Diffractive Sensor Elements for Registration of Long-Term Instability at Writing of Computer-Generated Holograms

The research and development of methods using of the specialized diffractive microstructure sensors embedded in the pattern of computer-generated holograms (CGH) manufactured on circular and X-Y laser writing systems is discussed. These microstructures consist of two parts: one of which is written before the CGH in the field of future hologram and the second one is written during the long-term writing of the CGH. The shift between the first and second part of the microstructure is the trace of the writing errors and allows one to determine and calculate the error of CGH fabrication along both orthogonal coordinates. The developed method is based on the principle of diffraction-based overlay with 1D and 2D built-in diffractive microstructure-sensors. Mathematical modeling and results of experimental test writings of such diffractive microstructure sensors are described. The efficiency of using these types of build-in sensors for the writing errors estimation for CGHs is demonstrated.

Mathematical Model for Errors Estimation of Difference of Objects’s Elevation Determination Using Flying Platform

In this paper the method for determination of the object’s elevation on the ground as well as the mathematical model for error estimation of object’s determination are suggested. It is assumed that the object is situated beyond line-of-sight or, whatsoever, beyond the horizon. It has been obtained the analytic expression for error estimation of the object’s elevation determination using flying platform in case of the known inaccuracy of goniometry and distance measures. The effect of inaccuracy of goniometry and distance measurements on the error estimation of the object’s elevation determination is traced. Analytic expressions of evaluating requirements for accuracy of goniometer and distance measurer are deduced. These requirements will ensure the specified accuracy of the object’s elevation determination. A relationship between object’s elevation determination and its location with respect to the observing station and flying platform is investigated.

On GPS L1 Positioning Errors’ Estimation in the Adriatic Region

Prediction of satellite positioning errors represents a substantial step towards the Global Navigation Satellite System (GNSS) performance assessment. Satellite positioning accuracy in the particular area can be expected to be similar due to prevailing environmental conditions. This similarity opens the opportunity to estimate and predict the positioning errors of close locations. The paper aims to develop a regional model of positioning errors estimation for Global Positioning System (GPS) single-frequency receivers based on ground truth data from reference stations, in this phase considering different levels of space weather activity as one f the criteria defining environmental conditions. The model should provide a simple positioning error prediction in cases where reference stations and respective data do not exist. The space weather conditions were examined to determine the influence on GPS satellite positioning performance at three selected International GNSS Service (IGS) stations in the Adriatic Region - Graz, Padua, and Matera. The mutual relations in terms of positioning error patterns were elaborated. The same 15-day period in three consecutive years was analysed. Pearson’s coefficient was utilised as a major indicator for determining the degree of correlation. The data from IGS stations Padua and Graz showed better, significant correlation results. The IGS station Matera, located farther and southward slightly differed in positioning deviations’ patterns and was not used for the model development. Satellite positioning errors of IGS Padua were used as a reference to determine the positioning errors of IGS Graz. Due to the significant correlation results, the linear regression model has been developed for the latitude, longitude, and height positioning errors. The final model coefficients were calculated as average values of the model coefficients for latitude, longitude, and height errors for elaborated periods. The cross-validation with five folds has been carried out, showing good model performance with R2 values of 0.7785 for geographic latitude, 0.8132 for the geographic longitude, and 0.7796 for height above sea level, respectively. The validation showed that the model could be applied during all levels of space weather activity on a regional basis.

Determinants of agri-lending in Kenya

Purpose The purpose of this paper is to examine the factors that influence financial institutions’ lending to the agricultural sector in Kenya. Design/methodology/approach The paper employs a panel data of 15 licensed financial institutions (commercial banks and deposit-taking microfinance institutions) from 2011 to 2016. The random effects and ordinary least squares panel corrected standard errors estimation techniques are employed to estimate the effect of liquidity, size, equity, lending rate (LR), type of financial institution and non-performing loans on agri-lending. Findings The results indicate that only 3.9 per cent of loan portfolio of the sampled financial institutions were advanced to the agricultural sector over the study period. From the panel regression analysis, the paper finds agricultural credit risk to reduce lending to the agricultural sector while size, LR and type of financial institution were observed to significantly increase agricultural lending. Compared to 2011, agri-lending was also observed to have declined between 2012 and 2015. Practical implications The findings highlight important indicators for enhancing lending to the agricultural sector in Kenya and other emerging economies. Originality/value As far as the authors are concerned, this presents the first empirical evidence on the determinants of agri-lending by financial institutions in Kenya.