Research Scholar X

As artificial intelligence (AI) increasingly permeates all aspects of human life, ensuring that AI systems remain ethically grounded and human-centric has become paramount. This paper presents a holistic framework integrating adaptive machine learning capabilities with principles of ethical governance. By focusing on collaborative intelligence, exp...

In the context of regulated software systems—such as those used in healthcare, finance, and aerospace—the need for reliable Quality Assurance (QA) processes is paramount. Risk-Based Quality Assurance (RBQA) has emerged as a pragmatic approach to streamline QA activities by aligning testing efforts with the assessed level of risk associated with var...

As the financial landscape grows increasingly complex and volatile, the Banking, Financial Services, and Insurance (BFSI) sector is under heightened pressure to ensure operational resilience. This paper examines how blockchain technology, particularly in its applications to immutable audit trails and real-time risk intelligence systems, is reshapin...

The increasing complexity and volume of cyber threats necessitate robust, scalable, and intelligent cybersecurity solutions. This paper proposes a unified framework that integrates Application Programming Interfaces (APIs) with artificial intelligence (AI) models to enhance real-time threat detection and automated incident response. The study evalu...

Artificial Intelligence (AI) and Machine Learning (ML) have become pivotal in transforming decision-making and predictive analytics across various industries. AI and ML enable systems to process large volumes of data, recognize patterns, and improve outcomes through adaptive learning mechanisms. This paper explores the theoretical foundations and p...

The rapid advancement of artificial intelligence (AI), particularly in the domain of cognitive architectures and autonomous reasoning, has redefined the integration of intelligent systems into critical infrastructure. This paper explores the cognitive evolution of AI, focusing on developments in machine learning, symbolic reasoning, and adaptive co...

The escalating frequency and complexity of cyber threats have pushed enterprises to adopt more resilient and intelligent cybersecurity mechanisms. This paper explores the integration of Artificial Intelligence (AI) with API-driven security frameworks and adaptive architectures to create dynamic, self-learning, and scalable security ecosystems. Thro...

Learning meaningful representations without large amounts of labeled data has become a cornerstone challenge in machine learning, especially in scenarios involving multimodal data and sparse annotation. This paper explores a hybrid approach combining contrastive learning and generative self-supervised techniques for robust feature extraction in cro...

The exponential growth in data volume and complexity has necessitated transformative approaches to database architecture. This paper explores the integration of Artificial Intelligence (AI) techniques into modern database management systems (DBMS) to enable predictive query processing, autonomous indexing, and dynamic schema evolution. The study re...

The accelerating digitization of critical infrastructure and enterprise operations has intensified the demand for adaptive and intelligent cybersecurity mechanisms. Traditional perimeter-based defenses are insufficient in the face of API-driven architectures, cloud-native applications, and advanced persistent threats (APTs). This paper proposes a h...

Modern IT infrastructure demands high availability, robustness, and fault tolerance, especially in distributed cloud-native systems. As digital ecosystems grow increasingly complex, traditional manual recovery mechanisms prove insufficient. This paper investigates how Chaos Engineering combined with automated recovery protocols enhances system resi...

The rapid integration of Artificial Intelligence (AI) into public sector policy and governance presents both transformative opportunities and considerable challenges. As governments worldwide increasingly adopt AI-driven tools for decision-making, service delivery, and resource allocation, the societal impact spans ethical, economic, and political...

The rising demand for scalable and efficient data processing has driven the adoption of cloud-native architectures. However, designing pipelines that adapt automatically to fluctuating workloads while minimizing cost remains a complex challenge. This study proposes an AutoML-powered framework for dynamically optimizing data processing pipelines in...

Healthcare data integration remains a critical challenge and opportunity in modern medicine. As electronic health records (EHRs), genomics, imaging, and real-time monitoring data proliferate, integrating these diverse and often incompatible systems is essential to enable accurate clinical decision-making and improve patient outcomes. This paper pro...

The rapid growth of mobile computing has significantly transformed how users access information and services, enabling seamless connectivity and real-time data processing. However, increasing demands for faster response times and enhanced data security have driven the need for more adaptive and resilient network architectures. This paper explores t...

As cyber threats grow in complexity and scale, traditional security protocols struggle to maintain resilience and adaptability. In response, the integration of Artificial Intelligence (AI) and modular software frameworks is transforming cybersecurity architectures by enabling real-time, adaptive threat detection and response. This paper explores ho...

