the European Commission. He also owns an IT SME consultancy company in Polkowice and Lubin, Poland.

Dr.Ajay Khunteta isan accomplished professional with a rich background in academia and research, spanning over 22 years. Currently serving as a Professor and Dean in the Faculty of Computer Science & Engineering at Poornima University in Jaipur, Rajasthan, India, he has made significant contributions to the field. His expertise lies in the areas of AI, Cloud Computing, Data Security, and Distributed Systems. With a passion for guiding and mentoring students, Dr. Ajay Khunteta has successfully supervised 46 M.Tech dissertations and 6 PhD theses on various topics related to AI and Cloud technology. He has authored and co-authored over 106 research papers in esteemed international journals and conferences. He has completed many Research and MODROB project grants from prestigious organizations such as AICTE and DST. He is also the member of the editorial board of several journals and served as a reviewer in a wide range of international journals. In addition to his academic achievements, he is actively involved in organizing conferences sponsored by IEEE and Elsevier at Poornima University.

Inhalt

Intro
Preface
About This Book
Contents
Editors and Contributors
1 A Survey on Computer Vision Methods and Approaches for the Detection of Humans in Video Surveillance Systems
1 Introduction
2 Database
3 Pre-Processing Techniques
4 Feature Extraction
5 Classification
6 Real Time Detection Systems
7 Human Detection Challenges
7.1 Image Plane Variations
7.2 Variation in Pose
7.3 Texture and Lighting Variation
7.4 Variation in Background
7.5 Variation in Shape
8 Conclusion
References
2 UNFAZEDROADS: Pothole Management System
1 Introduction
2 Literature Survey
3 Methodology
3.1 Research Design
3.2 Data Collection
3.3 Data Analysis
4 Proposed System
5 Table of Analysis
6 Results and Discussions
7 Scope of Research
8 Future Scope
9 Conclusion
References
3 DeepMint: Non-fungible Token Generation Using Deep Learning
1 Introduction
2 Literature Review
2.1 Review of Existing Systems
2.2 Limitations of Existing Systems
3 Analysis
4 Implementation
4.1 Design Details
4.2 Architecture and Methodology
5 Results
5.1 Performance Evaluation Parameters
5.2 Implementation Results
6 Conclusion
References
4 Empowering Gestures: Composing Succinct Meaning Using Vision and Swin Transformers for Indian Sign Language
1 Introduction
2 Literature Survey
3 Overview of Techniques
3.1 Convolutional Neural Networks
3.2 Vision Transformers
3.3 Swin Transformer
3.4 ReLU Activation Function
3.5 SoftMax Activation Function
3.6 GELU Activation Function
4 Experimentation and Implementation
4.1 Data
4.2 Design Methodology
5 Results and Evaluation
6 Conclusion
References
5 An Accuracy of Identifying Recyclable Objects and the Number of Objects Identified from Municipal Waste Without Occlusion Using Computer Vision Techniques
1 Introduction
2 Related Work
3 Proposed Work
4 Implementation
5 Result and Discussion
6 Conclusion
References
6 A Hybrid Approach for Summarizing Text and Image Data Using ResNet and BART
1 Introduction
2 Literature Survey
3 Methodology
4 Results and Dicussion
5 Conclusion
References
7 Epileptic Seizure Recognition System Using Neural Networks and Support Vector Machine Models
1 Introduction
2 Dataset
2.1 UCI Dataset
2.2 CHB-MIT Dataset
3 Survey of Existing Systems
4 Proposed Methodology
4.1 Support Vector Machine Model
4.2 Neural Networks Model
5 Results and Discussions
5.1 UCI
