Published Papers
SUBJECT
Psychology - Neuroscience / Developmental / Cognitive / Learning & Memory

Scientific Journal
IJSRC - International Journal of Social Relevance & Concern
Name of Scholar
Saiesha Moparthi
Topic
A Systematic Review of The Impact of Music on Attention, Mood And Driving Behavior
About the Scholar
Saiesha is a student at The Gaudium School, Hyderabad, India.
Name of Mentor
Emily Beswick
PhD in Psychology - University of Edinburgh
BA (Hons) in Psychology - University of Edinburgh
Summary
The automobile is the primary mode of transport for most families, but automobile accidents remain the leading cause of death for children and young adults. The most common cause of automobile accidents is incorrect driver action and research aims to minimize the factors that contribute to this, specifically driver aggression and inattention. Music has been shown to have an impact on driving and may be a useful tool to help mitigate these behaviors that can increase the risk of automobile accidents. The aim of this study is to systematically review and summarize the current published literature on the impact of listening to music whilst driving on the driver’s behavior, mood and attention.
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SUBJECT
CS - AI / ML / Data Science / Quantum Computing / Blockchain / Computer Vision

Scientific Journal
IJSRST - International Journal of Scientific Research in Science and Technology
Name of Scholar
Pruthviraj Sunil Rajput
Topic
Exoplanet Detection Using Machine Learning : A Comparative Study Using Kepler Mission Data
About the Scholar
Pruthviraj is a student at Symbiosis International School, Pune, India.
Name of Mentor
Subhabrata Chaudhary
PhD in Engineering Science - University of Oxford
MSc in Computer Science - Saarland University, Germany
Summary
This work explores the application of machine learning to detect exoplanets from NASA’s Kepler mission. Our dataset comprises Kepler Objects of Interest (KOIs), encompassing their characteristic features and confirmed exoplanet status. We experiment with multiple supervised classification techniques including classical, tree-based, and neural methods. The best-performing model Histogram Gradient Boosting achieves a strong performance of 94.6% precision and 94.1% recall on a held-out dataset demonstrating the strong potential of integrating machine learning techniques into astronomy, potentially leading to new insights into planetary systems outside the solar system.
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SUBJECT
Economics - Micro / Macro / Developmental / Behavioral

Scientific Journal
IJSR - International Journal of Science and Research
Name of Scholar
Kavinkrishnan Gokulakrishnan
Topic
The Effect of Christmas on the Cryptocurrency Market with a Data Science Case Study
About the Scholar
Kavinkrishnan is a student at New Millenium School, Bahrain.
Name of Mentor
Damianos Michaelides
PhD in Statistics - University of Southampton
BSc, (Hons) in Mathematics, Operational Research, Statistics, Economics (MORSE) - University of Southampton
Summary
This paper investigates the impact of the Christmas period on the prices of five cryptocurrencies Bitcoin, Ethereum, Ripple, Litecoin and Dogecoin from 2017 to 2021 By employing statistical and data science analysis, the study aims to enhance the understanding of seasonality anomalies in the cryptocurrency market The results reveal significant price fluctuations during the Christmas period, highlighting the potential for seasonal effects in digital currencies.
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SUBJECT
Economics - Micro / Macro / Developmental / Behavioral

Scientific Journal
IJSRC - International Journal of Social Relevance & Concern
Name of Scholar
Aditi Shriram
Topic
The Externalities of Infrastructure Investment
About the Scholar
Aditi is a student at Don Bosco International School, Mumbai, India.
Name of Mentor
Ms. Sreevidya Ayyar
MRes/PhD in Economics (Pursuing) - London School of Economics and Political Science
MSc in Econometrics & Mathematical Economics - London School of Economics and Political Science
BA in Economics and Management - University of Oxford
Summary
In this paper, I analyze the relationship between infrastructure investment, environmental degradation and. I first present their theoretical link through the lens of the theory of externalities; in particular, investment in infrastructure is associated with a positive externality since infrastructure is a public good, but both the usage and the construction of infrastructure pose negative environmental externalities. I synthesize the relatively disparate literature on this topic, before jointly estimating these externalities using cross-country data. I find that a 1% increase in infrastructure investments is associated with a 1.04% increase in average GDP, and a 0.77% increase in greenhouse gas (GHGs) emissions. I find that a 1% higher tax rate on energy dampens the association of such investments on GHGs.
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SUBJECT
Economics - Micro / Macro / Developmental / Behavioral

Scientific Journal
IJSR - International Journal of Science and Research
Name of Scholar
Lakshya Batta
Topic
A Correlational Study on Income Inequality and Economic Growth
About the Scholar
Lakshya is a student at Canadian International School, Bangalore, India
Name of Mentor
Ms. Sreevidya Ayyar
MRes/PhD in Economics (Pursuing) - London School of Economics and Political Science
MSc in Econometrics & Mathematical Economics - London School of Economics and Political Science
BA in Economics and Management - University of Oxford
Summary
The relationship between income inequality and economic growth has been the subject of extensive theoretical debate, with varying predictions on whether inequality fosters or hinders growth. This study investigates the relationship between income inequality and economic growth using a fixed-effects model, estimated on cross-country data spanning from 1963 to 2015. The findings suggest a robust negative correlation between income inequality and economic growth, with stronger effects observed in more developed countries
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SUBJECT
Physics - Classical / Quantum / Superconductivity / Particle

Scientific Journal
IJSR - International Journal of Science and Research
Name of Scholar
Ritvika Tripathi
Topic
Comparative Study of Active and Passive Thermal Control Systems: A Case Study of Terra Satellite
About the Scholar
Ritvika is a student at GEMS Wellington International School, Dubai.
Name of Mentor
Imran Naved
DPhil in Engineering Science - University of Oxford
MEng in Engineering Science - University of Oxford
Summary
Space is an extreme environment, which can heat and cool rapidly. Therefore, satellites that must function in this harsh climate for prolonged periods can sustain damage to equipment and wiring if the isolated system of the satellites is not temperature regulated [1]. Therefore, all satellites launched into orbit in space have some form of the thermal control system, which ensures that the satellite is regulated at an ideal temperature for payloads [2] that work at lower temperatures and to prevent damage caused to physical structures, misalignment of optical systems etc. due to large temperature differences. Generally, two types of thermal control systems are integrated into satellites: active and passive systems. Active systems being thermal control systems that use moving fluids and mechanisms [3]. Conversely, passive methods do not have any mechanically moving fluids or parts [4]. The purpose of this study is to compare active and passive thermal control systems and assess their effectiveness for satellite applications through a case study of the Terra satellite. This study highlights the importance of efficient thermal management in satellites, balancing cost, energy consumption, and reliability for longterm missions.
