The Dynamic Process of Development through Sport

This article presents a global vision for sport through a new framework that incorporates the elements necessary for a developmentally sound approach to youth sport involvement. This framework proposes that youth sport involvement includes three basic elements: (1) taking part in activities (what), while creating relationships with others (who), in a specific setting (where). When these three elements positively interact, it creates a context that, when repeated on a regular basis, leads to changes in the personal assets of the participants. Changes in individuals’ personal assets, such as Competence, Confidence, Connection, and Character (4 C’s), have long been associated with positive sport experiences, which in turn lead to long-term outcomes, including continued sport Participation, higher levels of Performance in sport, and Personal development through sport (3 P’s). Research linking the three basic elements of youth sport (activities, relationships, and settings) to positive changes in personal assets (4 C’s) and long-term outcomes (3 P’s) are discussed and the Personal Assets Framework is presented

Automatic Identification of Large Fragments in a Pile of Broken Rock Using a Time-of-Flight Camera

This paper presents a solution to part of the problem of making robotic or semi-robotic digging equipment less dependant on human supervision. A method is described for identifying rocks of a certain size that may affect digging efficiency or require special handling. The process involves three main steps. First, by using range and intensity data from a time-of-flight (TOF) camera, a feature descriptor is used to rank points and separate regions surrounding high scoring points. This allows a wide range of rocks to be recognized because features can represent a whole or just part of a rock. Second, these points are filtered to extract only points thought to belong to the large object. Finally, a check is carried out to verify that the resultant point cloud actually represents a rock. Results are presented from field testing on piles of fragmented rock. Note to Practitioners—This paper presents an algorithm to identify large boulders in a pile of broken rock as a step towards an autonomous mining dig planner. In mining, piles of broken rock can contain large fragments that may need to be specially handled. To assess rock piles for excavation, we make use of a TOF camera that does not rely on external lighting to generate a point cloud of the rock pile. We then segment large boulders from its surface by using a novel feature descriptor and distinguish between real and false boulder candidates. Preliminary field experiments show promising results with the algorithm performing nearly as well as human test subjects.