Speeding up research with the Semantic Web

Speeding up research with the Semantic Web

Data for Rare Diseases are often distributed. Ideally, we can combine relevant data and biological insights from any place in the world and use it directly as input for computational analysis. However, too often data is poorly described making it hard to find, hard to assess its quality, and hard to integrate with other data. A valid question is: ‘Why can’t we analyse data as if it came from on...

Speeding up Web Page Loads with Shandian

Web page loads are slow due to intrinsic inefficiencies in the page load process. Our study shows that the inefficiencies are attributable not only to the contents and structure of the Web pages (e.g., three-fourths of the CSS resources are not used during the initial page load) but also the way that pages are loaded (e.g., 15% of page load times are spent waiting for parsing-blocking resources...

IMPROVE THE RECOMMENDER SYSTEM USING SEMANTIC WEB

To buy his/her necessities such as books, movies, CD, music, etc., one always trusts others’ oral and written consultations and offers and include them in his/her decisions. Nowadays, regarding the progress of technologies and development of e-business in websites, a new age of digital life has been commenced with the Recommender systems. The most important objectives of these systems include a...

Speeding-up Reinforcement Learning with

Speeding up the Memory

Scalable Flat Cache Only Memory Architectures (Flat COMA) are designed for reduced memory access latencies while minimizing programmer and operating system involvement. Indeed, to keep memory access latencies low, neither the programmer needs to perform clever data placement nor the operating system needs to perform page migration. The hardware automatically replicates the data and migrates it ...