Notice Board :

Call for Paper
Vol. 5 Issue 2

Submission Start Date:
February 01, 2019

Acceptence Notification Start:
February 10, 2019

Submission End:
February 15, 2019

Final MenuScript Due:
February 25, 2019

Publication Date:
February 28, 2019


                         Notice Board: Call for PaperVol. 5 Issue 2      Submission Start Date: February 01, 2019      Acceptence Notification Start: February 10, 2019      Submission End: February 15, 2019      Final MenuScript Due: February 25, 2019      Publication Date: February 28, 2019




Volume IV Issue VIII

Author Name
Mr.Shubham Agrawal, Mr. Kapil Sahu
Year Of Publication
2018
Volume and Issue
Volume 4 Issue 8
Abstract
Machine Learning is very emerging technology that is used in each and every system. Education data mining is very importantdisciplines, because the result of student is so important for their future and the amount of data in education system is increasing day by day .In education it is relatively new but its importance increases because of increasing database. There are many approach for measuring students’ performance .data mining is one of them .With the help of data mining the hidden information in the database is get out which help for improvement of students’ performance education data mining is used to study the data available in education field to bring the hidden data i.e. important and useful information from it. There are many methods of machine learning which is used to analysis of students’ performance clustering method like K-means is most used to measure the students’performance. With the help of these it is easy to improve the result and future of students. More methods
PaperID
2018/IJRRETAS/8/2018/37661

Author Name
Ms.Saba Khan, Mrs. Nisha Bhati
Year Of Publication
2018
Volume and Issue
Volume 4 Issue 8
Abstract
Wireless sensor networks are challenging technology regarding communication because of its limited resource nature and various network topologies. Wireless Sensor Network is to minimize energy consumption by each sensor node and increase network communication lifetime. This paper using a modified algorithm for Low Energy Adaptive Clustering Hierarchy protocol. The movement of mobile nodes is decided on the basis of their distance from CHs. These papers analyze the several clustering techniques with Modified LEACH concept.
PaperID
2018/IJRRETAS/8/2018/37666

Author Name
Ms. Rida Khan, Mrs. Nisha Bhati
Year Of Publication
2018
Volume and Issue
Volume 4 Issue 8
Abstract
The classification in recovery systems Brain is to differentiate among normal and abnormal brain tissue. In this paper use feature extraction from MRI is carried out by Wavelet transform and ANN techniques. Wavelet transform tool for feature extraction because it gives better contrast to an image. Due to better contrast it improves easily hanging signals of an image and reduces the overhead. GLCM is used to select the best features for classification..
PaperID
2018/IJRRETAS/8/2018/37667

Author Name
Ms. Monika Labana, Mr. Mohit Jain
Year Of Publication
2018
Volume and Issue
Volume 4 Issue 8
Abstract
The fast growth of mobile communication in recent years is especially observed in the field of mobile system, wireless local area network, and ubiquitous computing. Security is a main concern for protected communication between mobile nodes in an unfriendly environment. In hostile environments adversaries can bunch active and passive attacks against intercept able routing in embed in routing message and data packets. Ad hoc networks use mobile nodes to enable communication outside wireless transmission range. Attacks on ad hoc network routing protocols disrupt network performance and reliability. MANET has no clear line of defense, so, it is accessible to both legitimate network users and malicious attackers.The issues rise when the nodes are mobile and poor routing techniques allow a user to change or modify the information during data transmission because, during network communication the data is transmitted through the intermediate routers where any node can leave or join the networ
PaperID
2018/IJRRETAS/8/2018/37662