Advanced approach to numerical forecasting using artifi cial neural networks.

Abstract ŠTENCL, M., ŠŤASTNÝ, J.: Advanced approach to numerical forecasting using artifi cial neural networks. Acta univ. agric. et silvic. Mendel. Brun., 2009, LVII, No. 6, pp. 297-304 Current global market is driven by many factors, such as the information age, the time and amount of information distributed by many data channels it is practically impossible analyze all kinds of incoming information fl ows and transform them to data with classical methods. New requirements could be met by using other methods. Once trained on patterns artifi cial neural networks can be used for forecasting and they are able to work with extremely big data sets in reasonable time. The patterns used for learning process are samples of past data. This paper uses Radial Basis Functions neural network in comparison with Multi Layer Perceptron network with Back-propagation learning algorithm on prediction task. The task works with simplifi ed numerical time series and includes forty observations with prediction for next fi ve observations. The main topic of the article is the identifi cation of the main diff erences between used neural networks architectures together with numerical forecasting. Detected diff erences then verify on practical comparative example. Artifi cial Neural Networks, Radial basis function, Numerical Forecasting, Multi Layer Perceptron Network The knowledge of the future creates the advantage in all kind of business. The methods traditionally used for numerical forecasting are based on precise analysis of past values. The prognosis is then built as approximation of future values using functions estimated from dependencies founded by past values analysis. The statistical time series model is used as a traditional method for economical forecasting

Intra- and inter-individual variability in the underwater pull-out technique in 200 m breaststroke turns.

The purpose of the present study was to investigate the intra- and inter-individual variability in arm-leg coordination during the underwater phase of the turn segment in 200 m breaststroke. Thirteen male swimmers were recruited and performed a 200 m breaststroke in a pre-calibrated 25 m pool. Sub-phases during the underwater segment were obtained using a notational analysis, and the mean velocity, displacement and duration during each sub-phase were obtained. A hierarchical cluster analysis (HCA) was performed using the analysed variables in all phases to identify inter-individual variability and random intra-individual variability. In addition, a linear mixed model (LMM: lap as a fixed effect and the participant as a random effect) was conducted to investigate systematic intra-individual variability. HCA identified three coordination patterns that were distinguished by the timing of the dolphin kick relative to the arm pull-out and the duration of the glide with arms at the side. All swimmers except one performed the arm pull-out after the dolphin kick. Nine swimmers maintained one coordination pattern, but other swimmers switched their coordination during the trial, particularly by shortening the duration of the glide with arms at the side. LMM showed a linear decrease (from the first to the last turn) in the time gap between the end of the dolphin kick and the start of the arm pull-out (a glide with the streamlined body position; F = 9.64, p = 0.034) and the glide duration with the arms at the side (F = 11.66, p = 0.015). In conclusion, both inter- and intra-individual variabilities during the underwater phase were evident in 200 m breaststroke turns, which were categorised into three patterns based on the timing of the dolphin kick and the duration of glides

Urban climate in central european cities and global climate change

Urban areas are among those most endangered with the potential global climate changes. The studies concerning the impact of global changes on local climate of cities are of a high significance for the urban inhabitants' health and wellbeing. This paper is the final report of a project (Urban climate in Central European cities and global climate change) with the aim to raise the public awareness on those issues in five Central European cities: Szeged (Hungary), Brno (Czech Republic), Bratislava (Slovakia), Kraków (Poland) and Vienna (Austria). Within the project, complex data concerning local geomorphological features, land use and long-term climatological data were used to perform the climate modelling analyses using the model MUKLIMO_3 provided by the German Weather Service (DWD)

TIME SERIES CLUSTERING IN LARGE DATA SETS

Abstract FEJFAR, J., ŠŤASTNÝ, J.: Time series clustering in large data sets. Acta univ. agric. et silvic. Mendel. Brun., 2011, LIX, No. 2, pp. 75-80 The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM) with the unsupervised learning algorithm for clustering of time series. A er the fi rst experiment (Fejfar, Weinlichová, Šťastný, 2009) it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to fi nd the correlation between confi gured parameters and results more precisely. The second requirement arose in a need for a well-defi ned evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications. The objective of the presented paper is to compare clustering results made with diff erent parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with diff erent topologies varying from few neurons to large maps. There are other algorithms discussed, usable for fi nding similarities between time series and fi nally conclusions for further research are presented. We also present an overview of the related actual literature and projects. time series, self-organizing map, clustering Many objects that we are observing change themselves in time. When we measure properties of these objects we obtain time series -values caught sequentially in time Basically, we are investigating two types of tasks on time series: prediction and classifi cation / clustering. There are many problems as need for querying large databases of time series, subjectivity of similarity of time series, data handling problems: sample rates, data formats, missing values. We have plenty of methods for dealing with these problems. In the classifi cation and prediction area we are focusing on the promising concept using artifi cial neural networks (ANN). This area is not yet described in all its parts and consequences. Our results in the prediction of economical time series using ANN are presented in the paper (Štencl, Šťastný, 2009). The objective of this paper is our presentation of the huge time series dataset clustering results, with discussing the infl uence of process properties on those results. It describes the signal-processing phase resulting in a dataset of 1024 time series. It searches for a feedback of time series normalisation on resulting classes. It is also investigating the impact of the Kohonen Self-organizing map properties on resulting classes giving suggestions for setting these variables. Finally it is discussing the complicated fact of the unsupervised SOM performance evaluation

