Research Student

Critical infrastructure protection has emerged as a cornerstone of national and global security in an increasingly interconnected digital landscape. This comprehensive article analysis explores the multifaceted approaches required to protect vital infrastructure systems from evolving cyber threats while ensuring operational resilience. The article...

The proliferation of customer relationship management (CRM) systems such as Salesforce has led to the accumulation of vast amounts of sensitive client data across globally distributed servers. However, privacy regulations and organizational policies often restrict centralization of such data. This paper proposes a federated learning (FL) framework...

In the rapidly evolving financial services landscape, investment banking middle office functions are increasingly recognized as critical enablers of operational efficiency, regulatory compliance, and risk mitigation. This paper explores how artificial intelligence (AI) is reshaping data management and automation in the middle office of investment b...

The dynamic nature of Agile software development has elevated the need for advanced, proactive Quality Assurance (QA) mechanisms. This paper explores the integration of Artificial Intelligence (AI) in predictive quality assurance within Agile frameworks, focusing on the role of AI-driven metrics and continuous feedback systems. Through comprehensiv...

As organizations increasingly rely on Customer Relationship Management (CRM) systems to manage client interactions, the demand for workflow automation across diverse tenants has intensified. Traditional CRM platforms, however, struggle to accommodate high degrees of customization and scalability, especially in multi-tenant environments. This paper...

The rise of remote work has transformed how organizations manage internal communication. Artificial Intelligence (AI), particularly natural language processing (NLP) and communication analytics, offers novel strategies to improve communication efficiency, reduce information overload, and enhance decision-making. This study synthesizes recent litera...

As AI-driven microservices gain prominence in enterprise applications, optimizing resource allocation while maintaining cost efficiency has become increasingly critical. Multi-cloud environments, particularly those integrating Salesforce infrastructure, present unique challenges and opportunities for implementing effective auto-scaling strategies....

Digital Twins (DTs) have emerged as a transformative technology for real-time monitoring and predictive analytics in IT infrastructure. By creating virtual replicas of physical systems, DTs enable continuous data synchronization, anomaly detection, and performance forecasting. This paper explores the application of Digital Twins in IT infrastructur...

Data security and user privacy remain pivotal concerns for cloud-based platforms, particularly for CRM systems like Salesforce. Traditional centralized data processing methods expose sensitive data to potential breaches, making it imperative to adopt more robust security frameworks. This paper explores the implementation of federated learning (FL)...

Cybersecurity threats have increased in complexity and frequency in recent years, posing significant risks to individuals, corporations, and governments. Traditional reactive security measures have proven inadequate in handling sophisticated cyberattacks, necessitating the adoption of proactive threat mitigation and intelligent defense mechanisms....

As enterprises increasingly adopt Salesforce Cloud platforms for CRM and operational needs, integrating Artificial Intelligence (AI) within DevOps pipelines has become crucial for scalable, automated, and efficient Continuous Integration and Deployment (CI/CD). This paper investigates how AI-driven pipelines enhance automation, optimize testing cyc...

The evolution of supply chain management (SCM) increasingly demands agile, automated, and collaborative digital infrastructure. The global shift toward digital-first operations and remote collaboration, the integration of Robotic Process Automation (RPA) with GitHub-based DevOps platforms presented a unique opportunity for optimizing SCM workflows....

The integration of artificial intelligence (AI) workloads within distributed cloud infrastructures presents significant interoperability challenges, particularly when leveraging platform ecosystems like Salesforce APIs. This paper explores the complexities associated with AI workload integration in multi-cloud environments, emphasizing data interop...

The proliferation of autonomous systems across high-stakes domains such as healthcare, transportation, defense, and finance has necessitated the development of trustworthy Artificial Intelligence (AI) architectures. Trustworthiness in these systems hinges on two foundational pillars: explainability and ethical compliance. This paper explores the de...

This paper explores the potential of GitHub-based DevOps pipelines to optimize Robotic Process Automation (RPA) within agile supply chain systems. In the rapidly evolving digital economy, the convergence of DevOps and RPA promises to enhance responsiveness, reduce latency, and improve operational efficiency across global supply chains. Using a conc...

In an era of increasing digital dependence, cyber threats have become more sophisticated and pervasive. Traditional security measures are no longer sufficient to combat advanced cyberattacks, necessitating the development of adaptive threat detection and resilient network defense mechanisms. This paper explores the current state of cybersecurity st...

