Considerable Expressive Power Research Articles

Geological Hazard Susceptibility Assessment Based on RS and PSO-SVR Model

It is crucial to undertake thorough study and data mining on factors that determine the occurrence of geohazards to prevent and anticipate their occurrence. A small-sample learning method with a strong theoretical underpinning, the classical support vector machine model provides considerable expressive power in dealing with the interaction of nonlinear characteristics and lessens reliance on the entire data set. However, its excellent generalization capabilities result in an excessively large optimal search space, which impacts the search for kernel parameters and reduces the model’s accuracy. The particle swarm algorithm, which has a robust search capability, is thus introduced to improve it. This paper's research area is Chian Town, China. The prediction study of geological hazard susceptibility in Chian town was validated using Gaofen 2 remote sensing imagery in conjunction with a support vector machine regression model enhanced by the particle swarm algorithm. The findings show that the high-risk zone comprises 17% of the overall area and has an 88.88% prediction accuracy. The results imply that integrating high-resolution remote sensing imagery-based and optimized machine learning algorithm models has prospective applications in investigating geological hazard susceptibility with small samples, numerous feature factors, and large-scale data.

Fitting Tractable Convex Sets to Support Function Evaluations

The geometric problem of estimating an unknown compact convex set from evaluations of its support function arises in a range of scientific and engineering applications. Traditional approaches typically rely on estimators that minimize the error over all possible compact convex sets; in particular, these methods do not allow for the incorporation of prior structural information about the underlying set and the resulting estimates become increasingly more complicated to describe as the number of measurements available grows. We address both of these shortcomings by describing a framework for estimating tractably specified convex sets from support function evaluations. Building on the literature in convex optimization, our approach is based on estimators that minimize the error over structured families of convex sets that are specified as linear images of concisely described sets -- such as the simplex or the spectraplex -- in a higher-dimensional space that is not much larger than the ambient space. Convex sets parametrized in this manner are significant from a computational perspective as one can optimize linear functionals over such sets efficiently; they serve a different purpose in the inferential context of the present paper, namely, that of incorporating regularization in the reconstruction while still offering considerable expressive power. We provide a geometric characterization of the asymptotic behavior of our estimators, and our analysis relies on the property that certain sets which admit semialgebraic descriptions are Vapnik-Chervonenkis (VC) classes. Our numerical experiments highlight the utility of our framework over previous approaches in settings in which the measurements available are noisy or small in number as well as those in which the underlying set to be reconstructed is non-polyhedral.

Z3str2: an efficient solver for strings, regular expressions, and length constraints

In recent years, string solvers have become an essential component in many formal verification, security analysis, and bug-finding tools. Such solvers typically support a theory of string equations, the length function, and the regular-expression membership predicate. These enable considerable expressive power, which comes at the cost of slow solving time, and in some cases even non-termination. We present three techniques, designed for word-based SMT string solvers, to mitigate these problems: (1) detecting overlapping variables, which is essential to avoiding common cases of non-termination; (2) pruning of the search space via bi-directional integration between the string and integer theories, enabling new cross-domain heuristics; and (3) a binary search based heuristic, allowing the procedure to skip unnecessary string length queries and converge on consistent length assignments faster for large strings. We have implemented above techniques atop the Z3-str solver, resulting in a significantly more robust and efficient solver, dubbed Z3str2, for the quantifier-free theory of string equations, the regular-expression membership predicate, and linear arithmetic over the length function. We report on a series of experiments over four sets of challenging real-world benchmarks, where we compare Z3str2 with five different string solvers: S3, CVC4, Kaluza, PISA and Stranger. Each of these tools utilizes a different solving strategy and/or string representation (based e.g. on words, bit vectors or automata). The results point to the efficacy of our proposed techniques, which yield dramatic performance improvement. We also demonstrate performance improvements enabled by Z3str2 in the context of symbolic execution for string-manipulating programs. We observe that the techniques presented here are of broad applicability, and can be integrated into other string solvers to improve their performance.

