This article aims to address the wind-farm power tracking problem, which requires farm's total generation track time-varying references and, therefore, allows wind farm participate in ancillary services such as frequency regulation. A novel preview-based robust deep reinforcement learning (PR-DRL) method is proposed handle tasks are subject uncertain environmental conditions and strong aerodyna...

Background and purpose: European Society for Therapeutic Radiology and Oncology (ESTRO) has set up a Quality Assurance network for radiotherapy (EQUAL) carrying out dosimetry audit. Some of the work is done in cooperation with the IAEA. The network deals with measurements performed with mailed TLD irradiated in reference and non-reference conditions, for on-axis points in photons and electrons ...

For the dose study, a semi-automated method of data collection is used in this study. The participating centres were asked to fill out a spreadsheet with all necessary data and return it. For direct digital (DR) systems, the relevant data available in the DICOM header were used. All data is automatically added to a database and processed. The data were used to calculate the mean glandular dose ...

In recent years, a real-time control method based on deep reinforcement learning (DRL) has been developed for urban combined sewer overflow (CSO) and flooding mitigation is more advantageous than traditional methods in the context of drainage systems (UDSs). Since current studies mainly focus analyzing feasibility DRL comparing them with methods, there still need to optimize design cost methods...

Purpose: To investigate the effect of Phellodendron chinense Schneid (PCS) extracts on carrageenaninduced chronic prostatitis in rats. Methods: Experimental chronic non-bacterial prostatitis (CNP) was induced in rats by injecting carrageenan into prostatitis. Rats in treated groups were administered either PCS extract or positive control (cernilton) for 3 weeks while those in the control group ...