Authors: Y C Kamala

Abstract: The century between the Battle of Plassey (1757) and the founding of the universities of Calcutta, Bombay and Madras (1857) is usually treated as a prehistory of modern science in India, a period of surveys and collections before the age of the laboratory. This paper argues that these years laid down institutional foundations that shaped how physics would later be taught and practised in the subcontinent. Drawing on published educational records and the historiography of colonial science, it examines three clusters of institutions: the state’s instruments of measurement and communication (the observatory, the Great Trigonometrical Survey and the electric telegraph); the policy debates that decided whether, in what language and for whom natural philosophy would be taught; and the colleges and translation bodies through which Indian students first met mechanics, optics and higher mathematics. The analysis shows that the physical sciences entered colonial India chiefly as practice in the service of the state, in the form of precision measurement, geodesy, meteorology and telegraphy, while formal teaching of natural philosophy remained thin, uneven and dependent on Indian initiative. The examining universities of 1857 consolidated this pattern by rewarding the reproduction of knowledge rather than its creation. The paper concludes that the later struggle to build research-led physics in India was, in large part, a struggle against the institutional settlement of this first colonial century

DOI: https://doi.org/10.5281/zenodo.23472477

Published by: vikaspatanker

Authors: Prabal Kumar Joshi

Abstract: IoT (internet of things) is defined as a worldwide framework for information world, which provides advanced services by connecting physical and virtual things through information technology and adoptable communication available in the evolution process. IoT is just applied to overcome the concerns related to safety. Sharing information among different devices can affect the private information of users. Therefore, a proper approach mechanism is required to prevent the risk of malicious and vulnerable failures. Multi-services IoT is vulnerable to many types of malicious attacks. Trust management provides a potential solution for safety issues of distributed networks. In this article, an algorithm is designed in order to calculate trust, which does not calculate the amount of trust for all neighbors and just calculates it for suspicious neighbors located in the list of suspicious nodes. Subsequently, energy consumption in comparison to the approach of basis article has so much decrease.

DOI: http://doi.org/10.5281/zenodo.17034568

Published by: vikaspatanker

Authors: Hema Latha Boddupally

Abstract: Adaptive User Interfaces (AUIs) have become increasingly essential as modern software applications are expected to deliver seamless, intuitive, and personalized experiences across a broad spectrum of devices, screen dimensions, accessibility needs, and interaction contexts. With users frequently transitioning between desktops, tablets, mobile phones, and other emerging platforms, traditional fixed or solely responsive design approaches often fall short in addressing deeper adaptive requirements such as behavior-driven adjustments, contextual awareness, and user-specific personalization. This paper presents a hybrid model for AUI development that integrates ASP.NET MVC’s robust server-side rendering pipeline with React flexible, component-based client-side architecture, enabling interfaces that not only adapt visually but also evolve functionally based on user roles, preferences, device capabilities, and real-time interaction patterns. By leveraging server-side logic for initial content shaping and client-side React components for dynamic rendering and state-driven updates, the proposed model supports fine-grained adaptation, modular UI evolution, and scalable interface personalization. Building on established concepts in responsive design, adaptive graphical interfaces, and context-aware interaction models, the study outlines key architectural strategies, design principles, and implementation techniques that facilitate the development of maintainable, high-performance AUI systems. Furthermore, the paper examines practical challenges such as context modeling, synchronization between server and client layers, managing diverse user scenarios, and optimizing rendering performance, ultimately demonstrating how the synergy of MVC and React provides a powerful foundation for creating intelligent, user-centered adaptive interfaces capable of meeting the demands of modern digital ecosystems.