Notes on the Scarodytes savinensis-complex with the description of two new taxa (Coleoptera: Dytiscidae)

Fery, H., Šťastný, J. (2007): Notes on the Scarodytes savinensis-complex with the description of two new taxa (Coleoptera: Dytiscidae). Linzer biologische Beiträge 39 (2): 877-899, DOI: 10.5281/zenodo.541677

Long-term population dynamics of the field vole from the Czech Republic

Tkadlec, E., Bejček, V., Flousek, J., Šťastný, K., Zima, J., Sedláček, F

Benefits of Using Traffic Volumes Described on Examples in the Open Transport Net Project Pilot Regions

The paper describes the goals of the Open Transport Net project in the pilot regions for regional development and the motivation to use traffic volumes in order to reach the project objectives. In the introduction, a short overview of the Open Transport Net project is provided. It is followed by descriptions of the identified problems in the pilot regions and incentives to use traffic volumes for achieving good quality results. The basics of traffic volumes as well as their visualisation are further described and demonstrated including several examples

The Influence of Interleukin-1β on γ-Glutamyl Transpeptidase Activity in Rat Hippocampus

Summary Brain infections as well as peripheral challenges to the immune system lead to an increased production of interleukin1beta (IL-1β), a cytokine involved in leukocyte-mediated breakdown of the blood-brain barrier. The effects of IL-1β have been reported to depend on whether the route of administration is systemic or intracerebral. Using 50-day-old male rats, we compared the effects of IL-1β on brain γ-glutamyl transpeptidase (GGT; an enzymatic marker of brain capillary endothelium) at 2, 24 and 96 h after either an intravenous (i.v.) injection of 5 μg IL-1β or an intracerebroventricular (i.c.v. -lateral ventricle) infusion of 50 ng IL-1β. When the i.v. route was used, the GGT activity underwent small but significant changes; decreasing in the hippocampus 2 h after the i.v. injection, increasing 24 h later and returning to control levels at 96 h. No significant changes in the hippocampal GGT activity were observed at 2 and 24 h following the i.c.v. infusion. The GGT activity in the hypothalamus remained unchanged regardless of the route of IL-1β administrations. Similar changes in GGT activity were revealed histochemically. The labeling was found mainly in the capillary bed, the changes being most evident in the hippocampal stratum radiatum and stratum lacunosum-moleculare. A transient increase in GGT activity at 24 h, together with a less sharp delineation of GGT-stained vessels, may reflect IL-1β induced increased turnover of glutathione and/or oxidative stress, that may in turn, be related to altered permeability of the blood-brain barrier in some neurological and mental disorders, including schizophrenia

Concurrent validity of Myotest for assessing explosive strength indicators in countermovement jump

Background: Previous research has determined the validity and reliability of accelerometer-based devices, but the findings are not consistent. Objective: The purpose of this study was to determine the validity of an accelerometer (Myotest PRO) for measuring explosive strength indicators (jump height, peak force, peak velocity, and peak power) during the countermovement jump. Methods: Thirty-three university students (22 males and 11 females; 178.6 ± 5.6 cm, 69.3 ± 6.5 kg, 21.8 ± 1.7 years) performed five individual countermovement jumps. Jump height was derived from an accelerometer (Myotest, frequency 200 Hz), optic timing system (Optojump) and from a force plate (Kistler, frequency 800 Hz) using both flight time and force impulse algorithms. Peak force, peak velocity, and peak power were calculated by the accelerometer and force plate. Results: The Myotest resulted in systematic bias, overestimating jump height by 8.0 ± 2.1 cm (p < .001) compared to force impulse algorithm; flight time algorithm by 5.5 ± 2.0 cm (p < .001) using the force plate and by 5.9 ± 2.0 cm (p < .001) using the Optojump. The Myotest also underestimated peak force by 167 ± 182 N (p < .001). Compared to force impulse algorithm, the Myotest displayed less agreement for peak velocity (r2 = .245) and peak power (r2 = .557). Conclusion: Accelerometers are valid and may be used consistently to evaluate countermovement jump height. However, they are not valid, and should neither be used to measure peak force, velocity, or power nor be compared against other methods due to a bias