Verifying data refinements using a model checker

In this paper, we consider how refinements between state-based specifications (e.g., written in Z) can be checked by use of a model checker. Specifically, we are interested in the verification of downward and upward simulations which are the standard approach to verifying refinements in state-based notations. We show how downward and upward simulations can be checked using existing temporal logic model checkers.In particular, we show how the branching time temporal logic CTL can be used to encode the standard simulation conditions. We do this for both a blocking, or guarded, interpretation of operations (often used when specifying reactive systems) as well as the more common non-blocking interpretation of operations used in many state-based specification languages (for modelling sequential systems). The approach is general enough to use with any state-based specification language, and we illustrate how refinements between Z specifications can be checked using the SAL CTL model checker using a small example.     

A novel keyword search paradigm in relational databases: Object summaries

This paper introduces a novel keyword search paradigm in relational databases, where the result of a search is an Object Summary (OS). An OS summarizes all data held about a particular Data Subject (DS) in a database. More precisely, it is a tree with a tuple containing the keyword(s) as a root and neighboring tuples as children. In contrast to traditional relational keyword search, an OS comprises a more complete and therefore semantically meaningful set of information about the enquired DS.The proposed paradigm introduces the concept of Affinity in order to automatically generate OSs. More precisely, it investigates and quantifies the Affinity of relations (i.e. Affinity) and their attributes (i.e. Attribute Affinity) in order to decide which tuples and attributes to include in the OS. Experimental evaluation on the TPC-H and Northwind databases verifies the searching quality of the proposed paradigm on both large and small databases; precision, recall, f-score, CPU and space measures are presented.     

A study of homogeneity in relational databases

We define four different properties of relational databases which are related tothe notion of homogeneity in classical model theory. The main question for their definition is, for any given database to determine the minimum integer k, such that whenever two k-tuples satisfy the same properties which are expressible in first order logic with up to k variables (FO ^k ), then there is an automorphism which maps each of these k-tuples onto each other. We study these four properties as a means to increase the computational power of subclasses of the reflective relational machines (RRMs) of bounded variable complexity. These were introduced by S. Abiteboul, C. Papadimitriou and V. Vianu and are known to be incomplete. For this sake we first give a semantic characterization of the subclasses of total RRM with variable complexity k (RRM ^k ) for every natural number k. This leads to the definition of classes of queries denoted as Q C Q ^k . We believe these classes to be of interest in their own right. For each k>0, we define the subclass Q C Q ^k as the total queries in the class C Q of computable queries which preserve realization of properties expressible in FO ^k . The nature of these classes is implicit in the work of S. Abiteboul, M. Vardi and V. Vianu. We prove Q C Q ^k =total(RRM ^k ) for every k>0. We also prove that these classes form a strict hierarchy within a strict subclass of total(C Q). This hierarchy is orthogonal to the usual classification of computable queries in time-space-complexity classes. We prove that the computability power of RRM ^k machines is much greater when working with classes of databases which are homogeneous, for three of the properties which we define. As to the fourth one, we prove that the computability power of RRM with sublinear variable complexity also increases when working on databases which satisfy that property. The strongest notion, pairwise k-homogeneity, allows RRM ^k machines to achieve completeness.     

Organizing the description of a relational data base

The design and implementation of the data structures used within a software system such as a compiler, an operating system or a data base management system are fundamental to the development of that system. Unfortunately, there are very few standard techniques for designing such data structures and for structuring the software used to support them. This paper proposes that it is possible to use data base techniques to design and implement such data structures. For this reason, it describes a methodology which is used to design large relational data bases, and then demonstrates how the methodology was modified and used to design the internal data structures of a relational data base management system. This paper concludes that this approach produces data structures which are better understood and easier to modify than those resulting from an ad-hoc approach.     

On the complexity of finding bounds for projection cardinalities in relational databases

We address the problem of deriving lower and upper bounds for the cardinality of the projections of a database relation, given a set of functional dependencies on the relation schema and measures of the cardinalities of the attributes in the schema. It is shown that deciding whether a given number is the least upper bound of a projection cardinality is an NP-complete problem, whereas determining whether the greatest lower bound and the least upper bound coincide can be easily solved in linear time.     

