Daily Archives: May 16, 2026

Authors: Associate Professor Dr. S.Sureshbabu, Research Scholar Mr. A.kannan

Abstract: This study examines farmers' perceptions of marketing functions and services rendered by Cooperative Marketing Societies (CMS) through comprehensive exploratory factor analysis of data from 620 farm-members. Principal Components Analysis with Varimax rotation identifies five distinct dimensions of CMS marketing functions: Market Operations and Transaction Efficiency, Pricing and Bargaining Effectiveness, Market Access and Infrastructure Support, Post-Harvest and Quality Support Services, and Information and Financial Support Services. The findings reveal that farmers rate infrastructure support (mean = 4.30) and storage facilities (mean = 4.23) most favorably, while expressing moderate satisfaction with pricing transparency (mean = 2.69) and income impact (mean = 3.28). Cluster analysis segments farmers into three groups: 62.4% highly satisfied, 23.2% moderately satisfied, and 14.4% less satisfied with CMS functions. The five-factor model explains 64.183% of cumulative variance, establishing a robust framework for understanding CMS service quality and performance. The study provides evidence-based insights for strengthening cooperative marketing functions and designing targeted interventions to enhance farmer satisfaction across service dimensions.

DOI: https://doi.org/10.5281/zenodo.20242694

Published by: vikaspatanker

Authors: Dr Vijayalakshmi V, Ms.Sneha R. V. Kumbhar

Abstract: However, the rise in cloud computing usage has resulted in increased complexity and vulnerability of organizations' IT infrastructure. In addition, cloud services have created new vulnerabilities that can easily be targeted by sophisticated attacks since traditional intrusion detection methods lack the ability to cope with the dynamically changing nature of cloud environments. This paper offers a novel, AI-powered hybrid deep learning framework for intrusion detection in cloud environments. The hybrid IDS is based on a combination of Triplet Attention-based Residual CNN for spatial feature extraction of network traffic, Bi-LSTM with attention mechanism for temporal dependency modeling, and Particle Swarm Optimization for hyperparameter optimization. Based on the evaluation results performed on the CSE-CIC-IDS2018 and UNSW-NB15 dataset, the suggested hybrid architecture attains an impressive accuracy of 99.12%, precision of 98.9%, and recall of 99.0%, outperforming the performance of individual CNN (96.4%) and Bi-LSTM (95.8%). In terms of efficiency, the PSO-based architecture has a latency less than 50 ms with minimal false positive rate of only 1.2%.

DOI: https://doi.org/10.5281/zenodo.20233688

Published by: vikaspatanker

Authors: Harishankar T, Dr.T.R.Ganesh Babu

Abstract: In the context of their growing use in critical fields of application, like aviation electronics, automotive control systems, and industrial automation, FPGA circuits' operation must be guaranteed against both soft errors and any other defects that may arise during run-time. This paper analyzes in depth an approach for implementing Totally Self-Checking (TSC) comparators for online diagnostics in FPGAs in a way which maximizes its effectiveness in terms of test pattern complexity and hardware overhead. In particular, the presented technique utilizes the circuitry features of Look-Up Tables (LUTs) to provide comprehensive online testing with a number of test vectors proportional to O(n), while guaranteeing complete fault coverage and regardless of the specific LUTs configuration. The results of a comparison among recent techniques for implementing TSC, both BIST-based and Dual Modular Redundancy (DMR), show that the described solution offers an outstandingly effective performance with regard to SER (0.055 FIT).

DOI: https://doi.org/10.5281/zenodo.20233433

Published by: vikaspatanker

Authors: Mr. Uddesh Dhanraj Dongre, Prof. Mithlesh Pandey

Abstract: Solar thermal collectors are widely used for converting solar energy into useful thermal energy for domestic and industrial applications. Conventional collectors suffer from energy loss during cloudy weather and nighttime due to the absence of efficient thermal storage systems. To overcome this limitation, Phase Change Materials (PCM) are integrated into solar thermal collectors. PCM absorbs excess heat during sunshine hours and releases stored thermal energy during low solar radiation conditions. This research focuses on the design and optimization of a solar thermal collector integrated with PCM. Paraffin wax is selected as PCM because of its high latent heat capacity, thermal stability, chemical inertness, non-corrosive nature, and suitable melting temperature range. The performance of the collector is evaluated based on thermal storage capability, charging and discharging characteristics, outlet water temperature, heat retention, and efficiency improvement. The study shows that PCM integration significantly improves thermal efficiency and maintains outlet temperature for longer duration compared to conventional collectors. The optimized collector demonstrates enhanced energy utilization, reduced temperature fluctuation, and better thermal stability. The proposed system is suitable for domestic water heating, industrial thermal applications, agricultural drying systems, and renewable energy storage applications.

