Arbitrary amplitude ion acoustic solitary waves and double layers in a magnetized auroral plasma with q-nonextensive electrons

Using the Sagdeev pseudo-potential technique, further investigation on the effect of nonextensive hot electrons on finite amplitude nonlinear low-frequency electrostatic waves in a magnetized two-component plasma have been reported in detail. The plasma model consists of cold ions fluid and nonextensively distributed electrons. The existence domain for the nonlinear structures have been established analytically and numerically. Apart from the compressive and rarefactive soliton solutions that have been reported earlier, the present investigation shows that double layer structures can be obtained for certain values of nonextensive electrons in the supersonic Mach number regime. The present results may provide an explanation for the observed nonlinear structures in the auroral region of the Earth’s magnetosphere.     

Unified bounding surface model for monotonic and cyclic behaviour of clay and sand

Acta Geotechnica - This paper presents a constitutive model enabled to simulate monotonic and cyclic behaviour of clay and sand in a unified framework. The bounding surface concept has been...     

Prediction of significant wave height using regressive support vector machines

Wave parameters prediction is an important issue in coastal and offshore engineering. In this literature, several models and methods are introduced. In the recent years, the well-known soft computing approaches, such as artificial neural networks, fuzzy and adaptive neuro-fuzzy inference systems and etc., have been known as novel methods to form intelligent systems, these approaches has also been used to predict wave parameters, as well. It is not a long time that support vector machine (SVM) is introduced as a strong machine learning and data mining tool. In this paper, it is used to predict significant wave height (H_s). The data set used in this study comprises wave wind data gathered from deep water locations in Lake Michigan. Current wind speed (u) and those belonging up to six previous hours are given as input variables, while the significant wave height is the output parameter. The SVM results are compared with those of artificial neural networks, multi-layer perceptron (MLP) and radial basis function (RBF) models. The results show that SVM can be successfully used for prediction of H_s. Furthermore, comparisons indicate that the error statistics of SVM model marginally outperforms ANN even with much less computational time required.     

Ice mass change in Greenland and Antarctica between 1993 and 2013 from satellite gravity measurements

We construct long-term time series of Greenland and Antarctic ice sheet mass change from satellite gravity measurements. A statistical reconstruction approach is developed based on a principal component analysis (PCA) to combine high-resolution spatial modes from the Gravity Recovery and Climate Experiment (GRACE) mission with the gravity information from conventional satellite tracking data. Uncertainties of this reconstruction are rigorously assessed; they include temporal limitations for short GRACE measurements, spatial limitations for the low-resolution conventional tracking data measurements, and limitations of the estimated statistical relationships between low- and high-degree potential coefficients reflected in the PCA modes. Trends of mass variations in Greenland and Antarctica are assessed against a number of previous studies. The resulting time series for Greenland show a higher rate of mass loss than other methods before 2000, while the Antarctic ice sheet appears heavily influenced by interannual variations.