Vignan University

About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

Brain Tumor Segmentation of T1w MRI Images Based on Clustering Using Dimensionality Reduction Random Projection Technique.

Abstract: Background Early diagnosis of a brain tumor may increase life expectancy. If not diagnosed at an early stage, the brain tumor shortens the life expectancy of the diseased. Accompanied by several segmentation algorithms, Magnetic Resonance Imaging (MRI) preferred as a reliable assessment technique. The availability of high-dimensional medical image data during the identification procedure can place a heavy computational burden and require a suitable preprocessing step for lower-dimensional representation. At the same time, to reduce the storage requirement and complexity of the image data Random Projection Technique (RPT) is widely accepted as the multivariate approach for data reduction. Aims This paper mainly focuses on T1-weighted MRI images clustering for brain tumor segmentation with dimension reduction by using a conventional Principle Component Analysis (PCA) and RPT. Methods Two clustering algorithms, K-Means and Fuzzy C-Means, are used to detect the brain tumor. The primary objective is to present a comparison of two cluster methods between the PCA algorithm and RPT on MRIs. Apart from the original dimension of 512×512, the analysis used three other sizes, 256×256, 128×128, and 64×64, to study the effect of methods. Results As per the average reconstruction, Euclidean distance, and segmentation distance errors, the RPT attained better results as compared with PCA along with clustered images. According to the performance metrics, the RPT supported the Fuzzy C-Means algorithm in achieving the best clustering performance, and significant results for each resize of MRI images.

Gain Ratio as Attribute Selection Measure in Elegant Decision Tree to Predict Precipitation

Abstract: Prediction of precipitation is a necessary tool in meteorology. To date, it is technologically and scientifically a challenging task for scientists and researchers around the globe. Rainfall is a liquid form of precipitation that depends primarily on humidity, temperature, pressure, wind speed, dew point, and so on. Because rainfall depends on several parameters, its prediction becomes very complex. Approaches such as the back propagation, linear regression, support vector machine, Bayesian networks, and fuzzy logic can be applied, but their rate of prediction is very low, which leads to unpredictable results. This paper aims at improving the prediction of precipitation compared to Supervised Learning in Quest (SLIQ) decision trees, especially when datasets are large. Because SLIQ decision trees take more computational steps to find split points, they consume more time and thus cannot be applied to huge datasets. An elegant decision tree using gain ratio as an attribute selection measure is adopted, which increases the accuracy rate and decreases the computation time. This approach provides an average accuracy of 76.93% with a reduction of 63% in computational time over SLIQ decision trees.

Highly selective and sensitive detection of histidine by naked eye and fluorimetric method in aqueous medium via hydrogen bonding

Abstract: A new turn on fluorescent rhodamine dye primarily based probe was designed and synthesized. The dye suggests a sensitive detection of histidine at a variety of concentrations in aqueous medium by using fluorimetric method. The absorption and emission depth had been all at once changed upon the addition of histidine with probe, there is no change when addition of other competitors. The dye confirmed color change from colorless to pink during addition of histidine, which could be determined by naked eye. The Job’s plot indicated that the 1:1 binding ratio of probe with analyte. The probe shows the detection limit of histidine is 1.67 nM. The binding of probe with histidine was proven through NMR titrations, mass and strips method.

Modeling and multi response optimization of mechanical properties for E-glass/polyester composite using Taguchi-grey relational analysis:

Abstract: In the present work, E-glass/polyester composite laminates were manufactured in a customized resin transfer mould (RTM) with different layers of fiber at selected resin injection pressures. Experim...

SVIP-Enhanced Security Mechanism for SIP Based VoIP Systems and Its Issues

Abstract: As the SIP based VoIP system is entirely based on IP network, the vulnerabilities in it affects the VoIP system. This may result in degrading of quality of service in three aspects such as confidentiality, integrity and availability. This paper diagnose the security issues such as registration hijacking, session teardown, message tampering, IP spoofed flooding, disguised proxy and Spam over Internet Telephony (SPIT) and as well as the enhancements to improve the security mechanism to overcome the issues and to provide the quality of service to the legitimate users.