Ground-penetrating radar (GPR) has recently gained a wide acceptance in the archaeological community as a method that can quickly and accurately locate buried archaeological features, artifacts, and important cultural strata in the near-surface. The GPR method has been especially effective in certain sediments and soils between about 20 cm and 5 m below the ground surface, where the targets to ...

Data-driven techniques based on Bayesian framework like Gaussian Process Regression (GPR) can not only predict the lithium-ion battery Remaining Useful Life (RUL), but also provide the uncertainty representation. However, it is always difficult to choose the covariance function of GPR and the confidence bound is usually large if the training data are not enough. In order to solve this problem, ...

Gaussian process regression (GPR) is a powerful non-linear technique for Bayesian inference and prediction. One drawback is its O(N) computational complexity for both prediction and hyperparameter estimation for N input points which has led to much work in sparse GPR methods. In case that the covariance function is expressible as a tensor product kernel (TPK) and the inputs form a multidimensio...

Three nonlinear count models, Poisson R.egression (PR), Negative Binomial Regression (NBR), and Generalized Poisson Regression (GPR) are used for assessing the effects of risk factors on agricultural injuries from farm injury data. A sample of 1,322 respondents who participated in the farm safety/injury baseline survey in nine rural counties in Alabama and Mississippi, aged 18 years and older a...

Precise models of the robot inverse dynamics allow the design of significantly more accurate, energy-efficient and more compliant robot control. However, in some cases the accuracy of rigidbody models does not suffice for sound control performance due to unmodeled nonlinearities arising from hydraulic cable dynamics, complex friction or actuator dynamics. In such cases, estimating the inverse d...

The selection of a near-field or far-field ground-penetrating radar (GPR) model is an important question for an accurate but computationally effective characterization of medium electrical properties using full-wave inverse modeling. In this study, we determined an antenna height threshold for the near-field and farfield full-wave GPR models by analyzing the variation of the spatial derivatives...

GPR and reflection seismics share common physical and methodological bases but are sensitive to different subsurface physical properties. The peculiarities of the electromagnetic case impact data acquisition, processing and interpretation. We review multi-offset techniques in GPR applications focusing on similarities and differences through examples taken from different subsurface and target co...