Atmospheric temperature gradients related to clear air turbulence in the upper troposphere and lower stratosphere

Relationship between atmospheric temperature gradients and clear air turbulence of lower atmospher

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

A Novel Multi-Objective Self-Organizing Migrating Algorithm

In the paper, a novel stochastic Multi-Objective Self Organizing Migrating Algorithm (MOSOMA) is introduced. For the search of optima, MOSOMA employs a migration technique used in a single-objective Self Organizing Migrating Algorithm (SOMA). In order to obtain a uniform distribution of Pareto optimal solutions, a novel technique considering Euclidian distances among solutions is introduced. MOSOMA performance was tested on benchmark problems and selected electromagnetic structures. MOSOMA performance was compared with the performance of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2). MOSOMA excels in the uniform distribution of solutions and their completeness

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

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

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

Using a Tolerance-based Surrogate Method for Computer Resources Saving in Optimization

This paper presents a very simple surrogate optimization method - a Tolerance-based Surrogate Method. A surrogate optimization in general is essential to more and more frequently used optimization in the development process of new technologies. Fitness functions of such systems are often costly, therefore keeping a number of evaluations of the fitness functions at minimum is of a great importance in order to save computer and time resources, i.e. the overall cost of design. Unlike other complex surrogate optimization methods, the tolerance-based surrogate method does not require excessive computational resources, is easy to implement, and is flexible for all types of optimization algorithms. Behaviour of the tolerance-based surrogate method is demonstrated on several modified benchmark problems. Afterwards, our method is verified on a real-world time-demanding optimization task

Systematic study of Mn-doping trends in optical properties of (Ga,Mn)As

We report on a systematic study of optical properties of (Ga,Mn)As epilayers spanning the wide range of accessible substitutional Mn_Ga dopings. The growth and post-growth annealing procedures were optimized for each nominal Mn doping in order to obtain films which are as close as possible to uniform uncompensated (Ga,Mn)As mixed crystals. We observe a broad maximum in the mid-infrared absorption spectra whose position exhibits a prevailing blue-shift for increasing Mn-doping. In the visible range, a peak in the magnetic circular dichroism blue shifts with increasing Mn-doping. These observed trends confirm that disorder-broadened valence band states provide a better one-particle representation for the electronic structure of high-doped (Ga,Mn)As with metallic conduction than an energy spectrum assuming the Fermi level pinned in a narrow impurity band.Comment: 22 pages, 14 figure

Multi-objective Synthesis of Antennas from Special and Conventional Materials

In the paper, we try to provide a comprehensive look on a multi-objective design of radiating, guiding and reflecting structures fabricated both from special materials (semiconductors, high-impedance surfaces) and conventional ones (microwave substrates, fully metallic antennas). Discussions are devoted to the proper selection of the numerical solver used for evaluating partial objectives, to the selection of the domain of analysis, to the proper formulation of the multi-objective function and to the way of computing the Pareto front of optimal solutions (here, we exploit swarm-intelligence algorithms, evolutionary methods and self-organizing migrating algorithms). The above-described approaches are applied to the design of selected types of microwave antennas, transmission lines and reflectors. Considering obtained results, the paper is concluded by generalizing remarks