Helsinki University of Technology

About: Helsinki University of Technology is a based out in . It is known for research contribution in the topics: Artificial neural network & Finite element method. The organization has 8962 authors who have published 20136 publications receiving 723787 citations. The organization is also known as: TKK & Teknillinen korkeakoulu.

Unsupervised models for morpheme segmentation and morphology learning

Abstract: We present a model family called Morfessor for the unsupervised induction of a simple morphology from raw text data. The model is formulated in a probabilistic maximum a posteriori framework. Morfessor can handle highly inflecting and compounding languages where words can consist of lengthy sequences of morphemes. A lexicon of word segments, called morphs, is induced from the data. The lexicon stores information about both the usage and form of the morphs. Several instances of the model are evaluated quantitatively in a morpheme segmentation task on different sized sets of Finnish as well as English data. Morfessor is shown to perform very well compared to a widely known benchmark algorithm, in particular on Finnish data.

Quantized vortices in superfluid He-3

Abstract: The first measurements on vortices in rotating superfluid $^{3}\mathrm{He}$ have been conducted in the Low Temperature Laboratory at Helsinki University of Technology during the past five years. These experiments have revealed unique vortex phenomena that are not observed in any other known superfluids. In this review, the concept of broken symmetry is applied to investigate the quantized vortex lines in superfluid $^{3}\mathrm{He}$. In the superfluid $A$ phase, vorticity can be supported by a continuous winding of the order parameter; this gives rise to continuous "coreless" vortices with two flow quanta. Novel vortices with a half-integer number of circulation quanta may also exist in $^{3}\mathrm{He}$-$A$ due to a combined symmetry of the superfluid state. In the superfluid $B$ phase, the vortices have a complicated core structure. The vortex-core matter is ferromagnetic and superfluid, and it displays broken parity. The ferromagnetism of the core is observed in NMR experiments due to a gyromagnetic effect. The calculated core structures exhibit an experimentally observed first-order phase transition. This vortex-core transition in rotating $^{3}\mathrm{He}$-$B$ may be understood in terms of a change in the topology for flaring-out of the vortex singularity into higher dimensions; the topological identification further suggests that the phase transition manifests a spontaneous bifurcation of vorticity---involving half-quantum vortices in $^{3}\mathrm{He}$-$B$. These recent advances of interest in quantum liquids are also of general relevance to a wide range of fields beyond low-temperature physics.

Methodology for Combined TMS and EEG

Abstract: The combination of transcranial magnetic stimulation (TMS) with simultaneous electroencephalography (EEG) provides us the possibility to non-invasively probe the brain’s excitability, time-resolved connectivity and instantaneous state. Early attempts to combine TMS and EEG suffered from the huge electromagnetic artifacts seen in EEG as a result of the electric field induced by the stimulus pulses. To deal with this problem, TMS-compatible EEG systems have been developed. However, even with amplifiers that are either immune to or recover quickly from the pulse, great challenges remain. Artifacts may arise from the movement of electrodes, from muscles activated by the pulse, from eye movements, from electrode polarization, or from brain responses evoked by the coil click. With careful precautions, many of these problems can be avoided. The remaining artifacts can be usually reduced by filtering, but control experiments are often needed to make sure that the measured signals actually originate in the brain. Several studies have shown the power of TMS–EEG by giving us valuable information about the excitability or connectivity of the brain.

Density-functional study of bulk and surface properties of titanium nitride using different exchange-correlation functionals

Abstract: The adsorption and diffusion of hydrogen on the (100) surface of titanium nitride was studied using density-functional theory (DFT) and the generalized gradient approximation (GGA) for the exchange and correlation energy. The adsorption site was found to be on top of the titanium atom with the chemisorption energy of -2.88 eV. The diffusion barrier was determined as 0.73 eV along the path connecting the neighboring titanium atoms. The surface energies and surface relaxations of the three most important surfaces of TiN were studied. The surface energies have the following order: ${S}_{100}l{S}_{110}l{S}_{111}.$ Three different GGA functionals, the Perdew-Wang 1991 (PW91), the Perdew-Burke-Ernzerhof (PBE), and the revised PBE (RPBE) functionals, were tested on crystals, small molecules and TiN surfaces. The RPBE functional when applied to the surface studies of TiN was found to produce slightly lower values of surface energies and of hydrogen adsorption energies than the PW91 functional.