Multi-mode Routing Mechanism with Cryptographic Techniques and Reduction of Packet Drop Using 2ACK Scheme MANETs

Narayana, V. Lakshman; Bharathi, C. R.

doi:10.1007/978-981-13-1921-1_63

Cited by 10 publications

(12 citation statements)

References 3 publications

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“…In spite of the fact that they achieved higher precision contrasted and the other nearby network discovery strategies, however because of high time unpredictability of their methodology, it isn't adaptable in discovering networks in huge informal communities. Seed-driven methodology isn't constrained to the neighborhood network location issue [14]. An OSN is formally spoken to by a diagram, where hubs are clients and edges are connections that can be either coordinated or not relying upon how the SNS oversees connections [15].…”

Section: Related Workmentioning

confidence: 99%

Certified Node Frequency in Social Network Using Parallel Diffusion Methods

Gopi¹,

Narayana²,

Venkatesh³

et al. 2019

ISI

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Informal community examination is one of the key zones of research amid present day times. The informal community is developing with more clients and the ties between them step by step. It has two parts: separating the versatile interpersonal organization into a few networks by considering data dispersion and choosing networks to discover persuasive hubs by a dynamic programming. A dynamic engendering model considering each the overall quality and individual fascination of the talk is given upheld sensible situation for sure, inside and out totally not the same as existing issues with impact decrease. Specifically, every center is distributed a versatility time limit. If the piece time of each customer outperforms that edge, the utility of the framework will decrease. Our proposed technique can discover new networks dependent on the past structure of the system without recomposing them sans preparation. We present an overview of agent techniques managing these issues and propose a scientific categorization that outlines the best in class. The goal is to give a thorough investigation and guide of existing endeavors around data dissemination in informal communities. The proposed calculation utilizes parallel preparing motor to determine this postpone issue in the present situation. The calculation in parallel discovers the prevalent seed set in the system and extends it in parallel to discover the network. Test results on the engineered and true informal organizations show that our strategy is both viable and proficient in finding networks in unique interpersonal organizations.

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Section: Related Workmentioning

confidence: 99%

Certified Node Frequency in Social Network Using Parallel Diffusion Methods

Gopi¹,

Narayana²,

Venkatesh³

et al. 2019

ISI

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“…The unlabeled data is given to the classifier in order to predict the class-label of the unlabeled instance [17]. Classification can be performed on structured or unstructured data [18]. The goal of classification is to identify the category where new data comes under.…”

Section: 6 Represents the Schematic Representation Of Classificationmentioning

confidence: 99%

Machine Learning Methodology for Medical Data Analysis for Prediction of Risk

Sravanthi¹,

Harika²,

Archana³

et al. 2020

jcr

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Mining data is a nontrivial procedure of finding information from a large volume of data. Such information can be helpful in settling on significant choices. Medical data show special features including noise coming about because of human just as methodical blunders, missing qualities and even meager conditions. The nature of data has huge ramifications for the nature of the mining results. Medical data classification is important to perform preprocessing steps so as to expel or at least lighten a portion of the issues related with medical data. Clustering is a descriptive-based data mining task. The clustering algorithm is also called as unsupervised learning algorithm that learns the unlabeled dataset and groups or clusters the instances based on their similarity and builds the clustering model. Clustering is same as classification in which data is grouped, but in this, groups are not predefined. In clustering, clusters are not predefined. Classification of different types of clustering is as follows: Hierarchical clustering, Partition clustering, Categorical clustering, Density based clustering and Grid based clustering. The main intension of the research is to classify the medical data with high accuracy value. In order to achieve promising results, a novel data classification methods have been designed that utilize a Improved Cluster Optimal Classifier (ICOC). The proposed method is compared with traditional methods and the results show that the proposed method performance is better and accurate.

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“…Detection of glaucoma in iris and performance analysis is presented in proposed method. Glaucoma detection method is explained in methodology section [23]. Results and performance analysis reports are listed in result section.…”

Section: Hari Krishna Kanagala Vvjayarama Krishnaiahmentioning

confidence: 99%

“…It is just prepared dependent on force and not focused on the cup limit. To beat this issue, neural retinal cup discovery [23] is utilized to improve the precision of limit estimation. Circle fitting was performed for acquired plate limit and curved body was utilized for choosing highlight focuses around neural-retina cup district.…”

Section: Literature Surveymentioning

confidence: 99%

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Identification of Glaucoma using Structural Modifications of Retina Images with AM Segmentation Method

Kanagala*¹,

Krishnaiah²

2019

IJRTE

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Abstract: Glaucoma is the second driving reason for blindness after waterfalls and its identification is basic to anticipate visual harm. Glaucoma is the third driving reason for blindness in India. The structure composed, will have the capacity to help in early discovery and conclusion of glaucoma utilizing AM segmentation and Cup to Disk Ratio (CDR) are used for the accurately detected of Glaucoma. Optic disk and optic cup diameter is measured by region props technique. Drive database is used for analyzing the proposed work. Structural parameters are measure to check the structural variation with the help of bench mark image. Report said, due to glaucoma, its structure get varies. Hence, helping ophthalmologist in prior location of glaucoma which will help the general public thus to fight the quiet enemy of vision.

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Multi-mode Routing Mechanism with Cryptographic Techniques and Reduction of Packet Drop Using 2ACK Scheme MANETs

Cited by 10 publications

References 3 publications

Certified Node Frequency in Social Network Using Parallel Diffusion Methods

Certified Node Frequency in Social Network Using Parallel Diffusion Methods

Machine Learning Methodology for Medical Data Analysis for Prediction of Risk

Identification of Glaucoma using Structural Modifications of Retina Images with AM Segmentation Method

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