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Land of High Hopes
(2019)
We are living in the era of sophisticated, state-of-the-art technology, artificial intelligence, accelerating data sciences at ultimate speed and sheer unlimited possibilities. We are able to shoot unmanned rockets equipped with vehicles into the orbit. We can afford to spend fortunes on research and development. However, and that leaves me bloodcurdling and furious, we haven´t managed yet to settle at least some of the most pressing global humanitarian needs: access to food, water, electricity, education and healthcare. So how can we be proud of any achievements? What does make us proud anyway?! ...
Texturen können als Oberflächenstrukturen realer Objekt aufgefasst werden und sind Variationen in Farbe, Geometrie, Transparenz, usw.. Im Gegensatz zu Algorithmen für die künstliche Generierung von Texturen gibt es nur wenige Ansätze zu Textur-Synthese-Sprachen oder zu Hilfsmittel für die Textur-Beschreibung. Die bekannten Werkzeuge decken zudem jeweils nur Teilgebiete der Generierung ab. Mit HiLDTe (Hierachical Language for the Description of Textures) ist nun eine Sprache entwickelt worden, mit der möglichst alle bekannten Texturtypen beschrieben werden können. HiLDTe basiert auf einem am Fachgebiet GRIS entwickelten Texturmodell, in dem Texturen generische, eventuell komplex zusammengesetzte Objekte repräsentieren. Aufgabe dieser Arbeit war es nun, Konzepte für die Sprache HiLDTe zu entwickeln, eine entsprechende Grammatik aufzubauen und mit Hilfe der UNIX-Werkzeuge LEX und YACC einen Compiler zu implementieren, mit dem ein ausführbarer Zwischen-Code für die in HiLDTe spezifizierten Texturen erstellt wird.
In this paper, we present an approach to adopt UMLsec, which is defined for UML 1.5, to support the current UML version 2.3. The new profile UMLsec4UML2 is technically constructed as a UML profile diagram, which is equipped with a number of integrity conditions expressed using OCL. Consequently, the UMLsec4UML2-profile can be loaded in any Eclipse-based EMF- and MDT-compatible UML editing tool to develop and analyze different kinds of security models. The OCL constraints replace the static checks of the tool support for the old UMLsec defined for UML 1.5. Thus, the UMLsec4UML2-profile not only provides the whole expresiveness of UML2.3 for security modeling, it also brings considerably more freedom in selecting a basic UML editing tool, and it integrates modeling and analyzing security models. Since UML2.3 comprises new diagram types, as well as new model elements and new semantics of diagram types already contained in UML1.5, we consider a number of these changes in detail. More specifically, we consider composite structure and sequence diagrams with respect to modeling security properties according to the original version of UMLsec. The goal is to use UMLsec4UML2 to specify architectural security patterns.
Investing as Random Trial
(2017)
We introduce an investment algorithm for a market of individual securities. The investment algorithm is derived from constraints depending on investment parameters in order to limit the risk and to take into account an individual investor. One constraint is devoted to trading costs. Purchased securities are selected randomly among securities that meet the buy condition, making trading a random trial. Simulations with historical price data are demonstrated for a simple example: The buy condition is evaluated on the basis of the price relationship for two subsequent trading days and the sales condition is defined by holding securities only for one day. A trading expert evaluates the expected return for the investment algorithm with respect to the random selection. Thus, the expert informs precisely on how many market players perform using the same investment algorithm. Its findings are for a parametrized set of buy conditions simultaneously, which makes a trading expert a valuable tool for theorists as well as for practitioners. In our example, the trading expert demonstrated clearly a significant mean reversion effect for a horizon of one day.
The construction of a basis of a certain lattice of interest is a basic tool in many fields of algorithmic number theory. All too often we can not compute with the original lattices because of irrational numbers involved but have to work with approximations of them. While helpful bounds were shown about the reduction of lattice bases in cite{buchmann94reducing}, here we introduce the notion of a $(epsilon,delta)$-constructable basis of a lattice and determine the precision of vectors that is necessary to extend a set to a $(epsilon,delta)$-constructable basis.
The task of the Center for Language Research is to provide content-based English language instruction for students of computer science and engineering. As such, we find ourselves at the confluence of many of the streams currently running through the English Language Teaching profession, including English for Science and Technology (EST), English for Academic Purposes (EAP), English for Specific Purposes (ESP), Computer-assisted language learning (CALL), content-based instruction, and multimedia applications in foreign language pedagogy. This paper describes our initial attempts to construct a number of World Wide Web pages where students will be able to study EST, EAP, and computer science topics on their own in a multimedia environment.