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Survey Report

Survey on Removal of Rain or Snow From a Single Color Image

It is well-known that a bad weather, e.g., haze, rain, or snow, affects severely the quality of the captured images or videos, which consequently degrades the performance of many image processing and computer vision algorithms such as object detection, tracking, recognition, and surveillance. Rain/snow removal from a video or a single image has been an active research topic over the past decade. Today, it continues to draw attention to outdoor vision systems (e.g., surveillance) where the ultimate goal is to produce a clear and clean image or video. Here, the most critical task is to separate rain/snow components from the other part.

Published by: Binju Bentex, Dr. K S Angel Viji

Author: Binju Bentex

Paper ID: V4I1-1181

Paper Status: published

Published: January 9, 2018

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Case Study

Case Report-Post Cataract Surgery Herpes Simplex Keratitis and its Management

Herpes simplex keratitis (HSK) is a leading cause of corneal opacification and infection-related visual loss. Even though an individual may not have had the clinically apparent disease, high fever, immune-suppression, and sometimes surgery can reactivate latent herpes1. Its presentation can be distinctively divided into two types, epithelial keratitis or stromal keratitis due to a difference in pathogenesis, this inevitably postulates treatment difference. In this report, a case of postoperative herpes simplex virus (HSV) keratitis after a cataract surgery is described. The diagnosis and medical management of herpes simplex keratitis are discussed.

Published by: Dr. Nishant Vardhan

Author: Dr. Nishant Vardhan

Paper ID: V4I1-1179

Paper Status: published

Published: January 9, 2018

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Thesis

Test

Test Abstract

Published by: Manish, Rajesh, Ankit Singla, Shafina

Author: Manish

Paper ID: Z1T1-1125

Paper Status: approved

Submitted: January 9, 2018

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Research Paper

DNA Methylation Data Analytics in Cancer Research

Many studies demonstrated that the DNA methylation, which occurs in the context of a CpG, has strong correlation with diseases, including cancer. There is a strong interest in analyzing the DNA methylation data to find how to distinguish different subtypes of the tumor[1]. However, the conventional statistical methods are not suitable for analyzing the highly dimensional DNA methylation data with bounded support. DNA methylation is one of the most extensively studied epigenetic marks, and is known to be implicated in a wide range of biological processes, including chromosome instability, X-chromosome inactivation, cell differentiation, cancer progression and gene regulation[4]. Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. In order to explicitly capture the properties of the data, a deep neural network is used, which composes of several stacked binary restricted Boltzmann machines, to learn the low-dimensional deep features of the DNA methylation data.

Published by: Apoorva Patil, Rashmi A. Rane

Author: Apoorva Patil

Paper ID: V4I1-1161

Paper Status: published

Published: January 8, 2018

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Research Paper

A Study on the Volatility and Return with Reference to Stocks of Bank Nifty

Study on stock market trends has been an area of vast interest both for who wish to make a profit by trading stock in the stock market. India is one of the emerging economies, which has witnessed significant developments in the stock markets during the liberalization policy initiated by the government. However, investing in banking shares include high risks which can be guided but not controlled. The banking sector is the backbone of country’s economy. This sector has given very good return to the investors in the past. But the recent financial crisis has proved, that the Banking stocks tend to be more volatile than other stocks. This paper is a humble attempt to measure the volatility of the Bank index stocks and compare it with that of the volatility of NIFTY. Stock markets, in general, are considered volatile and volatility plays a key role in measuring the risk-return trade-offs. Estimating volatility enables the pricing of securities and, understanding stock market volatility or individual stock price volatility enables good decisions on the part of investors.  Investors who are risk-averse would not be happy to invest in a highly fluctuating stock, whereas those with a thirst for riskiness would happily invest in a highly volatile market. The study evaluates the performance of banking stocks mainly to identify the required rate of return and risk of a particular stock based upon different risk elements prevailing in the market and other economic factors.

Published by: Rohith U J

Author: Rohith U J

Paper ID: V4I1-1150

Paper Status: published

Published: January 8, 2018

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Survey Report

A Literature Survey on Intrusion Detection and Protection System using Data Mining

In the modern world of security many researchers have proposed various new approaches; among those techniques application of data mining for Intrusion detection is one of the best suitable approaches.The system proposes a security system, name the Intrusion Detection and Protection System (IDPS) at system call level, which creates the personal profile for the user to keep track of user usage habits as the forensic features. The IDP uses a local computational grid to detect malicious behavior in a real-time manner. In this paper, a security system, named the IDPS is proposed to detect insider attacker at SC level by using data mining and forensic techniques.

Published by: Chaitali Choure , Leena H. Patil

Author: Chaitali Choure

Paper ID: V4I1-1144

Paper Status: published

Published: January 8, 2018

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