The rapid advancement of Artificial Intelligence (AI) and Robotics has revolutionized agricultural practices, particularly in the domain of precision agriculture. This study presents a comprehensive framework for integrating AI and robotics to enhance crop monitoring and optimize yield outcomes. The proposed system leverages advanced machine learni...

With the proliferation of smart devices and the growing need for real-time, intelligent decision-making at the edge, the integration of reinforcement learning (RL) in a federated learning (FL) setting has emerged as a transformative approach for privacy-preserving collaborative intelligence. In this paper, we propose a Federated Reinforcement Learn...

Industrial Internet of Things (IIoT) applications demand real-time data processing capabilities due to their mission-critical nature. Traditional cloud computing models introduce latency issues that hinder real-time responsiveness. This research explores the evolution and implementation of scalable edge-cloud hybrid computing frameworks that addres...

This paper investigates the comparative efficiencies of AI model lifecycle management in cloud-native versus traditional architectures, particularly in the context of Salesforce-driven enterprise environments. With the growing reliance on AI for automated decision-making and CRM systems like Salesforce, the infrastructure underpinning model develop...

The growing deployment of service robots in dynamic indoor environments necessitates robust navigation systems capable of coping with unpredictability and sensor noise. This paper presents a multimodal sensor fusion framework integrating LiDAR, vision, and inertial sensors to enhance autonomous navigation in complex indoor settings. By leveraging c...

The proliferation of serverless computing has transformed cloud-native application deployment by abstracting infrastructure management and scaling mechanisms. However, ensuring energy-efficient resource allocation within these dynamic environments remains a critical challenge. This study proposes a novel evolutionary game theory (EGT)-based resourc...

The increasing integration of DevOps practices into modern software supply chains has revolutionized development pipelines, enabling continuous integration and delivery. However, this shift also introduces complex security and risk vectors, particularly when automation technologies like Robotic Process Automation (RPA) are orchestrated via platform...

The rapid urbanization and exponential increase in traffic volumes demand intelligent, real-time solutions for adaptive traffic management. This paper presents a novel Multi-Agent Deep Learning (MADL) framework designed for dynamic and context-aware traffic signal control in Intelligent Urban Transportation Systems (IUTS). The proposed architecture...

Autonomous robotics has rapidly evolved, leveraging advanced machine learning (ML) models to enhance decision-making capabilities in complex and dynamic environments. This paper explores the integration of state-of-the-art ML models in autonomous robotics, emphasizing their role in optimizing decision-making processes. We conduct a comprehensive li...

In the rapidly evolving landscape of distributed supply chains, the convergence of DevOps and Robotic Process Automation (RPA) offers a promising frontier for enhancing agility, transparency, and operational efficiency. This paper explores how GitHub-based collaboration platforms, combined with automation artifacts, can be utilized to bridge the ga...

The increasing complexity of Very-Large-Scale Integration (VLSI) chips presents significant challenges in fault localization, particularly as traditional deterministic testing methods struggle with scalability and coverage. This research explores the integration of semi-supervised learning techniques with temporal test signature analysis for enhanc...

Bioinspired robotic systems have emerged as promising platforms capable of robust locomotion across unstructured and unpredictable terrains. Mimicking the adaptive strategies of biological organisms, these robots aim to overcome the limitations of traditional mechanical systems, particularly in navigation tasks where terrain variability presents si...

The modern software development ecosystem demands agility, speed, and reliability. Agile methodologies address adaptability and iterative development, while DevOps practices empower automation, collaboration, and deployment efficiency. This paper analyzes the impact of DevOps practices—particularly Continuous Integration/Continuous Deployment (CI/C...

Forecasting temporal events from high-dimensional sparse observational data presents significant challenges due to noise, confounding factors, and data sparsity. Traditional sequence models often struggle in extracting underlying causal relationships, leading to biased forecasts. Causal Representation Learning (CRL) aims to uncover latent causal fa...

Abstract: The integration of artificial intelligence (AI), particularly self-learning algorithms, into financial operations has transformed how investment banks manage the vast influx of structured and unstructured data. Structured data, such as transaction logs and market prices, and unstructured data, including emails, news feeds, and social medi...

Federated Learning (FL) enables decentralized training of machine learning models by allowing edge devices to collaboratively learn without sharing raw data. However, deploying FL in cloud environments introduces challenges due to dynamic node availability and latency-sensitive applications, particularly in heterogeneous infrastructures. This study...

