Other: Papers, Dissertations, Presentations, Posters, Reports, Course notes, Proposals
The
proposals listed below did or did not get funding. Many of them were
written by various groups. Copying part of a proposal without giving
due credit must be considered plagiarism. If you are interested in
this research consider contacting one of the partners to discuss
posibilities.
Bioinformatics
Analysis, Normalization & Estimation Algorithms for the Stratification of AML/ALL Cancer Patients
October 2006 - Werner Van Belle
This is a postdoctoral proposal sent to the University in Bergen. This project aims to apply signal processing techniques to analyze, normalize and build models for cancer proteomics. Through linking biomedical parameters (such as survival rate) to specific protein samples (from patients), better therapy might come into reach. The project parallelly investigates data handling procedures for mass spectrometry (MALDI TOF), 2D electrophoretic gels and gene array data. The built models will be validated as estimators in a cancer research setting.
Denoising of MALDI-TOF, 2D Gels and NMR Spectra
June 2005 - Werner Van Belle, Kjell-Arild Høgda
In this project we aim to use signal processing techniques to remove noise and normalize data of three different spectroscopy techniques: MALDI-TOF mass spectrometry, 2D gel images and NMR spectroscopy. Removal of noise is important in order to obtain more accurate data, to allow for automatic analysis in high throughput proteomics and to understand experimental limitations. Normalization schemes are necessary to compare results between different machines and different samples. This research will lead to a better quantitative understanding of experimental inaccuracies and allow for quantified biological comparisons. The developed algorithms will be freely accessible through a web interface
Model Inference and Simulation of the PI3 Kinase Pathway
June 2005 - Werner Van Belle, Niels Aarsæther
Cell simulation is the mathematical modeling of the behavior of a cell such that the model can be algorithmically executed, thereby enabling visualized prediction of the behavior of real living cells. Such models will be useful in the future to optimize and regulate biological processes such as the growth of yeasts, fungi and to find new medicines which merely regulate and coerce the cell in working differently/correctly (cancer research, diabetes, ...). In Norway, model inferencing techniques and learning techniques are being used at some institutions (Jonathan M. Irish, Randi Hovland et al, and Bø, T. H., Dysvik, B., Jonassen), nevertheless these models are seldom used in a predictive cell simulating context. As far as we know, there is currently no active research around whole cell simulation in Norway. From a methodological point of view it is clear that new methodological approaches that include molecular biology, cellular imaging, real-time kinetic analysis and network integrated analysis are required to progress in understanding the nature of signaling specificity. To keep track of and to quantify the complexity of pathways, a computational approach seems essential.
MarFlow Sample Tracking
November 2004 - Werner Van Belle
Tracking samples throughout many different organisations which all use different labeling protocols and are located at different geographical locations is difficult. This R&D program aims at the creation of a sample tracking system. The system will offer a) a labelling protocol designed for storage and unique identification of samples integrating many different labeling techniques b) a decentralised storage capacity (every organisation can store the data locally) and c) a security model which will take into account the ethics of sample exchange. A second aspect of the project aims at offering integration and data exchange towards existing sample tracking systems and analysis programs. We believe that this project and associated effort will reduce the costs of future information systems as well as increase cooperation between different research groups. The longer term goal of this project is the development of one or more commercial products related to sample tracking in cooperation with interested partners.
CodFormatics: Design of a Bioinformatic System to Assist the Cod Breeding Program
June 2004 - Tor Flå, Werner Van Belle, Said H. Ahmed, Madjid Delghandi
As input to the national codbreeding program, it is important to identify regions within the genome that are responsible for quantitative properties (QTL's). Obtaining these however is complicated by the huge amount of involved (environmental) factors. To be able to approach this problem we propose the creation of a bioinformatics tool that will a) help in analysing current datasets and b) help in guiding future experiments. E.g; by carefully selecting a set of fishes with the most desirable properties it might be possible to find the QTL much quicker than what would be possible by analysing all fishes.
Signal
Processing
Where are the Emotional
Cues in Music ?
May
2006
- Werner Van Belle, Bruno Laeng
What
are the underlying dimensions that give
structure and meaning to music ? To answer this
question, we aim
to integrate methodological techniques from other disciplines (signal
processing & mathematics) into the field of psychology and
psycho-physiology.
Our main goal is to measure in a mathematical and computational way
musical parameters and relate those to the human judgment of a song
its emotional content and in addition compare these to
psycho-physiological
measures (pupillometry and EEG).
Designing Music
Therapy: Developing Algorithms to Extract Emotion from Music
November
2005
- Werner Van Belle, Bruno Laeng
The effect of music
as a psychotherapeutic
tool has been recognized for a long time. Alone, or in combination
with classical treatment, music can alleviate depression, stress and
anxiety, as well as acute and chronic pain. Such beneficial effects
are likely to derive from its ability to induce mood changes. However,
it remains unclear which aspects of music can cause emotional changes.
