Volume 2 Issue 4
Authors: Leping Zou; Yangjun Chen
Abstract: With the growing importance of XML in data exchange, much research has been done in providing flexible query mechanisms to extract data from XML documents. In this paper, we focus on the query evaluation in an XML streaming environment, in which data streams arrive continuously and queries have to be evaluated even before all the data of an XML document are available. Two algorithms will be discussed. One is for the unordered tree matching, by which only ancestor-descendant and parent-child relationships are considered. It requires O(|T’|·leafQ) time, where T’ is a subtree of document tree T, in which each node matches at least one node in query Q and leafQ is the number of leaf nodes in Q. The other is for the ordered tree matching, by which the left-to-right order of nodes must also be taken into account. It runs in O(|T’|·|Q|) time. Furthermore, our algorithms achieve high time performance without trading off space requirements. They have the same caching space and buffering space overhead as state-of-the-art stream-querying algorithm. We show the efficiency and effectiveness of our algorithms by a lot of experiments.
Keywords: XML Documents; Trees; Paths; XML Streams; XML Pattern Matching
Authors: Rabees Rustum; Adebayo Adeloye
Abstract: This paper presents the results of modelling to predict the effluent biological oxygen demand (BOD5) concentration for primary clarifiers using a hybridisation of unsupervised and supervised artificial neural networks. The hybrid model is based on the unsupervised self-organising map (SOM) whose features were then used to train a multi-layered perceptron, feedforward back propagation artificial neural networks (MLP-ANN). In parallel with this, another MLP-ANN was trained but using the raw data. A comparison of the outputs from the two MLP-ANNs showed that the hybrid approach was far superior to the raw data approach. The study clearly demonstrates the usefulness of the clustering power of the SOM in helping to reduce noise in observed data to achieve better modelling and prediction of environmental systems behaviour.
Keywords: Wastewater Treatment Plant; Primary Clarifier Modelling; Neural Networks; Kohonen Self-Organising Map
Authors: Krassimira Ivanova; Iliya Mitov; Peter Stanchev; Evgeniya Velikova
Abstract: An approach for extracting higher-level visual features for art painting classification based on MPEG-7 descriptors was implemented in the system “Art Painting Image Colour Aesthetics and Semantics” (APICAS). The approach consists of the following steps: (1) tiling images into non-overlapping rectangles in order to capture more detailed local information; (2) the tiles of the images are clustered for each MPEG 7 descriptor; (3) vector quantization is used to assign a unique value to each tile, which corresponds to the number of the cluster where the tile belongs, in order to reduce the dimensionality of the data. The distribution of significance of the attributes, the importance of the underlying MPEG 7 descriptors as well as analysis of spatial granularity for class prediction in this domain are analyzed.
Keywords: Content-Based Image Retrieval (CBIR); Multimedia Semantics; MPEG 7 Descriptors; Vector Quantization; Categorization
Authors: Jean Daniel Zucker; Yann Chevaleyre; NguyenThi Ngoc Anh
Abstract: In recent years, the number of people affected by natural disasters and in particular tsunamis has been increasing. Artificial Intelligence and Operation Research approaches to simulate crowd evacuation and prepare cities for Tsunamis are of critical interest. Given an extremely simple model of human behavior, i.e. a memory-less stochastic agent, we address the problem of optimizing the placement of Tsunami evacuation signs with respect to evacuation time and casualties. Moreover, we formalise this optimisation problem as a Mixed Integer Linear Programming (MILP) problem and we ran some experiments with a MILP solver to give an early warning for the evacuation of the road network of Nhatrang city in Vietnam.
Keywords: Agent Based Model;Optimization Sign Placement;Mixed Integer Linear Programming;Simulation
Authors: geetha venkat; N. Sreenath
Abstract: Deadlocks affect the performance of all systems that support concurrent execution of transactions. Presence of deadlocks is usually detected by checking for cycles in Wait-For graph. Once deadlocks are detected, the cycle can be broken by aborting one of the transactions (Victim). Main objective of victim selection is avoiding starvation. This paper analyses the performance of various victim selection algorithms given in the literature to find out how optimal they are with respect to other desirable parameters of a system like throughput, fairness, resource utilization and resolution latency apart from starvation. This paper also proposes weight based resolution algorithm to dynamically select least cost victim.
Keywords: Distributed System; Resolution; Transaction Attributes; Resource Characteristics, Victim Selection