ABSTRACT
This project aims to implement a database management system. This interprets a subset of database administration and SQL commands. It possesses a subset of functionalities provided by MySQL 4.0. The interpretation would result in actions on the underlying database. The development includes the design of the database architecture and a SQL interpreter. The various stages involved are Lexical Analysis, Syntax Analysis, Semantic Analysis, Type Checking, Intermediate File Generation, Evaluation and displaying results on a GUI.
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Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood
relations since the neighbors of many objects have to be investigated in a single run of a typical
algorithm. Therefore, providing general concepts for neighborhood relations as well as an efficient
implementation of these concepts will allow a tight integration of spatial data mining algorithms
with a spatial database management system. This will speed up both, the development and
the execution of spatial data mining algorithms. In ....etc

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Introduction

This is a web oriented application allows us to access the whole information about the college, staffs, students, facilities etc. This application provides a virtual tour of Campus. Here we will get the latest information about the students and staffs. This generic application designed for assisting the students of an institute regarding information on the courses, subjects, classes, assignments, grades and timetable. It also provides support that a faculty can also check about his daily schedule, can uplo ....etc

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C-STORE A COLUMN ORIENTED DBMS
presented by
JACOB K JOSE
DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING
COLLEGE OF ENGINEERING TRIVANDRUM
2007-11 Batch




Contents

Abstract
1. Introduction
2. Features of C-store
3. Data models
3.1 Storage Keys
3.2 Join Indices
4. Internal architecture
5. Readable store (rs)
6. Writeable store (ws)
7. Storage Management
8. Updates and Transactions
8.1 Providing Snapshot isolation
9. Recovery
10. Tuple ....etc

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NETWORKING OF GPS., SENSORS AND SOFTWARE SYSTEMS WITH DBMS
(APPLICATION TO INDIAN RAILWAYS)
Introduction
What is G.P.S ?
The acronym for G.P.S is Global Positioning System.
G.P.S is a worldwide network radio navigation system.
G.P.S constitutes a constellation of minimum of 24 satellites.
Indian Railways:
World’s largest Railway network.
Large means of public transport.
Drawbacks:
Lack of sufficient Safety.
Still wide use of manual and traditional methods.
Crea ....etc

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HI THIS IS RAJSHREE LANDE STUDING IN FINAL YEAR FROM ANURADHA COLLEGE OF ENGINEERING...
I WANT A PPTS FOR DATA MINIG AND DATA WAREHOUSING....
I SEARCHING BASICS ON DATA MING AND DATA WAREHOUSING...
BUT I CONFUSE WHAT SHOULD BE ACTUAALY ADD IN THAT TOPIC
WHAT PONTS SHOULD BE THERE...
WHAT ARE THE IMPORTANT TOPICS.....
AND I WANT A DEATIL DESCRIPTION ON THIS TOPICS
IF U GET A IDEAS ON THIS TOPIC PLZ UPLOAD AS SOON AS POSSIBLE.....
WATING FOR SOON RPY.......

RAJSH ....etc

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Presented By
Shailendra Kumar Misra


Abstract
Backup and recovery are more important today than ever before. Take, for example, a recent announcement from a major database vendor that it now has the ability to process nearly half a million transactions per minute. That's three times the speed of the next-fastest database.
What is significant about that kind of increase? It clearly shows that businesses today are demanding higher throughput as they continue to store and process more data. It wasn't long a ....etc

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Dbms , thanks for your usefull helping thaaannnnkkkkssssasss i wish ithis message more than40 leters
Thank youuuuUuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu soooo much ....etc

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i just want to do a mini project frontend as oracle ....etc

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Abstract :-
Many DAG scheduling algorithms generate schedules that require prohibitively large number of processors. To addressthis problem, we propose a generic algorithm, SC, to minimize the processor requirement of any given valid schedule. SC preserves theschedule length of the original schedule and reduces processor count by merging processor schedules and removing redundant
duplicate tasks. To the best of our knowledge, this is the first algorithm to address this highly unexplored aspect of DAG scheduling. Onaverage, SC reduced ....etc

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