Background: In the context of the recent Greek economic crisis and its detrimental impact on healthcare system as well as the complete absence of a mechanism to map and plan human resources, a need for rethinking healthcare workforce management at a national level was emerged. Objectives: The aim of the study was to identify factors that influence the current and future demand for and supply of...

Here we introduce two new notions of approximate matching with application in computer assisted music analysis. We present algorithms for each notion of approximation: for approximate string matching and for computing approximate squares.

To perform any economic management of a petroleum reservoir in real time, a predictable and/or updateable model of reservoir along with uncertainty estimation ability is required. One relatively recent method is a sequential Monte Carlo implementation of the Kalman filter: the Ensemble Kalman Filter (EnKF). The EnKF not only estimate uncertain parameters but also provide a recursive estimat...

This study addresses an image-matching problem in challenging cases, such as large scene variations or textureless scenes. To gain robustness to situations, most previous studies have attempted encode the global contexts of a via graph neural networks transformers. However, these do not explicitly represent high-level contextual information, structural shapes semantic instances; therefore, enco...

Background: Understanding the physiological and psycho-social effects of pregnancy through Assisted Reproductive Technologies (ARTs) will enable health care providers to identify and treat any adverse outcomes, and provide support to women seeking fertility treatments. The aim of this paper was to review studies describing prenatal care in pregnancy through ARTs. Methods: A systematic search o...

Two geostatistical methods for history matching are presented. Both rely on the sequential simulation principle for generating geologically sound realizations. The first method relies on perturbing the sequential simulation through the perturbation of the conditional distribution models; the second method relies on the perturbation of random numbers. We show that both approaches are general in ...

Production forecasting is the basis for decision making in oil and gas industry, can be quite challenging, especially terms of complex geological modeling subsurface. To help solve this problem, assisted history matching built on ensemble-based analysis such as ensemble smoother Kalman filter useful estimating models that preserve realism have predictive capabilities. These methods tend, howeve...