As organizations increasingly adopt diverse data management technologies, integrating data from heterogeneous distributed databases becomes a significant challenge. Schema matching, the process of identifying correspondences between semantically related entities of different schemas, is central to achieving semantic interoperability. Traditional sc...

In an era where cloud-native applications span across multi-cloud platforms, ensuring fault tolerance, security, and seamless orchestration is critical. This paper introduces a blockchain-integrated orchestration framework that leverages decentralized identity management (DID) to enhance the security and resiliency of cloud services. By integrating...

The rapid advancement in artificial intelligence (AI) and cloud computing has paved the way for innovative data analytics frameworks tailored for real-time industrial applications. This paper critically evaluates AI-enhanced cloud computing models for data analytics, focusing on their impact on operational efficiency, scalability, and predictive ac...

The escalating complexity of modern System-on-Chip (SoC) designs has demanded innovative methodologies for effective simulation analysis during the validation phase. Traditional analysis of simulation outputs suffers from poor scalability and limited automation, necessitating advanced techniques to streamline the validation effort. In this paper, w...

Modern healthcare facilities demand digital accessibility to guarantee equal access to telemedicine platforms, online pharmacy services, and health monitoring devices that can be worn or are handy. With the rising call for the implementation of robust digital healthcare solutions, people with disabilities encounter impediments in their endeavor of...

This research explores the efficacy of phytocompounds isolated from chicory (Cichorium intybus) to inhibit Glycogen Synthase Kinase 3 beta (GSK-3β), an important regulator of neurogenesis and Wnt/β-catenin signaling, by employing molecular docking simulations. GSK-3β dysregulation has been implicated in Alzheimer's disease, and for this reason, it...

The ticketing industry is plagued mainly by scalping, fraud and platform interoperability on top of its inflexibility with centralized systems. In this paper, we propose a blockchain based generic and reusable framework that is implemented on AWS cloud so that they will be scalable. The framework is built on Amazon Managed Blockchain, Hyperledger F...

Global Navigation Satellite Systems (GNSS) provides precise position, navigation and timing data (PNT) for global and regional satellite constellations. Geodetic GNSS receivers used for surveying and geospatial uses have the limitations of high cost and complexity. Compact, lower cost GNSS receivers/ modules, and handheld devices were commercially...

Real-time AI services deployed over serverless cloud infrastructures face unique challenges due to latency constraints, resource heterogeneity, and ephemeral function execution. Context-aware model adaptation is a promising strategy that allows AI models to adjust behavior based on environmental cues such as input complexity, network load, or user...

With the increasing proliferation of edge devices and context-aware applications, real-time personalization of services is becoming critical in domains such as healthcare, smart homes, and mobile computing. Traditional federated learning (FL) models face challenges in personalization due to data heterogeneity and latency constraints. This study pre...

Deep learning models, particularly Convolutional Neural Networks (CNNs), have achieved remarkable accuracy in medical image analysis tasks like pneumonia detection from chest X-rays. However, their "black-box" nature and the potential brittleness of common explainability methods (e.g., saliency maps) hinder clinical trust and adoption. This paper p...

Efficiently managing the AI model lifecycle in cloud-native ecosystems has become increasingly complex, especially in multi-zone cloud platforms. To maintain performance and reliability across geographies, intelligent orchestration strategies are necessary to automate deployment, predict resource needs, and ensure service continuity. This paper pre...

Purpose: This study explores the relationships between social workers' traits, professional identification, shared vision, job satisfaction and professional commitment in Mainland China. The study proposes that six traits of servant leaders, namely Commitment, Humility, Resilience, Integrity, Service and Teamwork, are essential for social workers....

This article examines the transformative impact of artificial intelligence on electronics manufacturing processes and decision-making strategies. The article explores how AI systems optimize key manufacturing parameters including first pass yield, test coverage, cycle time, and cost of quality while revolutionizing supply chain management and quali...

The increasing complexity of next-generation System-on-Chip (SoC) platforms poses significant challenges in functional validation. Traditional approaches struggle with managing the expanding validation coverage, data volume, and integration scenarios. This paper proposes a novel AI-driven framework leveraging knowledge graphs (KGs) to systematicall...

