CRAY mini manual. Revision D

This document briefly describes the use of the CRAY supercomputers that are an integral part of the Supercomputing Network Subsystem of the Central Scientific Computing Complex at LaRC. Features of the CRAY supercomputers are covered, including: FORTRAN, C, PASCAL, architectures of the CRAY-2 and CRAY Y-MP, the CRAY UNICOS environment, batch job submittal, debugging, performance analysis, parallel processing, utilities unique to CRAY, and documentation. The document is intended for all CRAY users as a ready reference to frequently asked questions and to more detailed information contained in the vendor manuals. It is appropriate for both the novice and the experienced user

The Scalable Brain Atlas: instant web-based access to public brain atlases and related content

The Scalable Brain Atlas (SBA) is a collection of web services that provide unified access to a large collection of brain atlas templates for different species. Its main component is an atlas viewer that displays brain atlas data as a stack of slices in which stereotaxic coordinates and brain regions can be selected. These are subsequently used to launch web queries to resources that require coordinates or region names as input. It supports plugins which run inside the viewer and respond when a new slice, coordinate or region is selected. It contains 20 atlas templates in six species, and plugins to compute coordinate transformations, display anatomical connectivity and fiducial points, and retrieve properties, descriptions, definitions and 3d reconstructions of brain regions. The ambition of SBA is to provide a unified representation of all publicly available brain atlases directly in the web browser, while remaining a responsive and light weight resource that specializes in atlas comparisons, searches, coordinate transformations and interactive displays.Comment: Rolf K\"otter sadly passed away on June 9th, 2010. He co-initiated this project and played a crucial role in the design and quality assurance of the Scalable Brain Atla

USING THE AUTOMATIC VECTORISATION METHOD IN GENERATING THE VECTOR ALTIMETRY OF THE HISTORICAL VLTAVA RIVER VALLEY

The article describes, in detail, the generation procedure of vector altimetry of an upper and middle course of the Vltava River historical valley. By the historical valley, the shape of the river valley before the construction of dams on the Vltava River in the second half of the 20th century is understood. The vector altimetry will serve as the base for creating a 3D model of this valley. The initial input data were old maps, specifically scanned first-edition prints of the State Map 1 : 5 000 - Derived (SMO-5). By combining automatic and manual vectorisation, the altimetry component of these maps (contour lines and spot elevations) will be converted to a vector format. Individual processing steps, including the description of automatic vectorisation in the ArcScan extension to the ArcGIS system, together with examples of the results, are presented in the text below

Cooperative Text and Line Art Extraction from a Topographic Map

The black layer is digitized from a USGS topographic map digitized at 1000 dpi. The connected components of this layer are analyzed and separated into line art, text, and icons in two passes. The paired street casings are converted to polylines by vectorization and associated with street labels from the character recognition phase. The accuracy of character recognition is shown to improve by taking account of the frequently occurring overlap of line art with street labels. The experiments show that complete vectorization of the black line-layer bitmap is the major remaining problem

Automatic and topology-preserving gradient mesh generation for image vectorization

Demonska vjera polazi od toga da se ne nalazi isključivo u nevjeri, nego je ona onkraj nevjere. Ovim radom smo prvo željeli prikazati glavne postavke najbitnijih elemenata teologalne vjere da bismo kasnije kroz filozofske teze F. Hadjadja prikazali glavna obilježja vjere zlih demona koja su duhovnog karaktera i predstavljaju veliku opasnost za čovjeka i njegovu vjeru. Unatoč različitim tumačenjima, Hadjadj želi upozoriti na to da se zli demoni ne nalaze samo među ateistima, agnosticima i ostalim pokretima koji, na neki način, niječu Božu opstojnost, nego ti zli demoni zapravo vjeruju, pa zato za polazište uzima redak iz Jakovljeve poslanice u kojoj piše da oni „vjeruju i dršću”. Na kraju smo ovim radom prikazali važnost sinteze duše i tijela, odnosno utjelovljenja u kršćanstvu jer je misterij katoličke vjere misterij utjelovljenja i nemoguće je odbacivati tjelesnost kao što je to slučaj u različitim spiritualističkim dimenzijama.Demonic faith is not strictly associated with infidelity itself, but rather exists beyond it. This work aims to present the main postulates of the most crucial elements of the theological faith in order to show, using F. Hadjadj's philosophical thesis, the main characteristics associated with evil demons, which are of the spiritual nature and present great danger for man and his faith. Despite various interpretations, Hadjadj wishes to point out that evil demons do not dwel lonly within atheists, agnostics and other movements which, in a way, negate the existence of God, but that these evil demons actually do believe, and therefore he uses as a starting point the line from the Epistle of Jacob that states that demons „believe and tremble”. In the end, this work presented the importance of the body-soul synthesis, which is the incarnation in Christianity, since the mistery of the Catholic faith is the mistery of the incarnation, and it is impossible to discard corporeality, which is the case in various spiritual dimensions

API design for machine learning software: experiences from the scikit-learn project

Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts. In this paper, we present and discuss our design choices for the application programming interface (API) of the project. In particular, we describe the simple and elegant interface shared by all learning and processing units in the library and then discuss its advantages in terms of composition and reusability. The paper also comments on implementation details specific to the Python ecosystem and analyzes obstacles faced by users and developers of the library