Authors: Mr. Aadhi Keerthi P, Mr. Logesh B, Mrs. Chitra B

Abstract: Consumer buying behaviour plays a vital role in the success of the electronic gadgets industry. The increasing use of smartphones, laptops, tablets, smartwatches, and other electronic devices has significantly influenced consumer lifestyles and purchasing patterns. This study titled “A Study on Consumer Buying Behaviour towards Electronic Gadgets with Special Reference to Coimbatore” aims to examine the factors affecting consumer preferences and buying decisions related to electronic gadgets. The study focuses on understanding how factors such as price, brand image, product quality, technological features, advertisements, social media influence, and after-sales service impact consumer purchasing behaviour. Both primary and secondary data are used for the research. Primary data were collected through a structured questionnaire distributed among consumers in Coimbatore city, while secondary data were collected from journals, books, websites, and previous studies. Statistical tools like percentage analysis and ranking methods are applied for data interpretation. The findings indicate that consumers highly prefer branded electronic gadgets with advanced features and reasonable prices. Online reviews, digital marketing, and social influence also affect purchasing decisions. The study concludes that electronic gadget companies should focus on innovation, quality improvement, customer satisfaction, and effective promotional strategies to strengthen their market position and meet changing consumer expectations.

DOI: http://doi.org/10.5281/zenodo.20612956

Published by: vikaspatanker

Authors: Nidhi Singh, Dr Navneet Seth

Abstract: The financial sector is undergoing a profound metamorphosis, driven by the accelerating integration of Artificial Intelligence (AI) into core decision-making processes. This paper investigates the multi-dimensional impact of AI on financial decision-making, encompassing investment analysis, credit risk assessment, fraud detection, financial forecasting, and customer service. Employing a descriptive-quantitative research design with a structured questionnaire administered to 100 respondents comprising banking professionals, financial analysts, investors, and accountants, the study deploys percentage analysis, frequency distribution, mean scoring, and Chi-Square hypothesis testing to derive empirical evidence. Findings reveal that 85% of respondents demonstrate awareness of AI-enabled financial tools, 75% affirm that AI materially elevates decision-making accuracy, and 80% express high satisfaction with AI-powered financial services. The Chi-Square test confirms a statistically significant relationship between AI adoption and financial decision-making effectiveness (χ² = 18.64, p < 0.05). Notwithstanding these benefits, data privacy concerns (35%), cybersecurity vulnerabilities (25%), and elevated implementation costs (20%) constitute critical impediments. The paper concludes that AI is not merely an operational efficiency enhancer but a strategic imperative for modern financial institutions, and advocates for responsible, ethics-driven AI governance frameworks to sustain its transformative potential.

Published by: vikaspatanker

Authors: Alexander Stewart, Elizabeth Watson, Andrew Peterson, Natalie Brooks, Chaitanya Srinivas, Rishi Kumar

Abstract: Modern enterprises rely heavily on complex digital infrastructures, cloud-native applications, distributed networks, and real-time operational systems that generate massive volumes of monitoring data continuously. Traditional monitoring approaches often struggle to identify emerging system failures, operational anomalies, cybersecurity threats, and performance degradation in a timely manner, leading to increased downtime, financial losses, and reduced service reliability. Smart monitoring systems powered by artificial intelligence and intelligent analytics have emerged as advanced solutions for proactive incident prediction and detection in dynamic enterprise environments. This research paper explores the integration of artificial intelligence, machine learning, real-time analytics, and event-driven monitoring architectures to enhance operational visibility and predictive incident management capabilities. The study examines how intelligent monitoring platforms leverage anomaly detection, predictive analytics, behavioral analysis, automated alerting, and cloud-native observability tools to identify potential incidents before they impact business operations. Furthermore, the paper discusses the role of distributed data streaming, automated response systems, infrastructure monitoring, and AI-assisted decision intelligence in improving operational resilience and system reliability. Key challenges including scalability, false-positive reduction, data consistency, cybersecurity protection, and monitoring complexity are also analyzed. Through comprehensive evaluation and industry-oriented insights, the research demonstrates how smart monitoring systems enable proactive incident prevention, intelligent operational management, faster root-cause analysis, and continuous service optimization across modern digital enterprise ecosystems.

