The g-Good-Neighbor Connectivity of Some Cartesian Product Graphs

The g-good-neighbor connectivity of G is a generalization of the concept of connectivity, which is just for, and an important parameter in measuring the fault tolerance and reliability of interconnection network. Many well-known networks can be constructed by the Cartesian products of some simple graphs. In this paper, we determine the g-good-neighbor connectivity of some Cartesian product graphs. We give the exact value of g-good-neighbor connectivity of the Cartesian product of two complete graphs and for , mesh for , cylindrical grid and torus for .

Rupture Degree of Some Cartesian Product Graphs

The rupture degree of a noncomplete-connected graph G is defined by , where is the number of components of and is the order of the largest component of. In this paper, we determine the rupture degree of some Cartesian product graphs.

Cartesian product over interval valued intuitionistic fuzzy sets

The intuitionistic fuzzy set(IFS) based on fuzzy theory,which is of high efficiency to solve the fuzzy problem, has been introduced by Atanassov. Subsequently, he pushed the research one step further from the IFS to the interval valued intuitionistic fuzzy set(IVIFS). On the basis of fuzzy set(FS), the IFS is a generalization concept. And the IFS is generalized to the IVIFS.In this paper, the definition of the sixth Cartesian product over IVIFSs is first introduced and its some properties are explored.We prove some equalities based on the operation and the relation over IVIFSs. Finally, we present one geometric interpretation and a numerical example of the sixth Cartesian product over IVIFSs.

Linear arboricity of Cartesian products of graphs

A linear forest is a forest whose components are paths. The linear arboricity la （G） of a graph G is the minimum number of linear forests which partition the edge set E（G） of G. The Cartesian product G□H of two graphs G and H is defined as the graph with vertex set V（G□H） = {（u, v）｜ u ∈V（G）, v∈V（H） } and edge set E（G□H） = { （ u, x） （ v, Y）｜u=v and xy∈E（H）, or uv∈E（G） and x=y}. Let Pm and Cm,, respectively, denote the path and cycle on m vertices and K, denote the complete graph on n vertices. It is proved that （Km□Pm）=[n＋1/2]for m≥2,la（Km□Cm）=[n＋2/2],and la（Km□Km）=[n＋m-1/2]. The methods to decompose these graphs into linear forests are given in the proofs. Furthermore, the linear arboricity conjecture is true for these classes of graphs.

Embedding Cartesian Product of Some Graphs in Books

The book embedding of a graph G consists of placing the vertices of G in a line called spine and assigning edges of the graph to pages so that the edges assigned to the same page do not intersect. The number of pages is the minimum number in which the graph can be embedded. In this paper, we study the book embedding of the Cartesian product Pm × Sn, Pm × Wn, Cn × Sm, Cn × Wm, and get an upper bound of their pagenumber.

Cartesian Product Based Transfer Learning Implementation for Brain Tumor Classification

Knowledge-based transfer learning techniques have shown good performance for brain tumor classification,especially with small datasets.However,to obtain an optimized model for targeted brain tumor classification,it is challenging to select a pre-trained deep learning(DL)model,optimal values of hyperparameters,and optimization algorithm(solver).This paper first presents a brief review of recent literature related to brain tumor classification.Secondly,a robust framework for implementing the transfer learning technique is proposed.In the proposed framework,a Cartesian product matrix is generated to determine the optimal values of the two important hyperparameters:batch size and learning rate.An extensive exercise consisting of 435 simulations for 11 state-of-the-art pre-trained DL models was performed using 16 paired hyperparameters from the Cartesian product matrix to input the model with the three most popular solvers(stochastic gradient descent with momentum(SGDM),adaptive moment estimation(ADAM),and root mean squared propagation(RMSProp)).The 16 pairs were formed using individual hyperparameter values taken from literature,which generally addressed only one hyperparameter for optimization,rather than making a grid for a particular range.The proposed framework was assessed using a multi-class publicly available dataset consisting of glioma,meningioma,and pituitary tumors.Performance assessment shows that ResNet18 outperforms all other models in terms of accuracy,precision,specificity,and recall(sensitivity).The results are also compared with existing state-of-the-art research work that used the same dataset.The comparison was mainly based on performance metric“accuracy”with support of three other parameters“precision,”“recall,”and“specificity.”The comparison shows that the transfer learning technique,implemented through our proposed framework for brain tumor classification,outperformed all existing approaches.To the best of our knowledge,the proposed framework is an efficient framework that helped reduce the computational complexity and the time to attain optimal values of two important hyperparameters and consequently the optimized model with an accuracy of 99.56%.

