Transductions Computed by One-Dimensional Cellular Automata

Cellular automata are investigated towards their ability to compute transductions, that is, to transform inputs into outputs. The families of transductions computed are classified with regard to the time allowed to process the input and to compute the output. Since there is a particular interest in fast transductions, we mainly focus on the time complexities real time and linear time. We first investigate the computational capabilities of cellular automaton transducers by comparing them to iterative array transducers, that is, we compare parallel input/output mode to sequential input/output mode of massively parallel machines. By direct simulations, it turns out that the parallel mode is not weaker than the sequential one. Moreover, with regard to certain time complexities cellular automaton transducers are even more powerful than iterative arrays. In the second part of the paper, the model in question is compared with the sequential devices single-valued finite state transducers and deterministic pushdown transducers. It turns out that both models can be simulated by cellular automaton transducers faster than by iterative array transducers.Comment: In Proceedings AUTOMATA&JAC 2012, arXiv:1208.249

Proceedings of JAC 2010. Journées Automates Cellulaires

The second Symposium on Cellular Automata “Journ´ees Automates Cellulaires” (JAC 2010) took place in Turku, Finland, on December 15-17, 2010. The first two conference days were held in the Educarium building of the University of Turku, while the talks of the third day were given onboard passenger ferry boats in the beautiful Turku archipelago, along the route Turku–Mariehamn–Turku. The conference was organized by FUNDIM, the Fundamentals of Computing and Discrete Mathematics research center at the mathematics department of the University of Turku. The program of the conference included 17 submitted papers that were selected by the international program committee, based on three peer reviews of each paper. These papers form the core of these proceedings. I want to thank the members of the program committee and the external referees for the excellent work that have done in choosing the papers to be presented in the conference. In addition to the submitted papers, the program of JAC 2010 included four distinguished invited speakers: Michel Coornaert (Universit´e de Strasbourg, France), Bruno Durand (Universit´e de Provence, Marseille, France), Dora Giammarresi (Universit` a di Roma Tor Vergata, Italy) and Martin Kutrib (Universit¨at Gie_en, Germany). I sincerely thank the invited speakers for accepting our invitation to come and give a plenary talk in the conference. The invited talk by Bruno Durand was eventually given by his co-author Alexander Shen, and I thank him for accepting to make the presentation with a short notice. Abstracts or extended abstracts of the invited presentations appear in the first part of this volume. The program also included several informal presentations describing very recent developments and ongoing research projects. I wish to thank all the speakers for their contribution to the success of the symposium. I also would like to thank the sponsors and our collaborators: the Finnish Academy of Science and Letters, the French National Research Agency project EMC (ANR-09-BLAN-0164), Turku Centre for Computer Science, the University of Turku, and Centro Hotel. Finally, I sincerely thank the members of the local organizing committee for making the conference possible. These proceedings are published both in an electronic format and in print. The electronic proceedings are available on the electronic repository HAL, managed by several French research agencies. The printed version is published in the general publications series of TUCS, Turku Centre for Computer Science. We thank both HAL and TUCS for accepting to publish the proceedings.Siirretty Doriast

A Discriminative Model of Stochastic Edit Distance in the form of a Conditional Transducer

pages 240-252International audienceMany real-world applications such as spell-checking or DNA analysis use the Levenshtein edit-distance to compute similarities between strings. In practice, the costs of the primitive edit operations (insertion, deletion and substitution of symbols) are generally hand-tuned. In this paper, we propose an algorithm to learn these costs. The underlying model is a probabilitic transducer, computed by using grammatical inference techniques, that allows us to learn both the structure and the probabilities of the model. Beyond the fact that the learned transducers are neither deterministic nor stochastic in the standard terminology, they are conditional, thus independant from the distributions of the input strings. Finally, we show through experiments that our method allows us to design cost functions that depend on the string context where the edit operations are used. In other words, we get kinds of \textit{context-sensitive} edit distances

Linking Programming to Representations : Understanding meaning-making in physics education through semiotic resources

Programming is investigated with a social semiotic lens to study how programming can contribute to meaning-making in physics. The analysis focuses on how new and dynamic representations can be created with the help of programming and how programming allows students to investigate and create their own models of physical phenomena. This is described from a semiotic perspective and the semiotic perspective is also developed with new theoretical constructions to better describe the students' use of representations in physics

New experimental and computational methods for ultrasound brain tomography

Fast, portable, and affordable neuroimaging is currently unavailable in clinical practice, hindering prevention and treatment of pathologies such as stroke, a leading cause of death and disability worldwide. Full-waveform inversion (FWI), an ultrasound-based tomographic technique, has been recently proposed as a solution to this problem, but is yet to be successfully applied experimentally. Two fundamental barriers hinder its experimental application: a lack of numerical models that accurately replicate experimental measurements, and of domain-specific software that implements FWI algorithms efficiently. Here, I address both problems, opening the door to universally available neuroimaging. Addressing the first barrier entails finding numerical models that can explain the behaviour of the acquisition system: the transmission and reception response of the transducers, and their spatial location and orientation. As I demonstrate here, existing position-estimation methods fail when the surface of the transducers is bigger than the wavelength, a prerequisite for imaging through the skull, while available response-estimation techniques cannot achieve the precision required by full-wave methods. Therefore, I present spatial response identification, a new algorithm for transducer calibration and modelling, and show how it can be used to explain experimental devices with higher accuracy than existing methods. Additionally, I present experimental reconstructions of a tissue-mimicking phantom, achieving improved imaging quality with respect to standard calibration techniques. The second barrier stems from the fact that FWI is mathematically challenging and orders of magnitude more computationally expensive than conventional ultrasound imaging, while there is an absence of open codes, slowing the pace of research and hindering reproducibility. Therefore, I introduce Stride, an open-source Python library that combines high-level interfaces with automatically generated, high-performance solvers and scalable parallelisation. Here, I demonstrate that Stride can achieve state-of-the-art modelling accuracy and how it can be used to image in 2D and 3D, scaling from a local workstation to a high-performance cluster.Open Acces

