Two-Sided Derivatives for Regular Expressions and for Hairpin Expressions

The aim of this paper is to design the polynomial construction of a finite recognizer for hairpin completions of regular languages. This is achieved by considering completions as new expression operators and by applying derivation techniques to the associated extended expressions called hairpin expressions. More precisely, we extend partial derivation of regular expressions to two-sided partial derivation of hairpin expressions and we show how to deduce a recognizer for a hairpin expression from its two-sided derived term automaton, providing an alternative proof of the fact that hairpin completions of regular languages are linear context-free.Comment: 28 page

The computational linguistics of biological sequences

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Protein sequences are analogous in many respects, particularly their folding behavior. Proteins have a much richer variety of interactions, but in theory the same linguistic principles could come to bear in describing dependencies between distant residues that arise by virtue of three-dimensional structure. This tutorial will concentrate on nucleic acid sequences

An Investigation of the Lattice Boltzmann Method for Large Eddy Simulation of Complex Turbulent Separated Flow

Lattice Boltzmann method (LBM) is a relatively recent computational technique for fluid dynamics that derives its basis from a mesoscopic physics involving particle motion. While the approach has been studied for different types of fluid flow problems, its application to eddy-capturing simulations of building block complex turbulent flows of engineering interest has not yet received sufficient attention. In particular, there is a need to investigate its ability to compute turbulent flow involving separation and reattachment. Thus, in this work, large eddy simulation (LES) of turbulent flow over a backward facing step, a canonical benchmark problem which is characterized by complex flow features, is performed using the LBM. Multiple relaxation time formulation of the LBM is considered to maintain enhanced numerical stability in a locally refined, conservative multiblock gridding strategy, which allows efficient implementation. Dynamic procedure is used to adapt the proportionality constant in the Smagorinsky eddy viscosity subgrid scale model with the local features of the flow. With a suitable reconstruction procedure to represent inflow turbulence, computation is carried out for a Reynolds number of 5100 based on the maximum inlet velocity and step height and an expansion ratio of 1.2. It is found that various turbulence statistics, among other flow features, in both the recirculation and reattachment regions are in good agreement with direct numerical simulation and experimental data

A TYPE ANALYSIS OF REWRITE STRATEGIES

Rewrite strategies provide an algorithmic rewriting of terms using strategic compositions of rewrite rules. Due to the programmability of rewrites, errors are often made due to incorrect compositions of rewrites or incorrect application of rewrites to a term within a strategic rewriting program. In practical applications of strategic rewriting, testing and debugging becomes substantially time-intensive for large programs applied to large inputs derived from large term grammars. In essence, determining which rewrite in what position in a term did or did not re comes down to logging, tracing and/or di -like comparison of inputs to outputs. In this thesis, we explore type-enabled analysis of strategic rewriting programs to detect errors statically. In particular, we introduce high-precision types to closely approximate the dynamic behavior of rewriting. We also use union types to track sets of types due to presence of strategic compositions. In this framework of high-precision strategic typing, we develop and implement an expressive type system for a representative strategic rewriting language TL. The results of this research are sufficiently broad to be adapted to other strategic rewriting languages. In particular, the type-inferencing algorithm does not require explicit type annotations for minimal impact on an existing language. Based on our experience with the implementation, the type system significantly reduces the time and effort to program correct rewrite strategies while performing the analysis on the order of thousands of source lines of code per second

Procedural modeling of cities with semantic information for crowd simulation

En aquesta tesi de màster es presenta un sistema per a la generació procedural de ciutats poblades. Avui en dia poblar entorns virtuals grans tendeix a ser una tasca que requereix molt d’esforç i temps, i típicament la feina d’artistes o programadors experts. Amb aquest sistema es vol proporcionar una eina que permeti als usuaris generar entorns poblats d’una manera més fàcil i ràpida, mitjançat l’ús de tècniques procedurals. Les contribucions principals inclouen: la generació d’una ciutat virtual augmentada semànticament utilitzant modelat procedural basat en gramàtiques de regles, la generació dels seus habitants virtuals utilitzant dades estadístiques reals, i la generació d’agendes per a cada individu utilitzant també un mètode procedural basat en regles, el qual combina la informació semàntica de la ciutat amb les característiques i necessitats dels agents autònoms. Aquestes agendes individuals són usades per a conduir la simulació dels habitants, i poden incloure regles com a tasques d’alt nivell, l’avaluació de les quals es realitza al moment de començar-les. Això permet simular accions que depenguin del context, i interaccions amb altres agents.En esta tesis de máster se presenta un sistema para la generación procedural de ciudades pobladas. Hoy en día poblar entornos virtuales grandes tiende a ser una tarea que requiere de mucho tiempo y esfuerzo, y típicamente el trabajo de artistas o programadores expertos. Con este sistema se pretende proporcionar una herramienta que permita a los usuarios generar entornos poblados de un modo más fácil y rápido, mediante el uso de técnicas procedurales. Las contribuciones principales incluyen: la generación de una ciudad virtual aumentada semánticamente utilizando modelado procedural basado en gramáticas de reglas, la generación de sus habitantes virtuales utilizando datos estadísticos reales, y la generación de agendas para cada individuo utilizando también un método procedural basado en reglas, el cual combina la información semántica de la ciudad con las características y necesidades de los agentes autónomos. Estas agendas individuales son usadas para conducir la simulación de los habitantes, y pueden incluir reglas como tareas de alto nivel, la evaluación de las cuales se realiza cuando empiezan. Esto permite simular acciones que dependan del contexto, e interacciones con otros agentes.In this master thesis a framework for procedural generation of populated cities is presented. Nowadays, the population of large virtual environments tends to be a time-consuming task, usually requiring the work of expert artists or programmers. With this system we aim at providing a tool that can allow users to generate populated environments in an easier and faster way, by relying on the usage of procedural techniques. Our main contributions include: a generation of semantically augmented virtual cities using procedural modelling based on rule grammars, a generation of a virtual population using real-world data, and a generation of agendas for each individual inhabitant by using a procedural rule-based approach, which combines the city semantics with the autonomous agents characteristics and needs. The individual agendas are then used to drive a crowd simulation in the environment, and may include high-level rule tasks whose evaluation is delayed until they get triggered. This feature allows us to simulate context-dependant actions and interactions with other agents

Traffic and Related Self-Driven Many-Particle Systems

Since the subject of traffic dynamics has captured the interest of physicists, many astonishing effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by so-called ``phantom traffic jams'', although they all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction of the traffic volume cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize in lanes, while similar systems are ``freezing by heating''? Why do self-organizing systems tend to reach an optimal state? Why do panicking pedestrians produce dangerous deadlocks? All these questions have been answered by applying and extending methods from statistical physics and non-linear dynamics to self-driven many-particle systems. This review article on traffic introduces (i) empirically data, facts, and observations, (ii) the main approaches to pedestrian, highway, and city traffic, (iii) microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts like a general modelling framework for self-driven many-particle systems, including spin systems. Subjects such as the optimization of traffic flows and relations to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are discussed as well.Comment: A shortened version of this article will appear in Reviews of Modern Physics, an extended one as a book. The 63 figures were omitted because of storage capacity. For related work see http://www.helbing.org