Al-Kindi Center for Research and Development (KCRD) (E-Journals)
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6248 research outputs found
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Optimizing CDS Views: Best Practices and Performance Enhancements
No full textThis comprehensive technical article explores optimization strategies for ABAP Core Data Services (CDS) views within SAP environments. Beginning with an introduction to CDS and its implementation of the Code-to-Data paradigm, the article examines how this architectural approach shifts processing from application to database layers, resulting in significant performance improvements. The document presents detailed best practices for optimizing CDS views, including efficient join strategies, filter optimization techniques, effective use of annotations, simplification of complex logical expressions, union operation enhancements, and authorization handling recommendations. It further explores ABAP code efficiency when working with CDS views, emphasizing the importance of proper abstraction through DDL names, selective attribute retrieval, effective OData query implementation, and shifting calculations to the data layer. The article concludes with user interface performance enhancement strategies, covering library and dependency loading optimization, asynchronous processing implementation, user experience improvements through engaging elements, CDN utilization, and preloading techniques for faster rendering. Throughout, the document references SAP technical documentation, community discussions, and performance studies to substantiate recommended approaches
Telecommunications Solutions for E-commerce: Enhancing Customer Engagement and Sales
No full textThe integration of telecommunications solutions into e-commerce platforms has revolutionized customer engagement and sales strategies in the digital marketplace. Modern contact centers leveraging advanced technologies enable seamless omnichannel communication, personalized customer experiences, and efficient service delivery. The convergence of artificial intelligence, machine learning, and social media integration has transformed how businesses interact with customers, manage relationships, and optimize operations. Implementation of these solutions, supported by strategic planning and technical considerations, has led to enhanced customer satisfaction, improved operational efficiency, and increased revenue growth across the e-commerce landscape
Securing the Modern Healthcare Ecosystem: Endpoint Management for Medical Environments
No full textThis comprehensive article explores the evolving landscape of endpoint management in healthcare environments, examining how Unified Endpoint Management (UEM) solutions address the unique security challenges faced by medical institutions. The article investigates the complex balancing act healthcare organizations must perform between maintaining robust security controls and enabling efficient clinical workflows across thousands of diverse endpoints. It details how cloud-based UEM platforms provide centralized device registration, automated compliance verification, and identity-driven access control to protect sensitive patient information while supporting clinical mobility. The article includes real-world impacts of UEM implementation, the accelerated digital transformation catalyzed by the COVID-19 pandemic, and forward-looking trends in healthcare cybersecurity. By highlighting the strategic importance of comprehensive endpoint management in an era of expanding attack surfaces and increasingly sophisticated threats, this article offers valuable insights for healthcare IT leaders navigating the intersection of technology, security, and patient care in an increasingly digitized healthcare ecosystem
Advances in Personalized Investment Advisory through Reinforcement Learning: A Technical Review
No full textReinforcement learning (RL) represents a transformative technology in personalized investment advisory services, addressing fundamental limitations of traditional static approaches. This article explores the application of diverse RL frameworks to financial decision-making, from contextual multi-armed bandits for tactical allocations to full Markov Decision Processes for long-term planning. The integration of sophisticated state representations, multi-objective reward functions, and offline learning methodologies enables systems that adapt to individual investor behaviors while maintaining appropriate risk controls. Technical implementations demonstrate measurable improvements in risk-adjusted returns, behavioral alignment, and client retention across various market conditions. Key innovations include artificial potential field representations, privacy-preserving federated architectures, uncertainty-aware distributional modeling, and potential-based reward shaping techniques that accelerate learning while preserving optimality guarantees. As these systems evolve, they promise to democratize access to sophisticated financial guidance by reducing minimum viable account sizes while maintaining service quality, extending professional advisory capabilities to broader populations with diverse financial needs
Harnessing AI for Dynamic Real-Time Network Optimization
No full textArtificial intelligence is revolutionizing network management by enabling dynamic real-time optimization to address the unprecedented demands faced by modern digital infrastructure. As global traffic volumes surge and latency-sensitive applications proliferate, traditional reactive frameworks to network management prove increasingly inadequate. This article explores the transformative potential of AI-driven systems that continuously analyze telemetry data and make preemptive adjustments to maintain optimal network performance. The technical foundations of these systems include comprehensive data collection frameworks, sophisticated AI algorithms for traffic analysis, and robust decision-making frameworks that operate within strict time constraints. A systematic implementation framework outlines the infrastructure requirements, phased deployment method, and operational integration considerations essential for successful adoption. Despite promising results, organizations face technical hurdles related to data quality and computational requirements, alongside organizational barriers including skills gaps and resistance to automation. Case studies across cloud providers, telecommunications carriers, and financial institutions demonstrate substantial improvements in latency, throughput, and fault recovery times, validating the business value of these implementations