Banks are important economic growth agents globally because of their roles in the intermediation of funds for investment and entrepreneurial activities. There is a relationship that develops between parties in the process of intermediation; the Banker-Customer relationship. The contract in the banker-customer relationship requires the bank to pay t...

The integration of Artificial Intelligence in healthcare represents a transformative advancement in modern medicine, particularly in diagnostic applications and personalized treatment approaches. This comprehensive article examines the current state and future prospects of AI in healthcare, focusing on medical diagnosis, data analytics, and precisi...

As multi-die systems become prevalent in modern semiconductor architectures, validation complexities have increased significantly. Root cause analysis (RCA) of failures in such complex systems demands interpretable methods that ensure engineers can understand and act upon the outcomes. This paper explores how interpretable machine learning (ML) tec...

In the age of data-driven decision-making, Salesforce dashboards have emerged as a cornerstone for real-time analytics in enterprise environments. However, integrating heterogeneous data sources into a unified and scalable dashboard framework remains a critical challenge. This paper proposes a modular, cloud-compatible data integration framework ta...

Customer churn prediction has become a pivotal challenge for industries operating in subscription-based or competitive market environments. Advances in artificial intelligence, particularly sequential learning models such as Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks, offer unprecedented potential for detecting patt...

This study introduces a method to explore the gaps between consecutive prime numbers, aiming to identify patterns without relying on traditional heuristic models or probabilistic estimations. As numbers grow larger, gaps between primes generally increase, aligning roughly with formula (Gap=g(Pn) trends. However, a purely pattern-based approach coul...

The rapid evolution of enterprise IT infrastructure has exposed critical challenges in managing data complexity, particularly the proliferation of ungoverned "data swamps" that undermine scalability and interoperability. This paper proposes Agnostic Informational Architecture (AIA)a technology-agnostic framework emphasizing interoperability, govern...

The proliferation of artificial intelligence (AI) and robotic process automation (RPA) technologies has revolutionized back-office processes across the banking sector. However, achieving scalable, adaptable, and governance-aligned intelligent automation remains a challenge, especially for institutions navigating complex regulatory environments. Thi...

This article conducts a thorough analysis of the dynamic interactions among exchange rates, inflation rates, and two prominent stock market indices: SENSEX (India) and SZSE Component Index (China). Its core objective is to examine how fluctuations in exchange rates and inflation rates influence the behaviour of these critical stock market benchmark...

Data and records have been a staple of human civilization through the millennia. As humanity progresses the data generation has grown exponentially. Sharing large datasets across servers is critical for industries dependent on distributed systems, real-time processing, and data-driven decisions. Scientific research, Media, Finance, Healthcare, and...

This comprehensive technical article examines Salesforce's evolution in integration capabilities, focusing on its architectural advancements and implementation frameworks. The article explores API architecture, middleware integration through MuleSoft, pre-built connector frameworks, and real-time integration capabilities. The article delves into th...

PCI Express (PCIe) technology is a cornerstone of high-speed data transfer, driving innovation across numerous modern applications. This article delves into the increasingly complex landscape of PCIe verification, specifically addressing the unique challenges presented by advanced features in PCIe 6.0 and PCIe 7.0, such as Pulse Amplitude Modulatio...

This comprehensive technical article examines Salesforce's evolution in integration capabilities, focusing on its architectural advancements and implementation frameworks. The article explores API architecture, middleware integration through MuleSoft, pre-built connector frameworks, and real-time integration capabilities. The article delves into th...

This study provides a detailed comparison of two leading policy management software in the insurance industry, Guidewire PolicyCenter and Duck Creek Policy Administration in terms of architecture, key features, core functionality, scalability, and industry adoption by evaluating real-world implementations and customer case studies. The study aims t...

The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies has emerged as a transformative force in enterprise digital transformation, fundamentally reshaping operational paradigms and competitive landscapes. This comprehensive article examines the strategic implementation of AI/ML solutions alongside automation technolo...

Salesforce Field Service represents a transformative solution in the field service management landscape, revolutionizing how organizations handle mobile workforce operations. The platform integrates artificial intelligence and machine learning capabilities to enhance service delivery, optimize scheduling, and improve resource allocation. Through au...

The financial sector is undergoing a profound transformation through the convergence of Artificial Intelligence (AI) and Business Intelligence (BI). This article examines how AI technologies are revolutionizing financial analytics and data visualization while emphasizing the critical balance between technological advancement and human expertise. Th...

