Deviation concept

Kjelldn, U. The deviation concept in occupational accident control. Part I Definition and classification and part II Data collection and assessment of significance. Accident Analysis Prevention 16 289-323, 1984. 

Kjellen, U. 1984. The Deviation Concept in Occupational Accident Control, Part I Definition and Classifieation and Part II Data CoUeetion and Assessment of Significance, Accident Anal Prev 16 289—323. 

Deviation concept Ergonomic and behavioral methods Kjellen 1984a, b... 

Both the integrative model by Smillie Ayoub (1975) and the deviation concept by Kjellen (1984a) connect the general systems theory to the sequencing and energy models of accident causation. They encompass technical, organizational and human components of the system. Various methods of system safety analysis (e.g. fault tree analysis, incidental factor analysis) support the identification of technical and human deviations as well as the analysis of the conditions and consequences of these deviations. From the discussion of near misses and conflicts it became clear that frameworks of accident causation should cover all kinds of incidents, thus becoming frameworks of incidents. 

Kjellen, U., The deviation concept in occupational accident control-I, definition and classification. Accident Analysis Prevention, 1984(a), 15, pp. 289-306. 

This point of view is consistent with modern safety approaches, e.g, the deviation concept (Kjellen 1984) or the systems approach (Summala 1985). Human performance variables such as the reliability of monitoring, fault detection, and action are expected to vary to a normal extent. The range of variation from excellent to poor is determined by physiological, psychological, and social causes. The boundaries are established by task requirements. A performance variable is classified as a deviation when its value falls outside the boundary or norm, and together with other technical deviations may lead to an accident. This may not only be valid for individual and technical factors, but also for organizational measures (Kjellen Larsson 1981). 

Nothing can be stated about the validity of either of these hypotheses when based on accident distributions only. Special methods and procedures are necessary. Studies which attempt to estimate the combined effects of person and environmental variables in areas other than accident research are becoming more common (Mischel 1968). In the area of accident research there are only a few studies which allow for the estimation of the situational and personal involvement in the accident process. Marek Sten s (1977) aspiration of a differential hypothesis is yet to be actualized the deviation concept (Hale S Perusse 1978, Kjellen 1984) is a promising start in this area. 

Discussion of the concepts and procedures involved in designing packed gas absorption systems shall first be confined to simple gas absorption processes without compHcations isothermal absorption of a solute from a mixture containing an inert gas into a nonvolatile solvent without chemical reaction. Gas and Hquid are assumed to move through the packing in a plug-flow fashion. Deviations such as nonisotherma1 operation, multicomponent mass transfer effects, and departure from plug flow are treated in later sections. 

The degree of data spread around the mean value may be quantified using the concept of standard deviation. O. If the distribution of data points for a certain parameter has a Gaussian or normal distribution, the probabiUty of normally distributed data that is within Fa of the mean value becomes 0.6826 or 68.26%. There is a 68.26% probabiUty of getting a certain parameter within X F a, where X is the mean value. In other words, the standard deviation, O, represents a distance from the mean value, in both positive and negative directions, so that the number of data points between X — a and X -H <7 is 68.26% of the total data points. Detailed descriptions on the statistical analysis using the Gaussian distribution can be found in standard statistics reference books (11). 

The estimation of the mean and standard deviation using the moment equations as described in Appendix I gives little indication of the degree of fit of the distribution to the set of experimental data. We will next develop the concepts from which any continuous distribution can be modelled to a set of data. This ultimately provides the most suitable way of determining the distributional parameters. 

The ideal concept is usually a good approximation for close boiling components of a system, wherein the components are all of the same family of hydrocarbons or chemicals for example paraffin hydrocarbons. When odd or non-family components are present, the possibility of deviations from non-ideality becomes greater, or if the system is a wide boiling range of components. 

Many process components do not conform to the ideal gas laws for pressure, volume and temperature relationships. Therefore, when ideal concepts are applied by calculation, erroneous results are obtained—some not serious when the deviation from ideal is not significant, but some can be quite serious. Therefore, when data are available to confirm the ideality or non-ideality of a system, then the choice of approach is much more straightforward and can proceed with a high degree of confidence. 

The heart of the question of non-ideality deals with the determination of the distribution of the respective system components between the liquid and gaseous phases. The concepts of fugacity and activity are fundamental to the interpretation of the non-ideal systems. For a pure ideal gas the fugacity is equal to the pressure, and for a component, i, in a mixture of ideal gases it is equal to its partial pressure yjP, where P is the system pressure. As the system pressure approaches zero, the fugacity approaches ideal. For many systems the deviations from unity are minor at system pressures less than 25 psig. 

The importance of the method in corrosion testing and research has stimulated other work, and since Stern s papers appeared there have been a number of publications many of which question the validity of the concept of linear polarisation. The derivation of linearity polarisation is based on an approximation involving the difference of two exponential terms, and a number of papers have appeared that have attempted to define the range of validity of polarisation resistance measurements. Barnartt" derived an analytical expression for the deviations from linearity and concluded that it varied widely between different systems. Leroy", using mathematical and graphical methods, concluded that linearity was sufficient for the technique to be valid in many practical corrosion systems. Most authors emphasise the importance of making polarisation resistance measurements at both positive and negative overpotentials. 

So how does one infer that two samples come from different populations when only small samples are available The key is the discovery of the t-distribution by Gosset in 1908 (publishing under the pseudonym of Student) and development of the concept by Fisher in 1926. This revolutionary concept enables the estimation of ct ( standard deviation of the population) from values of standard errors of the mean and thus to estimate... 

It is worth emphasizing that although overpotentials are usually associated with electrode-electrolyte interfaces, in reality they refer to, and are measured as, deviations of the potential (

associated with an electrode and not with an electrode-electrolyte interface, although the nature of this interface will, in general, dictate the magnitude of the measured overpotential. 

A more general access to biologically important and structurally more diverse aldose isomers makes use of ketol isomerases for the enzymatic interconversion of ketoses to aldoses. For a full realization of the concept of enzymatic stereodivergent carbohydrate synthesis, the stereochemically complementary i-rhamnose (Rhal EC 5.3.1.14) and i-fucose isomerases (Fuel EC 5.3.1.3) from E. coli have been shown to display a relaxed substrate tolerance [16,99,113,131]. Both enzymes convert sugars and their derivatives that have a common (3 J )-OH configuration, but may deviate in... 

Sxx is the sum of squares of the residuals, r, that are obtained when the average value Xmean is subtracted from each observation a ,. Xmean is the best estimate for the true mean fj.. When discussing theoretical concepts or when the standard deviation is precisely known, a small Greek sigma, a, is used in all other cases, the estimate Sx appears instead. 

For standard deviations, an analogous confidence interval CI(.9jr) can be derived via the F-test. In contrast to Cl(Xmean), ClCij ) is not symmetrical around the most probable value because by definition can only be positive. The concept is as follows an upper limit, on is sought that has the quality of a very precise measurement, that is, its uncertainty must be very small and therefore its number of degrees of freedom / must be very large. The same logic applies to the lower limit. s/ ... 

In the previous sections of Chapter 2 it was assumed that the standard deviation obtained for a series of repeat measurements at a concentration X would be the same no matter which x was chosen this concept is termed homoscedacity (homogeneous scatter across the observed range). 

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