Research Jan Paredaens

Abstract

This project represents a formal research agreement between UA and on the other hand the Flemish Public Service. UA provides the Flemish Public Service research results mentioned in the title of the project under the conditions as stipulated in this contract.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

This project represents a formal research agreement between UA and on the other hand Locus. UA provides Locus research results mentioned in the title of the project under the conditions as stipulated in this contract.

Researcher(s)

• Promoter: Paredaens Jan
• Promoter: Vallet Nathalie
• Co-promoter: Vallet Nathalie

Research team(s)

• Henry van de Velde

Project type(s)

• Research Project

Abstract

The goal of the project is to develop of new database techniques to support the cleaning of data, metadata and data transformations. In this context, cleaning is to be understood as the identification and correction of incompleteness, inconsistencies, inaccuracies and errors.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

The specific research questions the project aims to resolve are: 1. How can we achieve efficient reasoning support in case of distribution? 2. What is an efficient way of modularizing and distributing ontology-based data?

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

In this research we aim to find ways of summarizing a database by using the patterns that occur within it. Employing state of the art data mining techniques, the goal is to retrieve a concise subset of all patterns, that characterize the data as well as possible.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Mampaey Michael

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

The project proposes a methodology for text mining with heterogeneous information sources and its application to molecular genetics/genomics and knowledge management. State of the art text analysis and graph-based data mining techniques will be extended to make the methodology possible, and the methodology will be applied in a biomedical application (ranking of candidate disease-causing genes) and a knowledge management application (person profiling from www information).

Researcher(s)

• Promoter: Daelemans Walter
• Co-promoter: Del-Favero Jurgen
• Co-promoter: De Rijk Peter
• Co-promoter: Paredaens Jan

Research team(s)

• Centre for Computational Linguistics, Psycholinguistics and Sociolinguistics (CLiPS)

Project website

Project type(s)

• Research Project

Abstract

Software-intensive systems are among the most complex artefacts ever built. In the development of such systems, the use of rigorous models and analysis methods is essential to make sure that the software satisfies its requirements and exhibits the desired properties (e.g., safety, security, reliability, consistency). At the same time, in order to adapt to the constantly changing requirements and technology, these systems must be able to evolve over time, without breaking their essential properties. This project combines the leading Belgian research teams in software engineering, with recognised scientific excellence in model-driven engineering (MDE), software evolution, formal modelling and verification (FMV) and aspect-oriented software development (AOSD). The project aims to advance the state of the art in each of these domains. The long term objective of our network is to strengthen existing collaborations and forge new links between those teams, and to leverage and disseminate our research expertise in this domain at a European level.

Researcher(s)

• Promoter: Demeyer Serge
• Co-promoter: Janssens Dirk
• Co-promoter: Paredaens Jan

Research team(s)

• Antwerp Systems and software Modelling (AnSyMo)

Project type(s)

• Research Project

Abstract

Finding patterns in arbitrary relational databases remains an interesting problem for which only very few efficient techniques exist. We study the framework in which pairs of queries over the data are used as patterns and consider the problem of finding interesting associations between them. More specifically, we investigate small subclasses of conjunctive queries that still allow to find interesting patterns efficiently.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Le Page Wim

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

The project has practical objectives and aims at calculating a "BEL-20 index" (capital gain as well as total return index) for the period 1832-2005 for the Brussels Stock Exchange. These indices will be compared with returns calculated for the risk free rate, for the banking sector, for the all share index and other portfolios of the Brussels Stock Exchange for the same period. By doing so a brand new benchmark will be available for a long historical period.

Researcher(s)

• Promoter: Cuyvers Ludo
• Co-promoter: Annaert Jan
• Co-promoter: De Ceuster Marc
• Co-promoter: Deloof Marc
• Co-promoter: De Smedt Helma
• Co-promoter: Devos Greta
• Co-promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Hidders Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

In this project, we study the realization of an inductive database model. The most important steps in the realization of such a model are : a) a uniform representation of patterns and data; b) a query-language for querying the data and the patterns; c) the integration of existing optimization techniques into the physical layer.

