48,380 research outputs found
Client-Driven Content Extraction Associated with Table
The goal of the project is to extract content within table in document images
based on learnt patterns. Real-world users i.e., clients first provide a set of
key fields within the table which they think are important. These are first
used to represent the graph where nodes are labelled with semantics including
other features and edges are attributed with relations. Attributed relational
graph (ARG) is then employed to mine similar graphs from a document image. Each
mined graph will represent an item within the table, and hence a set of such
graphs will compose a table. We have validated the concept by using a
real-world industrial problem
A collaborative platform for integrating and optimising Computational Fluid Dynamics analysis requests
A Virtual Integration Platform (VIP) is described which provides support for the integration of Computer-Aided Design (CAD) and Computational Fluid Dynamics (CFD) analysis tools into an environment that supports the use of these tools in a distributed collaborative manner. The VIP has evolved through previous EU research conducted within the VRShips-ROPAX 2000 (VRShips) project and the current version discussed here was developed predominantly within the VIRTUE project but also within the SAFEDOR project. The VIP is described with respect to the support it provides to designers and analysts in coordinating and optimising CFD analysis requests. Two case studies are provided that illustrate the application of the VIP within HSVA: the use of a panel code for the evaluation of geometry variations in order to improve propeller efficiency; and, the use of a dedicated maritime RANS code (FreSCo) to improve the wake distribution for the VIRTUE tanker. A discussion is included detailing the background, application and results from the use of the VIP within these two case studies as well as how the platform was of benefit during the development and a consideration of how it can benefit HSVA in the future
Content Based Traffic Engineering in Software Defined Information Centric Networks
This paper describes a content centric network architecture which uses
software defined networking principles to implement efficient metadata driven
services by extracting content metadata at the network layer. The ability to
access content metadata transparently enables a number of new services in the
network. Specific examples discussed here include: a metadata driven traffic
engineering scheme which uses prior knowledge of content length to optimize
content delivery, a metadata driven content firewall which is more resilient
than traditional firewalls and differentiated treatment of content based on the
type of content being accessed. A detailed outline of an implementation of the
proposed architecture is presented along with some basic evaluation
Abmash: Mashing Up Legacy Web Applications by Automated Imitation of Human Actions
Many business web-based applications do not offer applications programming
interfaces (APIs) to enable other applications to access their data and
functions in a programmatic manner. This makes their composition difficult (for
instance to synchronize data between two applications). To address this
challenge, this paper presents Abmash, an approach to facilitate the
integration of such legacy web applications by automatically imitating human
interactions with them. By automatically interacting with the graphical user
interface (GUI) of web applications, the system supports all forms of
integrations including bi-directional interactions and is able to interact with
AJAX-based applications. Furthermore, the integration programs are easy to
write since they deal with end-user, visual user-interface elements. The
integration code is simple enough to be called a "mashup".Comment: Software: Practice and Experience (2013)
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