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.

Dynamics of Respiratory Microbiome Profiles Contributes to Imbalance and Lung Dysbiosis in the Respiratory Tract

Abstract: Lungs and the other regions of respiratory tract are not sterile. Respiratory system consists of separate and balanced microbial communities called respiratory microbiome. Respiratory microbiome is the set of diverse microbial communities residing on the mucosal surface of respiratory tract. The presence of microbiota in respiratory tract is identified by 16S rRNA amplicon sequencing and the diversity of microbes in the respiratory tract was clearly understood. Microbiome equilibrium is maintained in healthy state of an individual. The composition of microbiome gets altered during disease. During health conditions the shape of microbiome is maintained by three detrimental factors: microbial immigration, emigration, and relative reproduction of microbes. Sometimes balance among these three factors is disturbed and the constancy of microbiota is affected. This condition is called as respiratory dysbiosis. There are certain factors such as smoking, antibiotics, chronic respiratory disorders (CRDs), and lung transplantation that contribute to imbalance and dynamic change of microbiome in respiratory tract. In this chapter, we discussed briefly the changes in microbial communities in response to these factors.

A Study on Class Imbalancing Feature Selection and Ensembles on Software Reliability Prediction

Abstract: Software quality can be improved by early software defect prediction models. However, class imbalance due to under representation of defects and the irrelevant metrics used to predict them are two major challenges that hinder the model performance. This article presents a new two-stage framework of Ensemble of Hybrid Feature selection (EHF) with Weighted Support Vector Machine Boosting (WSVMBoost), which further enhance the model performance. The EHF is the ensemble feature ranking of feature selection models such as filters and embedded models to select the relevant metrics. The classification ensembles, namely Random Forest, RUSBoost, WSVMBoost, and the base learners, namely Decision Tree, and SVM are also explored in this study using five software reliability datasets. From the statistical tests, EHF with WSVMBoost attained best mean rank in terms of performance than the rest of the feature selection hybrids in predicting the software defects. Additionally, this study has shown that both McCabe and Hasalted method level metrics are equally important in improving the model performance.

Image Retrieval System Based on Perceptual Browsing Component Using Interactive Genetic Algorithm

Abstract: The most recent upgrades in digital imaging and computing innovation brought on a quick development of advanced media in the individualized computing and media outlet. Moreover, vast accumulations of such information as of now exist in various logical application spaces, for example medical imaging and geographical information system (GIS). Overseeing expansive accumulations of multimedia information require the advancement of new tools and technologies. A system for retrieving images PC framework for surfing, testing and recuperating images from substantial databases that are used to store and manage digital images. Keeping in mind the end goal to surge in the rightness of image retrieval, the descriptor contains a perceptual browsing component (PBC) which is realized by employing an algorithm based on GA which is interactive in nature and is advertised. PBC system contains color, edge, and texture as primitive low-level image descriptors. The proposed system does the recovery mechanism in two phases. In the first phase, query image is considered for getting feature descriptors and they are taken out. Thus, it is further used to compare against the images available within the database. In the development stage, highly relevant images are identified and arranged. Thus, the proposed GA-based approach can provide close results to users. The experimental evaluation is made using a database of color images which is named UCI dataset. The empirical results revealed that the proposed system is used in retrieving highly relevant images.

Performance Optimization of LANMAR Routing Protocol in Mobile Ad Hoc Network Using DoE

Abstract: A MANET is a team of remote versatile devices or nodes that structure a system to trade data even with the lack of permanent network infrastructure. All the nodes work with the help of battery power. The efficient energy consumption is a main challenge in MANET which indeed affects the operational life of a MANET. So, the aim of this paper is to discover the most significant factor that is responsible for high energy consumption. The routing protocols’ performance is examined using simulation where one-factor-at-a-time (OFAT) approach is promoted. But, in reality, multiple factors affect the performance. But, design of experiments (DOE) approach lets many input factors to be experimented and tested in parallel that affect required output (response). This paper highlights the benefits of using Taguchi design of experiments approach to optimize the Landmark Routing Protocol in MANETs in terms of total energy consumption, control overhead and throughput. MANETs perform subjective to the design of the routing protocols and its configurable parametric values. The specific required network scenarios are simulated using EXata simulator/emulator. To recognize the most significant factor that affects the responses, Analysis of Variance (ANOVA) is applied, and the possible best factor-level combination is found using the signal-to-noise ratio analysis. ANOVA highlighted that the fisheye scope followed by fisheye update interval has the greatest impact on the responses. Later, by fine-tuning the most significant factor in the dynamic network environment, it is observed that LANMAR Routing Protocol performed better.

Implementation of Reversible Arithmetic and Logical Unit and Its BILBO Testing

Abstract: Reversible logic is gaining more importance day by day, because of its feature of low power dissipation which is the basic need in designing nano electronic devices, bioinformatics, low power CMOS designs and quantum computing. Reversible logic is one which realizes n-input n-output functions that map each possible input vector to a unique output vector. It is a promising computer design paradigm for constructing arithmetic and logic units which are the basic building blocks of computer that do not dissipate heat. After designing a system, it is also equal important to test it. In this paper reversible ALU (Arithmetic and Logical Unit) performing four operations (Addition, Multiplication, Subtraction and Bit wise- AND) is implemented and the simulated results like power consumed, delay and area obtained are compared with that of conventional ALU. Testing is also done on proposed reversible ALU by using BILBO (Built—in Logic Block Observer) blocks, which was the first BIST (Built-in Self Test) architecture to be proposed and undergo wide spread use. The proposed reversible ALU is implemented and simulated using Verilog HDL in Xilinx 13.4 version.