A Proof System with Names for Modal Mu-calculus

Fixpoints are an important ingredient in semantics, abstract interpretation and program logics. Their addition to a logic can add considerable expressive power. One general issue is how to define proof systems for such logics. Here we examine proof systems for modal logic with fixpoints. We present a tableau proof system for checking validity of formulas which uses names to keep track of unfoldings of fixpoint variables as devised by Jungteerapanich.

A Family of Dynamic Description Logics for Representing and Reasoning About Actions

Description logics provide powerful languages for representing and reasoning about knowledge of static application domains. The main strength of description logics is that they offer considerable expressive power going far beyond propositional logic, while reasoning is still decidable. There is a demand to bring the power and character of description logics into the description and reasoning of dynamic application domains which are characterized by actions. In this paper, based on a combination of the propositional dynamic logic PDL, a family of description logics and an action formalism constructed over description logics, we propose a family of dynamic description logics DDL(X @) for representing and reasoning about actions, where X represents well-studied description logics ranging from the to the , and X @ denotes the extension of X with the @ constructor. The representation power of DDL(X @) is reflected in four aspects. Firstly, the static knowledge of application domains is represented as RBoxes and acyclic TBoxes of the description logic X. Secondly, the states of the world and the pre-conditions of atomic actions are described by ABox assertions of the description logic X @, and the post-conditions of atomic actions are described by primitive literals of X @. Thirdly, starting with atomic actions and ABox assertions of X @, complex actions are constructed with regular program constructors of PDL, so that various control structures on actions such as the "Sequence", "Choice", "Any-Order", "Iterate", "If-Then-Else", "Repeat-While" and "Repeat-Until" can be represented. Finally, both atomic actions and complex actions are used as modal operators for the construction of formulas, so that many properties on actions can be explicitly stated by formulas. A tableau-algorithm is provided for deciding the satisfiability of DDL(X @)-formulas; based on this algorithm, reasoning tasks such as the realizability, executability and projection of actions can be effectively carried out. As a result, DDL(X @) not only offers considerable expressive power going beyond many action formalisms which are propositional, but also provides decidable reasoning services for actions described by it.

Implementing logical connectives in constraint programming

Combining constraints using logical connectives such as disjunction is ubiquitous in constraint programming, because it adds considerable expressive power to a constraint language. We explore the solver architecture needed to propagate such combinations of constraints efficiently. In particular we describe two new features named satisfying sets and constraint trees. We also make use of movable triggers (Gent et al., 2006) [1], and with these three complementary features we are able to make considerable efficiency gains. A key reason for the success of Boolean Satisfiability (SAT) solvers is their ability to propagate Or constraints efficiently, making use of movable triggers. We successfully generalise this approach to an Or of an arbitrary set of constraints, maintaining the crucial property that at most two constraints are active at any time, and no computation at all is done on the others. We also give an And propagator within our framework, which may be embedded within the Or. Using this approach, we demonstrate speedups of over 10,000 times in some cases, compared to traditional constraint programming approaches. We also prove that the Or algorithm enforces generalised arc consistency (GAC) when all its child constraints have a GAC propagator, and no variables are shared between children. By extending the Or propagator, we present a propagator for AtLeastK, which expresses that at least k of its child constraints are satisfied in any solution. Some logical expressions (e.g. exclusive-or) cannot be compactly expressed using And, Or and AtLeastK. Therefore we investigate reification of constraints. We present a fast generic algorithm for reification using satisfying sets and movable triggers.

