Al-Kindi Center for Research and Development (KCRD) (E-Journals)
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6248 research outputs found
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Building a Robust CI/CD Pipeline for AI-Powered Cloud Applications
No full textThe deployment of AI applications in cloud environments presents unique challenges that traditional CI/CD pipelines fail to address, particularly in model versioning, data quality management, and system integration. This paper presents a comprehensive framework for building AI-specific CI/CD pipelines that effectively bridge these gaps. Through empirical analysis of successful implementations, we demonstrate how specialized pipeline architectures incorporating automated testing, intelligent resource allocation, and continuous monitoring can reduce deployment incidents by 37% while improving model reliability by 42%. Our findings show that organizations adopting these practices achieve 65% higher success rates in production deployments and reduce operational overhead by 41%. The proposed approach provides a practical roadmap for organizations seeking to streamline their AI deployment processes while maintaining robust security and performance standards
The Future of PLM: Industry 4.0 Technologies and the Connected Product Lifecycle Management
No full textThe convergence of Industry 4.0 technologies and Product Lifecycle Management (PLM) is revolutionizing how organizations manage product innovation, development, and maintenance. The transformation from traditional PLM systems to intelligent, connected platforms has enabled data-driven decision-making and agile manufacturing processes. Through the integration of IoT, digital twins, artificial intelligence, and machine learning, organizations have achieved significant improvements in operational efficiency, product quality, and customer satisfaction. The evolution extends across the entire value chain, from product development to manufacturing operations, while addressing implementation challenges through technical and organizational solutions. As manufacturing complexity grows, PLM systems continue to adapt, incorporating emerging technologies like blockchain and extended reality, while emphasizing sustainability and digital transformation initiatives
AI-Powered Access Governance: Automating Risk-Based Identity in Enterprise Cloud
No full textIdentity management stands at the forefront of modern cybersecurity challenges, particularly as organizations navigate increasingly complex cloud environments. This article explores the implementation of artificial intelligence and machine learning technologies to revolutionize access governance in enterprise cloud settings, with a specific focus on telecommunications domains. The article examines how advanced analytics can transform traditional identity management approaches through behavioral analysis, automated provisioning, and dynamic access controls. By investigating the integration capabilities with major Cloud Infrastructure Entitlement Management platforms, this article demonstrates how AI-driven solutions can enhance security posture while maintaining operational efficiency. The article reveals significant improvements in threat detection, compliance management, and privilege abuse prevention through the implementation of zero-standing privilege models and automated remediation workflows
Demystifying Data Pipelines: A Beginner\u27s Guide to ML Data Infrastructure
No full textData pipelines constitute the foundation of machine learning systems, serving as the critical infrastructure that transforms raw data into valuable insights. This article demystifies the complex world of ML data pipelines for newcomers, breaking down essential components and considerations through accessible concepts and practical guidance. The article begins with fundamental pipeline architecture, examining the journey data takes from collection through transformation to model delivery. Key distinctions between ML pipelines and traditional data workflows illuminate the unique requirements of machine learning systems, including feature consistency, reproducibility, versioning complexity, and drift detection capabilities. The ecosystem of specialized tools and frameworks is mapped, highlighting how organizations increasingly adopt dedicated solutions for different pipeline stages. Critical design considerations reveal the importance of balancing competing factors such as quality versus quantity, batch versus streaming processing, scalability needs, monitoring practices, governance requirements, and technical debt management. Throughout, quantitative evidence demonstrates how effective pipeline design directly correlates with model performance, development speed, maintenance costs, and ultimately business outcomes. The comprehensive examination establishes data pipelines not merely as technical plumbing but as strategic assets worthy of thoughtful design and investment
Advancements in Privacy-Preserving Techniques for Patient Data Protection
No full textPrivacy-preserving techniques for patient data protection have emerged as crucial safeguards in an increasingly digitized healthcare landscape. As electronic health records have become ubiquitous, traditional security approaches have proven inadequate against sophisticated cyber threats targeting sensitive medical information. This article examines advanced privacy-enhancing technologies that enable secure computation while maintaining data utility. Homomorphic encryption allows computation on encrypted data without decryption, particularly valuable for sensitive genomic analysis. Federated learning enables collaborative model development across institutions without sharing raw patient data. Secure multi-party computation facilitates joint analysis while keeping individual contributions private, supporting cross-institutional research. Differential privacy provides mathematical guarantees against re-identification in statistical analyses and publications. Despite promising implementations, these technologies face challenges including computational overhead, integration with legacy systems, regulatory uncertainty, and standardization gaps. As quantum computing advances, both threats and opportunities emerge for healthcare privacy. The evolution of these technologies represents a fundamental shift from access restriction to privacy-preserving computation, offering pathways to resolve tensions between data protection and utilization
