Recently, there has been a lot of interest in temporal granularity, and its applications in temporal dependency theory and data mining. Generalization hierarchies used in multi-dimensional databases and OLAP serve a role similar to that of time granularity in temporal databases, but they also apply to non-temporal dimensions, like space. In this paper, we first generalize temporal functional de...

BACKGROUND The interRAI-Home Care (interRAI-HC) instrument is commonly used in routine care to assess care and service needs, resource utilisation and health outcomes of community dwelling home care clients. Potentially, the interRAI-HC can also be used to calculate societal costs in economic evaluations. The purpose of this study was to assess the convergent validity of the interRAI-HC instrum...

AIM Physicians' inappropriate prescribing habits affect patients' lives both medically and financially. To avoid these unwanted situations, the World Health Organization defined the rational use of drugs (RUD) in 1985. This study aimed to investigate whether patients were as informed about their diagnosis and medication as anticipated and their knowledge about the RUD in general. METHODS A qu...

Background: Drilling is one of the most widely used process in orthopaedic surgical operation and the same drill bit is used a number of times in hospitals. Using the same drill bit a several times may be the cause of osteosynthesis and osteonecrosis. Methods: In the present work, the effect of repeated orthopaedic surgical twist drill bit on the tool wear, force, torque, temperature and chip m...

drought is among the natural disasters that causes heavy damages to water resources and makes managers face serious challenges. drought monitoring is one of the important measures to manage droughts. different indices and methods employing varied indicators, have been developed in this regard. in this paper it is aimed to compare two well known meteorological indices of spi and edi with a hydro...

Deep Deterministic Policy Gradient (DDPG) algorithm is one of the most well-known reinforcement learning methods. However, this method inefficient and unstable in practical applications. On other hand, bias variance Q estimation target function are sometimes difficult to control. This paper proposes a Regularly Updated (RUD) policy gradient for these problems. theoretically proves that procedur...