Desirable properties for XML update mechanisms

The adoption of XML as the default data interchange format and the standardisation of the XPath and XQuery languages has resulted in significant research in the development and implementation of XML databases capable of processing queries efficiently. The ever-increasing deployment of XML in industry and the real-world requirement to support efficient updates to XML documents has more recently prompted research in dynamic XML labelling schemes. In this paper, we provide an overview of the recent research in dynamic XML labelling schemes. Our motivation is to define a set of properties that represent a more holistic dynamic labelling scheme and present our findings through an evaluation matrix for most of the existing schemes that provide update functionality

Query management in a sensor environment

Traditional sensor network deployments consisted of fixed infrastructures and were relatively small in size. More and more, we see the deployment of ad-hoc sensor networks with heterogeneous devices on a larger scale, posing new challenges for device management and query processing. In this paper, we present our design and prototype implementation of XSense, an architecture supporting metadata and query services for an underlying large scale dynamic P2P sensor network. We cluster sensor devices into manageable groupings to optimise the query process and automatically locate appropriate clusters based on keyword abstraction from queries. We present experimental analysis to show the benefits of our approach and demonstrate improved query performance and scalability

Querying XML data streams from wireless sensor networks: an evaluation of query engines

As the deployment of wireless sensor networks increase and their application domain widens, the opportunity for effective use of XML filtering and streaming query engines is ever more present. XML filtering engines aim to provide efficient real-time querying of streaming XML encoded data. This paper provides a detailed analysis of several such engines, focusing on the technology involved, their capabilities, their support for XPath and their performance. Our experimental evaluation identifies which filtering engine is best suited to process a given query based on its properties. Such metrics are important in establishing the best approach to filtering XML streams on-the-fly

An extended preorder index for optimising XPath expressions

Many of the problems with native XML databases relate to query performance and subsequently, it can be difficult to convince traditional database users of the benefits of using semi- or unstructured databases. Presently, there still lacks an index structure providing efficient support for structural queries and the traditional data-centric and content queries. This paper presents an extended index structure based on the preorder traversal rank and the level (or depth) rank of each node in a document tree. The extended index fully supports the navigation of all XPath axes while efficiently supporting data-centric queries. The ability to start path traversals from arbitrary nodes in a document tree also enables the extended index to support the evaluation of path traversals embedded in XQuery expressions. Furthermore, an encoding technique is presented where properties of the level ranking may be exploited to provide efficient and optimised level-based XPath evaluations

Data cube computational model with Hadoop MapReduce

XML has become a widely used and well structured data format for digital document handling and message transmission. To find useful knowledge in XML data, data warehouse and OLAP applications aimed at providing supports for decision making should be developed. Apache Hadoop is an open source cloud computing framework that provides a distributed file system for large scale data processing. In this paper, we discuss an XML data cube model which offers us the complete views to observe XML data, and present a basic algorithm to implement its building process on Hadoop. To improve the efficiency, an optimized algorithm more suitable for this kind of XML data is also proposed. The experimental results given in the paper prove the effectiveness of our optimization strategies

Rethinking the bile acid/gut microbiome axis in cancer

Dietary factors, probiotic agents, aging and antibiotics/medicines impact on gut microbiome composition leading to disturbances in localised microbial populations. The impact can be profound and underlies a plethora of human disorders, including the focus of this review; cancer. Compromised microbiome populations can alter bile acid signalling and produce distinct pathophysiological bile acid profiles. These in turn have been associated with cancer development and progression. Exposure to high levels of bile acids, combined with localised molecular/genome instability leads to the acquisition of bile mediated neoplastic alterations, generating apoptotic resistant proliferation phenotypes. However, in recent years, several studies have emerged advocating the therapeutic benefits of bile acid signalling in suppressing molecular and phenotypic hallmarks of cancer progression. These studies suggest that in some instances, bile acids may reduce cancer phenotypic effects, thereby limiting metastatic potential. In this review, we contextualise the current state of the art to propose that the bile acid/gut microbiome axis can influence cancer progression to the extent that classical in vitro cancer hallmarks of malignancy (cell invasion, cell migration, clonogenicity, and cell adhesion) are significantly reduced. We readily acknowledge the existence of a bile acid/gut microbiome axis in cancer initiation, however, in light of recent advances, we focus exclusively on the role of bile acids as potentially beneficial molecules in suppressing cancer progression. Finally, we theorise that suppressing aggressive malignant phenotypes through bile acid/gut microbiome axis modulation could uncover new and innovative disease management strategies for managing cancers in vulnerable cohort

Data transformation and query management in personal health sensor networks

Sensor technology has been exploited in many application areas ranging from climate monitoring, to traffic management, and healthcare. The role of these sensors is to monitor human beings, the environment or instrumentation and provide continuous streams of information regarding their status or well being. In the case study presented in this work, the network is provided by football teams with sensors generating continuous heart rate values during a number of different sporting activities. In wireless networks such as these, the requirement is for methods of data management and transformation in order to present data in a format suited to high level queries. In effect, what is required is a traditional database-style query interface where domain experts can continue to probe for the answers required in more specialised environments. The challenge arises from the gap that emerges between the low level sensor output and the high level user requirements of the domain experts. This paper describes a process to close this gap by automatically harvesting the raw sensor data and providing semantic enrichment through the addition of context data

Rushes video summarization using a collaborative approach

This paper describes the video summarization system developed by the partners of the K-Space European Network of Excellence for the TRECVID 2008 BBC rushes summarization evaluation. We propose an original method based on individual content segmentation and selection tools in a collaborative system. Our system is organized in several steps. First, we segment the video, secondly we identify relevant and redundant segments, and finally, we select a subset of segments to concatenate and build the final summary with video acceleration incorporated. We analyze the performance of our system through the TRECVID evaluation

Probing the fuzzy sphere regularisation in simulations of the 3d \lambda \phi^4 model

We regularise the 3d \lambda \phi^4 model by discretising the Euclidean time and representing the spatial part on a fuzzy sphere. The latter involves a truncated expansion of the field in spherical harmonics. This yields a numerically tractable formulation, which constitutes an unconventional alternative to the lattice. In contrast to the 2d version, the radius R plays an independent r\^{o}le. We explore the phase diagram in terms of R and the cutoff, as well as the parameters m^2 and \lambda. Thus we identify the phases of disorder, uniform order and non-uniform order. We compare the result to the phase diagrams of the 3d model on a non-commutative torus, and of the 2d model on a fuzzy sphere. Our data at strong coupling reproduce accurately the behaviour of a matrix chain, which corresponds to the c=1-model in string theory. This observation enables a conjecture about the thermodynamic limit.Comment: 31 pages, 15 figure

Fuzzy Scalar Field Theory as a Multitrace Matrix Model

We develop an analytical approach to scalar field theory on the fuzzy sphere based on considering a perturbative expansion of the kinetic term. This expansion allows us to integrate out the angular degrees of freedom in the hermitian matrices encoding the scalar field. The remaining model depends only on the eigenvalues of the matrices and corresponds to a multitrace hermitian matrix model. Such a model can be solved by standard techniques as e.g. the saddle-point approximation. We evaluate the perturbative expansion up to second order and present the one-cut solution of the saddle-point approximation in the large N limit. We apply our approach to a model which has been proposed as an appropriate regularization of scalar field theory on the plane within the framework of fuzzy geometry.Comment: 1+25 pages, replaced with published version, minor improvement