A Product Oriented Modelling Concept: Holons for systems synchronisation and interoperability

Nowadays, enterprises are confronted to growing needs for traceability, product genealogy and product life cycle management. To meet those needs, the enterprise and applications in the enterprise environment have to manage flows of information that relate to flows of material and that are managed in shop floor level. Nevertheless, throughout product lifecycle coordination needs to be established between reality in the physical world (physical view) and the virtual world handled by manufacturing information systems (informational view). This paper presents the "Holon" modelling concept as a means for the synchronisation of both physical view and informational views. Afterwards, we show how the concept of holon can play a major role in ensuring interoperability in the enterprise context

Self Super-Resolution for Magnetic Resonance Images using Deep Networks

High resolution magnetic resonance~(MR) imaging~(MRI) is desirable in many clinical applications, however, there is a trade-off between resolution, speed of acquisition, and noise. It is common for MR images to have worse through-plane resolution~(slice thickness) than in-plane resolution. In these MRI images, high frequency information in the through-plane direction is not acquired, and cannot be resolved through interpolation. To address this issue, super-resolution methods have been developed to enhance spatial resolution. As an ill-posed problem, state-of-the-art super-resolution methods rely on the presence of external/training atlases to learn the transform from low resolution~(LR) images to high resolution~(HR) images. For several reasons, such HR atlas images are often not available for MRI sequences. This paper presents a self super-resolution~(SSR) algorithm, which does not use any external atlas images, yet can still resolve HR images only reliant on the acquired LR image. We use a blurred version of the input image to create training data for a state-of-the-art super-resolution deep network. The trained network is applied to the original input image to estimate the HR image. Our SSR result shows a significant improvement on through-plane resolution compared to competing SSR methods.Comment: Accepted by IEEE International Symposium on Biomedical Imaging (ISBI) 201

Supporting 'design for reuse' with modular design

Engineering design reuse refers to the utilization of any knowledge gained from the design activity to support future design. As such, engineering design reuse approaches are concerned with the support, exploration, and enhancement of design knowledge prior, during, and after a design activity. Modular design is a product structuring principle whereby products are developed with distinct modules for rapid product development, efficient upgrades, and possible reuse (of the physical modules). The benefits of modular design center on a greater capacity for structuring component parts to better manage the relation between market requirements and the designed product. This study explores the capabilities of modular design principles to provide improved support for the engineering design reuse concept. The correlations between modular design and 'reuse' are highlighted, with the aim of identifying its potential to aid the little-supported process of design for reuse. In fulfilment of this objective the authors not only identify the requirements of design for reuse, but also propose how modular design principles can be extended to support design for reuse

Substructure Discovery Using Minimum Description Length and Background Knowledge

The ability to identify interesting and repetitive substructures is an essential component to discovering knowledge in structural data. We describe a new version of our SUBDUE substructure discovery system based on the minimum description length principle. The SUBDUE system discovers substructures that compress the original data and represent structural concepts in the data. By replacing previously-discovered substructures in the data, multiple passes of SUBDUE produce a hierarchical description of the structural regularities in the data. SUBDUE uses a computationally-bounded inexact graph match that identifies similar, but not identical, instances of a substructure and finds an approximate measure of closeness of two substructures when under computational constraints. In addition to the minimum description length principle, other background knowledge can be used by SUBDUE to guide the search towards more appropriate substructures. Experiments in a variety of domains demonstrate SUBDUE's ability to find substructures capable of compressing the original data and to discover structural concepts important to the domain. Description of Online Appendix: This is a compressed tar file containing the SUBDUE discovery system, written in C. The program accepts as input databases represented in graph form, and will output discovered substructures with their corresponding value.Comment: See http://www.jair.org/ for an online appendix and other files accompanying this articl

Federation views as a basis for querying and updating database federations

This paper addresses the problem of how to query and update so-called database federations. A database federation provides for tight coupling of a collection of heterogeneous component databases into a global integrated system. This problem of querying and updating a database federation is tackled by describing a logical architecture and a general semantic framework for precise specification of such database federations, with the aim to provide a basis for implementing a federation by means of relational database views. Our approach to database federations is based on the UML/OCL data model, and aims at the integration of the underlying database schemas of the component legacy systems to a separate, newly defined integrated database schema. One of the central notions in database modelling and in constraint specifications is the notion of a database view, which closely corresponds to the notion of derived class in UML. We will employ OCL (version 2.0) and the notion of derived class as a means to treat (inter-)database constraints and database views in a federated context. Our approach to coupling component databases into a global, integrated system is based on mediation. The first objective of our paper is to demonstrate that our particular mediating system integrates component schemas without loss of constraint information. The second objective is to show that the concept of relational database view provides a sound basis for actual implementation of database federations, both for querying and updating purposes.

A Three-Level Process Framework for Contract-Based Dynamic Service Outsourcing

Service outsourcing is the business paradigm, in which an organization has part of its business process performed by a service provider. In dynamic markets, service providers are selected on the fly during process enactment. The cooperation between the parties is\ud specified in a dynamically made electronic contract. This contract includes a process specification that is tailored towards service matchmaking and crossorganizational process enactment and hence has to conform to specific market and specification standards. Process enactment, however, relies on intraorganizational process specifications that have to comply with the infrastructure available in an organization. In this position paper, we present a three-level process specification framework for dynamic contract-based\ud service outsourcing. This framework relates the two process specification levels through a third, conceptual level. This approached is inspired by the well-known ANSI-SPARC model for data management. We show how the framework can be placed in the context of infrastructures for cross-organizational process support