Geodetic Number and Geo-Chromatic Number of 2-Cartesian Product of Some Graphs

A set S ⊆ V (G) is called a geodetic set if every vertex of G lies on a shortest u-v path for some u, v ∈ S, the minimum cardinality among all geodetic sets is called geodetic number and is denoted by . A set C ⊆ V (G) is called a chromatic set if C contains all vertices of different colors in G, the minimum cardinality among all chromatic sets is called the chromatic number and is denoted by . A geo-chromatic set Sc ⊆ V (G) is both a geodetic set and a chromatic set. The geo-chromatic number of G is the minimum cardinality among all geo-chromatic sets of G. In this paper, we determine the geodetic number and the geo-chromatic number of 2-cartesian product of some standard graphs like complete graphs, cycles and paths.

The Signed Domination Number of Cartesian Product of Two Paths

Let G be a finite connected simple graph with vertex set V(G) and edge set E(G). A function f:V(G) → {1,1} is a signed dominating function if for every vertex v∈V(G), the closed neighborhood of v contains more vertices with function values 1 than with −1. The signed domination number γs(G) of G is the minimum weight of a signed dominating function on G. In this paper, we calculate The signed domination numbers of the Cartesian product of two paths Pm and Pn for m = 3, 4, 5 and arbitrary n.

Domination Number of Square of Cartesian Products of Cycles

A set ?is a dominating set of G if every vertex of ?is adjacent to at least one vertex of S. The cardinality of the smallest dominating set of G is called the domination number of G. The square G2 of a graph G is obtained from G by adding new edges between every two vertices having distance 2 in G. In this paper we study the domination number of square of graphs, find a bound for domination number of square of Cartesian product of cycles, and find the exact value for some of them.

On the Signed Domination Number of the Cartesian Product of Two Directed Cycles

Let D be a finite simple directed graph with vertex set V(D) and arc set A(D). A function ?is called a signed dominating function (SDF) if ?for each vertex . The weight ?of f is defined by . The signed domination number of a digraph D is . Let Cm × Cn denotes the cartesian product of directed cycles of length m and n. In this paper, we determine the exact values of gs(Cm × Cn) for m = 8, 9, 10 and arbitrary n. Also, we give the exact value of gs(Cm × Cn) when m, ?(mod 3) and bounds for otherwise.

Full Friendly Index Sets of Cartesian Products of Two Cycles

Let G =（V, E） be a connected simple graph. A labeling f ： V → Z2 induces an edge labeling f＊ ： E → Z2 defined by f＊（xy） = f（x） ＋f（y） for each xy ∈ E. For i ∈ Z2, let vf（i） = ｜f^-1（i）｜ and ef（i） = ｜f＊^-1（i）｜. A labeling f is called friendly if ｜vf（1） - vf（0）｜ ≤ 1. For a friendly labeling f of a graph G, we define the friendly index of G under f by if（G） = e（1） - el（0）. The set [if（G） ｜ f is a friendly labeling of G} is called the full friendly index set of G, denoted by FFI（G）. In this paper, we will determine the full friendly index set of every Cartesian product of two cycles.

The Crossing Number of the Cartesian Products of Wm with Pn

Most results on crossing numbers of graphs focus on some special graphs, such as the Cartesian products of small graphs with path, star and cycle. In this paper, we obtain the crossing number formula of Cartesian products of wheel Wm with path Pn for arbitrary m ≥ 3 and n ≥ 1.

Dimensional Results for Cartesian Products of Homogeneous Moran Sets

M（J, {ms ＊ ns}, {Cs}） be the collection of Cartesian products of two homogenous Moran sets with the same ratios {cs} Where J = [0, 1] × [0, 1]. Then the maximal and minimal values of the Hausdorff dimensions for the elements in M are obtained without any restriction on {msns} or {cs}.

L（2, 1）-Circular Labelings of Cartesian Products of Complete Graphs

For positive integers j and k with j ≥ k, an L（j, k）-labeling of a graph G is an assignment of nonnegative integers to V（G） such that the difference between labels of adjacent vertices is at least j, and the difference between labels of vertices that are distance two apart is at least k. The span of an L（j, k）-labeling of a graph G is the difference between the maximum and minimum integers it uses. The λj, k-number of G is the minimum span taken over all L（j, k）-labelings of G. An m-（j, k）-circular labeling of a graph G is a function f ： V（G） →{0, 1, 2,..., m - 1} such that ｜f（u） - f（v）｜m ≥ j if u and v are adjacent; and ｜f（u） - f（v）｜m 〉 k ifu and v are at distance two, where ｜x｜m = min{｜xl｜, m-｜x｜}. The minimum integer m such that there exists an m-（j, k）-circular labeling of G is called the σj,k-number of G and is denoted by σj,k（G）. This paper determines the σ2,1-number of the Cartesian product of any three complete graphs.

