Database Programming

computer-based system(it contains both hard ware and software) that can process data that are incomplete or only partially correct

Fuzzy logic was introduced as an artificial intelligence technique, when it was realized that normal boolean logic would not suffice. When we make intelligent decisions, we cannot limit ourselves to "true" or "false" possibilities (boolean). We have decisions like "maybe" and other shades of gray. This is what is introduced with fuzzy logic: the ability to describe degrees of truth.

Example:

in fuel station if you stop a fuel injecting motor at 1.55897ltrs.it can be done with the help of fuzzy logic.fuzzy has a meaning like accurate.

Indexed sequential file organization. =In indexed sequential file organization, the records arestored in sequence according to a primary key and an index is created to allow random access of the file. This type of organization also allows the file to be accessed sequentially. Indexed sequential is the most commonlyused type of file organization. writer-k.k.b -montanna

The file(s) (data) which are accessed in a sequential or a orderly manner is called as a sequentially accessing a file.

The differences between the three approaches Table 1: A Comparison of Database Management Systems Criteria RDBMS ODBMS ORDBMS Defining standard SQL2 ODMG-2.0 SQL3 (in process) Support for object-oriented features Does not support; It is difficult to map program object to the database Supports extensively Limited support; mostly to new data types Usage Easy to use OK for programmers; some SQL access for end users Easy to use except for some extensions Support for complex relationships Does not support abstract datatypes Supports a wide variety of datatypes and data with complex inter-relationships Supports Abstract datatypes and complex relationships Performance Very good performance Relatively less performance Expected to perform very well Product maturity Relatively old and so very mature This concept is few years old and so relatively mature Still in development stage so immature. The use of SQL Extensive supports SQL OQL is similar to SQL, but with additional features like Complex objects and object-oriented features. SQL3 is being developed with OO features incorporated in it Advantages Its dependence on SQL, relatively simple query optimization hence good performance It can handle all types of complex applications, reusability of code, less coding Ability to query complex applications and ability to handle large and complex applications Disadvantages Inability to handle complex applications Low performance due to complex query optimization, inability to support large-scale systems Low performance in web applications Support from vendors It is considered to be highly successful so the market size is very large but many vendors are moving towards ORDBMS Presently lacking vendor support due to vast size of RDBMS market All major RDBMS vendors are after this so has very good future

#include"stdio.h"
#include"conio.h"
int fabo(int);
void main()
{
int result=0,a=1,b=1,c;
printf("enter upto which you want to generate the series");
scanf("%d",&c);
result=fabo(c);
printf("%d\n%d\n",a,b);
printf("the fabonnaci series is %d\n",result);
getch();
}
int fabo(int n)
{
if (n==1);
return 1;
else if(n==2);
return 1;
else
return fabo(n-1)+fabo(n-2);
}

In a binary search tree, insertion, deletion and lookup are O(log n) (i.e. fast) when balanced.
With unsorted arrays, insertion and deletion are O(1) (i.e. very fast) but lookup is O(n) (i.e. slow).
With sorted arrays, insertion and deletion are O(n) (i.e. slow) and lookup is O(log n) (i.e. fast).

Binary search trees are good if you do all three operation (insertion, deletion, lookup) often and have enough data to justify the added burden of more complex structures and algorithms.

IN COMPUTER SCIENCE, A SPACE-TIME OR TIME-MEMORY TRADEOFF IS A SITUATION WHERE THE MEMORY USE CAN BE REDUCED AT THE COST OF SLOWER PROGRAM EXECUTION (OR, VICE VERSA, THE COMPUTATION TIME CAN BE REDUCED AT THE COST OF INCREASED MEMORY USE). AS THE RELATIVE COSTS OF CPU CYCLES, RAM SPACE, AND HARD DRIVE SPACE CHANGE HARD DRIVE SPACE HAS FOR SOME TIME BEEN GETTING CHEAPER AT A MUCH FASTER RATE THAN OTHER COMPONENTS OF COMPUTERS. THE APPROPRIATE CHOICES FOR SPACE-TIME TRADEOFFS HAVE CHANGED RADICALLY. OFTEN, BY EXPLOITING A SPACE-TIME TRADEOFF, A PROGRAM CAN BE MADE TO RUN MUCH FASTER.

THE MOST COMMON SITUATION IS AN ALGORITHM INVOLVING A LOOKUP TABLE: AN IMPLEMENTATION CAN INCLUDE THE ENTIRE TABLE, WHICH REDUCES COMPUTING TIME, BUT INCREASES THE AMOUNT OF MEMORY NEEDED, OR IT CAN COMPUTE TABLE ENTRIES AS NEEDED, INCREASING COMPUTING TIME, BUT REDUCING MEMORY REQUIREMENTS. A SPACE-TIME TRADEOFF CAN BE APPLIED TO THE PROBLEM OF DATA STORAGE. IF DATA IS STORED UNCOMPRESSED, IT TAKES MORE SPACE BUT LESS TIME THAN IF THE DATA WERE STORED COMPRESSED (SINCE COMPRESSING THE DATA REDUCES THE AMOUNT OF SPACE IT TAKES, BUT IT TAKES TIME TO RUN THECOMPRESSION ALGORITHM). DEPENDING ON THE PARTICULAR INSTANCE OF THE PROBLEM, EITHER WAY IS PRACTICAL. ANOTHER EXAMPLE IS DISPLAYING MATHEMATICAL FORMULAE ON PRIMARILY TEXT-BASED WEBSITES, SUCH AS WIKIPEDIA.

