Miguel Alemán-Flores, Departamento de Informática y Sistemas, Universidad de Las Palmas de

This paper presents a new approach to noise reduction and contrast enhancement for different types of medical images. An anisotropic scheme is used to iteratively reduce noise as well as to define image regions and enhance region contrast. This allows an easier semiautomatic segmentation of the regions of interest. The process is performed in three stages, which consists in reducing noise, enhancing contrast and segmenting regions. The final values of the regions are automatically extracted from the image histogram, thus providing a fast method to obtain the most significant information in the image and a good approximation to region boundaries. This technique can be applied, not only to multiple region image segmentation, but also to certain processes of computer aided diagnosis which include several types of feature extraction and shape analysis.

Chris Bailey, Department of Computer Science, University of York, Heslington Researcher, York Researcher, UK Researcher

Digital electronics is an area of student learning that benefits substantially from ‘hands-on’ experience. Simply simulating circuits at a high level will not instill a full understanding of the pitfalls involved in circuit building, testing and design in the real world. Consequently most electronics related curriculums will include practical lab-work to supplement any other activities to be delivered as part of a course module. At many UK universities the use of ‘bread-boards’ is common. These are rapid circuit construction boards, which allow circuits based upon chips to be wired and tested. However, it is less practical for students to undertake such work unsupervised (due to health and safety legislation), and also often not practical for them to undertake this work at home. Consequently, a Digital Bread Board simulator to supplement such teaching styles is a valuable teaching aid. This paper describes the Bread- Board Simulator developed at the University of York over a number of years, and a new project to release the tool-set as an Open-Source Learning Platform.

Laura Plaza, Facultad de Informática, Universidad Complutense de Madrid, C/ Prof. José García

One of the main handicaps in research on automatic summarization is the vague semantic comprehension of the source, which is reflected in the poor quality of the consequent summaries. Using further knowledge, as that provided by ontologies, to construct a complex semantic representation of the text, can considerably alleviate the problem. In this paper, we introduce an ontology-based extractive method for summarization. It is based on mapping the text to concepts and representing the document and its sentences as graphs. We have applied our approach to news articles, taking advantages of free resources such as WordNet. Preliminary empirical results are presented and pending problems are identified.

BUILDING A COLLABORATORY IN AN ENGINEERING R, D ORGANIZATION Zita P. Correia, Catarina Egreja, Maria Joaquina Barrulas. LNEG – Laboratório Nacional

This paper presents the results achieved throughout the process of preparing the ground to develop a collaboratory in an Engineering R&D organization. This case study is part of a broader research project engaged in building a collaboratory in order to share knowledge and resources among the Portuguese State laboratories. In the process of preparing the ground to develop the collaboratory in the first of the laboratories studied, an information audit was conducted and an online survey was launched. The survey targeted 241 people, including mainly professional researchers, but also research trainees and some technical staff integrating the research teams. The questionnaire was designed so as to collect data on the organization’s information management and information culture, and on the information flows taking place, and their relationship with the objectives of the organization. The questionnaire comprised two distinct and independent parts. The first (on the organization’s information culture and information management) obtained seventy nine responses, while the second (information flows) achieved ninety two, corresponding to 32,8% and 38,2% of the total population, respectively. The work carried out provided the basic requirements for the task of developing a software infrastructure to support the collaboratory, addressing the various aspects of collaborative tools, information archiving, hierarchical tag classification, search, transparent integration of the user local environment with the platform and remote control of scientific instruments.

Mauro Figueiredo. Universidade do Algarve.

This paper presents an efficient collision detection algorithm designed to support assembly and maintenance simulation of complex assemblies. This approach exploits the surface knowledge, available from CAD models, to determine intersecting surfaces. It proposes a novel combination of Overlapping Axis-Aligned Bounding Box (OAABB) and R-tree structures to gain considerable performance improvements. This paper also shows an efficient traversal algorithm based on the R-tree structure of Axis-Aligned Bounding Boxes to determine intersecting objects and intersecting surfaces between three- dimensional components, for supporting the recognition of constraints in assembly and disassembly operations in virtual prototyping environments. The implementation of the proposed collision detection algorithm, known as S-CD (Surface Collision Detection) toolkit, performs well against moderately complex industrial case studies. Current experimental results show that S-CD is effective in determining intersecting surfaces at interactive rates with moderately complex real case studies.

Yajie Ma

In this paper, we investigate the development of distributed real-time data mining algorithms for sensor network applications with a focus on air pollution monitoring applications. Our approach is based on a considering two-layer sensor network framework comprising mobile and stationary sensors. We present architectural abstractions for such a network that are suitable for conducting peer-to-peer data mining algorithms. We also develop and evaluate the performance of a real-time peer-to-peer data clustering algorithm for the identification of pollution hotspots and for analyzing the dispersion of pollution clouds. We conduct an experimental evaluation of our algorithms to compare the accuracy of our algorithms to centralized implementations and identify the associated tradeoffs.

Matthew Kowgier, Rafal Kustra. Dalla Lana School of Public Health, University of Toronto

We present a novel Hidden Markov Model for detecting copy number variations (CNV) from genotyping arrays. Our model is a novel application of HMM to inferring CNVs from genotyping arrays: it assumes a continuous-time framework and is informed by prior findings from previously analyzed real data. This framework is also more realistic than discrete-time models which are currently used since it does not assume that CNV breakpoints occur at the genotyped loci. We show how to estimate the model parameters using a training data of normal samples whose CNV regions have been confirmed, and present results from applying the model to a set of HapMap samples containing aberrant SNPs.

Michael Decker. Institute AIFB, Karlsruhe Institute of Technology (KIT), Kaiserstr.

The basic notion of Location-Aware Access Control (LAAC) is to evaluate the current position of a mo- bile user as provided by a locating system like GPS when making the decision if a user’s request to per- form a particular operation on a particular resource under the control of an information system should be granted or denied. LAAC is a mean to forbid the access to computer resources when the mobile user stays at a place where it is not reasonable or not safe enough to access the respective resources. For ex- ample, using this approach a policy could be enforced that demands that a confidential document (re- source) can only be read (operation) while staying on the premises of a particular company. The aim of this paper is to give an overview on works in the field of LAAC. The special focus is on Access Control Models (ACM) which are the data models needed to formulate and maintain location-aware access con- trol policies.

Pedro Isaías

Editorial preface for Volume 5, Issue 1 of the IADIS International Journal on Computer Science and Information Systems (IJCSIS). This issue brings together peer-reviewed original research contributions covering the wide spectrum of Information Systems, Artificial Intelligence, Software Engineering, and Digital Transformation.