Interpretation of data

Engineering geologists recognize, interpret, and assess the data acquired during a high-resolution geophysical survey. The purpose is to identify the potential significant 

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Repeatability. This refers to two aspects of inspection similarity between objects that are inspected and possibility of maintaining constant inspection conditions (settings) for all the inspections performed. Obviously, interpretation of data in repeatable conditions is significantly simplified. Usually, inspection during or after manufacturing process will be repeatable. Another example of repeatable inspection is inspection of heat exchangers in power nuclear plants, inspection of aircrafts as these are well standardised. However, a large part of the NDT inspection done is not repeatable. 

The first system called LiSSA has been developed for interpretation of data from eddy-current inspection of heat exchangers. The data that has to be interpreted consists of a complex impedance signal which can be absolute and/or differential and may be acquired in several frequencies. The interpretation of data is done on the basis of the plot of the signal in the impedance plane the type of defect and/or construction is inferred from the signal shape, the depth from the phase, and the volume is roughly proportional to the signal amplitude. 

Documentation of experimental method so that work can be reproduced at a later time Appropriate data handling statistical methods conclusions based on fact, supportable by data Define and execute critical experiments to prove or disprove hypothesis Mechanistic or fundamental interpretation of data preferred Communication of Conclusions to Incorporate Technical Learning in Organization Experimental W rk Done in Support of New or Existing Processes Should be Captured in Process Models... 

Rules of matrix algebra can be appHed to the manipulation and interpretation of data in this type of matrix format. One of the most basic operations that can be performed is to plot the samples in variable-by-variable plots. When the number of variables is as small as two then it is a simple and familiar matter to constmct and analyze the plot. But if the number of variables exceeds two or three, it is obviously impractical to try to interpret the data using simple bivariate plots. Pattern recognition provides computer tools far superior to bivariate plots for understanding the data stmcture in the //-dimensional vector space. 

A scientific basis for the evaluation and interpretation of data is contained in the accompanying table descriptions. These tables characterize the way in which sample values will vary by chance alone in the context of individual obsei vations, averages, and variances. 

Warnings are noted in the literature to be careful in the interpretation of data from electrochemical techniques applied to systems in which complex and often poorly understood effects are derived from surfaces which contain active or viable organisms, and so forth. Rather, it is even more important to not use such test protocol unless the investigator fuhy understands both the corrosion mechanism and the test technique being considered—and their interrelationship. 

Virolainen, R 1984, On Common Cause Failures Statistical Dependence and Calculation of Uncertainty Disagreement in Interpretations of Data, Nuc. Eng. and E 77 pp 103-108. 

There are three major limitations with using tribology analysis in a predictive maintenance program equipment costs, acquiring accurate oil samples and interpretation of data. 

Interpretation of data obtained under the conditions of uniaxial extension of filled polymers presents a severe methodical problem. Calculation of viscosity of viscoelastic media during extension in general is related to certain problems caused by the necessity to separate the total deformation into elastic and plastic components [1]. The difficulties increase upon a transition to filled polymers which have a yield stress. The problem on the role and value of a yield stress, measured at uniaxial extension, was discussed above. Here we briefly regard the data concerning longitudinal viscosity. 

The interpretation of data on the change of Kp as a result of the reduction treatment of the chromium oxide catalyst (97) is hindered by the absence of precise data on the composition of the surface complexes being formed. 

Although considerable effort has been made to present this informatioh as accurately as possible, mistakes and errors in transcription and translation do occur. Therefore, the authors encourage the readers to consult original sources, when possible, and to feel free to point out errors and omissions of important works so that corrections and additions can be listed in the next volume. The interpretations of data and opinions expressed are often those of the authors and are not necessarily those nor the responsibility of officials of ARRADCOM or the Department of the Army... 

Chemical treatment programs are designed to promote clean internal waterside surfaces, but continuous freedom from deposition and corrosion requires excellent operational control. Application of products, regular monitoring, and comparison of analytical results with recognized standards and interpretation of data are all important components of the program. 

Kabanov [351] has provided an excellent review of the application of measurements of electrophysical effects in studies of the thermal decomposition of solids, including surveys of electrical conductivity, photoconductivity, dielectric measurements and interface (contact), Hall and thermal (Seebeck) potentials. Care must be exercised in applying the results obtained in such studies to the interpretation of data for thermal decomposition in the absence of an applied electric field since many examples have been given [352] in which such a field markedly influences the course of decomposition. 

