Daily Archives: May 20, 2026

Authors: Ms. K. Divarshini, Dr. P. Poornima

Abstract: The rapid growth of e-commerce and smartphone usage has significantly transformed consumer buying behaviour. Online shopping platforms provide convenience, variety, and easy access to products, influencing consumer decisions. This study aims to analyse the buying behaviour of consumers towards the Flipkart mobile application. Primary data was collected through a structured questionnaire from 100 respondents. The findings reveal that factors such as discounts, product variety, user-friendly interface, and delivery services play a major role in influencing consumer decisions. The study concludes that Flipkart is widely preferred due to its convenience and attractive offers, but improvements in delivery speed and product quality can further enhance customer satisfaction.

DOI: http://doi.org/10.5281/zenodo.20309209

Published by: vikaspatanker

Authors: Shubham sahu, Dr. Dharmbir Yadav

Abstract: The rapid growth of modern telecommunication technologies such as 2G, 4G LTE, and 5G has significantly increased the complexity of telecom network management. Telecom operators continuously generate massive amounts of network data related to traffic usage, bandwidth utilization, latency, throughput, and user activity. Traditional telecom monitoring systems mainly rely on manual analysis and threshold-based alert mechanisms, which are often unable to predict future network congestion, performance degradation, or operational failures effectively. To overcome these limitations, intelligent and automated monitoring solutions are required for efficient telecom network management. This research work, titled “Telecom Network Intelligence System using AI,” proposes an Artificial Intelligence (AI) and Machine Learning (ML) based framework for intelligent telecom network monitoring, traffic prediction, congestion detection, and performance analysis. The proposed system integrates telecom KPI analytics, predictive Machine Learning models, and real-time dashboard visualization to support proactive telecom operations and data-driven decision-making. The system analyzes important telecom Key Performance Indicators (KPIs) such as Call Setup Success Rate (CSSR), Call Drop Rate, LTE Throughput, PRB Utilization, Network Latency, and User Throughput collected from 2G, 4G LTE, and 5G networks. Machine Learning algorithms including Linear Regression, Random Forest, and Long Short-Term Memory (LSTM) are utilized for traffic forecasting, anomaly detection, and congestion prediction. The proposed framework also integrates Python, SQL, Advanced Excel, and Microsoft Power BI for telecom data preprocessing, predictive analytics, and interactive dashboard development. The AI-driven dashboards provide real-time KPI monitoring, network health visualization, congestion alerts, and technology-wise performance comparison. Experimental analysis demonstrates that the proposed system improves prediction accuracy, reduces operational complexity, supports proactive fault management, and enhances telecom network efficiency. The research contributes toward the development of intelligent telecom monitoring systems capable of supporting future AI-driven telecom operations, AIOps integration, self-healing networks, and next-generation 5G/6G communication infrastructures.

Published by: vikaspatanker

Authors: Dr. Mohammad Shah Alam Chowdhury

Abstract: The present study explores the representation of socialism and social realism in the selected works of Aravind Adiga and Rohinton Mistry. Socialism, as a socio-economic ideology, advocates equality, collective welfare, and the reduction of class divisions; however, its practical implementation in India has often revealed contradictions marked by poverty, corruption, exploitation, and social inequality. Contemporary Indian English literature reflects these realities by portraying the struggles of marginalized communities and critiquing the failures of political and economic systems. The study examines how Adiga and Mistry depict the harsh realities of Indian society through themes such as class oppression, poverty, labor exploitation, corruption, identity crisis, and social injustice. Aravind Adiga’s novels, particularly The White Tiger and Last Man in Tower, expose the inequalities of post-liberalization India where capitalist ambitions overshadow socialist ideals. His narratives present a satirical and confrontational critique of economic disparity, moral decay, and institutional corruption. In contrast, Rohinton Mistry’s works, including A Fine Balance and Such a Long Journey, offer a compassionate and humanistic portrayal of ordinary individuals struggling against political oppression, social discrimination, and economic hardships. The research further compares the narrative techniques, ideological perspectives, and social concerns reflected in the writings of both authors. While Adiga emphasizes rebellion, survival, and individual ambition within a corrupt socio-economic structure, Mistry focuses on resilience, human dignity, empathy, and collective suffering. Despite their differing approaches, both writers critically examine the failures of governance and the widening gap between the privileged and marginalized sections of society. The study concludes that the works of Adiga and Mistry serve as powerful critiques of socio-political realities in contemporary India. Their fiction not only reflects the complexities of socialism and capitalism but also highlights the role of literature as a medium for social awareness, resistance, and the representation of marginalized voices.

