Category Archives: Uncategorized

Authors: Dheeraj Vaswani, Anushka Mane, Nikhil More, Sanjana Nitnware, Priyanka Patil, Anuradha Sangram Solanki

Abstract: Our research presents the design and im-plementation of an immersive Virtual Reality based educational system for learning about the Solar Sys-tem, enhanced with Generative Artificial Intelligence. Traditionally the spatial and dynamic relationships between celestial bodies aren’t conveyed effectively. Hence, to reduce this limitation, the system uses Unity D to create an interactive virtual reality environment where everyone can explore all celestial bodies in real time. The system also uses a Gemini Generative AI API to provide dynamic, context-aware explanations with respect to the level of knowledge of the learner. The combination of immersive visualization and adap-tive learning keeps students engaged, while making complex concepts feel natural and intuitive, rather than overwhelming. The system is also built on a scalable architecture, meaning future capabilities like performance tracking and intelligent assessments can be added without rebuilding from the ground up.

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Authors: Dr. Vinit Kumar Sharma, Aanchal Gupta

Abstract: Graph theory and network analysis are closely interconnected disciplines that play a crucial role in understanding complex systems. Graph theory provides the mathematical framework for representing entities and relationships, while network analysis applies these concepts to investigate structural and functional properties of real-world networks. This paper explores the relationship between graph theory and network analysis, discusses key graph-theoretic measures, examines applications across multiple domains, and identifies emerging research directions including graph neural networks and temporal networks. The study demonstrates that graph theory serves as the theoretical backbone of network analysis and continues to drive innovations in modern data science and artificial intelligence.

DOI: http://doi.org/10.5281/zenodo.20507775

Published by: vikaspatanker

Authors: Chetan Kumar Pandey, Dr. Alakhanda Rajawat

Abstract: The integration of artificial intelligence into international commercial arbitration is an indicator of a paradigm shift that disrupts the traditional pillars of the adjudicative process. This research paper examines how AI has evolved from a non-dominant administrative tool to a so-called silent arbitrator that takes control of the substantive substance of the arbitral mandate. The introduction of automation into global commerce means that institutions, such as the International Chamber of Commerce (ICC), the Singapore International Arbitration Centre (SIAC), and the Hong Kong International Arbitration Centre (HKIAC), face the challenge of efficiency and procedural due process. A thorough examination of the 2025 International Arbitration Survey shows that there is an increase in the utilisation of AI in fact-finding and document review, and that standpoints on applying AI to the execution of judgment and discretion remain strong. This paper analyses the regulatory response, including the European Union Artificial Intelligence Act and the proliferation of light regulations issued by the Silicon Valley Arbitration and Mediation Centre (SVAMC) and the Chartered Institute of Arbitrators (CIArb). In addition, the research considers the jurisprudential consequences of AI-aided awards observed in recent cases, including LaPaglia v. Valve Corp. It suggests guidelines to a strong regulatory system that ensures human control and maintains party independence.

DOI: https://doi.org/10.5281/zenodo.20507543

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Authors: Gulshama, Professor Subhashini Sharma

Abstract: This project studies in detail the harmful effects of atmospheric sulfur dioxide (SO₂) and acid rain on cement-based materials, which are widely used in construction activities such as buildings, bridges, and roads. These materials are continuously exposed to environmental conditions, especially in industrial and urban areas where pollution levels are significantly high. Among various pollutants, sulfur dioxide plays a major role in the formation of acid rain, which adversely affects the durability, strength, and overall performance of cement-based structures. The project further explains the chemical reactions involved in the formation of acid rain, where sulfur dioxide reacts with oxygen and water vapor present in the atmosphere to form sulfuric acid. This acid, when deposited on cement surfaces through rainfall, initiates a series of chemical reactions with important components of cement such as calcium hydroxide and calcium silicate compounds. These reactions lead to the formation of harmful products like gypsum and ettringite, which cause expansion, cracking, and gradual weakening of the material. In addition, this study describes the mechanism of degradation, including the penetration of acidic solutions into the pores of cement, internal stress development, and surface damage. The long-term effects include reduction in compressive strength, increased porosity, and structural instability of cement-based materials. Finally, the project also highlights various preventive measures to enhance durability, such as the use of sulfate-resistant cement, protective coatings, and control of environmental pollution. Overall, this study provides a clear understanding of the impact of acid rain on construction materials and suggests ways to improve their lifespan and performance.

DOI: https://doi.org/10.5281/zenodo.20506966

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Authors: Dr Vinit Kumar Sharma, Kanika

Abstract: Diophantine equations are polynomial equations in two or more variables whose solutions are restricted to integers. These equations are named after the ancient Greek mathematician Diophantus of Alexandria, who made significant contributions to number theory through his work Arithmetica. Diophantine equations play an important role in modern mathematics, cryptography, computer science, optimization, and algebraic geometry. Although Diophantine equations are a branch of pure number theory concerned with integer solutions of equations, they have several practical applications that affect everyday human life, often indirectly through technology and optimization.

DOI: http://doi.org/10.5281/zenodo.20503729

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Authors: Dr. Praveen B. Hulloli

Abstract: This Scientometric research study evaluates India’s research landscape in Biomedical within Science Artificial Intelligence (AI) from 2015 to 2024 (10 years). Utilizing data from the Web of Science (WoS), Analyzing a corpus of 622 publications and 10,359 citations, the research tracks the transition from a developmental phase to a high-impact era. Results from the Relative Quality Index (RQI) identify 2015, 2017, 2021, and 2022 as peak years for research excellence, while a subsequent dip in citation rates for 2023-2024 suggests challenges in sustaining global influence despite rising publication volumes. Journal productivity analysis reveals Computers in Biology and Medicine as the field leader with an h-index of 36.3. While top-tier journals maintain strong impacts, a score convergence of 18.1 among specialized outlets indicates a stabilizing, competitive ecosystem. The findings underscore the need for enhanced interdisciplinary collaboration to bridge the gap between quantitative growth and clinical utility, ensuring Indian AI research maintains consistent international academic prestige.