The rapid advancement of intelligent systems and their integration into computer architecture have significantly transformed software engineering processes. Modern intelligent systems, powered by artificial intelligence (AI) and machine learning (ML), offer innovative solutions to optimize performance, enhance adaptability, and automate complex dec...

Predictive analytics is transforming cash management for small and medium banks (SMBs) by enhancing forecasting accuracy, optimizing liquidity management, and improving regulatory compliance. This paper explores how predictive analytics leverages historical data, machine learning models, and real-time analysis to provide actionable insights into ca...

Predictive analytics is transforming cash management for small and medium banks (SMBs) by enhancing forecasting accuracy, optimizing liquidity management, and improving regulatory compliance. This paper explores how predictive analytics leverages historical data, machine learning models, and real-time analysis to provide actionable insights into ca...

Cybersecurity and network security have become critical areas of focus due to the increasing complexity and volume of cyber threats. Traditional security systems often struggle to keep pace with the evolving nature of these threats. This paper explores how machine learning (ML) and artificial intelligence (AI) can enhance threat detection and mitig...

Enterprise Integration and Document Automation represent cornerstone technologies that fundamentally transform organizations through seamless system connectivity and intelligent document processing capabilities. These technologies form the backbone of modern business operations, enabling efficient communication between disparate systems while conve...

Cloud computing has significantly transformed how libraries manage resources, offering enhanced flexibility, cost-efficiency, and scalability. This study examines the adoption of cloud computing services in libraries, evaluating their benefits, challenges, and overall impact on library operations. A survey of 125 library professionals was conducted...

This comprehensive article examines the optimization strategies, challenges, and best practices in implementing signal processing algorithms for embedded hardware systems. The article explores various aspects including hardware-software co-design, algorithm optimization techniques, and emerging trends in edge computing. Through articles of multiple...

This work investigated the spectral collocation technique for solving the fractional Klein-Gordon Equation (FKGE) (Caputo Derivative Sense) with the assistance of Chebyshev polynomials of the first order. The essential feature is to turn the provided issue into a system of algebraic equations that can be solved easily using any of the normal techni...

The increasing complexity of healthcare data and the need for real-time decision support necessitate scalable and interoperable data architectures. This paper explores the fundamental principles, challenges, and best practices for designing healthcare data architectures that support seamless system integration, secure data exchange, and real-time a...

Multi-cloud architectures are increasingly being adopted by enterprises and organizations to optimize resource utilization, ensure resilience, and enhance security in large-scale data processing. However, challenges related to interoperability, security, and real-time analytics persist, making traditional cloud frameworks inefficient for handling d...

In the ever-evolving landscape of retail and e-commerce, the management of inventory is a critical determinant of success. Effective sorting algorithms play an important role in enhancing inventory management, particularly when it comes to visual merchandising. One such application is the sorting of commercial products based on their colors. This a...

The creation of an Automated Sorting System utilizing a Programmable Logic Controller (PLC) responds to the demand for effective and dependable sorting mechanisms across diverse industrial and logistical sectors. This system employs PLC technology to streamline the sorting of materials or products according to established criteria, thereby improvin...

The landscape of software development and operations has undergone a significant transformation with the emergence of DevOps and Site Reliability Engineering (SRE) practices. Organizations are experiencing profound improvements in deployment frequency, change lead times, and system reliability through the adoption of these methodologies. The conver...

Modern pricing and packaging strategies have undergone a significant transformation driven by artificial intelligence, data analytics, and personalized customer engagement. Organizations are increasingly adopting dynamic pricing systems that leverage real-time market intelligence and automated decision-making capabilities. These advancements enable...

The emerging field of Hybrid Quantum-Classical Neural Networks (HQCNNs) represents a groundbreaking fusion of quantum computing capabilities with traditional neural network architectures. HQCNNs leverage the quantum advantages of superposition states and high-dimensional Hilbert spaces while maintaining the robust pattern recognition capabilities o...

This comprehensive article explores the evolution and impact of causal inference techniques across various industrial and technological domains. The article examines how causal inference has transformed traditional statistical approaches, particularly in addressing confounding variables and hidden drivers in complex systems. The article highlights...

This article examines the comprehensive modernization initiative undertaken by a clothing manufacturer to transform its production tracking and payroll processing operations. It details the challenges of legacy systems in manufacturing environments, focusing on operational inefficiencies, maintenance costs, and technical limitations that hinder bus...

