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This study analyzed the relationship between the occupational decisions of teachers or potential teachers and salary differences that exist between teachers and workers who are employed in alternative occupations. Occupational choice theory is reviewed, and research related to teacher salary, teacher recruitment, and teacher retention is analyzed. A conceptual model of causal relationships among variables in determining the occupational decisions of both prospective and practicing teachers is presented. A sample of teachers or potential teachers was drawn from the National Longitudinal Study of the High School Class of 1972 (NLS-72), its five follow-up surveys, the Postsecondary Education Transcript Study, and the Teaching Supplement questionnaire, resulting in 737 valid cases for the study of attraction to teaching and 495 cases for the study of retention. Findings indicate that the level of teachers' earnings relative to alternative occupations pursued by college graduates has a direct effect on occupational decisions of prospective and current teachers. Women showed a lower response to earnings than did men. The analysis confirmed the effects of various predictors of choosing and leaving teaching--gender, race, family background, the level of teaching, school type, subject specialty, and satisfaction with teaching. (Contains approximately 60 references.) (JDD)

In vehicular safety applications, a vehicular positioning algorithm plays a crucial role in preventing road accidents through the perception of a dangerous situation in advance. However, most of vehicular positioning devices, e.g. a low-cost GPS receiver, have too large position error to be used for these applications. To reduce this error, we present the vehicular positioning accuracy enhancement (VITAE) algorithm which reduces the position error of a vehicle by taking into account the GPS estimate and the sensing estimate of each nearby vehicle; A GPS estimate is obtained from vehicle-to-vehicle communications, whereas a sensing estimate is measured at local sensors, e.g. vehicular radar. We first present a greedy data-association (GDA) algorithm to find a minimal-weight matching between a GPS estimate and a sensing estimate based on an Euclidian distance. We next adjust the position estimate of the vehicle by using the difference in the mass center of GPS estimates and that of sensing estimates. From the law of large numbers, this adjustment leads to the reduction of the position error by 1/√N times, where N is the number of nearby vehicles. To further reduce the position error, we combine our positioning algorithm with the Kalman filter. From the numerical results, we demonstrate that our positioning algorithm can reduce the position error by 81.8% on average. [ABSTRACT FROM PUBLISHER]

A key feature of the vehicular ad-hoc networks (VANETs) is to broadcast the beacon message containing the position, speed, heading, etc. However, the fixed-rate scheme in the current standards may incur too large traffic load to the DSRC channel leading to a significant degradation of the network performance. In this paper, we present a new beacon rate control algorithm that succeeds in tracking the movement of nearby vehicles until K consecutive losses of the beacon message. From the numerical results of the simulation, we show that the proposed scheme can achieve much better performance than the fixed-rate scheme in term of the DSRC channel utilization and the successful vehicle tracking probability. [ABSTRACT FROM PUBLISHER]