In the paper, the variation of the intensity of the geomagnetic field force is analysed in time and space. For the research, the data from measurements of the intensity of the geomagnetic field force at four airports (Kaunas, Klaip˙eda, Palanga andVilnius) and 6 geomagnetic field repeat stations aswell as the data from Belsk Magnetometric Observatory (Poland) were used. For the data analysis, the theory of covariance functions was applied. The estimates of the cross-covariance functions of the measured intensity of the geomagnetic field force or the estimates of auto-covariance functions of single data were calculated according to the random functions created from the force intensity measurement data arrays. The estimates of covariance functions were calculated upon varying the quantization interval on the time scale and applying the software created using Matlab package of procedures. The impact of radars of airports on the intensity of geomagnetic field variation and on changes of their covariance functions was established.
Single-frame methods of determining the attitude of a nanosatellite are compared in this study. The methods selected for comparison are: Single Value Decomposition (SVD), q method, Quaternion ESTimator (QUEST), Fast Optimal Attitude Matrix (FOAM) − all solving optimally the Wahba’s problem, and the algebraic method using only two vector measurements. For proper comparison, two sensors are chosen for the vector observations on-board: magnetometer and Sun sensors. Covariance results obtained as a result of using those methods have a critical importance for a non-traditional attitude estimation approach; therefore, the variance calculations are also presented. The examined methods are compared with respect to their root mean square (RMS) error and variance results. Also, some recommendations are given.
The primary goal of the study is to diagnose satisfaction and loyalty drivers in Polish retail banking sector. The problem is approached with Customer Satisfaction Index (CSI) models, which were developed for national satisfaction studies in the United States and European countries. These are multiequation path models with latent variables. The data come from a survey on Poles’ usage and attitude towards retail banks, conducted quarterly on a representative sample. The model used in the study is a compromise between author’s synthesis of national CSI models and the data constraints.
There are two approaches to the estimation of the CSI models: Partial Least Squares – used in national satisfaction studies and Covariance Based Methods (SEM, Lisrel). A discussion is held on which of those two methods is better and in what circumstances. In this study both methods are used. Comparison of their performance is the secondary goal of the study.