The dimension of underground structure is a key factor in its stability. Rock blotting has important effect in rock mechanic projects. It increases the stability of rock blocks. The performance of rock bolt is depending on the quality of its set up. Quality of its set up is determined by pull out test method. Numerical simulation is other method for determination of rock blotting behavior. In this paper, the effect of tensile loading on the “ Y” shape joint is determined using franc2D. The angularity of large joint tail (β ) changes from 0° to 90° with increment of 45° . The angularity of small joint tail related to large joint tail (α ) changes from 20° to 160° with increment of 20° . The spacing between joint and loading place change from 2a to 4a with increment of “ a” which “ a” is the length of large joint tail. Totally 52 model were simulated. In the case of horizontal joint the crack growth length is maximum and vertical joint has minimum effect on the crack growth. When the angularity of large joint tail related to horizontal was 45° , the maximum of crack growth was occurred. The maximum of crack growth from small joint tail was occurred when it is in horizontal configuration. The maximum number of small joint tail growth occurred when its angularities related to horizontal axis was 45° .

The purpose of this essay is to examine the correlation between variable dollar and four currencies.This essay tries to predict the optimal model.regreation model. Therefore, this essay presents the use of these results have been achieved from this research.There is a correlation between dollar and euro and they have aline correlation. And their index R equals %973.on which the variable euro is based.There is a correlation between dollar and franc and they have aline correlation. And their index R equals %989.on which the variable franc is based.There is a correlation between dollar and yen and they have aline correlation. And their index R equals %991.on which the variable yen is based.There is a correlation between dollar and pound and they have aline correlation. And their index R equals %980.on which the variable pound is based.

The measured potential field data can be considered as the result of the superposition of the anomalies from sources with various depths. Regional anomalies due to the origin of deep structures and residual anomalies due to the origin of shallow structures form the long and short parts of the total measured field wavelength, respectively. Therefore, one of the most important steps in the potential field data processing is the regional-residual anomalies separation which is used as the basis for inversion and interpretation. The process of separating regional and residual anomalies in potential field data is usually performed in the measured or frequency domain. Methods such as moving averaging, polynomial fitting, and minimum curvature are some of the well-known methods in the potential field separation in the measuring domain. Methods that perform the separation process in the frequency domain have superior performance compared to other methods, making them more common and widely used. Methods such as simple wavenumber filtering, matched filters, preferential filters, and Wiener filters are some of the common methods in the frequency domain to separate regional and residual anomalies. Various researches have shown that the rank of trajectory matrix obtained from measured potential field data depends on the depth of the anomaly source, and the rank of trajectory matrix of the deep sources are lower than that of the shallow sources. In this paper, the spectral analysis of singular values (SSA) was used to reduce the rank of the trajectory matrix obtained from gravity data in order to separate the regional and residual anomalies. Based on the theory of the SSA method, the following method was proposed to separate regional and regional anomalies in 2D gravity data. At the first step, the trajectory matrix is calculated from the Henkel matrices obtained from the measured data. Then, the obtained trajectory matrix is decomposed to eigen triples by employing the SVD and the eigenimages of it are calculated. The optimal value of rank is obtained from the elbow point of the cumulative contribution chart for eigenimages and the trajectory matrix related to regional anomaly is constructed using optimal rank. Finally, the separated regional anomaly is obtained by averaging along anti-diagonals element of the reconstructed trajectory matrix. The efficiency of the proposed method is investigated on both synthetic and real field data examples. Investigating the relationship between the depth of origin of the anomaly and the rank of the trajectory matrix calculated from the measured data showed that there is an inverse relationship between them. The obtained results of synthetic and real data showed that the technique of reducing the rank of the trajectory matrix using SSA can be used as a method of separating anomalies with different depths of origin in potential field data. Also, comparing the results of the proposed method with the results of polynomial fitting and matched filtering methods showed that the proposed method has a better performance in the separation of residual and regional anomalies and can produce better results in environments with high geological complexity.

In this work, several 2D extensions of the principal component analysis (PCA) and linear discriminant analysis (LDA) techniques were applied in a lossless dimensionality reduction framework for face recognition applications. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (SVM) classifier. At the same time, the loss of useful information was minimized using the projection penalty idea. The well-known face databases were used to train and evaluate the proposed methods. The experimental results obtained indicated that the proposed methods had a higher average classification accuracy, in general, compared to the classification based on the Euclidean distance, and also compared to the methods that first extracted the features based on the dimensionality reduction technics, and then used the SVM classifier as the predictive model.

The accumulation and movement of salts in the soil and its modeling have been considered significantly in recent years. In this article, the simulation of movement of salts in soil using HYDRUS-2D Model for various leaching times has been performed and profiles of advancing salt movement on the dry and wet basins has been drawn and also the effect of initial moisture has been investigated. This model has a strong ability for simulation. Results of the above model show that the leaching repetition causes a quick movement of salts to bottom of the root zone. this movement had more speed on the dry basin in comparison with the wet.The applied conclusion of this article is that if the soil is dry before the irrigation; salts would be influenced by prefrential flows by Joint gaps resulting from contraction and expansion and therefore will smoothly transported. After a week of leaching, results show a faster salts movement on the dry basin causing by capillary forces and therefore the accumulation on the topsoil.

2D materials are a class of materials with only one dimension in nanoscale. Due to the increase in the number of surface atoms in two-dimensional materials, the physical and chemical reactivity compared to the bulk counterpart significantly increased. 2D materials characteristics such as high anisotropy, high surface area, unique morphology, and tunable mechanical, optical, electrical, and magnetic functionalities come out to be a fascinating candidate for application in electro-optical and electronic devices, energy and environmental fields, as well as biomedical and drug delivery in medicine. 2D materials are divided into ten major groups, including carbon-based 2D materials (includes graphene, graphene oxide, reduced graphene oxide, graphane, fluorographene, graphyne, graphdiyne, graphone), hexagonal boron nitride (hBN), graphitic C3N4, elemental 2D materials (elements groups 14 and 15), transition metal dichalcogenides (TMDs), transition metal oxides (TMOs), MXenes, 2D perovskite materials, 2D metal materials, and 2D clay materials (silicate clays and layered double hydroxides (LDHs)). In this paper, after the classification of these materials, the introduction, application, and related properties are investigated. So far, more studies have been done on graphene than other 2D materials. These materials are expected to have a similar capacity to graphene in terms of properties and applications, while ongoing research will increase the diversities of this category and depth of knowledge on these groups of materials.

Typical VLF data exhibit considerable 2D effects and 2D inversion offers several advantages when applied to profiles of VLF data. First it provides a quantitative estimate of the basement conductivities away from conductors. Secondly the relation between real and imaginary parts of the tipper vector provides information about the depth of the major conductors giving rise to the anomalies. In this paper, a synthetic model of a vertical contact and a profile of airborne VLF data are discussed.