Combinatorial designs have many interesting and genuine wide applications in areas including analysis design of algorithms, cryptography, experiments, storage system design, tournament scheduling, optical communications, computer networks to mention just a few areas. In this paper, we are concerned with the transversal authentication codes as direct combinatorial designs. The novelty current pa...

Graph classification is a critical research problem in many applications from different domains. In order to learn graph model, the most widely used supervision component an output layer together with loss (e.g., cross-entropy softmax or margin loss). fact, discriminative information among instances are more fine-grained, which can benefit tasks. this paper, we propose novel Label Contrastive C...

This paper examines the mutual relationship between the organizational use of Computer Mediated Communication (CMC) and organizational culture (OC). CMC supplements communication among members of an organization to maintain the culture, especially when those persons cannot communicate by other means. On the other hand, a strong OC allows a more effective use of CMC by providing members with som...

This paper deals with some results concerning the notion of extended ideal based zero divisor graph $overline Gamma_I(R)$ for an ideal $I$ of a commutative ring $R$ and characterize its bipartite graph. Also, we study the properties of an annihilator of $overline Gamma_I(R)$.

the omega polynomial(x) was recently proposed by diudea, based on the length of stripsin given graph g. the sadhana polynomial has been defined to evaluate the sadhana index ofa molecular graph. the pi polynomial is another molecular descriptor. in this paper wecompute these three polynomials for some infinite classes of nanostructures.

Background: In recent years, there has been an increase in the amount and variety of data generated in the field of healthcare, (e.g., data related to the prevalence of contagious diseases in the society). Various patterns of individuals’ relationships in the society make the analysis of the network a complex, highly important process in detecting and preventing the incidence of diseases....

This paper addresses the problem of segmenting a textured mesh into objects or object classes, consistently with user-supplied seeds. We view this task as transductive learning and use the flexibility of kernel-based weights to incorporate a various number of diverse features. Our method combines a Laplacian graph regularizer that enforces spatial coherence in label propagation and an SVM class...

Graph neural networks (GNNs) have developed rapidly in recent years because they can work over non-Euclidean data and possess promising prediction power many real-word applications. The graph classification problem is one of the central problems networks, aims to predict label a with help training graph-structural datasets. pooling scheme an important part for objective. Previous works typicall...