Thursday, March 17, 2016

HAPTIC TECHNOLOGY

HAPTIC TECHNOLOGY

Abstract :

Engineering as it finds its wide range of application in every field not an exceptioneven the medical field. One of the technologies which aid the surgeons to perform even the most complicated surgeries successfully is Virtual Reality. Even though virtual reality is employed to carry out operations the surgeon's attention is one of the most important parameter. If he commits any mistakes it may lead to a dangerous end. So, one may think of a technology that reduces the burdens of a surgeon by providing an efficient interaction to the surgeon than VR. Now our dream came to reality by means of a technology called “HAPTIC TECHNOLOGY”. Haptic is the “science of applying tactile sensation to human interaction with computers”. In our paper we have discussed the basic concepts behind haptic along with the haptic devices and how these devices are interacted to produce sense of touch and force feedback mechanisms.

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Tag. 
Project paper for research and paper presentation. 
IEEE Paper for final year project
IEEE Pare On Palm Vein Technology  Abstract
Iee paper download for free

PALM VEIN TECHNOLOGY Abstract

PALM VEIN TECHNOLOGY

ABSTRACT:

With the increase in technology threat to personal data and national security hadalso increased. The methods that were developed to secure important information from outsideintervention were not up to safe mark .There was a need to introduce a technology that securesour data more efficiently from unlawful intervention .Fujitsu has developed a palm vein pattern authentication technology that usesvascular patterns as personal identification data .Vein recognition technology is secure becausethe authentication data exists inside the body and is therefore very difficult to forge. It is highlyaccurate. This technology can be used in various fields like banking, hospitals, governmentoffices, in passport issuing etc. Business growth will be achieved with these solutions byreducing the size of the palm vein sensor and shortening the authentication time.Hand vein is a biometric modality that seems promising as it is acquired in Near Infrared light (NIR), which implies that skin variations and dirtiness are less sensible than invisible light. Moreover, the haemoglobin which flows in the veins is sensible to NIR light, thisway allowing a good quality of acquisition of the hand veins. It is possible to use either the back of the hand or the hand palm. A recent study using back hand vein data and tested with 5sessions per person and 50 persons showed promising results. The main problem of this databaseis the low resolution of the images (images at resolution 132x124 pixels).The first commercialized products have been produced by Hitachi on the back andFujitsu on the palm. They have been patented but only little information is available on them.These companies claim a very low FRR ( False Rejection Rate) at very low FAR (FalseAcceptance Rate) on a huge database ± close to 0% on 140000 hands. Unfortunately at thismoment, there is no public database allowing verifying these figures.In general, in the various papers present in the literature, after the acquisitionphase, some matching algorithms are used such as the Line segment Hausdorff Distance (LHD)method. The LHD method has good experiment results. But, the structure information of palmvein is not as clear as hand vein, so line-based feature is not a good choice for palm veinrecognition. Matching based on minutiae analysis and Hausdorff distance (MHD) was used for hand vein recognition. Minutiae-like feature could also be extracted from palm vein pattern

Tag. 
Project paper for research and paper presentation. 
IEEE Paper for final year project
IEEE Pare On Palm Vein Technology  Abstract
Iee paper download for free

Tuesday, March 15, 2016

SQL GROUP BY Clause

The SQL GROUP BY statement is used together with the SQL aggregate functions to group the retrieved data by one or more columns. The GROUP BY concept is one of the most complicated concepts for people new to the SQL language and the easiest way to understand it, is by example.

Remember we used the SUM keyword to calculate the total sales for all stores? What if we want to calculate the total sales for each store? Well, we need to do two things: First, we need to make sure we select the store name as well as total sales. Second, we need to make sure that all the sales figures are grouped by stores. The corresponding SQL syntax is,


SELECT "column_name1", SUM("column_name2")

FROM "table_name"
GROUP BY "column_name1";

Let's illustrate using the following table,
Table Store_Information
Store_NameSalesTxn_Date
Los Angeles1500Jan-05-1999
San Diego250Jan-07-1999
Los Angeles300Jan-08-1999
Boston700Jan-08-1999

We want to find total sales for each store. To do so, we would key in,


SELECT Store_Name, SUM(Sales)

FROM Store_Information
GROUP BY Store_Name;


Result:

Store_Name  SUM(Sales)
Los Angeles1800
San Diego250
Boston700

SQL Aggregate Functions


SQL Aggregate Functions


SQL Aggregate functions return a single value, using values in a table column. Useful aggregate functions:




  • AVG( ) - Returns the average value
  • COUNT( ) - Returns the number of rows
  • FIRST( ) - Returns the first value
  • LAST( ) - Returns the last value
  • MAX( ) - Returns the largest value
  • MIN( ) - Returns the smallest value
  • SUM( ) - Returns the sum

In this chapter we are going to introduce a new table called Sales, which will have the following columns and data:

OrderIDOrderDateOrderPriceOrderQuantityCustomerName
112/22/20051602Smith
208/10/20051902Johnson
307/13/20055005Baldwin
407/15/20054202Smith
512/22/200510004Wood
610/2/20058204Smith
711/03/200520002Baldwin

The SQL COUNT function returns the number of rows in a table satisfying the criteria specified in the WHERE clause. If we want to count how many orders has made a customer with CustomerName of Smith, we will use the following SQL COUNT expression:

SELECT COUNT (*) FROM Sales WHERE CustomerName = 'Smith'

Let's examine the SQL statement above. The COUNT keyword is followed by brackets surrounding the * character. You can replace the * with any of the table's columns, and your statement will return the same result as long as the WHERE condition is the same.