Effects of self-disclosure on relational intimacy in Facebook

The present study examined the association between self-disclosure and intimacy in the context of Facebook. As the antecedents of self-disclosure, the study included the need for affiliation and the motivations for relationship maintenance and initiation. Using data from an online survey (N = 249), structural equation modeling analyses revealed that self-disclosure amount and positivity were positively associated with intimacy, while self-disclosure honesty and intent were not associated with intimacy. The study also found no direct association between the need for affiliation and self-disclosure. Rather, the need for affiliation was associated with the motivations for relationship maintenance and initiation, which in turn affected self-disclosure and intimacy. The theoretical implications of the study were discussed.     

Fuzzy XML data modeling with the UML and relational data models

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data modeling has been extensively investigated in various data models. Currently, huge amounts of electronic data are available on the Internet, and XML has been the de facto standard of information representation and exchange over the Web. This paper focuses on fuzzy XML data modeling, which is mainly involved in the representation model of the fuzzy XML, its conceptual design, and its storage in databases. Based on “possibility distribution theory”, we developed this fuzzy XML data model. We developed this fuzzy UML data model to design the fuzzy XML model conceptually. We investigated the formal conversions from the fuzzy UML model to the fuzzy XML model and the formal mapping from the fuzzy XML model to the fuzzy relational databases.     

Supercomputer simulations of structure formation in the Universe

Gravitational N-body simulations are an indispensable tool for theoretical studies on cosmic structure formation. I present results from recent cosmological simulations of the formation of large-scale structure of the universe. I discuss the role of N-body simulations in making forecasts for ongoing and future large observational programs. I also present a state-of-the-art simulation of star formation in the early universe.     

An analysis of relational complexity in an air traffic control conflict detection task

Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.     

Numerical simulations of laser wakefield accelerators in optimal Lorentz frames

The simulation of laser wakefield accelerators with particle-in-cell codes in relativistic reference frames is described, with emphasis on the computational speed-ups, which may potentially exceed three orders of magnitude in comparison with laboratory frame configurations. The initialization of laboratory quantities in a relativistically moving frame is depicted, and the method for result comparison with the plasma rest frame is described. Benchmarks with laboratory frame simulations and experimental data where gains of ∼20 times were obtained are discussed, and potential numerical issues are analyzed. This method enables numerical simulations with shorter turnaround times required for parameter scanning, and for one-to-one three-dimensional experimental modeling of current and next generation laser wakefield experiments.     

Reconsidering simulations in science education at a distance: features of effective use

Abstract  This paper proposes a reconsideration of use of computer simulations in science education. We discuss three studies of the use of science simulations for undergraduate distance learning students. The first one, The Driven Pendulum simulation is a computer-based experiment on the behaviour of a pendulum. The second simulation, Evolve is concerned with natural selection in a hypothetical species of a flowering plant. The third simulation, The Double Slit Experiment deals with electron diffraction and students are provided with an experimental setup to investigate electron diffraction for double and single slit arrangements. We evaluated each simulation, with 30 students each for The Driven Pendulum and Evolve simulations and about 100 students for The Double Slit Experiment . From these evaluations we have developed a set of the features for the effective use of simulations in distance learning. The features include student support, multiple representations and tailorability.     

Robust heuristic algorithms for exploiting the common tasks of relational cloud database queries

Cloud computing enables a conventional relational database system's hardware to be adjusted dynamically according to query workload, performance and deadline constraints. One can rent a large amount of resources for a short duration in order to run complex queries efficiently on large-scale data with virtual machine clusters. Complex queries usually contain common subexpressions, either in a single query or among multiple queries that are submitted as a batch. The common subexpressions scan the same relations, compute the same tasks (join, sort, etc.), and/or ship the same data among virtual computers. The total time spent for the queries can be reduced by executing these common tasks only once. In this study, we build and use efficient sets of query execution plans to reduce the total execution time. This is an NP-Hard problem therefore, a set of robust heuristic algorithms, Branch-and-Bound, Genetic, Hill Climbing, and Hybrid Genetic-Hill Climbing, are proposed to find (near-) optimal query execution plans and maximize the benefits. The optimization time of each algorithm for identifying the query execution plans and the quality of these plans are analyzed by extensive experiments.     

