Daily Archives: June 15, 2025

Authors: LOKESWARAN. V, SHANMUGAVADIVU. M

Abstract: Protease enzymes play an important role in many biological processes, including protein digestion, cell signals and protective mechanisms. In this study, the isolation, refining and partial characteristics of the protease enzyme of Guava (Psidium Guajava) have been studied. Dry guava leaves are homogeneous and extracted by raw enzymes using phosphate stamps. The activity of the protease has been determined by the digestion of casein and raw enzyme extract refined by precipitating in ammonium sulfate. The specific activity of pure protease enzyme is significantly higher than the rough extract. The enzyme is characterized by its pH, its optimal temperature and stability, showing the maximum operation at pH 4 and 60° C. In addition, the molecular weight of the protease enzyme is about 135 kda. In addition, the ability to decrease protein enzyme shows its ability to apply in soft meat, hydrolysed protein in food processing and remove points in laundry detergent. This study emphasized that the promising potential of guava panels is a profitable and environmentally friendly biological substance for industrial applications, especially in the fields of food and detergents. Add in -Depth on its complete enzyme records and its industrial scale is reasonable

DOI: http://doi.org/

Published by: vikaspatanker

Authors: Dr.Pranesh Kulkarni ., Assistant Professor Department of Mathematics

Abstract: Mathematics is a fundamental component of Data Science, providing the theoretical foundations for many data analysis and Machine learning techniques. A breakdown of the fundamental math field required for data Science, Linear Algebra, Calculus, and Probability Theory. Through mathematics we can learn data analysis and visualization in this we learn plotting, charting and data storytelling.in this Article we discussed structuring and designing of mathematics in data science this provides a Comprehensive framework for understanding the mathematical foundations. Data analysis and visualizations, machine learning And modeling, and mathematical techniques used in data science. Being a data scientist is more than just using plug-and- play machine learning packages. Educators have to understand what the algorithm is actually doing first and foremost and know when and why to use it. The process to learn what the algorithms are doing is by studying the underlying mathematics. We know that Geometry and graph theory form essential pillars of data science, it providing tools to model, analyze, and visualize complex relationship. These mathematical concepts enable data scientists to efficiently uncover patterns, optimize systems, and efficiently represent intricate datasets. Now, I know “Big Data” and “Hadoop” have become a bit of a big deal in the data world and are being thrown around like a cool fad, but it feels like a lot of people still don’t really understand the concept behind it. In this article I’ve covered the why and what of Open-source software how does it all actually work? Data is essential for ML- enabled systems. Poor data will result in inaccurate predictions, which are referred to in the ML context as “garbage in, garbage out”. Hence, ML requires high-quality input data. From the viewpoint of RE, it is clear that data constitutes a new type of requirements Based on the Data Quality model defined in the standard ISO/IEC 25012, we elaborate on the data Perspective.

DOI: http://doi.org/10.5281/zenodo.15833884

Published by: vikaspatanker

Authors: Dr. Rajul Misra, Mr. Saurabh Saxena, Abhishek Singh,, Tushar Chauhan, Anit kumar

Abstract: This report presents a comprehensive study on Wireless Power Transmission (WPT), a groundbreaking technology that facilitates the transfer of electrical energy without the need for physical connectors or wires. The project explores various methodologies, including inductive coupling, resonant inductive coupling, and advanced techniques such as beam forming and UV-assisted wireless charging. The primary objective is to design an efficient WPT system capable of delivering power over varying distances while addressing challenges related to efficiency, range limitations, and safety standards. Through experimental evaluations, the project demonstrates that resonant inductive coupling enhances energy transfer efficiency and extends operational range compared to traditional methods. Additionally, the integration of innovative techniques like quasi-static cavity resonance allows for simultaneous charging of multiple devices. The findings indicate that while WPT systems hold significant promise for applications in consumer electronics, electric vehicles, and medical devices, ongoing research is essential to overcome existing challenges and facilitate widespread adoption. This study contributes valuable insights into the development of wireless energy transmission technologies and their potential impact on various industries

DOI: http://doi.org/

Published by: vikaspatanker