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RDF is widely used in order to catalogue the chaos of data across the internet. But these descriptions must be stored, evaluated, analyzed and verified. This creates the need to search for an environment to realize these aspects and strengthen RDFs influence. InterSystems postrelational database Caché exposes many features that are similar to RDF and provide persistence with semantic part. Some models for relational databases exist but these lack features like object-oriented data-structures and multidimensional variables. The aim of this thesis is to develop an RDF model for Caché that saves RDF data in an object-oriented form. Furthermore an interface for importing RDF data will be presented and implemented.
Zellularautomaten sind ein massiv paralleles Berechnungsmodell, das aus sehr vielen identischen einfachen Prozessoren oder Zellen besteht, die homogen miteinander verbunden sind und parallel arbeiten. Es gibt Zellularautomaten in unterschiedlichen Ausprägungen. Beispielsweise unterscheidet man die Automaten nach der zur Verfügung stehenden Zeit, nach paralleler oder sequentieller Verarbeitung der Eingabe oder durch Beschränkungen der Kommunikation zwischen den einzelnen Zellen. Benutzt man Zellularautomaten zum Erkennen formaler Sprachen und betrachtet deren generative Mächtigkeit, dann kann bereits das einfachste zellulare Modell kontextsensitive Sprachen akzeptieren. In dieser Arbeit wird die Beschreibungskomplexität von Zellularautomaten betrachtet. Es wird untersucht, wie sich die Beschreibungsgröße einer formalen Sprache verändern kann, wenn die Sprache mit unterschiedlichen Typen von Zellularautomaten oder sequentiellen Modellen beschrieben wird. Ein wesentliches Ergebnis im ersten Teil der Arbeit ist, daß zwischen zwei Automatenklassen, deren entsprechende Sprachklassen echt ineinander enthalten oder unvergleichbar sind, nichtrekursive Tradeoffs existieren. Das heißt, der Größenzuwachs beim Wechsel von einem Automatenmodell in das andere läßt sich durch keine rekursive Funktion beschränken. Im zweiten Teil der Arbeit werden Zellularautomaten dahingehend beschränkt, daß nur eine feste Zellenzahl zugelassen ist. Zusätzlich werden Automaten mit unterschiedlichem Grad an bidirektionaler Kommunikation zwischen den einzelnen Zellen betrachtet, und es wird untersucht, welche Auswirkungen auf die Beschreibungsgröße unterschiedliche Grade an bidirektionaler Kommunikation haben können. Im Gegensatz zum unbeschränkten Modell können polynomielle und damit rekursive obere Schranken bei Umwandlungen zwischen den einzelnen Modellen bewiesen werden. Durch den Beweis unterer Schranken kann in fast allen Fällen auch die Optimalität der Konstruktionen belegt werden.
It is shown that between one-turn pushdown automata (1-turn PDAs) and deterministic finite automata (DFAs) there will be savings concerning the size of description not bounded by any recursive function, so-called non-recursive tradeoffs. Considering the number of turns of the stack height as a consumable resource of PDAs, we can show the existence of non-recursive trade-offs between PDAs performing k+ 1 turns and k turns for k >= 1. Furthermore, non-recursive trade-offs are shown between arbitrary PDAs and PDAs which perform only a finite number of turns. Finally, several decidability questions are shown to be undecidable and not semidecidable.
In bioinformatics, biochemical signal pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically obtaining the most appropriate model and learning its parameters is extremely interesting. One of the most often used approaches for model selection is to choose the least complex model which “fits the needs”. For noisy measurements, the model which has the smallest mean squared error of the observed data results in a model which fits too accurately to the data – it is overfitting. Such a model will perform good on the training data, but worse on unknown data. This paper propose as model selection criterion the least complex description of the observed data by the model, the minimum description length. For the small, but important example of inflammation modeling the performance of the approach is evaluated. Keywords: biochemical pathways, differential equations, septic shock, parameter estimation, overfitting, minimum description length.
Data driven automatic model selection and parameter adaptation – a case study for septic shock
(2004)
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. This paper propose as model selection criterion the least complex description of the observed data by the model, the minimum description length. For the small, but important example of inflammation modeling the performance of the approach is evaluated.
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. In this paper, for the small, important example of inflammation modeling a network is constructed and different learning algorithms are proposed. It turned out that due to the nonlinear dynamics evolutionary approaches are necessary to fit the parameters for sparse, given data. Keywords: model parameter adaption, septic shock. coupled differential equations, genetic algorithm.
Work on proving congruence of bisimulation in functional programming languages often refers to [How89,How96], where Howe gave a highly general account on this topic in terms of so-called lazy computation systems . Particularly in implementations of lazy functional languages, sharing plays an eminent role. In this paper we will show how the original work of Howe can be extended to cope with sharing. Moreover, we will demonstrate the application of our approach to the call-by-need lambda-calculus lambda-ND which provides an erratic non-deterministic operator pick and a non-recursive let. A definition of a bisimulation is given, which has to be based on a further calculus named lambda-~, since the na1ve bisimulation definition is useless. The main result is that this bisimulation is a congruence and contained in the contextual equivalence. This might be a step towards defining useful bisimulation relations and proving them to be congruences in calculi that extend the lambda-ND-calculus.
We modify the concept of LLL-reduction of lattice bases in the sense of Lenstra, Lenstra, Lovasz [LLL82] towards a faster reduction algorithm. We organize LLL-reduction in segments of the basis. Our SLLL-bases approximate the successive minima of the lattice in nearly the same way as LLL-bases. For integer lattices of dimension n given by a basis of length 2exp(O(n)), SLLL-reduction runs in O(n.exp(5+epsilon)) bit operations for every epsilon > 0, compared to O(exp(n7+epsilon)) for the original LLL and to O(exp(n6+epsilon)) for the LLL-algorithms of Schnorr (1988) and Storjohann (1996). We present an even faster algorithm for SLLL-reduction via iterated subsegments running in O(n*exp(3)*log n) arithmetic steps.
In the last decade, much effort went into the design of robust third-person pronominal anaphor resolution algorithms. Typical approaches are reported to achieve an accuracy of 60-85%. Recent research addresses the question of how to deal with the remaining difficult-toresolve anaphors. Lappin (2004) proposes a sequenced model of anaphor resolution according to which a cascade of processing modules employing knowledge and inferencing techniques of increasing complexity should be applied. The individual modules should only deal with and, hence, recognize the subset of anaphors for which they are competent. It will be shown that the problem of focusing on the competence cases is equivalent to the problem of giving precision precedence over recall. Three systems for high precision robust knowledge-poor anaphor resolution will be designed and compared: a ruleset-based approach, a salience threshold approach, and a machine-learning-based approach. According to corpus-based evaluation, there is no unique best approach. Which approach scores highest depends upon type of pronominal anaphor as well as upon text genre.