BACKGROUND Despite the importance of identifying and screening dyslipidemia to prevent coronary artery diseases CAD(Coronary Artery Disease), little information is available on dyslipidemia in our large area. So the present study aimed to assess the management status of lipid abnormalities and its association with other CAD risk factors in an urban population of southeast of Iran. METHODS Thi...

Monitoring antibiotic-resistant pneumococcal strains not covered by the 7-valent conjugate vaccine is an important priority. The Centers for Disease Control and Prevention's Active Bacterial Core Surveillance identified 68 invasive penicillin-nonsusceptible serotype 35B (PN35B) isolates recovered from 1995 to 2001 from patients residing in the states of California, Colorado, Connecticut, Georgi...

This paper introduces a novel technique that significantly reduces the computational costs to perform a restart in conflict-driven clause learning (CDCL) solvers. Our technique exploits the observation that CDCL solvers make many redundant propagations after a restart. It efficiently predicts which decisions will be made after a restart. This prediction is used to backtrack to the first level a...

Conflict-directed clause learning (CDCL) is the basis of SAT solvers with impressive performance on many problems. CDCL with restarts (CDCL-R) has been shown to have essentially the same reasoning power as unrestricted resolution (formally, they p-Simulate each other). We show that this property generalizes to multi-valued CNF formulas. In particular, for Signed (or Multi-Valued) CNF formulas, ...

Beside impressive progresses made by SAT solvers over the last ten years, only few works tried to understand why Conflict Directed Clause Learning algorithms (CDCL) are so strong and efficient on most industrial applications. We report in this work a key observation of CDCL solvers behavior on this family of benchmarks and explain it by an unsuspected side effect of their particular Clause Lear...

Hedlamp is a UK EPSRC grant funded research project in which we aim to tackle challenges with knowledge engineering of automated planning techniques when applied to real applications. Normally, successful deployment of planning technology relies on groups of planning experts encoding detailed domain models and investing large amounts of time maintaining them. We are developing a high level, app...

In recent years, there has been an increasing supply of digital, pedagogical tools, known as Digital Learning Objects (DLO) – digital resources (image, film, animation, etc.) and software developed specifically for educational purposes. In the area of Computer Science, teaching Databases present a particular challenge because of a lack of quality tools to work with Relational Algebra. The prese...

Binary label information is widely used semantic information in discriminative dictionary learning and non-negative matrix factorization. A Discriminative Dictionary Learning (DDL) algorithm uses the label of some data samples to enhance the discriminative property of sparse signals. A discriminative Non-negative Matrix Factorization (NMF) utilizes label information in learning discriminative b...