Category Archives: Uncategorized

Authors: Yogeesh G Gowda, Vishwas G V, Santosh Patil, Pawan P R, Kumaraswamy S

Abstract: The integration of blockchain technology and smart contracts represents a transformative advancement in auction systems, offering efficient, transparent, and secure decentralized platforms. This project leverages these technologies to facilitate a range of auction functionalities, from placing bids and managing the auction lifecycle to ensuring fair outcomes without reliance on intermediaries. By offering enhanced transparency and immutability of records, decentralized auctions built on blockchain have the potential to reduce administrative burdens, improve trust among participants, and ensure continuity of the auction process. However, challenges such as scalability, gas costs, and regulatory considerations necessitate robust design and compliance mechanisms. This paper explores the capabilities, benefits, and limitations of this decentralized auction system, emphasizing its potential to revolutionize auction processes while addressing critical gaps in traditional centralized models.

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Published by: vikaspatanker

Authors: Noor jahan Fatima, Dr sarabjit kaur

Abstract: This study explores the structural characteristics of selected deformed nuclei using theoretical frameworks, focusing on their shapes, energy levels, and quadrupole moments. Nuclear deformation results from the complex interplay between shell effects and the strong nuclear force, causing deviations from spherical symmetry. Advanced models, including the Nilsson model, Hartree-Fock-Bogoliubov (HFB) theory, and collective models, are employed to examine the influence of deformation on nuclear structure. The key findings emphasize the role of deformation in shaping rotational spectra and intrinsic quadrupole moments, with significant results for nuclei such as 152Sm, 238U, and 240Pu. Calculations of quadrupole deformation parameters and energy levels show strong agreement with experimental data, validating the theoretical approaches. The study also investigates the stabilization of heavy nuclei through deformation, which redistributes charge density and mitigates Coulomb repulsion. These findings have important applications in nuclear astrophysics, particularly in the rapid neutron capture process (r-process), as well as in nuclear technology, where insights into deformed nuclei contribute to isotope development and reactor design. A deeper understanding of deformed nuclei in this research advances both fundamental nuclear physics and practical applications

DOI: http://doi.org/10.5281/zenodo.16941086

Published by: vikaspatanker

Authors: Suresh kumar, Dr Vandana, Shashikant Sheoran, Vandana Mahlawat

Abstract: This study explores the structural characteristics of selected deformed nuclei using theoretical frameworks, focusing on their shapes, energy levels, and quadrupole moments. Nuclear deformation results from the complex interplay between shell effects and the strong nuclear force, causing deviations from spherical symmetry. Advanced models, including the Nilsson model, Hartree-Fock-Bogoliubov (HFB) theory, and collective models, are employed to examine the influence of deformation on nuclear structure. The key findings emphasize the role of deformation in shaping rotational spectra and intrinsic quadrupole moments, with significant results for nuclei such as 152Sm, 238U, and 240Pu. Calculations of quadrupole deformation parameters and energy levels show strong agreement with experimental data, validating the theoretical approaches. The study also investigates the stabilization of heavy nuclei through deformation, which redistributes charge density and mitigates Coulomb repulsion. These findings have important applications in nuclear astrophysics, particularly in the rapid neutron capture process (r-process), as well as in nuclear technology, where insights into deformed nuclei contribute to isotope development and reactor design. A deeper understanding of deformed nuclei in this research advances both fundamental nuclear physics and practical applications.

