Investigating the Impact of Self-Efficacy and Job Performance with Mediating Role Mental Toughness Accountants: Case Study Offices Arvand Free Zone

Environmental stress, especially drought stress, can play an important role in the reduction of the plant growth stage, specifically duringgermination in arid and semi arid regions in Iran.. In order to study the effects of drought stress on germination indices in wheat cultivars, an experiment was conducted in factorial form, using a completely randomized design of four replications. In this e...

Search methods based on Monte-Carlo simulation have recently led to breakthrough performance improvements in difficult game-playing domains such as Go and General Game Playing. Monte-Carlo Random Walk (MRW) planning applies MonteCarlo ideas to deterministic classical planning. In the forward chaining planner ARVAND, MonteCarlo random walks are used to explore the local neighborhood of a search ...

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...

Like most teams SharifArvand consists of three parts:WorldModel, skills, and strategy. Duty of the WorldModel is getting received messages from the Soccer Server (Sserver[1]), creating a virtual model of the game field and updating the information about each object. Other layers of the program will take the necessary information for playing soccer from the WorldModel in a convenient format. Als...

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...