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.

Color Blind Cellular Automata

Abstract: We introduce the classes of color blind and typhlotic cellular automata, that is, cellular automata that commute with all symbol permutations and all symbol mappings, respectively. We show that color blind cellular automata form a relatively large subclass of all cellular automata which contains an intrinsically universal automaton. On the other hand, we give simple characterizations for the color blind CA which are also group homomorphisms, and for general typhlotic CA, showing that both must be trivial in most cases.

Comparison of DVB-H Link Layer FEC Decoding Strategies in a Mobile Fading Channel

Abstract: DVB-H offers reliable high data rate reception for mobile handheld and battery-powered devices. A link layer with error correction is defined to work on top of the DVB-T physical layer. The DVB-H standard suggests to use Reed-Solomon coding combined with cyclic redundancy check error detection as the link layer forward error correction. However, there exist more powerful methods for decoding. In this paper, a detailed comparison of five different decoding strategies is presented of which all are compatible with the current standard. Comparison is based on frame error, IP packet error and byte error rates after decoding. Also, the effect of errors on visual experience of a video stream is analyzed.

Job scheduling and management of wearing tools with stochastic tool lifetimes

Abstract: The problem of scheduling jobs using wearing tools is studied. Tool wearing is assumed to be stochastic and the jobs are processed in one machining centre provided with a limited capacity tool magazine. The aim is to minimize the expected average completion time of the jobs by choosing their processing order and tool management decisions wisely. All jobs are available at the beginning of the planning period. This kind of situation is met in production planning of CNC-machines. Previous studies concerning this problem have either assumed deterministic wearing for the tools or omitted the wearing completely. In our formulation of the problem, tool wearing is stochastic and the problem becomes very hard to solve analytically. A heuristic based on genetic algorithms is therefore given for the joint problem of job scheduling and tool management. The algorithm searches the most beneficial job sequence when the tool management decisions are made by a removal rule taking into account the future planned usage of the tools. The cost of each job sequence is evaluated by simulating the job processing. Empirical tests with heuristics indicate that by taking the stochastic information into account, one can reduce the average job processing time considerably.