A system response time model for local area networks

To predict the potential cost effectiveness of computer assisted information processing in the District Offices (DOs) of the Social Security Administration (SSA), we developed a model of manpower allocation in present DO operations. We adapted existing SSA management data sources to quantify this baseline model. We also constructed a description of the changes in manpower requirements expected to occur on introduction of a hypothetical computer assisted system. We used analyses of user functional requirements to determine overall system capabilities. We used the results of user performance trials on a simulated system to quantify this change model. Significant reductions in manpower for processing of individual claims in the DO appear to be attainable. Computer system response time was identified as a controllable design characteristic with a strong effect on manpower requirements. Introduction of computer assistance to the DO could free manpower from mechanical clerical activities for application to more creative and professional functions. This manpower could be applied to expansion of SSA services and to improvement of DO service quality. An overall increase of 25% to 33% in workload processing capacity appears potentially attainable with computer assistance at current DO manpower levels. Suitable workstations might be based on use of individual personal computers or on sharing the resources of a single larger machine among a number of users. Consideration of relative costs and benefits suggests that the personal computer approach, while initially more costly, offers better control over system response time, which can have a major effect on system acceptance and cost effectiveness. It is likely that computer assistance for DOs will be deployed through workstations based on individual personal machines. Full recovery of capital investment can potentially be achieved in two years of actual operation.

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Localizing subprocesses of visual search by correlating local brain activation in fMRI with response time model parameters

Journal of Neuroscience Methods ◽

10.1016/j.jneumeth.2008.03.010 ◽

2008 ◽

Vol 171 (2) ◽

pp. 316-330 ◽

Cited By ~ 5

Author(s):

Gisela Müller-Plath

Keyword(s):

Visual Search ◽

Response Time ◽

Brain Activation ◽

Model Parameters ◽

Time Model ◽

Response Time Model ◽

Local Brain

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Computer System Response Time and Psychophysiological Stress II

Proceedings of the Human Factors Society Annual Meeting ◽

10.1177/154193128202600805 ◽

1982 ◽

Vol 26 (8) ◽

pp. 698-702 ◽

Cited By ~ 8

Author(s):

Stuart Martin Weiss ◽

George Boggs ◽

Mark Lehto ◽

Sogand Shodja ◽

David J. Martin

Keyword(s):

Response Time ◽

Repeated Measures ◽

Psychological Impact ◽

Industrial Process ◽

Interactive Systems ◽

Upper And Lower Bounds ◽

System Response ◽

User Performance ◽

Experimental Conditions ◽

System Response Time

With the advent of time-shared interactive systems, the psychological impact of system response time (SRT) and SRT variability (SRTV) has become an important issue. Carbonell, et. al. (1968) have suggested that both SRT and SRTV may influence system user performance and satisfaction. A number of studies have been reported that address this issue, but results have been mixed. In this experiment, twenty subjects ( Ss) executed keyboard entries to control the temperature of a simulated industrial process via time-shared process control computer. Temperature was displayed in analog form on a CRT. The task was to maintain the temperature within upper and lower bounds that were clearly indicated on the display. The experimental design consisted of repeated measures with SRT and SRTV as experimental factors. Three SRT's were employed (2, 6 and 10 seconds) with two levels of SRTV (σ2 = 0 and σ2 = 0.33 seconds). Mean blood pressure (MBP) and heart rate (HR) were continuously monitored during experimental conditions. Task errors were defined as temperature excursions beyond the displayed bounds. Significant main effects were not obtained for MBP or HR. Significant differences for error rate (performance) were noted for SRT ( F(2, 15) = 23.10, p < .05), subjects x SRT ( F37, 15) = 1.66, p < .001), and SRT x SRTV ( F(1, 15) = 13.14, p < .05). Error data are consistent with the Carbonell et. al. suggestion that long and variable SRT may affect user performance. The results are discussed in terms of their incongruity with current literature.

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