Authors: Hafiz Umar

Abstract: Scalable application design has become a fundamental requirement in modern software engineering due to the rapid growth of users, data, and distributed computing environments. Systems today must handle increasing workloads efficiently while maintaining performance, reliability, and availability. This review explores the principles and architectural patterns used in designing scalable applications, including horizontal and vertical scaling, microservices architecture, load balancing, caching strategies, and distributed databases. It also examines cloud-native approaches that enable elasticity and on-demand resource provisioning. The study highlights the importance of system design considerations such as fault tolerance, high availability, and performance optimization in building robust applications. Furthermore, it discusses challenges such as network latency, data consistency, system complexity, and cost management in large-scale systems. Emerging trends like serverless computing, edge computing, and container orchestration are also reviewed. The findings emphasize that effective system design is essential for ensuring scalability, efficiency, and reliability in modern distributed applications.

DOI: http://doi.org/10.5281/zenodo.20284144

 

Published by: vikaspatanker

Authors: Nguyen Thanh Binh

Abstract: Cloud computing has become an essential foundation for modern digital infrastructure, enabling organizations to store, process, and manage data efficiently over distributed environments. However, the widespread adoption of cloud services has also introduced significant security challenges, including data breaches, misconfigurations, unauthorized access, and compliance risks. This study explores cloud security best practices designed to mitigate these risks and strengthen the overall security posture of cloud-based systems. It examines key security mechanisms such as identity and access management (IAM), encryption techniques, multi-factor authentication, secure network architecture, and continuous monitoring. The paper also highlights the importance of shared responsibility models, where both cloud service providers and users play a role in ensuring security. In addition, emerging practices such as zero trust architecture, DevSecOps integration, and automated threat detection are discussed. The findings emphasize that adopting structured cloud security best practices significantly reduces vulnerabilities, enhances data protection, and ensures compliance with regulatory standards, making cloud environments more secure and reliable.

DOI: http://doi.org/10.5281/zenodo.20284178

Published by: vikaspatanker

Authors: Liyana Abdullah

Abstract: Artificial intelligence (AI) has become a transformative force in modern enterprises by enabling data-driven decision-making through advanced analytics and predictive modeling. AI-driven insights allow organizations to process vast volumes of structured and unstructured data, uncover hidden patterns, and generate actionable intelligence for strategic and operational decisions. This study explores the role of AI in enhancing enterprise decision-making processes, focusing on techniques such as machine learning, deep learning, natural language processing, and data mining. It examines how AI systems integrate with enterprise platforms such as cloud computing, business intelligence tools, and data warehouses to support real-time and informed decision-making. The paper also highlights applications across domains including finance, healthcare, supply chain management, marketing, and human resource management. Furthermore, it discusses key challenges such as data quality issues, algorithmic bias, lack of transparency, security concerns, and integration complexities. Emerging solutions such as explainable AI, federated learning, and AI governance frameworks are also analyzed. The findings emphasize that AI-driven insights significantly enhance decision accuracy, operational efficiency, and strategic planning, making AI a critical component of modern enterprise decision-making systems.

DOI: http://doi.org/10.5281/zenodo.20284214

 

Published by: vikaspatanker

Authors: Sunita Rao

Abstract: DevOps has emerged as a transformative approach in modern software engineering, integrating development and operations to enhance collaboration, automation, and continuous delivery. In cloud environments, DevOps practices play a crucial role in improving scalability, reliability, and speed of software deployment. This study provides an analysis of DevOps practices within cloud computing environments, focusing on key components such as continuous integration and continuous deployment (CI/CD), infrastructure as code (IaC), automation, containerization, and monitoring. It examines how cloud platforms enable seamless implementation of DevOps pipelines and support rapid application development and deployment. The paper also explores the impact of DevOps on software quality, deployment frequency, system stability, and operational efficiency. Furthermore, it discusses challenges such as tool integration complexity, security concerns, cultural resistance, and skill gaps in DevOps adoption. Emerging trends such as DevSecOps, GitOps, and AI-driven automation are also analyzed. The findings highlight that DevOps practices in cloud environments significantly enhance agility, reduce time-to-market, and improve system reliability, making them essential for modern digital transformation initiatives.

DOI: http://doi.org/10.5281/zenodo.20284248

 

Published by: vikaspatanker

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