Prof. Edward Nęcka, a cognitive psychologist from the Jagiellonian University and Vice-President of the Polish Academy of Sciences, talks about cognitive misers, memory traps, and confusion in a myriad of new technologies.
The church of Santa Cruz de Oleiros, Spain (1967) shows architect Miguel Fisac’s perception of sacred space after the Second Vatican Council. In this place of worship, the architect responded to the new liturgical guidelines combining geometry and architectural forms with the material of the moment, concrete. However, ordinary religious celebrations reveal acoustic deficiencies for the main use of the building. This fact is corroborated by acoustic measurements in situ. With a methodology that uses simulation techniques for the sound field, the analysis of the current acoustic behaviour of the room will serve as the basis for an acoustic rehabilitation proposal aimed at improving the acoustic conditions and so, the functionality of the church.
The author analyses problems of disease, dying, and death addressed in a play by Margaret Edson entitled Wit. Special attention is paid to the structure of meta-theatre and the function of wit in the play. The author investigates limitations of reason in the approach adopted by the doctors who take care of Vivian Bearing, and who subject her to an excruciating experiment in order to achieve a potential research success. She also discusses the protagonist’s attitude to literary works, dealing with her own disease, to other people and to God. This offers an opportunity to ruminate on the exact meaning of irretrievable loss involved in suffering. She also concentrates on the attitude of the nurse who – thanks to her emotional intelligence and empathy – accompanies Vivian on her way to death.
The aim of the present study was to explore the role of temporal intelligence in English as a Foreign Language (EFL) learners’ self-regulation and self-efficacy. To this end, a general temporal intelligence (GTI-S) scale was designed based on the subconstructs of time in the literature. The scale, along with the learning self-regulation questionnaire (SRQ-L) and the English self-efficacy scale was administered to 520 EFL learners. To validate the GTI-S, confirmatory factor analysis (CFA) was run. The results of Pearson product-moment correlations demonstrated significantly positive relationships between temporal intelligence and controlled self-regulation, automatic self-regulation and self-efficacy (p<.05). Moreover, the findings of multiple regressions revealed that Linearity of Time, Economicity of Time, and Multitasking are the most important subconstructs of time with relation to these variables.
Speech enhancement is fundamental for various real time speech applications and it is a challenging task in the case of a single channel because practically only one data channel is available. We have proposed a supervised single channel speech enhancement algorithm in this paper based on a deep neural network (DNN) and less aggressive Wiener filtering as additional DNN layer. During the training stage the network learns and predicts the magnitude spectrums of the clean and noise signals from input noisy speech acoustic features. Relative spectral transform-perceptual linear prediction (RASTA-PLP) is used in the proposed method to extract the acoustic features at the frame level. Autoregressive moving average (ARMA) filter is applied to smooth the temporal curves of extracted features. The trained network predicts the coefficients to construct a ratio mask based on mean square error (MSE) objective cost function. The less aggressive Wiener filter is placed as an additional layer on the top of a DNN to produce an enhanced magnitude spectrum. Finally, the noisy speech phase is used to reconstruct the enhanced speech. The experimental results demonstrate that the proposed DNN framework with less aggressive Wiener filtering outperforms the competing speech enhancement methods in terms of the speech quality and intelligibility.