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AI-Driven Data Warehouse Modernization in the Healthcare Sector: A Blueprint for Efficiency Modernizing Legacy Data Warehouses with AI-Enhanced Workflows

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AI-Driven Data Warehouse Modernization in the Healthcare Sector: A Blueprint for Efficiency Modernizing Legacy Data Warehouses with AI-Enhanced Workflows/strong>
Authors:-Srinivasa Chakravarthy Seethala

Abstract-The healthcare industry is at a pivotal moment in terms of data management. Legacy data warehouses, which once served the sector’s needs, are now proving inefficient in an era of rapid technological advancements. This article proposes a framework for modernizing these legacy systems with Artificial Intelligence (AI) technologies, particularly AI-enhanced Extract, Transform, Load (ETL) workflows. These technologies have the potential to significantly improve data quality, operational efficiency, and scalability, especially in key areas such as Electronic Health Records (EHRs), Medical Imaging, Hospital Management, and Medical Research. Additionally, AI enables predictive analytics, offering healthcare organizations the ability to anticipate patient needs and optimize resource allocation. This paper explores the challenges healthcare organizations face, the benefits of AI-driven solutions, and best practices for implementation.

DOI: 10.61137/ijsret.vol.2.issue6.135
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Aspect-Oriented Programming in Spring: Enhancing Code Modularity and Maintainability

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Aspect-Oriented Programming in Spring: Enhancing Code Modularity and Maintainability
Authors:-RamaKrishna Manchana

Abstract-Aspect-Oriented Programming (AOP) in Spring allows for the modularization of cross-cutting concerns such as logging, security, and transaction management, improving code maintainability and reducing duplication. This paper explores AOP concepts, implementation details, and practical use cases, specifically focusing on the Common Logger and Global Exception Handler.

DOI: 10.61137/ijsret.vol.2.issue5.126

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Container Intelligence At Scale: Harmonizing Kubernetes, Helm, And OpenShift For Enterprise Resilience

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Authors: Harish Govinda Gowda

Abstract: Containers have become the backbone of modern enterprise IT, providing portability, agility, and consistency across environments. However, scaling containers across hybrid and multi-cloud infrastructures requires more than orchestration—it demands governance, security, and resilience. This article explores how Kubernetes, Helm, and OpenShift can be harmonized to achieve container intelligence at scale. Kubernetes provides orchestration, Helm simplifies application deployment and lifecycle management, and OpenShift delivers governance, compliance, and enterprise-grade security. By layering these tools together, organizations can create resilient, scalable ecosystems that balance agility with trust. The discussion highlights key challenges in scaling containers, the role of each tool, and best practices for enterprise adoption, emphasizing that true resilience comes from harmonizing orchestration, management, and governance into one cohesive framework.

DOI: http://doi.org/10.5281/zenodo.16992539

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Java Virtual Machine (JVM): Architecture, Goals, and Tuning Options

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Java Virtual Machine (JVM): Architecture, Goals, and Tuning Options
Authors:-RamaKrishna Manchana

Abstract-The Java Virtual Machine (JVM) plays a pivotal role in Java’s platform-independent execution, providing a runtime environment that translates Java bytecode into machine-specific instructions. This paper explores the architecture of the JVM, detailing its core subsystems, execution strategies, and tuning options available as of 2017. By examining the association between the JVM, JRE, and JDK, alongside advanced tuning techniques, this paper provides insights into optimizing performance metrics such as latency, throughput, and memory usage for various application needs.

DOI: 10.61137/ijsret.vol.1.issue3.42

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