Researcher(s)

• Promoter: Paredaens Jan
• Co-promoter: Calders Toon
• Co-promoter: Goethals Bart

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

The integration of different kinds of data is an important issue in the world of Content Management Systems, since one wishes to query all these (heterogeneous) data in an uniform way. The focus in our research is integrating relational data and XML by generating XML views for relational databases. Not only querying, but also updating the relational database using these XML views will be possible. However, updating the respective tables of a relational database through an (XML) view can cause some problems. Therefore we will investigate which updates are possible (and which are not), and we'll also try to convert the (relational) schema to a schema for the XML view.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Vercammen Roel

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Michiels Philippe

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Le Page Wim

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Given the present distinct lack of a generally accepted framework for data mining, the quest for such a framework is a major research priority. The most promising approach to this task is taken by inductive databases (IDBs), which contain not only data, but also patterns. Patterns can be either local patterns, such as frequent itemsets, which are of descriptive nature, or global models, such as decision trees, which are of predictive nature. In an IDB, inductive queries can be used to generate (mine), manipulate, and apply patterns. The IDB framework is appealing as a theory for data mining, because it employs declarative queries instead of ad hoc procedural constructs. Declarative queries are often formulated using constraints and inductive querying is closely related to constraint-based data mining. The IDB framework is also appealing for data mining applications, as it supports the process of knowledge discovery in databases (KDD): the results of one (inductive) query can be used as input for another and nontrivial multi-step KDD scenarios can be supported, rather than just single data mining operations.The state-of-the-art in IDBs is that there exist various effective approaches to constraint-based mining (inductive querying) of local patterns, such as frequent itemsets and sequences, most of which work in isolation. The proposed project aims to significantly advance the state-of-the-art by developing the theory of and practical approaches to inductive querying (constraint-based mining) of global models, as well as approaches to answering complex inductive queries that involve both local patterns and global models. Based on these, showcase applications/IDBs in the area of bioinformatics will be developed, where users will be able to query data about drug activity, gene expression, gene function and protein sequences, as well as frequent patterns (e.g., subsequences in proteins) and predictive models (e.g., for drug activity or gene function).

Researcher(s)

• Promoter: Paredaens Jan
• Co-promoter: Goethals Bart

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Information Extraction (IE) is concerned with extracting relevant data from a collection of structured or semi-structured documents. Current systems are trained using annotated corpora that are expensive and difficult to obtain in real-life applications. Therefore in this project we want to focus on the development of IE systems using semi-supervised learning, a technique that makes use of a large collection of un-annotated and easily-available data.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

In this project we consider languages for querying and updating semi-structured data as for example XML data. These languages are investigated for their theoretical and practical properties such as expressive power and suitability for query optimisation. If a database server of semi-structured data has to support such languages in an efficient way, then special techniques in the area of locking and indexing are necessary. Therefore we also investigate to what extent old techniques can be adapted for this and, if necessary, new more suitable techniques can be developed.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

The integration of different kinds of data is an important issue in the world of Content Management Systems, since one wishes to query all these (heterogeneous) data in an uniform way. The focus in our research is integrating relational data and XML by generating XML views for relational databases. Not only querying, but also updating the relational database using these XML views will be possible. However, updating the respective tables of a relational database through an (XML) view can cause some problems. Therefore we will investigate which updates are possible (and which are not), and we'll also try to convert the (relational) schema to a schema for the XML view.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Vercammen Roel