AI in Audit: Unlocking Deep Analytical-Based Testing
No full textThis article explores the transformative impact of artificial intelligence on the audit profession, documenting a paradigm shift from traditional sampling-based methodologies to comprehensive analytical approaches. As organizations generate unprecedented volumes of financial and operational data across multiple systems, conventional audit approaches face mounting challenges in providing adequate assurance. Artificial intelligence technologies—including machine learning, natural language processing, and computer vision—enable auditors to analyze entire datasets, identify subtle patterns, and detect anomalies with precision and efficiency previously unattainable. The implementation of AI in audit processes enhances risk assessment, fraud detection, continuous monitoring, and predictive capabilities, fundamentally altering how audit evidence is gathered and interpreted. While significant implementation challenges exist, including data quality issues, ethical considerations, and the need for auditor upskilling, organizations that successfully navigate these obstacles can achieve substantial benefits. The article concludes that the future of auditing lies not in AI replacing human auditors but in a collaborative approach that leverages technological capabilities alongside human expertise and judgment
Multi-Cloud and Hybrid Cloud Strategies for Enterprise API Architectures
No full textEnterprise organizations are increasingly adopting multi-cloud and hybrid cloud strategies to enhance operational efficiency, ensure business continuity, and avoid vendor lock-in. This comprehensive article examines the evolution of cloud computing strategies, focusing on implementation challenges, security considerations, and best practices in multi-cloud environments. The article investigates key aspects, including API portability, traffic management, load balancing, and security frameworks across cloud providers. Through extensive research and analysis of industry data, this article demonstrates how organizations can optimize their cloud infrastructure through standardized processes, automation, and strategic planning. The article reveals significant improvements in system reliability, cost optimization, and operational efficiency through the proper implementation of multi-cloud architectures and cloud-agnostic approaches
Digital Citizenship for All: Accessibility Requirements in Public Domain Websites
No full textGovernment website accessibility stands as a cornerstone of inclusive digital governance, enabling all citizens regardless of ability to access essential public services and information. Beyond mere legal compliance with frameworks like Section 508 and WCAG standards, accessibility implementation delivers multifaceted benefits across governmental operations. Technical components including semantic HTML structure, alternative text implementation, keyboard navigation, color contrast considerations, and accessible forms collectively create the foundation for truly inclusive digital experiences. Mobile accessibility has emerged as particularly crucial as citizens increasingly access government services through smartphones and tablets, requiring specialized approaches to touchscreen interfaces and responsive design. The benefits extend far beyond inclusion—accessible government websites demonstrate improved usability for all citizens, substantial cost savings through proactive implementation, enhanced public trust, increased democratic participation, and strengthened information security. As governments continue digital transformation efforts, prioritizing accessibility represents both an ethical imperative and a strategic investment in effective public service delivery
Leveraging Predictive Analytics for Strategic Compensation Forecasting
No full textThis article explores the transformative role of predictive analytics in modern compensation management and forecasting. The article examines how organizations leverage advanced analytics capabilities to enhance their compensation strategies while maintaining market competitiveness. Through a comprehensive analysis of implementation methodologies, the article demonstrates significant improvements in talent retention, employee engagement, and organizational performance through data-driven approaches. The article investigates various aspects, including predictive modeling techniques, time series analysis, multivariate regression models, and machine learning applications in compensation planning. It further explores strategic implementation considerations, highlighting the importance of data quality, model maintenance, and stakeholder engagement in successful analytics deployment. The article reveals substantial enhancements in forecasting accuracy, budget allocation efficiency, and cost management through the integration of advanced analytical capabilities
Natural Language Interfaces - From Queries to Conversations
No full textNatural Language Interfaces (NLIs) represent a transformative shift in human-computer interaction, enabling communication through everyday language rather than requiring users to adapt to rigid computational systems. This article examines the evolution, technological foundations, core capabilities, applications, and social implications of NLIs. The progression from early systems like ELIZA to contemporary large language models has dramatically expanded what is possible in human-machine communication, creating interfaces that are increasingly context-aware, adaptive, and capable of understanding nuanced human intent. These advances have led to widespread implementation across consumer, enterprise, healthcare, and educational domains, delivering significant improvements in accessibility, efficiency, and task completion. However, the proliferation of NLIs also introduces important ethical considerations regarding digital divides, privacy implications, questions of agency, and potential cognitive impacts. By synthesizing extensive data across these dimensions, this article provides a comprehensive assessment of how conversational interfaces are reshaping expectations around technology accessibility and use, potentially democratizing access to computational capabilities while also introducing new challenges that require thoughtful consideration as these systems become increasingly embedded in daily life