A detailed geomorphological mapping was performed in the valley of the Losenice R., which is situated on the NE slopes of the Šumava Mts. nearby the Kašperské Hory town. The dominant characteristics of the studied area are steep slopes of the deeply incised, narrow valleys, strong fragmentation of the bedrock composed of various types of gneisses and obvious structural influence on the valley network plan. Based on the analysis of the occurrence, parameters and relative position of selected landforms, which have significance for documenting certain processes, as well as other inputs, the relief of the studied area was divided into eight genetic types of relief segments: structural, erosional, erosional-structural, structuraldenudational and erosional-denudational slopes, flat denudational ridges and planation surface remnants and finally the valley floors with the floodplain., Filip Hartvich and Vít Vilímek., and Obsahuje bibliografii
The voice communicaton between technological devices and the operator becomes a stronger challenge as technology becomes more advanced and complex. New applicatons of artificial neural networks are capable of recognition and verification of effects and safety of commands given by the operator of the technological device. In this paper there is a review of the selected issues on estimation of results and safety of the operator‘s commands as well as supervision of the technological process. A view is offered of the complexity of effect analysis and safety assessment of commands given by the operator using neural networks. There is also an intelligent two-way voice communication system between the technological device and the operator presented, which consists of the intelligent mechanisms of operator identification, word and command recognition, command syntax and result analysis, command safety assessment, technological process supervision as well as operator reaction assessment. The first part of the paper introduces a new concept of modern supervising system of the technological process using and intelligent layer of two-way voice communication between the technical device and the operator and discusses the general topics and issues. The second part is devoted to a discussion of more specific topics of the automatic command verification that have led to interesting new approaches and techniques. and Obsahuje seznam literatury
This paper introduces a new sensitivity analysis method using nonsupervised neural nets, based on the Adaptive Resonance Theory (ART).This new method introduces the possibility of a sensitivity analysis being adaptive and being conducted at the saine tirne as net learning is taking place, taking advantage of the property of continuous (as opposed to phase-wise) learning of ART models. A sensitivity analysis can be conducted likewise, i.e. continuous by and capably adapting to any new relationships appearing among the input data. The method has been validated in the field of feature detection for iniage classification and, more specifically, for face recognition.
The core of the expert knowledge is typically represented by a set of rules (implications) assigned with weights specifying their (un)certainties. In the paper, a method for hierarchical selection and correction of expert's weighted rules is described particularly in the case when Łukasiewicz's fuzzy logic with evaluated syntax for dealing with weights is used.
The study of ischemia/reperfusion injury included 25 patients in the acute phase of myocardial infarction (19 perfused, 6 remained non-reperfused as evaluated according to the time course of creatine kinase and CK-MB isoenzyme activity) and a control group (21 blood donors). Plasma level of malondialdehyde was followed as a marker of oxidative stress. Shortly after reperfusion (within 90 min), a transient increase of malondialdehyde concentration was detected. The return to the baseline level was achieved 6 h after the onset of therapy. The activity of a free radical scavenger enzyme, plasma glutathione peroxidase (GPx), reached its maximum 90 min after the onset of treatment and returned to the initial value after 18 h. The specificity of the GPx response was confirmed by comparing with both non-reperfused patients and the control group, where no significant increase was detected. The erythrocyte Cu,Zn-superoxide dismutase (SOD) did not exhibit significant changes during the interval studied in perfused patients, probably due to the stability of erythrocyte metabolism. In non-reperfused patients, a decrease of SOD was found during prolonged hypoxia. These results help to elucidate the mechanisms of fast activation of plasma antioxidant system during the reperfusion after myocardial infarction., V. Mužáková, R. Kanďár, P. Vojtíšek, J. Skalický, Z. Červinková., and Obsahuje bibliografii
Tracking moving objects is a vital visual task for the survival of an animal. We describe oscillatory neural network models of visual attention with a central element that can track a moving target among a set of distracters on the screen. At the initial stage, the model forms the focus of attention on an arbitrary object that is considered as a target. Other objects are treated as distracters. We present here two models: 1) synchronisation based model designed as a network of phase oscillators and 2) spiking neural model which is based on the idea of resource-limited parallel visual pointers. Selective attention and the tracking process are represented by the partial synchronisation between the central unit and a subgroup of peripheral elements. Simulation results are in overall agreement with the findings from psychological experiments: overlapping between the target and distractors is the main source of errors.
Meconium aspiration syndrome (MAS) in newborns is characterized mainly by respiratory failure due to surfactant dysfunction and inflammation. Previous meta-analyses did not prove any effect of exogenous surfactant treatment nor glucocorticoid administration on final outcome of children with MAS despite oxygenation improvement. As we supposed there is the need to intervene in both these fields simultaneously, we evaluated therapeutic effect of combination of exogenous surfactant and selective inhibitor of NF-κB (IKK-NBD peptide). Young New Zealand rabbits were instilled by meconium suspension and treated by surfactant alone or surfactant in combination with IKK-NBD, and oxygen-ventilated for 5 h. PaO2/FiO2, oxygenation index, oxygen saturation and ventilation efficiency index were evaluated every hour; post mortem, total and differential leukocyte counts were investigated in bronchoalveolar lavage fluid (BALF) and inflammatory, oxidative and apoptotic markers were assessed in lung tissue homogenates. Exogenous surfactant combined with IKK-NBD improved oxygenation, reduced neutrophil count in BALF and levels of IL-1β, IL-6, p38 MAPK and caspase 3 in comparison with surfactant-only therapy. It seems that inhibition of inflammation may be strong supporting factor in surfactant treatment of MAS., J. Kopincova, P. Mikolka, M. Kolomaznik, P. Kosutova, A. Calkovska, D. Mokra., and Obsahuje bibliografii
The architecture and working of the Artificial Neural Networks are an inspiration from the human brain. The brain due to its highly parallel nature and immense computational powers still remains the motivation for researchers. A single system-single processor approach is a highly unlikely way to model a neural network for large computational needs. Many approaches have been proposed that adopt a parallel implementation of ANNs. These methods do not consider the difference in processing powers of the constituting units and hence workload distribution among the nodes is not optimal. Human brain not always has equal processing power among the neurons. A person having disability in some part of brain may be able to perform every task with reduced capabilities. Disabilities weaken the processing of some parts. This inspires us to make a self-adaptive system of ANN that would optimally distribute computation among the nodes. The self-adaptive nature of the algorithm makes it possible for the algorithm to taper dynamic changes in node performance. We used data, node and layer partitioning in a hierarchical manner in order to evolve the most optimal architecture comprising of the best features of these partitioning techniques. The adaptive hierarchical architecture enables performance optimisation in whatever condition and problem the algorithm is used. The system was implemented and tested on 20 systems working in parallel. Besides, the computational speed-up, the algorithm was able to monitor changes in performance and adapt accordingly.
The presented study evolved from authors considerations devoted to expected crediabiity of results obtained by finite element methods especially in cases when comparisons with those of experiment are not available. Thus, assessing the validity of numerical results one has to rely on the employed method of the solution itself. Out of many situations which might be of importance, we paid our attention to comparison of results obtaned by different element types, two different time integration operators, mesh refinements and finally to frequency analysis of the loading pulse and that of output signals expressed in displacements and strains obtained by solving a well defined transient task in solid continuum mechanics. Statistical tools for the quantitative assessment of 'close' solutions are discussed as well. and Obsahuje seznam literatury