Tagged node

In a different application scenario, tagged nodes can be used to define a known common anchor point in a set of molecules. A set of approximately 400 R-group instances from a combinatorial library (based around a quinazoline core) forms an example of such a set of molecules, where the functional attachment point forms the tagged Feature Tree node. A Feature Tree similarity... 

Fig. 4.10 R-group molecules or instances from a combinatorial library the common anchor point of the instances is marked with an R. One instance was used as a query in a similarity search (top molecule). On the left, the two most similar instances in the library without consideration of the anchor point are shown. When the anchor point is identified as a tagged node (circles), the most similar instances in the library have their anchor point at equivalent positions in the molecules, as shown on the right.

Another permanent marking point is made from the positive direction, stored in the collection S. The adjacent temporary marking points are then modified. If the permanent tag node is already in the collection E, setting the permanent marker as the center, tracing to find an optimal path respectively according to positive direction and reverse direction. If not, going to the next step. 

To each point t in S we assign an arbitrary predicate letter A. which corresponds to a predicate At(X,Y), except that the input condition predicate A(X) is always assigned to the initial point in the scheme and the ouput condition predicate B(X,Y) is always assigned to all STOPs in the scheme. Thus every node or address in S is tagged with a predicate which we call an inductive assertion. 

Type-3-controllability and control-loop-applied is apply tag-type-3-technology to node endcase endselect return node... 

Access to raw data is enabled in two steps the vendor enables a node on the X-ray system to which raw data can be sent, and at this node, a DICOM receiver (Jacobs et al. 2006) receives the QC image and extracts a series of data out of all relevant incoming raw data. By convention, the patient name tag is used to distinguish between an image for QC purposes and any other image. In practice, patient dose data analysis can also be performed on routine patient images using the same DICOM receiver software tool. 

A node is the smallest elementary data structure unit. Physical nodes are contiguous words in fast memory. It is useful to think of the realization of a data structure as a network of nodes embedded in memory, possibly connected by links. Parts of nodes and portions of memory words referred to as entities by programs are caAeA fields. A one-bit field is called a flag, or sometimes a tag. 

Binary trees always have tip nodes with unused pointers (link fields). Hence, af fhe small cost of a tag bit to indicate whether the link field is in use, this space can be used for traversal. The idea is that any pointer field not used to locate other data in the binary tree structure can be used to describe where to go in a traversal (via preorder, post-order, etc.). Hence, these tip fields can be used to speed algorithm execution. These pointer memory location values may be useful in indicating where the algorithm should go next. If a tag bit indicates that the purpose is data structure traversal, the locator is called a thread. 

Here, new is the standard Ruby constructor (overloaded in each class). The function names poly3, hOsO, idealgas, srk and m soave do all refer to actual model implementations, while ig is a phase tag used for the data base binding. If no function is specified in the constructor then anonymous will be called. The role of this function (which is also overloaded in each class) is simply to patch the calculation results from the underlying nodes without adding any private functionality. Finally, the operator is not implemented as such but rather as a call to method tell (again due to implementation details). 

We do not need to supply all the parameters in an attribute instance in a query. For example, we can write attributes has risk(likelihood(probable)) to mean find a node with an attribute risk whose iikeiihood is probable and with any severity. We can abbreviate this further by writing attributes has risk(probable), which will look for any parameter with value probabie, or even attributes has risk with which to find nodes tagged with any risk values. We can omit the second argument of a top-level quantifier, in which case it is taken to be true. For example, a root node can be queried by not(isBelow), which is equivalent to not(isBelow)frMe. A derived syntax for queries is given as ... 

Service delay of all the periodic safety message fragments queued before a tagged fragment within a batch Total number of nodes which acquired a time slot within n frame Average standstill distance Cardinality of a set X... 

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