Faculty Publications
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Publications by NITK Faculty
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Item Enhancing Data Quality in Hybrid Cloud Architectures(Institute of Electrical and Electronics Engineers Inc., 2024) Fernandes, G.H.; Divakarla, U.; Chandrasekaran, K.The emergence of the hybrid cloud model has completely changed how businesses handle, store and use their data. A common option for businesses looking to combine the benefits of cloud services and on-premises infrastructure is the hybrid cloud strategy. However, because of the complexity of data management across contexts and the integration of disparate systems, this paradigm presents serious hurdles to preserving data quality. Since data is the primary source for many important business decisions, ensuring data quality - which includes correctness, consistency, completeness, security, and reliability - remains a top priority. This study presents a unique method that makes use of cloud computing and machine learning (ML) algorithms to improve data quality in hybrid cloud environments. The detection, prevention and remediation of data quality issues by integrating state-of-the-art machine learning techniques into hybrid cloud systems is thoroughly examined in this study. The suggested architecture seeks to deliver more dependable and trustworthy data for decision-making processes by offering real-time monitoring, analysis and quality enhancement of data throughout the hybrid infrastructure. The efficacy of methodology in tackling data quality issues in hybrid cloud settings is illustrated using experiments and case studies. © 2024 IEEE.Item Cloud Computing Enabled Big Multi-Omics Data Analytics(SAGE Publications Inc., 2021) Koppad, S.; B, A.; Gkoutos, G.V.; Acharjee, A.High-throughput experiments enable researchers to explore complex multifactorial diseases through large-scale analysis of omics data. Challenges for such high-dimensional data sets include storage, analyses, and sharing. Recent innovations in computational technologies and approaches, especially in cloud computing, offer a promising, low-cost, and highly flexible solution in the bioinformatics domain. Cloud computing is rapidly proving increasingly useful in molecular modeling, omics data analytics (eg, RNA sequencing, metabolomics, or proteomics data sets), and for the integration, analysis, and interpretation of phenotypic data. We review the adoption of advanced cloud-based and big data technologies for processing and analyzing omics data and provide insights into state-of-the-art cloud bioinformatics applications. © The Author(s) 2021.Item The IproK ontology: a unified approach to managing construction project information(Taylor and Francis Ltd., 2025) Kone, V.; Mahesh, G.In the domain of construction project management, holistic decision-making and integrated project controls are paramount for success. However, integrating the vast spectrum of project data is challenging due to disparate software systems and data fragmentation, which leads to information silos and hinders semantic interoperability. An ontology-based framework presents a promising solution for creating a unified and machine-interpretable representation of this complex information. This research paper details the development, validation, and publication of the IproK ontology, a novel framework that provides deep, simultaneous integration of three critical project management domains: schedule, cost, and resources. A multi-faceted evaluation confirmed its technical soundness, conceptual validity according to domain experts, and practical utility by successfully answering all predefined Competency Questions (CQs) essential for integrated project control. IproK provides a validated semantic backbone for creating integrated project Knowledge Graphs, paving the way for next-generation, data-driven decision support systems and more intelligent construction project delivery. © 2025 Informa UK Limited, trading as Taylor & Francis Group.