This project aims to link advanced audio signal processing techniques
to empirical psychoacoustic testing to develop algorithms that
automatically
retrieve emotions associated with a particular piece of music. Such
algorithms could then be used to select and develop musical pieces
for therapeutic purposes
Development and Integration
of Algorithms that Extract Emotion from Music
Mars 2005
- Werner Van Belle, Bruno Laeng, Geir Davidsen
The described project
aims to link advanced audio signal processing
techniques to empirical psychoacoustic testing in order to develop
algorithms that can automatically retrieve (part of) the emotions
humans associate with music. The project is set up as a cooperation
between 3 partners: Norut IT, the Psychology department at the
University
of Tromsø and the music conservatory at Hoyskolen in
Tromsø. Commercial
relevance of the project is found in audio content extraction for
databases and search engines, quantitative assessment of emotion in
music for teaching, automatic creation of playlists, categorizing
sound libraries and plugins for sound production software used in
studios.
Computer
Science
Trustnet: Scalable,
Trusted Information Sharing for Ambient
Applications
June 2004
- Werner Van Belle, Lars K. Vognild, Tage Stabell-Kulø, Theo
D'Hondt
Peer-to-peer systems
are systems in which the gross of
the data is directly communicated between hosts, without going
through centrally placed servers. Typically, this kind of networks
organize themselves automatically, thereby neglecting the actual
network topology. This makes peer-to-peer systems a very attractive
means to support ad-hoc networks, such as interconnected embedded
devices. However, the peer-to-peer paradigm still poses a number of
research problems. Among them scalability,
finding useful information,
security
and the programming of applications in such volatile environments.
The objective is to address these problems by developing a scalable
and secure peer-to-peer
information sharing platform
together with a suitable programming model. The consortium
consists of three partners. Norut IT,
which is an applied research institute, the department of computer
science at the University of Tromsø (UiTø), which
pioneered the now wide spread distributed agent paradigm in 1996, and
the Programming Technology Lab at Brussels University, which is doing
research in programming language engineering for distributed systems.
By coupling the experience of these partners we ensure a strong, well
balanced consortium.
VRT
MPG Project
May 2001 -
Chris van Bruwaene, Lode Nachtergale, Bart Wouters, Werner Van Belle
The research project
is part of a transition toward a content-management system. This
content management system should be able to manage all new and old
media. This includes images, sound, text, graphics, games and
interactive scenario's...). The development of a content management
system implies a transition toward digital media. The MPG project is on
one track responsible for doing this conversion, in such a way that
releasing media on future communication channels (such as games via
television) is facilitated (IMEC). On a second track all this
media-content should be easily retrievable and automatically accessibly
throughout whole the corporation. Therefore research is being conducted
in component-based systems and ontologies (PROG). The total budget of
this project is 2'478'940 EUR.
Aanvraag IWT Specialisatiebeurs: Positie
Optimalisering in Mobile Multi-Agent Systems
September
1998, September 1999 - Werner Van Belle,
Wolfgang Demeuter, Theo D'Hondt
A research proposal
submitted to the institute for science and technology in Belgium. A
brand new programming paradigm is that of mobile software agents. One
is now able to move an agent from one machine to another
while its execution state remains intact. It is clear that
interaction between two agents on the same host is much faster than
the same interaction between agents on different hosts. Because of
this the performance of these systems can be finetuned by moving
agents to the same location if they are interacting enough. (This is
done of course while the system is running.) The only problem is the
unpredictability of the interaction patterns between the agents. For
this reason we can't make these systems run globally better than open
distributed systems. We can't predict that agent A should
always be near agent B in order to enhance
performance. In
this doctoral study we want to develop the necessary algorithms and
methodologies to automate the distribution of mobile agents, with the
main purpose of obtaining better global performance. The
methodology we will use consists of moving agents towards each other.
If agents interact on a local machine an after the interaction
retract to their original position it is possible to lower the
response time. This
will be done by an additional management layer to existing mobile
multi-agent systems. This extra will be able to reason about the
agents' positions at a different, higher level, while the agents
carry out their tasks. On this level we will develop some models to
describe the task execution of the agents (how they respond to
certain messages, what their standard behavior is and so on). It is
important to know that these models will only use local information.
After the agent models we will develop algorithms to fulfill our
Quest, that is, an automated higher global performance. To achieve
this we will look at genetic programming, subsymbolic statistic
techniques and learning techniques like reinforcement learning.
Object Gerichtheid en Message Passing in Wide
Area Networks - Mogelijke Agent Strategien
January
1997 & January 1998 - Werner Van Belle,
Wolfgang Demeuter
Submitted to the
belgium national fund for scientific research