Frustration in Biomolecules

Biomolecules are the prime information processing elements of living matter. Most of these inanimate systems are polymers that compute their structures and dynamics using as input seemingly random character strings of their sequence, following which they coalesce and perform integrated cellular functions. In large computational systems with a finite interaction-codes, the appearance of conflicting goals is inevitable. Simple conflicting forces can lead to quite complex structures and behaviors, leading to the concept of "frustration" in condensed matter. We present here some basic ideas about frustration in biomolecules and how the frustration concept leads to a better appreciation of many aspects of the architecture of biomolecules, and how structure connects to function. These ideas are simultaneously both seductively simple and perilously subtle to grasp completely. The energy landscape theory of protein folding provides a framework for quantifying frustration in large systems and has been implemented at many levels of description. We first review the notion of frustration from the areas of abstract logic and its uses in simple condensed matter systems. We discuss then how the frustration concept applies specifically to heteropolymers, testing folding landscape theory in computer simulations of protein models and in experimentally accessible systems. Studying the aspects of frustration averaged over many proteins provides ways to infer energy functions useful for reliable structure prediction. We discuss how frustration affects folding, how a large part of the biological functions of proteins are related to subtle local frustration effects and how frustration influences the appearance of metastable states, the nature of binding processes, catalysis and allosteric transitions. We hope to illustrate how Frustration is a fundamental concept in relating function to structural biology.Comment: 97 pages, 30 figure

Micro-poutres résonantes à base de films minces de nitrure d’aluminium piézoélectriques, application aux capteurs de gaz gravimétriques

Resonant MEMS and NEMS are excellent candidate for the realization of low cost and high resolution gas sensing systems that have several applications in security, defense, and environment and health care domains. However, the question of the transduction technique used to couple micro or nano scale signals to the macro scale is still a key issue. Piezoelectric transduction can be advantageously exploited but has been rarely studied at the nano-scale. The objective of this PhD is thus to progress toward the realization of high-resolution gas sensor using piezoelectric micro/nano cantilevers resonators and cover the whole prototyping chain from device fabrication to proof of principle experiment. Our first contribution in this research relates the analytical modeling of the sensing performance and the system and design optimization. In particular we demonstrate that decreasing the piezoelectric active film thickness below 100 nm is particularly beneficial. The second contribution relates the fabrication, characterization and demonstration of the high sensing performances of 80 μm long cantilevers embedding a 50 nm thick piezoelectric AlN film for transduction. These devices exhibit state of the art performances in terms of resonance frequency deviation down to the 〖10〗^(-8) range. They allow thus the detection of Di-Methyl-Methyl-Phosphonate vapors, a sarin gas simulant, with concentration as low as 10 ppb. Although the level of integration of our sensing system is not sufficient for real life application, these results prove the high potential of these piezoelectric cantilever resonators for future industrial development.Les MEMS et NEMS résonants sont d'excellents candidats pour la réalisation de systèmes de détection de gaz haute résolution et faible couts ayant des applications dans les domaines de la sécurité, la défense, l'environnement et la santé. Cependant, la question du choix des techniques de transduction est toujours largement débattue. La transduction piézoélectrique pourrait être avantageusement exploitée mais elle est encore peu connue à l'échelle nanométrique. L'objectif de cette thèse est donc de progresser vers la réalisation de capteur de gaz à haute résolution à l'aide résonateurs à base de micro / nano poutres piézoélectriques en couvrant la chaîne de prototypage complète depuis les techniques de dépôt des matériaux jusqu'à l'expérience de preuve de principe de mesure de gaz. Pour cela, notre première contribution concerne la modélisation analytique des performances et l'optimisation, design et système, d'un capteur de gaz à base de poutres résonantes piézoélectriques. En particulier, nous démontrons que la diminution de l'épaisseur du film piézoélectrique actif sous la barre des 100 nm permet d'atteindre les meilleures performances. La deuxième contribution concerne la fabrication, la caractérisation et la démonstration des performances capteur de poutres résonantes de 80 μm de long exploitant un film piézoélectrique en AlN de 50 nm d'épais. Ainsi nous avons démontré expérimentalement la stabilité fréquentielle exceptionnelle de ces dispositifs atteignant des déviations standard de l'ordre de 〖10〗^(-8), au niveau de l’état de l'art. Ainsi, ils permettent la détection de vapeurs Di -Methyl -méthyl- phosphonates, un simulateur de gaz sarin, avec des concentrations aussi faibles que 10 ppb. Bien que le niveau d'intégration de notre système de détection ne soit pas suffisant, ces résultats prouvent le fort potentiel de ces résonateurs cantilever piézoélectriques pour un développement industriel futur