A number of realistic synthetic examples demonstrate the method under various geological scenarios and several production data matching criteria.
The performance of the method is tested under several attacks and observed that it is very successful against additive white Gaussian noise, salt and pepper noise, Wiener filtering, JPEG compression, and cropping.
The performance of the proposed method was evaluated under several scenarios of gene selection criteria using two well known and challenging datasets: the GCM and NCI60 datasets containing 14 and 9 cancer tumor types, respectively.
The cost-effectiveness of sunitinib versus interferon-alpha for metastatic renal cell carcinoma, as recently calculated for NICE in the UK, is reassessed under several methods, including the proposed method.
In this part, the error bound of the method will be provided under several mild conditions such as solution boundedness of the main neutral differential equation.
In this paper, we compare these two major methods and their extensions under several scenarios in the platform trials setting.
We demonstrate the accuracy, efficiency and robustness of the proposed method via several nonlinear under-determined test cases.
The objectives of this study are (1) to calibrate retrospective PFOA serum concentration predictions for the participants in the C8 Health Project using two different calibration methods with single biomarker measurements and (2) to determine the individual-level calibration method with the least bias under several different scenarios using simulations.
We evaluate our method using simulated game outcomes under several data-generating mechanisms, and compare it to random pairings, to the standard knockout format, and to two variants of the standard format.
