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 linear 3D piezoelasticity theory along with active damping control (ADC) strategy are applied for non-stationary vibroacoustic response suppression of a doubly fluid-loaded functionally graded piezolaminated (FGPM) composite hollow cylinder of infinite length under general time-varying excitations. The control gain parameters are identified and tuned using Genetic Algorithm (GA) with a multi-objective performance index that constrains the key elasto-acoustic system parameters and control voltage. The uncontrolled and controlled time response histories due to a pair of equal and opposite impulsive external point loads are calculated by means of Durbin’s numerical inverse Laplace transform algorithm. Numerical simulations demonstrate the superior (good) performance of the GA-optimized distributed active damping control system in effective attenuation of sound pressure transients radiated into the internal (external) acoustic space for two basic control configurations. Also, some interesting features of the transient fluid-structure interaction control problem are illustrated via proper 2D time domain images and animations of the 3D sound field. Limiting cases are considered and accuracy of the formulation is established with the aid of a commercial finite element package as well as comparisons with the current literature.
The process of cognitive aging in global sense can be characterised by changes of the fluid and crystallised intelligence. In the context of this explanation the basic question is which cognitive functions and regulatory mechanisms play the basic role of the determinants for cognitive aging. Probable, mechanism of associative memory play a central role in top-down direction of cognitive processing. This type of memory connect the resources/networks of long term memory with the current processing in working memory. Another set of mechanisms concerns with bottom-up direction based on procedural memory, which is fundamental for the functioning of the mind as whole (Tulving theory,1985). Unfortunately, our knowledge about associative memory and its relations to working and procedural memory is incomplete and unclear. The importance of associative memory are partly, empirically supported by classic research on decreasing the cognitive components of intelligence aging, since the fluid and crystallized intelligence where discovered (Horn, Cattell, 1967). Changes of the mind functioning and its cognitive growth/aging can be characterised as a complex chain from primary, biologically determined mind, through Piagetian and Vygotsky’s type of mind to relatively balanced mind.
The aim of the study was to investigate the relationships between emotional intelligence (EI) and temperament. It was assumed that the two main components of EI – experiential and strategic – have different temperament correlates. One hundred and four Polish university students aged 19 to 26 completed self-descriptive questionnaires of temperament and emotional intelligence. The results confirmed that the relationship with temperament depends on the examined component of EI. Acceptance of emotions (which is a subcomponent of experiential EI) only correlated with two temperamental traits – activity and briskness. Many more dependencies were found in relation to strategic EI. Endurance, strength of inhibition, sensory sensitivity and perseveration turned out to be significant predictors of emotional control, which jointly explained 44% of the variance in results, while perseveration and sensory sensitivity explained 28% of the variance in results on the understanding emotions scale. Based on the results obtained, it can be assumed that the configuration of temperament traits that determines a high capacity for processing stimulation is most conductive to strategic EI. Other propitious traits include those that determine the speed of neural processes, flexibility and ease of adaptation to changing conditions as well as a low sensitivity threshold to sensory stimulus.
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.