Logical definability of Y-tree and trellis systolic ω-languages

In this paper we investigate the correspondence (in the style of the well known Büchi Theorem) between ω-languages accepted by systolic automata and suitable (proper) extensions of the Monadic Second Order theory of one successor (MSO[<]). To this purpose we extend Y-tree and trellis systolic automata to deal with ω-words and we study the expressiveness, closure and decidability properties of the two classes of ω-languages accepted by Y-tree and trellis automata, respectively. We define, then, two extensions of MSO[<], MSO[<,adj] and MSO[<,2x], which allow to express Y-tree ω-languages and trellis ω-languages, respectively

CLiFF Notes: Research In Natural Language Processing at the University of Pennsylvania

CLIFF is the Computational Linguists\u27 Feedback Forum. We are a group of students and faculty who gather once a week to hear a presentation and discuss work currently in progress. The \u27feedback\u27 in the group\u27s name is important: we are interested in sharing ideas, in discussing ongoing research, and in bringing together work done by the students and faculty in Computer Science and other departments. However, there are only so many presentations which we can have in a year. We felt that it would be beneficial to have a report which would have, in one place, short descriptions of the work in Natural Language Processing at the University of Pennsylvania. This report then, is a collection of abstracts from both faculty and graduate students, in Computer Science, Psychology and Linguistics. We want to stress the close ties between these groups, as one of the things that we pride ourselves on here at Penn is the communication among different departments and the inter-departmental work. Rather than try to summarize the varied work currently underway at Penn, we suggest reading the abstracts to see how the students and faculty themselves describe their work. The report illustrates the diversity of interests among the researchers here, as well as explaining the areas of common interest. In addition, since it was our intent to put together a document that would be useful both inside and outside of the university, we hope that this report will explain to everyone some of what we are about

Automata for branching and layered temporal structures: An investigation into regularities of infinite transition systems

This manuscript is a revised version of the PhD Thesis I wrote under the supervision of Prof. Angelo Montanari at Udine University. The leitmotif underlying the results herein provided is that, given any infinite complex system (e.g., a computer program) to be verified against a finite set of properties, there often exists a simpler system that satisfies the same properties and, in addition, presents strong regularities (e.g., periodicity) in its structure. Those regularities can then be exploited to decide, in an effective way, which property is satisfied by the system and which is not. Perhaps the most natural and effective way to deal with inherent regularities of infinite systems is through the notion of finite-state automaton. Intuitively, a finite-state automaton is an abstract machine with only a bounded amount of memory at its disposal, which processes an input (e.g., a sequence of symbols) and eventually outputs true or false, depending on the way the machine was designed and on the input itself. The present book focuses precisely on automaton-based approaches that ease the representation of and the reasoning on properties of infinite complex systems. The most simple notion of finite-state automaton, is that of single-string automaton. Such a device outputs true on a single (finite or infinite) sequence of symbols and false on any other sequence. We will show how single-string automata processing infinite sequences of symbols can be successfully applied in various frameworks for temporal representation and reasoning. In particular, we will use them to model single ultimately periodic time granularities, namely, temporal structures that are left-bounded and that, ultimately, periodically group instants of the underlying temporal domain (a simple example of such a structure is given by the partitioning of the temporal domain of days into weeks). The notion of single-string automaton can be further refined by introducing counters in order to compactly represent repeated occurrences of the same subsequence in the given input. By introducing restricted policies of counter update and by exploiting suitable abstractions of the configuration space for the resulting class of automata, we will devise efficient algorithms for reasoning on quasi-periodic time granularities (e.g., the partitioning of the temporal domain of days into years). Similar abstractions can be used when reasoning on infinite branching (temporal) structures. In such a case, one has to consider a generalized notion of automaton, which is able to process labeled branching structures (hereafter called trees), rather than linear sequences of symbols. We will show that sets of trees featuring the same properties can be identified with the equivalence classes induced by a suitable automaton. More precisely, given a property to be verified, one can first define a corresponding automaton that accepts all and only the trees satisfying that property, then introduce a suitable equivalence relation that refines the standard language equivalence and groups all trees being indistinguishable by the automaton, and, finally, exploit such an equivalence to reduce several instances of the verification problem to equivalent simpler instances, which can be eventually decided

