Category Archives: Uncategorized

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.

 

 

Published by: vikaspatanker

Authors:

 

 

Abstract:

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.

Published by: vikaspatanker

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

Authors: Sandhya Kumari, Manohar Jain, Selva Kumar

 

 

Abstract: Digital platforms have emerged as powerful catalysts in accelerating startup ecosystems by providing entrepreneurs with unprecedented access to markets, funding, collaboration, and resources. By lowering traditional barriers to entry, enabling rapid scalability, and fostering vibrant communities, these platforms have transformed how startups are conceived, launched, and grown. This article examines the multifaceted role digital platforms play in enhancing market reach, facilitating funding through crowdfunding and online angel networks, and building global entrepreneurial networks. It also addresses challenges such as digital inequality, data privacy concerns, and regulatory complexities that startups and ecosystem stakeholders must navigate. Highlighting case studies of successful platform-enabled startups and ecosystems, the article explores future trends driven by emerging technologies like artificial intelligence, blockchain, and the Internet of Things, which promise to further evolve platform capabilities. Policymakers, investors, and entrepreneurs alike must understand and strategically leverage digital platforms to foster inclusive, resilient, and innovative startup ecosystems that drive economic growth and technological progress worldwide.

DOI: http://doi.org/10.61137/ijsret.vol.10.issue6.663

 

 

Published by: vikaspatanker

Authors: Hemanth Kumar, Mamathu U

 

 

Abstract: The supply chain landscape of the 21st century is undergoing a profound transformation driven by the synergistic forces of automation, globalization, and sustainability. As businesses face unprecedented challenges and opportunities in an increasingly complex global market, supply chains have evolved from traditional logistical operations into strategic frameworks critical to resilience, agility, and long-term growth. Automation technologies—such as robotics, AI, and the Internet of Things—have redefined efficiency and responsiveness, while digital globalization has prompted companies to reconfigure sourcing models to balance cost-effectiveness with resilience. At the same time, sustainability has emerged as a core imperative, reshaping supply chains to prioritize environmental responsibility, ethical labor practices, and circular economy principles. This article examines how these three pillars—automation, globalization, and sustainability—interact to reshape modern supply networks. It highlights the benefits and risks associated with new technologies, explores the strategic reorientation of global operations, and underscores the importance of ethical and sustainable practices. Through this comprehensive analysis, the article offers a forward-looking perspective on how companies can build adaptive, transparent, and values-driven supply chains to remain competitive in the evolving business landscape. By aligning operational excellence with societal and environmental goals, organizations can transform their supply chains into engines of innovation, resilience, and sustainable value creation.

DOI: http://doi.org/10.61137/ijsret.vol.10.issue6.662

 

 

Published by: vikaspatanker