Analyzing Graphical Data

13 A fluid of viscosity /x and density p flows at velocity v through a rough pipe of diameter d when pressure drop A P is applied over a length /. With all other parameters held constant, AP is varied and v is measured. 

14 A fluid is pumped through a pipe that contains an orifice plate. The diameter of the orifice is half the diameter of the pipe, D.  

15 As discussed in Section 5.8, heat transfer to a fluid flowing through a tube may be described 

16 Heat transfer from a solid sphere moving through a fluid is characterized by three dimensionless numbers the Nusselt number (Nu), the Reynolds number (Re), and the Prandtl number (Pr), defined as 

Calculate h for a solid sphere of diameter = 3.7 mm moving through water at velocity = 0.29 m/sec. 

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At the present time the only online facility that we provide for analyzing the data is the display function, which provides graphical outputs tailored to the data in the diffraction data files. The user specifies the run number for the data he wishes to plot. The display program then loads the header from the appropriate data file and determines what kind of plot to display. The user can dump the resulting plot to the printer to provide a record of his experiment. The "revise file" function can be used to create auxiliary files for plotting selected features of the data. 

Cleveland, W.S. and McGill, R. (1985). Graphical perception and graphical methods for analyzing scientific data. Science 229 828-833. 

McGovern et al.26 analyzed the expression of heterologous proteins in E. coli via pyrolysis mass spectrometry and FT-IR. The application was to a2-interferon production. To analyze the data, artificial neural networks (ANN) and PLS were utilized. Because cell pastes contain more mass than the supernatant, these were used for quantitative analyses. Both the MS and IR data were difficult to interpret, but the chemometrics used allowed researchers to gain some knowledge of the process. The authors show graphics indicating the ability to follow production via either technique. 

There is no mention of control charts or other graphical QC tools (see chapter 4). There is a note that the selected methods should be appropriate for the type and volume of the work undertaken. As part of the emphasis on the overall quality framework, the standard now requires a laboratory to analyze QC data and to implement corrective action if results are outside predefined criteria. 

Simple peak purity analysis is relatively accurate when the impurity is present at significant concentration levels but, as the level of impurity diminishes, its impact on the target analyte spectrum becomes subtler and may require more sophisticated techniques. For this, statistical software routines are available for automated spectral comparisons. In these cases, peak purity determination and analysis of spectral differences are achieved using vector analysis algorithms. The more similar the spectra are, the closer the value is to 0.0° the more spectrally different they are, the larger the value. All the spectral data points across the peak are analyzed the data are converted into vectors, compared, and graphically plotted so that the results can be visualized. These software routines provide both numerical results and graphical representations such as similarity and threshold curves. 

The data will be analyzed graphically by plotting the volume of hydrogen gas produced vs. time for each set of conditions. By comparing the slopes of each graph, we will be able to determine how changing the variables affect the rate of the chemical reaction. 

With this method, disparities in the data are easily seen. Consequently, it is advantageous to use this technique to analyze the data before planning the next set of experiments. As explained in Appendix A.2, the graphical method involves plotting -ACa/A as a function of / and then using equal-area differentiation to obtain An illustrative example is also given in... 

Jordan, M. L, Ed. Learning in Graphical Models, MIT Press Cambridge, MA, 1999. Friedman, N. Lineal, M. Nachman, I. Pe er, D. Using Bayesian networks to analyze expression data. J. Comp. Biol. 2000, 7, 601-620. 

Another type of graphical plot used to analyze kinetic data is the Hanes-Woolf plot (Fig. 4.3). In this case, [S]/v is plotted along the y-axis and [S] is plotted along the x-axis. For this plot, the x-intercept = — the y-intercept = m/Finax nd the slope of the best-fit line estimates l/Vmax- The Hanes-Woolf... 

A network management station (NMS) is a centralized workstation or computer that collects data from agents over a network, analyzes the data, and displays information in graphical form. 

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