The assessment of pedophilic sexual preferences is an important part of forensic and research practice. Standardization of methods and stimuli used across sites is missing, making data transferability and comparability more difficult. The aim of this study was to investigate if the stimuli used in the USA and Canada are able to reliably distinguish between pedophilic and control subjects in the Czech Republic, based on their elicited sexual arousal. A stimuli set was first translated into Czech and voice recordings were created for the narratives. Sexual arousal was measured using circumferential penile plethysmography. 29 pedophilic (15 heterosexual; 14 homosexual) and 26 control (12 heterosexual; 12 homosexual) participants took part in the study. The sample comprised mostly non- delinquent individuals. The results revealed a significant difference in the subjective sexual arousal ratings as well as sexual reactivity between pedophiles and control participants in response to both child and adult stimulus categories. Correlation analysis revealed a significant positive relationship between subjective ratings and sexual reactivity to both child and adult stimulus categories. The results indicate that the audio recordings are a suitable tool to distinguish between pedophiles and controls. The...

The thesis is focused on the design and implementation of the portable stimulus verification scenarios for selected Berkelium processor modules based on RISC-V architecture from Codasip. The aim of this work is to use new standard for Portable Stimulus developed by Accellera organization to design and implement portable stimulus scenarios using the Questa InFact tool from Mentor. The proposed portable stimulus scenarios are then linked to the already existing verification environments of the UVM methodology and then they are used for verification of the Berkelium processor modules based on RISC-V architecture. The last part of the thesis is the evaluation of portability of the implemented scenarios to the individual levels of the Berkelium processor based on RISC-V architecture (IP blocks, subsystems, system level), in which it tries to use the proposed scenarios across all verificated levels.

The diploma thesis deal with what ways drivers react to an unexpected stimulus. In the theoretical part, the analysis of the current state, reaction time, methods of reaction of the driver, stimuli from the environment and finally is being analyzed, the vehicle and its assistance systems. The analytical part of the diploma thesis was performed by driving tests, where it was found that the way the driver reacts from the distance to which they are obstructed and the speed of the vehicle. For that reason, a TTC dependency analysis was performed. It was found that drivers at low TTC values chose an obstacle in which they brake the need to move their foot from the accelerator pedal to the brake pedal and they have to brake sharply. At medium TTC values, drivers brake most often. In the case of a combination of conductors, they chose braking with avoiding at lower TTC values and avoiding with braking at medium TTC values. There was also a dependence of the method of reaction on driving experience. Inexperienced drivers rather choose braking, experienced drivers use combinations.

Recombinative generalization is a generative outcome that involves responding to novel stimulus combinations, and it can be facilitated through an instructional approach called matrix training. A learner's history with constituent stimuli and the arrangement of combination stimuli within the instructional matrix may affect the likelihood of recombinative generalization. To investigate this further, the current project assessed recombinative generalization with novel combinations of abstract stimuli by programming specific training histories for undergraduate student participants. The matrix training conditions were: (a) trained constituents with overlap training, (b) untrained constituents with overlap training, (c) trained constituents with nonoverlap training, and (d) untrained constituents with nonoverlap training. We evaluated whether and the extent to which recombinative generalization occurred in each matrix training condition in comparison to a condition that included training the constituents and providing a word-order rule. Finally, we compared the training trials in experimental conditions to directly training all constituents and combinations. The results suggested both overlap conditions and the trained constituents with nonoverlap condition produced recombinative generalization, and the trained constituents with nonoverlap condition was the most efficient. These results could inform the training order and stimulus arrangements practitioners employ to program for recombinative generalization.

Ten developmentally disabled children participated in an assessment of stimulus control and transfer of training. Each subject was taught to perform a simple, nonverbal, imitative task in a training room, and transfer to a novel setting was assessed. During training, subjects were video-taped in order to determine how often each visual stimulus in the training room was looked at. After an initial transfer t est each subject participated in a test of the stimulus control acquired by visual stimuli from the training room. Utilizing two groups (N = 5 each), subjects received an additional transfer test in the novel setting while in the presence of a stimulus that had been either frequently or infrequently looked at during the training process. Subjects tested in the presence of a frequently-looked-at stimulus produced a greater number of correct responses during the transfer tests than subjects tested in the presence of an infrequently-looked-at stimulus. Individual data are also presented fer the subjects. The implications of these results are discussed.