5.2 CHB-MIT
6 Conclusion
References
8 Intelligent Tutoring Systems for Multidisciplinary Education
1 Introduction
1.1 Digital Pedagogy
1.2 Intelligent Tutoring System
1.3 Methodology
2 Pedagogy for Multidisciplinary Digital Education
3 Comparison of Learning Algorithms
3.1 Computer Programming Learning Algorithm
3.2 Recommender Algorithm for Philosophy Education
4 Analysis and Discussion
References
9 A Comprehensive Study of SOMs, iSOMs, and Hybrid SOMs for Complex Data
1 Introduction
2 Literature Review
2.1 Self-Organizing Maps (SOM)
3 Comparison of SOM, iSOM and Hybrid SOM
4 Conclusion and Future Work
References
10 Enhancing Energy Efficiency in Smart Cities Through Robust Deep Learning Frameworks
1 Introduction
1.1 Significance of Deep Learning in Smart City Energy Management
1.2 Challenges in Smart City Energy Management
1.3 Objectives and Structure
2 Literature Review
2.1 Deep Learning for Smart City Energy Management
2.2 Data-Driven Approaches and Integrative Reviews
2.3 Machine Learning-Assisted Approaches
2.4 Wearable Sensors and Real-Time Energy Management
2.5 Deep Learning in Smart Buildings
2.6 Sustainable Transportation in Smart Cities
2.7 Real-Time Energy Management in Smart Homes
2.8 Smart Grid and Machine Learning
2.9 Urban Energy Management in Smart Cities
3 Smart City Infrastructure and Energy Management
3.1 Smart City Ecosystem Overview
3.2 Urban Energy Consumption Dynamics
3.3 Deep Learning for Smart City Energy Management
3.4 Challenges in Smart City Energy Management
3.5 Wearable Sensors and Data Collection
3.6 Data Fusion and Feature Extraction
3.7 Real-Time Energy Management
3.8 Case Studies and Real-World Experiments
3.9 Performance Evaluation Metrics
4 Deep Learning Frameworks for Smart City Energy Efficiency
4.1 Introduction to Deep Learning Frameworks
4.2 Applications of Deep Learning in Smart City Energy Management
4.3 Strengths and Limitations of Deep Learning Frameworks
4.4 Challenges and Strategies in Real-World Deployment
4.5 Performance Evaluation Metrics for Energy Efficiency
4.6 Research Directions and Future Prospects
5 Robustness and Resilience of Deep Learning Models
5.1 Introduction to Robustness and Resilience
5.2 Challenges in Model Robustness
5.3 Adaptability to Disruptions
5.4 Strategies for Model Robustness
5.5 Resilience Testing and Benchmarking
5.6 Ethical Considerations
6 Result and Analysis
6.1 Overview of Deep Learning Model Performance
6.2 Methodologies and Benchmarking Criteria
6.3 Comparison Table: Key Metrics Across Research Papers
6.4 Interpretation of Key Findings
7 Discussion
7.1 Model Interpretability
7.2 Ethical Considerations
7.3 Data Privacy
8 Future Research Direction
8.1 Enhancing Model Interpretability
8.2 Addressing Ethical Considerations
8.3 Advancements in Data Privacy Techniques
8.4 Improving Model Robustness and Resilience
8.5 Interdisciplinary Collaboration
8.6 Validation and Benchmarking Frameworks
8.7 Long-Term Sustainability and Scalability
9 Conclusion
References
11 Transformative Potential of AI and Remote Sensing in Sustainable Groundwater Management
1 Introduction
2 Groundwater Research Landscape
2.1 Evolution of Groundwater Research
2.2 Challenges in Groundwater Research
2.3 Traditional Research Methods
2.4 Emerging Technologies
3 The Role of Digital Technologies in Groundwater Research
3.1 The Role of AI in Groundwater Research
3.2 Remote Sensing Techniques
4 AI with Remote Sensing (AI-RS) Technique
5 Digital Twin of Groundwater Using AI-Remote Sensing Technique
5.1 Reduced Environmental Impact
