Functional verification

Analytical verification Functional evaluation Parts and materials definition Preliminary reliability verification... 

Therefore, the verifications, functional safety assessments and audits recommended by ANSI/ISA-84.00.01-2004 should be used to ensure that the requirements defined in the hazard and risk analysis are met and that predictable failures do not defeat the intent of safety requirements specification. 

L.7.1.3.3 Due to the inherent complexities of software development, validation, and verification, functional testing alone may not be sufficient to ensure changes to software versions will not negatively impact the new version s use in an SIS. 

The first step of safety verification is to verify that the software requirements are consistent with or satisfy safety constraints. Safety verification exists to provide evidence that associated risk has been reduced or eliminated [1]. Safety verification is not the same as functional verification. Functional verification assures that the software fully satisfies its specifications, while safety verification uses the results of the safety analysis process to assure that the software meets the safety requirements [20]. The safety verification can be done in two ways [1] (1) static analysis which looks over the code and design documents of the system (e.g. fault tree, formal verification) and (2) dynamic analysis requires the execution of the software to check all of the systems safety features. Static analysis is the same as a structured code review. Systems can be proven to match requirements, but it will not catch any safety states that the requirements miss [Ij. The dynamic analysis has the ability to catch unanticipated safety problems, but it cannot prove that a system is safe (e.g. software testing). 

The necessary material to perform annual verification of flaw detector is mainly composed of an electronic function generator, an external calibrated attenuator and an oscilloscope. 

The uncertainties in choice of potential function and in how to approximate the surface distortion contribution combine to make the calculated surface energies of ionic crystals rather uncertain. Some results are given in Table VII-2, but comparison between the various references cited will yield major discrepancies. Experimental verification is difficult (see Section VII-5). Qualitatively, one expects the surface energy of a solid to be distinctly higher than the surface tension of the liquid and, for example, the value of 212 ergs/cm for (100)... 

Review Follow-up Verification In addition to someone tracking the follow-up through progress reports, responsibility should be assigned to verify that any process changes were ac tuaUy made in the field. This verification can be done by a review team as part of a process pre-start-up review. It could also be part of the project team management responsibihty or assigned to a particular functional (i.e., safety and loss prevention) representative. The closure of the review process is complete once implementation is verified. 

The standard requires a /ayout inspection and a functional verification to applicable customer engineering material and performance standards to be performed for all products at a frequency specified in the control plan. 

There are two systems used for maintaining the accuracy and integrity of measuring devices a calibration system and a verification system. The calibration system determines the accuracy of measurement and the verification system determines the integrity of the device. If accuracy is important then the device should be included in the calibration system. If accuracy is not an issue but the device s form, properties, or function is important then it should be included in the verification system. You need to decide the system in which your devices are to be placed under control and identify them accordingly. 

Where and to the extent that the availability of technical data pertaining to the measurement devices is a specified requirement, the standard requires such data to be made available, when required fay the customer or customer s representative, for verification that it is functionally adequate. 

With remarkable accuracy, Democritus in the fifth century B.C. set the stage for modem chemistry. His atomic theory of matter, which he formulated without experimental verification, still stands, more or less intact, and encapsulates the profound truth that nature s stunning wealth boils down to atoms and molecules. As science uncovers the mysteries of the world around us, we stand ever more in awe of nature s ingenious molecular designs and biological systems nucleic acids, saccharides, proteins, and secondary metabolites are four classes of wondrous molecules that nature synthesizes with remarkable ease, and uses with admirable precision in the assembly and function of living systems. 

The LC-FTIR part of the study was concerned with the verification of the presence of particular functional groups within each of the tryptic fragments and will not be considered any further here. 

A more complete discussion of the kinetics of isocyanate crosslinking in the presence of humidity along with experimental verification of the rate equations used above has been given by van der Ven, et al. (18). Equations 38 and 39 can be integrated numerically for different values of isocyanate to hydroxy ratio and H. Plots of the consumption of hydroxy and isocyanate functionality are shown in Figure 2 for H-0 and H-0.66 assuming equal Initial Isocyanate and hydroxy levels. High humidity increases the rate of consumption of isocyanate and reduces the consumption of hydroxy. 

Application verification (AV) monitors are devices that are placed within test plots to measure actual spray deposition that occurred during application. The main function of AV monitors is to show whether or not the intended amount of test material was actually deposited on the soil surface. Application monitors consisting of soil-filled containers, paper disks, polyurethane foam plugs, and glass Petri dishes have all been used successfully for this purpose. Prior to using a monitor in the field, it is important to determine that the test substance can indeed be successfully extracted from the monitor and that the compound will be stable on the monitor under field conditions... 

Fig 3.21. Rate of oxygen removal from a ZnO film (a.u.) as a function of s of water-dioxane mixtures (verification of the equation (3.29)). 

Monomers employed in a polycondensation process in respect to its kinetics can be subdivided into two types. To the first of them belong monomers in which the reactivity of any functional group does not depend on whether or not the remaining groups of the monomer have reacted. Most aliphatic monomers meet this condition with the accuracy needed for practical purposes. On the other hand, aromatic monomers more often have dependent functional groups and, thus, pertain to the second type. Obviously, when selecting a kinetic model for the description of polycondensation of such monomers, the necessity arises to take account of the substitution effects whereas the polycondensation of the majority of monomers of the first type can be fairly described by the ideal kinetic model. The latter, due to its simplicity and experimental verification for many systems, is currently the most commonly accepted in macromolecular chemistry of polycondensation processes. 

From the fact that the photocatalytic effect K is a function of ev (or ev+) there arises the necessity to correlate the magnitude of the effect and the initial (dark) electrical conductivity of a semiconductor. Let us return to the reactions considered in the present article. The lower the electronic component of conductivity and the greater the hole component at a given temperature, i.e., the greater is the value of v- (the influence of the surface on the conductivity is neglected, this being permissible in the case of fairly massive semiconductors), the higher is the K in absolute value [[see formulas (68), (84), (95)], i.e., the more pronounced is the photocatalytic effect. Experimental verification of this theoretical prediction would be of interest. 

Robustness It is difficult for any user to destroy the watermark without downgrading the quality, or altering the functionality of the object. Therefore, even when a watermarked object is modified by a malicious user, the verification algorithm still succeeds with high probability when run by the possessor, but nevertheless succeeds with low probability when carried out by malicious users. 

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