The FIMS (Far-ultraviolet IMaging Spectrograph; also known as SPEAR, Spectroscopy of Plasma Evolution from Astrophysical Radiation) is the primary payload of the STSAT-1, the first Korean science satellite, which was launched in September, 2003. The FIMS performs spectral imaging of diffuse far-ultraviolet emission with the unprecedented wide field of view and the relatively good spectral resolution. We present far-ultraviolet spectral observations of highly ionized interstellar medium including supernova remnants, superbubbles, soft X-ray shadows, and the molecular hydrogen fluorescent emission lines. The FIMS has detected He II, C III, 0 III, O IV, Si IV, O VI, and H2 fluorescent emission lines. The emission lines arise in shocked or thermally heated and in photo-ionized gases. We present an overview of the FIMS instrument and its initial observational results.

In this paper, we consider the problem of regrouping a number of service sites into a smaller number of service sites called centers. Each service site is represented as a point in the plane and has an associated value of service demand. We aim to group the sites so that each group has the balanced service demand and the sum of distances from the sites in the group to their corresponding center is minimized. To solve this problem, we propose a hybrid genetic algorithm that is combined with Voronoi diagrams. We provide a variety of experimental results by changing the weights of the two factors: service demands and distances. Our hybrid algorithm finds good approximate solutions in a shorter computation time in comparison with optimal solution by integer programming.

Given a protein, it is often necessary to study its geometric and physicochemical properties for studying its structure and predicting funtions of a protein. In this case, a connolly surface of a protein plays important roles for these purpose. A protein consists of a set of amino acids and a set of atoms comprise an amino acide. Since an atom can be represented by a hard 3D sphere in van der Waals model, a protein is usually modeled as a set of 3D spheres. In this paper, we present the algorithm for computing a connolly surface using Euclidean Voronoi diagram atoms of a protein. The algorithm initially locates the exterior aotms of a protein where connolly surface patches exist and computes the patches by tracking their boundary curves. Since a Euclidean Voronoi diagram is uniquely defined independent of probe radius different from other geometric structures, the connolly surfaces defined by probes of different radii can be computed without re-computing the Euclidean Voronoi diagram.