Category Archives: Uncategorized

Authors: Assistant Professor Ms. Shruti Rawat, Anmol Choudhary

Abstract: The primary objective of this research is to examine and analyze the impact of cultural diversity on the overall effectiveness and productivity of teams operating inside international organizations. The primary objective of this research is to bridge the existing knowledge deficit in the domain of cross-cultural management and organizational behavior. This is achieved by conducting an investigation into the intricate association between cultural diversity and team performance inside MNCs. In the context of this study, a mixed-methods approach is considered the most suitable methodology. This methodology enables a thorough examination of the correlation between cultural diversity and team performance, encompassing the utilization of both quantitative and qualitative data. The results emphasize the importance for MNCs to implement comprehensive strategies that take into account the specificities of leadership, organizational culture, and team dynamics in order to effectively use the benefits of cultural diversity. By engaging in such practices, firms can effectively tackle the complexities associated with cultural diversity and bolster their global competitive advantage. Through the implementation of these strategies, MNCs have the opportunity to effectively utilize the advantages presented by cultural diversity, hence enhancing their competitive advantage within the global market.

DOI: http://doi.org/

Published by: vikaspatanker

Authors: Shriram Deshpande, Shridhar Dhaduti, Rahul Meeshi, Daneshwari Jambagi

 

Abstract: Adequate quality and reliability of drinking water is vital for all inhabitants and for agriculture and industrial applications. Solar desalination is impactful method for getting potable water from brackish/wastewater in hot climatic condition and/or remote area where the scarcity of water as well as for electricity. In recent years, attention has been focused on development of various designs of solar still in order to overcome limitations possesses by conventional single basin single slope solar still. Pyramid solar still is one of the outcomes of such a development. This project reviews the development in the field of pyramid solar still as well as the various techniques to improve the performance of still. From the review on research carried out by the various researchers, it has been found that pyramid solar still is more efficient and economical in compare to conventional single slope single basin still.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.122

 

Published by: vikaspatanker

Authors: Parash Pandey, Siddarth Gupta, Abhishek Kumar, Anmol Choudhary

Abstract: Artificial Intelligence (AI) is rapidly becoming a key part of modern cybersecurity. This paper explores how AI is changing digital security systems by automating threat detection, analyzing patterns, and helping respond to attacks faster than ever. AI helps detect cyber threats, protect data, and reduce the need for manual monitoring. But it also introduces new risks, such as biased algorithms, adversarial attacks, and privacy concerns. This paper highlights current applications, advantages, and challenges of AI in cybersecurity, and suggests ways to ensure responsible use of this powerful technology.

 

 

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DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Girish Kishor Ingavale

 

Abstract: The exponential growth of various technologies, including artificial intelligence (AI), cloud computing, and big data analytics, has led to an unprecedented surge in the computational demands placed on data centers. This paper provides a detailed review of innovative zero-water cooling technologies that offer an alternative to traditional water-based cooling systems, ensuring optimal operating temperatures for AI hardware. We examine various waterless cooling methods, including immersion cooling, air-cooled heat sinks, and phase-change materials, assessing their effectiveness, energy efficiency, and environmental impact. Recent advancements in these technologies have significantly transformed thermal management practices in AI data centers, demonstrating a reduction of up to 50% in energy consumption while completely eliminating water usage in high-performance computing environments. We analyse recent innovations such as two-phase immersion cooling and advanced heat exchange systems, discussing their implementation in large-scale AI infrastructure. Additionally, the article examines the Closed Loop, Zero-Water Evaporation Design technique and its impact on Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE). The findings highlight the potential of these technologies to enhance sustainability and operational efficiency in data center cooling, offering a promising solution to the thermal management challenges posed by the growing demand for AI workloads.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.121

 

Published by: vikaspatanker

Authors: Ms. Rashmi, Professor Gaurav Aggarwal

Abstract: As technology advances, the development of lightweight yet secure encryption algorithms and improved key management strategies will play a crucial role in addressing emerging challenges. Ultimately, progressive encryption stands out as a vital component in fortifying cloud computing infrastructures against cyber threats, ensuring trust and reliability in the digital era.In this paper discussion will be made on the researches based on how we secure big data in cloud computing. Discussion of security algorithm has been made that are capable to secure data. Reduction of packet size using packet reduction logic leads to less space and time consumption. Mat lab based simulation will represent the working comparative analysis of time taken between tradition and proposed work after load balancing will conclude that proposed model will take less time. The main concentration of this research is towards the strategies of energy-efficient resource arrangement and security of data over cloud.

