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327 results on '"PRASAD, K. RAJENDRA"'

13. Positive Radial Solutions for an Iterative System of Nonlinear Elliptic Equations in an Annulus

Author

Khuddush, Mahammad and Prasad, K. Rajendra

Subjects
Mathematics - Analysis of PDEs, Mathematics - Classical Analysis and ODEs, 35J66, 35J60, 34B18, 47H10
Abstract

This paper deals with the existence of positive radial solutions to the iterative system of nonlinear elliptic equations of the form $$ \begin{aligned} \triangle{\mathtt{u}_{{\dot{\iota}} }}-\frac{(\mathtt{N}-2)^2r_0^{2\mathtt{N}-2}}{\vert x\vert^{2\mathtt{N}-2}}\mathtt{u}_{\dot{\iota}} +\ell(\vert x\vert)\mathtt{g}_{{\dot{\iota}} }(\mathtt{u}_{{\dot{\iota}} +1})=0,~\mathtt{R}_1<\vert x\vert<\mathtt{R}_2, \end{aligned} $$ where ${\dot{\iota}} \in\{1,2,3,\cdot\cdot\cdot,\mathtt{n}\},$ $ \mathtt{u}_1= \mathtt{u}_{\mathtt{n}+1},$ $\triangle{\mathtt{u}}=\mathtt{div}(\triangledown \mathtt{u}),$ $\mathtt{N}>2,$ $\ell=\prod_{i=1}^{m}\ell_i,$ each $\ell_i:(r_0,+\infty)\to(0,+\infty)$ is continuous, $r^{\mathtt{N}-1}\ell$ is integrable, and $\mathtt{g}_{\dot{\iota}} :[0,+\infty)\to\mathbb{R}$ is continuous, by an application of various fixed point theorems in a Banach space. Further, we also establish uniqueness of solution to the addressed system by using Rus's theorem in a complete metric space.

Published
2021

18. Effective texture features in mammogram images via multi-roi segmentation

Author

Prasad K. Rajendra, Praveen Kumar Chatakunta, Suneel Sajja, and Raghu Kumar Lingamallu

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

Digital mammography increasingly necessitates image segmentation for the purpose of dividing mammograms into individual slices. For the purpose of removing suspicious masses or tumours from mammograms, this process is carried out using a region of interest (ROI). More training photos are needed for mammography image classification, and these circumstances, ROI requires more processing time. The temporal complexity difficulties with the suggested multi-ROI method are the subject of this article. To show how effective the suggested multi-ROI is compared to the current segmentation approach, experiments are conducted on benchmarked datasets.

Published
2024
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19. Faster abnormality localization and recognition in a secured video bitstream by implementation of video encryption techniques

Author

Sivalakshmi Mallepogu, Prasad K. Rajendra, and Bindu Chigarapalle Shoba

Subjects
encryption, video processing, format-compliant encryption, video-decryption, anomaly detection., Engineering (General). Civil engineering (General), TA1-2040
Abstract

Cloud video storage uses an encrypted format to protect user data. It means encrypted video processing is an essential part of secured cloud storage. In order to detect suspicious or anomalous behavior, video surveillance must have encrypted cloud access. The primary goals of this research are to estimate parameters and detect abnormalities in an encrypted video bitstream. Various typical properties of video encoding frameworks and format-compliant encryption algorithms are investigated to identify abnormalities in an encrypted video bitstream using format-compliant encryption. The encrypted bitstream is decrypted to get three different kinds of enhancement features: the sizes of macroblocks, partitions of macroblocks, and the magnitude of the motion vector. The identification and localization methods now do not include video decryption or complete decompression. The proposed strategy has been created to implement the video encryption scheme efficiently and is compatible with various video encryption techniques. The experimental findings demonstrate that, in comparison to other methods, the proposed approach provides optimal running time and detection rate performance.

Published
2024
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30. Exploring and Designing of Data Warehouse in Coal

Author

Kumar, N. Vijay, Prasad, K. Rajendra, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Kumar, Amit, editor, Paprzycki, Marcin, editor, and Gunjan, Vinit Kumar, editor

Published
2020
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34. Big Data Sentiment Analysis Using Distributed Computing Approach

Author

Prasad, K. Rajendra, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bapi, Raju Surampudi, editor, Rao, Koppula Srinivas, editor, and Prasad, Munaga V. N. K., editor

Published
2019
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41. Develop extended visual methods for an effective clusters assessment of large datasets.

Author

Prasad, K. Rajendra, Basha, M. Suleman, Kumar, M. Kalyan, Reddy, K. Shivaram, Prakash, G. Jaya, and Lokesh, G.

Subjects
*EUCLIDEAN distance, *BLACKBERRIES, *INTERNET of things, *SOCIAL media, *ALGORITHMS
Abstract

Nowadays, smartphones, IoT (Internet of Things) devices, and social media produce massive amounts of data. To control this massive amount of data, we have to arrange the extensive data in groups called clusters. We have to apply some algorithms to the raw data to form the clusters. For this, we surveyed some algorithms for accessing the number of clusters (also called cluster tendency). Some of the existing algorithms to form Clusters are VAT (Visual Assessment Tendency), iVAT(improved Visual Assessment Tendency), inc-VAT(Increment Visual Assessment Tendency), inc-iVAT(Increment improved Visual Assessment Tendency), dec-VAT(Decrement Visual Assessment Tendency), dec-iVAT(Decrement improved Visual Assessment Tendency). These algorithms showed the number of clusters visually in the form of square-shaped dark blocks along the diagonal. A number of square-shaped dark-colored blocks indicate the value of cluster tendency. For small datasets, the above algorithms will work well, but for large datasets, the clustering accuracy decreases, and processing time increases. To overcome this problem, we are proposing a system with extended ideas of the state-of-the-art of visual methods. In the proposed work, visual algorithms are designed with cosine-metric for better assessment of cluster tendency rather than a normal Euclidean distance. In our system, we are using COSINE-based distance instead of Euclidean Distance to form the clusters on raw data, and also, we are verifying the clustering accuracy and processing time by using the existing algorithms with the help of COSINE based distance measures. The experiments are conducted on benchmarked large datasets for demonstrating and comparing the efficiency of proposed and existing visual clustering methods. [ABSTRACT FROM AUTHOR]

Published
2023
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