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Review Paper

CropSense: An Integrated Web App to Simulate an ML/DL-Based Decision Support System for Precision Farming and Agriculture

This review explores the integration of machine learning (ML) and deep learning (DL) technologies in precision farming, highlighting the potential of web applications to improve agricultural decision-making through crop and fertilizer recommendations, disease detection, and aerial farm analysis. Precision farming technologies support sustainable agricultural practices by enabling real-time, data-driven insights for optimized resource use and yield enhancement. This review assesses various ML/DL models and their applications, including CNN-based disease detection and recommendation systems that utilize decision trees, neural networks, and satellite data analysis. Key challenges such as data quality, scalability, and security are discussed, along with future directions, including advancements in edge computing and federated learning. By identifying current limitations and prospective improvements, this paper aims to contribute to the development of comprehensive, scalable solutions that are accessible and effective for diverse farming environments.

Published by: Adrian Mathew Aloysius, Dave Joseph Pinto, Narjit Leishangthem, Mohammed Affan, Mr. Shyam Dev R S, Dr. D Roja Ramani

Author: Adrian Mathew Aloysius

Paper ID: V10I6-1514

Paper Status: published

Published: December 31, 2024

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Research Paper

Silicon Dielectric Resonator Antenna

Any wireless network essentially requires an antenna for the network to enable wireless communication. In this paper, a silicon based dielectric resonator antenna, exciting in Hybrid mode, is presented for such applications. The proposed CDRA is designed to operate at 2GHz and simulated at the same center frequency to obtain perfect radiation patterns. This paper gives the key concept of DRA and also, a single element CDRA made with silicon is shown along with some measurement results. The proposed CDRA has the desired patterns, and various other parameters such as Return loss, Gain, Polarization, etc., are further discussed here. The CDRA is simulated in Ansys HFSS, successfully and then fabricated to verify the parameters.

Published by: Badavath Maniratnam Naik

Author: Badavath Maniratnam Naik

Paper ID: V10I6-1497

Paper Status: published

Published: December 31, 2024

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Research Paper

Machine Learning-Based Collaborative Filtering Book Recommendation System

The project aims to develop a book recommendation system tailored to support and inspire individuals with an interest in reading. Leveraging a collaborative filtering approach that incorporates collaborative filtering based on K-nearest neighbors (KNN) the system identifies similarities among users or items based on their book interactions and book ratings. Through meticulous dataset preprocessing, including feature extraction of genre, author, and user preferences, the system ensures high-quality recommendations. Evaluation metrics such as precision and recall gauge system performance, while a user-friendly interface provides easy access to personalized book suggestions. Continuous user feedback drives ongoing improvements, fostering a culture of reading discovery and habit cultivation. Ultimately, the deployment of this system aims to encourage individuals to explore new literary works and develop a lifelong passion for reading.

Published by: Vatsalya Maddu, P.Jusmitha, S.Lilly, K.Sai Sri, D.Janvitha Padma, T.Devika, N.V. Muralikrishna Raja

Author: Vatsalya Maddu

Paper ID: V10I6-1523

Paper Status: published

Published: December 31, 2024

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Research Paper

The Major Values of a Great Leader

Effective leadership is a cornerstone of organizational success, and the qualities that define a great leader extend beyond skills and technical expertise. This article explores the eight major values that contribute to great leadership: integrity, vision, empathy, courage, humility, accountability, commitment to growth, and gratitude. Each of these values plays a pivotal role in shaping leaders who inspire trust, foster collaboration, and drive sustained success. Through an analysis of these values, this paper offers insights into how leaders can cultivate these principles to create a thriving and motivated team environment.

Published by: Somsubhra Ganguly

Author: Somsubhra Ganguly

Paper ID: V10I6-1517

Paper Status: published

Published: December 30, 2024

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Research Paper

Assessment of Yield Parameters in Sweet Flag (Acorus calamus L.) Germplasm Under Northern Dry Zone of Karnataka

The present investigation was carried out to evaluate the mean performances of sweet flag (Acorus calamus L.) accessions collected from different parts of India. The experiment was conducted at the College of Horticulture, Munirabad, Karnataka. A total of ten sweet flag accessions were evaluated with three replications in a Randomized Complete Block Design. Significant variation was observed among all the accessions with respect to growth, yield and yield-attributing characters. The mean performance of accessions for yield attributing characters revealed that accession SF6 - Hosur village (Vijayanagara) performed well among the ten accessions which recorded maximum fresh weight of rhizomes (29.16 q/ha), dry weight of rhizomes (15.63 q/ha), dry recovery (46.94 %) and maximum oil content (6.10 %). Hence, the Hosur village collection can be recommended for commercial cultivation in Karnataka and can also be utilized in further breeding programmes.

Published by: Rajeshwari Nidagundi, Yogeshappa H, Shobha H, Somappa Jaggal

Author: Rajeshwari Nidagundi

Paper ID: V10I6-1505

Paper Status: published

Published: December 30, 2024

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Research Paper

AI-Based Video Authenticity Checker: Detecting Manipulated Videos Using CNN and LSTM Architectures

The rapid-fire increase in videotape content across digital platforms has boosted the need for effective results to decry manipulated videos. These include deepfakes and other phonies, which pose significant pitfalls to digital trust and security. This paper introduces a new approach, the" AI videotape Authenticity Checker," which employs a mongrel deep literacy frame. The model utilizes Convolutional Neural Networks( CNNs) for spatial analysis and Long Short-Term Memory( LSTM) networks for temporal analysis, furnishing a robust result for detecting fake vids. By preprocessing videotape data to regularize quality and format, the system ensures high trustability and scalability. Experimental results on standard datasets demonstrate a delicacy of 92, a perfection of 90, a recall of 91, and an F1-score of 90.5, showcasing its eventuality for real-world operations. This scalable and effective tool represents a critical advancement in videotape phoney discovery.

Published by: Jakku Kumarswami, Gorli Laxmi

Author: Jakku Kumarswami

Paper ID: V10I6-1507

Paper Status: published

Published: December 30, 2024

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