Scientific and engineering computing rely heavily on linear algebra for large-scale data analysis, modeling and simulation, machine learning, and other applied problems. Sparse linear system solution often dominates the execution time of such applications, prompting the ongoing development of highly optimized iterative algorithms and high-performance parallel implementations. In the Lighthouse ...

One of the main challenges in the design of modern clustering algorithms is that, in many applications, new data sets are continuously added into an already huge database. As a result, it is impractical to carry out data clustering from scratch whenever there are new data instances added into the database. One way to tackle this challenge is to incorporate a clustering algorithm that operates i...

Fifteen populations of Pimpinellifoliaeae section from the species; Rosa pimpinellifolia, R. hemispherica, R. foetida and a new species, R. abrica, were collected from eight provinces of Iran and were studied on the basis of their morphological characters. In each population five plants were randomly selected and some branches were harvested in spring and autumn for studying their vegetative an...

We present our work in progress on the Lighthouse framework, a multifaceted web-based user interface to a taxonomy of numerical software. The taxonomy provides an organized anthology of software components and programming tools needed for the construction of highly-optimized matrix algebra software. It builds upon and improves existing collections of numerical software, adding tools for the tun...

Fault detection is vital to wireless sensor networks since node death is a typical fault. One of the central challenges is to design a detection algorithm which has good performance in energy efficiency. In this paper, we propose an intelligent fault detection algorithm based on numerical taxonomy. Firstly, all nodes are divided into clusters according to their geographical distribution. Beside...