Construction work requires more repetitive and highly physical effort than, for example, office work. Despite technological advancements in construction, the human factor is still an essential part of the industry. Hence, the need to maintain a healthy work environment is a shared interest between workers and industry. This thesis addresses the problem of cumulative injuries among construction workers, with emphasis on masons, and examines ways to improve safety and productivity simultaneously.

A large portion of the injuries incurred on construction sites is due to the lack of posture awareness among labors and crew while performing highly physical tasks. Most of these injuries are caused by bad and inexpert poses. Posture and gesture awareness is therefore a critical issue that can substantially decrease the number of injuries on construction sites. This paper presents a framework for identifying the level of expertise based using a machine learning-based classification algorithm.

Purpose: To determine the interventions associated with the pharmacist’s patient counseling and review of discharge prescriptions of patients from a specialized cardiac center in Saudi Arabia. Methods: This was a prospective interventional study conducted at Prince Sultan Cardiac Center (PSCC) in Riyadh, Saudi Arabia for a duration of 12 months.