Principal component analysis as a tool to extract Sq variation from the geomagnetic field observations: conditions of applicability

In this paper, we analyze the applicability of the principal component analysis (PCA) as a tool to extract the Sq variation of the geomagnetic field. We tested different geomagnetic field components and used data measured at different levels of the solar and geomagnetic activity and during different months. Geomagnetic field variations obtained with PCA were classified as SqPCA using two types of reference series: SqIQD series calculated using geomagnetically quiet days and simulations of the ionospheric field with models. The results for the X and Y and Z components are essentially different. The Sq variation is always filtered to the first PCA mode for the Y and Z components. Thus, PCA can automatically extract the Sq variation from the observations of the Y and Z components of the geomagnetic field. For the X component, the automatic extraction of the Sq variation is not possible, and a complimentary analysis, like a comparison to a reference series, is always needed. We tested two types of reference series: the mean SqIQD and the outputs of the CM5 and DIFI3 models. Our results show that both the data-based and model-based reference series can be used but the DIFI3 model performs better. We also recommend estimating the similarity of the series not with the correlation analysis but using metrics that account for possible local stretching/compressing of the compared series, for example, the dynamic time warping (DTW) distance.Comment: 32 pages, 18 figures, 4 tables, 9 SM. Re-submitted to MethodsX in July 2022. arXiv admin note: substantial text overlap with arXiv:2104.0039

Datasets of ionospheric parameters provided by SCINDA GNSS receiver from Lisbon airport area

Here we present datasets provided by a SCINDA GNSS receiver installed in the Lisbon airport area from November of 2014 to July of 2019. The installed equipment is a NovAtel EURO4 with a JAVAD Choke-Ring antenna. The data are in an archived format and include the general messages on quality of records (*.msg), RANGE files (*.rng), raw observables as the signal-to-noise (S/N) ratios, pseudoranges and phases (*.obs), receiver position information (*.psn), ionosphere scintillations monitor (ISMRB; *.ism) and ionospheric parameters: total electron content (TEC), rate of change of TEC index (ROTI), and the scintillation index S4 (*.scn). The presented data cover the full 2015 year. The raw data are of 1-minute resolution and available for each of the receiver-satellite pairs. The processing and the analysis of the ionosphere scintillation datasets can be done using a specific "SCINDA-Iono" toolbox for the MATLAB developed by T. Barlyaeva (2019) and available online via MathWorks File Exchange system. The toolbox calculates 1-hour means for ionospheric parameters for each of the available receiver-satellite pairs and averaged over all available satellites during the analyzed hour. Here we present the processed data for the following months in 2015: March, June, October, and December. The months were selected as containing most significant geomagnetic events of 2015. The 1-hour means for other months can be obtained from the raw data using the aforementioned toolbox. The provided datasets are interesting for the GNSS and ionosphere based scientific communities.Comment: arXiv admin note: text overlap with arXiv:1910.0404

Triple junction disclinations in severely deformed Cu-0.4%Mg alloys

Stress fields arising from triple junction disclinations (TJDs) play a significant role in the microstructure evolution during the plastic deformation of metals. The calculation of TJD strengths from grain orientation data was developed by Bollmann more than 50 years ago, but so far applied only to collections of a few grains. Developed here is a new methodology for calculating TJD strengths and the associated stress fields in large polycrystalline assemblies using experimental electron back-scattered diffraction (EBSD) maps. The methodology combines Bollmann's approach with a representation of materials as cell complexes. It is computationally efficient and allows for obtaining the spatial distribution of TJD strengths from EBSD images containing thousands of grains. Analysed are the fraction, distribution, and strengths of TJDs within statistically representative microstructures of Cu-0.4%Mg alloy subjected to severe plastic deformation (SPD) by equal channel angular pressing. It is shown that the formation of low-angle grain boundaries (dislocation walls) during SPD leads to an increasing number of TJDs, whose spatial distribution is progressively more uniform and whose strength distribution remains nearly constant. This result suggests that the SPD reduces the internal stresses associated with disclinations in large regions of the material, as closely situated disclinations screen each other's fields. Regions with high local stresses can be expected between sparsely distributed TJDs with the highest strengths. The average distance between such TJDs could be considered as a natural length scale in a material

Total electron content PCA-NN model for middle latitudes

A regression-based model was previously developed to forecast the total electron content (TEC) at middle latitudes. We present a more sophisticated model using neural networks (NN) instead of linear regression. This regional model prototype simulates and forecasts TEC variations in relation to space weather conditions. The development of a prototype consisted of the selection of the best set of predictors, NN architecture and the length of the input series. Tests made using the data from December 2014 to June 2018 show that the PCA-NN model based on a simple feed-forward NN with a very limited number (up to 6) of space weather predictors performs better than the PCA-MRM model that uses up to 27 space weather predictors. The prototype is developed on a TEC series obtained from a GNSS receiver at Lisbon airport and tested on TEC series from three other locations at middle altitudes of the Eastern North Atlantic. Conclusions on the dependence of the forecast quality on longitude and latitude are made.Comment: arXiv admin note: text overlap with arXiv:2201.0347

Математичні моделі і інформаційні технології організації інноваційних проектів у системі стейкхолдерів

During the involvement of innovative projects into knowledge-intensive high-tech enterprises, the process of creating a system of interested stakeholder management becomes vital. The given work contains the results of conducted analysis concerning the problem of innovative potential management of high-tech enterprises. The necessity of the analysis of informational technologies in the conditions of the non-equilibrium economy is considered. Various models of project management in the system of stakeholders are presented in the work. The stages of Nicholas model are considered. A mathematical model is proposed for the management and investors of the project, in terms of maximizing profits under specified constraints.При залученні інноваційного проекту в наукомісткі високотехнологічні підприємства актуальним процесом стає створення системи управління зацікавленими учасниками. Проведено аналіз проблеми управління інноваційним потенціалом наукомістких підприємств. Розглянуто необхідність аналізу інформаційних технологій в умовах нерівноважної економіки. Розглянуто різні моделі управління проектами в системі зацікавлених осіб. Розглянуто етапи використання моделі Ніколаса. Запропоновано математичну модель для керівництва та інвесторів проекту, в умовах максимізації прибутку при заданих обмеженнях