5.2 Efficient Resource Management
5.3 Cost Savings
5.4 Long-Term Sustainability
5.5 Community and Stakeholder Engagement
6 Case Studies
7 Challenges and Future Directions
7.1 Data Quality and Availability
7.2 Data Privacy and Ethical Concerns
7.3 Interdisciplinary and Global Collaboration
7.4 Algorithm Validation and Interpretability
7.5 Scaling up Sustainable Technologies
7.6 Climate Change Adaptation
8 Conclusion
References
12 Impact on Ocean Acidification Along the Hawaii Coastline Using Learning Algorithm
1 Introduction
2 Proposed Algorithm
2.1 Tuning Process
2.2 Correlation Map of the Proposed Work
3 Results and Discussions
4 Conclusion
References
13 Smart Crop Security System Using IoT
1 Introduction
2 Literature Review
3 Methodology
3.1 Analysis and Discussion
4 Conclusion
4.1 Future Scope
References
14 Energy Efficient Fault Tolerance System for a Reliable IoT Environment
1 Introduction
2 Related Work
3 Software Defined FTM for IOT
4 System Design
5 Results and Discussion
6 Conclusions
References
15 A Novel Authentication Approach Based on Level 2 Minutiae-based Feature Extraction Using Gabor Filter
1 Introduction
1.1 Features in Fingerprint
1.2 Fingerprint Databases and Its Classification
2 Related Work
3 Proposed Methodology for Ridge Detection and Level 2 Feature Extraction
4 Experimental Results
5 Conclusion and Future Work
References
16 A Blockchain Based Electronic Health Record Management System with PoA Consensus
1 Introduction
2 Literature Review
3 Proposed Blockchain Architecture
4 Results and Discussion
4.1 Decentralized Data Management
4.2 Proof of Authority Consensus
4.3 Enhanced Scalability
4.4 Data Security
4.5 Lightweight Cryptography
5 Conclusion
References
17 Voice-Based Classification of Parkinson's Disease Using Machine Learning: An Extensive Study
1 Introduction
2 Relevant Studies
3 Materials and Methods
3.1 Dataset
3.2 Methods
4 Experimental Results
4.1 Accuracy and Classification Reports
4.2 Confusion Matrix
4.3 Comparison with Relevant Studies
5 Conclusion
References
18 A Brief Perusal of Image-based Diagnosis for COVID-19 Using Image Processing Perspective
1 First Section
2 Corona Virus Disease (COVID-19)
2.1 Symptoms of Coronavirus
3 Image-based Classification Method
3.1 Extraction of Features
3.2 Parallel Implementation
3.3 Manta Ray Foraging Optimization (MRFO)
3.4 Improved MRFO with Feature Selection Based on D.E
4 Appraisal of the Suggested Model
5 Motivation
6 Literature Review
6.1 Research Trend
6.2 Research Gap
7 Comparative Analysis
8 Conclusion
References
19 Classification of Mobile Images Using Inception V3 Algorithm
1 Introduction
2 Data Collection
3 Pre Processing
4 Methodology
5 Results
6 Conclusion
References
20 PIXEMO: Captioning Images Along with Emojis for Social Media Applications
1 Introduction
2 Literature Review
3 Datasets
3.1 Flickr8K
3.2 Custom Dataset
4 Implementation
4.1 Image Captioning
4.2 Emoji Prediction
5 Evaluation Parameters
5.1 Image Description
5.2 Emoji Prediction
6 Results
7 Conclusion
References
21 A Review on Recent Advancement in Wearable Textile Antennas & Its Applications
1 Introduction
2 Requirements for Wearable Antenna Design
2.1 Conductive and Non-Conductive Material
2.2 Fabrication Techniques
2.3 Specific Absorption Rate
3 Wearable Antenna Specifications and Performance Analysis
3.1 Dual L Strip Fed Split Ring Shaped EBG Textile Antenna
3.2 A Low-Profile Alford Antenna for WBAN
4 Results and Discussion
4.1 Challenges and Design Considerations
4.2 Challenges and Design Considerations
