Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

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Convex Analysisの二,三の進展について

Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing data integration systems is important in current real world applications, and is characterized by a number of issues that are interesting from a theoretical point of view. This document presents on overview of the material to be presented in a tutorial on data integration. The tutorial is focused on some of the theoretical issues that are relevant for data integration. Special attention will be devoted to the following aspects: modeling a data integration application, processing queries in data integration, dealing with inconsistent data sources, and reasoning on queries.

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Data integration: a theoretical perspective

Optimization, approximation, and complexity classes

We propose a new framework for combining entity resolution and query answering in knowledge bases (KBs) with tuple-generating dependencies (tgds) and equality-generating dependencies (egds) as rules. We define the semantics of the KB in terms of special instances that involve equivalence classes of entities and sets of values. Intuitively, the former collect all entities denoting the same real-world object, while the latter collect all alternative values for an attribute. This approach allows us to both resolve entities and bypass possible inconsistencies in the data. We then design a chase procedure that is tailored to this new framework and has the feature that it never fails; moreover, when the chase procedure terminates, it produces a universal solution, which in turn can be used to obtain the certain answers to conjunctive queries. We finally discuss challenges arising when the chase does not terminate.

A Framework for Combining Entity Resolution and Query Answering in Knowledge Bases

In several different applications, including data transformation and entity resolution, rules are used to capture aspects of knowledge about the application at hand. Often, a large set of such rules is generated automatically or semi-automatically, and the challenge is to refine the encapsulated knowledge by selecting a subset of rules based on the expected operational behavior of the rules on available data. In this paper, we carry out a systematic complexity-theoretic investigation of the following rule selection problem: given a set of rules specified by Horn formulas, and a pair of an input database and an output database, find a subset of the rules that minimizes the total error, that is, the number of false positive and false negative errors arising from the selected rules. We first establish computational hardness results for the decision problems underlying this minimization problem, as well as upper and lower bounds for its approximability. We then investigate a bi-objective optimization version of the rule selection problem in which both the total error and the size of the selected rules are taken into account. We show that testing for membership in the Pareto front of this bi-objective optimization problem is DP-complete. Finally, we show that a similar DP-completeness result holds for a bi-level optimization version of the rule selection problem, where one minimizes first the total error and then the size.

/pdf/knowledge-refinement-via-rule-selection-3ol3fcgj9e.pdf

Knowledge Refinement via Rule Selection

Since the early days of relational databases, it was realized that acyclic hypergraphs give rise to database schemas with desirable structural and algorithmic properties. In a by-now classical paper, Beeri, Fagin, Maier, and Yannakakis established several different equivalent characterizations of acyclicity; in particular, they showed that the sets of attributes of a schema form an acyclic hypergraph if and only if the local-to-global consistency property for relations over that schema holds, which means that every collection of pairwise consistent relations over the schema is globally consistent. Even though real-life databases consist of bags (multisets), there has not been a study of the interplay between local consistency and global consistency for bags. We embark on such a study here and we first show that the sets of attributes of a schema form an acyclic hypergraph if and only if the local-to global consistency property for bags over that schema holds. After this, we explore algorithmic aspects of global consistency for bags by analyzing the computational complexity of the global consistency problem for bags: given a collection of bags, are these bags globally consistent? We show that this problem is in NP, even when the schema is part of the input. We then establish the following dichotomy theorem for fixed schemas: if the schema is acyclic, then the global consistency problem for bags is solvable in polynomial time, while if the schema is cyclic, then the global consistency problem for bags is NP-complete. The latter result contrasts sharply with the state of affairs for relations, where, for each fixed schema, the global consistency problem for relations is solvable in polynomial time.

Structure and Complexity of Bag Consistency.

The probability of a property on the collection of all finite relational structures is the limit as n + ‘x) of the fraction of structures with n elements sat,isfying the property, provided the limit exists. It is known that a 0-1 law holds for any property expressible in first-order logic, i.e. the probability of any such property exists and is either 0 or 1. Moreover, the associated decision problem for the probabilities is PSPACEcomplete. We investigate here fragments of existential second-order logic in which we restrict the patterns of first-order quantifiers. We focus on the class C:(Ackermann) of existential second-order sentences in which the first-order part belongs to the Ackermann class, i.e., it contains at most one universal first-order quantifier. All properties expressible by Ci (Ackermann) sentences are NPcomputable and there are natural NP-complete properties, such as SATISFIABILITY, that are expressible by such sentences. We establish that t,he 0-1 law holds for the class Ci(Ackermann) and show that the associated decision problem is NEXPTIMGcomplete. We also show that the 0-1 law fails for other fragments of existential second-order logic in which the first-order part belongs to certain prefix classes with an unsolvable decision problem.

0-1 Laws and Decision Probleiiis for Fragments Second-Order Logic

AC-matching is the problem of deciding whether an equation involving a binary associative-commutative function symbol, formal variables and formal constants has a solution. This problem is known to be strong NP-complete and to play a fundamental role in equational unification and automated deduction. We initiate an investigation of the existence of a phase transition in random AC-matching and its relationship to the performance of AC-matching solvers.We identify a parameter that captures the "constrainedness" of AC-matching, carry out largescale experiments, and then apply finite-size scaling methods to draw conclusions from the experimental data gathered. Our findings suggest that there is a critical value of the parameter at which the asymptotic probability of solvability of random AC-matching changes from 1 to 0. Unlike other NP-complete problems, however, the phase transition in random AC-matching seems to emerge very slowly, as evidenced by the experimental data and also by the rather small value of the scaling exponent in the power law of the derived finite-size scaling transformation.

Phokion G. Kolaitis

Papers

A Framework for Combining Entity Resolution and Query Answering in Knowledge Bases

Knowledge Refinement via Rule Selection

Structure and Complexity of Bag Consistency.

0-1 Laws and Decision Probleiiis for Fragments Second-Order Logic

In Search of a Phase Transition in the AC-Matching Problem