Vol. 6 (2020): Distributed Learning and Broad Applications in Scientific Research

In this issue of Distributed Learning and Broad Applications in Scientific Research, we present a collection of innovative studies showcasing the latest advancements in distributed learning technologies and their applications across various scientific fields. Featured themes include cutting-edge machine learning algorithms, deep learning frameworks, and artificial intelligence techniques applied to areas such as computational biology, environmental modeling, and materials science.

This volume also offers insightful reviews on current trends and future directions in distributed learning, along with case studies demonstrating real-world impacts. Contributions from global experts and emerging scholars highlight the journal's commitment to fostering interdisciplinary collaboration and driving innovation in scientific research.

Explore these groundbreaking developments and stay at the forefront of distributed learning's potential to revolutionize science.

Published: 01-01-2020

Articles

Software Engineering Education and Training: Studying innovative approaches to software engineering education and training to prepare students for industry demands and challenges

Dr. Krzysztof Kowalski (Author)

28-36
- PDF
Software Configuration Management - Practices and Tools: Investigating software configuration management practices and tools for version control, change management, and release management

Dr. Beatriz Hernandez-Gomez (Author)

15-27
- PDF
Software Architecture Evaluation Methods and Tools: Analyzing methods and tools for evaluating software architectures to ensure adherence to quality attributes and design principles

Dr. Hans Müller (Author)

1-14
- PDF
Real-Time Integration of Data Between Different Systems in Healthcare: Implementing Advanced Interoperability Solutions for Seamless Information Flow

Navajeevan Pushadapu (Author)

37-91
- PDF
AI-Driven Customer Support in E-Commerce: Advanced Techniques for Chatbots, Virtual Assistants, and Sentiment Analysis

Swaroop Reddy Gayam (Translator)

92-123
- PDF
AI-Driven Energy Management in Manufacturing: Optimizing Energy Consumption and Reducing Operational Costs

Sudharshan Putha (Author)

313-353
- PDF
AI-Driven Fraud Detection in E-Commerce: Advanced Techniques for Anomaly Detection, Transaction Monitoring, and Risk Mitigation

Swaroop Reddy Gayam (Author)

124-151
- PDF
AI-Driven Metabolomics: Uncovering Metabolic Pathways and Biomarkers for Disease Diagnosis and Treatment

Sudharshan Putha (Author)

354-391
- PDF
AI-Powered Predictive Analytics for Retail Supply Chain Risk Management: Advanced Techniques, Applications, and Real-World Case Studies

Venkata Siva Prakash Nimmagadda (Author)

152-194
AI-Powered Risk Assessment Models in Property and Casualty Insurance: Techniques, Applications, and Real-World Case Studies

Venkata Siva Prakash Nimmagadda (Author)

194-226
- PDF
Machine Learning Algorithms for Enhancing Supplier Relationship Management in Retail: Techniques, Tools, and Real-World Case Studies

Mohit Kumar Sahu (Author)

227-271
- PDF
Machine Learning Algorithms for Personalized Financial Services and Customer Engagement: Techniques, Models, and Real-World Case Studies

Mohit Kumar Sahu (Author)

272-313
- PDF
Social Data Engineering: Leveraging User-Generated Content for Advanced Decision-Making and Predictive Analytics in Business and Public Policy

Jaswinder Singh (Author)

392-418
- PDF
A Data-Driven Approach to Incident Management: Enhancing DevOps Operations with Machine Learning-Based Root Cause Analysis

Venkata Mohit Tamanampudi (Author)

419-466
- PDF
AI-Powered Cloud Security for Agile Transformation: Leveraging Machine Learning for Threat Detection and Automated Incident Response

Seema Kumari (Author)

467-488
- PDF
API-led integration for improved healthcare interoperability

Dheeraj Kumar Dukhiram Pal, Vipin Saini, Ajay Aakula (Author)

488-527
- PDF
Optimizing Marketing Strategies in E-Commerce with AI: Techniques for Predictive Analytics, Customer Segmentation, and Campaign Optimization

Nischay Reddy Mitta (Author)

527-568
- PDF
The Role of AI in Regulatory Compliance and Reporting in the Banking Sector

VinayKumar Dunka (Author)

