Daily Archives: August 22, 2025

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

Authors: Rahul Kumar Satbhaiya, Jitendra

 

Abstract: High-rise buildings are particularly susceptible to lateral forces induced by seismic and wind loads, which often govern their overall performance and safety. Conventional reinforced concrete (RC) frames, although effective in carrying vertical loads, lack sufficient stiffness to resist such lateral actions, making them prone to excessive displacement, inter-story drift, and even structural instability. To address these challenges, lateral load resisting elements such as masonry infill walls and steel bracing systems are increasingly incorporated into RC frames to enhance seismic resistance. This paper presents a comparative study on the effectiveness of different lateral load resisting systems in improving the seismic performance of high-rise buildings. The investigation considers three structural configurations: bare frame, masonry infilled frame, and externally braced frame with X-bracing. A 12-story reinforced concrete building model (R+12) with 3 m floor height is analyzed using CSI ETABS software under seismic Zone V conditions and response spectrum analysis for soft soil. Key performance parameters including base shear, lateral displacement, inter-story drift, and moment distribution are evaluated to assess the influence of each system on overall seismic behavior. The results reveal that the inclusion of masonry infill significantly reduces the demands on beams and columns by increasing lateral stiffness and redistributing forces. However, the most notable improvement is observed with the use of external steel bracing, particularly X-braces, which provide superior stability and effectively minimize displacements. Steel-braced frames also demonstrate greater cost-efficiency compared to masonry infill, while ensuring higher ductility and energy dissipation. In comparison, bare frames exhibit the least stability and maximum lateral displacements. Overall, the study confirms that lateral load resisting elements play a crucial role in enhancing the seismic performance of RC frames, with steel bracing emerging as the most effective solution, followed by masonry infill..

DOI: https://doi.org/10.5281/zenodo.16925530

 

Published by: vikaspatanker