GROUP TESTING
Historically, group testing theory related to the testing of blood samples to identify a disease. Based on the algorithm, there are two types of group testing, Adaptive Group Testing (AGT) and Non-Adaptive Group Testing (NAGT). NAGT algorithm can be represented by a binary matrix M = (mij), where...
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| Format: | Theses |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/33944 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Historically, group testing theory related to the testing of blood samples to identify
a disease. Based on the algorithm, there are two types of group testing, Adaptive
Group Testing (AGT) and Non-Adaptive Group Testing (NAGT). NAGT algorithm
can be represented by a binary matrix M = (mij), where coloumns are labeled by
items and rows by tests (blocks). Criteria matrix is mij = 1 if test i contains item
j and the other mij = 0. On the other hand, the test results of each block is repre-
sented in a column vector, called outcome vector. Based on these representations,
the problem of group testing can be viewed as nding representation matrix M
which satises the equation Mx = y where y is an outcome vector and x samples
are tested. If there are d positive sample of n samples then we say d-Combinatorial
Group Testing, abbreviated by d-CGT. In this thesis will show the construction of
d-disjunct matrices which is a solution of group testing equation. Furthermore, from
the construction will be modied so that the new construction can be identied more
than d positive samples. |
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