Notice Board :

Call for Paper
Vol. 4 Issue 8

Submission Start Date:
August 01, 2018

Acceptence Notification Start:
August 10, 2018

Submission End:
August 15, 2018

Final MenuScript Due:
August 25, 2018

Publication Date:
August 31, 2018


                         Notice Board: Call for PaperVol. 4 Issue 8      Submission Start Date: August 01, 2018      Acceptence Notification Start: August 10, 2018      Submission End: August 15, 2018      Final MenuScript Due: August 25, 2018      Publication Date: August 31, 2018




Volume II Issue VII

Author Name
Shailesh Raut , Megha Singh, Dr. Rekha Rathore
Year Of Publication
2016
Volume and Issue
Volume 2 Issue 7
Abstract
Secure communication and authentication is possible through encryption of data and verification . Most of the existing data encryption techniques are location-independent. Data encrypted with such techniques cannot restrict the location and time of data decryption. The concept of "Geoencryption and Authentication " or " geo location-based encryption and authentication " is being developed for such a purpose. This paper proposes a survey between different technique to which is related to Geo location based Networks. The purpose of Geo location based network is to secure system from disparate user, so that the right user can take the right decision for the security of the items which are relevant for them. In this paper we are comparing different techniques on different aspects of systems which is used in Geo Location based network.
PaperID
2016/IJRRETAS/8/2016/11614

Author Name
Shubhangi sharma, Maya yadav
Year Of Publication
2016
Volume and Issue
Volume 2 Issue 7
Abstract
The data mining is a tool which includes various mathematical definitions and methodologies by which the data is corrected, manipulated, and identified according to their patterns. Additionally that is frequently used for various data classification, pattern recognition and other decision making tasks. The learning of data mining techniques are basically depends on the datasets or the training samples. According to the training samples the learners can be classified as supervised and unsupervised models. Additionally when the supervised learning is used the data sets are played more essential roles to guide the learning algorithm. But due to incomplete, random and inconsistent data can affect the performance of supervised classifiers. Therefore the proposed study work is concentrated over improving the data set quality using the pre-analysis of data. In order to find most optimum data analysis algorithm various techniques and methodologies are studied. But most of them have limitations
PaperID
2016/IJRRETAS/8/2016/11615

Author Name
Vinod mahajan, Dr.Ankur geete, Seshagiri rao G.V.R
Year Of Publication
2016
Volume and Issue
Volume 2 Issue 7
Abstract
In the present work, laminar cross flow forced convective heat transfer of nano fluid over tube banks with Circular geometry under constant wall temperature condition is investigated numerically. In this study nanofluid instead of pure fluid, as external cross flow, because of its potential to increase heat transfer rate of the system. The effect of the nanofluid on the compact heat exchanger performance was studied and compared to that of a conventional fluid. The two dimensional steady state Navier-Stokes equations and the energy equation governing laminar incompressible flow are solved using a finite volume method for the case of flow across an in-line bundle of tube banks as commercial compact heat exchanger. The nanofluid used was copper water 1% and the performance was compared with water. In this paper, the effect of parameters such as tube shape circular and heat transfer comparison between nanofluid and pure fluid is studied. Temperature profile, heat transfer coefficient and
PaperID
2016/IJRRETAS/8/2016/11616

Author Name
Neelesh Shrival, Kapil Sahu
Year Of Publication
2016
Volume and Issue
Volume 2 Issue 7
Abstract
The data mining architecture works on facts and figures which are used for any type of decision making. To perform any analysis and decision making, these facts must be complete so that the analyst can make a strategy for decision making. In fact the most important problem in knowledge discovery is the missing values of the attributes of the Dataset. The presence of such imperfections usually requires a preprocessing stage in which the data are prepared and cleaned, in order to be useful, and sufficiently clear for the knowledge extraction process. In this thesis presenting the Comparative study of the different method employed for Imputation or Replacement of the missing values. These methods can work with text dataset, Boolean dataset and with numeric dataset. We have discussed the parametric, non-parametric and semi-parametric imputation methods.
PaperID
2016/IJRRETAS/8/2016/11617