Predictive Analytics for Equipment Failure: Implementation and Outcomes of the Equipment Predisposed Tool
No full textThis article presents a comprehensive investigation of the Equipment Predisposed Tool (EPT), a predictive analytics system designed to forecast equipment failures in industrial environments. It examines how advanced data analytics and machine learning techniques can transform maintenance operations from reactive to proactive paradigms. It details the data infrastructure, analytical methods, system architecture, and implementation strategies that underpin successful predictive maintenance initiatives. The article analyzes how the integration of sensor data, operational metrics, maintenance records, and environmental information can provide early detection of potential failures. It further explores various analytical techniques including time series analysis, machine learning classification, and reliability engineering models that collectively enable accurate prediction. Additionally, the analysis documents the operational benefits, financial returns, and key insights gained from the implementation while identifying future development directions in areas such as deep learning, digital twins, and prescriptive analytics
Orchestrating the Chaos: Scalable Event-Driven Architectures for Distributed Ride-Sharing Platforms in Multi-Region Cloud Environments
No full textThis article presents a comprehensive framework for event-driven architectural patterns that enable global ride-sharing platforms to operate at scale across distributed cloud environments. Loose coupling between services, asynchronous communication, and regional event propagation strategies contribute to systems capable of handling continuous streams of ride requests, driver location updates, and payment transactions. The proposed classification system for events by criticality and regional affinity enables intelligent routing and processing decisions. Properly implemented event-driven architectures significantly enhance system scalability during demand surges while maintaining operational resilience through service isolation and regional redundancy. A detailed case study of a production ride-sharing platform identifies key implementation challenges including eventual consistency management, regional data sovereignty, and observability in distributed environments. The work provides both theoretical foundations and practical guidance for engineers designing next-generation transportation systems and other high-volume, geographically distributed applications requiring real-time event coordination
Cloud-Driven Financial Reconciliation for Insurers: Overcoming Data Complexity
No full textCloud-driven financial reconciliation represents a transformative opportunity for insurance organizations facing increasingly complex data environments across policy, claims, and billing systems. The fragmented nature of insurance financial ecosystems, characterized by disparate systems and siloed processes, creates persistent reconciliation challenges that impact operational efficiency, regulatory compliance, and strategic decision-making. Legacy reconciliation approaches typically lack standardization and struggle to accommodate growing product complexity and expanding distribution channels. Cloud-based reconciliation platforms leverage multi-layered service models and advanced technologies including AI-driven matching algorithms, machine learning techniques, and rule-based validation systems to address these challenges. These solutions enable transformation from periodic batch reconciliation to continuous processing models, fundamentally altering error patterns and financial close cycles. Implementation requires structured frameworks addressing both technical and organizational dimensions, with particular emphasis on change management and readiness assessment. The business impact manifests across multiple dimensions: reduced error rates, accelerated closing processes, enhanced compliance capabilities, and improved financial accuracy. Long-term strategic advantages include scalable operations, enhanced acquisition integration capabilities, and finance transformation from transaction processing to strategic partnership. Cloud reconciliation ultimately enables insurance organizations to achieve operational excellence while redirecting financial resources toward higher-value analytical activities that support strategic initiatives
EFL Lexical Knowledge Depth: Proficiency Level and Order of Acquisition Parameters
No full textThe study at hand attempts to trace the development of three EFL lexical knowledge depth aspects - meaning, synonymy and collocation- across three academic levels- high school, second and fourth-year university. It aims to trace any possible “order of development” for the three linguistic knowledge aspects. The second objective of the study is to determine whether proficiency level affects the development of the three lexical knowledge aspects. The linguistic tasks used for data collection are translation, acceptability judgment and multiple choice. The study has found that the connectivity between L1 and EFL mental lexicons affects the three lexical knowledge aspects and tends to decrease relatively as the academic level of the learners increases. Second, the research has revealed a noticeable “order” of acquisition between the three lexical aspects, though not a very strong one. Such findings are of pivotal importance for materials and syllabus designers as well as for L2/FL teachers
Ibn Tofail University Students’ Attitudes Towards Implementing English as a Medium of Instruction (EMI)
No full textThis study investigates Ibn Tofail Faculty of Science students’ attitudes towards implementing English as a medium of instruction (EMI). This research examines students’ language proficiency, educational backgrounds, and equity issues in a possible shift to EMI. Findings corroborate existing literature indicating strongly positive attitudes towards a possible shift to EMI but highlight disparities in linguistic readiness between public and high school graduates. This study underscores the need for a comprehensive language policy centred around fostering equity to ensure the success of any possible shift to EMI