Daily Archives: January 5, 2026

Authors: Dr. Pranav Mulaokar

Abstract: When interviewing the first year engineering students, it was observed that there is the urgent need to empower them with communication skills. This research paper focuses on the importance of communication, proficiency in English, concepts of LSRW, common mistakes, soft skills and global relevance. During the survey, the observations and recommendations were noted. English communication comes into light for international collaboration, technical documentation, workplace situations, etc. Real-life application of communication should be taught from the beginning of the learning process. The challenges which students face are discussed and solutions provided. The global scope of being a good communicator is noted in the paper.

Published by: vikaspatanker

Authors: Dr. Bangarappa L, Dr. Danappa G.T

Abstract: This present study has provided the fabrication of Mg/MWCNT nano composites, Mg/FA and Mg/MWCNT/FAhybrid nano composites with powder metallurgy processing techniques. The specimens prepared were characterized for mechanical properties like density of the materials, Vickers hardness, elastic modulus, and tensile properties. Nanocomposites are versatile material or multi-functional materials achieved by the unnatural mixture of verities of materials in turn to attain the characteristics in separate components by it that can’t be overcome. The extraordinary attention on carbon nano tubes were due to their unique structure and characteristics, they have a very tiny size of about 0.42nm and less than in diameter & the mechanical properties they exhibit. Carbon nanotubes have been expected to be one of the best reinforced materials to enhance the mechanical characterization as they possess good young’s modulus along with material strength and aspect ratios.

DOI:

Published by: vikaspatanker

Authors: Sukanya, G.Bharath Kumar, Karthik.D, Nikhil Reddy, ChannaKeshwa

Abstract: Crop diseases pose a major global threat to agricultural productivity, farmer income, and overall food security. Widespread disease outbreaks reduce crop quality, decrease yield, and contribute to economic instability—especially in regions dependent on agriculture for livelihood. The complexity of crop diseases arises from diverse environmental conditions, varying plant species, and the presence of multiple visually similar infections. Addressing these challenges requires a systematic, data-driven approach capable of identifying hidden patterns and supporting farmers and agricultural experts with timely, actionable insights. This project presents the design and development of an AI- Driven Crop Disease Prediction and Monitoring Dashboard, an interactive platform built using Streamlit. The dashboard enables visualization, prediction, and analysis of plant disease data using a trained Convolutional Neural Network (CNN). The system architecture is organized into three primary layers: the Presentation Layer, the Logic Layer, and the Data Layer. The Presentation Layer provides a user-friendly web interface developed in Streamlit, integrating dynamic components such as real-time prediction panels, probability bars, and comparative disease charts generated with Plotly Express. It also includes essential UI elements such as an image upload section and model output visualization to ensure smooth user interaction. The Logic Layer performs core analytical and computational tasks. It preprocesses leaf images, applies the CNN model for classification, generates confidence scores, and provides diseasespecific treatment recommendations. Pandas handles metadata processing, while session-state management ensures efficient handling of user inputs and outputs. The Data Layer consists of a structured plant disease dataset derived from sources such as PlantVillage, supplemented with augmented images to improve model robustness across lighting and environmental variations.

Published by: vikaspatanker