One of the foremost challenges confronting healthcare companies today is the dual objective of reducing the cost of care while enhancing healthcare quality for patients. The term "cost of care" refers to the expenses incurred by healthcare insurance companies in managing a patient's health. A prevalent factor exacerbating these costs is the "fee-fo...

The evolution of Customer Relationship Management (CRM) systems has positioned them as critical repositories of sensitive customer data, making robust security measures essential. The integration of encryption, tokenization, and secure API protocols safeguards customer information while maintaining operational efficiency. Advanced security framewor...

The financial services industry is experiencing a revolutionary transformation through the integration of artificial intelligence and advanced automation technologies in risk management and fraud detection systems. This transformation encompasses the evolution from traditional rule-based systems to sophisticated AI-driven architectures, incorporati...

Distributed search systems achieve scalability and low latency through the orchestrated implementation of five fundamental architectural components. At the foundation lies distributed indexing strategies, which optimize data distribution through range-based partitioning and consistent hashing, enabling systems to scale horizontally while maintainin...

This research investigates the aerodynamic performance of Low-Induction Axial Momentum (LIAM) propeller blades by exploring innovative design modifications. The study aims to enhance UAV performance and support humanitarian missions by comparing blade designs incorporating airfoil geometries and wave patterns along the edges. Simulations conducted...

Next-Generation SAP BW migration to AWS infrastructure presents a transformative approach to enterprise data management, offering organizations enhanced scalability, performance, and cost-effectiveness. This comprehensive guide explores the essential phases of migration, from initial assessment through implementation to post-migration validation. T...

This article presents an innovative approach to incident management through the integration of AI-driven chatbot solutions within Microsoft enterprise ecosystems. The article explores the evolution from traditional help desk systems to sophisticated AI-powered platforms, emphasizing the transformative impact of Large Language Models and advanced an...

Accurate patient identity resolution across disparate healthcare systems is a significant challenge due to the absence of a universal patient identifier. This fragmentation hampers cohesive patient care and poses obstacles to effective data exchange. Beyond healthcare, industries employing Customer Data Platforms (CDPs) face analogous issues in uni...

Cloud computing has revolutionized the IT industry, providing scalable, flexible, and cost-effective solutions for businesses and individuals. However, the shift to cloud environments has also introduced significant cybersecurity challenges. This paper explores various threats associated with cloud security, including data breaches, insider attacks...

This article provides a comprehensive exploration of implementing Zero Trust principles in API security for cloud-native applications. It delves into the critical aspects of securing APIs in modern, distributed environments, addressing the challenges posed by multi-cloud deployments and containerized applications. The article covers a range of topi...

This article explores the transformative role of artificial intelligence in regulatory compliance across the technology sector, with a particular focus on automating legal enforcement mechanisms. The article examines how AI technologies are revolutionizing traditional compliance approaches through sophisticated machine learning models, real-time mo...

This article explores the transformative role of Artificial Intelligence in modernizing legacy mainframe systems within enterprise environments. As organizations face increasing pressure to evolve their critical infrastructure while maintaining operational continuity, AI technologies emerge as pivotal solutions in addressing modernization challenge...

Machine learning models have become increasingly prevalent in consumer finance, revolutionizing credit decisioning while raising significant concerns about fairness and transparency. This article presents a comprehensive framework for bias testing in machine learning models within the financial services sector, addressing both regulatory compliance...

Blockchain technology is revolutionizing cross-border payment systems by addressing longstanding challenges in global financial transactions. This comprehensive article explores the technical architecture, implementation frameworks, and future developments of blockchain-based payment solutions. It examines how distributed ledger technology and smar...

AI and ML-driven middleware represents a transformative evolution in enterprise integration, revolutionizing how organizations handle system integration, data processing, and workflow automation. This advanced technology stack incorporates sophisticated machine learning models and neural networks to create dynamic, self-Dileep Kumar Siripurapu http...

Generative AI is revolutionizing robotic sensing by significantly enhancing the adaptability and efficiency of robots in dynamic, unstructured environments. Traditional camera-based robotic sensing systems, particularly those based on feature extraction methods like SIFT and SURF, often struggle in complex real-world conditions, such as varying lig...

This comprehensive technical article explores the implementation of Multi-Factor Authentication (MFA) in financial systems, focusing on advanced security mechanisms that protect digital assets and sensitive data. The article examines the evolution of authentication factors, quantum-resistant protocols, and artificial intelligence-driven security mo...

