Effects of the golfer-ground interaction on clubhead speed in skilled male golfers.

The purposes of this study were to characterise the golfer-ground interactions during the swing and to identify meaningful associations between the golfer-ground interaction force/moment parameters and the maximum clubhead speed in 63 highly skilled male golfers (handicap ≤ 3). Golfers performed shots in 3 club conditions (driver, 5-iron and pitching wedge) which were captured by an optical motion capture system and 2 force plates. In addition to the ground reaction forces (GRFs), 3 different golfer-ground interaction moments (GRF moments, pivoting moments and foot contact moments) were computed. The GRF moment about the forward/backward (F/B) axis and the pivoting moment about the vertical axis were identified as the primary moments. Significant (p < 0.05) correlations of peak force parameters (all components in the lead foot and F/B component in the trail foot) and peak moment parameters (lead-foot GRF moment and trail-foot pivoting moment) to clubhead speed were found. The lead-foot was responsible for generating the GRF moment, while the trail foot contributed to the pivoting moment more. The instant the lead arm becomes parallel to the ground was identified as the point of maximum angular effort, and the loading onto the lead-foot near this point was critical in generating both peak moments.

Process correlation analysis model for process improvement identification.

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.