DOI: http://doi.org/10.5281/zenodo.16940701

Published by: vikaspatanker

Authors: Suresh kumar, Dr Vandana

Abstract: Deformed nuclei, characterized by deviations from spherical symmetry, exhibit unique structural properties that are critical to understanding nuclear stability, reaction dynamics, and excitation phenomena. This theoretical study investigates the structural properties of selected deformed nuclei using advanced nuclear models and computational approaches. Employing Density Functional Theory (DFT) with Skyrme and Gogny interactions, alongside Hartree-Fock-Bogoliubov (HFB) calculations, the research analyses deformation effects on nuclear binding energy, charge distributions, and level densities. Transitional and neutron-rich nuclei are emphasized to explore the evolution of deformation, triaxiality, and nuclear softness. The results reveal significant impacts of deformation on nuclear moment of inertia and energy spectra, particularly in rare-earth and actinide regions. The inclusion of triaxiality further enhances the accuracy of predictions for level densities and excitation spectra. Comparisons with experimental data from gamma-ray spectroscopy and Coulomb excitation validate the robustness of the theoretical frameworks employed. This study addresses key gaps in understanding nuclear deformation, particularly for isotopic chains near the neutron drip line and transitional regions. The findings provide critical insights for refining existing nuclear models and guiding future experimental investigations. Furthermore, this research highlights the importance of incorporating pairing correlations and deformation effects to predict properties of nuclei far from stability. The study contributes to the broader understanding of nuclear structure and its applications in nuclear energy, astrophysics, and particle physics. These findings underscore the role of theoretical models in complementing experimental efforts and advancing nuclear physics research.

DOI: http://doi.org/10.5281/zenodo.16940412

 

Published by: vikaspatanker

Authors: Vengadeshwaran B

 

 

Abstract: Conventional keyword-based search systems lack contextual understanding and often return irrelevant or incomplete results. In enterprise environments, this becomes a bottleneck when users attempt to extract precise information from large and complex documents. This paper introduces AskMyDoc, a scalable project management tool and smart document querying system that leverages semantic search, large language models (LLMs), and vector databases. Unlike traditional SQL databases susceptible to human errors during updates, AskMyDoc processes and indexes documents using embedding techniques and retrieves answers using generative AI, thereby ensuring accuracy, speed, and consistency. The system is built with LangChain, FAISS, Sentence Transformers, and OpenAI's GPT models, supporting real-time natural language querying even across gigabyte-scale documents.

Published by: vikaspatanker

Authors: Santhosh SG, Sampath Kumar

Abstract: As digital data rapidly increases, there will be a corresponding depletion of textural data for various uses, as the number of image-based documents with usable text continues to rise. But too often, this is complicated by the obstacles of storing images with distortion, algorithmic font types, misaligned printed text, random text orientation and other forms of noise. For considering image-based documents with bilingual documents like government forms, educational transcripts, medical records, and business receipts with multiple integrated languages across a single document, become more complex and piled on these particular layers of challenges. The research paper "Optimizing Evaluation Metrics with PSNR, AMBE, and F1 Score to ensure Consistency in Document Improvement and Consistency in Classification Accuracy" is intended to examine some of the issues that both have been examined and expressed. This effort confronted the problems this work has discussed and expressed through consistent and reliable classification accuracy; AMBE determines the interference with the brightness distribution; and PSNR applies a clarity "score" to determine the clarity of an image. Combined, the three metrics present a possible framework to enhance the reliability and consistency of document processing system.

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Published by: vikaspatanker

Authors: Ravichandra Mulpuri

Abstract: This article examines the transformative potential of integrating Large Language Models (LLMs) into Salesforce to create conversational enterprises capable of dynamic decisioning. It explores how natural language interfaces and AI-driven intelligence reshape CRM systems from passive repositories of customer data into active engines of contextual insights and guided action. The discussion highlights the evolution of Salesforce toward an augmented ecosystem that democratizes access to analytics, accelerates decision-making, and enhances enterprise agility. Key use cases across sales, service, marketing, and leadership demonstrate the breadth of impact, while architectural principles emphasize integration, governance, security, scalability, and user experience as foundational requirements. Challenges such as data quality, AI reliability, compliance, and cultural adoption are also addressed, underscoring the need for careful strategy and governance. Looking ahead, the article outlines future directions including autonomous decision support, multimodal integration, interoperability across federated cloud environments, and the emergence of new professional roles.

