Robust H∞ Control of Discrete-Time Uncertain Recurrent Neural Networks with Discrete and Distributed Interval Time-Varying Delays
This paper is concerned with the problem of delay-dependent H∞ control of discrete-time uncertain recurrent neural networks with time-varying delays. The neural network is subject to parameter uncertainty, and time-varying delay. For the robust H∞ stabilization problem, a state feedback controller is designed to ensure the global robust stability of the closed-loop system about its equilibrium point for all admissible uncertainties. By using the Laypunov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish sufficient conditions. A simulation example is exploited to show the usefulness of the derived LMI-based stability conditions.
Published by: K. Meenakshi, M. Syed Ali
Author: K. Meenakshi
Paper ID: V3I1-1367
Paper Status: published
Published: February 20, 2017
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
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
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
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
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