The presence of three polypeptides in Table 5.8 tliat were not predicted from the relationship between the amino acid sequence and the enzyme used for digestion is worthy of note when interpretation of data of this sort is undertaken. The MALDI data showed six further unexpected polypeptides, none of which were detected in the LC-MS data ... 

Our research design, shown in Fig. 13.1, followed the typical action research cycle as proposed by Ferrance (2000) which involves the following five phases (1) Identification of problem area, (2) Collection and organisation of data, (3) Interpretation of data, (4) Action based on data and (5) Refiection and evaluation of results. Finally, the results are used in a new cycle of research. 

Overlooking others use of flawed data or questionable interpretation of data... 

On many occasions the file has provided Information about effects of drugs of which the user was previously unaware. Undoubtedly this has helped the care of some patients. We are aware of several cases In which prolonged workups of unusual test values were avoided because of the simple explanations provided by the file. We expect to expand the application of the file by Introducing It In a revised form Into several hospitals for online Interpretation of data. Also, discussions have been held with several different Institutions overseas to set up national centers for dissemination of Information and to provide a better monitoring of foreign language publications to augment the content of the file. 

Such conformational dependence presents challenges and an opportunity. The challenges he in properly accounting for its consequences. In many cases, exact conformational energetics and populations in a sample may be unknown, and the nature of the sample inlet may sometimes also mean that a Boltzmann distribution cannot be assumed. Introducing this uncertainty into the data modeling process produces some corresponding uncertainty in the theoretical interpretation of data... 

The results of environmental monitoring exercises will be influenced by a variety of variables including the objectives of the study, the sampling regime, the technical methods adopted, the calibre of staff involved, etc. Detailed advice about sampling protocols (e.g. where and when to sample, the volume and number of samples to collect, the use of replicates, controls, statistical interpretation of data, etc.) and of individual analytical techniques are beyond the scope of this book. Some basic considerations include the following, with examples of application for employee exposure and incident investigation. 

Grunwald, E. (1954). Interpretation of data obtained in nonaqueous media. 

The latter interpretation of data is more in accord with the recent Al and Si NMR findings of Ellison Warrens (1987), who found that the structure of an appreciable fraction of the glass changed under acid attack with some loss of aluminium including all in fivefold coordination (see Section 5.9.2). Thus, acid attack was not entirely confined to the surface layer of a glass particle. If this is so then silicic acid as well as ions must migrate from the body of the particle and it is reasonable to suppose that silicic acid deposits as siliceous gel at the particle-matrix interface. 

To identify ancillary data needs and potential confounding factors that should be considered or documented to ensure the defensible interpretation of data on monitored biological indicators... 

This book proposes a monitoring program that will help determine trends for mercury concentrations in the environment and assess the relatiorrship between these concentrations and mercnry emissions. Environmental models are also often used to predict trends and examine relationships among variables. Models can facilitate the interpretation of data emerging from monitoring programs recommended in this book and that the data will help develop better modehng tools. 

There are a number of other problems relating to the manipulation and interpretation of data that cause difficulty. The most common are (i) uncertainty about the number of replicate results required for proper comparison of the certified reference value, and (2) the actual analytical result and how gross outlier results should be handled. These issues and how to deal with data that falls outside the confidence limit are reviewed in detail by Walker and Lumley (1999), who conclude that whilst customer requirements may provide answers the judgement of the analyst must always be the final arbiter in any decision ... 

A mass of evidence seems to confirm that the mixing rate of radiocarbon in the atmosphere is rapid, and that with respect to its radiocarbon content the atmosphere can be considered as a homogeneous entirety. The contamination of samples with matter from an extraneous source can nevertheless invalidate this assumption. Two types of contamination can be differentiated physicochemical contamination and mechanical intrusion. There are two forms of physicochemical contamination. One is due to the dilution of the concentration of radiocarbon in the atmosphere by very old carbon, practically depleted of radiocarbon, released by the combustion of fossil fuel, such as coal and oil. The other is by the contamination with radiocarbon produced by nuclear bomb tests during the 1950s and later in the twentieth century. The uncertainties introduced by these forms of contamination complicate the interpretation of data obtained by the radiocarbon dating method and restrict its accuracy and the effective time range of dating. 

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