DOI: http://doi.org/10.5281/zenodo.18042587

Published by: vikaspatanker

Authors: Y C Kamala

Abstract: In 1924 Satyendra Nath Bose, then at the University of Dacca, derived Planck’s radiation law without appeal to classical electrodynamics. He divided the phase space of light quanta into cells of volume h³ and counted the ways in which quanta could be distributed among them. Einstein translated the paper and extended its method to material particles, and the result became Bose–Einstein statistics. This paper re-reads Bose’s derivation as an exercise in combinatorics. It shows that Bose’s own counting, in terms of the numbers of cells that contain a given number of quanta, is exactly equivalent to the “stars and bars” count of indistinguishable objects in distinguishable boxes, and it proves the equivalence with a generating function. Exact enumerations confirm the equivalence for small systems and show how sharply it departs from the count for distinguishable quanta. Numerical maximisation of Bose’s weight recovers the geometric distribution of quanta per cell that yields Planck’s law, and exact finite-system calculations show the convergence of the single-cell distribution and of the fluctuations to their thermodynamic limits, including Einstein’s fluctuation formula with its particle and wave terms. The paper relates Bose’s counting to Planck’s combinatorial argument of 1900, to Natanson’s analysis of 1911 and to the Ehrenfest–Kamerlingh Onnes derivation of 1915, and argues that the novelty of Bose’s work lay less in a new formula than in a new choice of the objects to be counted.

DOI: https://doi.org/10.5281/zenodo.23473406

Published by: vikaspatanker

Authors: Madhusudan Rao Karri

Abstract: The rapid growth of healthcare information generated from electronic health records, clinical applications, laboratory systems, medical devices, insurance platforms, and external healthcare services has created significant challenges in managing heterogeneous and distributed data environments. Differences in data structures, formats, semantics, metadata definitions, and governance policies can reduce data interoperability, quality, consistency, and analytical usability. This research proposes a Unified Metadata-Driven Framework for Healthcare Data Modeling, Integration, and Governance to provide a systematic approach for managing enterprise healthcare data throughout its lifecycle. The proposed framework uses metadata as a central mechanism for describing data structures, business definitions, relationships, lineage, quality rules, integration mappings, and governance policies. It integrates metadata-driven data modeling with standardized data integration processes to support consistent transformation and exchange of healthcare information across heterogeneous systems. The framework also incorporates governance capabilities for data quality, security, privacy, access control, lineage, ownership, and regulatory compliance. A layered architecture comprising metadata management, data modeling, integration, governance, quality management, and monitoring components is proposed to improve scalability and operational consistency. The framework can further support automated schema mapping, metadata validation, lineage tracking, and policy enforcement, thereby reducing manual intervention and improving data management efficiency. Evaluation of the framework can be performed using measures such as integration efficiency, data quality, metadata completeness, transformation accuracy, processing time, lineage coverage, and governance compliance. The proposed approach provides a unified foundation for building scalable, interoperable, and governed healthcare data environments capable of supporting analytics, reporting, clinical decision-making, and enterprise data management.

DOI: https://doi.org/10.5281/zenodo.23391272

Published by: vikaspatanker

Authors: Srujana Parepalli

Abstract: Data quality has emerged as a critical challenge in modern enterprise information systems, as rapid growth in data volume, velocity, and heterogeneity amplifies issues such as inconsistency, incompleteness, redundancy, and semantic ambiguity across distributed platforms. Traditional rule-based data validation techniques, including integrity constraints and handcrafted business rules, offer strong interpretability and auditability but often fail to scale or adapt in dynamic environments where schemas, data sources, and usage patterns continuously evolve. In contrast, purely statistical and machine-learning driven approaches excel at identifying latent patterns and anomalies in large datasets but frequently suffer from limited explainability, making governance, regulatory compliance, and root-cause analysis difficult. This article presents an integrated framework for Intelligent Data Quality Engineering that synergistically combines constraint-based validation, probabilistic modeling, and AI-driven anomaly detection to overcome these limitations. By grounding adaptive learning models in well-established research on conditional functional dependencies, probabilistic databases, and entity resolution, the framework enables predictive detection of quality issues and supports self-healing data pipelines capable of learning from historical errors and feedback. This hybrid approach effectively bridges deterministic data rules with adaptive intelligence, delivering scalable, transparent, and governance-aligned data quality solutions suitable for enterprise-grade analytics and decision systems.

