Fabrizio Pecoraro, Daniela Luzi, Fabrizio L. Ricci. Institute for Research on Population

This paper proposes a semi -automatic approach to extract information stored in a HL7 Clinical Document Architecture (CDA) and transform them to be loaded in a Data Warehouse for secondary purposes. It represents a suitable solution to faci litate the design and implementation of Extract, Transform and Load (ETL) tools that are considered the most time -consuming step of the data warehouse development process. The implementation of this framework is also proposed adopting the XSLT style sheet language that converts an original CDA XML -based document to an output XML document that can be easily loaded in the Data Warehouse. A case study is also provided to demonstrate the feasibility of the approach proposed.

Saeed Samet. eHealth Research Unit, Faculty of Medicine, Memorial University

Health informatics, using new information technol ogy, provides a fruitful set of data resource and knowledge that is very useful for secondary data users and researchers in various health systems and applications. Privacy acts, on the other hand, prevent direct access to this information without patient' s consent. Various solutions have been proposed such as data anonymization and de-identification, on-site analysis, and limited remote access, to preserve the data owner's privacy. Each of those approache s has different drawbacks and limitations. For instance, data de-identification will reduce data utility because of low precision of the final released data, and also it has a risk of data re -identification using available public data and background knowledge . On-site analysis has physical limitations , such as lack of data centers in every geographic area, and time-consuming procedures, such as background checks. Remote access increases security risks, and when data has to be pulled from multiple data resources, it requires patient consent for data dis closure. In this paper, we propose a set of privacy -preserving methods and techniques for some popular health statistical analysis methods. Using this set of secure protocols health researchers and other data users are able to issue their requests as some queries, and receive only the results of their queries from the data owners, while each data custodian can keep their sensitive data private. Proposed methods have been tested using sample data to illustrate the performance of the results in terms of computational and communication complexities. Security proof of the proposed protocols has also been provided as a proof of concept.

Samuel Gallastegui. University of the Basque Country.

Many studies on computer games explore the concept of immersion, related with the idea of engagement and presence. However, immersion defines only one side of the relation between physical space and virtual space in games. When the virtual content of the game is orientated outside the boundaries of virtual space another relation is being generated, which this paper appoints as emersion. This paper will focus on this unstudied emersive orientation of the game interface. Specifically, this research addresses the question of how a change at interface level transforms the orientation of the interface inside out. The thesis is that from specific changes made at this level, different experiences of space in video games could in fact be generated. The aim is to analyze how these changes that are being made at interface level impact the spatial experience. In order to achieve this aim, firstly, a conceptual framework will be developed. Secondly, an analytical model for space involvement will be proposed. Lastly, some case -studies will be proposed and some conclusions offered. This paper will contribute to the def inition of the features iof emersion and to the analysis of the new possibilities for experiencing space in digital games.

Andreas Hufgard. IBIS Prof. Thome AG. Leitenweg, D-97286 Winterhausen. http://www.ibis-thome.de

In business IT, empirical data is very rarely in the form of corporate usage data from system analyses. This article is based on 105 ERP-systems that have been analyzed in -depth, and whose data delive r empirical conclusions about usage and the level of maturity of business processes, and quantify the primary types of activities users are involved in. The approach is applied by comparing two groups in the database: “Automotive Industry” and “Non -Automotive Industry”. Here we focus on identifying significant differences in the efficient use of business processes in purchasing between the groups. These efficiency indicator s where deviated from most accepted purchasing maturity models . The research question is to validate the high evaluation of the Automotive Industry in those models against the reality we can find in the ERP -System. The usage data was gathered from usage analyses of SAP systems via RBE Plus, a reverse business engineering tool. It is based on the activities of more than 270,000 users in organizations in Europe and the USA. The findings offer enterprises a standard of comparison and reveal potential for improvement in sub-processes.

Sejal Desai, Vinuth Chandrasheker, Vijay Mathapati, Venugopal K Rajuk, Sundaraja S Iyengar, Lalit M Patnaik

Keyword based search is extensively used method to discover k nowledge on the web. Generally, web users unable to arrange and define input queries relevant to their search because of adequate knowledge about domain. Hence, the input queries are normally short and ambiguous. Query recommendation is a method to recomme nd web queries that are related to the user initial query which helps them to locate their required information more precisely. It also helps the search engine to return appropriate answers and meet their needs. Usually users have ambiguous

Luis Alexandre da Silva, Kelton Augusto Pontara da Costa, Patricia Bellin Ribeiro

Nowadays, spam detection has been one of the foremost machine learning -oriented applications in the context of security in computer networks. In this work, we propose to learn intrinsic properties of e-mail messages by means of Restricted Boltzmann Machines (RBM s) in order to identity whether such messages contain relevant (ham) or non-relevant (spam) content. The main idea contribution of this work is to employ Harmony Search-based optimization techniques to fine-tune RBM parameters, as well as to evaluate their robustness in the context spam detection. The unsupervised learned features are then used to feed the Optimum-Path Forest classifier, being the original features extracted from e-mail content and compared against the new ones. The results have shown RBMs are suitable to learn features from e-mail data, since they obtained favorable results in the datasets considered in this work.

Irina Bernst, Christof Kaufmann, Jörg Frochte. Dept. of Electrical Engineering

The work we present deals with the problem to provide learning assistance systems in the context of simulation and modelling. We develop a classification scheme for learning assistance systems and the ir use cases. Beyond this, we discuss how learning from simulation data differs from traditional knowledge discovery from data bases. The discussion contains a classification and review of existing approaches followed by a n enclosing case study of an assistance system for load balancing purpose in FEM simulation. The pres ented application case uses a two -stage architecture to minimize additional computational costs. The approach does not require labeled data in the sense of a quality rating for a load distribution nor a teacher for the initial setup and can improve itself unsupervised. For the FEM simulation on heterogeneous distributed systems we introduce a novel feature set and perform an evaluation for several problem sets.

Jorun Børsting. Department of Informatics, University of Oslo, P.B., Oslo, Norway. Researcher

This paper is concerned with the design of a system that handles published research literature evaluation related to clinical DNA sequencing and analysis of genetic variants. The literature handling system is part of a larger system, the Norwegian clinical genetic Analysis Platform, currently under development at the Department of Medical Genetics at Oslo University Hospital. The genAP project has inquired int o data handling requirements, procedures and supportive bioinformatics tools for analysis of genetic data. Finding and evaluating relevant literature that reports on clinical classifications of genetic variants is an important part of this process. In many cases, it is a requirement to compare local assessments with those published in high-quality external references, ensuring that the correct decision on the clinical nature of the variant is reached. The implications of the decisions made as part of this process are relevant for both patients and knowledge production and its transferability. We chose to use user -centered design as our research approach, in both qualitative (walk -troughs, interviews and talk -aloud evaluations) and quantitative (questionnaire) inquiries. User involvement in design and evaluation of the reference handling prototype was important for identifying diverse usability problems and design issues, which could then be improved in later iterations of the prototype. These issues included identifying the most relevant articles for a particular genetic variant and communicating uncertainty in individual assessments. Users have also contributed to defining more general guidelines for the re -design of later versions, e.g., a need for customiza tion, as users often have different strategies for working with references. We assert that user involvement in the design and evaluation processes, such as described in this paper, leads to system design that is more in tune with users’ needs, making the adoption and use of the system easier and improving the efficiency and quality of the analysis.

Pedro Isaías

Editorial preface for Volume 11, 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.