Manjushree Nayak

Manjushree Nayak is Assistant Professor in NIST Institute of Science and Technology, Odisha, India. Worked in MSIT Department of MATS University Raipur(C.G.) for six years .She has 18 year experience of work in academic and Administration. She has completed her Ph.D. in Computer Application and IT. She has completed her MCA, PGDCA. Her area of interest is Bigdata, Machine Learning, Soft computing, Wireless networking, Deep Learning, Data Analytics. She has published two books in Lambert publication. She has published more than 25 papers in national and international journals. She has presented papers in national and international conferences, Life members in Indian Science congress and International Association of Engineers.

Publications

Empowering Safety: A Deep Dive Into AI and Machine Learning Solutions for Women's Security
Empowering Safety: A Deep Dive Into AI and Machine Learning Solutions for Women's Security
Omkar Pattnaik, Manjushree Nayak, Sasmita Pani, Rahul Kumar, Bhisham Sharma. © 2024. 11 pages.
In an era characterized by technological innovation, the imperative to address women's security concerns has found a powerful ally in the realms of artificial intelligence...
Precision Profiling: The Microeconomic Dynamics of Small Business Tax Optimization Through Digital Twins and Blockchain
Precision Profiling: The Microeconomic Dynamics of Small Business Tax Optimization Through Digital Twins and Blockchain
Manjushree Nayak, Shreekta Pattnayak, Subham Sharma, Omkar Pattnaik. © 2024. 19 pages.
In the current economic landscape, small businesses play a significant role in global economies, making it essential to understand the dynamics of tax optimization for sustaining...
An AI-Based Efficient Model for the Classification of Traffic Signals Using Convolutional Neural Network
An AI-Based Efficient Model for the Classification of Traffic Signals Using Convolutional Neural Network
Manjushree Nayak, Ashish Kumar Dass, Sapna Singh Kshatri. © 2023. 16 pages.
The objective of this study is to build a model for the classification of traffic signs available in the image into many categories using a CNN and Keras library to detect the...