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Generating data

At pressures above the highest real data point, the extrapolated data were generated by the correlation of Lyckman et al. (1965), modified slightly to eliminate any discontinuity between the real and generated data. This modification is small, only a few percent, well within the uncertainties of the Lyckman method. The Lyckman correlation was always used within its recommended limits of validity--that is, at reduced temperatures no greater than 1.5 to 2.0. [Pg.139]

This paper describes the procedure generation, data acquisition and data visualisation functions of the CantuS system. [Pg.766]

Typical Generation Rates Typical unit waste-generation rates for selected industrial sources are reported in Table 25-54. Because waste-generation practices are changing so rapidly, the presentation of typical waste-generation data may not be rehable. [Pg.2234]

The sources of data for this report were associated with NUREG-0737, (c) Diesel generator data submitted to the USNRC in response to a questionnaire prepared as part of the study. [Pg.115]

Generation data to complement the planning study were plentiful. As long as the utilities owned the physical facilities and were in control of future facility expansion, data were generally a nonissue. The parameters of generating plants were dialed into the calculations or computers, similar to transmission. Obviously, alternate locations for new plants could be evaluated, and oftentimes studies were finalized some ten years ahead of construction, with only limited analysis required as the in-seivicc date approached. [Pg.1200]

Both of these factors are difficult. Obtaining representative samples of filamentous organisms from cultures is difficult and both substrate and product are relatively insoluble. Thus it is difficult to monitor these processes. Nevertheless, in practice satisfactory procedures have been developed to generate data that are sufficiently accurate to enable reasonable monitoring of cultures. [Pg.315]

Now, we can generate data by plug-in numbers in the above equation. We need to illustrate inverse rate versus substrate concentration. After the data are plotted we can justify a suitable type of bioreactor... [Pg.300]

Refers to the physical substrate to which biological samples are attached to create features (spots). In gene expression profiling arrays are hybridized with labeled sample and then scanned and analyzed to generate data. [Pg.222]

Purpose Generate data sets using mixed deterministic/stochastic models with N = 1. .. 1000. These data sets can be used to test programs or to do Monte Carlo studies. Five different models are predefined sine wave, saw tooth, base line, GC-peaks, and step functions. Data file SIMl.dat was... [Pg.380]

Raw data is almost always incomplete, being highly dependent on the data production platform and often localized to a platform or regional database. Applications (and processes) generate data. However, applications often use proprietary data types and cannot parse data types from other third-party applications. It is important to consider that there are translation issues plus the host of reasons stated below in the requirements for data standards. [Pg.174]

Figure 2. Typical computer-generated data analysis report... Figure 2. Typical computer-generated data analysis report...
In the earliest SFG experiments [Tadjeddine, 2000 Guyot-Sionnest et al., 1987 Hunt et al., 1987 Zhu et al., 1987], a first-generation data acquisition method was used, and, because of the limited signal-to-noise ratios, IR attenuation by the electrolyte solution was a substantial handicap. So, in earlier SFG studies, as in IRAS studies, measurements were performed with the electrode pressed directly against the optical window [Baldelli et al., 1999 Dederichs et al., 2000]. With the in-contact geometry, the electrolyte was a thin film of uncertain and variable depth, probably of the order of 1 p.m. However, the thin nonuniform electrolyte layers can strongly distort the potential/coverage relationship and hinder the ability to study fast kinetics. [Pg.378]

For analytical methods used for generating data required in the field of residue behavior, environmental fate, and other fields, the guidance document SANCO/3029/99 rev. 4 was developed."... [Pg.20]

In contrast to the requirements for enforcement methods, validation of a previously collaboratively tested method, which is used to generate data, should be validated for new laboratory conditions. Also, where published methods are submitted, validation is required, when applied to the relevant sample matrix and laboratory conditions. [Pg.33]

In contrast to the requirements for enforcement methods and to ensure sufficient quality of the generated data, validation data should be submitted for all types of crop samples to be analyzed. However, matrix comparability and a reduced validation data set may be considered where two or more very similar matrices are to be analyzed (e.g., cereal grain). A reduced sample set may also be acceptable (two levels, at least three determinations and an assessment of matrix interference) provided that the investigated samples belong to the same crop group as described in SANCO/825/00 (see also Section 4.2.1). [Pg.34]

PCR analysis is one of the techniques used to generate data for the genetic analysis requirement. [Pg.669]

A brief summary of EPA method requirements for tolerance enforcement methods is given in Table 1. Taken in total, these requirements ensure that the means to conduct the method are available to laboratories and that experimental evidence to establish method performance, on a substrate-by-substrate basis, is generated prior to analysis of samples and as part of each analytical set. Thus, an analyst who must generate data to support method performance in his or her hands can obtain whatever is required to reproduce the method. [Pg.721]

In addition to incorporating the preceding elements into any metrology program, periodic audits of the calibration and maintenance practices should occur. This is particularly important for systems generating data that are subject to review by... [Pg.1042]

In order to audit effectively studies with electronically generated data, QA should create a special checklist or add electronic issues to a current checklist. The checklist should include items such as ensuring that the computer system in use is current and validated and that necessary maintenance is documented. [Pg.1049]

Chronic-Duration Exposure and Cancer. No data were located regarding chronic-duration exposure of humans or animals to americium. Chronic-duration inhalation and oral MRLs were not derived for americium due to the lack of human or animal data. To generate appropriate data for deriving chronic-duration inhalation and oral MRLs for americium, at least one comprehensive chronic-duration inhalation and one chronic-duration oral toxicity study of at least one animal species exposed to several dose levels would be needed. Such studies could be designed to also generate data regarding potential age-related differences in toxicity. However, since americium is not found naturally, and is produced and used... [Pg.120]

The purpose of the regulations was to ensure proper operation of laboratories that generated data to support either INDs or NDAs. In particular, they addressed animal studies, including animal care and animal accountability. They also involved the equipment used to do the various procedures for analysis and the maintenance and calibration of the equipment. In general, these regulations now cover the operation of the laboratories and how the data are collected and... [Pg.640]

Are records kept on the amount of waste generated per unit of production Provide specific waste generation data for the last 12 months. Identify the risk category. [Pg.13]


See other pages where Generating data is mentioned: [Pg.140]    [Pg.2818]    [Pg.94]    [Pg.1823]    [Pg.2167]    [Pg.157]    [Pg.128]    [Pg.442]    [Pg.445]    [Pg.130]    [Pg.438]    [Pg.102]    [Pg.102]    [Pg.106]    [Pg.135]    [Pg.756]    [Pg.28]    [Pg.373]    [Pg.298]    [Pg.20]    [Pg.929]    [Pg.941]    [Pg.1055]    [Pg.391]    [Pg.120]    [Pg.120]    [Pg.300]    [Pg.677]   
See also in sourсe #XX -- [ Pg.518 ]




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Data generation

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