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Michiels Philippe

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Large sums have been invested in gathering information about genomes, genes, proteins and other molecular characteristics of various organisms. One strongly hopes that it will be useful in describing the way cells function, explaining phylogenetic relations between various species, designing new pharmaceuticals and therapies to cure presently uncurable diseases. This precious data is however stored in databases which do not follow any widely accepted design principles, do not offer any standardized query languages and, last but not least, do not give any chance of interoperation. The truth is that there are no widely accepted design principles and no standardized query languages for the databases of bioinformatics. Moreover, often databases do not allow querying all the data, which they store. A paradigmatic example is the COG database http://www.ncbi.nlm.nih.gov/COG/. COGs are Clusters of Ortologous Genes, where each of the clusters is a set of sequences of homologous proteins from currently 73 different organisms. For each of the over 3300 COGs a phylogenetic tree has been reconstructed, based on similarity analyses of the proteins in that cluster. The trees contain a vast amount of derived information, which has been once determined and stored in the database. However, surprisingly enough, the database of COGs does not include any mechanism allowing one to use queries referring to the information stored in the trees, like, e.g., "find pairs of organisms, whose proteins are siblings in at least two trees and are at least three tree branches apart in another at least two". It seems self-evident that the family of trees over all COGs should have the status of a materialized view, often met in the classical databases, and that the user should be allowed to pose queries referring to those trees.The same situation is found in many other databases. It seems therefore unquestionable that a remedy is strongly needed, to make all what is really known in molecular biology fully accessible

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

This project aims at a systematic study of the possibilities and problems for a database system for data mining. The development of a database system for data mining brings up a lot of fundamental questions. How will we represent the data? In which way can we integrate the data mining algorithms in query languages? How can we optimize the queries? A theoretical and fundamental approach to these questions is the central theme in this project.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Calders Toon

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

In the international arena increased efforts are being made to give people with mental retardation access to modern technologies. The three centers involved have been collaborating since 1990 with regard to the design and adaptation of software and hardware for this target group. This fieldwork requires scientific support: a database of available products will be developed and the centers' extensive expertise will allow them to fill major gaps on the supply side.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Information Extraction (IE) is concerned with extracting relevant data from a collection of structured or semi-structured documents. Current systems are trained using annotated corpora that are expensive and difficult to obtain in real-life applications. Therefore in this project we want to focus on the development of IE systems using semi-supervised learning, a technique that makes use of a large collection of un-annotated and easily-available data.

Researcher(s)

• Promoter: Tjong-Kim-Sang Erik
• Co-promoter: Daelemans Walter
• Co-promoter: Paredaens Jan

Research team(s)

• Centre for Computational Linguistics, Psycholinguistics and Sociolinguistics (CLiPS)

Project type(s)

• Research Project

Abstract

This project aims to assist in the research of the many side-aspects and problems that are involved when designing XML-Databases. The project focuses around three main subjects: -XML Query optimization -Multiuser issues in XML databases -XML Updating Language Furthermore, it is meant to provide a good reference to future XML-database implementers by supplying them with a detailed overview of many optimization techniques and algorithms in a multiuser XML storage environment.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Michiels Philippe

Research team(s)

Project type(s)

• Research Project

Abstract

Because of recent developments in knowledge engineering and hardware, large digital databases have become common. The value of these databases, however, is not only determined by their size, but also by the possibility of analysis. Data mining is the discovery of previously unknown dependencies in data. The goal is to find and reveal structure in the data, rather than going into the details of the data. These kinds of meta-data determine the value of the database. There are already important applications of data mining in the industry. The advantages of data mining for a company are huge. Since data mining is concerned with the meta-level of the data, there are many similarities with artificial intelligence and knowledge engineering. Because of this, data mining is regularly referred to as `knowledge discovery in databases.' Data mining is also strongly linked with OLAP online analytical processing. The research of data mining techniques started in the early nineties and grew enormously since 1995. Association rules are a type of rules commonly studied in data mining. There are a lot of known algorithms for finding this type of rules. However, this type of rules is very elementary. It would be interesting to study more general rules. A possible description language is first order logic. There are multiple complexity measures that can be studied: complexity in the number of tuples, in the number of attributes, and in the length of the rules. An interesting problem is the classification of these rules by their complexities. Afterwards, the research can go into studying patterns that allow algorithms with acceptable running times. In my graduate thesis, the search for a certain type of more general rules is studied. Another aspect of data mining is the following: how can a user of database- and OLAP-systems make maximal use of data mining tools? In this perspective, there is a need for expressive query languages that give the user the opportunity to query the database in a simple way. Another point of interest is the notion of `genericity'. Generic queries are queries that are independent of the chosen data structure. In data mining, however, many of the methods are strongly dependent on the physical shape of the data. At the moment, there is a lot of interest in data mining. At the UIA (University of Antwerp), a project on data mining, funded by FWO, is running. The proposed project is an extension to this project. The understanding of theoretical foundations is important. In contrast with much of the current research, that is performed in an ad-hoc way, this project has as goal to enlarge the theoretical knowledge in data mining.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Calders Toon

