Abstract

Abstract
Blood pressure (BP) determination is a fundamental parameter in cardiovascular assessment. The gold standard method to measure BP is based on the inflatable arm cuff, however has several disadvantages for continuous monitoring. New techniques were developed to overcome these limitations using correlations between the pulse transit time (PTT) and BP. This work draws attention to the PTT rationale using several methods. In order to determine the PTT, an electrocardiogram (ECG) was used combined with multiple photoplethysmography (PPG) sensors applied to different arm locations, these signals were acquired with a bioPLUX device. The Ultrassound system (SonoSite Edge) was used to measure the artery diameter. As reference, BP was measured using a cuff- based sphygmomanometric device. Measurements were performed in a study population of 36 volunteers. The correlation coefficient for DBP determined and DBP measured was r = 0,689. The results suggest PTT deduced from different locations can be used to measure BP.

Abstract
High-performance computing applications that will run on future exascale-class supercomputing systems are projected to encounter accelerated rates of faults and errors. For these large-scale systems, maintaining fault resilient operation is a key challenge. The most widely used resiliency approach today, which is based on checkpoint and rollback (C/R) recovery, is not expected to remain viable in the presence of frequent errors and failures. In this paper, we present a framework for enabling application-level recovery from error states through fault amelioration. Our approach is based on programming model extensions that enable algorithm-based fault amelioration knowledge to be expressed as an intrinsic feature of the programming environment. This is accomplished through a set of language extensions that are supported by a compiler infrastructure and a runtime system. We experimentally demonstrate that the framework enables recovery from errors in the program state with low overhead to the application performance. © 2015 IEEE.

Abstract
This paper deals with the radial distribution system reconfiguration problem in a multi-objective scope, aiming to determine the optimal configuration by means of minimization of active power losses and several reliability indices. A novel way to calculate these indices under a mixed-integer linear programming (MILP) approach is provided. Afterwards, an efficient implementation of the e-constraint method using lexicographic optimization is employed to solve the multi-objective optimization problem, which is formulated as a MILP problem. After the Pareto Efficient solution set is generated, a multi-attribute decision making procedure is used, namely the technique for order preference by similarity to ideal solution (TOPSIS) method, so that a decision maker (DM) can express preferences over the solutions and facilitate the final selection.

Abstract

Abstract
Isolated islanded energy systems do not have any connection to continental grids and nor do have an easy access to conventional energy sources. In order to face this specific challenge, El Hierro project on the small El Hierro island, Canary Islands, was put in practice. This project embodies the first major Megawatt-level energy project by linking energy storage systems with wind power generation using water storage delivered by the pumping system between two artificial lakes. In this paper, we analyse the project and discuss the first results after the inauguration.