5 Conclusion
References
22 Deploying Gaussian Processes to Predict Avocado Price Fluctuations
1 Introduction
2 Data
3 Methods
3.1 Definition of Gaussian Process
3.2 Model Implementation
4 Results
5 Discussion
6 Conclusion
7 Contributions
8 A. Avocado Data Summary Statistics & State-by-State Price Breakdown
9 B. Avocado Price Distribution Plots, By Year
References
23 Deepfake Image Detection for Low and High Quality Images for Biometric Face Recognition
1 Introduction
2 Related Work
3 Dataset Description
4 Proposed Deepfake Detection Approach
5 Results and Discussions
6 Conclusion
References
24 Unveiling the Pinnacle of Time Series Forecasting: Replicating and Comparing State-of-the-Art Models
1 Introduction
2 Literature Review
3 Models
3.1 TRMF
3.2 DeepAR
3.3 Informer
3.4 MTGNN
3.5 SCINet
4 Data and Metrices
5 Results
6 Conclusion
References
25 Identification of Banana Leaf Diseases: A Collaboration of Deep Learning Models
1 Introduction
2 Literature Review
3 Research Methodology
4 Experimental Analysis
5 Conclusion and Future Enhancement
References
26 Perspectives on Utilizing Green Practices and Digital Technologies for Vertical Farming in Oman
1 Introduction
2 Literature Review
2.1 Vertical Farming & Digital Technologies
2.2 Green Technologies and Sustainability in Vertical Farming
2.3 Oman's Economic Context and Food Security
2.4 Comprehensive Approach: Integrating Digital and Green Technologies
3 Research Methodology
4 Findings and Discussion
4.1 Onsite Observation
4.2 Qualitative Analysis Using NVivo
5 Conclusion
References
27 Usage of Fitness Applications by the Sports People: A Bibliometric Analysis
1 Introduction
2 Methodology
3 Results and Analysis
3.1 Most Prolific Sources
4 Discussion and Conclusion
References
28 Advancing Web-Based Visual Question Answering with Efficient Image-Text Alignment
1 Introduction
2 Similar Study
2.1 Image-Text Matching Loss
2.2 Detection-Free Visual Encoder
2.3 Intermodal Attention
2.4 Knowledge Distillation
3 Problem Statement
4 Multimodal Baseline Models
4.1 VLP Baseline
4.2 RoBERTa Baseline
5 Experimental Methodology
5.1 WebQA Dataset
5.2 Evaluation Metrics
5.3 VLP Baseline Setting
5.4 RoBERTa Baseline Setting
6 Result and Discussion
6.1 Baseline Results
6.2 Discussion
7 New Research Ideas
7.1 Image-Text Match Loss
7.2 Detection-Free Visual Encode
7.3 Cross Versus Unified Attention Modules
7.4 Multimodal Knowledge Distillation
References
29 U-Net Based Image Segmentation Drawbacks in Medical Images: A Review
1 Introduction
2 Related Work
3 U-Net
3.1 Architecture
3.2 U-Net++
3.3 3D U-Net
3.4 Attention U-Net
4 U-Net in Biomedical Image Segmentation
5 Drawbacks
6 Conclusion
References
30 Novel Approach in Healthcare System Using Cloud Computing and IOT: A Survey
1 Introduction
2 Methodology
2.1 Ease of Cloud Computing in HealthCare Using Fog and Raspberry Pi
2.2 IOT Based HealthCare System Using Cloud Computing (WBASN-Wireless Body Area Sensor Network)
2.3 Elderly HealthCare Services Using Digital Twin (DT)
3 Conclusion
References
31 A Thorough Investigation of Conventional and Advanced Feature Extraction Methods in Natural Language Processing for Sentiment Analysis Employing SVM Kernels
1 Introduction
2 Related Work
3 Methodology
3.1 Data Aggregation
3.2 Machine Learning Algorithms
3.3 Feature Extraction Techniques
3.4 Proposed Methodology
3.5 Experimental Evaluation
3.6 Result Discussion
3.7 Result Discussion
References
Conclusion
Author Index

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