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Leveraging Data Analytics in Investment Banking: Transforming Insights into Strategic Decisions

Data analytics has become extremely important for modern-day businesses, especially banks. Most of the information in banks is stored in computers as Big data. Analysing this data allows the banks to function efficiently and smoothly. There are various data analytics categories in banking, such as descriptive, diagnostic, prescriptive and predictive analytics. Data analytics has various advantages and challenges. So, an organisation may face various challenges like privacy regulations not allowing the organisation to analyse data freely, technical & architectural challenges, etc. For data analytics to be helpful for the company, it needs to be applied effectively; this can be done by asking practical questions to the software while analysing data or by making the data analysis platform easier for less skilled employees. Various tests, such as the T-test and regression model, play a key role in analysing data. Various companies have capitalised on data analysis by developing software and platforms focusing solely on data analysis. These companies use these platforms to other companies as a service they charge for. The biggest data analysis and investment research company is Bloomberg.

Published by: Aryaman Jolly

Author: Aryaman Jolly

Paper ID: V11I1-1352

Paper Status: published

Published: February 11, 2025

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Research Paper

Advancing Girls’ Education In Underprivileged Societies

Girls' education in underprivileged societies remains a critical issue that significantly impacts socioeconomic development, gender equality, and poverty alleviation. This paper explores the challenges and opportunities associated with advancing girls' education, emphasizing its role in empowerment, breaking the cycle of poverty, improving health outcomes, reducing child marriage, lowering fertility rates, promoting gender equality, fostering economic growth, enhancing social development, reducing gender-based violence, and creating global impact. Various socio-cultural, economic, and political barriers prevent girls from accessing quality education, perpetuating inequality and hindering national progress. By analyzing the existing challenges and proposing strategic interventions, this study highlights the need for holistic policy measures, financial investments, and community engagement to bridge the gender education gap. The findings suggest that empowering girls through education can lead to transformative changes, benefiting individuals and society at large (UNESCO, 2021; UNICEF, 2020).

Published by: Tanvi Garodia

Author: Tanvi Garodia

Paper ID: V11I1-1322

Paper Status: published

Published: February 10, 2025

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Research Paper

Nano-Enhanced Hydrophobic Coating with ZnO Nanoparticles for Preserving Cultural Heritage Building

Preserving outdoor heritage assets is an ongoing challenge in heritage conservation. The purpose of applying preservative coatings is to improve the hydrophobicity of exposed surfaces of building materials and protect against pollutants, microbiological growths, and especially the effects of rainwater. A good protective coating significantly lowers water absorption, maintains high water-vapor permeability, penetrates deeply, is UV light resistant, offers sufficient breathability, and is environmentally friendly. Polysiloxanes and their precursors have been widely used to protect stone surfaces. To avoid degradation or other modifications to the treated surfaces, the treatment's safety and effectiveness must be evaluated before being directly applied to historical materials. In the past, several nanoparticles were developed and tested to improve the functionality of these coatings. The initial protective layer is made of a solvent-based substance called silane-siloxane, which has poor adherence. As a result, water can partially wash off dirt, pollutants, and microbial colonies. The hydrophobicity of protective coating materials made of ZnO nanoparticles is substantially superior. Photocatalytic coatings can oxidize organic materials on surfaces. Pollutant particles and any other dry deposition were quickly and thoroughly removed by rainwater from protective coatings made of nanoparticles.

Published by: Dr. Vimal Kumar Jaiswal, Dr. S. Vinodh Kumar, Dr. M. K. Bhatnagar

Author: Dr. Vimal Kumar Jaiswal

Paper ID: V11I1-1337

Paper Status: published

Published: February 9, 2025

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Research Paper

Social Determinants Of Saving

This comprehensive research paper explores the complex landscape of household saving behaviors, moving beyond traditional economic models by integrating psychological, sociological, and economic perspectives. By examining the complex interplay of social determinants, this study employs a mixed-methods approach, incorporating quantitative data from national surveys and qualitative insights through interviews and case studies to provide a nuanced understanding of financial decision-making processes that shape individual and collective saving strategies.

Published by: Ayera Jain

Author: Ayera Jain

Paper ID: V11I1-1334

Paper Status: published

Published: February 8, 2025

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Review Paper

Trada – An AI-Driven Trading Assistant and Stock Analysis Service

The stock market poses significant challenges for traders and investors due to fragmented access to essential data and insights. Navigating multiple platforms to gather real-time data, historical trends, and financial information leads to inefficiencies and missed opportunities. Trada is an AI-driven trading assistant that centralizes stock analysis, providing users with real-time data and personalized buy/sell recommendations in one platform. By leveraging advanced machine learning algorithms such as ARIMA, LSTM, EMA, and XGBoost, Trada delivers predictive stock analysis and actionable insights. LLaMA enhances the platform's ability to summarize financial reports, helping users make informed trading decisions without the need to rely on multiple resources.

Published by: Rutuja Jamale, Aatish Jawalkar, Samruddhi Duse, Omkar Chole, Prachi Sorte

Author: Rutuja Jamale

Paper ID: V11I1-1332

Paper Status: published

Published: February 6, 2025

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Research Paper

Refined Detection of Knee Osteoarthritis Using Center Net with a Pixel-Wise Voting Approach

This paper introduces an advanced approach for detecting Knee Osteoarthritis (OA) using an optimized CenterNet framework integrated with a pixel-wise voting strategy. Early and accurate detection of knee OA is vital for timely intervention and efficient disease management. The proposed method enhances the CenterNet architecture—a leading object detection framework—by incorporating a pixel-based voting mechanism, which leverages local image data to improve detection accuracy. Each pixel contributes to determining whether it belongs to an object or the background, and this aggregated information enables precise identification of objects and their locations. Experiments conducted on a publicly available knee OA dataset demonstrate that the proposed method outperforms existing techniques, achieving state-of-the-art results. The integration of CenterNet with the pixel-wise voting strategy holds significant promise in aiding clinicians with early diagnosis and treatment planning for knee OA patients.

Published by: Usha Kumari V, Abhishek S, Ajay R, Karnan K, Asim Ulla Khan

Author: Usha Kumari V

Paper ID: V11I1-1318

Paper Status: published

Published: February 4, 2025

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