Noise, performance-influencing factors

At the next organizational level are factors directly causing error 1) job characteristics such o Complexity, time stress, noise, lighting, environment, or mental requirements, and 2) individual factors such as personality, and team performance. These, collectively, are called performance-influencing factors, or PIFs. 

Environmental factors may influence man s performance level either positively, negatively, or not at all. Among the most important environmental factors in the workplace are lighting and color dynamics, noise and sounds, vibrations, climate, and chemical substances. Environmental influence factors, in general, can be perceived by means of the sensory organs. Some exceptions are chemical substances, invisible irradiation, and inaudible sound. 

The main purpose for the heating and air conditioning of work spaces is to provide an environment that is acceptable and does not impair the health and performance of the occupants. During production processes and in the external environment it may be necessary to work in unacceptable conditions for a limited time period. However, it must be ensured that these conditions do not impair the health of the employees. Light, noise, air quality, and the thermal environment are all factors that influence the acceptability of conditions for and performance of the occupants. This section will only deal with the thermal environment. Several standards dealing with methods for the evaluation of the thermal environment have been published by international standard organizations such as ISO and CEN. 

MEMS devices have to meet certain criteria with respect to their functional parameters, for example, a scale factor, offset of the output value, temperature coefficient, nonlinearity, hysteresis, noise, resolution, and cross sensitivities, which characterize the system s performance. In addition, we are interested in the reliability, yield, and cost of the devices. The set of functional parameters depends on a set of model parameters, consisting of processing, material, and geometrical parameters. All model parameters act as input parameters for the design procedure as well as for the manufacturing process. Material parameters are influenced by... 

A.K. Elbergali and R.G. Brereton, Influence of Noise, Peak Position and Spectral Similarities on Resolvability of Diode-Array High-Performance Liquid Chromatography by Evolutionary Factor Analysis, Chemometrics Intelligent Laboratory Systems 23 (1994), 97-106. 

A.K. Elbergali, R.G. Brereton and A. Rahmani, Influence of the Method of Calculation of Noise Thresholds on Wavelength Selection in Window Factor Analysis of Diode Array High-Performance Liquid Chromatography, Analyst (London) 121 (1996), 585-590. 

An area of analytical chemistry very well suited to optimization strategies is high-performance liquid chromatography (HPLC). Many papers and a recent book have focused on simplex optimization experiments in this area. Among the factors that influence a chromatographic experiment, many are controllable and thus are susceptible to optimization, but some are not. Examples of uncontrollable faaors include noise, drift, and column performance. Examples of controllable factors include flow rates of mobile phase, mobile phase composition, and temperature. 

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