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The current Hungarian Soil Classification System (HSCS) was elaborated during the 1960s, based on the genetic principles of Dokuchaev. It was developed before sufficient data and modern data processing tools were available and served different purposes than current users need or apply it for.The central unit is the soil type, grouping soils that were believed to have developed under similar soil-forming factors and processes. The major soil type is the highest category that groups soils based on climatic, geographical and genetic bases. Subtypes and varieties are distinguished according to the assumed dominance of soil-forming processes and observable/measurable morphogenetic properties. STEFANOVITS (1963) defined the 23 soil-forming processes that have a dominant impact on the differentiation of the 39 soil types of the system.Based on accumulated data and experience, as well as on numerical tools for defining taxonomic relationships a modernization process was carried out. The process included: linking processes to diagnostics, review and numerical study of similarities and dissimilarities of existing units, development of new central units, development of a computer assisted key, and definition of methodology to derive the lower level units. The new, 15 soil types are defined by stronger morphogenetic and measurable criteria, but with the application of legacy data and the developed key, the earlier units can be converted to the new ones, hence the value of legacy data can be preserved.

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The problem of handling outliers in a deformation monitoring network is of special importance, because the existence of outliers may lead to false deformation parameters. One of the approaches to detect the outliers is to use robust estimators. In this case the network points are computed by such a robust method, implying that the adjustment result is resisting systematic observation errors, and, in particular, it is insensitive to gross errors and even blunders. Since there are different approaches to robust estimation, the resulting estimated networks may differ. In this article, different robust estimation methods, such as the M-estimation of Huber, the “Danish”, and the L 1 -norm estimation methods, are reviewed and compared with the standard least squares method to view their potentials to detect outliers in the Tehran Milad tower deformation network. The numerical studies show that the L 1 -norm is able to detect and down-weight the outliers best, so it is selected as the favourable approach, but there is a lack of uniqueness. For comparison, Baarda’s method “data snooping” can achieve similar results when the outlier magnitude of an outlier is large enough to be detected; but robust methods are faster than the sequential data snooping process.

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The Earth topographic masses are compensated by an isostatic adjustment. According to the isostatic hypothesis a mountain is compensated by mass deficiency beneath it, where the crust is floating on the viscous mantle. For study of the impact of the compensating mass on the topographic mass a crustal thickness (Moho boundary) model is needed. A new gravimetric-isostatic model to estimate the Moho depth, Vening Meinesz-Moritz model, and two well-known Moho models (CRUST2.0 and Airy-Heiskanen) are used in this study. All topographic masses cannot be compensated by simple isostatic assumption then other compensation mechanism should be considered. In fact small topographic masses can be supported by elasticity of the larger masses and deeper Earth’s layers. We discuss this issue applying spatial and spectral analyses in this study. Here we are going to investigate influence of the crustal thickness and its density in compensating the topographic potential. This study shows that the compensating potential is larger than the topographic potential in low-frequencies vs. in high-frequencies which are smaller. The study also illustrates that the Vening Meinesz-Moritz model compensates the topographic potential better than other models, which is more suitable for interpolation of the gravity field in comparison with two other models. In this study, two methods are presented to determine the percentage of the compensation of the topographic potential by the isostatic model. Numerical studies show that about 75% and 57% of the topographic potentials are compensated by the potential beneath it in Iran and Tibet. In addition, correlation analysis shows that there is linear relation between the topographic above the sea level and underlying topographic masses in the lowfrequencies in the crustal models. Our investigation shows that about 580±7.4 metre (in average) of the topographic heights are not compensated by variable the crustal root and density.

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variations on electrical behavior of a neocortical neuron model . Acta Biol. Hung. 65 , 379 – 384 . 6. Shirahata , T. ( 2015 ) Numerical study of a mathematical

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M. Zhan 2009 Numerical study on deformation behaviors of thin-walled tube NC bending with large diameter and small bending radius Computational Materials Science

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–202. Dunai L. Ádány S., Kovács N., Calado L. Experimental and numerical studies on bolted connections of steel frames under seismic actions , Final Technical Report, Joint Research between Budapest University of Technology and Economics and Technical

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References [1] Howell R. , Qin N. , Edwards J. , et al. ( 2009 ), Wind tunnel and numerical study of a small VAWT . Renewable

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-concrete interaction in dissipative zones of frames: II, Numerical study , Steel and Composite Structures , Vol. 15 , No. 3 , 2013 , pp. 323 – 348 . [7] Ohsaki M

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. A numerical study of the effects of ambient wind direction on flow and dispersion in urban street canyons using the RNG k-ε turbulence model , Atmospheric Environment , Vol. 38 , No. 19 , 2004 , pp. 3039 – 3048 . [13

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2001 87 54501-1 4 Betaa C., Schneider K., Farge M., Bockhorna H. Numerical study of mixing of passive and reactive

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