Attribute value

In Fig. 42.9 we show the simulation results obtained by Janse [8] for a municipal laboratory for the quality assurance of drinking water. Simulated delays are in good agreement with the real delays in the laboratory. Unfortunately, the development of this simulation model took several man years which is prohibitive for a widespread application. Therefore one needs a simulator (or empty shell) with predefined objects and rules by which a laboratory manager would be capable to develop a specific model of his laboratory. Ideally such a simulator should be linked to or be integrated with the laboratory information management system in order to extract directly the attribute values. 

Frame-like structures can be used to represent the facts, objects and concepts. In this context frames must be interpreted as a software stmcture (a frame) in which all characteristics of an object or a concept is described. The simplest example of frame-like structures are the so-called object-attribute-value" triplets. Examples of such triplets to describe a chromatographic column are ... 

Like the differences in composition, the sequence attribute differences between ordered and disordered sequences are exactly as would be expected if disorder were encoded by the sequence. Attribute values, of course, depend on amino acid compositions, so the composition and attribute results are not independent. Nevertheless, the attribute analysis is useful because it provides a biophysical perspective, allowing insight into the amino acid properties that are important for promoting order or disorder. 

Section 2.4 abstracts from individual objects and snapshots of their attribute values to a type model, which characterizes all objects having these attributes. Here, we introduce parameterized attributes graphical associations between objects, collections of objects, and type constants and type combination operators. 

Not all combinations of attributes values are legal. Section 2.5 introduces static invariants as a way of describing integrity constraints on the values of attributes, shows some common uses of such invariants, and outlines how these invariants appear in the business domain as well as in code. 

If you ve done any database design, you ll be familiar with the idea that every entity must have a unique key, which it is up to you to assign. The key is an explicit combination of the entity s attributes, and any two entities with the same attribute values are actually the same one. But in object-oriented design, we always assume an imphcit unique key. If you implement in an OO language or on an OO database, it provides the key for you otherwise, you make it explicit when you get to coding. 

Two different navigation paths may refer to the same object for example, the object referred to as my boss may be the same object as that referred to as my friend s wife. In Figure 2.2, session-5.instructor and session-32.instructor both refer to the same object, laura. If both names refer to the same object, they both see the same attribute values and changes to those values, x = y means x and y refer to same object x <> y means that x and y refer to different objects. These symbols are based on the Object Constraint Language (OCL) in UML in C++ and Java we d use == and =. 

The meaning of identity for an object type is defined, to a great extent, by constraints on whether two distinct objects can have the same attribute values. For example, in a navigation application we may deal with a type Location consisting of a latitude and longitude. If part of the definition of this type includes a constraint that no two distinct location... 

Not all combinations of attribute values are legal. We have already seen how the type diagram constrains the snapshots that are allowed (Figure 2.6 and Figure 2.9 showed some examples). Those constraints were all about the type of object an individual attribute referred to. 

But sometimes we need to disallow certain combinations of attribute values. To do this we can write an invariant a Boolean (true/false) expression that must be true for every permitted snapshot. (We will scope the snapshots by the set of actions to which this applies in Section 3.5.5, Context and Control of an Invariant.)... 

The unique attribute means that no other object of this owner type has the same attribute value, unique can apply to a tuple of attributes. 

A postcondition makes an assertion about the states immediately before and after the action has happened. For every object there are therefore two snapshots and two complete sets of attribute values to refer to. By default, every mention of an attribute in a postcondition refers to the newer version but you can refer to its prior value by suffixing it with pre. 

If you examine the history ofany object that correctly implements T andfind in that history any occurrence of the operation M, then if P was true of the invocation parameters and attribute values immediately before that invocation occurred, Q should have become true immediately after that invocation completed. 

In an entity model, each type should have a key a set of attributes that together define the object s identity and distinguish one object from another. In an object model, every instance has an implicit identity two objects may have all the same attribute values and yet still be different objects. 

