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: Control theory & CMOS. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

Face Super Resolution by Tangential and Exponential Kernel Weighted Regression Model

Abstract: The need of recognizing individual from the low resolution non-frontal picture is hard hassle in video surveillance. In an effort to alleviate the hassle of popularity in low decision photograph, literature presents unique strategies for face recognition after converting the low decision photograph to excessive resolution. For this reason, this paper provides a method for multi-view face video notable decision using the tangential and exponential kernel weighted regression model. In this paper, a brand new hybrid kernel is proposed to carry out non-parametric kernel regression version for estimation of neighbor pixel within the first-rate decision after the face detection is done the usage of Viola-Jones algorithms. The experimentation is finished with the U.S. Face video databases and the quantitative results are analyzed the usage of the SDME with the prevailing strategies. From the result final results, we prove that the most SDME of 77.3 db is obtained for the proposed approach compared with the existing techniques like, nearest interpolation, bicubic interpolation and bilinear interpolation.

Augmentation of sensitivity of FBG sensor using microwave photonics and nonlinear effect

Abstract: A simple and unique scheme of high sensitive Fiber Bragg Grating(FBG) interrogation system based on microwave signal measurement utilizing the concept of microwave photonics and nonlinear Four wave mixing(FWM), is proposed. The concept of FWM process is combined with microwave photonics to enhance the sensitivity of FBG sensor. The strain induced wavelength shift of the sensing FBG is translated to higher wavelength shift of the corresponding higher order FWM signals on either side of FBG sensor wavelength in opposite directions. Thus the wavelength separation between the FWM signals increases with small increase in strain. Utilizing the FWM effect and microwave photonics technique, the microwave phase difference is altered, which ultimately is converted to significant change in RF intensity. A novel mathematical relationship relating FWM, applied strain and the microwave power of the proposed scheme is established. A high strain sensitivity of 36.52 μV/με (26.67 μW/με) is attained using the proposed FWM and microwave photonics technique against initial sensitivity of 4.9 μV/με (0.48 μW/με) using only microwave photonics technique. The proposed scheme automatically compensates the temperature variations and eliminates the requirement of high dispersive component to enhance the sensitivity.

Dynamic Weighted Feature Subset Logistic Regression Model for Heart Disease Prediction

Abstract: Predicting heart disease is one of the medical industry's toughest challenges. Heart disease, also known as cardiovascular disease, is an umbrella term for a variety of conditions affecting the cardiovascular system. It is estimated that approximately one person dies every minute due to cardiovascular illness. Death from cardiovascular disease is the leading cause of mortality in the United States. Many forms of heart disease are both preventable and treatable. Early diagnosis can help in preventing unnecessary deaths and increasing the likelihood of survival. It takes data science to process the massive amounts of data generated by the healthcare sector. Since cardiac disease prediction is difficult, automation is required to minimise risks and provide early warning to the patient. In this article, different Machine Learning methods such as Multinomial, Support Vector Classifier and Logistic Regression are compared. As a result of the experimental findings, it is determined that Logistic Regression is the most accurate technique for detecting whether a person has heart disease or not, with an accuracy of 83 percent.

Essential Oils from Plants and Their Role in Nanomaterial Synthesis Characterization and Applications

Abstract: Many industries focussed on nanotechnology due to its application in various fields. Synthesis of nanomaterials by chemical and physical processes is expensive, release toxic substances into the environment, requires high energy and generates more waste. So biological sources are the best alternative for nanomaterial synthesis. There are several plants consisting of essential oils (EOs) that show antimicrobial, antiviral, anti-carcinogenic, anti-mutagenic and anti-inflammatory properties. They are used as active compounds in packaging food products and serve as natural additives in food materials, aromatherapy, cosmetic and medical industries. So synthesis of nanomaterials by plant parts is required as it is eco-friendly and sustainable. Synthesis of nanomaterials from plant EOs is more effective and eco-friendlier compared to nanomaterials made from physical and chemical processes. The present book chapter gives a detailed explanation on EOs from plant parts, its significance and synthesis of nanomaterials. It also highlights the characterization and application techniques of nanomaterial synthesized from the plant EOs.

Cognition-as-a-Service: Arbitrage Opportunity of Cognition Algorithms in Cloud Computing

Abstract: Present era of web services are evolving and extending its services with Cloud computing based remote mobile devices rapidly. The contact of the information world moving from programmable system era to cognitive systems era (Kelly III John E (2015) IBM Research Whitepaper on Cognitive computing, [1]). So the web users have high levels of expectations for the quality of interactions, accuracy of the results and the availability of the services. In the world of cognition and reasoning based web systems to answer the selected problems, to recommend a product information result in right ‘context’, we need more diverse reasoning strategies and on the fly strategies based intelligent Cognition Algorithms to supply Cognition-as-a-service to the cloud based web users. Here we summarize recent works and early findings such as: (1) How natural extension takes place in cognitive knowledge of dynamic web services. (2) How information processing time differs in between HDES and AES. (3) How arbitrage opportunity of cognition algorithm improves the frequency of exact findings in information search.