DOI: http://doi.org/10.5281/zenodo.20608477

Published by: vikaspatanker

Authors: Alexander Stewart, Elizabeth Watson, Hannah Richardson, Isabella Foster, Chaitanya Srinivas, Rishi Kumar

Abstract: Enterprise risk intelligence has become a critical component of modern digital enterprises due to the increasing complexity of financial transactions, cybersecurity threats, operational uncertainties, and rapidly changing market conditions. Traditional risk management systems often struggle to process large volumes of dynamic data in real time, resulting in delayed decision-making and limited operational visibility. Real-time event-driven processing provides an advanced architectural approach that enables organizations to capture, analyze, and respond to critical business events instantly through distributed data streaming and intelligent automation technologies. This research paper explores the integration of event-driven architectures, real-time analytics, cloud-native computing, and microservice-based systems to enhance enterprise risk intelligence capabilities across financial and operational environments. The study examines the role of event brokers, stream processing platforms, API-driven communication, artificial intelligence, and machine learning in detecting anomalies, predicting risks, and supporting rapid operational decisions. Furthermore, the paper discusses scalability, resilience, low-latency processing, and security mechanisms required for high-performance enterprise risk management systems. Challenges related to distributed system coordination, data consistency, compliance requirements, and observability are also analyzed. Through comprehensive evaluation and industry-focused insights, the research demonstrates how real-time event-driven processing improves organizational agility, operational efficiency, proactive risk mitigation, and intelligent enterprise decision-making in modern digital ecosystems.

DOI: http://doi.org/10.5281/zenodo.20608245

Published by: vikaspatanker

Authors: Jonathan Parker, Abigail Stewart, Christopher Allen, Natalie Simmons, Chaitanya Srinivas, Rishi Kumar

Abstract: High-throughput financial systems are becoming essential for modern banking, digital payments, stock trading, insurance platforms, and fintech applications that demand real-time processing, scalability, reliability, and secure transaction management. Traditional monolithic architectures often struggle to handle massive transaction volumes, rapid scalability requirements, and continuous service availability in highly dynamic financial environments. Microservice architectures provide an effective solution by decomposing complex financial applications into independently deployable, loosely coupled services that improve agility, fault isolation, scalability, and continuous delivery. This paper explores the role of microservice architectures in enabling high-throughput financial systems by examining core architectural principles, distributed transaction management, event-driven communication, API gateways, containerization, orchestration, and real-time data streaming technologies. The study also highlights the integration of cloud computing, DevOps practices, and resilient messaging systems to achieve enhanced performance, low latency, and operational efficiency in enterprise financial ecosystems. Furthermore, the paper discusses major challenges including security vulnerabilities, data consistency, service coordination, compliance requirements, and monitoring complexities in distributed environments. Through analytical evaluation and industry-oriented insights, the research demonstrates how microservice-powered financial platforms can support millions of concurrent transactions while ensuring scalability, resilience, maintainability, and business continuity in modern digital finance infrastructures.

DOI: http://doi.org/10.5281/zenodo.20608047

Published by: vikaspatanker

Authors: Sophia Bennett, Ethan Walker, Grace Phillips, Daniel Mitchell, Chaitanya Srinivas, Rishi Kumar

Abstract: The rapid growth of digital enterprises, cloud-native technologies, and real-time analytics has significantly increased the demand for resilient data streaming architectures capable of processing high-volume, low-latency data across distributed environments. Modern enterprise transformation initiatives rely heavily on real-time streaming platforms to support intelligent decision-making, operational automation, predictive analytics, and continuous business monitoring. This research examines resilient real-time streaming architectures designed to enhance enterprise scalability, fault tolerance, operational continuity, and data-driven decision systems within dynamic cloud ecosystems. The study explores core streaming technologies including Apache Kafka, event-driven architectures, distributed messaging systems, stream processing frameworks, and cloud-native orchestration platforms that enable reliable real-time data movement across enterprise infrastructures. Particular emphasis is placed on architectural resilience mechanisms such as replication, partitioning, load balancing, failover recovery, observability, and distributed fault management that ensure uninterrupted data processing and high system availability. The research further investigates governance, security, and compliance considerations associated with enterprise streaming environments, including data integrity, access control, encryption, monitoring, and operational governance within multi-cloud and hybrid infrastructures. Evidence mapping techniques are utilized to analyze deployment strategies, operational performance, scalability patterns, and resilience contributions of modern streaming architectures across enterprise domains such as finance, healthcare, retail, telecommunications, and industrial automation. The findings demonstrate that resilient streaming frameworks significantly improve organizational agility, operational intelligence, business continuity, and real-time decision capabilities while enabling enterprises to accelerate digital transformation and maintain competitive advantage in rapidly evolving technological environments.

DOI: http://doi.org/10.5281/zenodo.20607778

Published by: vikaspatanker

Authors: William Turner, Charlotte Evans, Benjamin Lewis, Amelia Scott, Chaitanya Srinivas, Rishi Kumar

Abstract: The rapid adoption of cloud-native technologies and distributed enterprise systems has significantly accelerated the deployment of microservice architectures across highly regulated industries such as finance, healthcare, insurance, and government sectors. While microservices improve scalability, agility, operational flexibility, and continuous service delivery, they also introduce complex governance, security, compliance, and interoperability challenges that organizations must address to maintain regulatory integrity and operational resilience. This research examines the role of platform governance frameworks in managing regulated microservice architectures by analyzing governance mechanisms related to policy enforcement, identity and access management, API security, compliance automation, service observability, risk management, and operational accountability. The study further investigates how governance platforms support secure communication, workload isolation, auditability, and continuous compliance validation within cloud-native ecosystems operating under regulations such as GDPR, HIPAA, PCI DSS, and ISO/IEC 27001. Evidence mapping techniques are utilized to evaluate governance contributions across enterprise microservice environments and identify emerging best practices that improve service reliability, cybersecurity resilience, and regulatory alignment. The findings demonstrate that integrated governance frameworks combined with automation, Zero Trust principles, and continuous monitoring capabilities significantly enhance organizational ability to manage distributed microservice infrastructures securely and efficiently. The research highlights the strategic importance of governance-driven architectures in enabling scalable digital transformation while ensuring compliance, operational transparency, and long-term enterprise sustainability in modern regulated environments.