569-602
- PDF
Network Isolation Techniques in Multi-Tenant EKS Clusters

Babulal Shaik (Author)
- PDF
Batch vs. Stream Processing: In-depth Comparison of Technologies, with Insights on Selecting the Right Approach for Specific Use Cases

Muneer Ahmed Salamkar (Author)
- PDF
Data Integration Techniques: Exploring tools and methodologies for harmonizing data across diverse systems and sources

Muneer Ahmed Salamkar, Karthik Allam (Author)
- PDF
Data as a Product: How Data Mesh is Decentralizing Data Architectures

Naresh Dulam, Venkataramana Gosukonda, Kishore Reddy Gade (Author)
- PDF
Data Mesh in Practice: How Organizations are Decentralizing Data Ownership

Naresh Dulam, Abhilash Katari, Karthik Allam (Author)
- PDF
Moving data warehousing and analytics to the cloud to improve scalability, performance and cost-efficiency

Sarbaree Mishra (Author)
- PDF
Training AI models on sensitive data - the Federated Learning approach

Sarbaree Mishra, Vineela Komandla, Srikanth Bandi, Sairamesh Konidala, Jeevan Manda (Author)
- PDF
Automating the data integration and ETL pipelines through machine learning to handle massive datasets in the Enterprise

Sarbaree Mishra (Author)
- PDF

Vol. 6 (2020): Distributed Learning and Broad Applications in Scientific Research

Articles

Software Engineering Education and Training: Studying innovative approaches to software engineering education and training to prepare students for industry demands and challenges

Software Configuration Management - Practices and Tools: Investigating software configuration management practices and tools for version control, change management, and release management

Software Architecture Evaluation Methods and Tools: Analyzing methods and tools for evaluating software architectures to ensure adherence to quality attributes and design principles

Real-Time Integration of Data Between Different Systems in Healthcare: Implementing Advanced Interoperability Solutions for Seamless Information Flow

AI-Driven Customer Support in E-Commerce: Advanced Techniques for Chatbots, Virtual Assistants, and Sentiment Analysis

AI-Driven Energy Management in Manufacturing: Optimizing Energy Consumption and Reducing Operational Costs

AI-Driven Fraud Detection in E-Commerce: Advanced Techniques for Anomaly Detection, Transaction Monitoring, and Risk Mitigation

AI-Driven Metabolomics: Uncovering Metabolic Pathways and Biomarkers for Disease Diagnosis and Treatment

AI-Powered Predictive Analytics for Retail Supply Chain Risk Management: Advanced Techniques, Applications, and Real-World Case Studies

AI-Powered Risk Assessment Models in Property and Casualty Insurance: Techniques, Applications, and Real-World Case Studies

Machine Learning Algorithms for Enhancing Supplier Relationship Management in Retail: Techniques, Tools, and Real-World Case Studies

Machine Learning Algorithms for Personalized Financial Services and Customer Engagement: Techniques, Models, and Real-World Case Studies

Social Data Engineering: Leveraging User-Generated Content for Advanced Decision-Making and Predictive Analytics in Business and Public Policy

A Data-Driven Approach to Incident Management: Enhancing DevOps Operations with Machine Learning-Based Root Cause Analysis

AI-Powered Cloud Security for Agile Transformation: Leveraging Machine Learning for Threat Detection and Automated Incident Response

API-led integration for improved healthcare interoperability

Optimizing Marketing Strategies in E-Commerce with AI: Techniques for Predictive Analytics, Customer Segmentation, and Campaign Optimization

The Role of AI in Regulatory Compliance and Reporting in the Banking Sector

Network Isolation Techniques in Multi-Tenant EKS Clusters

Batch vs. Stream Processing: In-depth Comparison of Technologies, with Insights on Selecting the Right Approach for Specific Use Cases

Data Integration Techniques: Exploring tools and methodologies for harmonizing data across diverse systems and sources

Data as a Product: How Data Mesh is Decentralizing Data Architectures

Data Mesh in Practice: How Organizations are Decentralizing Data Ownership

Moving data warehousing and analytics to the cloud to improve scalability, performance and cost-efficiency

Training AI models on sensitive data - the Federated Learning approach

Automating the data integration and ETL pipelines through machine learning to handle massive datasets in the Enterprise

Journal Snapshot

Make a Submission

Invitation for Submissions