The result of the above SQL statement will be the number 3, because the customer Smith has made 3 orders in total.

If you don't specify a WHERE clause when using COUNT, your statement will simply return the total number of rows in the table, which in our case is 7:

SELECT COUNT(*) FROM Sales


How can we get the number of unique customers that have ordered from our store? We need to use the DISTINCT keyword along with the COUNT function to accomplish that:


SELECT COUNT (DISTINCT CustomerName) FROM Sales


The SQL SUM function is used to select the sum of values from numeric column. Using the Sales table, we can get the sum of all orders with the following SQL SUM statement:


SELECT SUM(OrderPrice) FROM Sales


As with the COUNT function we put the table column that we want to sum, within brackets after the SUM keyword. The result of the above SQL statement is the number 4990.


If we want to know how many items have we sold in total (the sum of OrderQuantity), we need to use this SQL statement:


SELECT SUM(OrderQuantity) FROM Sales



The SQL AVG function retrieves the average value for a numeric column. If we need the average number of items per order, we can retrieve it like this:


SELECT AVG(OrderQuantity) FROM Sales


Of course you can use AVG function with the WHERE clause, thus restricting the data you operate on:


SELECT AVG(OrderQuantity) FROM Sales WHERE OrderPrice > 200


The above SQL expression will return the average OrderQuantity for all orders with OrderPrice greater than 200, which is 17/5.

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The SQL MIN function selects the smallest number from a numeric column. In order to find out what was the minimum price paid for any of the orders in the Sales table, we use the following SQL expression:

SELECT MIN(OrderPrice) FROM Sales


The SQL MAX function retrieves the maximum numeric value from a numeric column. The MAX SQL statement below returns the highest OrderPrice from the Sales table:


SELECT MAX(OrderPrice) FROM Sales

SQL Operators

SQL Operators

An operator is a reserved word or a character used primarily in an SQL statement's WHERE clause to perform operation(s).There are two type of Operators, namely

  • Comparison Operators 
  • Logical Operators.
There are Operators That are used to specify conditions in an SQL statement and to serve as conjunctions for multiple conditions in a statement.
  • Arithmetic operators
  • Comparison operators
  • Logical operators
  • Operators used to negate conditions
SQL Arithmetic Operators:
Assume variable a holds 10 and variable b holds 20, then:

OperatorDescriptionExample
+Addition - Adds values on either side of the operatora + b will give 30
-Subtraction - Subtracts right hand operand from left hand operanda - b will give -10
*Multiplication - Multiplies values on either side of the operatora * b will give 200
/Division - Divides left hand operand by right hand operandb / a will give 2
%Modulus - Divides left hand operand by right hand operand and returns remainderb % a will give 0


Comparison Operators:

Comparison operators are used to compare the column data with specific values in a condition.
Comparison Operators are also used along with the SELECT statement to filter data based on specific conditions.

Assume variable a holds 10 and variable b holds 20, then:
OperatorDescriptionExample
=Checks if the values of two operands are equal or not, if yes then condition becomes true.(a = b) is not true.
!=Checks if the values of two operands are equal or not, if values are not equal then condition becomes true.(a != b) is true.
<>Checks if the values of two operands are equal or not, if values are not equal then condition becomes true.(a <> b) is true.
>Checks if the value of left operand is greater than the value of right operand, if yes then condition becomes true.(a > b) is not true.
<Checks if the value of left operand is less than the value of right operand, if yes then condition becomes true.(a < b) is true.
>=Checks if the value of left operand is greater than or equal to the value of right operand, if yes then condition becomes true.(a >= b) is not true.
<=Checks if the value of left operand is less than or equal to the value of right operand, if yes then condition becomes true.(a <= b) is true.
!<Checks if the value of left operand is not less than the value of right operand, if yes then condition becomes true.(a !< b) is false.
!>Checks if the value of left operand is not greater than the value of right operand, if yes then condition becomes true.(a !> b) is true.

SQL Logical Operators:
There are three Main Logical Operators namely, AND, OR, and NOT. These operators compare two conditions at a time to determine whether a row can be selected for the output. When retrieving data using a SELECT statement, you can use logical operators in the WHERE clause, which allows you to combine more than one condition.

