Volume- 2, Issue- 1, Page- 30 to 39
A cybersecurity area that focuses on college students, digital citizens of our time, who play an important role in determining the future of cybersecurity. It focuses on the unique challenges college students face, from identity theft to cyber and sensitive data security. This report examines best practices and methods for building college students’ online barriers
Volume- 11, Issue- 2, Page- 11 to 2
Root-knot nematodes, (RKN) are obligatory endoparasites of over 3000 plant species, causing $70 billion in annual economic losses globally. The second stage juveniles hatch from the eggs invade the root apex and inject pathogen effectors that induce specialized feeding cell called Giants cell that are large multinucleated cell formed, due to repeated cycles of mitosis
Volume- 14, Issue- 1, Page- 1 to 12
The proposed paper is discussed about the “integration of IoT in smart grid” which has been elevated facilitating new ideas in order to facilitate developments of infrastructure for electric power. IoT has been a very important tool for power grids which makes them smarter and advanced as compared to traditional power grids. This paper focuses
Volume- 11, Issue- 01, Page- 29 to 44
In the dynamic landscape of cybersecurity, organizations confront increasingly intricate cyber threats that necessitate sophisticated security measures.
Volume- 2, Issue- 1, Page- 11 to 23
Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related
Volume- 10, Issue- 3, Page- 1 to 10
Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related
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