The rapid evolution of cloud computing and the Internet of Things (IoT) has increased cybersecurity vulnerabilities, making threat detection and mitigation crucial. Machine learning (ML) has emerged as a powerful tool to counteract cyber threats by analyzing patterns, detecting anomalies, and preventing attacks in real time. This study provides a c...

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...

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...

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 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 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...

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...

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-optimizing frameworks that s...

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...

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...

The rapid expansion of cloud computing and high-performance computing (HPC) infrastructures has led to an increasing demand for efficient resource optimization and workload distribution strategies. With the growing complexity of global data management, organizations face challenges in balancing cost-effectiveness while maintaining high performance....

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 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...

DevOps has emerged as a transformative methodology in modern software development and IT operations, revolutionizing how organizations approach system development, deployment, and maintenance. This article examines the evolution of DevOps from its inception as a grassroots movement to its current state as a comprehensive framework driving innovatio...

This comprehensive article explores the evolution of managed SD-WAN services through closed-loop automation and its transformative impact on enterprise networking. The article examines market dynamics, technical implementation challenges, and the strategic importance of automation in SD-WAN deployments. It highlights how standards-based closed-loop...

This comprehensive article explores the transformative impact of data engineering on manufacturing and supply chain efficiency. The article examines how advanced data pipeline architectures, real-time processing capabilities, and predictive analytics are revolutionizing traditional manufacturing processes. The article investigates the implementatio...

This technical article examines the successful implementation of PayPal's payment processing system at Blueberry Brands, demonstrating significant improvements in fraud prevention, cost reduction, and international market expansion. The article explores how integrated payment solutions can transform business operations through enhanced security mea...

The rapid adoption of cloud computing has revolutionized the digital landscape by enabling scalable, flexible, and efficient computing environments. Emerging technologies such as edge computing, AI-driven automation, and multi-tenant security architectures have enhanced cloud infrastructure, ensuring improved performance, security, and reliability....

The integration of generative artificial intelligence (AI) with cloud technologies is revolutionizing healthcare customer relationship management (CRM). These advancements enable predictive and adaptive solutions, transforming patient care through data-driven insights and automation. This paper explores the role of generative AI and cloud systems i...

Aggressive periodontitis is a rapidly progressing periodontal disease associated with distinct subgingival microbial communities. Next-generation sequencing (NGS) technologies have revolutionized microbiome profiling, enabling a comprehensive analysis of microbial diversity in subgingival plaque. This study explores the bacterial composition of sub...

With the rapid growth of the Internet of Things (IoT), there is a pressing need for secure, efficient, and scalable edge computing solutions. Traditional cloud-based AI models struggle with latency, bandwidth constraints, and security vulnerabilities. Federated Learning (FL) emerges as a promising decentralized machine learning paradigm that enable...

This article examines the transformative impact of artificial intelligence and automation technologies on human resource management processes within SAP Human Capital Management (HCM) systems. Through comprehensive analysis of current implementations and emerging trends, the article explores how AI-driven solutions are revolutionizing core HR funct...

Cloud computing and edge computing have revolutionized the digital landscape by providing scalable, on-demand resources and enabling low-latency processing. However, the increasing reliance on these technologies has introduced new vulnerabilities and expanded the attack surface, creating significant challenges for cybersecurity and network resilien...

Adopting hybrid cloud architectures has fundamentally transformed enterprise IT infrastructure, enabling organizations to create dynamic and resilient systems that leverage cloud-based and on-premises infrastructure. This comprehensive article explores the evolution of hybrid cloud implementations, examining core infrastructure components, key arch...

This comprehensive article explores the transformative impact of hyperautomation in modern enterprise environments, focusing on its integration with cloud technologies and artificial intelligence. The article examines how hyperautomation revolutionizes workflow automation through the convergence of various technologies, including Artificial Intelli...

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...

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...

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...

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...

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...

Intelligent chatbots powered by Natural Language Processing (NLP) have become essential tools for enterprise knowledge systems, enhancing customer support, employee assistance, and information retrieval. This paper explores the design and implementation of NLP-based chatbots for enterprise environments, focusing on key challenges such as intent rec...

This in-depth technical article examines how cloud applications have changed, moving from small-scale implementations to enterprise-class solutions. Microservices and containerization-based architectural foundations, performance optimization through sophisticated caching and database strategies, enterprise-grade security implementations, high avail...

