Sr0.9_{0.9}K0.1_{0.1}Zn1.8_{1.8}Mn0.2_{0.2}As2_{2}: a ferromagnetic semiconductor with colossal magnetoresistance

A bulk diluted magnetic semiconductor (Sr,K)(Zn,Mn)$_{2}$As$_{2}$ was synthesized with decoupled charge and spin doping. It has a hexagonal CaAl$_{2}$Si$_{2}$-type structure with the (Zn,Mn)$_{2}$As$_{2}$ layer forming a honeycomb-like network. Magnetization measurements show that the sample undergoes a ferromagnetic transition with a Curie temperature of 12 K and \revision{magnetic moment reaches about 1.5 $\mu_{B}$/Mn under $\mu_0H$ = 5 T and $T$ = 2 K}. Surprisingly, a colossal negative magnetoresistance, defined as $[\rho(H)-\rho(0)]/\rho(0)$, up to $-$38\% under a low field of $\mu_0H$ = 0.1 T and to $-$99.8\% under $\mu_0H$ = 5 T, was observed at $T$ = 2 K. The colossal magnetoresistance can be explained based on the Anderson localization theory.Comment: Accepted for publication in EP

An integrated approach for automatic semantic structure extraction in document images

Abstract. In this paper we present an integrated approach for semantic structure extraction in document images. Document images are initially processed to extract both their layout and logical structures on the base of geometrical and spatial information. Then, textual content of logical components is employed for automatic semantic labeling of layout structures. To support the whole process different machine learning techniques are applied. Experimental results on a set of biomedical multi-page documents are discussed and future directions are drawn.

The search for genericity in graphics recognition applications: Design issues of the Qgar software system

Colloque avec actes et comité de lecture. internationale.International audienceThis paper presents the main design and development issues of the Qgar software environment for graphics recognition applications. We aim at providing stable and robust implementations of state-of-the-art methods and algorithms, within an intuitive and user-friendly environment. The resulting software system is open, so that our applications can be easily interfaced with other systems, and, conversely, that third-party applications can be "plugged" into our environment with little effort. The paper also presents a quick tour of the various components of the Qgar environment, and concentrates on the usefulness of this kind of system for testing and evaluation purposes