HUX: handling updates in XML
We demonstrate HUX (Handling Updates in XML) which provides a reliable and efficient solution for the XML view update problem. Given an update over an XML view, our U-Filter subsytem first determines whether the update is translatable or not by examining potential conflicts in both schema and data. If an update is determined to be translatable, our U-Translator subsystem searches potential translations and finds a "good" one. Our demonstration illustrates the working, as well as the performance, of the two sub-systems within HUX for different application scenarios.

title: Updating Views Over Recursive XML
abstract: We study the problem of updating XML views defined over XML documents. A view update is performed by finding the base updates over the underlying data sources that achieve the desired view update. If such base updates do not exist, the view update is said to be untranslatable and rejected. In SQL, determining whether a view update is translatable is performed using schema level analysis, where the view definition and the base schema are used. XML schemas are more complex than SQL schemas, and can specify recursive types and cardinality constraints. In this paper, we propose a solution based on schema level analysis for determining whether an update over XML views is translatable and for finding the translation if one exists, while considering the features of XML schemas.

title: An Optimized Two-Step Solution for Updating XML Views
abstract: View updating is a long standing difficult problem. Given a view defined over base data sources and a view update, there are several different updates over the base data sources, called translations, that perform the update. A translation is said to be correct if it performs the update and at the same time does not update any portion of the view not specified in the update (no view side-effects). The view update problem finds a correct translation for a given view update if one exists. In the relational scenario, previous research has attempted to study the view update problem either by utilizing only the schema knowledge, or by directly examining the base data. While utilizing only the schema knowledge is very efficient, we are not guaranteed to find a correct translation even if one exists. On the other hand, examining the base data is guaranteed to find a correct translation if one exists, but is very time-consuming. The view update problem is even more complex in the XML context due to the nested hierarchical structure of XML and the restructuring capabilities of the XQUERY view specification. In this paper we propose a schema-centric framework, named HUX, for efficiently updating XML views specified over relational databases. HUX is complete (always finds a correct translation if one exists) and is efficient. The efficiency of HUX is achieved as follows. Given a view update, HUX first exploits the schema to determine whether there will never be a correct translation, or there will always be a correct translation. Only if the update cannot be classified using the schema, HUX will examine the base data to determine if there is a correct translation. This data-level checking is further optimized in HUX, by exploiting the schema knowledge extracted in the first step to significantly prune the space of potential translations that is explored. Experiments illustrate the performance benefits of HUX over previous solutions.

title: Nonlinear behavior of the parameterized Logistic differential systems
abstract: This paper deals with local stability, Hopf bifurcation and chaos in the parameterized Logistic differential systems with delay. By applying the Halanay inequality, the local stability of the Logistic differential systems is discussed. The stability of bifurcation periodic solutions and the direction of Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. In the end, interesting nonlinear behavior of the parameterized Logistic differential systems with a single parameter delay is detected by numerical examples.

title: Feature Mining Paradigms for Scientific Data
abstract: Numerical simulation is replacing experimentation as a means to gain insight into complex physical phenomena. Analyzing the data produced by such simulations is extremely challenging, given the enormous sizes of the datasets involved. In order to make efficient progress, analyzing such data must advance from current techniques that only visualize static images of the data, to novel techniques that can mine, track, and visualize the important features in the data. In this paper, we present our research on a unified framework that addresses this critical challenge in two science domains: computational fluid dynamics and molecular dynamics. We offer a systematic approach to detect the significant features in both domains, characterize and track them, and formulate hypotheses with regard to their complex evolution. Our framework includes two paradigms for feature mining, and the choice of one over the other, for a given application, can be determined based on local or global influence of relevant features in the data.

title: A Surface Reconstruction Method for Highly Noisy Point Clouds
abstract: In this paper we propose a surface reconstruction method for highly noisy and non-uniform data based on minimal surface model and tensor voting method. To deal with ill-posedness, noise and/or other uncertainties in the data we processes the raw data first using tensor voting before we do surface reconstruction. The tensor voting procedure allows more global and robust communications among the data to extract coherent geometric features and saliency independent of the surface reconstruction. These extracted information will be used to preprocess the data and to guide the final surface reconstruction. Numerically the level set method is used for surface reconstruction. Our method can handle complicated topology as well as highly noisy and/or non-uniform data set. Moreover, improvements of efficiency in implementing the tensor voting method are also proposed. We demonstrate the ability of our method using synthetic and real data.

title: Properties of Periodic Solutions for Common Logistic Model with Discrete and Distributed Delay
abstract: This paper discusses about the existence and uniqueness of periodic solutions of Logistic model with discrete and distributed delay By using a Lyapunov function which unlike the former method, the conditions of existence and uniqueness of periodic solutions for this Logistic model are obtained The result of this paper extend results of periodic solutions for the delay differential equations.

title: Stochastic Lotka-Volterra Competitive Systems with Variable Delay
abstract: In this paper we reveal that the environmental noise will not only suppress a potential population explosion in the stochastic Lotka-Volterra competitive systems with variable delay, but also make the solutions to be stochastically ultimately bounded. To reveal these interesting facts, we stochastically perturb the Lotka-Volterra competitive systems with variable delay ẋ(t)=diag(x1(t),...,xn(t))[b+Ax(t−δ(t))] into the Ito form dx(t)=diag(x1(t),...,xn(t))[b+Ax(t−δ(t))]dt+σx(t)dw(t) and show that although the solution to the original delay systems may explode to infinity in a finite time, with probability one that of the associated stochastic delay systems do not. We also show that the stochastic systems will be stochastically ultimately bounded without any additional conditions on the matrix A.