Thesis deal with motivation employees in Česká pojišťovna. On the basis bring out is analysed present circumstances in company, intended troubleshooting areas and designed procuration on improvement.

The thesis aims to enhance the performance of NH Glass Company, Ltd., through an innovative incentive program. The above company has been in the glass industry. The theoretical part is describing the nature and content of motivation and motivational theories. The practical part includes the evaluation of survey results on the basis of the suggested possible improvements to the current incentive system in a selected company. This proposal will help to improve and enhance employee performance.

This thesis focuses on the issues of motivation and stimulation of employees in company Gala Prostejov, and the goal is to evaluate current motivation system in the company and propose recommendations that will help to increase work motivation of employees, and also their satisfaction. The theoretical part describes the basic concepts associated with employee motivation. The practical part analyzes the current situation of the company, its evaluation and proposal of recommendations for improvement.

The purpose of this study was to determine the prevalence of the binaural interaction component (BIC) in a large sample of normal hearing adults, and to measure the absolute latency and amplitude of the BIC as a function of the click rate of the stimulus and the electrode montage. The BIC is obtained by subtracting the auditory evoked potential waveform obtained with binaural stimulation from the waveform obtained by adding the responses from the left and right monaural stimulation. The tested hypothesis was that the recordings of the BIC vary among normal hearing individuals, and BIC latency and amplitude values change as a function of stimulus rate. Studies of the BIC help to explain the neural correlates of some binaural processes, and to develop an electrophysiological index of binaural processes for objective clinical evaluations. Data was completed and analyzed on 47 adults between the ages of 20 and 41 (mean = 25) with hearing in the normal range (thresholds less than or equal to 20 dB HL at 500, 1000, 2000, and 4000 Hz in each ear) and no known neurological disorders. The results revealed a great variability in BIC morphology between subjects. The BIC waveforms were categorized into five distinct groups according to the number of positive and negative peaks present. Chi-square analyses revealed a significant relationship between click rate and BIC category; however, the relationship between recording montage and BIC category was insignificant. An Analysis of Variance (ANOVAs) revealed a significant increase in absolute latency and decrease in absolute amplitude of both negative and positive peaks as click rate increased from 7.7/s to 57.7/s. The results did not reveal a significant change in the type of BIC as an effect of electrode montage. In conclusion, the BIC within the binaural difference waveform may be obtained in the majority of young individuals with normal hearing. Specifically, a slower stimulus rate revealed more components of the waveform, as well as an improvement in the morphology of the BIC compared to a faster stimulus rate. As these findings may aid in the development of an electrophysiological index of binaural neural processes in young individuals with normal hearing, more research should be attempted in the study of BIC in other age groups and patients with different audiograms.

Objectives: Development of accurate auditory attention decoding (AAD) algorithms, capable of identifying the attended sound source from the speech evoked electroencephalography (EEG) responses, could lead to new solutions for hearing impaired listeners: neuro-steered hearing aids. Many of the existing AAD algorithms are either inaccurate or very slow. Therefore, there is a need to develop new EEG-based AAD methods. The first objective of this project was to investigate deep neural network (DNN) models for AAD and compare them to the state-of-the-art linear models. The second objective was to investigate whether generative adversarial networks (GANs) could be used for speech-evoked EEGdata augmentation to improve the AAD performance. Design: The proposed methods were tested in a dataset of 34 participants who performed an auditory attention task. They were instructed to attend to one of the two talkers in the front and ignore the talker on the other side and back-ground noise behind them, while high density EEG was recorded. Main Results: The linear models had an average attended vs ignored speech classification accuracy of 95.87% and 50% for ∼30 second and 8 seconds long time windows, respectively. A DNN model designed for AAD resulted in an average classification accuracy of 82.32% and 58.03% for ∼30 second and 8 seconds long time windows, respectively, when trained only on the real EEG data. The results show that GANs generated relatively realistic speech-evoked EEG signals. A DNN trained with GAN-generated data resulted in an average accuracy 90.25% for 8 seconds long time windows. On shorter trials the GAN-generated EEG data have shown to significantly improve classification performances, when compared to models only trained on real EEG data. Conclusion: The results suggest that DNN models can outperform linear models in AAD tasks, and that GAN-based EEG data augmentation can be used to further improve DNN performance. These results extend prior work and brings us closer to the use of EEG for decoding auditory attention in next-generation neuro-steered hearing aids.