National training course, emergency medical technician - paramedic. Instructor's lesson plans. Module XV: telemetry and communications.

Mode of access: Internet.

Commercial driver's license identification manual. U.S.A. Canada. Mexico.

Federal Highway Administration, Washington, D.C.

Basic training course/ emergency medical technician. Course guide. Second edition.

Mode of access: Internet.

Basic training course/ emergency medical technician. Instructor's lesson plans. Second edition.

Mode of access: Internet.

Basic training course/ emergency medical technician. Student study guide. 1977 edition.

Mode of access: Internet.

Curriculum workshops for college and university driver education instructors.

National Highway Traffic Safety Administration, Washington, D.C.

The R.O.T.C. manual, infantry : a text book for the Reserve Officers Training Corps.

Vol. 1-2 are 20th ed.

The R.O.T.C. manual. Infantry. A text book for the Reserve officers training corps.

Vols. III-IV are 18th edition.

Training program for operation of emergency vehicles : instructor lesson plans.

Bibliography: p. 1-3 - 1-8.

Abstract of the definition, philosophy, legal requirements and procedures for expediting programs in health, physical education, driver education and safety /

Mode of access: Internet.

Motorcycle operator training evaluation plan /

Cover title varies: Motorcycle rider training evaluation plan.

The organization and training of joint task forces /

"April 1996."

The incidence and intensity of employer funded training: Australian evidence on the impact of flexible work

The interaction between the growth of flexible forms of employment and employer funded training is important for understanding labour market performance. In particular, the idea of a trade-off has been advanced to describe potential market failures in the employment of flexible workers. This study finds that evidence of a trade-off is apparent in both the incidence and intensity of employer funded training. Flexible workers receive training that is 50-80% less intense than the workforce average. Casual workers - especially males - suffer more acutely from the trade-off. This suggests that flexible production externalities may seriously reduce human capital formation in the workforce.

Does anticipation training affect drivers' risk taking?

Skill and risk taking are argued to be independent and to require different remedial programs. However, it is possible to contend that skill-based training could be associated with an increase, a decrease, or no change in fisk-taking behavior. In 3 experiments, the authors examined the influence of a skill-based training program (hazard perception) on the fisk-taking behavior of car drivers (using video-based driving simulations). Experiment 1 demonstrated a decrease in risk taking for novice drivers. In Experiment 2, the authors examined the possibilities that the skills training might operate through either a nonspecific reduction in risk taking or a specific improvement in hazard perception. Evidence supported the latter. These findings were replicated in a more ecological context in Experiment 3, which compared advanced and nonadvanced police drivers.

An advanced real-time predictive maintenance framework for large scale machine systems

This thesis introduces and develops a novel real-time predictive maintenance system to estimate the machine system parameters using the motion current signature. Recently, motion current signature analysis has been addressed as an alternative to the use of sensors for monitoring internal faults of a motor. A maintenance system based upon the analysis of motion current signature avoids the need for the implementation and maintenance of expensive motion sensing technology. By developing nonlinear dynamical analysis for motion current signature, the research described in this thesis implements a novel real-time predictive maintenance system for current and future manufacturing machine systems. A crucial concept underpinning this project is that the motion current signature contains infor­mation relating to the machine system parameters and that this information can be extracted using nonlinear mapping techniques, such as neural networks. Towards this end, a proof of con­cept procedure is performed, which substantiates this concept. A simulation model, TuneLearn, is developed to simulate the large amount of training data required by the neural network ap­proach. Statistical validation and verification of the model is performed to ascertain confidence in the simulated motion current signature. Validation experiment concludes that, although, the simulation model generates a good macro-dynamical mapping of the motion current signature, it fails to accurately map the micro-dynamical structure due to the lack of knowledge regarding performance of higher order and nonlinear factors, such as backlash and compliance. Failure of the simulation model to determine the micro-dynamical structure suggests the pres­ence of nonlinearity in the motion current signature. This motivated us to perform surrogate data testing for nonlinearity in the motion current signature. Results confirm the presence of nonlinearity in the motion current signature, thereby, motivating the use of nonlinear tech­niques for further analysis. Outcomes of the experiment show that nonlinear noise reduction combined with the linear reverse algorithm offers precise machine system parameter estimation using the motion current signature for the implementation of the real-time predictive maintenance system. Finally, a linear reverse algorithm, BJEST, is developed and applied to the motion current signature to estimate the machine system parameters.