DOI: https://doi.org/10.5281/zenodo.20504166

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Authors: Mrs.J.Jaisy

Abstract: Gas turbines are among the most important energy conversion systems used in aerospace propulsion, power generation, and industrial applications. This paper presents a comprehensive review of turbine and compressor design principles, thermodynamic operation, cooling technologies, aerodynamic instabilities, and axial compressor design methodologies. Particular emphasis is placed on compressor staging, velocity-triangle analysis, turbine cooling methods, stall mechanisms, and surge phenomena. The paper synthesizes fundamental design approaches and provides a structured framework suitable for engineering education and preliminary turbomachinery design studies.

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Authors: He Weiyi, Md. Yeasin Arafat

Abstract: Artificial intelligence (AI) has become an important technology for improving customer engagement, personalized marketing, and operational efficiency in cross-border e-commerce platforms. With the rapid growth of digital commerce and online consumer activities, understanding customer purchasing behavior through AI-driven analytics has become increasingly valuable for modern business optimization. This research presents an AI-based consumer behavior analysis framework for cross-border e-commerce optimization using multiple real-world datasets, including customer demographic information, shopping behavior data, social media advertising interactions, recommendation system data, and online purchase intention records. The study applies machine learning models, including Random Forest and XGBoost, to predict customer purchase decisions and analyze factors influencing online consumer behavior. Data preprocessing, feature engineering, exploratory data analysis, and classification techniques were implemented using Python-based analytics tools. Experimental results demonstrate that AI-driven models can effectively predict purchasing behavior and identify important factors affecting customer engagement and online purchase intention. The findings indicate that customer browsing behavior, social media advertising interaction, recommendation systems, and demographic characteristics significantly influence cross-border e-commerce purchasing decisions. This research contributes to the development of intelligent digital commerce systems by integrating AI analytics, consumer behavior analysis, and recommendation-based optimization strategies. The proposed framework provides practical insights for improving customer targeting, personalized marketing, and operational performance in international e-commerce environments.

DOI: https://doi.org/10.5281/zenodo.20489885

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Authors: Riya Sharma, Prof. Abha Dubey

Abstract: Industrialization has significantly contributed to economic growth and modernization, but it has also emerged as a major source of environmental degradation. Industrial activities release a wide range of pollutants, including sulfur dioxide, nitrogen oxides, particulate matter, heavy metals, toxic chemicals, industrial effluents, and greenhouse gases, which adversely affect air, water, and soil quality. These pollutants disrupt natural ecosystems, alter biogeochemical cycles, and pose serious threats to human health and biodiversity. Air pollution from industries leads to problems such as acid rain, global warming, and respiratory diseases, while untreated industrial wastewater contaminates rivers and groundwater, causing toxicity to aquatic life and scarcity of safe drinking water. Soil pollution due to industrial waste disposal reduces soil fertility, agricultural productivity, and food safety. Environmental degradation resulting from industrial pollution directly challenges the goals of sustainable development, which aims to balance economic growth with environmental protection and social well-being. This study emphasizes the urgent need for sustainable industrial practices, including the adoption of cleaner production technologies, effective waste treatment, recycling, and strict implementation of environmental regulations. Promoting environmental awareness and corporate responsibility is equally important. Addressing industrial pollution is therefore essential to minimize environmental degradation and to ensure a sustainable and healthy future for present and coming generations.

DOI: https://doi.org/10.5281/zenodo.20488155

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Authors: Shimpe Kumari, Amrita Kumari, Balwant Singh, Dr. Balwant Singh

Abstract: Plastic pollution has emerged as a significant environmental challenge affecting freshwater ecosystems globally. This study investigated the effects of plastic pollution on freshwater ecosystems by assessing microplastic contamination and selected water quality parameters across different sampling sites exposed to varying levels of anthropogenic activities. A quantitative and descriptive research design was employed to evaluate the distribution, abundance, and ecological impacts of microplastics in freshwater environments. Water, sediment, and biological samples were collected using standardized sampling and laboratory procedures to identify and quantify plastic particles. Key physicochemical parameters, including dissolved oxygen, pH, and turbidity, were also analyzed to determine the relationship between plastic pollution and water quality. The findings revealed considerable spatial variation in microplastic concentration among the sampling sites. Highly urbanized and industrialized areas recorded elevated levels of contamination, with the highest concentration observed at Site F (390 particles/L), followed by Site C (340 particles/L). Sites with increased microplastic abundance also exhibited lower dissolved oxygen levels, higher turbidity, and slight reductions in pH, indicating ecological stress and deterioration of water quality. The study further showed that microplastics persist in freshwater environments and pose serious risks to aquatic organisms through ingestion, habitat alteration, and toxic chemical transfer within aquatic food webs. The study concludes that plastic pollution significantly threatens freshwater ecosystem health and biodiversity. Effective waste management strategies, environmental regulations, and continuous monitoring programs are therefore essential to reduce plastic contamination and protect freshwater resources.

DOI: http://doi.org/10.5281/zenodo.20487718

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