Research team(s)

Project type(s)

• Research Project

Abstract

A theoretical model will be defined in which complexity of computation and communication can be studied simultaneously, allowing one to analyse the tradeoffs between them, as well as to develop new protocols of query evaluation, optimizing the cumulative cost of the whole process of querying. The asymmetry concerning the computing power of the parties involved will be studied, as well as their access to the data.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Because of recent developments in knowledge engineering and hardware, large digital databases have become common. The value of these databases, however, is not only determined by their size, but also by the possibility of analysis. Data mining is the discovery of previously unknown dependencies in data. The goal is to find and reveal structure in the data, rather than going into the details of the data. These kinds of meta-data determine the value of the database. There are already important applications of data mining in the industry. The advantages of data mining for a company are huge. Since data mining is concerned with the meta-level of the data, there are many similarities with artificial intelligence and knowledge engineering. Because of this, data mining is regularly referred to as `knowledge discovery in databases.' Data mining is also strongly linked with OLAP online analytical processing. The research of data mining techniques started in the early nineties and grew enormously since 1995. Association rules are a type of rules commonly studied in data mining. There are a lot of known algorithms for finding this type of rules. However, this type of rules is very elementary. It would be interesting to study more general rules. A possible description language is first order logic. There are multiple complexity measures that can be studied: complexity in the number of tuples, in the number of attributes, and in the length of the rules. An interesting problem is the classification of these rules by their complexities. Afterwards, the research can go into studying patterns that allow algorithms with acceptable running times. In my graduate thesis, the search for a certain type of more general rules is studied. Another aspect of data mining is the following: how can a user of database- and OLAP-systems make maximal use of data mining tools? In this perspective, there is a need for expressive query languages that give the user the opportunity to query the database in a simple way. Another point of interest is the notion of `genericity'. Generic queries are queries that are independent of the chosen data structure. In data mining, however, many of the methods are strongly dependent on the physical shape of the data. At the moment, there is a lot of interest in data mining. At the UIA (University of Antwerp), a project on data mining, funded by FWO, is running. The proposed project is an extension to this project. The understanding of theoretical foundations is important. In contrast with much of the current research, that is performed in an ad-hoc way, this project has as goal to enlarge the theoretical knowledge in data mining.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Calders Toon

Research team(s)

Project type(s)

• Research Project

Abstract

The purpose of this project is to design new query languages to support data mining in relational and object-oriented database systems; to study the semantics of such query languages; to study their computational complexity and expressive power; and to develop execution mechanisms for these query languages.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

The research in this project is on query languages for spatial databases in the polynomial constraint model. Both databases and queries are described by means of polynomial inequalities in this context. Especially, the notion of genericity, that also plays a central role in the theory of the relational database model, is the main motivation for this research. The aim of this project is to acquire a better understanding of the expressive power of languages that are either complete for certain geometric notions of genericity, or can express certain complexity classes within a certain notion of genericity . More specifically, complete languages for the computable topological queries are investigated, extensions of the constraint model to spatio-temporal databases are studied, and query languages based on ruler and compass constructions are investigated.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Kuijpers Bart J P

Research team(s)

Project type(s)

• Research Project

Abstract

A recent development in database research, the shift of focus from general-purpose database models to special-purpose models which capture more of the semantics of the data, has revealed the existence of a number of concepts common to these new models The aim of this project is to identify a general and theoretical framework for further research in modern database applications, by integrating recent findings in three of these new applications; spatial databases, text-based databases and OLAP-systems.

Researcher(s)

• Promoter: Paredaens Jan
• Co-promoter: Gyssens Marc

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

The project aims to cataloguise company specific information and digitise price information contained in the archive of the BSE. Furthermore, empirical finance research and historical research will be initiated based on this database.

