Helsinki Institute for Information Technology

About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.

Relational link-based ranking

Abstract: Link analysis methods show that the interconnections between web pages have lots of valuable information. The link analysis methods are, however, inherently oriented towards analyzing binary relations. We consider the question of generalizing link analysis methods for analyzing relational databases. To this aim, we provide a generalized ranking framework and address its practical implications. More specically, we associate with each relational database and set of queries a unique weighted directed graph, which we call the database graph. We explore the properties of database graphs. In analogy to link analysis algorithms, which use the Web graph to rank web pages, we use the database graph to rank partial tuples. In this way we can, e.g., extend the PageRank link analysis algorithm to relational databases and give this extension a random querier interpretation. Similarly, we extend the HITS link analysis algorithm to relational databases. We conclude with some preliminary experimental results.

Practical power modeling of data transmission over 802.11g for wireless applications

Abstract: Previous studies have shown that a significant part of the overall energy consumption of battery-powered mobile devices is caused by network data transmission. Power models that describe the power consumption behavior of the network data transmission are therefore an essential tool in estimating the battery lifetime and in minimizing the energy usage of mobile devices. In this paper, we present a simple and practical power model for data transmission over an 802.11g WLAN and show its accuracy against physical data measured from three popular mobile platforms, Maemo, Android and Symbian. Our model estimates the energy usage based on the data transmission flow characteristics which are easily available on all the platforms without modifications to low-level software components or hardware. Based on our measurements and experimentation on real networks we conclude that our model is easy to apply and of adequate accuracy.

The Urbanet Revolution: Sensor Power to the People!

Abstract: With mobile devices becoming ubiquitous, the time is ripe to bring sensor data out of close-loop networks into the center of daily urban life The Internet has become a great success because its applications appeal to regular people This isn't the case with sensor networks, which are generally perceived as "something" remote in the forest or on the battlefield With few exceptions, first-generation sensor networks address application-specific, static-sensor deployments to accurately monitor the sensed environment in real time

A novel min-cost flow method for estimating transcript expression with RNA-Seq

Abstract: Through transcription and alternative splicing, a gene can be transcribed into different RNA sequences (isoforms), depending on the individual, on the tissue the cell is in, or in response to some stimuli. Recent RNA-Seq technology allows for new high-throughput ways for isoform identification and quantification based on short reads, and various methods have been put forward for this non-trivial problem. In this paper we propose a novel radically different method based on minimum-cost network flows. This has a two-fold advantage: on the one hand, it translates the problem as an established one in the field of network flows, which can be solved in polynomial time, with different existing solvers; on the other hand, it is general enough to encompass many of the previous proposals under the least sum of squares model. Our method works as follows: in order to find the transcripts which best explain, under a given fitness model, a splicing graph resulting from an RNA-Seq experiment, we find a min-cost flow in an offset flow network, under an equivalent cost model. Under very weak assumptions on the fitness model, the optimal flow can be computed in polynomial time. Parsimoniously splitting the flow back into few path transcripts can be done with any of the heuristics and approximations available from the theory of network flows. In the present implementation, we choose the simple strategy of repeatedly removing the heaviest path. We proposed a new very general method based on network flows for a multiassembly problem arising from isoform identification and quantification with RNA-Seq. Experimental results on prediction accuracy show that our method is very competitive with popular tools such as Cufflinks and IsoLasso. Our tool, called Traph (Transcrips in gRAPHs), is available at: http://www.cs.helsinki.fi/gsa/traph/ .

A shared document-based annotation tool to support learner-centred collaborative learning.

Abstract: A shared document-based annotation tool was presented, and its usefulness in two different real-life web-based university-level courses (adult learners, n= 27 and adolescent learners, n= 23) was empirically investigated. The study design embodied three data collection phases: (1) a pretest measuring self-rated motivation, learning strategies, and social ability; (2) log file data analysis showing actual use of the system features; and (3) a posttest in a form of an email survey. For both groups, the results showed that the level of motivation has a positive effect on activity in the system and the final grade. The learners, who reported to have good time-management strategies, were the most active users of the system. The level of social ability predicted both the number of consecutive comments in the documents and the threads in document-related newsgroup discussions. Log file data analysis showed that user activity in the system was positively related to the final grade in both samples. Results of the posttest showed that all the respondents agreed when asked: (1) if the system brought added value to the learning process; (2) if the use of the system changed their studying habits favourably; and (3) if they would like to use the system in other courses. [ABSTRACT FROM AUTHOR]