Daily Archives: September 17, 2026

Authors: Rajpurohit Priya Bhavani Singh, Assistant Professor Ms Manisha Kalra

Abstract: Micro, Small and Medium Enterprises (MSMEs) are widely described as the backbone of the Indian economy, contributing close to 30 per cent of national income, a little over a third of manufacturing output, and roughly 45 per cent of the country's merchandise exports, while sustaining employment for more than 110 million people. Despite this scale, the sector has historically operated under a severe financing constraint, with credible estimates of the gap between demand and formally supplied credit ranging from about ₹20 lakh crore to ₹30 lakh crore in recent years. This paper examines the evolving relationship between bank credit and industrial credit in India, with specific reference to the MSME sector, using secondary data drawn from the Reserve Bank of India (RBI), the Ministry of Micro, Small and Medium Enterprises, Parliamentary disclosures, and other government and industry publications. Employing a Pearson correlation framework on annual data for scheduled commercial bank (SCB) credit to MSMEs and to the industrial sector as a whole, the study finds a very strong, statistically significant positive association between the two series (r ≈ 0.98, p < 0.001), leading to rejection of the null hypothesis of no relationship. The paper further documents that credit to MSMEs grew faster than credit to any other major sector in 2024-25, even as overall bank credit growth dece Fund lerated, reflecting the cumulative effect of policy interventions such as the Credit Guarantee Trust for Micro and Small Enterprises (CGTMSE), the Emergency Credit Line Guarantee Scheme (ECLGS), and priority sector lending norms. At the same time, the study finds that formal credit penetration remains low — by some estimates only about one in seven MSMEs has access to institutional finance — and that collateral requirements, asset-quality caution among lenders, and disparities across enterprise size and gender continue to constrain the sector. The paper concludes with a set of policy-relevant observations on deepening formal credit flow to MSMEs.

DOI: https://doi.org/10.5281/zenodo.22812490

Published by: vikaspatanker

Authors: Research Scholar Ms. Monali Khune, Dr. Amol Y. Deshmukh

Abstract: Background: Brain–computer interface (BCI) systems frequently utilize P300 and steady-state visual evoked potential (SSVEP) paradigms. Because neither approach yields universal success across users, recent research has explored hybrid BCI designs that merge multiple techniques to expand user compatibility. Although hybrid P300/SSVEP systems are a relatively recent innovation with limited performance optimization studies to date, they represent a promising avenue for improving system accessibility. New method: In this research, we contrast a conventional hybrid P300/SSVEP BCI framework with an innovative approach. Specifically, shape alterations are utilized instead of color modulations to evoke the P300 wave, aiming to minimize any adverse impact on SSVEP signal strength. Result: The new hybrid paradigm presented in this paper yields much better performance than the traditional hybrid paradigm. Comparison with existing method: The novel hybrid paradigm yields an SSVEP classification improvement of close to 20% over the standard approach. Furthermore, all tested paradigms—excluding the conventional hybrid model—achieve a perfect 100% accuracy rate in P300 classification. Conclusions: The innovative hybrid P300/SSVEP brain-computer interface paradigm replaces traditional color-shifting stimuli with shape-altering visual elements, matching the classification accuracy of conventional SSVEP and P300 setups. Furthermore, the author explored how presenting multiple visual stimuli at once triggers overlapping brain responses and evaluated the resulting interference on signal detection.

DOI: https://doi.org/10.5281/zenodo.22806381

Published by: vikaspatanker