Anubhav Tewari

ORCID: 0009-0004-7764-0345
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About
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Research Areas
  • Entrepreneurship Studies and Influences
  • Energy Efficient Wireless Sensor Networks
  • Endometrial and Cervical Cancer Treatments
  • Video Surveillance and Tracking Methods
  • Cancer survivorship and care
  • Family Business Performance and Succession
  • Mechanical and Thermal Properties Analysis
  • International Business and FDI
  • Indoor and Outdoor Localization Technologies
  • Face and Expression Recognition
  • Sports Dynamics and Biomechanics
  • Advanced Neural Network Applications
  • Colorectal and Anal Carcinomas
  • Sports Analytics and Performance
  • Video Analysis and Summarization
  • Fatigue and fracture mechanics
  • Engineering Structural Analysis Methods
  • IoT-based Smart Home Systems

Presidency University
2022

The University of Sydney
2018

Shri Mata Vaishno Devi University
2015

This study explores how entrepreneurial attitudes and intentions are influenced by supportive social norms education (EE), integrating social, cognitive, educational perspectives. Analyzing 704 Indian commerce students using confirmatory factor analysis, Analysis of Moment Structures (AMOS), Hayes's Statistical Package for Social Sciences PROCESS macro, it finds that attitude (EA) mediates the effect on intentions, moderated education. The findings suggest EE mitigates negative effects...

10.1080/26437015.2025.2467086 article EN Journal of the International Council for Small Business 2025-03-25

Abstract In this research paper we propose a model of Wireless Sensor Networksused for pre-detection disasters. Here have discussed the basic architecture WSNs and how these can be used in disaster management. The major reasons mass destruction are Earthquake Tsunami. Millions lives lost owing to these. Disaster, it natural or man-made has catastrophic impact on lives, money infrastructure. We do not sensitive system yet which provides pre detection calamities. Therefore need take serious...

10.1016/j.procs.2015.04.240 article EN Procedia Computer Science 2015-01-01

10.11127/ijammc.2016.09.09 article EN International Journal of Advanced Materials Manufacturing and Characterization 2016-08-01

Detecting and localizing objects in real-time with enhanced speed accuracy remain a challenging task. Object detection its applications have been highly researched topic due to various obstacles like the lack of computational power, limited data, deformations viewpoint variations, many more, but or is most significant all. There seems be trade-off between accuracy, an increase leads decrease vice versa. To enhance using deep learning machine approach simplest way find solution where...

10.1109/mlcss57186.2022.00058 article EN 2022-08-01
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