Aunu Integer Sequence as Non-Associative Structure and Their Graph Theoretic Properties ()
Received 14 March 2016; accepted 15 May 2016; published 18 May 2016

1. Introduction
An overview of Aunu numbers, Aunu permutations patterns, the 123 and 132 avoiding patterns and their applications was reported by the authors in [2] . This paper considered the prime enumerative function
generated by the author in [3] and defined an operator on some
using the addition and subtractions as an operators such that the pairing of elements in
was closed in
.
In simplest form, a graph is a collection of vertices that can be connected to each other by means of edges. In particular, each edge of graph joins exactly two vertices. Using a formal notation, a graph is defined as follows.
Definition 2.1: A graph G consists of a collection of V vertices and a collection of edges E, for which we write
Each edge
is said to join two vertices, which are called its end points. If e joins
, we write
Vertex u and v in this case are said to be adjacent. Each e is said to be incident with vertices u and v respectively.
We will often write
and
to denote the set of vertices and edges associated with graph G respectively. It is important to realize that an edge can actually be represented as an unordered tuple of two vertices, that is, its end points. For this reason, we make no distinction between
and
: they both represent the fact that vertex u and v are adjacent [4] .
Definition 2.2: A graph H is a subgraph of G if
and
such that for all
with
, we have that
. When H is a subgroup of G, we write
[4] .
Definition 2.3: Adjacency matrix is a table A with n rows and m columns with entry
denoting the number of edges joining vertex
and
[4] .
Definition 2.4: An incidence matrix M of graph G consists of n rows and m columns such that
counts the number of times that edge
is incident with vertex
. Note that
is either 0, 1 or 2.
Theorem 2.1: For all graphs G, the sum of the vertex degrees is twice the number of edges [4] . That is,
. (1)
Corollary 2.1: For any graph G, the number of vertices with odd degrees is even [4] .
2. Method of Construction
Let
where in this case
(being prime numbers). The restriction
is deliberately put
since we are only interested in enumerations involving Aunu numbers of (123)-avoiding category which, by definition begins from 5 upwards as reported in [5] . Then;
.
We now obtain from
a restricted subset
. Then ![]()
contains all elements of
up to 21.
We are now set to carry out some algebraic theoretic investigations on
being a direct subset of
.
First let us introduce an operator on
such that:
Define an operator
(2)
where:
is an operator which induces addition or subtraction on any pair
whereby addition or subtraction in absolute value is closed in
and
implies whichever of ![]()
Then we obtain from
set of pairs
![]()
where the superscript p on
indicates that
is obtained from
by breaking elements of
into pairs such that application of
of (1) on
is closed in
.
3. Results
3.1. Testing for Nonassociative Properties Using the Stated Pairing Scheme Yields the Following Results
1) Given
, we note that: the operation rule is either “+ or −” as earlier defined.
![]()
Also ![]()
![]()
, hence it is not associative.
2) ![]()
Also, ![]()
![]()
, hence it is not associative.
3) ![]()
Also,![]()
![]()
, hence it is not associative.
4) ![]()
Also, ![]()
![]()
, hence it is not associative.
5) ![]()
Also,![]()
![]()
![]()
, hence it is not associative.
6) ![]()
Also, ![]()
![]()
, hence it is not associative.
7) ![]()
Also, ![]()
![]()
, hence it is not associative
8) ![]()
Also, ![]()
![]()
, hence it is not associative.
9) ![]()
Also, ![]()
![]()
, hence it is not associative.
10) ![]()
Also, ![]()
![]()
, hence it is not associative.
11) ![]()
Also, ![]()
![]()
, hence it is not associative
12) ![]()
Also, ![]()
![]()
, hence it is not associative.
13) ![]()
Also, ![]()
![]()
, hence it is not associative.
3.2. Graph Theoretic Schemes Generated Using Pairs of Elements in An and Bn
In what follows some graph theoretic models are presented using pairs of points of
and
as adjacent nodes.
Figure 6 shows some examples of regular graphs and their adjacency and incidence matrices can be constructed using the same format as outlined in Table 1-10.
![]()
Table 1. Adjacency matrix of Figure 1.
Theorem 2.1 and corollary 2.1 has been satisfied. Note also that, every column of incidence matrix has
entries 1.
![]()
Table 2. Incidence matrix of Figure 1.
![]()
Table 3. Adjacency matrix of subgraph in Figure 2.
Theorem 2.1 and corollary 2.1 has been satisfied. Note also that, every column of incidence matrix has
entries 1.
![]()
Table 4. Incidence matrix of subgraph in Figure 2.
![]()
Table 5. Adjacency matrix of subgraph of Figure 3.
Theorem 2.1 and corollary 2.1 has been satisfied. Note also that, every column of incidence matrix has
entries 1.
![]()
Table 6. Incidence matrix of subgraph of Figure 3.
![]()
Table 7. Adjacency matrix of subgraph of Figure 4.
Theorem 2.1 and corollary 2.1 has been satisfied. Note also that, every column of incidence matrix has
entries 1.
![]()
Table 8. Incidence matrix of subgraph of Figure 4.
![]()
Table 9. Adjacency matrix of subgraph of Figure 5.
Theorem 2.1 and corollary 2.1 has been satisfied. Note also that, every column of incidence matrix has
entries 1.
![]()
Table 10. Incidence matrix of subgraph of Figure 5.
![]()
Figure 1. Graph network constructed from elements of An and Bn.
![]()
Figure 2. Subgraph of the network of Figure 1.
![]()
Figure 3. Subgraph of the network of Figure 1.
![]()
Figure 4. Subgraph of the network of Figure 1.
![]()
Figure 5. Subgraph of the network of Figure 1.
![]()
Figure 6. Subgraph of the network of Figure 1.
![]()
Figure 7. Subgraph of the network of Figure 1.
Figure 7(i)-(vi) also shows some examples of regular graphs and their adjacency and incidence matrices can be constructed using the same format as outlined in Table 1-10 and can also be viewed as Eulerian circuits.
4. Conclusion
After establishing the non-associativity of the finite sets
and
under the action of an operator
we have also established some good applications in graph network analysis. This, we have achieved by generating some Eulerian circuits which are of some consequences in the study of network theory and in circuits theory. Our results would thus have some promising applications in both the communication and in the signal processing formalisms. Also the results involving adjacency and incidence matrices could be used in communication and coding theory which could be investigated in further researches.