DOI: https://doi.org/10.5281/zenodo.20305758

Published by: vikaspatanker

Authors: Bikku Kumar

Abstract: Mergers and acquisitions (M&A) have emerged as the most consequential instruments of corporate strategy in India's post-liberalisation growth narrative. This paper undertakes a rigorous multi-dimensional examination of India's ten largest M&A transactions — spanning banking, e-commerce, steel, telecommunications, cement, aluminium, pharmaceuticals, and automotive sectors — executed between 2007 and 2023 with a cumulative deal value exceeding USD 113 billion. Employing a descriptive-analytical framework grounded in secondary financial data, the study evaluates pre- and post-merger performance across key metrics including Return on Equity (ROE), Earnings Per Share (EPS), and Debt-to-Equity (D/E) ratio. A comparative matrix is deployed to assess strategic intent realisation, post-merger integration efficacy, and sector-specific determinants of M&A success or failure. Statistical analysis of financial ratios reveals a statistically significant divergence between successful and failed deals when measured against pre-merger benchmarks, with successful integrations yielding a mean ROE improvement of 2.1 percentage points. The findings unequivocally establish that strategic alignment, due diligence rigour, and cultural integration capacity are the decisive success factors — not deal size alone. The research contributes an empirically grounded, sector-comparative understanding of M&A dynamics in an emerging market context.

DOI: https://doi.org/10.5281/zenodo.20305623

Published by: vikaspatanker

Authors: Dr. Mohammad Shah Alam Chowdhury

Abstract: Since its independence in 1971, Bangladesh has transformed from one of the poorest nations in the world famously mischaracterized as a "basket case" to one of the fastest-growing economies in South Asia. This paper examines the trajectory of Bangladesh's economic growth, driven primarily by a booming ready-made garment (RMG) industry, robust remittance inflows, and significant advancements in social development indicators such as female labor force participation. However, despite reaching lower-middle-income status in 2015, the nation currently faces severe macroeconomic headwinds. Elevated inflation, banking sector vulnerabilities, low tax revenue mobilization, and external shocks have slowed recent GDP growth. This paper analyzes the historical drivers of growth, structural bottlenecks, and the urgent policy reforms required to ensure sustainable and inclusive economic development.

DOI: https://doi.org/10.5281/zenodo.20305441

Published by: vikaspatanker

Authors: Ragula Rajesh, Potti Rakesh, Poojari Jayakrishna, Mrs.V. Elavenil

Abstract: This study describes the deployment of a cloud-native AI system designed to assist HR departments by offering automated resume screening and candidate-job matching. To provide precise and contextually aware responses, the system employs a Retrieval-Augmented Generation (RAG) technique, which combines a language model with a local knowledge store of job descriptions. We developed this totally with free and open-source technologies like AWS Lambda, BERT, and ChromaDB to make the solution more accessible for startups and SMEs. Open-source approaches, such as Tesseract for OCR, are used to add scanned resume capabilities. To ensure accuracy and validity, the data is also gathered from reputable sources like ESCO skill ontology and LinkedIn datasets. We used PDFs from these sources for RAG and stored them in vector databases for efficient document retrieval, as this system aims to bridge the information gap in high-volume hiring.

DOI: https://doi.org/10.5281/zenodo.20304132

Published by: vikaspatanker

Authors: Gajabheenkar Roshini, Dr.Lavanya Pamulaparty

Abstract: This research focuses on analyzing NFL offensive player statistics from 1999–2013 using Tableau visualization techniques. The dataset contains player demographics combine performance, draft information, and offensive statistics. Various visualizations such as bar charts, heat maps, dashboards, and highlight tables are used to identify player performance trends and statistical patterns. The analysis helps understand how player attributes and performance metrics contribute to offensive success in the NFL.

Published by: vikaspatanker

Authors: Malgaram Punith Teja, Srishti Singh, Baddula Sreeya Yadav, Mrs.Sumayya Samreen

Abstract: This research paper examines what makes an e-commerce business succeed. They use a data set on fifty thousand Amazon transactions to see the effect of all sorts of different variables on sales. What factors we considered was the sale price, discount percentage, ratings and amount of reviews. We examined the mechanics of pricing ,examined the level of consumer confidence in a product , we studied preferences we considered payment mode It shows how offs, and customer ratings influence earned money of the businessThis results from suggesting discounts might increase sales over a specific term but influence long term revenues via performing well on customer ratings and consumer trust. We find that both markets of North America and Middle-East have the revenue. The findings of this research may be accessed by merchants and marketers who wish to set their prices to helps consumers in their purchase decisions and at the same time, increase their revenues. Based on these results, they are able decide about their business.

DOI: https://doi.org/10.5281/zenodo.20302852

Published by: vikaspatanker

Authors: Eeshritha

Abstract: India generates millions of tonnes of plastic waste annually, much of which is non-biodegradable. This paper explores the feasibility of using recycled polypropylene (PP) to produce polymer currency notes. Drawing on Australia’s pioneering adoption of polymer banknotes, the study eval-uates technical, economic, policy, and social challenges, and proposes a phased roadmap for India to transition towards sustainable currency pro-duction. The findings suggest that recycled PP notes could simultaneously address waste management, enhance currency durability, and position India as a global leader in sustainable finance innovation.

Published by: vikaspatanker