Search

The Jump graph J(G) of a graph G is the graph whose vertices are edges of G and two vertices of J(G) are adjacent if and only if they are not adjacent in G. Equivalently complement of line graph L(G) is the Jump graph J(G) of G. In this paper, we give characterization for the Jump graph of cycles into Monotonic star decomposition. Also we give characterization for the Jump graph of complete bipartite graphs into even decomposition. [ABSTRACT FROM AUTHOR]

Food is required for human survival. Paddy is a vital food crop serving 60% of the Indian population. Food quality is determined by the plant yield. Unfavorable environmental circumstances, soil fertility, bacteria, viruses, nematodes, fertilizer use, and the absence of nutritional shortages substantially influence plant yield. As a result, it is critical to protect the plants from illness. Crop yield must be improved to meet food scarcity of growing population. Although disease symptoms are apparent in various parts of plant like leaves, stem, fruits and stem, the infections are commonly observed in the leaves. Understanding plant pathology plays a vital role in disease detection. Early detection of diseases is a prompt intervention that aids the farmers in controlling disease spread, resulting in increased agricultural quantity and quality. Image processing techniques with advanced computer vision technologies like machine learning and deep learning have proven the automation of plant disease diagnosis precisely. The main objectives of this research are to investigate computer vision technologies for the early identification of plant diseases and help novice researchers in the same domain learn about plant diseases and the methodologies for disease detection in paddy plant leaves. Consequently this manuscript reviews significant paddy plant infections, highlights related study of tools and techniques, current research, limitations and conclusions for future research in this field. [ABSTRACT FROM AUTHOR]

Paddy is a major food crop serving more than half the population of people in the world. It is inevitable to improve the quantity and quality of food crop with the growing population. Different factors including soil fertility, water availability, erratic climate variations, diseases, and pests, have an impact on paddy crop yield. It is crucial to identify the root cause for the reduction in yield of paddy. Early disease diagnosis prevents the plants from getting worst through its consecutive stage. The concern with manually diagnosing plant leaf diseases with the naked eye is that the results can be less accurate and even unreliable. Automatic disease diagnosis eliminates the need for experts and provides accurate results. This paper will assist the farmers to identify the leaf diseases automatically with the aid of Convolutional Neural Networks. This research includes paddy leaf disease categories: bacterial blight, blast, tungro, brown spot and healthy leaves. The dataset contains 800 images, 160 images from each of the five categories. Images are resized to 256 * 256 pixels and normalized. The network architecture created with convolutional, maxpooling, flatten and dense layers. The Dataset is divided into training and validation set in 70:30 ratios and model is trained with 20 epochs of batch size 16. The novelty of the study is the implementation of extended Huber loss function for minimizing the loss. Furthermore, it is cross compared with existing loss functions. The Proposed model has achieved 96.63% training accuracy and 86.61% validation accuracy with 5 classes. Performance of model is evaluated with confusion matrix with precision, recall, F1-score and support as parameters. [ABSTRACT FROM AUTHOR]

Harmonious coloring of graph G is a proper vertex coloring, where each pair of colors occurs at most on one pair of adjacent vertices. Minimum number of colors required for Harmonious coloring of G is the harmonious chromatic number, χH (G). Here we determine the Harmonious chromatic number of the line graph of commuting graph and non-commuting graph of the dihedral group, D2n. [ABSTRACT FROM AUTHOR]

Let Γ be a non-abelian group and α ⊂ Γ. Then the Commuting graph C(Γ,α) has α as its vertex set and two distinct vertices in α are adjacent if they commute with each other in Γ. Let G = L(C(Γ,α)) be the Line graph of the Commuting graph. A vertex vi of G is given by {x, y} = {y, x} where x and y are the vertices that are adjacent in C(Γ,α) . In this paper, we discuss certain properties of the Line graph of the Commuting graph on the Dihedral group D2n. More specifically, we obtain the chromatic number, clique number and genus of this graph. [ABSTRACT FROM AUTHOR]

Most of the internet applications required high speed internet connectivity. Crosspoint Buffered Switches are widely used switching architectures and designing a scheduling algorithm is a major challenge. PQRS and D-PQRS are the two most successful schedulers used in Crosspoint Buffered Switches under unicast traffic. In this paper, we analysed the performance of PQRS and DPQRS algorithms by varying the crosspoint buffer size. Simulation result shows the delay performance of the switch increases if the size of the buffer increases. [ABSTRACT FROM AUTHOR]

Ensuring security biometrically is essential in most of the authentication and identification scenario. Recognition based on iris patterns is a thrust area of research cause to provide reliable, simple and rapid identification system. Machine learning classification algorithm of support vector machine [SVM] is applied in this work for personal identification. The profuse as well as unique patterns of iris are acquired and stored in the form of matrix template which contains 4800 elements for each iris. The row vectors of 2400 elements are passed as inputs to SVM classifier. The SVM generates separate classes for each user and performs matching based on the template's unique spectral features of iris. The experimental results of this proposed work illustrate a better performance of 98.5% compared to the existing methods such as hamming distance, local binary pattern and various kernels of SVM. The popular CASIA (Chinese Academy of Sciences - Institute of Automation) iris database with fifty users' eye image samples are experimented to prove, that the least Square method of Quadratic kernel based SVM is comparatively better with minimal true rejection rate. [ABSTRACT FROM AUTHOR]

A decomposition of a graphGis a family of edge-disjoint subgraphs {G1,G2,…,Gk} such thatE(G)=E(G1) ∪E(G2) ∪ … ∪E(Gk). If eachGiis isomorphic toHfor some subgraphHofG, then the decomposition is called aH-decomposition ofG. In this paper, we give necessary and sufficient condition for the decomposition of the total graph of standard graphs and corona of graphs into paths on three edges. [ABSTRACT FROM PUBLISHER]