2.introduction to amazon web services
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This document introduces Amazon Web Services (AWS) and cloud computing. It discusses that cloud computing provides on-demand availability of computer resources like data storage and computing power over the internet without direct user management. Key characteristics of cloud computing include on-demand self-service, broad network access, multi-tenancy, rapid elasticity and scalability, and measured service. Benefits of AWS include its global infrastructure and management interface.
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Modeling the Influence of Environmental Factors on Concrete Evaporation RateJournal of Soft Computing in Civil Engineering Newly poured concrete opposing hot and windy conditions is considerably susceptible to plastic shrinkage cracking. Crack-free concrete structures are essential in ensuring high level of durability and functionality as cracks allow harmful instances or water to penetrate in the concrete resulting in structural damages, e.g. reinforcement corrosion or pressure application on the crack sides due to water freezing effect. Among other factors influencing plastic shrinkage, an important one is the concrete surface humidity evaporation rate. The evaporation rate is currently calculated in practice by using a quite complex Nomograph, a process rather tedious, time consuming and prone to inaccuracies. In response to such limitations, three analytical models for estimating the evaporation rate are developed and evaluated in this paper on the basis of the ACI 305R-10 Nomograph for “Hot Weather Concreting”. In this direction, several methods and techniques are employed including curve fitting via Genetic Algorithm optimization and Artificial Neural Networks techniques. The models are developed and tested upon datasets from two different countries and compared to the results of a previous similar study. The outcomes of this study indicate that such models can effectively re-develop the Nomograph output and estimate the concrete evaporation rate with high accuracy compared to typical curve-fitting statistical models or models from the literature. Among the proposed methods, the optimization via Genetic Algorithms, individually applied at each estimation process step, provides the best fitting result.
22PCOAM16_MACHINE_LEARNING_UNIT_IV_NOTES_with_QB
22PCOAM16_MACHINE_LEARNING_UNIT_IV_NOTES_with_QBGuru Nanak Technical Institutions 22PCOAM16_MACHINE_LEARNING_UNIT_IV_NOTES_with_QB
AI-Powered Data Management and Governance in Retail
AI-Powered Data Management and Governance in RetailIJDKP Artificial intelligence (AI) is transforming the retail industry’s approach to data management and decisionmaking. This journal explores how AI-powered techniques enhance data governance in retail, ensuring data quality, security, and compliance in an era of big data and real-time analytics. We review the current landscape of AI adoption in retail, underscoring the need for robust data governance frameworks to handle the influx of data and support AI initiatives. Drawing on literature and industry examples, we examine established data governance frameworks and how AI technologies (such as machine learning and automation) are augmenting traditional data management practices. Key applications are identified, including AI-driven data quality improvement, automated metadata management, and intelligent data lineage tracking, illustrating how these innovations streamline operations and maintain data integrity. Ethical considerations including customer privacy, bias mitigation, transparency, and regulatory compliance are discussed to address the challenges of deploying AI in data governance responsibly.
A Study of Bank Line Shifting of the Selected Reach of Jamuna River Using Mul...
A Study of Bank Line Shifting of the Selected Reach of Jamuna River Using Mul...Journal of Soft Computing in Civil Engineering
Modeling the Influence of Environmental Factors on Concrete Evaporation Rate
Modeling the Influence of Environmental Factors on Concrete Evaporation RateJournal of Soft Computing in Civil Engineering
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