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Machine learning (ML) techniques are becoming more commonplace as a result of their utility in addressing complex issues in several contexts. Using ML methods in ultrasonic imaging applications is nothing new, but there has been a meteoric rise in research into this area over the last several years. Medical diagnostics and non-destructive assessment use ultrasonic imaging extensively, and both have benefited from the use of machine learning methods. In the former, which constitutes the bulk of the review, solutions that pertain to the detection/classification of material defects or specific patterns are reported, while in the latter, studies were categorised according to the body organ examined and the methodologyadopted. Finally, the study's analysis is summarised, and the key benefits of machine learning are explored..

The Campbell Dudek smith (CDS) algorithm was used to schedule the manufacturing process, with makespan optimization in mind, to create 12-inch pan goods, 14-inch griddle products, 16-inch griddle products, 18-inch griddle products, and 20-inch griddle products. The Campbell, Dudek, and Smith (CDS) algorithm is a flow shop TABLE-type scheduling approach that can reduce make span 2 machines in a series configuration by adapting Johnson's rule. The work results in a program that can autonomously plan the manufacturing of things by the machine. The testing revealed that a work order of 20 grids, 18 grids, 16 grids, and 12 grids resulted in a minimum makespan value of 210.12 minutes, assuming a total production of 12 pieces across all products with 6 repeats. Testing the application's accuracy revealed a rate of 99.99% the first time and 99.96% the second when compared to hand-computed values. Keywords: Optimization; production; scheduling; CDS; Makespan.

International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 09, September 2018, pp. 1589-1596, Article ID: IJMET_09_09_174 Available online at https://iaeme.com/Home/issue/IJMET?Volume=9&Issue=9 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 USE OF NEURAL NETWORKS FOR EMOTION AND OPINION MINING OF SPATIO-TEMPORAL DATA Navin Garg Department of Comp. Sc. & Info. Tech., Graphic Era Hill University, Dehradun, Uttarakhand, India 248002 Citation: Navin Garg, Use of neural networks for emotion and opinion mining of spatio-temporal data, International Journal of Mechanical Engineering and Technology (IJMET), 9(9), 2018, pp. 1589-1596. DOI: https://doi.org/10.17605/OSF.IO/BX47E

Signcryption techniques combine encryption and digital signature processes to reduce the overhead of doing these steps individually. This is why digital signatures are so important in systems where sensitive data has to be protected. Digital signatures based on elliptic curves may be used to increase application security at cheap cost. Experts are making every effort to make ECDSA more robust so that it can withstand a range of difficulties, despite the fact that it is the most novel of all asymmetric digital signature systems. If the signed message is intercepted and sent, the digital signature will not be able to stop a replay attack. The intruder may even forge the sender's digital signature in order to conceal their true identity. This method is an advancement in cryptography since it combines digital signatures and public encryption into a single system. Keywords: Cloud, Digital Signature, Enhanced Digital Signature, Elliptic Curve, Signing Process, Verification Process and Comparison.