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Research Paper

AI-Driven Portfolio Optimization: Enhancing Investment Strategies Using Machine Learning

With the evolution of complexity in today’s markets and investment opportunities, traditional methods of appropriate multi-asset portfolio optimization have become insufficient, exposing the funds to overly large levels of risk. This paper addresses the question of how decision-making and investment strategies involving portfolios are assisted by artificial intelligence (AI) and, in particular, machine learning (ML). Everything, including processes such as supervised learning, unsupervised learning, and reinforcement learning, is studied in the context of critical tasks within portfolio management such as investment, risk, and trading strategies. A portfolio processed using AI reported an increase of 12% in predictive accuracy and a decrease of 20% in computation time for backtesting simulations. This was mainly due to well-developed noise filtering features that enable the model to operate in unstable market conditions. Even the key results show that in terms of risk-adjusted performance and managing uncertainty in the market, AI-based models are far better than traditional approaches. In addition, this research draws attention to emerging data sources and ethical AI, AI-based models and practices that further increase transparency, and AI methods associated with ethical concerns and data biases. These results demonstrate how something like AI stands to completely revolutionize the concept of investment and the strategies that accompany it, bringing about a form of change that is very much needed in today’s financial system.

Published by: Mariam Karanjia

Author: Mariam Karanjia

Paper ID: V10I6-1379

Paper Status: published

Published: December 6, 2024

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Research Paper

AI-Powered SEO: Revolutionizing Digital Marketing

Artificial Intelligence (AI) has redefined how digital marketing strategies are conceived and implemented, particularly in Search Engine Optimization (SEO). AI-driven tools now enhance SEO processes by offering predictive analytics, content generation, and advanced user behavior tracking. This paper explores the impact of AI on SEO, supported by statistical insights and real-world applications, and highlights the challenges and future trends associated with this technology.

Published by: Aakash V

Author: Aakash V

Paper ID: V10I6-1374

Paper Status: published

Published: December 6, 2024

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Research Paper

Real-Time Health Monitoring System of a Distribution Transformer

All Transformers are vital components of power systems, and their failure can significantly disrupt the balance of the entire system. Damage to transformers is often caused by overcurrent or excessive temperatures. This project aims to monitor the health of distribution transformers in real time to prevent such failures. Key parameters, including current, voltage, temperature, and oil level, are continuously monitored using sensors. The system leverages IoT technology, with a Wi-Fi module transmitting recorded data via the HTTP protocol, allowing remote access from anywhere. By automating this process, the system eliminates human error and enables quick responses to potential issues. Alerts are sent when parameters exceed predefined thresholds, helping prevent critical failures. The solution is scalable, adaptable to varying operational demands, and designed to enhance current monitoring practices. Data visualization and analysis are implemented using platforms such as ThingSpeak, which provides graphical representations of monitored parameters. Notifications are sent through IFTTT protocols, enabling timely and efficient maintenance responses. This real-time monitoring system ensures the reliable operation of distribution transformers, reduces manual intervention and improves overall efficiency. Its cost-effectiveness and versatility make it an ideal solution for modern power systems, offering a proactive approach to transformer health management.

Published by: Aman Kumar Singh, Devika Aggarwal, Aditya Sharma

Author: Aman Kumar Singh

Paper ID: V10I6-1373

Paper Status: published

Published: December 5, 2024

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Research Paper

A Survey on Improved Dehazing System for Underwater Night Light Fog Images Using Machine Learning Algorithm

The absorption of light in water and scattering leads to the degradation of images captured at night under the water. This degradation causes low brightness, diminished color, and distinguishable objects in the image affected by the night light. Many researchers worked to improve the images underwater during daylight using contrast stretching and the white balance method. The majority of investigations were done using white balance to reduce the greenish effect due to absorption of higher wavelength, which is reduced when propagated through water, this survey presents many works like guided filter transmission used as an edge-preserving smoothly operator and also “CLAHE” (“contrast limited adaptive histogram equalization”) & RGB model. These methods helped to change the intensity of the dehazed image and the level of contrast in the image. All these methodologies developed by the previous researchers were on the dehazing of daylight fog images. Hence, there is a scope for developing an improved dehazing of night light fog images.

Published by: Tamanna Pawar, Shridevi Soma

Author: Tamanna Pawar

Paper ID: V10I6-1362

Paper Status: published

Published: December 4, 2024

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Research Paper

Developing an EOG-Based Communication Interface for Quadriplegic Patients: Prototype, Signal Processing, and Algorithm Design

Electrooculography (EOG) is an electrophysiological signal that determines the human eye orientation and is therefore widely used in Human Tracking Interfaces (HCI). The purpose of this project is to develop a communication method for quadriplegic patients using EOG signals aimed at text and voice generation. The system consists of 3D eye movement tracking embedded using a custom-built prototype to measure the eyeball's left-right and up-down movements. The ESP32 board, which has a set of parameters to convert the data into content displayed on LCDs and MP3 players, is used to capture and process the signal. Helps people by facilitating more natural and efficient symptom expression. The blink system will be able to incorporate face masks and more eye tests as it continues to develop. Even if it might work, more research and clinical trials are needed to evaluate the system's usefulness and ensure that it performs as planned in real-world scenarios. With this project, assistive technology will make significant progress and improve the lives of many who suffer from severe motor impairments.

Published by: Aniket Raj, Amit Kumar

Author: Aniket Raj

Paper ID: V10I6-1342

Paper Status: published

Published: December 3, 2024

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Review Paper

Unemployment Trends in India

The increase in the young population due to demographic dividends or the rise in young people seems to be one of the sources of future economic growth in India. Although with the increase in school and college enrolment rates, the proportion of youth in the labor force has been declining their high proportions in the labor force indicate that the problem of youth unemployment and underemployment would remain a serious policy issue for many more years to come in India. During the last two & half decades, from 1983 to 2007-2008, it analyses labor and workforce participation rate trends. Unemployment, joblessness, working poor, growth and employment elasticities, etc. the poor employability of the workforce would hamper the advantages due to demographic dividend if measures are not taken to improve the educational attainment and skill development of the youth. The present paper has focused on the causes of unemployment, various types of unemployment, and possible measures have been suggested.

Published by: Sushmitha M, Deepu.M, Shalini.K, Aswini.B, Rehana Banu

Author: Sushmitha M

Paper ID: V10I5-1272

Paper Status: published

Published: December 3, 2024

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