Security-Policy Analysis with eXtended Unix Tools

During our fieldwork with real-world organizations---including those in Public Key Infrastructure (PKI), network configuration management, and the electrical power grid---we repeatedly noticed that security policies and related security artifacts are hard to manage. We observed three core limitations of security policy analysis that contribute to this difficulty. First, there is a gap between policy languages and the tools available to practitioners. Traditional Unix text-processing tools are useful, but practitioners cannot use these tools to operate on the high-level languages in which security policies are expressed and implemented. Second, practitioners cannot process policy at multiple levels of abstraction but they need this capability because many high-level languages encode hierarchical object models. Finally, practitioners need feedback to be able to measure how security policies and policy artifacts that implement those policies change over time. We designed and built our eXtended Unix tools (XUTools) to address these limitations of security policy analysis. First, our XUTools operate upon context-free languages so that they can operate upon the hierarchical object models of high-level policy languages. Second, our XUTools operate on parse trees so that practitioners can process and analyze texts at multiple levels of abstraction. Finally, our XUTools enable new computational experiments on multi-versioned structured texts and our tools allow practitioners to measure security policies and how they change over time. Just as programmers use high-level languages to program more efficiently, so can practitioners use these tools to analyze texts relative to a high-level language. Throughout the historical transmission of text, people have identified meaningful substrings of text and categorized them into groups such as sentences, pages, lines, function blocks, and books to name a few. Our research interprets these useful structures as different context-free languages by which we can analyze text. XUTools are already in demand by practitioners in a variety of domains and articles on our research have been featured in various news outlets that include ComputerWorld, CIO Magazine, Communications of the ACM, and Slashdot

Tension-driven Automatic Music Generation

The Ancient Greeks are one of the first civilisations we know of to have created algorithms to compose music. Since then, algorithmic techniques have vastly improved with increasingly sophisticated computers. In the last two decades, much research in this area has focused on two goals: designing algorithms which generate music as close as possible to that of human composers and implementing those algorithms to automatically generate music in interactive scenarios, such as video games. To meet these goals, automatically generated music should: - focus on higher-level concepts, such as musical tension, - have long-term structure, and - be able to adapt to changes in real time. Combining these three requirements is, however, a challenging task. This dissertation investigates three steps to overcome this challenge. First, we argue that Lerdahl’s model of musical tension is suited to the automatic generation of tonal music that has long-term structure and that matches a given tension profile. By means of an illustrative example, we review Lerdhal’s model and implement a novel computational system to automate it. Second, we show that an effective generation strategy is to combine statistical methods with both rule-based methods and generative grammars to create a music generation system. Third, we implement the system and evaluate it through a collection of computational tests and empirical studies. Our evaluation shows that: (1) the system works effectively in real time, as long as the input tension profiles do not contain too many steep transitions, (2) the hierarchical structure perceived by listeners matches the patterns intended by the system in the generated music, and (3) tension-changing input profiles are accurately matched by the generated music

Image and Evidence: The Study of Attention through the Combined Lenses of Neuroscience and Art

: Levy, EK 2012, ‘An artistic exploration of inattention blindness’, in Frontiers Hum Neurosci, vol. 5, ISSN=1662-5161.Full version unavailable due to 3rd party copyright restrictions.This study proposed that new insights about attention, including its phenomenon and pathology, would be provided by combining perspectives of the neurobiological discourse about attention with analyses of artworks that exploit the constraints of the attentional system. To advance the central argument that art offers a training ground for the attentional system, a wide range of contemporary art was analysed in light of specific tasks invoked. The kinds of cognitive tasks these works initiate with respect to the attentional system have been particularly critical to this research. Attention was explored within the context of transdisciplinary art practices, varied circumstances of viewing, new neuroscientific findings, and new approaches towards learning. Research for this dissertation required practical investigations in a gallery setting, and this original work was contextualised and correlated with pertinent neuroscientific approaches. It was also concluded that art can enhance public awareness of attention disorders and assist the public in discriminating between medical and social factors through questioning how norms of behaviour are defined and measured. This territory was examined through the comparative analysis of several diagnostic tests for attention deficit hyperactivity disorder (ADHD), through the adaptation of a methodology from economics involving patent citation in order to show market incentives, and through examples of data visualisation. The construction of an installation and collaborative animation allowed participants to experience first-hand the constraints on the attentional system, provoking awareness of our own “normal” physiological limitations. The embodied knowledge of images, emotion, and social context that are deeply embedded in art practices appeared to be capable of supplementing neuroscience’s understanding of attention and its disorders