DOI: http://doi.org/10.5281/zenodo.16925791

Published by: vikaspatanker

Authors: Sambasiva Rao Madamanchi

Abstract: This article examines the orchestration of Tomcat, JBoss, and WebSphere across hybrid Unix/Linux infrastructures, emphasizing the role of automation in creating resilient middleware frameworks. It explores the challenges of heterogeneous environments, including fragmentation, manual administration, compliance demands, and security risks. The discussion highlights how governance can be embedded into middleware provisioning, patching, and monitoring through tools such as Puppet, Chef, Ansible, Nagios, Zabbix, and Tripwire. Case studies from finance, telecommunications, healthcare, and government demonstrate how automated middleware governance improves resilience, compliance, and efficiency in mission-critical operations. The article also addresses challenges such as configuration drift, cultural resistance, and scalability while offering best practices for mitigation. Looking ahead, it identifies future directions including AI-driven predictive monitoring, cloud-native middleware orchestration, continuous compliance, and sustainability integra This article examines the transformation of enterprise governance from a compliance-centric model to a cognition-driven framework enabled by artificial intelligence. It highlights the limitations of traditional governance approaches, which focus on static audits and regulatory adherence, and explores how AI can enhance oversight by providing real-time anomaly detection, predictive compliance, and dynamic policy enforcement. Linux and Solaris, long recognized for their robust security and auditing capabilities, are positioned as ideal platforms for building AI-augmented governance systems that integrate intelligence, automation, and transparency. The discussion presents an architectural blueprint that layers AI engines and automation workflows over existing governance features, ensuring adaptability across hybrid IT environments. Challenges such as AI bias, ethical considerations, and data privacy are addressed alongside practical applications in finance, healthcare, telecommunications, and the public sector. Beyond technical benefits, the article demonstrates the strategic value of cognitive governance in reducing compliance costs, enhancing resilience, and fostering innovation.

DOI: http://doi.org/10.5281/zenodo.16925705

Published by: vikaspatanker

Authors: Sambasiva Rao Madamanchi

Abstract: This article examines the orchestration of Tomcat, JBoss, and WebSphere across hybrid Unix/Linux infrastructures, emphasizing the role of automation in creating resilient middleware frameworks. It explores the challenges of heterogeneous environments, including fragmentation, manual administration, compliance demands, and security risks. The discussion highlights how governance can be embedded into middleware provisioning, patching, and monitoring through tools such as Puppet, Chef, Ansible, Nagios, Zabbix, and Tripwire. Case studies from finance, telecommunications, healthcare, and government demonstrate how automated middleware governance improves resilience, compliance, and efficiency in mission-critical operations. The article also addresses challenges such as configuration drift, cultural resistance, and scalability while offering best practices for mitigation. Looking ahead, it identifies future directions including AI-driven predictive monitoring, cloud-native middleware orchestration, continuous compliance, and sustainability integra This article examines the transformation of enterprise governance from a compliance-centric model to a cognition-driven framework enabled by artificial intelligence. It highlights the limitations of traditional governance approaches, which focus on static audits and regulatory adherence, and explores how AI can enhance oversight by providing real-time anomaly detection, predictive compliance, and dynamic policy enforcement. Linux and Solaris, long recognized for their robust security and auditing capabilities, are positioned as ideal platforms for building AI-augmented governance systems that integrate intelligence, automation, and transparency. The discussion presents an architectural blueprint that layers AI engines and automation workflows over existing governance features, ensuring adaptability across hybrid IT environments. Challenges such as AI bias, ethical considerations, and data privacy are addressed alongside practical applications in finance, healthcare, telecommunications, and the public sector. Beyond technical benefits, the article demonstrates the strategic value of cognitive governance in reducing compliance costs, enhancing resilience, and fostering innovation.

DOI: http://doi.org/10.5281/zenodo.16925705

Published by: vikaspatanker

Authors: Veerendra Battula

Abstract: This article examines the orchestration of Tomcat, JBoss, and WebSphere across hybrid Unix/Linux infrastructures, emphasizing the role of automation in creating resilient middleware frameworks. It explores the challenges of heterogeneous environments, including fragmentation, manual administration, compliance demands, and security risks. The discussion highlights how governance can be embedded into middleware provisioning, patching, and monitoring through tools such as Puppet, Chef, Ansible, Nagios, Zabbix, and Tripwire. Case studies from finance, telecommunications, healthcare, and government demonstrate how automated middleware governance improves resilience, compliance, and efficiency in mission-critical operations. The article also addresses challenges such as configuration drift, cultural resistance, and scalability while offering best practices for mitigation. Looking ahead, it identifies future directions including AI-driven predictive monitoring, cloud-native middleware orchestration, continuous compliance, and sustainability integration.

DOI: http://doi.org/10.5281/zenodo.16925647

Published by: vikaspatanker