We present the hyperbola recognition problem in Ground Penetrating Radar – GPR – data as an example for pattern recognition in complex engineering sensor data. Traditionally, GPR data are analyzed manually by human experts in a tedious and time-consuming process, e.g., to deduce the positioning of linear object underneath roads just before reconstruction works take place. For supporting this pr...

DESIGN AND OPTIMIZATION OF UWB ANTENNA FOR AIR COUPLED GPR APPLICATIONS Report Title This thesis presents a novel antenna structure that satisfies the challenging requirements of an air coupled high speed ground penetrating radar (GPR). The desired GPR system is to achieve high spatial resolution and accurate inspection results while scanning at relatively high speed for highway pavement and br...

In the development of geophysical methods for unexploded ordnance detection, a very important role is played by UXO test sites, where known and other explosive/nonexplosive items are buried in ground at defined positions. At such various detection can be compared, developed tested. Based on cooperation between Department Applied Geophysics (Comenius University), Institute Forensic Science (Slov...

OBJECTIVE The aim of this study was to investigate the effects of global postural re-education (GPR) on the treatment of spinal disorders by performing a systematic review and a meta-analysis. DESIGN MEDLINE, Scopus, and PEDro databases were searched without language or publication date restrictions. Data on pain and function were used to evaluate the effectiveness of GPR. Randomized controll...

We studied the developmental acquisition of three of the cotransmitters found in the gastropyloric receptor (GPR) neurons of the stomatogastric nervous systems of the lobsters Homarus americanus and Homarus gammarus. By using wholemount immunocytochemistry and confocal microscopy, we examined the distribution of serotonin-like, allatostatin-like, and FLRF(NH2)-like immunoreactivities within the...

Gaussian process regression (GPR) is a popular tool for nonlinear function approximation. Unfortunately, GPR can be difficult to use in practice due to the O(n) memory and O(n) processing requirements for n training data points. We propose a novel approach to scaling up GPR to handle large datasets using the recent concept of doubly stochastic functional gradients. Our approach relies on the fa...

Œe problem of building statistical models of cyber-physical systems using operational data is addressed in this paper, using the case study of aircra‰ engines. Œese models serve as a complement to physics-based models, which may not accurately reƒect the operational performance of systems. Œe accurate modeling of fuel ƒow rate is an essential aspect of analyzing aircra‰ engine performance. In t...

Forward modeling of reflection seismic data is a computational process through which a geologic model (units: horizontal distance, vertical depth; layer acoustic impedance) of the subsurface is transformed into a synthetic reflection seismic record (units: horizontal distance, 2-way travel time; reflection amplitude). Synthetic seismic records (synthetics) are often generated both before and af...

Long-term draining of peatlands results in transformation vegetation and obliteration their morphological features. In many areas, efforts are made to restore the original ecosystems increase water retention potential. Using combined analyses a LiDAR-based digital terrain model (DTM), colour-infrared (CIR) imagery data, ground-penetrating radar (GPR) data electrical resistivity tomography (ERT)...