Posted by Saurabh on August 4th, 2010
IBM researchers have successfully mapped out the long-distance network of the brain of the Macaque monkey, which holds significant ramifications for reverse-engineering the brain and creating a network of cognitive computing chips. “We have collated a comprehensive, consistent, concise, coherent, and colossal network spanning the entire brain and grounded in anatomical tracing studies that is a stepping stone to both fundamental and applied research in neuroscience and cognitive computing,” says IBM Almaden’s Dharmendra S. Modha.
The researchers concentrated on the long-distance network of nearly 400 brain regions and more than 6,600 long-distance brain connections that pass through the brain’s white matter. The work builds on the publicly available Collation of Connectivity data on the Macaque brain database. The scientists’ ranking of brain regions uncovered evidence suggesting that the prefrontal cortex is a functionally central part of the brain that might serve as an integrator and distributor of information. They determined that the brain network does not appear to be scale-free like Web social networks, but is exponential–a discovery that will help inform the design of a cognitive computing chip network’s routing architecture.
View Full Article
Posted by Saurabh on July 21st, 2010
Writing programs for sorting of a given set of numbers is one of the common programming tasks. Various types of sorting techniques like selection sort, inserting sort and quick sort are quite popular. Here C code for Quick sort is being presented. Here, in each iteration the array is subdivided into 2 arrays, and hence is a good example of Divide and Conquer algorithm. The program has the worst case complexity of O(n²) and an average and best case complexity of O(n logn).
Following is the C code implementation of Quick Sort algorithm :
#include "stdio.h"
int split ( int*, int, int ) ;
void main( )
{
int arr[10] = { 11, 2, 9, 13, 57, 25, 17, 1, 90, 3 } ;
int i ;
void quicksort ( int *, int, int ) ;
quicksort ( arr, 0, 9 ) ;
printf ( "\nArray after sorting:\n") ;
for ( i = 0 ; i <= 9 ; i++ )
printf ( "%d\t", arr[i] ) ;
}
void quicksort ( int a[ ], int lower, int upper )
{
int i ;
if ( upper > lower )
{
i = split ( a, lower, upper ) ;
quicksort ( a, lower, i - 1 ) ;
quicksort ( a, i + 1, upper ) ;
}
}
int split ( int a[ ], int lower, int upper )
{
int i, p, q, t ;
p = lower + 1 ;
q = upper ;
i = a[lower] ;
while ( q >= p )
{
while ( a[p] < i )
p++ ;
while ( a[q] > i )
q-- ;
if ( q > p )
{
t = a[p] ;
a[p] = a[q] ;
a[q] = t ;
}
}
t = a[lower] ;
a[lower] = a[q] ;
a[q] = t ;
return q ;
}
Posted by Saurabh on July 20th, 2010
China’s relentless focus on science and technology could ultimately lead it to become the world leader in technology. In China, the labor pool is getting increasingly sophisticated, the leadership is focused on innovation, and the country is adopting policies to pressure U.S. firms into transferring their technology.
The country’s focus on science and technology may be unstoppable for five reasons. First, China’s leadership understands engineering, with eight of the nine members of the Standing Committee of the Political Bureau holding engineering degrees. Additionally, China’s leadership is striving to out-innovate the U.S., which translates to more money invested in technological innovations, from supercomputers to nanotechnology. Third, China’s science and technical talent pool is vast. Another boon for the Chinese innovation movement is that just 3 percent of all ninth-grade students in the United States will eventually earn an undergraduate degree in science or engineering. Finally, China is getting almost all of the U.S.’s technology and succeeding in creating what it calls an indigenous innovation policy. U.S. Commerce Secretary Gary Locke says the policy is designed to encourage technology transfer and force U.S. companies to transfer their research operations to China in exchange for access to its markets.
View Full Article
Posted by Saurabh on July 19th, 2010
Searching and sorting have been popular operations in elementry data structures. Although now a days many advanced sorting techniques are used to sort a set of data, the basic sorting methods are still popular and are the used frequently. Here C code for bubble sort is given. The algorithm for bubble sort is quite simple. In each iteration the adjacent elements are compared and they are swapped if their order is not correct. The complexity of this algorithm comes out to be O(n²).
The C code is as follows :
#include "stdio.h"
#include "conio.h"
void main( )
{
int arr[5] = { 25, 17, 31, 13, 2 } ;
int i, j, temp ;
for ( i = 0 ; i <= 3 ; i++ )
{
for ( j = 0 ; j <= 3 - i ; j++ )
{
if ( arr[j] > arr[j + 1] )
{
temp = arr[j] ;
arr[j] = arr[j + 1] ;
arr[j + 1] = temp ;
}
}
}
printf ( "\n\nArray after sorting:\n") ;
for ( i = 0 ; i <= 4 ; i++ )
printf ( "%d\t", arr[i] ) ;
}
Posted by Saurabh on July 18th, 2010
Searching and sorting have been popular operations in elementry data structures. Although now a days many advanced sorting techniques are used to sort a set of data, the basic sorting methods are still popular and are the used frequently. Here C code for selection sort is given. The algorithm for selection sort is quite simple. In the first iteration, 1st element is compared against all the other elements (from array index 1 to array index n). In the second iteration 2nd element is compared with the elements from array index 2 to n. This process is repeated n-1 times.
The C code is as follows :
#include "stdio.h"
void main( )
{
int arr[5] = { 25, 17, 31, 13, 2 } ;
int i, j, temp ;
for ( i = 0 ; i <= 3 ; i++ )
{
for ( j = i + 1 ; j <= 4 ; j++ )
{
if ( arr[i] > arr[j] )
{
temp = arr[i] ;
arr[i] = arr[j] ;
arr[j] = temp ;
}
}
}
printf ( "\n\nArray after sorting:\n") ;
for ( i = 0 ; i <= 4 ; i++ )
printf ( "%d\t", arr[i] ) ;
}