Learning to assign degrees of belief in relational domains

A recurrent problem in the development of reasoning agents is how to assign degrees of beliefs to uncertain events in a complex environment. The standard knowledge representation framework imposes a sharp separation between learning and reasoning; the agent starts by acquiring a “model” of its environment, represented into an expressive language, and then uses this model to quantify the likelihood of various queries. Yet, even for simple queries, the problem of evaluating probabilities from a general purpose representation is computationally prohibitive. In contrast, this study embarks on the learning to reason (L2R) framework that aims at eliciting degrees of belief in an inductive manner. The agent is viewed as an anytime reasoner that iteratively improves its performance in light of the knowledge induced from its mistakes. Indeed, by coupling exponentiated gradient strategies in learning and weighted model counting techniques in reasoning, the L2R framework is shown to provide efficient solutions to relational probabilistic reasoning problems that are provably intractable in the classical paradigm.     

双螺杆挤出机流场数值模拟中流道进出口边界条件的探讨

在对双螺杆挤出机流场的数值模拟中,流道进出口边界条件的设置一直是一个颇具争议的问题。由于事先无法获得计算域进出口平面上的真实边界条件,研究人员在进行双螺杆挤出机的流场分析时,大都采用放松边界条件。为了考察放松边界条件对双螺杆挤出机流场数值模拟结果的影响,本文采用聚合物流动分析软件POLYFLOW,在流量恒定的前提下对双螺杆挤出机流道进出口给定三种不同分布形式的速度边界条件,对其流场进行了数值模拟。数值计算结果表明,在体积流量恒定的条件下,流道进出口不同分布形式的速度边界条件对流场的影响主要集中在进出口附近区域,但对离进出口边界较远的流场影响很小。一般而言,当计算域所对应的螺杆较长时,可以忽略流道进出口的放松边界条件所引起的误差;当计算域较短时,不宜直接采用放松边界条件,而应根据螺杆的实际构型．在计算域的进出口增加适当长度的发展段。     

Monte Carlo simulations of the site-diluted three-dimensional XY model

We present extensive Monte Carlo simulations of the classical XY model in three dimensions on a simple cubic lattice with periodic boundary conditions subject to quenched, random site dilution. By using a hybrid algorithm and finite-size scaling techniques we estimate the transition temperatures and the critical exponents associated with the diluted system. Our results for the critical exponents and universal cumulants are, within statistical errors, the same as for the zero dilution case and are independent of the amount of dilution, in agreement with the Harris criterion. The initial reduction of the critical temperature with dilution is also evaluated and compared to recent experimental results.     

Monte Carlo simulations of a single polystyrene chain in spherical confinement

We report on Monte Carlo simulations of a single coarse-grained polystyrene chain in spherical confinement. To this end we employ a variant of the freely rotating chain model, the parameters of which are chosen to mimic polystyrene in good solvent conditions. Entanglements are analyzed as a function of molecular weight and capsid radius to provide an educated guess about the structure of a single polystyrene chain in a miniemulsion droplet. We also show that significant knotting occurs first when the radius of the confining sphere falls below the chain?s radius of gyration.     

Direct numerical simulations of localized disturbances in pipe Poiseuille flow

We consider pipe Poiseuille flow subjected to a disturbance which is highly localized in space. Experiments by Peixinho and Mullin have shown this disturbance to be efficient in triggering turbulence, yielding a threshold dependence on the required amplitude as R^-1.5 on the Reynolds number, R. The experiments also indicate an initial formation of hairpin vortices, with each hairpin having a length of approximately one pipe radius, independent of the Reynolds number in the range of R=2000-3000. We perform direct numerical simulations for R=5000. The results show a packet of hairpin vortices traveling downstream, each having a length of approximately one pipe radius. The perturbation remains highly localized in space while being advected downstream for approximately 10 pipe diameters. Beyond that distance from the disturbance origin, the flow becomes severely disordered.