DOI: http://doi.org/10.5281/zenodo.20607626

Published by: vikaspatanker

Authors: Rakibul Hasan Amin, Mohammad Mehedi Hasan, Mohammad Shah Alam Chowdhury, Md. Raidul Islam, Rakibul Islam, Syed Tamzid Ahmed

Abstract: Fishing communities constitute one of the most vulnerable socio-economic groups in Bangladesh, relying heavily on natural water resources for their livelihood and survival. Despite their significant contribution to local economies and food security, these communities often face numerous human rights challenges, including poverty, limited access to education and healthcare, inadequate housing facilities, occupational hazards, social exclusion, and restricted access to government welfare programs. The present study examines the human rights conditions of fishing communities residing in the Mawa-Munshiganj region of Bangladesh. The research explores the extent to which fundamental human rights, such as the right to education, health, livelihood, social security, and a dignified standard of living, are ensured among the fisher folk population. A mixed-method research design was employed, and primary data were collected from 100 fishermen through structured questionnaires, interviews, and focus group discussions. The findings reveal widespread deprivation in several dimensions of human rights, affecting both male and female members of the fishing community. Major challenges identified include food insecurity, inadequate access to healthcare services, limited awareness of legal rights, and vulnerability to harassment and exploitation. While 62 percent of the respondents reported receiving some form of government assistance during fishing ban periods, the support was often insufficient to meet their livelihood needs. Furthermore, the study found that approximately 80 percent of the respondents were illiterate, highlighting the community’s educational disadvantages. The study concludes that fishing communities in the Mawa-Munshiganj region continue to face significant socio-economic and human rights challenges. Based on the empirical findings, the research offers policy recommendations aimed at improving their living conditions, strengthening social protection measures, enhancing access to education and healthcare, and promoting the overall welfare and human rights of riverine fishing communities in Munshiganj.

DOI: http://doi.org/10.5281/zenodo.20604876

Published by: vikaspatanker

Authors: Pankaj Kumar Rai, P. N. Ahirwar

Abstract: Development of residual stresses during additive manufacturing (AM) imposes challenges on functionality and performance of the component. Being able to predict, measure and reduce residual stress by proper post processing will prevent pre-mature failure of the components. In this study finite element package of ANSYS software is employed to predict residual stress, distortion, melt pool dimensions and thermal history for the powder bed fusion (PBF) process of AM. Experimental validation of the residual stress predicted by the numerical modeling were carried out on additively manufactured coupon through X-ray diffraction. A small compressive residual stress on the top surface of the coupon is determined by both the experimental and numerical approach contradicting the reported work of tensile residual stress on the top surface.

DOI: http://doi.org/10.5281/zenodo.20592906

Published by: vikaspatanker

Authors: Ms. Snehal Kadbhane, Ms. Bhagyashri Shankar Thorbole, Ms.Nikita Sanjay Pachange, Dr. Vijaykumar Kale, Dr. Mahesh Thakare

Abstract: In this study, making of polyherbal candy for treatment of Dengue is the primary goal, using natural ingredient to treat the dengue fever and boost the immunity against Dengue. Dengue fever is a flu-like illness transmitted by female mosquitos of the Aedes aegypti species. Another name for it in Ayurveda is dandaka jwara. It is particularly prevalent in tropical and subtropical climate zones worldwide. Common symptoms of dengue include vomiting, a strong headache, nausea, rashes, joint discomfort, pain behind the eyes, muscular pain, and enlarged glands. Platelets play a crucial role in blood coagulation. During the course of their infection, DENV [Dengue Virus] patients frequently experience thrombocytopenia, making them susceptible to bleeding symptoms and other serious consequences. It also causes bone marrow depression and reduces platelet production. The active constituent carica papaya which increasing the number of platelet count and it shows the Anti-inflammatory and Anti-viral activity. Giloy sativa increases platelet count and speeds up the recovery process and also during dengue fever helps to strengthen the immune system. Other ingredients in formulation such as Sugar, Gum acacia, Lemon juice, Beetroot (powder) helps in reducing dengue symptoms, such as fever and pain, and improving patient outcomes. The development of herbal candies for dengue therapy is a novel and promising approach to disease management, with potential advantages for both patients and healthcare systems.

Published by: vikaspatanker