Multi-Objective Self-Organizing Migrating Algorithm: Sensitivity on Controlling Parameters

In this paper, we investigate the sensitivity of a novel Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) on setting its control parameters. Usually, efficiency and accuracy of searching for a solution depends on the settings of a used stochastic algorithm, because multi-objective optimization problems are highly non-linear. In the paper, the sensitivity analysis is performed exploiting a large number of benchmark problems having different properties (the number of optimized parameters, the shape of a Pareto front, etc.). The quality of solutions revealed by MOSOMA is evaluated in terms of a generational distance, a spread and a hyper-volume error. Recommendations for proper settings of the algorithm are derived: These recommendations should help a user to set the algorithm for any multi-objective task without prior knowledge about the solved problem

High-temperature phase transitions in SrBi_2Ta_2O_9 film: a study by THz spectroscopy

Time-domain THz transmission experiment was performed on a $\rm SrBi_2Ta_2O_9$ film deposited on sapphire substrate. Temperatures between 300 and 923 K were investigated and complex permittivity spectra of the film were determined. The lowest frequency optic phonon near 28 cm$^{-1}$ reveals a slow monotonic decrease in frequency on heating with no significant anomaly near the phase transitions. We show that the dielectric anomaly near the ferroelectric phase transition can be explained by slowing down of a relaxational mode, observed in the THz spectra. A second harmonic generation signal observed in a single crystal confirms a loss of center of symmetry in the ferroelectric phase and a presence of polar clusters in the intermediate ferroelastic phase.Comment: subm. to J. Phys.: Condens. Matte

Time-Domain Finite Elements for Virtual Testing of Electromagnetic Compatibility

The paper presents a time-domain finite-element solver developed for simulations related to solving electromagnetic compatibility issues. The software is applied as a module integrated into a computational framework developed within a FP7 European project High Intensity Radiated Field – Synthetic Environment (HIRF SE) able to simulate a large class of problems. In the paper, the mathematical formulation is briefly presented, and special emphasis is put on the user point of view on the simulation tool-chain. The functionality is demonstrated on the computation of shielding effectiveness of two composite materials. Results are validated through experimental measurements and agreement is confirmed by automatic feature selective algorithms

From Sensor Readings to Predictions: On the Process of Developing Practical Soft Sensors.

Automatic data acquisition systems provide large amounts of streaming data generated by physical sensors. This data forms an input to computational models (soft sensors) routinely used for monitoring and control of industrial processes, traffic patterns, environment and natural hazards, and many more. The majority of these models assume that the data comes in a cleaned and pre-processed form, ready to be fed directly into a predictive model. In practice, to ensure appropriate data quality, most of the modelling efforts concentrate on preparing data from raw sensor readings to be used as model inputs. This study analyzes the process of data preparation for predictive models with streaming sensor data. We present the challenges of data preparation as a four-step process, identify the key challenges in each step, and provide recommendations for handling these issues. The discussion is focused on the approaches that are less commonly used, while, based on our experience, may contribute particularly well to solving practical soft sensor tasks. Our arguments are illustrated with a case study in the chemical production industry

THE INFLUENCE OF SILAGE ADDITIVES FOR QUALITATIVE PARAMETERS OF CLOVER-GRASS SILAGES

We observed the infl uence of silage additives for choice qualitative parameters at 109 samples of clovergrass silages in working conditions. We evaluated total classifi cation and categorization to quality classes according to fermentation process. It has been found out positive effect of the silage additives for fermentation class and for total silage quality of silages. This positive effec t has been more considerable at classifi cation to the fermentation classes at clover-grass silages. The high content of crude fi bre decreased fermentation results and total silage quality at test clover-grass silages. The greatest (deterioration) infl uence for clasifi cation to total quality class has crude fi bre content. It is see from correlation coefi cient at clover-grass silages – r = 0,75 (P < 0,05). The weak dependence r = 0,37 (P < 0,05) was detected between fermentation class and acetic acid content. It was detected large dependence between fermentation class and butyric acid content r = 0,73 (P < 0,05)

VLIV ADITIV NA VYBRANÉ KVALITATIVNÍ UKAZATELE JETELOTRAVNÍCH SILÁŽÍ

We observed the infl uence of silage additives for choice qualitative parameters at 109 samples of clovergrass silages in working conditions. We evaluated total classifi cation and categorization to quality classes according to fermentation process. It has been found out positive effect of the silage additives for fermentation class and for total silage quality of silages. This positive effec t has been more considerable at classifi cation to the fermentation classes at clover-grass silages. The high content of crude fi bre decreased fermentation results and total silage quality at test clover-grass silages. The greatest (deterioration) infl uence for clasifi cation to total quality class has crude fi bre content. It is see from correlation coefi cient at clover-grass silages – r = 0,75 (P < 0,05). The weak dependence r = 0,37 (P < 0,05) was detected between fermentation class and acetic acid content. It was detected large dependence between fermentation class and butyric acid content r = 0,73 (P < 0,05).U 109 vzorků jetelotravních siláží byl v provozních podmínkách sledován vliv silážních aditiv na kvalitativní ukazatele. Posuzováno bylo jednak celkové zatřídění a zařazení do tříd jakosti podle fermentačního procesu. U silážovaných krmiv bylo potvrzeno, že aditiva mají pozitivní vliv na fermentační proces a tím i na celkovou kvalitu siláží. Tento pozitivní vliv byl ještě více patrný na zatřídění do třídy fermentace. Vysoký obsah vlákniny u sledovaných silážovaných krmiv zhoršoval fermentační výsledky i celkovou jakost siláží. Z korelačních koefi cientů hodnotící jetelotravní siláže je patrné, že největší (zhoršující) vliv na zařazení do celkové třídy jakosti má množství vlákniny r 0,75 (P < 0,05). Mírná závislost r 0,37 (P < 0,05) byla zjištěna mezi třídou fermentace a obsahem kyseliny octové. Mezi třídou fermentace a obsahem kyseliny máselné byla zjištěna velká závislost r 0,73 (P < 0,05)