Abstract: We study the possibility of using geometric operators
in the selection of human resources. We develop three new methods
that use the ordered weighted geometric (OWG) operator in different
indexes used for the selection of human resources. The objective of
these models is to manipulate the neutrality of the old methods so the
decision maker is able to select human resources according to his
particular attitude. In order to develop these models, first a short
revision of the OWG operator is developed. Second, we briefly
explain the general process for the selection of human resources.
Then, we develop the three new indexes. They will use the OWG
operator in the Hamming distance, in the adequacy coefficient and in
the index of maximum and minimum level. Finally, an illustrative
example about the new approach is given.
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
Abstract: Approximate tandem repeats in a genomic sequence are
two or more contiguous, similar copies of a pattern of nucleotides.
They are used in DNA mapping, studying molecular evolution
mechanisms, forensic analysis and research in diagnosis of inherited
diseases. All their functions are still investigated and not well
defined, but increasing biological databases together with tools for
identification of these repeats may lead to discovery of their specific
role or correlation with particular features. This paper presents a new
approach for finding approximate tandem repeats in a given sequence,
where the similarity between consecutive repeats is measured using
the Hamming distance. It is an enhancement of a method for finding
exact tandem repeats in DNA sequences based on the Burrows-
Wheeler transform.