Towards applied theories based on computability logic

AbstractComputability logic (CL) is a recently launched program for redeveloping logic as a formal theory of computability, as opposed to the formal theory of truth that logic has more traditionally been. Formulas in it represent computational problems, “truth” means existence of an algorithmic solution, and proofs encode such solutions. Within the line of research devoted to finding axiomatizations for ever more expressive fragments of CL, the present paper introduces a new deductive system CL12 and proves its soundness and completeness with respect to the semantics of CL. Conservatively extending classical predicate calculus and offering considerable additional expressive and deductive power, CL12 presents a reasonable, computationally meaningful, constructive alternative to classical logic as a basis for applied theories. To obtain a model example of such theories, this paper rebuilds the traditional, classical-logicbased Peano arithmetic into a computability-logic-based counterpart. Among the purposes of the present contribution is to provide a starting point for what, as the author wishes to hope, might become a new line of research with a potential of interesting findings—an exploration of the presumably quite unusual metatheory of CL-based arithmetic and other CL-based applied systems.

Reasoning About Semantic Web Services with an Approach Based on Dynamic Description Logics

The semantic Web services vision is to enable effective automation of various Web service related activities,such as Web service discovery,composition and execution.An obvious concern about the semantic Web service is to combine in some way the static descriptions of the information provided by ontologies with the dynamic descriptions of Web services′ capabilities.Based on the dynamic description logic DDL(SHOIN(D)),this paper presents an approach to model and reason about semantic Web services.With this approach,the OWL-S ProcessModel of Web services will be firstly translated into an action theory which is based on the DDL(SHOIN(D)).This action theory allows for modeling atomic processes with their inputs,outputs,local variables,preconditions and results.It also offers considerable expressive power for modeling not only data flows of composite processes but also control flows such as the Sequence,Choice,Any-Order,If-Then-Else,Iterate,Repeat-While and Repeat-Until.Based on the action theory,the realizability,executability,projection and planning problems on semantic Web services can be reasoned about.These mechanisms provide effective supports for the discovery and composition of semantic Web services.

Logics of Kripke meta-models

This paper introduces and studies a new type of logical construction, which allows to combine various non-classical propositional logics with the temporal or modal background. The possible candidates include (but are not restricted to) a number of epistemic, multi-agent, deontological and other well-studied logics. In this construction, that we call refinement, the Kripke structure of a chosen Kripke complete logic is imposed on clusters of the background transitive frame. Refinements fit in a wider framework of fibred logics, while having some unique features. First of all, when applied to classes of frames of Kripke complete logics, refinement preserves good meta-logical properties of constituent logics, in contrast with the well-known products of logics. Another advantage of refinements is that they allow for augmented languages of considerable expressive power, while preserving good meta-logical and semantical properties. In particular we show that refinement of logics preserves the effective finite model property and decidability for a wide class of constituent logics.

OWL rules: A proposal and prototype implementation

Although the OWL Web Ontology Language adds considerable expressive power to the Semantic Web it does have expressive limitations, particularly with respect to what can be said about properties. We present the Semantic Web Rule Language (SWRL), a Horn clause rules extension to OWL that overcomes many of these limitations. SWRL extends OWL in a syntactically and semantically coherent manner: the basic syntax for SWRL rules is an extension of the abstract syntax for OWL DL and OWL Lite; SWRL rules are given formal meaning via an extension of the OWL DL model-theoretic semantics; SWRL rules are given an XML syntax based on the OWL XML presentation syntax; and a mapping from SWRL rules to RDF graphs is given based on the OWL RDF/XML exchange syntax. We discuss the expressive power of SWRL, showing that the ontology consistency problem is undecidable, provide several examples of SWRL usage, and discuss a prototype implementation of reasoning support for SWRL.

Owl Rules: A Proposal and Prototype Implementation

Although the OWL Web Ontology Language adds considerable expressive power to the Semantic Web it does have expressive limitations, particularly with respect to what can be said about properties. We present SWRL (the SemanticWeb Rules Language), a Horn clause rules extension to OWL that overcomes many of these limitations. SWRL extends OWL in a syntactically and semantically coherent manner: the basic syntax for SWRL rules is an extension of the abstract syntax for OWL DL and OWL Lite; SWRL rules are given formal meaning via an extension of the OWL DL model-theoretic semantics; SWRL rules are given an XML syntax based on the OWL XML presentation syntax; and a mapping from SWRL rules to RDF graphs is given based on the OWL RDF/XML exchange syntax. We discuss the expressive power of SWRL, showing that the ontology consistency problem is undecidable, provide several examples of SWRL usage, and discuss a prototype implementation of reasoning support for SWRL.