Adjacent Vertex Distinguishing Incidence Coloring of the Cartesian Product of Some Graphs

An adjacent vertex distinguishing incidence coloring of graph G is an incidence coloring of G such that no pair of adjacent vertices meets the same set of colors.We obtain the adjacent vertex distinguishing incidence chromatic number of the Cartesian product of a path and a path,a path and a wheel,a path and a fan,and a path and a star.

On total{k}-domatic number of Cartesian and direct product of graphs

For a positive integer k,the total{k}-dominating function(T{k}DF)of a graph G without isolated vertices is a function f from the vertex set V(G)to the set{0,1,2,…,k}such that for each vertex v∈V(G),the sum of the values of all its neighbors assigned by f is at least k.A set{f_(1),f_(2),…,f_(d)}of pairwise different T{k}DF s of G with the property that∑d i=1 f_(i)(v)≤k for each v∈V(G),is called a total{k}-dominating family(T{k}D family)of G.The total{k}-domatic number of a graph G,denoted by d^({k})_(t)(G),is the maximum number of functions in T{k}D family.In 2013,Aram et al.proposed a problem that whether or not d^({k})_(t)(C_(m)□C_(n))=3 when 4 nmk,and d^({k})_(t)(C m□C n)=4 when 4|nmk.It was shown that d^({k})_(t)(C_(m)□C_(n))=3 if 4 nmk and k≥2 or 4|nmk and 2 nk,which partially answered the above problem.In addition,the total{k}-domatic number of the direct product of a cycle and a path,two paths,and two cycles was studied,respectively.

The Crossing Numbers of Cartesian Products of Stars with a 5-Vertex Graph

In this paper, we compute the crossing number of a specific graph Hn, and then by contraction, we obtain the conclusion that cr（G13 × Sn） = 4[n/2] [n-1/2]＋[n/2] . The result fills up the blank of the crossing numbers of Cartesian products of stars with all 5-vertex graphs presented by Marian Klesc.

Paired Domination of Cartesian Products of Graphs

Let γpr（G） denote the paired domination number and G □ H denote the Cartesian product of graphs G and H. In this paper we show that for all graphs G and H without isolated vertex, γpr（G）γpr（H）≤ 7γpr （G □H）.

集合论、笛卡尔乘积和多项式定理在生命表研究中的应用:以取食玉米粒和茶树叶片的棉铃虫生命表为例

【目的】自我重复取样技术(bootstrap technique)广泛用于计算生命表各参数的方差、标准误和置信区间(confidence interval),而配对自我重复取样检验(paired bootstrap test,PBT)则用于检测处理间的生命表参数差异。本研究以取食玉米粒和茶树叶片的棉铃虫Helicoverpa armigera生命表为例,进一步解释集合论、笛卡尔乘积和多项式定理在害虫种群生物学研究中的应用。【方法】利用年龄-龄期两性生命表对取食玉米粒和茶树叶片的棉铃虫种群参数进行分析,利用集合论、笛卡尔乘积和多项式定理将种群统计分析以明确数学的方法呈现,以检测所有可能的自我重复取样样本、精确计算种群参数置信区间以及处理之间差异的置信区间,计算可育和不育样本的概率。【结果】取食茶树叶片的棉铃虫其成虫前期存活率、内禀增长率(r)、周限增长率(λ)、净增殖率(R_(0))、平均世代周期(T)均显著低于取食玉米粒的,说明茶树叶片不是棉铃虫的适宜寄主植物。因取食茶树叶片棉铃虫种群不育样本数较多,利用bootstrap重复取样接受可育与不育样本时,其结果与不用bootstrap技术计算的差异小于5%;若取样时仅接受可育样本,结果与原数值差异显著,误差较大(>5%)。使用笛卡尔配对检验(Cartesian paired test,CPT)比较取食两种食物的棉铃虫种群的R0的差异时,可计算两种处理bootstrap抽样结果所有可能差异的精确置信区间,而使用自我重复取样检验通常会导致置信区间的估值过高或过低,尤其是自我重复取样数较小时。多项式定理可以揭示可育和不育样本的自我重复取样结果。自我重复取样抽样记录必须保留,以便在后续分析中进一步应用。【结论】本研究进一步明确了两性生命表理论的数学基础,也为昆虫学研究中的生命表技术的应用提供数学支撑。

具有优异汉明相关特性的混沌跳频序列构造方法

跳频通信具有码分多址、频带共享、抗干扰和抗截获的能力,在无线通信系统中得到了广泛的应用。目前基于混沌方法构造的跳频序列大多具有较高的线性复杂度,所得到的跳频序列虽然具有良好的随机性,但是其汉明相关性还不够。在选取具有优异汉明相关特性的m序列的基础上,结合混沌序列,利用笛卡尔积构造得到了具有优异汉明自相关性的跳频序列。该跳频序列具备与混沌序列一致的线性复杂度,而且可以保证其周期不小于m序列的周期,汉明自相关值不超过m序列的汉明自相关值。