Example sentences of "the [noun sg] [vb -s] " in BNC.
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1 | The fingerboard/neck jointing and overall fretwork is exemplary ; the neck-edging feels impossibly smooth , and hopefully manufacturing consistency means that all similar-spec 'd Bass Collection instruments will be as good as this . |
2 | Once the interlining has been locked in , the two layers of fabric can be treated as one and made up in the same way . |
3 | Once it has recorded features of the sequence of parses , the algorithm continues : |
4 | He reports that the algorithm does indeed usually converge . |
5 | We agree that the specific algorithm we used wold have been inappropriate if we were interested in examining seasonal or short-term changes in primary production , not because the algorithm does not include a grazing term but because it does not include terms for irradiance and quantum efficiency . |
6 | A node and its children may all have almost identical f values , so the algorithm lacks sensible guidance . |
7 | The algorithm passes credit between rules , similarly . |
8 | Records will be read into primary storage , their keys will be transformed by the algorithm being used , and if the address the algorithm produces is free they will be stored in that address on the direct access device . |
9 | The algorithm keeps a second list , called CLOSED , of nodes which have been expanded and removed from OPEN . |
10 | As well as the set OPEN of known nodes which might lead to goals , and whose children have yet to be explored , the algorithm keeps a set called CLOSED of other known nodes whose children have been constructed . |
11 | The algorithm keeps a set of several strings . |
12 | The number of strings which the algorithm keeps may range up to a few thousand , and each bit string may be a few hundred long . |
13 | The algorithm calculates diff recursively for nodes in successive layers , starting at the top output layer and working back down to the input layer — hence its name , back propagation . |
14 | In each learning cycle , the algorithm calculates H , for each of its strings . |
15 | In one cycle , the algorithm takes one operator out of the list LOp and applies it to N , so producing just one child . |
16 | The algorithm takes about 50 CPU seconds on a SUN SPARCStation II to order 180 probes and 1150 clones from the S.pombe YAC library , and 247 CPU seconds to order 667 probes and 2837 clones from the S.pombe cosmid library , including the phase of contig ordering and consistency checking . |
17 | The algorithm involves two numbers , K and c . |
18 | Maybe P and Q and R behave alike , but there may be times when the algorithm folds a set { P , Q , R } where , say , Q sometimes occurs in a context which never contains P or R. The algorithm looks for any context which contains some of X 's children but not the others . |
19 | The algorithm chooses for expansion the node having the best actual score so far , together with the best estimated score , h* ( n ) . |
20 | The algorithm runs thus : IF Vs>Vdb |
21 | The algorithm runs thus . |
22 | It keeps a list , called OPEN , of nodes which the algorithm has found and which are not goals but whose children might be goals . |
23 | The algorithm has a new variable , S , whose value is such a pair . |
24 | This f is used only to detect when the algorithm has reached a summit or plateau . |
25 | The algorithm has been implemented in a program called probeorder . |
26 | The algorithm has been implemented in two versions ( using least and most distant neighbours ) . |
27 | The algorithm examines every shallow state , which can be constructed by a short path from start , before it examines deeper states . |
28 | The algorithm scans the sequence of top symbols of parses , and looks for pairs M , P which crop up together unexpectedly often . |
29 | All the essential work is done by a function called hbba whose value is the goal , if the algorithm finds one , or else false . |
30 | The choice between searching for the least or most distant neighbours may depend on the experimental ( or even presentational ) needs because in the former case the algorithm finds more detailed and possibly informationally redundant order of probes , while in the latter case it finds a minimal set of probes connected by clones spanning large regions of the genome . |