Predicting Solar and Wind Based Computation using Square Difference Labelling Technique

In this paper we have shown that the graph Dbn, C(Ln), T(n, m), K1 + K1,n, balloon of the triangular snake , DHF(n), bull graph (C3), Duplication of the pendant vertex by the edge of bull graph (C3) and one point union of (bull (C3))k is a square difference graph.

Considering Square Difference Labelling for Validating Theta Graphs of Dynamic Machinaries

In this work, we prove that the graphs Z-Pn, braid graph, switching of an apex vertex of CHn, ʘ K2, bull graph (Cn), truncated tetrahedron, frutcht graph are Square difference graph (SDG).

Degree Spilliting Analysis for Polynomials Developed for Electrical Systems

In this paper, we investigate the degree splitting graphs of Pn (n > 3), comb graph, , Cmʘ , S(K1,n) and Tadpole graph are Square difference graph (SDG).

Change Detection of Optical Remote Sensing Image Disturbed by Thin Cloud Using Wavelet Coefficient Substitution Algorithm

The detection of changes in optical remote sensing images under the interference of thin clouds is studied for the first time in this paper. First, the optical remote sensing image is subjected to thin cloud removal processing, and then the processed remote sensing image is subjected to image change detection. Based on the analysis of the characteristics of thin cloud images, a method for removing thin clouds based on wavelet coefficient substitution is proposed in this paper. Based on the change in the wavelet coefficient, the high- and low-frequency parts of the remote sensing image are replaced separately, and the low-frequency clouds are suppressed while maintaining the high-frequency detail of the image, which achieves good results. Then, an unsupervised change detection algorithm based on a combined difference graph and fuzzy c-means clustering algorithm (FCM) clustering is applied. First, the image is transformed into a logarithmic domain, and the image is denoised using Frost filtering. Then, the mean ratio method and the difference method are used to obtain two graph difference maps, and the combined difference graph method is used to obtain the final difference image. The experimental results show that the algorithm can effectively solve the problem of image change detection under thin cloud interference.

To: “An exact solution for the gravity curvature (Bullard B) correction” by T. R. LaFehr (GEOPHYSICS, 56, 1179–1184, August 1991)

In Figure 2 on p. 1180, the difference graph should show a scale of microgal per decameters or microgal per 10 m; near sea level, the correction is about 1.4 microgal per m, not 14 microgal per m.