 

 

Published by: vikaspatanker

Authors: Assistant professor Mrs. R. Bhuvaneshwari, Ms. T. Misha

Abstract: Predicting house prices is both vital and complex due to the ever-changing nature of the real estate market. Conventional statistical approaches often fall short in identifying intricate data trends, making machine learning a more suitable solution. This project adopts the Support Vector Machine (SVM) algorithm to forecast housing prices by analyzing historical data and key market influences. Known for its ability to manage high-dimensional datasets and model nonlinear relationships, SVM proves to be a dependable method for accurate price prediction. The system evaluates multiple factors including geographic location, property dimensions, prevailing market trends, and economic conditions to improve prediction precision. Through SVM’s capabilities in both classification and regression, the model delivers strong, data-informed insights that assist homebuyers, sellers, and investors in navigating the dynamic real estate environment effectively.

Published by: vikaspatanker

Authors: Assistant professor Mrs. R. Bhuvaneshwari, Ms. T. Misha

Abstract: Predicting house prices is both vital and complex due to the ever-changing nature of the real estate market. Conventional statistical approaches often fall short in identifying intricate data trends, making machine learning a more suitable solution. This project adopts the Support Vector Machine (SVM) algorithm to forecast housing prices by analyzing historical data and key market influences. Known for its ability to manage high-dimensional datasets and model nonlinear relationships, SVM proves to be a dependable method for accurate price prediction. The system evaluates multiple factors including geographic location, property dimensions, prevailing market trends, and economic conditions to improve prediction precision. Through SVM’s capabilities in both classification and regression, the model delivers strong, data-informed insights that assist homebuyers, sellers, and investors in navigating the dynamic real estate environment effectively.

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Authors: Prabhu Prasad, Hemanth Kumar

 

 

Abstract: Venture capital plays a crucial role in accelerating the commercialization and scaling of nanotechnology innovations, bridging the gap between early-stage research and market-ready products. Nanotech ventures face unique challenges such as high R&D costs, complex manufacturing, regulatory uncertainties, and long development timelines, which require patient capital and strategic support. This article explores how venture capitalists evaluate, invest in, and actively support nanotech startups through specialized investment strategies, risk management, and ecosystem building. It highlights the evolving landscape of nanotech VC funding, the impact of venture capital on technological advancement, and emerging trends that will shape the future of this sector. By understanding the dynamics between venture capital and nanotechnology, entrepreneurs, investors, and policymakers can better harness funding mechanisms to foster innovation, economic growth, and societal benefits.

DOI: http://doi.org/10.61137/ijsret.vol.10.issue6.664

 

 

Published by: vikaspatanker

Authors: Assistant Professor Bharathi V, Divya Bairavi

Abstract: Quantum computing represents a paradigm shift from classical computing by leveraging the principles of quantum mechanics—superposition, entanglement, and quantum interference—to solve problems that were previously considered intractable. This chapter provides a comprehensive introduction to quantum computing, tracing its evolution from theoretical foundations laid by Feynman and Deutsch to landmark achievements such as Google’s demonstration of quantum supremacy. We explore the fundamental differences between classical bits and quantum bits (qubits), elucidating how quantum phenomena empower new algorithmic capabilities exemplified by Shor’s and Grover’s algorithms. The discussion highlights transformative applications across cryptography, optimization, molecular simulation, and artificial intelligence, emphasizing the disruptive potential of quantum machine learning and quantum neural networks. Despite its promise, quantum computing faces critical engineering and theoretical challenges, including qubit decoherence, error correction, and scalability. However, with rapid advancements in quantum hardware and algorithms, the technology is poised to redefine computing in the 21st century. This chapter invites readers to engage with the unfolding narrative of quantum computing, a frontier where science fiction converges with computational reality.

 

 

Published by: vikaspatanker