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Changes in perception of on-the-job problems following laboratory training: IIFreedman, Arthur M. January 1963 (has links)
Thesis (M.B.A.)--Boston University
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Personal Protective Equipment and Laboratory Safety Training: The Roles of Attitude, Subjective Norm, and Perceived ControlRuffing, Ami A. 01 May 2013 (has links) (PDF)
Chemical and biological agents can cause serious adverse occupational health effects, and can adversely impact environmental health. Adverse incidents occur in laboratories using chemical, biological and radiologic agents, and laboratories pose a number of dangers to workers. Adverse incidents occur more frequently in teaching and research institutions when compared to industrial laboratories. Good laboratory safety practices, including the use of personal protective equipment, can reduce the number and severity of laboratory accidents, thus reducing the risk of chemical, biological and radiologic exposure for workers and for the public. Improving laboratory safety training should also result in fewer lab accidents. This study was conducted at a mid-sized Midwestern research university. The study population consisted of people who had attended a laboratory safety training session in 2010, 2011 or 2012. Following administration of a pilot survey and development of additional items, a sample (N=451) of the total population (N=936) received a survey inquiring about the use of personal protective equipment, and about laboratory safety training. 143 completed surveys were returned. The survey was based on the Theory of Planned Behavior (Ajzen, 1991). Theoretical constructs investigated included personal protective equipment attitude, subjective norm, behavioral control, behavioral intention, past self-reported behavior, and safety training attitude. Multiple regression showed that the overall model accounted for 56% of the variability in the study population. Subjective norm was the theoretical construct most strongly predictive of behavioral intention (B=.653, p=.001). Attitude was next most strongly predictive of intention (B=.343, p=.001). Behavioral control was not significantly correlated with behavioral intention. There was a positive significant correlation between training attitude and behavioral intention (Pearson's r = 0.233, p=.006, 2-tailed). There was also a positive significant correlation between attitude toward personal protective equipment, and attitude toward training (Pearson's correlation coefficient was 0.332, p=.001, 2-tailed). Self-reported behavior was regressed on the three theoretical constructs. Subjective norm was most significantly predictive of self-reported behavior (B = .523, p= .001), followed by attitude (B = .281, p= .034). Behavioral control was not significantly predictive of self-reported behavior. The study determined that about 80% of respondents felt that their lab was usually or always a safe place to work, although 40% reported having been injured in a lab. Training can be improved by emphasizing the importance of subjective norm, by clarifying the responsibilities of lab supervisors, and by providing additional information regarding how to obtain, use, and care for personal protective equipment. Use of personal protective equipment may be increased by emphasizing the importance of subjective norm during training.
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Využití teorie hromadné obsluhy při návrhu a optimalizaci paketových sítí / Queueing theory utilization in packet network design and optimization processRýzner, Zdeněk January 2011 (has links)
This master's thesis deals with queueing theory and its application in designing node models in packet-switched network. There are described general principles of designing queueing theory models and its mathematical background. Further simulator of packet delay in network was created. This application implements two described models - M/M/1 and M/G/1. Application can be used for simulating network nodes and obtaining basic network characteristics like packet delay or packet loss. Next, lab exercise was created, in that exercise students familiarize themselves with basic concepts of queueing theory and examine both analytical and simulation approach to solving queueing systems.
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