This comprehensive article explores the evolution and current state of DevOps engineering, examining its transformation from a conceptual framework to an essential practice in modern software development. It investigates how the integration of cloud computing has catalyzed DevOps adoption, enabling organizations to achieve superior deployment capab...

The digital transformation has fundamentally reshaped data protection strategies, particularly concerning personally identifiable information (PII) in enterprise systems. Organizations face increasing challenges in safeguarding sensitive data amid evolving cyber threats and regulatory requirements. Traditional security measures prove inadequate aga...

This article examines the critical challenges and potential solutions regarding quantum computing's impact on Transport Layer Security (TLS) and QUIC protocols. The article analyzes the vulnerabilities introduced by quantum algorithms, particularly Shor's algorithm and Grover's algorithm, which threaten current cryptographic systems. By investigati...

This research aims at exploring the usage of machine learning (ML) in the DevOps methodology as means of improve health care patient data management systems. As the volume and growing variability of health care data have escalated, conventional approaches to data management have proven inadequate and error-prone. Incorporating ML models into Contin...

Business process automation (BPA) has evolved significantly with the advent of artificial intelligence (AI) and machine learning (ML). This paper explores various architectural frameworks and computational paradigms that enhance BPA, focusing on efficiency, scalability, and adaptability. By examining literature before 2024, this study identifies ke...

Business process automation (BPA) has evolved significantly with the advent of artificial intelligence (AI) and machine learning (ML). This paper explores various architectural frameworks and computational paradigms that enhance BPA, focusing on efficiency, scalability, and adaptability. By examining literature before 2024, this study identifies ke...

The exponential growth of cloud computing, cybersecurity threats have become more sophisticated and difficult to mitigate. Traditional security mechanisms often struggle with real-time threat detection and adaptive risk mitigation. This paper presents a deep learning-driven framework leveraging federated learning and blockchain-assisted anomaly det...

The rapid evolution of 5G networks demands advanced architectural enhancements to support ultra-low latency applications. Cloud-native architectures, coupled with intelligent automation and Software-Defined Networking (SDN), play a crucial role in meeting these stringent requirements. This paper explores the integration of SDN and automation within...

The healthcare sector is experiencing a transformative digital revolution driven by Big Data analytics, fundamentally changing how medical services are delivered and managed. This comprehensive article analysis explores the integration of advanced technologies in healthcare, focusing on predictive analytics for clinical decision support, genomics a...

With the rise of complex software applications, modern architectural paradigms such as Microservices Architecture (MSA), Service-Oriented Architecture (SOA), and Cloud-Based Architectureshave gained significant traction. These architectures aim to improve scalability, resilience, and maintainability in distributed systems. While they share common p...

Multifunctional nanostructured materials with tunable electronic and catalytic properties have gained significant attention in recent years due to their wide range of applications in chemical, biomedical, and environmental fields. These materials exhibit unique physicochemical characteristics, including high surface area, quantum confinement effect...

Machine Learning (ML) and Deep Learning (DL) have revolutionized artificial intelligence (AI) by enabling automated decision-making, pattern recognition, and predictive analytics. This paper provides a comprehensive review of classical and modern ML algorithms along with advanced deep learning architectures, highlighting their applications, challen...

The rapid advancement in energy storage and catalysis technologies has necessitated the development of novel materials with tailored electronic properties. Transition metal-based inorganic complexes have emerged as promising candidates due to their tunable electronic structure, hierarchical morphology, and diverse catalytic functionalities. This pa...

The rise of cloud computing has brought unprecedented opportunities for resource optimization but also significant challenges in efficiently managing resources across dynamic environments. Artificial Intelligence (AI)-driven decision systems offer robust solutions for optimizing resource allocation by predicting workloads, automating scaling, and m...

Generative AI has revolutionized intelligent service deployment in cloud computing, offering scalable solutions for data processing and analytics. This paper explores theoretical underpinnings and practical applications of generative AI within Amazon Web Services (AWS) architectures, focusing on optimizing cloud-based workflows. The study systemati...

The advent of artificial intelligence (AI) has catalyzed transformative shifts across various sectors, including very-large-scale integration (VLSI) and semiconductor manufacturing. This paper explores the emerging paradigms driven by AI in process control and defect detection, which are pivotal to sustaining advancements in semiconductor technolog...