The combination of Genesys CTI and Salesforce CRM platforms is examined in this technical article, which also looks at how this convergence transforms call center operations. The article looks into the commercial effects, performance optimization techniques, integration mechanisms, and architectural framework of integrating CTI-CRM solutions. Accor...

This comprehensive article explores cutting-edge techniques for optimizing machine learning models, with a particular focus on advanced strategies for enhancing AI algorithms and large language models (LLMs). We begin by examining the critical role of feature engineering and selection in model performance, emphasizing the importance of word embeddi...

This comprehensive article examines the transformative impact of cloud computing technologies on healthcare delivery systems, focusing on scalable transaction systems for patient data management and real-time diagnostics. The article explores how cloud-based solutions have revolutionized electronic health records management, improved data accessibi...

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...

This article provides a practical guide to improving performance in Android applications using Jetpack Compose. It addresses key challenges developers face when building smooth, responsive user interfaces across various device categories. The article explores essential optimization strategies including efficient list rendering through lazy layouts,...

The integration of Artificial Intelligence (AI) with Internet of Things (IoT) technology has emerged as a transformative approach in smart agriculture, enabling real-time monitoring and decision-making to optimize agricultural processes. This paper explores a framework that leverages AI for processing IoT-generated data, aiming to enhance predictiv...

The rapid adoption of heterogeneous cloud-based CRM (Customer Relationship Management) systems poses challenges for data interoperability, semantic consistency, and service integration. This study proposes an ontology-based data harmonization framework designed to enable seamless integration across different CRM platforms deployed on multiple cloud...

Salesforce's rapid adoption across industries demands robust access control mechanisms that scale with component-based architecture. Traditional field-level permissions are often inconsistently enforced in Lightning Web Components (LWC), primarily due to server-side data handling and implicit system-level bypasses. This paper presents a Policy-Awar...

Quantum computing has gained significant attention for its potential to revolutionize high-performance computing, data processing, and cryptographic security. As cloud architectures evolve, integrating quantum computing can lead to improved computational speeds, secure encryption mechanisms, and optimized big data processing. This paper explores th...

Deep learning has emerged as a cornerstone of artificial intelligence (AI), revolutionizing cognitive automation and enhancing human-machine collaboration. By leveraging multilayered neural networks and computational advancements, deep learning provides a robust framework for complex data interpretation, real-time decision-making, and adaptive inte...

Generative AI has witnessed remarkable advancements in recent years, largely due to developments in deep learning and natural language processing. However, the potential for further enhancement lies in integrating multimodal techniques, combining data from various modalities such as text, image, audio, and video. This paper explores key strategies...

Federated machine learning (FML) has emerged as a transformative approach for privacy-preserving healthcare applications by enabling collaborative model training without centralizing sensitive patient data. However, significant challenges remain regarding the robustness and fairness of these models, especially in the presence of heterogeneous data...

The evolution of software testing has transitioned from manual execution to automation-centric frameworks and now toward intelligent, self-adaptive mechanisms driven by Artificial Intelligence (AI) and Machine Learning (ML). This paper proposes a lifecycle-based framework for integrating AI and ML techniques throughout the software testing continuu...

In high-stakes domains such as healthcare, law, and finance, the need for interpretable artificial intelligence (AI) systems has become increasingly critical. Neural-symbolic integration, combining the learning capabilities of neural networks with the reasoning strengths of symbolic systems, has emerged as a promising approach to address the interp...

The use of generative AI has evolved greatly over time and has been seen as having transformative capabilities in most industries, but these capabilities bring with them significant ethical concerns and regulatory challenges. This study seeks to explore the ethical implications of generative AI; for example, it delves into bias, misinformation, dat...

Cloud computing has become a cornerstone of modern IT infrastructure, offering scalable and on-demand resources. However, the increasing demand for cloud services has raised concerns about scalability and energy efficiency. This paper proposes a novel framework that integrates adaptive resource allocation algorithms with machine learning techniques...

The rapid expansion of smart cities demands the deployment of energy-efficient, intelligent systems at the network edge. Traditional cloud-centric artificial intelligence (AI) architectures are insufficient due to high latency, bandwidth constraints, and excessive energy consumption. In this paper, we explore the development of energy-efficient alg...