Thursday, 26 December 2013

COMPUTER SCIENCE AND ENGINEERING DEPARTMENT

Vision:
To impart high quality training to students so as to provide human resource appropriate to the local and national needs. To create and disseminate knowledge for the betterment of mankind in general and rural masses in particular. To establish centers of excellence in collaboration with industries, research laboratories and other agencies to meet the changing needs of society.


Objectives:

  • To achieve academic excellence and 100% placements for the students
  • To develop department intranet providing groupware tools for the faculty, courses and study materials for the students.
  • To conduct at least one faculty development program every semester
  • To conduct National and International conferences regularly.
  • To conduct seminars and workshops regularly.
  • To promote research and development activities among the faculty and students

Wednesday, 18 December 2013

JAVA INTERVIEW QUESTIONS AND ANSWERS

1. What is the difference between private, protected, and public?

These keywords are for allowing privileges to components such as java methods and variables.

Monday, 9 December 2013

What Is Soft Computing?

What Is Soft Computing?
Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind.

Java SE 7 Features and Enhancements

Java SE 7 Features and Enhancements


Java Platform, Standard Edition 7 is a major feature release. This document includes information on features and enhancements in Java SE 7 and in JDK 7, Oracle's implementation of Java SE 7. 

Sunday, 8 December 2013

INTRODUCTION ABOUT DATA MINING

1.1  Data Mining
The term data mining is often used to apply to the two separate processes of knowledge discovery and prediction. Knowledge discovery provides explicit information about the characteristics of the collected data, using a number of techniques (e.g., association rule mining).

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