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| S.No | Particular | Page No. | |
|---|---|---|---|
| 1 |
Manish Chaudhari, Sachin Patel, Krupa VegdaAbstract: Amino acid derivatives of RNA & DNA bases constituent an important class of heterocyclic compounds. These organic syntheses organized in solvent phase with the help of microwave irradiation. |
|
1-10 |
| 2 |
Akshee Shivam, Dr. B.B. PradhanAbstract: The current research work focuses on laser beam machining (LBM) of AISI 4118 alloy steel. Laser beam machining is highly efficient advance machining process used to machine difficult to machine materials. |
|
11-26 |
| 3 |
Selvapriya. B, Raghu .BAbstract: Medical imaging is the technique and process of creating visual representations of the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues. |
|
32-42 |
| 4 |
Ramnath Shenoy, Tanul MaheshwariAbstract: Box Compression Strength (BCT) can be defined as the measure of the maximum compressive force per unit width that a paper board box can withstand during a compression test till it reaches the buckling stage. |
|
43-54 |
| 5 |
Nikita Thakur Dr. C.RAM SinglaAbstract: The ever-expanding realm of cloud computing, while offering unparalleled scalability and accessibility, presents a complex security landscape. Traditional security methods struggle to keep pace with the evolving nature of cyber threats. Here, machine learning (ML) emerges as a powerful tool, offering a new paradigm for securing cloud environments. This paper explores the potential of an ML-based security architecture for cloud computing. The core strength of ML lies in its ability to analyze vast amounts of data and identify patterns. In a cloud context, this translates to the ability to analyze network traffic, user behavior, and system logs to detect anomalies indicative of malicious activity. Anomaly detection algorithms can be trained on historical data containing known attacks, enabling them to recognize and flag suspicious patterns in real-time. This proactive approach significantly reduces the time it takes to identify and respond to threats. Furthermore, ML excels at threat prediction. By analyzing historical attack data and current network activity, ML models can predict the likelihood of specific attack types. This allows cloud providers to prioritize security measures and allocate resources more effectively. Additionally, ML can be used for behavior analysis, learning the typical usage patterns of authorized users. Deviations from these patterns, such as unusual access times or data downloads, could indicate compromised accounts, enabling faster incident response. |
|
70-78 |
| 6 |
S. Rinu SamAbstract: The synthesis of CdSnano particles was widely studied for their potential usage in the field of optics. Semi conductor nanoparticles doped with transition metal ions have attracted wide attention due to their excellent luminescent properties. |
|
55-69 |
