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In Vitro Antioxidant Potential of Pure Fractions of Eclipta Alba

Abstract–Oxidative stress and Ultraviolet (UV) irradiation-induced skin damage, is involved in numerous diseases. Eclipta alba which belongs to Asteraceae family is used traditionally in ayurvedic system of medicine in India for the treatment of liver diseases. Our study shows that water extract of E. alba has a potent effect in scavenging 1, 1-diphenyl-2-picrylhydrazyl (DPPH), chelating ferrous ion, and superoxide radicals, exhibiting IC50 values of 0.21 mg/mL, 1.20 mg/mL, and .49 mg/mL, respectively. Identification and quantification of the wedelolactone, one of the active constituents of the Eclipta alba plant extract, was carried out by HPLC analysis. The result of the present study indicates that the Eclipta alba extract shows a high amount of ascorbic acid, tannins, flavonoids, phenolics, contents. The hydroalcoholic extract of Eclipta alba effectively scavenged free radicals at all different concentrations and showed potent antioxidant potency. Eclipta alba extract shows antioxidative properties.

Published by: Anjali Singh, Ayodhya Singh, Vandana Dwivedi

Author: Anjali Singh

Paper ID: V3I1-1366

Paper Status: published

Published: February 20, 2017

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Research Paper

Advanced Fuzzy Logic based Image Watermarking Technique for Medical Images

The segmentation algorithms vary for the types of medical images such as MRI, CT, US, etc. The current study work can further be extended to develop a GUI tool based approach for separating the ROI. Additionally, a new technique of separating ROI from the original image that will be applicable for all type of medical images can be evolved. Separated ROI can be stored with min, xmax, ymin and ymax value so that at the end of embedding process before transmitting watermarked image, the segmented ROI can be attached with watermarked image. Any medical image watermarking approach will be suitable, if we segment the ROI from the medical image with the four values, then embedding of the watermark can be done on whole medical image, in this paperwork on a different scan like ctscan ,brain scan etc. our results significant high than other.

Published by: Kamalpreet Kaur, Er. Suppandeep Kaur

Author: Kamalpreet Kaur

Paper ID: V3I1-1365

Paper Status: published

Published: February 20, 2017

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Smart Grid Technology for Intelligent Power Use

The existing Power Grids is antiquated, congested and inefficient in many ways and it does not take full advantage of new automation technologies that for example can prevent an outage or restore power much faster after an outage. It does not take advantage of new materials which can make the equipment throughout the grid more efficient. It was not designed for integrating large amounts of renewable energy generation into the grid which is necessary in order to reduce greenhouse gas emissions and prevent climatic changes. This paper proposes a method for better implementation of smart grids that integrates technologies of advanced sensing, control methodologies and communication capabilities into the current power grids at both the transmission level and distribution levels.

Published by: Aniket Jambukar, Mr. Rohith Prakash

Author: Aniket Jambukar

Paper ID: V3I1-1364

Paper Status: published

Published: February 20, 2017

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Human Depth Perception

We introduce the perceptual issues relevant to seeing three dimensions in digital imagery. Technological constraints like limited field-of-view and spatial resolution prevent the display of images that match the real world in all respects. Therefore, only some elements of real world depth perception are utilized when viewing 3D CGI. Depth Cue Theory is the main theory of depth perception. It states that different sources of information, or depth cues, combine to give a viewer the 3D layout of a scene. Alternatively, the Ecological Theory takes a generalized approach to depth perception. It states that the HVS relies on more than the image on the retina; it requires an examination of the entire state of the viewer and their surroundings (i.e., the context of viewing). In this paper, we rely on Depth Cue Theory, although we acknowledge the importance of visual context where appropriate. As seen later, the type of visual environment and the viewer’s task play a significant part in the effectiveness of a 3D VDS. Both theories assert that there are some basic sources of information about 3D layout. These are generally divided into three types: pictorial, coulometer and stereo depth cues. The perceptual process by which these cues combine to form a sense of depth is a complicated and outdebated issue. Different approaches to measuring the ability to perceive depth have also been posited. We discuss these issues with respect to CGI.

Published by: Ajit Kumar Sharma, Kiran Kumari

Author: Ajit Kumar Sharma

Paper ID: V3I1-1363

Paper Status: published

Published: February 20, 2017

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Physical and Cyber Crime Detection using Digital Forensic Approach: A Complete Digital Forensic Tool

Criminalization may be a general development that has significantly extended in previous few years. In order, to create the activity of the work businesses easy, use of technology is important. Crime investigation analysis is a section record in data mining plays a crucial role in terms of predicting and learning the criminals. In our paper, we've got planned an incorporated version for physical crime as well as cyber crime analysis. Our approach uses data mining techniques for crime detection and criminal identity for physical crimes and digitized forensic tools (DFT) for evaluating cybercrimes. The presented tool named as Comparative Digital Forensic Process tool (CDFPT) is entirely based on digital forensic model and its stages named as Comparative Digital Forensic Process Model (CDFPM). The primary step includes accepting the case details, categorizing the crime case as a physical crime or cybercrime and sooner or later storing the data in particular databases. For physical crime analysis, we've used k-means approach cluster set of rules to make crime clusters. The k-means method effects are a lot advantageous by the utilization of GMAPI generation. This provides advanced and consumer-friendly visual aid to k-means approach for tracing the region of the crime. we have applied KNN for criminal identification with the help of observing beyond crimes and finding similar ones that suit this crime, if no past document is discovered then the new crime sample are introduced to the crime dataset. With the advancements of the web, the network form has become much more complicated and attacking methods are furthermore than that as well. For crime analysis, we're detecting the attacks executed on a host system through an outside the usage of assorted digitized forensic tools to produce information security with the help of generating reports for an event which could need any investigation. Our digitized technique aids the development of the society by helping the investigation businesses to follow a custom-built investigative technique in crime analysis and criminal identification as opposed to manually looking the database to analyze criminal activities, and as a result, facilitate them in combating crimes.

Published by: Dr. Nilakshi Jain, Neha Bhanushali, Sayali Gawade, Gauri Jawale

Author: Dr. Nilakshi Jain

Paper ID: V3I1-1362

Paper Status: published

Published: February 20, 2017

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Smart Group-Based Work in Cognitive Radio Network

In this paper, consider the multiple channels and group-based cognitive radio network, the secondary users having heterogeneous sensing ability in terms of high accuracy for sensing. We use cooperative spectrum sensing (CSS) scheme for cooperating secondary users in multiple workgroups such that different work group is responsible for sensing different channel. The group-base CSS scheme use in workgroup we share the channel in same cooperating users are in multiple rounds.In this work, we propose adaptively assigning that the heterogeneous Co-operating secondary users to different groups to maximize the throughput efficiency while maintaining a predefined sensing accuracy. In Cognitive Radio Network is detected by channel are use or not, if not the avoid are there but sometimes the lot of constraints & challenges, also issues are there it get the amount of busy server. The PU users get not possible to provide network then use smartly SU.It provides a network to group-based with the help of different sensing round. The Heterogeneous group based channel shares CSS scheme. It is Adaptive Secondary User’s solve problem about Heterogeneous Group user and achieves that the maximize throughput efficiency & low computational complexity significantly that can be as compared with existing non-adaptive assignment and sequential CSS scheme.

Published by: Aniket Nale, Dhaigude N. B

Author: Aniket Nale

Paper ID: V3I1-1361

Paper Status: published

Published: February 20, 2017

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