Researcher(s)

• Promoter: Cuyvers Ludo
• Co-promoter: Annaert Jan
• Co-promoter: De Ceuster Marc
• Co-promoter: De Smedt Helma
• Co-promoter: Devos Greta
• Co-promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

There are two fundamental, linguistic problems to model the interpretation of a context: 1. Making connections that are not explicitely mentioned in the text, such as co-reference and temporal relationships 2. the contextual disambiguation of ambiguous words or constructions. In this project we will focus on the represenation and interpretation of temporal expressions in Dutch. We use the representation language of Discourse Representation Theory as basis. The goal is to use data mining techniques to formulate disambiguation rules. We will need new data modelling techniques, as well as new inferention methodologies for this purpose. The project's aim is to research the possibilities to use abduction for the interpretation of the context of temporal expressions, as well as the usage of inductive reasoning for the extraction of disambiguation rules.

Researcher(s)

• Promoter: Paredaens Jan
• Co-promoter: Daelemans Walter

Research team(s)

Project type(s)

• Research Project

Abstract

To cope with the need to build increasingly large and complex software systems, there is a growing demand for declarative approaches which abstract away unnecessary details and focus on the functionality of the systems. The network wants to further promote the development of such approaches which emerge from work in databases, functional and logic programming.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Analysis and design of a database for the administration of a medical department. The data contains e.g. patient information, protocols and images.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

As future research work I propose to do further investigation into the area of drawing Visual Representation System for HoHs beatifully. I would like to investigate more for alternative planarity definitions for the representations. Later, I would go for developing algorithms to generate optimal drawings for the representations. Next I propose to explore the possibility of designing a more complex Visual Representation system using the new model hyrcon as a building block. This may be quite interesting as it gives rise to the possibility of attaining higher and higher levels of data abstraction. Finally I would like to enrich hyrcon with the capability of expressing Cartesian product of sets. Furthermore investigation has to be done to enrich hyrcon with other functions that makes it a still more powerful system for expressing information.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Possibilities and limitations of advanced database systems are investigated by means of formal methods. Examples of systems under investigation are relational, object oriented, spatial, temporal and text databases.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Van Den Bussche Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Query languages and update languages are designed for object oriented database systems. Their user interfaces are studied. The relationship with logic is als discussed. The theory is applied to numerical mathematics.

Researcher(s)

• Promoter: Paredaens Jan
• Co-promoter: Cuyt Annie

Research team(s)

Project type(s)

• Research Project

Abstract

A recent research trend in databases tries to integrate the notion of object orientation into existing database models and techniques, in such a way that the results obtained thus far remain applicable as much as possible. It is in this area that research is conducted. In particular, attention is paid to the logical foundations of databases and their query languages.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Van Den Bussche Jan

Research team(s)

Project type(s)

• Research Project

Abstract

This is a network of European universities and research institutes that coordinate the research in databases and multimedia. The main contractor is the university of Hamburg. The UIA is responsible for the distribution of information.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

A number of new models and languages for relational databases are designed and their expressiveness is studied. Extentions of the flat relational model are discussed.

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

A recent research trend in databases tries to integrate the notion of object orientation into existing database models and techniques, in such a way that the results obtained thus far remain applicable as much as possible. It is in this area that research is conducted. In particular, attention is paid to the logical foundations of databases and their query languages.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Van Den Bussche Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan
• Co-promoter: Gyssens Marc

Research team(s)

Project type(s)

• Research Project

Abstract

A recent research trend in databases tries to integrate the notion of object orientation into existing database models and techniques, in such a way that the results obtained thus far remain applicable as much as possible. It is in this area that research is conducted. In particular, attention is paid to the logical foundations of databases and their query languages.

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Van Den Bussche Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Andries Mark

Research team(s)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

This project concerns the automatic calculation of the readability level of French texts and the automatic correction of style and syntax errors

Researcher(s)

• Promoter: Tasmowski Liliane
• Co-promoter: Paredaens Jan

Research team(s)

Project type(s)

• Research Project

Abstract

Researcher(s)

• Promoter: Paredaens Jan
• Fellow: Van Den Bussche Jan

Research team(s)

Project type(s)

• Research Project