A Grid-Based Algorithm for On-Device GSM Positioning

Lecturer : 
Petteri Nurmi
Event type: 
HIIT seminar
Event time: 
2010-11-05 10:15 to 11:00
Place: 
Exactum C222
Description: 

ABSTRACT:
The talk introduces a grid-based GSM positioning algorithm that can be deployed entirely on mobile devices. The algorithm uses Gaussian distributions to model signal intensity variations within each grid cell. Position estimates are calculated by combining a probabilistic centroid algorithm with particle filtering. In addition to presenting the positioning algorithm, we describe methods that can be used to create, update and maintain radio maps on a mobile device. We have implemented the positioning algorithm on Nokia S60 and Nokia N900 devices and we evaluate the algorithm using a combination of offline and real world tests. The results indicate that the accuracy of our method is comparable to state-of-the-art methods, while at the same time having significantly smaller storage requirements.

Inverse problems and Bayesian tracking: An application to neurophysiological data

Lecturer : 
Cristina Campi
Event type: 
HIIT seminar
Event time: 
2010-11-12 10:15 to 11:00
Place: 
Exactum C222
Description: 

ABSTRACT:
As a first issue, during this talk I will discuss the framework of inverse problems: what they are, why they are difficult to solve and what are the possible strategies for solving them. Then I will focus on Bayesian tracking as a statistical inversion method for solving dynamical inverse problems. As a final step, I will present some results obtained applying a Bayesian Tracking algorithm to real data recorded using Magnetoencephalography.

BIO:
I am a postdoctoral researcher in the Neuroinformatics research group. I received my PhD in Mathematics and Application from the University of Genova, Italy on April 2010. I spent six months as postdoc at the Department of Mathematics, University of Genova. During my PhD I dealt with the study of the solution of inverse problems for infering information about the brain activity from neurophysiological data.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Event type: 
Doctoral dissertation
Doctoral dissertation
Respondent: 
Esa Pitkänen
Opponent: 
professor Jacques van Helden
Custos: 
professor Esko Ukkonen
Event time: 
2010-11-12 12:00 to 14:00
Place: 
Main building, auditorium XII
Description: 

Esa Pitkänen will defend his thesis "Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks" on 12 Nov 2010 at 12 noon in the Main building, auditorium XII. His opponent is Professor Jacques van Helden (Université Libre de Bruxelles, Belgia) and custos Professor Esko Ukkonen.

Abstract:

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism.

In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae.

In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis.

In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Time-Consistency Problem in the Long Term Decision Making

Lecturer : 
Professor Leon Petrosjan
Event type: 
Guest lecture
Event time: 
2010-11-18 12:00 to 14:00
Place: 
Kumpula (room C222)

Multi-user resource-sharing problem for the Internet

Event type: 
Doctoral dissertation
Doctoral dissertation
Respondent: 
Andrey Lukyanenko
Opponent: 
Professor Leon Petorsjan
Custos: 
Professor Jussi Kangasharju
Event time: 
2010-11-17 12:00 to 14:00
Place: 
University of Helsinki, Prothania campus (Yliopistonkatu 3), PIII auditorium
Description: 

Andrey Lukyanenko will defend his thesis "Multi-user resource-sharing problem for the Internet" on 17 November at 12:00 in Porthanian, auditorium PIII. His opponent is Professor Leon Petorsjan and custos Professor Jussi Kangasharju.  The thesis is available at the link above.

Popular abstract:

In this thesis we study a series of multi-user resource-sharing problems for the Internet, which involve distribution of a common resource among participants of multi-user systems (servers or networks). We study concurrently accessible resources, which for end-users may be exclusively accessible or non-exclusively. For all kinds we suggest a separate algorithm or a modification of common reputation scheme. Every algorithm or method is studied from different perspectives: optimality of protocols, selfishness of end users, fairness of the protocol for end users. On the one hand the multifaceted analysis allows us to select the most suited protocols among a set of various available ones based on trade-offs of optima criteria. On the other hand, the future Internet predictions dictate new rules for the optimality we should take into account and new properties of the networks that cannot be neglected anymore.

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