Storing only the LaTeX source and rendering it as an image every time the page is requested would be trading time for space - more time used, but less space. Rendering the image when the page is changed and storing the rendered images would be trading space for time - more space used, but less time. Note that there are also rare instances where it is possible to directly work with compressed data, such as in the case of compressed bitmap indices, where it is faster to work with compression than without compression. Larger code size can be traded for higher program speed when applying loop unrolling. This technique makes the code longer for each iteration of a loop, but saves the computation time required for jumping back to the beginning of the loop at the end of each iteration. Algorithms that also make use of space-time tradeoffs include:

BABY-STEP GIANT-STEP ALGORITHM FOR CALCULATING DISCRETE LOGARITHMS.

RAINBOW TABLES IN CRYPTOGRAPHY, WHERE THE ADVERSARY IS TRYING TO DO BETTER THAN THE EXPONENTIAL TIME REQUIRED FOR A BRUTE FORCE ATTACK. RAINBOW TABLES USE PARTIALLY PRECOMPUTED VALUES IN THE HASH SPACE OF A CRYPTOGRAPHIC HASH FUNCTION TO CRACK PASSWORDS IN MINUTES INSTEAD OF WEEKS. DECREASING THE SIZE OF THE RAINBOW TABLE INCREASES THE TIME REQUIRED TO ITERATE OVER THE HASH SPACE.

THE MEET-IN-THE-MIDDLE ATTACK USES A SPACE-TIME TRADEOFF TO FIND THE CRYPTOGRAPHIC KEY IN ONLY 2N + 1 ENCRYPTIONS (AND O(2N) SPACE) VERSUS THE EXPECTED 22N ENCRYPTIONS (BUT ONLY O(1) SPACE) OF THE NAIVE ATTACK.

DYNAMIC PROGRAMMING, WHERE THE TIME COMPLEXITY OF A PROBLEM CAN BE REDUCED SIGNIFICANTLY BY USING MORE MEMORY.

InsertNode(NODE **q,int num)

{

NODE *r,*temp ;

temp = *q;

r= malloc(sizeof(NODE));

r->data = num;

//if it's fisrt node to be inserted

if ( *q == NULL num < (*q)->data)

{

*q = r ;

(*q)->link=temp;

}

else

{

while(temp)

{

if ( (num > temp->data) && (num < temp->link->data ) )

{

r->link = temp->link;

temp->link = r;

return;

}

temp = temp->link;

}

r->link = NULL;

temp->link = r;

}

}

It depends on what version of VB you are using, and what version of SQL Server you're attempting to connect to. Also, there are several ways to connect from each version of VB to each version of SQL Server (ODBC, ADODB, DSN-less, etc.). Since your question does not provide enough specifics to answer adequately, I refer you to the "Connection Strings" link at the bottom of this page (or you may just type in www.connectionstrings.com in your browser).

A unit of power equal to one thousandth (10-3) of a watt.

The question itself is a bit vague since it doesn't suggest whether you're asking about the types of trees or the operations which can be performed on trees.

A tree is a data structure which stores information in a logical way that typically is ideally suited for searching quickly, often by ordering the nodes or items of the tree, also ideally, nodes should be able to be added to or removed from a tree quickly and efficiently. Often, trees are chosen as a means of simply structuring data in a meaningful way with no concerns as to their performance.

When trees are chosen as an alternative to a list, the reason for this is to gain the benefits of rapid insertion, searching and deletion of nodes. Common tree structures for this purpose are the binary tree and the black and red tree. A binary tree has an extremely simple and extremely fast method of searching for data, but it is highly dependent on nodes being added in an order which is somewhat random. If ordered data is added to a tree, the depth of the tree will be linear, thereby providing no benefits over a linked list in addition, removal of nodes can cause a binary tree to have to be rebuilt as all the nodes beneath the deleted node will have to be re-added to the tree, typically under different nodes, commonly causing linear branches of the tree and slowing down application performance.

R&B trees were designed to address many of the issues of a binary tree. By developing a data structure which intentionally keeps the depth of the tree shallow, high speed searching and node removal can be achieved, but at a cost to the insertion algorithm which is designed to "shake things up" a little. R&B trees are far beyond the scope of this answer.

General trees are used less as a means of providing ideal performance but instead are intended as a means of providing structure for data. General trees store information in a way which reflects the data format itself. An example of a general tree is the file system of a disk drive. The root directory contains zero or more children which each contain zero or more children which each contain zero or

more... you get the point. This structure is also used for things like the abstract syntax tree of a compiler. Source code is parsed into "tokens" which are the structured as nodes of a tree which are then "walked" when optimizing and producing binary code.

There are many more types of trees. Many of which ate covered by Donald Knuth in extensive, if not insane detail in "The Art of Computer Programming".

Among the operations you'd perform on the tree are insertion, deletion, searching, walking, reduction, simplification and more.

Conventional OS aim to give users the ability to run other software that are interactive in nature to perform different tasks. On the other hand, embedded OS only run fixed set of tasks and deliver the expected results in real time.

Having an unsigned integer means that the integer is positive, and not negative; literally, the integer is unsigned and assumed to be positive. The unsigned integer 8 is positive-eight, not negative-eight.

is quantity or item controlled by the decision maker.

Quite simply, an inner class is one class within another. Typically the inner class will be a private inner class, and will only be used by the outer class.

class MyOuterClass {

class MyInnerClass {

}

}