Dírkonošci (Foraminifera), mořští prvoci s vápenatou schránkou, obývají naši planetu více než půl miliardy let. Zkoumáním způsobu života těch současných se mnohé dozvíme o jejich pravěkých předcích i o dávných mořích, ve kterých žili., Foraminifera - a rich group of mainly marine microorganisms - are widely used for paleoecological reconstructions. Their occurrence provides important data about past ecological conditions of the sites. We reconstructed former conditions in Židlochovice research site (southern Moravia) by comparing fossil communities with the recent ones present on the island of Rab (Adriatic Sea)., and Anna Poštulková.
To build a general model for the propagation of destructive events during disasters, we consider a networked system. The model involves network nodes as single objects and delayed interactions along directed links.
In this work, a disaster is understood as a sequence of dynamic destructive events which cause nonreversible changes, spreading in cascade-like manner. We define a global state of the system and suppose that the Markovian property holds. Hence, we can describe any object‘s first affect using the phase type distribution. This model can be used to improve disaster awareness and anticipated disaster response management. and Obsahuje seznam literatury
This paper is concerned with the determination of the relationship for the calculation of the discharge coefficient at free overflow over a rectangular sharp-edged broad-crested weir without lateral contraction. The determination was made on the basis of new measurement in a range of the relative thickness of the weir from 0.12 to 0.30 and newly in a large range of relative height of the weir extremely from 0.24 to 6.8 which greatly expands the application possibilities of low weirs. In addition, the effects of friction and surface tension on the value of the discharge coefficient were evaluated as well as the effect of the relative thickness of the weir. The new equation for discharge coefficient, expressed using the relative height of the weir, was subjected to verification made by an independent laboratory which confirmed its accuracy.
The activity of 194 neurons was recorded in three subdivisions of the medial geniculate body (74 neurons in the ventral, 62 in the medial and 44 neurons in the dorsal subdivision, i.e. vMGB, mMGB and dMGB) of guinea pigs anesthetized with ketamine-xylazine. The discharge properties of neurons were evaluated by means of peristimulus time histograms (PSTHs), interval histograms (INTHs) and auto-correlograms (ACGs). In the whole MGB, the most frequent PSTH responses to pure tone stimuli were onset (43 %) or chopper (32 %). The onset responses were mostly present in the vMGB, whereas chopper responses dominated in the dMGB. In the whole MGB Poisson-like and bimodal INTHs were found in 46 % and 40 % of neurons, respectively. The mMGB revealed fewer bimodal and more symmetrical types of INTH. In the whole MGB, 60 % of units were found to have ACGs typical for short bursts (<100 ms), 23 % for long bursts (>100 ms) and 15 % of units fired without bursts. Neurons in the vMGB were characterized by short bursting, whereas those in the mMGB and dMGB expressed more activity in the long bursts. The results demonstrate that the type of information processing in the vMGB, which belongs to the ”primary” auditory system, is different from that in two other subdivisions of the MGB., E. Kvašňák, J. Popelář, J. Syka., and Obsahuje bibliografii
This paper deals with Markov Control Processes (MCPs) on Euclidean spaces with an infinite horizon and a discounted total cost. Firstly, MCPs which result from the deterministic controlled systems will be analyzed. For such MCPs, conditions that permit to establish the equation known in the literature of Economy as Euler's Equation (EE) will be given. There will be also presented an example of a Markov Control Process with deterministic controlled system where, to obtain the optimal value function, EE applied to the value iteration algorithm will be used. Secondly, the MCPs which result from the perturbation of deterministic controlled systems with a random noise will be dealt with. There will be also provided the conditions which allow to obtain the optimal value function and the optimal policy of a perturbed controlled system, in terms of the optimal value function and the optimal policy of deterministic controlled system corresponding. Finally, several examples to illustrate the last case mentioned will be presented.
A group of fuzzy IF-THEN rules is belonging to one of the most popular, most effective, and user-friendliest knowledge representations. For this reason, extraction of these rules is becoming a more-and-more important part of the Data Mining stage in the Knowledge Discovery in Databases Process. In this paper, a direct algorithm for extracting fuzzy IF-THEN rules on the basis of linguistic variable elimination is described. The algorithm is implemented within a designed object-oriented software library Fuzzy Rule Miner. Besides the introduced algorithm, it implements two algorithms for fuzzy rule extraction based on using fuzzy decision trees of ID3 kind. An essential precondition for comparing the implemented algorithms and for verifying the legitimacy of the introduced algorithm is performance of experiments. The goal of experiments is to take in the behavior of algorithms on testing databases from the UCI Repository of Machine Learning Databases and to make comparisons of algorithms with one another. According to the conducted experiments, the introduced algorithm achieves high accuracy levels of discovered knowledge. The paper also contains a classification of rules and a specification of the Fuzzy Rule Discovery in Databases Process.
The use of computational intelligence systems such as neural networks, fuzzy set, genetic algorithms, etc., for stock market predictions has been widely established. This paper presents a generic stock pricing prediction model based on a rough set approach. To increase the efficiency of the prediction process, rough sets with Boolean reasoning discretization algorithm is used to discretize the data. The rough set reduction technique is applied to find all the reducts of the data which contains the minimal subset of attributes that are associated with a class label for prediction. Finally, rough sets dependency rules are generated directly from all generated reducts. Rough confusion matrix is used to evaluate the performance of the predicted reducts and classes. Using a data set consisting of the daily movements of a stock traded in Kuwait Stock Exchange, a preliminary assessment indicates that rough sets are shown to be applicable and is an effective tool to achieve this goal. For comparison, the results obtained using the rough set approach were compared to that of the neural networks algorithm and it was shown that the Rough set approach has a higher overall accuracy rate and generates more compact and fewer rules than the neural networks.
We consider quasirandom properties for Cayley graphs of finite abelian groups. We show that having uniform edge-distribution (i.e., small discrepancy) and having large eigenvalue gap are equivalent properties for such Cayley graphs, even if they are sparse. This affirmatively answers a question of Chung and Graham (2002) for the particular case of Cayley graphs of abelian groups, while in general the answer is negative., Yoshiharu Kohayakawa, Vojtěch Rödl, Mathias Schacht., and Obsahuje seznam literatury
In this article, we consider the operator $L$ defined by the differential expression \[ \ell (y)=-y^{\prime \prime }+q(x) y ,\quad - \infty < x < \infty \] in $L_2(-\infty ,\infty)$, where $q$ is a complex valued function. Discussing the spectrum, we prove that $L$ has a finite number of eigenvalues and spectral singularities, if the condition \[ \sup _{-\infty < x < \infty} \Big \lbrace \exp \bigl (\epsilon \sqrt{|x|}\bigr ) |q(x)|\Big \rbrace < \infty, \quad \epsilon > 0 \] holds. Later we investigate the properties of the principal functions corresponding to the eigenvalues and the spectral singularities.