All these expressions clearly reduce to the theorem of corresponding states for a one-component system (cf. Eqs. (8) and (10)). The problem is now to attribute values to the reduced volumes and for A and B molecules in their respective mean fields in other words how is the available volume V shared between the molecules A and B We recover here a typical problem of the cell model. Three different assumptions on , (vBy have been proposed11 leading to slightly different versions of the APM ... 

Note that the dialog box is changing the attribute Value. Type in the text for the initial condition, 5 in this case ... 

The ideal point model is useful when a point in the space can be found that is most like the physicochemical parameter. Thus, the ideal point is the hypothetical stimulus, if it existed, that would contain the maximum amount of the physicochemical attribute. The attribute reaches its maximum at the ideal point and falls off in all directions as the square of the distance from the ideal point. The ideal point is located in an MDS space by a special kind of regression proposed by Carroll ( ) that correlates the physicochemical attribute values with the stimulus coordinates and a dummy variable constructed from the sums of squares of the coordinates for each point ... 

A critical assumption of all additive, compensatory MADA tools is that the decision maker s preferences with respect to one objective are independent of the alternative s attribute value with respect to another objec-... 

Starting with a theoretical alternative where all objectives have the worst possible attribute value, the decision maker is asked to change one attribute from worst to best beginning with the objective he considers most important. A value of 100 is assigned to this most important objective. The benefit of a swing from worst to best for all other objectives, rank-ordered by their importance, is assessed relative to this value. 

The decision maker compares two hypothetical alternatives that differ in two attribute values only. One alternative performs best on the first and worst on the second objective and the other vice versa. The decision maker chooses the preferred alternative thus deciding on which objective is more important. Subsequently, one alternative s performance is modified until the decision maker is indifferent between both alternatives. While only n-1 evaluations are required redundant comparisons allow consistency checks on the weights obtained. 

Two different types of scales can be used (cf. Belton and Stewart 2002, pp. 121-122). A local scale is defined with the best and worst existing alternatives forming the reference points for the bounds of the scale while a global scale is defined relative to absolute values for best and worst performance. Local scales are easier to define but global scales allow the decision maker to define objective weights independent of observed attribute values. 

Instead of directly scoring alternatives on a normalized scale or assuming a linear correlation between attribute values and decision makers preferences an explicit value function can be constructed to convert observed attributes into preference values (cf. Goodwin and Wright 2004, pp. 37-39). 

PROMETHEE evaluates discrete alternatives based on pairwise comparisons for each sub-objective. However, these comparisons are not performed "manually". Instead, partial preference functions, usually using the difference between two alternatives attribute values as data input, are used to perform the pairwise comparisons. These partial preference functions have to be defined for each sub-objective as a first step of using PROMETHEE. They are used to determine the decision maker s strength of preference for an alternative (with 0 assigned for indifference, 1 for strict preference and values between 0 and 1 for intermittent preference values). 

Belton V (1986) A comparison of the analytic hierarchy process and a simple multi-attribute value function. European Journal of Operational Research 26 7-21... 

Brownlow SA, Watson SR (1987) Structuring Multi-Attribute Value Hierarchies. The Journal of the Operational Research Society 38 309-317... 

Unstructured models, as detailed in Sections 8.3.1 and 8.3.2, are formulated by a series of kinetic and differential non-linear equations that represent the dynamics of all the state variables during the process. Thus, to simulate a model that consists of parameters and state variables, it is necessary to attribute values to the parameters. 

The molecule element in this example contains five child elements cml metadata, cml identifier, cml atomArray, cml bondArray, and cml prop-ertyList. Of these, cml metadata, cml atomArray, and cml bondArray have no children and are empty containers, defining only attribute/value pairs, whereas cml propertyLi st has one child, cml property. The latter itself has a child cml scalar. As well as the namespace, the cml molecule element itself has two other attributes, id and title. 

Pathway Tools can export PGDBs into several different file formats that are described at http //bioinformatics.ai.sri.com/ ptools/flatfile-format.html. These formats include column-delimited tables, SBML (see http //sbml.org/), BioPAX (see http //biopax.org/), Genbank, FASTA, and attribute-value. 

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