Tampere University of Technology

About: Tampere University of Technology is a based out in . It is known for research contribution in the topics: Laser & Context (language use). The organization has 6802 authors who have published 19787 publications receiving 431793 citations. The organization is also known as: Tampereen teknillinen yliopisto.

Computational auditory scene recognition

Abstract: In this paper, we address the problem of computational auditory scene recognition and describe methods to classify auditory scenes into predefined classes. By auditory scene recognition we mean recognition of an environment using audio information only. The auditory scenes comprised tens of everyday outside and inside environments, such as streets, restaurants, offices, family homes, and cars. Two completely different but almost equally effective classification systems were used: band-energy ratio features with 1-NN classifier and Mel-frequency cepstral coefficients with Gaussian mixture models. The best obtained recognition rate for 17 different scenes out of 26 and for an analysis duration of 30 seconds was 68.4%. For comparison, the recognition accuracy of humans was 70% for 25 different scenes and the average response time was around 20 seconds. The efficiency of different acoustic features and the effect of test sequence length were studied.

Comparison of entropy and complexity measures for the assessment of depth of sedation

Abstract: Entropy and complexity of the electroencephalogram (EEG) have recently been proposed as measures of depth of anesthesia and sedation. Using surrogate data of predefined spectrum and probability distribution we show that the various algorithms used for the calculation of entropy and complexity actually measure different properties of the signal. The tested methods, Shannon entropy (ShEn), spectral entropy, approximate entropy (ApEn), Lempel-Ziv complexity (LZC), and Higuchi fractal dimension (HFD) are then applied to the EEG signal recorded during sedation in the intensive care unit (ICU). It is shown that the applied measures behave in a different manner when compared to clinical depth of sedation score the Ramsay score. ShEn tends to increase while the other tested measures decrease with deepening sedation. ApEn, LZC, and HFD are highly sensitive to the presence of high-frequency components in the EEG signal.

Developing a computer science-specific learning taxonomy

Abstract: Bloom's taxonomy of the cognitive domain and the SOLO taxonomy are being increasingly widely used in the design and assessment of courses, but there are some drawbacks to their use in computer science. This paper reviews the literature on educational taxonomies and their use in computer science education, identifies some of the problems that arise, proposes a new taxonomy and discusses how this can be used in application-oriented courses such as programming.

Kohn-Sham potential with discontinuity for band gap materials

Abstract: We model a Kohn-Sham potential with the discontinuity at integer particle numbers starting from the approximation by (GLLB) Gritsenko et al. [Phys. Rev. A 51, 1944 (1995)]. We evaluate the Kohn-Sham gap and the discontinuity to obtain the quasiparticle gap. This allows us to compare the Kohn-Sham gaps to those obtained by accurate many-body perturbation-theory-based optimized potential methods. In addition, the resulting quasiparticle band gap is compared to experimental gaps. In the GLLB model potential, the exchange-correlation hole is modeled using a generalized gradient approximation (GGA) energy density and the response of the hole-to-density variations is evaluated by using the common-denominator approximation and homogeneous electron-gas-based assumptions. In our modification, we have chosen the PBEsol potential as the GGA to model the exchange hole and add a consistent correlation potential. The method is implemented in the GPAW code, which allows efficient parallelization to study large systems. A fair agreement for Kohn-Sham and the quasiparticle band gaps with semiconductors and other band gap materials is obtained with a potential which is as fast as GGA to calculate.