Paraconsistent Declarative Semantics for Extended Logic Programs

We introduce a fixpoint semantics for logic programs with two kinds of negation: an explicit negation and a negation-by-failure. The programs may also be prioritized, that is, their clauses may be arranged in a partial order that reflects preferences among the corresponding rules. This yields a robust framework for representing knowledge in logic programs with a considerable expressive power. The declarative semantics for such programs is particularly suitable for reasoning with uncertainty, in the sense that it pinpoints the incomplete and inconsistent parts of the data, and regards the remaining information as classically consistent. As such, this semantics allows to draw conclusions in a non-trivial way, even in cases that the logic programs under consideration are not consistent. Finally, we show that this formalism may be regarded as a simple and flexible process for belief revision.

The Logic of Propagation Strategies: Axiomatizing a Fragment of Organizational Ecology in First-Order Logic

As a part of a larger effort to apply formal logic to organization science, we axiomatize the theory of propagation strategies (life history strategies) of Organization Ecology. We provide an axiomatic system in first-order logic that derives the theory's predictions as theorems from a set of underlying assumptions. First-order logic is widely seen as a standard language for the formalization of scientific theories; it couples considerable expressive power with acceptable computational properties. Our axiomatization increases the understanding on the scope and the limits of Organization Ecology, and yields a consistent theory of propagation strategies with a sound explanatory structure.

A New Language Design for Prototyping Numerical Computation

To naturally and conveniently express numerical algorithms, considerable expressive power is needed in the languages in which they are implemented. The language Matlab is widely used by numerical analysts for this reason. Expressiveness or ease-of-use can also result in a loss of efficiency, as is the case with Matlab. In particular, because numerical analysts are highly interested in the performance of their algorithms, prototypes are still often implemented in languages such as Fortran. In this article we describe a language design that is intended to both provide expressiveness for numerical computation, and at the same time provide performance guarantees. In our language, EQ, we attempt to include both syntactic and semantic features that correspond closely to the programmer's model of the problem, including unordered equations, large-granularity state transitions, and matrix notation. The resulting language does not fit into standard language categories such as functional or imperative but has features of both paradigms. We also introduce the notion of language dependability, which is the idea that a language should guarantee that certain program transformations are performed by all implementations. We first describe the interesting features of EQ, and then present three examples of algorithms written using it. We also provide encouraging performance results from an initial implementation of our language.

Constraint hierarchies

Constraints describe relations that must be maintained, and provide a useful tool for such applications as interactive simulations, algorithm animation, and graphical user interface construction. We describe a major overhaul and extension to the constraint satisfaction mechanism in ThingLab, a constraint-oriented simulation laboratory written in the Smalltalk-80 language. First, a specification is presented of constraint hierarchies . Such hierarchies include both required constraints and default constraints of differing strengths, thus adding considerable expressive power to the system. Second, an algorithm for satisfying constraint hierarchies is described. The new satisfier is substantially faster than the previous version, even though it also includes new functionality.

A data type encapsulation scheme utilizing base language operators

A data type encapsulation scheme in which the “space” operations are expressed naturally in terms of the base language operators is described. The scheme results from a conceptual separation of operators and procedure calls in the base language and produces a language of considerable expressive power. The scheme has been implemented and several examples are given.

A data type encapsulation scheme utilizing base language operators

A data type encapsulation scheme in which the “space” operations are expressed naturally in terms of the base language operators is described. The scheme results from a conceptual separation of operators and procedure calls in the base language and produces a language of considerable expressive power. The scheme has been implemented and several examples are given.