DOI: http://doi.org/10.5281/zenodo.17987694

Published by: vikaspatanker

Authors: Kranthi Kumar Routhu

Abstract: The rapid evolution of information technology over the past two decades has fundamentally transformed the way organizations manage their human capital. Human Resource (HR) systems, once confined to on-premise infrastructures, have steadily progressed toward cloud-based Human Capital Management (HCM) ecosystems that integrate data, analytics, and user experience into a unified digital platform. This transformation reflects not merely a technological shift, but a strategic reorientation of HR’s role from administrative recordkeeping to value-driven talent management. Traditional on-premise HR systems such as Oracle E-Business Suite and PeopleSoft provided strong control, customization, and data security but required heavy maintenance, complex upgrades, and significant capital expenditure. In contrast, cloud-based HCM platforms introduced a service-oriented model that offers agility, scalability, and continuous innovation through subscription-based delivery. Oracle’s HCM Cloud represents a culmination of this digital evolution, combining the reliability and maturity of legacy systems with the adaptability of cloud-native architecture. The purpose of this study is to examine how this migration reshaped enterprise HR strategy and infrastructure. It explores the transformation journey from on-premise deployment to Oracle Cloud HCM, focusing on the organizational, technical, and regulatory challenges encountered during migration. Furthermore, it evaluates the strategic opportunities created through the adoption of Oracle’s cloud-driven HR ecosystem, particularly in enhancing workforce analytics, compliance automation, and employee engagement. Through this lens, the study demonstrates how Oracle’s Cloud HCM framework serves as both a technological and organizational enabler of modern HR excellence.

DOI: https://doi.org/10.5281/zenodo.17669776

Published by: vikaspatanker

Authors: Y C Kamala

Abstract: In 1920 Meghnad Saha, a young lecturer at the University College of Science, Calcutta, published a theory of thermal ionisation that explained the sequence of stellar spectra as a sequence of temperatures. The Saha equation became a foundation of astrophysics and later of plasma physics, and it marked the entry of Indian science into theoretical astrophysics. This paper revisits the equation in its historical and physical context. It sets out the thermodynamic argument by which Saha obtained it, shows that the numerical form he published is consistent with the modern statistical-mechanical expression, and reproduces with the Saha and Boltzmann equations the calculations that made the theory persuasive: the degree of ionisation of hydrogen as a function of temperature and pressure, the maximum strength of the Balmer lines near 10 000 K, the successive ionisation of calcium, and the progression of line-forming populations of calcium, hydrogen and helium that underlies the spectral sequence from M to O stars. The pressure dependence of ionisation, which explains the differences between giant and dwarf stars, is also quantified. The paper then discusses how the theory was taken up by Fowler, Milne and Payne, how it relates to the earlier work of Eggert, and what it meant for science in India, where it was produced without access to a telescope.

DOI: https://doi.org/10.5281/zenodo.23474513

Published by: vikaspatanker

Authors: Harish Govinda Gowda

Abstract: Containers have become the backbone of modern enterprise IT, providing portability, agility, and consistency across environments. However, scaling containers across hybrid and multi-cloud infrastructures requires more than orchestration—it demands governance, security, and resilience. This article explores how Kubernetes, Helm, and OpenShift can be harmonized to achieve container intelligence at scale. Kubernetes provides orchestration, Helm simplifies application deployment and lifecycle management, and OpenShift delivers governance, compliance, and enterprise-grade security. By layering these tools together, organizations can create resilient, scalable ecosystems that balance agility with trust. The discussion highlights key challenges in scaling containers, the role of each tool, and best practices for enterprise adoption, emphasizing that true resilience comes from harmonizing orchestration, management, and governance into one cohesive framework.

DOI: http://doi.org/10.5281/zenodo.16992539

Published by: vikaspatanker