Technology at Washington University School of Medicine Library: BACS, PHILSOM, and OCTANET

A brief overview of the Bibliographic Access and Control System developed by the Washington University School of Medicine Library is presented. Because the system has been described in two previous reports, this paper focuses on its relationship to other automated programs (i.e., PHILSOM and OCTANET), education of users, evaluation of the system, and outreach to the medical center. In operation for more than two years, BACS represents the computerization of much of the managerial and operational functions of the library, and marks the completion of stage 1 of the three stages of library evolution described in the AAMC report Academic Information in the Academic Health Sciences Center: Roles for the Library in Information Management.     

Beyond the online catalog: developing an academic information system in the sciences

The online public access catalog consists essentially of a machine-readable database with network capabilities. Like other computer-based information systems, it may be continuously enhanced by the addition of new capabilities and databases. It may also become a gateway to other information networks. This paper reports the evolution of the Bibliographic Access and Control System (BACS) of Washington University in end-user searching, current awareness services, information management, and administrative functions. Ongoing research and development and the future of the online catalog are also discussed.     

Automatic detection of collisions in elite level rugby union using a wearable sensing device

Elite rugby union teams currently employ the latest technology to monitor and evaluate the physical demands of training and games on their players. Tackling has been shown to be the most common cause of injury in rugby union, yet current player monitoring technology does not effectively evaluate player tackling measurements. Currently, to evaluate measurements specific to player tackles, a time-consuming manual analysis of player sensor data and video footage is required. The purpose of this work is to investigate tackle modeling techniques which can be utilised to automatically detect player tackles and collisions using sensing technology already being used by elite international and club level rugby union teams. This paper discusses issues relevant to automatic tackle analysis, describes a technique to detect tackles using sensing data and validates the technique by comparing automatically detected collisions to manually labeled collisions using data from elite club and international level players. The results of the validation show that the system is able to consistently identify collisions with very few false positives and false negatives, achieving a recall and precision rating of 0.933 and 0.958, respectively. The aim is that the automatically detected tackles can provide coaching, medical and strength and conditioning staff with objective tackle-specific measurements, in real time, which can be used in injury prevention and rehabilitation strategies.     

Recognizing the face of Johnny, Suzy, and me: insensitivity to the spacing among features at 4 years of age

Four-year-olds were tested for their ability to use differences in the spacing among features to recognize familiar faces. They were given a storybook depicting multiple views of 2 children. They returned to the laboratory 2 weeks later and used a "magic wand" to play a computer game that tested their ability to recognize the familiarized faces and their own face based on the spacing of features. Children performed at chance levels. Follow-up studies confirmed that they had attended to internal facial features and validated the stimuli. The results contrast with studies showing some sensitivity to the spacing of features in infants and preschool children; multiple mechanisms of face processing may make use of spatial relations and develop at different rates.