Thursday, 31 May 2012
Wednesday, 30 May 2012
How to convert scanned image to word
- Scan a paper and save it as .tif(target image format ).
- Go to Ms Office Ms Tools -->;Ms office Document Imaging. [note : if u don’t find this option go to control panel -->Add remove programs-->; Ms Office -->; repair -->; Check for Document Imaging click on it -->this will install this plug in]
- Now Open the image in MS office Document Imaging .
- Select Tools-->Send Text to Word.
- Done
Sunday, 27 May 2012
How to connect MS Access database to odbc in Win 7 x64 bit?
How to connect MS Access database to odbc in Win 7 x64 bit?
After you finish creating database in MS Access follow the steps as given:
· Go to start menu
· Select Computer and click on c drive.
· Click on Windows folder in c derive
· Then Click on SysWOW64.
· Check for odbcad32 and click on it.
· After that click on System DSN from popup box.
· Click on add option
· A dialog box will open called create New Data Source from that select .mdb option and click on it.
· One new dialog box will open
i) Enter your Data Source Name ,you can give different or same name to your DSN
(1) For eg if database name is lab.mdb
(2) You can save your DSN as lab or labmaster
(3) NOTICE:lab and Lab makes a difference in DSN so be carrefull while specifying your DSN.
ii) ----Database—
iii) Click on the select button , a select dialog box will open .
iv) In the select dialog box select your database name just by changing the drive from the drive column .
v) Then Click Ok.
· After that Click OK until all dialog box is closed.
After you finish creating database in MS Access follow the steps as given:
· Go to start menu
· Select Computer and click on c drive.
· Click on Windows folder in c derive
· Then Click on SysWOW64.
· Check for odbcad32 and click on it.
· After that click on System DSN from popup box.
· Click on add option
· A dialog box will open called create New Data Source from that select .mdb option and click on it.
· One new dialog box will open
i) Enter your Data Source Name ,you can give different or same name to your DSN
(1) For eg if database name is lab.mdb
(2) You can save your DSN as lab or labmaster
(3) NOTICE:lab and Lab makes a difference in DSN so be carrefull while specifying your DSN.
ii) ----Database—
iii) Click on the select button , a select dialog box will open .
iv) In the select dialog box select your database name just by changing the drive from the drive column .
v) Then Click Ok.
· After that Click OK until all dialog box is closed.
Thursday, 3 May 2012
MSc Computer Science Part I Reference Book
Links for Reference Book of MSc Computer Science Part-I Mumbai University
Click below links to download| Paper | Subject | Section | Refrence Book |
|---|---|---|---|
| I | Compiler | I | Compiler Design -- Compilers Principles, Techniques and Tools - Aho, Sethi |
| II | Compiler Design -- Compilers Principles, Techniques and Tools - Aho, Sethi |
||
| II | Digital Signal Processing | I | Theory and Application of Digital Signal Proceesing - Lawrence R.Rabiner Bernard Gold |
| II | Theory and Application of Digital Signal Proceesing - Lawrence R.Rabiner Bernard Gold |
||
| III | Mobile Computing ========================= Computer Simulation Model |
I | Wireless Communication and Networks - William Stallings |
| II | Discrete Event System Simulation - Jerry Banks, John Carson , Barry Nelson, David Nicol |
||
| IV | Data Warehousing | I | Data Warehousing Fundamentals- Paulraj Ponnian,John Wiley |
| Data Mining | Data Mining Introductory and Advanced Topics-M.H.Dunham,Pearson Education |
||
| Adavance Database Systems | II | Fundamentals of Database Systems- Elmarshi and Navathe ============================== Database Management Systems- Raghu Ramakrishnan,Johannes Gehrke McGraw-Hill |
Friday, 24 February 2012
K-mean Clustering Algorithm
Q. Use the k-mean clustering to solve the problem ? Itemsets ={2,4,10,2,3,20,30,11,25} and Suppose that k=2. With m1=2 and m2=4.
Solution:
Let
Cluster : k1=1 and k2=2
M1 | M2 | K1 | K2 |
2 | 4 | {2,3} | {4,10,11,12,20,25,30} |
Recalculate mean m1,m2 with items in k1 ={2,3} and k2= {4,10,11,12,20,25,30}
Therfore m1 =(2+3)/2 = 2.5 m2 =(4,10,11,12,20,25,30)/7 = 16
Now we have DistanceMean1 (2.5) ,DistanceMean2 (16)
M1 | M2 | K1 | K2 |
2 | 4 | {2,3} | {4,10,11,12,20,25,30} |
2.5 | 16 | {2,3,4} | {10,11,12,20,25,30} |
Recalculate mean m1,m2 with items in k1 ={2,3,4} and k2= {10,11,12,20,25,30}
Therfore m1 =(2+3+4)/3 = 3 m2 =(10+11+12+20+25+30)/6 = 18
Now we have DistanceMean1 (3) ,DistanceMean2 (18)
M1 | M2 | K1 | K2 |
2 | 4 | {2,3} | {4,10,11,12,20,25,30} |
2.5 | 16 | {2,3,4} | {10,11,12,20,25,30} |
3 | 18 | {2,3,4,10} | {11,12,20,25,30} |
Recalculate mean m1,m2 with items in k1 ={2,3,4,10} and k2= {11,12,20,25,30}
Therfore m1 =(2+3+4+10)/4 = 4.75 m2 =(11+12+20+25+30)/5 = 19.6
Now we have DistanceMean1 (4.75) ,DistanceMean2 (19.6)
M1 | M2 | K1 | K2 |
2 | 4 | {2,3} | {4,10,11,12,20,25,30} |
2.5 | 16 | {2,3,4} | {10,11,12,20,25,30} |
3 | 18 | {2,3,4,10} | {11,12,20,25,30} |
4.75 | 19.6 | {2,3,4,10,11,12} | {20,25,30} |
Recalculate mean m1,m2 with items in k1 ={2,3,4,10,11,12} and k2= {20,25,30}
Therfore m1 =(2+3+4+10+11+12)/6 = 7 m2 =(11+12+20+25+30)/3 = 25
Now we have DistanceMean1 (7) ,DistanceMean2 (25)
M1 | M2 | K1 | K2 |
2 | 4 | {2,3} | {4,10,11,12,20,25,30} |
2.5 | 16 | {2,3,4} | {10,11,12,20,25,30} |
3 | 18 | {2,3,4,10} | {11,12,20,25,30} |
4.75 | 19.6 | {2,3,4,10,11,12} | {20,25,30} |
7 | 25 | {2,3,4,10,11,12} | {20,25,30} |
Recalculate mean m1,m2 with items in k1 ={2,3,4,10,11,12} and k2= {20,25,30}
Therfore m1 =(2+3+4+10+11+12)/6 = 7 m2 =(11+12+20+25+30)/3 = 25
Now we have DistanceMean1 (7) ,DistanceMean2 (25)
Since we have same mean as previous iteration we stop here.
Thus k1 = {2,3,4,10,11,12} and k2 = {20,25,30}
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