Metalloenzymes play a crucial role in biological catalysis and have significant applications in biomedical and industrial fields. Understanding their structure-function relationship through computational and experimental approaches provides valuable insights into their mechanism, stability, and efficiency. Computational methods such as molecular dy...

The telecommunications industry is witnessing a fundamental transformation in Business Support Systems (BSS) to meet evolving enterprise demands. This comprehensive article examines the shift from traditional uniform approaches to specialized enterprise-centric solutions, highlighting the impact of AI-driven service customization, advanced backend...

This article explores the concept of holistic observability in modern distributed systems, emphasizing its crucial role in managing and optimizing cloud-native environments. It delves into the limitations of traditional monitoring approaches and highlights how the integration of metrics, logs, and traces provides a comprehensive view of system heal...

Enterprise integration challenges have become increasingly complex as organizations adopt diverse cloud and on-premise solutions. Oracle Integration Cloud (OIC) emerges as a comprehensive platform to address these integration needs, yet its technical complexity often presents a barrier to adoption. This article analyzes OIC's architecture, componen...

Rare Earth Elements (REEs) are vital for modern technological applications, including renewable energy technologies and electronics. The exploration of REE deposits in hydrothermal systems requires an understanding of geochemical and isotopic signatures that characterize their formation and mobilization. This paper reviews the role of isotopic trac...

Mobile applications have become integral to modern life, offering convenience and functionality across diverse domains. However, the increasing prevalence of mobile app usage has also led to heightened security threats, ranging from data breaches and malware attacks to phishing and unauthorized access. This paper delves into the critical strategies...

Super AI, also known as artificial general intelligence (AGI), represents the next paradigm shift in artificial intelligence (AI) research. Unlike narrow AI systems designed for specific tasks, Super AI aspires to surpass human intelligence in all cognitive tasks, displaying reasoning, learning, problem-solving, and even creativity. This paper expl...

Biomedical implants play a critical role in restoring function and improving the quality of life for patients requiring orthopedic and dental prosthetics. This study focuses on the topology and shape optimization of biomedical implants to enhance their biomechanical performance and osseointegration using finite element analysis (FEA). A detailed re...

This article presents a comprehensive framework for developing and evaluating AI products in enterprise software systems, addressing the critical challenges organizations face during AI transformation initiatives. The article introduces a structured approach to decision-making for AI integration, encompassing ROI evaluation, user value assessment,...

Classification tasks are typically handled using Machine Learning (ML) models, which lack a balance between accuracy and interpretability. This paper introduces a new approach for classification tasks using Large Language Models (LLMs) in an explainable method. Unlike ML models, which rely heavily on data cleaning and feature engineering, this meth...

Healthcare organizations face increasingly complex challenges in integrating and managing patient data while maintaining stringent security and compliance standards. This comprehensive technical article presents a structured framework for implementing secure, compliant, and scalable data integration solutions in healthcare environments. The article...

Fraudulent financial transactions pose a significant threat to global financial systems, demanding timely and intelligent countermeasures. This study presents a short research exploration into the development of AI-driven systems for early fraud detection through transactional anomaly detection techniques. Focusing on machine learning and statistic...

Time-varying sales data, characterized by non-stationarity and dynamic trends, presents a significant challenge for accurate forecasting. This paper proposes an adaptive forecasting framework that leverages multi-resolution learning models, integrating hierarchical temporal features to enhance prediction accuracy. The framework employs hybrid machi...

As the demand for artificial intelligence (AI) services continues to scale, cloud-native paradigms like serverless computing have emerged as critical enablers of efficient, elastic, and cost-effective AI deployments. This study investigates the design and evaluation of resource-aware AI services using serverless functions in the cloud. We explore a...

The proliferation of AI models across industries has spurred the need for flexible and interoperable deployment strategies that enable seamless migration and sharing across heterogeneous cloud environments. This paper proposes a modular AI deployment framework that decouples model development, packaging, and orchestration layers to ensure cloud-agn...

This study investigates how Artificial Intelligence (AI)-driven predictive analytics has been revolutionizing knowledge management (KM) practices in large enterprises. While traditional KM systems focused on static knowledge repositories and information retrieval, predictive analytics enables proactive knowledge delivery, anticipatory decision-maki...

In an increasingly digitized global economy, the integrity of supply chain processes is paramount. Compliance and traceability in supply chain operations are often challenged by fragmented manual documentation, delayed reporting, and limited data transparency. This paper proposes a novel approach to enhancing auditability by integrating GitHub-base...