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.

Study on Moisture Behavior Properties of Milkweed and Milkweed/Cotton Blended Sanitary Napkins

Abstract: Menstrual hygiene is one of the most important health-related aspects which must be given higher priority to overcome the menstrual cycle period of women. Currently, there are many types of sanitar...

An extensive survey on traditional and deep learning-based face sketch synthesis models

Abstract: In recent days, Face sketch synthesis (FSS) attracts various researchers for sketching the images to retrieve faces and in multimedia applications. The intention of FSS is to create a sketch for the image provided from a collection of sketch and photo images as the training set. Presently, the rise of deep learning (DL) models becomes useful in FSS because of its diverse benefits. As the FSS is employed in various applications, detailed experimentation to analyze the state of the art approaches methods is nontrivial. Though numerous FSS approaches are available, there is no review paper exist regarding the hierarchical classification of DL based FSS. Keeping this in mind, in this paper, we provide an extensive review of the available DL as well as conventional FSS techniques. We made a clear classification of the FSS techniques, and these are categorized into data-driven and model-driven methods. A comparative analysis of the reviewed techniques is made based on various aspects such as the objective, algorithms used, benefits, and performance measures.

Segmentation of Lungs from Chest X Rays Using Firefly Optimized Fuzzy C-Means and Level Set Algorithm

Abstract: Segmentation of lungs from chest x ray is a non trivial task required as a preprocessing step for detection of different diseases like cardiomelagy, tuberculosis, pneumonia High accuracy in segmentation of lung results in high accuracy of detection of diseases from lungs For the past four decades multiple techniques were proposed for automatic segmentation of lungs In this paper, we propose a hybrid segmentation technique based on firefly optimized fuzzy c-means clustering algorithm The output of the fuzzy c-means is given to level set to finalize the segmentation of the lungs The performance of the proposed technique is evaluated using two public chest x ray datasets: JRST and Montgomery County JRST contains 247 chest x-rays and MC dataset contains 138 chest x-rays The Jaccard coefficient for the proposed segmentation technique is 951 which is on par with the state of art segmentation techniques

Improvement of transient stability in microgrids using RSFCL with series active power filter

Abstract: Now a day’s non-conventional energy sources like PV power and Wind power sources are well developed because conventional energy sources are reduced day by day and at the same time the population has been increased. These drawbacks can be overcome by developing the microgrids. In current trends, microgrid protection is a very challenging task. Due to the interconnection of several distributed generators, fault currents are produced. Resistive type superconducting fault current limiter is used for the protection of microgrids because its operating time is very less, it stops the abnormal currents with in the first cycle and continuity of supply is possible. But R-SFCL had some disadvantages, it is not compensated for the reactive power. Then voltage levels are not compensated, for that reason series active power filters are used along with R-SFCL. Here series active power filters are compensating the voltage magnitudes and reduce the harmonics and then transient stability is improved in the microgrids. This work is done using MATLAB/Simulink.

A Gini Index Based Elegant Decision Tree Classifier to Predict Precipitation

Abstract: Water is one of the most important of nature's gifts to the living creatures on Earth. Rainfall is one form of precipitation, and it primarily depends on humidity, temperature, pressure, wind speed, dew point, and so on. The present research is focused on using the gini index as an attribute selection measure in an elegant decision tree to predict precipitation for voluminous datasets. This study aims at improving the prediction of precipitation over the supervised learning in a Quest decision tree, especially when the datasets are large. A decision tree using the gini index increases the accuracy rate while decreasing computational time by reducing the computation of total split points. This approach provides an average accuracy of 72.98% with a reduction of 63% in computational time over a SLIQ decision tree.