What is a grammar?

Starting from a continuation-based interpreter for a simple logic programming language, propositional Prolog with cut, we derive the corresponding logic engine in the form of an abstract machine. The derivation originates in previous work (our article at PPDP 2003) where it was applied to the lambda-calculus. The key transformation here is Reynolds's defunctionalization that transforms a tail-recursive, continuation-passing interpreter into a transition system, i.e., an abstract machine. Similar denotational and operational semantics were studied by de Bruin and de Vink (their article at TAPSOFT 1989), and we compare their study with our derivation. Additionally, we present a direct-style interpreter of propositional Prolog expressed with control operators for delimited continuations.

. It is usually believed that adding computer parallelism makes algorithms faster, but does not change their feasibility. The usual proof of this claim is based on the assumption that our space is Euclidean. But according to modern physics, the actual space-time geometry is non-Euclidean. We show that for several physically meaningful non-Euclidean spaces (including Lobachevsky space) adding parallelism does enlarge the class of feasible algorithms, to the point that every problem becomes (in principle) solvable by a feasible algorithm. In general, whether or not adding parallelism changes feasibility, depends on a simple geombinatoric property of space: namely, on the number of (non-intersecting) spheres of radius r 0 ! R that can be placed inside a sphere of radius R. 1. WHAT IS A FEASIBLE ALGORITHM? In theory of computation, it is well known that not all algorithms are feasible (see, e.g., (Garey et al 1979), (Lewis et al 1981), (Martin 1991)): it depends on how many computationa...

This thesis focuses on the automatic acquisition of language structure and the subsequent use of the learned language structure to improve the performance of a speech recognition system. First, we develop a grammar inference process which is able to learn a grammar describing a large set of training sentences. The process of acquiring this grammar is one of generalization so that the resulting grammar predicts likely sentences beyond those contained in the training set. From the grammar we construct a novel probabilistic language model called the phrase class n-gram model (pcng), which is a natural generalization of the word class n-gram model [11] to phrase classes. This model utilizes the grammar in such a way that it maintains full coverage of any test set while at the same time reducing the complexity, or number of parameters, of the resulting predictive model. Positive results are shown in terms of perplexity of the acquired phrase class n-gram models and in terms of reduction of ...

Access control has been an important issue in military systems for many years and is becoming in-creasingly important in commercial systems. There are three important access control paradigms: the Bell-LaPadula model, the protection matrix model and the role-based access control model. Each of these models has its advantages and disadvantages. Partial orders play a significant part in the role-based access control model and are also important in defining the security lattice in the Bell-LaPadula model. The main goal of this thesis is to improve the understanding and specification of access control models through a rigorous mathematical approach. We examine the mathematical foundations of the role-based access control model and conclude that antichains are a fundamental concept in the model. The analytical approach we adopt enables us to identify where improvements in the administration of role-based access control could be made. We then develop a new administrative model for role-based access control based on a novel, mathematical interpretation of encapsulated ranges. We show that this model supports discretionary access control features which have hitherto been difficult to incorporate into role-based access control frameworks.

The natural language learning problem has attracted the attention of researchers for several decades. Computational and formal models of language acquisition have provided some preliminary, yet promising insights of how children learn the language of their community. Further, these formal models also provide an operational framework for the numerous practical applications of language learning. We will survey some of the key results in formal language learning. In particular, we will discuss the prominent computational approaches for learning different classes of formal languages and discuss how these fit in the broad context of natural language learning.

Born about three decades ago, Kolmogorov Complexity Theory (KC) led to important discoveries that, in particular, give a new understanding of the fundamental problem: interrelations between classical continuum mathematics and reality (physics, biology, engineering sciences, . . . ).

A repository of router configuration files from production networks would provide the research community with a treasure trove of data about network topologies, routing designs, and security policies. However, configuration files have been largely unobtainable precisely because they provide detailed information that could be exploited by competitors and attackers. This paper describes a method for anonymizing router configuration files by removing all information that connects the data to the identity of the originating network, while still preserving the structure of information that makes the data valuable to networking researchers. Anonymizing configuration files has unusual requirements, including preserving relationships between elements of data, anonymizing regular expressions, and robustly coping with more than 200 versions of the configuration language. Conventional tools and techniques are poorly suited to the problem. Our anonymization method has been validated with a major carrier, earning unprivileged researchers access to the configuration files of thousands of routers in hundreds of networks. Through example analysis, we demonstrate that the anonymized data retains the key properties of the network design. The paper sets out techniques that could be used in an attempt to break the anonymization and concludes the method is most applicable to enterprise networks. When applied to backbone networks, which are few in number and many of whose properties can be publicly measured, the anonymization might be broken by fingerprinting techniques described in this paper.

When we only know the interval of possible values of a certain quantity (or a more general set of possible values), it is desirable to characterize this interval by supplying the user with the "simplest" element from this interval, and by characterizing how different from this value we can get. For example, if, for some unknown physical quantity x, measurements result in the interval [1:95; 2:1] of possible values, then, most probably, the physicist will publish this result as y 2. Similarly, a natural representation of the measurement result x 2 [3:141592; 3:141593] is x . In this paper, we show that the problem of choosing the simplest element from a given interval (or from a given set) is, in general, not algorithmically solvable. 1 1 In Case of Interval (or More General Set) Uncertainty, a User Would Like to Have a Representative Value from This Interval (Set) The value of a physical quantity y is usually obtained either by a direct measurement, or by an indirect mea...

This paper presents a novel method for early detection of fatigue crack anomaly in complex mechanical structures, which is built upon the concepts of Symbolic Dynamics and Finite State Machines. The experimental apparatus, on which the crack detection method is tested, is a multi-degree of freedom massbeam structure excited by oscillatory motion of two vibrators. The evolution of fatigue crack at one or more of the three failure sites causes slow variations in the natural frequencies of the mechanical structure, which are detected at an early stage from the time series data of displacement sensor signals. The proposed anomaly detection method has been validated by comparison with existing pattern recognition techniques. 1