International Journal of Trend in Scientific Research and Development

In digitalized environment, heterogeneous users are host and deploy their applications as a digital transformation. As the growing of dynamic business requirements, the operational values of service level agility, scaling and availability of resources are the more focusing components. However, enterprises are needed to deliver the data with atmost desired security value to its genuineness users. All the client level processes are initiated by verifying the strong security level access parameters. So, it is important to process the data migration with the adopted cloud vendors. Lots of security breaches are causing the data level protection in the service access environment. The proposed work will implement the secured transformation users data, applications, and resources to the desired virtual set up in order to strengthen the customers application. The approach will be used to finding the service adoption by verifying the level of service guaranty with the cloud vendor adoption. 

Parallel computing is a type of computation in which many processing are performed concurrently often by dividing large problems into smaller ones that execute independently of each other. There are several different types of parallel computing. The first one is the shared memory architecture which harnesses the power of multiple processors and multiple cores on a single machine and uses threads of programs and shared memory to exchange data. The second type of parallel computing is the distributed architecture which harnesses the power of multiple machines in a networked environment and uses message passing to communicate processes actions to one another. This paper implements several computational algorithms using parallel programming techniques namely distributed message passing. The algorithms are Mandelbrot set, Bucket Sort, Monte Carlo, Grayscale Image Transformation, Array Summation, and Insertion Sort algorithms. All these algorithms are to be implemented using C .NET and tested in a parallel environment using the MPI.NET SDK and the DeinoMPI API. Experiments conducted showed that the proposed parallel algorithms have faster execution time than their sequential counterparts. As future work, the proposed algorithms are to be redesigned to operate on shared memory multi processor and multi core architectures. 

Due to the large use of MRI in hospitals, large storage areas are needed to store these images. Also, if you want to access these images over the system repeatedly, a large bandwidth is required. To solve this problem, it will be necessary to compress and store the medical imaging system quickly and without disruption. It has been seen that in the studies made on MRIs, the non-used regions NON-ROI occupy a large space and the image size can be reduced significantly when the unnecessary area in the image is cleaned. In this method developed with CUDA, the region of interest ROI in the MRI is detected by sending a 3x3 Kirsch filter matrix to the CUDA cores and the NON-ROI region is extracted from the image with CUDA. These operations are first executed by the serial application on CPU, then by a parallel application on GPU. As a result, the application running on the GPU produced 34 times faster results than the application on the CPU. When images are compressed with this new improved method, it takes up 89 less than the original image size and 15 less than the original compressed image. 

by Mahmut Ãœnver" ROI Determination and Compression in MRI Using Gradient Method with CUDA" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1, December 2018, 

One of the most important areas that use image processing is the health sector. In order to detect some diseases, the need to visualize a certain part of the patients body using medical imaging devices has emerged. This field in the health sector is the Radiology department. MR, Tomography, Ultrasound, X-ray, Echocardiography. Because of the importance of time in the health sector, GPU technologies are a technology that should be used in hospitals. Medical MRI images showed that the unused areas NON-ROI occupy a large area and this unnecessary area in the image could reduce the image size significantly. In this method developed with CUDA, the ROI Region of Interest region within the Medical MR images is determined by sending a 3X3 Kirsch filter matrix to the CUDA cores, and the NON-ROI region is extracted with CUDA from the image. It is then compressed with a new compression method developed. As a result of this method The parallel application with CUDA solves the problem 34 times faster than the sequential application for each image, while the compressed image takes up 90 less space than the original image size it takes 40 less space than the compressed size of the original image. 

by Mahmut Ãœnver | Atilla Ergüzen "Compressing of Magnetic Resonance Images with Cuda" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1, December 2018, 

In today's life everyone is busy and wants to save their time as much as possible. In weekends many people want to spend their days and evenings somewhere out from their home, but in weekends crowd are generally much more than usual days and hence it leads to wait for a long time. Even for taking parcel we have to wait for a longer time. 

Getting table and waiting for food after ordering will become a headache and create a challenging environment for managers of restaurants and hotels. If fortunately, we got table then we get bind to that restaurant's menu and items only whether we like it or not. In colleges sta?s are provided with coupons which is used as to- ken in canteen, but sometime it may be lost or tempered. It is also a very time-consuming process for sta? members and canteen management as well. Now we are coming with a great application with some interesting ideas and ingredients. 

It helps to reduce the time, e?orts, and resources for both vendors (Hotels and restaurants) and customers. Through this application we may able to pre-order our food, and will be able to view waiting period of table availability at that particular restaurant. Customers can select through choices of their food or restaurants nearby them, which will give them a large amount of ?exibility and options to worth their time spending at that place. 

by Nilesh Kumavat | Nikita Dhavan | Priyanka Patil "F.O.O.D - Food Ordering Online Desk" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018,