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Here is a list of all the logical operators available in SQL.

OperatorDescription
ALLThe ALL operator is used to compare a value to all values in another value set.
ANDThe AND operator allows the existence of multiple conditions in an SQL statement's WHERE clause.
ANYThe ANY operator is used to compare a value to any applicable value in the list according to the condition.
BETWEENThe BETWEEN operator is used to search for values that are within a set of values, given the minimum value and the maximum value.
EXISTSThe EXISTS operator is used to search for the presence of a row in a specified table that meets certain criteria.
INThe IN operator is used to compare a value to a list of literal values that have been specified.
LIKEThe LIKE operator is used to compare a value to similar values using wildcard operators.
NOTThe NOT operator reverses the meaning of the logical operator with which it is used. Eg: NOT EXISTS, NOT BETWEEN, NOT IN, etc. This is a negate operator.
ORThe OR operator is used to combine multiple conditions in an SQL statement's WHERE clause.
IS NULLThe NULL operator is used to compare a value with a NULL value.
UNIQUEThe UNIQUE operator searches every row of a specified table for uniqueness (no duplicates).

ALL SQL COMANDS COLLECTION

Here is the collection of all sql commands. You can use this for recap and Quick study of SQL Commands.
This post consist of all SQL Commands with syntax and Functions for quick understanding. 

This tutorial gives you a quick start with SQL by listing all the basic SQL Syntax:

All the SQL statements start with any of the keywords like SELECT, INSERT, UPDATE, DELETE, ALTER, DROP, CREATE, USE, SHOW and all the statements end with a semicolon (;).

Important point to be noted is that SQL is case insensitive which means SELECT and select have same meaning in SQL statements but MySQL make difference in table names. So if you are working with MySQL then you need to give table names as they exist in the database.

SQL SELECT Statement:
SELECT column1, column2....columnN
FROM   table_name;

SQL DISTINCT Clause:
SELECT DISTINCT column1, column2....columnN
FROM   table_name;

SQL WHERE Clause:
SELECT column1, column2....columnN
FROM   table_name

WHERE  CONDITION;
SQL AND/OR Clause:
SELECT column1, column2....columnN
FROM   table_name
WHERE  CONDITION-1 {AND|OR} CONDITION-2;

SQL IN Clause:
SELECT column1, column2....columnN
FROM   table_name
WHERE  column_name IN (val-1, val-2,...val-N);

SQL BETWEEN Clause:
SELECT column1, column2....columnN
FROM   table_name
WHERE  column_name BETWEEN val-1 AND val-2;

SQL Like Clause:
SELECT column1, column2....columnN
FROM   table_name
WHERE  column_name LIKE { PATTERN };

SQL ORDER BY Clause:
SELECT column1, column2....columnN
FROM   table_name
WHERE  CONDITION
ORDER BY column_name {ASC|DESC};

SQL GROUP BY Clause:
SELECT SUM(column_name)
FROM   table_name
WHERE  CONDITION
GROUP BY column_name;

SQL COUNT Clause:
SELECT COUNT(column_name)
FROM   table_name
WHERE  CONDITION;

SQL HAVING Clause:
SELECT SUM(column_name)
FROM   table_name
WHERE  CONDITION
GROUP BY column_name
HAVING (arithematic function condition);

SQL CREATE TABLE Statement:
CREATE TABLE table_name(
column1 datatype,
column2 datatype,
column3 datatype,
.....
columnN datatype,
PRIMARY KEY( one or more columns )

SQL DROP TABLE Statement:
DROP TABLE table_name;

SQL CREATE INDEX Statement :
CREATE UNIQUE INDEX index_name
ON table_name ( column1, column2,...columnN);

SQL DROP INDEX Statement :
ALTER TABLE table_name

DROP INDEX index_name;
SQL DESC Statement :
DESC table_name;

SQL TRUNCATE TABLE Statement:
TRUNCATE TABLE table_name;

SQL ALTER TABLE Statement:
ALTER TABLE table_name {ADD|DROP|MODIFY} column_name {data_ype};

SQL ALTER TABLE Statement (Rename) :
ALTER TABLE table_name RENAME TO new_table_name;

SQL INSERT INTO Statement:
INSERT INTO table_name( column1, column2....columnN)
VALUES ( value1, value2....valueN);

SQL UPDATE Statement:
UPDATE table_name
SET column1 = value1, column2 = value2....columnN=valueN
[ WHERE  CONDITION ];

SQL DELETE Statement:
DELETE FROM table_name
WHERE  {CONDITION};

SQL CREATE DATABASE Statement:
CREATE DATABASE database_name;

SQL DROP DATABASE Statement:
DROP DATABASE database_name;

SQL USE Statement:
USE DATABASE database_name;

SQL COMMIT Statement:
COMMIT;

SQL ROLLBACK Statement:
ROLLBACK;

 
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