Published by: vikaspatanker

Authors: Salama Juma Shehe, Dr. Sahil Nazir

Abstract: This study examined the impact of social media marketing on consumer buying behavior. The rapid growth of digital technology and social networking platforms has transformed the way businesses communicate with customers and promote their products and services. The main objective of the study was to analyze how social media marketing influences consumer purchasing decisions. Specifically, the study examined the role of social media advertisements, online reviews, influencer marketing, and promotional content in shaping consumer buying behavior. The study employed a quantitative research design using a survey method. Data were collected through an online questionnaire created using Google Forms and distributed through social media platforms. A total of sample size 100 respondents participated in the study. The collected data were analyzed using descriptive statistics, including frequencies and percentages, and presented using tables and charts. The findings indicated that social media marketing significantly influences consumer buying behavior. The results showed that most consumers rely on social media platforms to obtain information about products, read reviews, and compare alternatives before making purchase decisions. The study concludes that social media marketing plays a critical role in influencing modern consumer purchasing behavior. Businesses should therefore invest in effective social media marketing strategies to improve brand visibility, customer engagement, and sales performance. The study recommends that companies should enhance their social media presence, collaborate with influencers, and provide reliable and engaging content to attract and retain customers.

Published by: vikaspatanker

Authors: Prachi Barnwal, Dr Navneet Seth

Abstract: Training and development policies play a crucial role in improving employee competence, organizational productivity, and overall business performance. In the modern competitive environment, organizations increasingly invest in employee training programs to enhance technical skills, communication abilities, leadership qualities, and job efficiency. The present study examines the impact of training and development policies on employee competence using a data-oriented approach. The study is based on secondary data collected from research journals, HR reports, and organizational studies. The findings reveal that effective training policies significantly improve employee skills, motivation, productivity, and job satisfaction. The study concludes that organizations with strong training and development practices achieve higher employee performance and organizational effectiveness.

Published by: vikaspatanker

Authors: Mandeep Kaur, Dr joe Christy N

Abstract: The rapid growth of social media platforms has transformed consumer buying behavior, with YouTube emerging as one of the most influential digital marketing channels. This research paper examines the impact of YouTube on consumer purchase decisions through a data-oriented approach. The study analyzes how YouTube advertisements, influencer marketing, product reviews, unboxing videos, and user-generated content affect consumer awareness, purchase intention, and actual buying behavior. Secondary data from recent empirical studies and industry reports are used to evaluate consumer responses toward YouTube-based marketing strategies. The findings reveal that YouTube significantly influences consumer decision-making, particularly among younger audiences such as Generation Z and Millennials. Factors such as content credibility, emotional engagement, influencer trustworthiness, and video quality positively affect purchase intentions. The study concludes that YouTube has become a powerful tool for marketers in shaping consumer attitudes and driving purchasing decisions.

Published by: vikaspatanker

Authors: Jatinder Singh, Manisha Kalra

Abstract: – Microfinance has emerged as an important financial instrument for reducing poverty, promoting self-employment, and improving the socio-economic conditions of low-income households. The concept of microfinance involves providing small loans, savings facilities, insurance, and other financial services to economically weaker sections who are generally excluded from the formal banking sector. This research paper examines the role of microfinance in poverty reduction by analyzing its impact on income generation, employment opportunities, women empowerment, and rural development. The study also highlights the challenges faced by microfinance institutions (MFIs) and suggests measures for improving their effectiveness. The paper concludes that microfinance plays a significant role in poverty alleviation when combined with proper training, financial literacy, and government support.

Published by: vikaspatanker

Authors: Jyotish Kumar, Dr. Meentu Grover

Abstract: India's mobile economy is no longer a future promise — it is today's commercial reality. This study examines the impact of mobile marketing on consumer engagement with empirical evidence drawn from 150 respondents across Punjab, India. Adopting a descriptive-analytical research design and administering structured questionnaires, the study investigates how SMS campaigns, social media advertisements, push notifications, mobile applications, and influencer marketing shape consumer purchase intentions, brand loyalty, and overall satisfaction. Statistical techniques including descriptive analysis, correlation, regression, and chi-square testing were employed to interrogate the data. Results confirm that mobile marketing exerts a statistically significant positive effect on consumer engagement (β = 0.61, p < 0.001), with social media marketing and personalized notifications emerging as the strongest predictors. Brand trust and perceived usefulness were identified as critical mediating constructs. These findings carry decisive implications for digital marketers, policy designers, and scholars navigating India's fast-evolving mobile-first marketplace.

Published by: vikaspatanker

Authors: K.Ravindhar, P.KamalaKar, Dr.Diana Moses

Abstract: This analysis examines a restaurant chain sales dataset covering transaction recorded across November and December 2022, spanning five major European cities — London, Lisbon, Madrid, Berlin, and Paris. The dataset capture nine key attributes including Order ID, Date, Product, Price, Quantity, Purchase Type, Payment Method, Manager, and City, forming a structured foundation for evaluating multi-dimensional sales performance. Burger emerge as the highest revenue-generating product, followed by Fries and Chicken Sandwiche, while Sides & Other contributes the least to overall revenue. Geographically, Lisbon leads in both total revenue and quantity sold, closely followed by London, whereas Berlin and Paris record comparatively lower performance. Purchase behavior analysis reveals that Online transaction are the most frequently used channel, followed by Instore and Drive thru. In terms of payment preferences, Credit Card dominates as the most widely adopted method, ahead of Cash and Gift Card usage. These finding highlight key revenue regional performance disparities, and customer purchasing preferences, offering a data-driven foundation for improving inventory planning, targeted marketing strategies, and overall operational decision-making.

Published by: vikaspatanker