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Research Paper

AFBAP : Attention For Binding Affinity Prediction

This paper introduces the AFBAP model, a novel machine learning model that leverages transfer learning benefits from pre-trained transformers ProtBert and ChemBERTa for feature extraction, and utilises a CNN-based prediction module prefaced by a task-adaptive feature transformation to predict protein-ligand binding affinity with state-of-the-art accuracy. It accepts one-dimensional sequential inputs for both proteins and ligands, in the form of amino acid strings and SMILES strings respectively. AFBAP’s performance over a number of datasets using standard evaluation metrics validates the fact that the model achieves higher accuracy with lower training times and lower compute. AFBAP democratizes access to computational methods of optimizing drug discovery, paving the way for rapid and accessible innovation in drug discovery research.

Published by: Harihar Prasad

Author: Harihar Prasad

Paper ID: V10I5-1386

Paper Status: published

Published: October 27, 2024

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Case Study

Building a Comprehensive Enterprise Data Lake Architecture

Organizations need to be driven by “data” more than ever to stay ahead of the curve and be competitive. With the tremendous data growth of data both by volume as well as variety, it is no longer sustainable to store the data in traditional data warehouses as they are not designed to be scalable. Data lake architecture which is typically built on top of cheap hardware is the most economically viable solution for this problem as they are elastic and can scale up based on the increasing data needs of an organization. While the solution might seemingly look straightforward there are many nuances associated with this shift in paradigm and a very careful and thoroughly thought through design is necessary when building an enterprise data lake architecture. This white paper explores various aspects related to setting up a comprehensive enterprise data lake which can steer towards the success of the organization. It also touches up on the pit falls and opportunities based on the research and case studies relevant in this area. Finally, a summary and outlook on data lake management is presented to the readers.

Published by: Ramla Suhra

Author: Ramla Suhra

Paper ID: V10I5-1324

Paper Status: published

Published: October 25, 2024

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Review Paper

Crops and Weeds Detection System using Machine Learning

Weeds are one of the most harmful agricultural pests for crops. For the waste of crops, Weeds are highly responsible. For the solution of this problem research community as build up a crops and weeds detection system. This technology is build up by using Machine learning. In this paper, we present a literature review on current state-of-the-art ML techniques for weed detection. Our study presents a detailed analysis of ML.

Published by: Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava

Author: Shrusti Jasani

Paper ID: V10I5-1372

Paper Status: published

Published: October 25, 2024

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Case Study

A Study on Circular Economy and its Influence on Economic Development

The circular economy is clearly beneficial to sustainability efforts, but it also offers economic benefits to organizations. Moreover, consumers are increasingly demanding more sustainable practices from the brands with which they interact, and expect to see positive outcomes for the planet through their purchases. The innovation to enable circularity will drive new opportunities for growth, greater resource security and sustainability and a more competitive economy. However, the circular economy model could provide a strong framework for development and a basis for setting principles to guide business innovation, policy, and education. Therefore, the paper largely focuses on the circular economy and its growth on economic development and the methodology of the study is purely based on the secondary data.

Published by: P. Sree Devi

Author: P. Sree Devi

Paper ID: V10I5-1377

Paper Status: published

Published: October 25, 2024

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Research Paper

Preliminary Investigations for Iron Ore Occurrences in Warangal District, Telangana

The mining of iron ore, an essential raw material for Iron & Steel Industry is arguably of prime importance among all mining activities undertaken by any country. India is amongst the leading producers as well as exporters of iron ore in the world. Iron ore deposits occur within the Pakhals in the area around Bayyaram and also in the adjacent area comprising of Dharwars. The deposits present in the Pakhals are exposed, generally on the hills comprising of ferruginous Sandstones and shale. Iron ore deposits of considerable importance, occurring at Motla Timmapur (170 41’’: 800 07) ; Bayyaram (170 58’ 00”) 800 11’ 00”) & Irslapuram (170 36’00” ; 800 8’ 45’’). Preliminary geological prospecting carried out to know the available resources.

Published by: Kadari Suresh, D Rajitha, A Narsing Rao

Author: Kadari Suresh

Paper ID: V10I5-1376

Paper Status: published

Published: October 24, 2024

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Research Paper

Energy Storage Method: Superconducting Magnetic Energy Storage

Abstract - Magnetic Energy Storage (SMES) is a highly efficient technology for storing power in a magnetic field created by the flow of direct current through a superconducting coil. SMES has fast energy response times, high efficiency, and many charge-discharge cycles. These qualities make SMES a good candidate for smoothing power fluctuations and enhancing grid resilience, as well as providing better stability for renewable energy systems. This paper covers the fundamental concepts of SMES, its advantages over conventional energy storage systems, its comparison with other energy storage technologies, and some technical and economic challenges related to its widespread deployment in renewable energy. The prospects for SMEs contributing to a more sustainable and efficient energy infrastructure are also considered.

Published by: Thinalisha M, Yogesh Vk, Subanesh V, Bindu

Author: Thinalisha M

Paper ID: V10I5-1302

Paper Status: published

Published: October 24, 2024

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