Turku Centre for Computer Science

About: Turku Centre for Computer Science is a facility organization based out in Turku, Finland. It is known for research contribution in the topics: Decidability & Word (group theory). The organization has 382 authors who have published 1027 publications receiving 19560 citations.

Conditional ranking on relational data

Abstract: In domains like bioinformatics, information retrieval and social network analysis, one can find learning tasks where the goal consists of inferring a ranking of objects, conditioned on a particular target object. We present a general kernel framework for learning conditional rankings from various types of relational data, where rankings can be conditioned on unseen data objects. Conditional ranking from symmetric or reciprocal relations can in this framework be treated as two important special cases. Furthermore, we propose an efficient algorithm for conditional ranking by optimizing a squared ranking loss function. Experiments on synthetic and real-world data illustrate that such an approach delivers state-of-the-art performance in terms of predictive power and computational complexity. Moreover, we also show empirically that incorporating domain knowledge in the model about the underlying relations can improve the generalization performance.

Undecidability of the state complexity of composed regular operations

Abstract: We consider the regularity-preserving operations of intersection and marked catenation and construct an infinite sequence Ci, i = 1, 2, . . ., of compositions formed from the two operations. We construct also an infinite sequence of polynomials Si, i = 1, 2, . . ., with positive integer coefficients. As a main result we prove that it is undecidable whether or not Si is a state complexity function of Ci. All languages needed are over a fixed alphabet with at most 50 letters. We also consider some implications and generalizations, as well as present some open problems.

An energy consumption model for an embedded java virtual machine

Abstract: In this paper we establish a general framework for estimating the energy consumption of an embedded Java virtual machine (JVM). We have designed a number of experiments to find the constant overhead of the Virtual Machine and establish an energy consumption cost for individual Java Opcodes. The results show that there is a basic constant overhead for every Java program, and that a subset of Java opcodes have an almost constant energy cost. We also show that memory access is a crucial energy consumption component.

Visual monitoring of financial stability with a self-organizing neural network

Abstract: Since the outset of the deregulation of international financial markets in the 1980s, the frequency of currency crises has increased. Solely in the 1990s, five global storms of financial turmoil, also including collapses of the currency, have occurred. To date, crisis forecasting and monitoring of financial stability is still at a preliminary stage. This paper explores whether the application of the Self-Organizing Map (SOM), a neural network-based visualization tool, facilitates the monitoring of multidimensional economic data. The paper presents a visualization of both the evolution of economic indicators over time and of benchmarking countries, on a given point in time, as to their vulnerability for an imminent crisis. The results of this paper indicate that the SOM is a feasible tool for dynamic visualization of currency crises' early warning signals.

Life cycle assessment of printed antenna: Comparative analysis and environmental impacts evaluation

Abstract: THIS paper presents cradle to grave life cycle assessment of printed electronics resources. In this work, an attempt has been made to investigate and evaluate the life cycle assessment and environmental impacts of printed electronics resources such as polymer substrate-printed RFID antenna. Life cycle inventory analysis for these resources has been carried out to quantify total systems' inputs and outputs that are relevant to the environmental impacts especially emissions to air, fresh water, industrial soil and sea water.