Generic Prediction Rules for Regime Change in Bimodal Processes

Several bimodal complex processes having great socio-economic impact exist in nature, yet more often than not it is non-trivial to find prediction rules for their regime change. Generic prediction rules for regime transition and duration of subsequent regime are given for several two-regime models. It is demonstrated that prediction rules are a universal property of a large class of bimodal processes. An effort is made to explore the applicability of generic prediction rules to real-world bimodal processes, namely the Indian summer monsoon rainfall and the Indian Ocean Dipole event. Time series representative of these phenomena are analyzed to establish their bimodality and to show that prediction rules hold well for these time series also.     

Earthquake Genesis and Earthquake Early Warning Systems: Challenges and a Way Forward

Surveys in Geophysics - Several natural hazards, including earthquakes, may trigger disasters and the presence of disaster drivers further lead to the massive loss of life and property, every year...     

Variogram Fractal Dimension Based Features for Hyperspectral Data Dimensionality Reduction

In this paper a new approach for fractal based dimensionality reduction of hyperspectral data has been proposed. The features have been generated by multiplying variogram fractal dimension value with spectral energy. Fractal dimension bears the information related to the shape or characteristic of the spectral response curves and the spectral energy bears the information related to class separation. It has been observed that, the features provide accuracy better than 90 % in distinguishing different land cover classes in an urban area, different vegetation types belonging to an agricultural area as well as various types of minerals belonging to the same parent class. Statistical comparison with some conventional dimensionality reduction methods validates the fact that the proposed method, having less computational burden than the conventional methods, is able to produce classification statistically equivalent to those of the conventional methods.     

The b-value and fractal dimension of local seismicity around Koyna Dam (India)

Earthquakes began to occur in Koyna region (India) soon after the filling of Koyna Dam in 1962. In the present study, three datasets 1964–1993, 1993–1995, and 1996–1997 are analyzed to study the b-value and fractal dimension. The b-value is calculated using the Gutenberg–Richter relationship and fractal dimension D _corr. using correlation integral method. The estimated b-value and D _corr. of this region before 1993 are found to be in good agreement with previously reported studies. In the subsequent years after 1995, the b-value shows an increase. The estimated b-values of this region are found within the limits of global average. Also, the pattern of spatial clustering of earthquakes show increase in clustering and migration along the three zones called North-East Zone, South-East Zone (SEZ), and Warna Seismic Zone. The earthquake events having depth ≤5 km are largely confined to SEZ. After 1993, the D _corr. shows decrease, implying that earthquake activity gets clustered. This seismic clustering could be helpful for earthquake forecasting.     

On properties of narrow CMEs observed with SOHO/LASCO

We have investigated properties such as speed, angular width, location, acceleration and occurrence rate of narrow CMEs (defined as having angular width ≤20°) observed during 1996–2007 by SOHO/LASCO. The results obtained are compared with those of normal CMEs (angular width >20°) from the same time interval to find whether there are any real differences between the two populations. Our study of 3464 narrow CMEs from the online SOHO/LASCO, CME catalogue leads us to conclude that (1) the fraction of narrow CMEs during solar minimum is 38% and during solar maximum 19%, (2) during solar maximum narrow CMEs are generally faster than normal CMEs, (3) the maximum speed of narrow CMEs is much smaller than that of the normal CMEs, (4) during solar maximum narrow CMEs appear at all latitudes similar to normal CMEs, (5) narrow and normal CMEs have unequal deceleration and (6) the occurrence rate of narrow CMEs remain constant after 1998 until the beginning of 2006 while the normal CMEs occurrence rate seems to follow solar cycle variation until 2004. Thus narrow CMEs and normal CMEs have some differences, in disagreement with previous studies.     

The Development of a Biologically Inspired Propulsor for Unmanned Underwater Vehicles

Fish are remarkable in their ability to maneuver and to control their body position. This ability is the result of the coordinated movement of fins which extend from the body and form control surfaces that can create and vector forces in 3-D. We have embarked on a research program designed to develop a maneuvering propulsor for unmanned undersea vehicles (UUVs) that is based on the pectoral fin of the bluegill sunfish. For this, the anatomy, kinematics, and hydrodynamics of the sunfish pectoral fin were investigated experimentally and through the use of computational fluid dynamics (CFD) simulations. These studies identified that the kinematics of the sunfish pectoral fin are very complex and are not easily described by traditional ldquorowingrdquo- and ldquoflappingrdquo-type kinematics. A consequence of the complex motion is that the pectoral fin can produce forward thrust during both its outstroke (abduction) and instroke (adduction), and while doing so generates only small lateral and lift forces. The results of the biological studies were used to guide the design of robotic pectoral fins which were built as experimental devices and used to investigate the mechanisms of thrust production and control. Because of a design that was based heavily on the anatomy of the sunfish fin, the robotic pectoral fins had the level of control and degrees of freedom necessary to reproduce many of the complex fin motions used by the sunfish during steady swimming. These robotic fins are excellent experimental tools, and are an important first step towards developing propulsive devices that will give the next generation of UUVs the ability to produce and control thrust like highly maneuverable fish.     

Soil characterization using electrical resistivity tomography and geotechnical investigations

Electrical Resistivity Tomography (ERT) has been used in association with Standard Penetration Test (SPT) and Dynamic Cone Penetration Test (DCPT) for Geotechnical investigations at two sites, proposed for thermal power plants, in Uttar Pradesh (UP), India. SPT and DCPT tests were conducted at 28 points and two ERT profiles, each measuring 355 m long, were recorded using 72 electrodes deployed at 5 m spacing. Electrical characterization of subsurface soil was done using borehole data and grain size analysis of the soil samples collected from boreholes. The concept of electrical resistivity variation with soil strength related to the grain size distribution, cementation, porosity and saturation has been used to correlate the transverse resistance of soil with the number of blow counts (N-values) obtained from SPT and DCPT data. It was thus observed that the transverse resistance of soil column is linearly related with the number of blow counts (N-values) at these sites. The linear relationships are site-specific and the coefficients of linear relation are sensitive to the lithology of subsurface formation, which was verified by borehole data. The study demonstrates the usefulness of the ERT method in geotechnical investigations, which is economic, efficient and less time consuming in comparison to the other geotechnical methods, such as SPT and DCPT, used for the purpose.     

Performance assessment of genetic programming (GP) and minimax probability machine regression (MPMR) for prediction of seismic ultrasonic attenuation

The determination of seismic attenuation (s) (dB/cm) is a challenging task in earthquake science. This article employs genetic programming (GP) and minimax probability machine regression (MPMR) for prediction of s. GP is developed based on genetic algorithm. MPMR maximizes the minimum probability of future predictions being within some bound of the true regression function. Porosity (n) (%), permeability (k) (millidarcy), grain size (d) (μm), and clay content (c) (%) have been considered as inputs of GP and MPMR. The output of GP and MPMR is s. The developed GP gives an equation for prediction of s. The results of GP and MPMR have been compared with the artificial neural network. This article gives robust models based on GP and MPMR for prediction of s.     

Analysis and Design of Retaining Wall having Reinforced Cohesive Frictional Backfill

The case of a rigid wall with inclined back face retaining reinforced cohesive-frictional backfill subjected to uniformly distributed surcharge load has been analyzed using limit equilibrium approach. The analysis considers the stability of an element of the failure wedge, which is assumed to develop in the reinforced earth mass adjoining the back face of wall. The non-dimensional charts have been developed for computing the lateral earth pressure on wall and the height of its point of application above the base of wall. The theoretical findings have been verified by model tests on a rigid wall retaining a dry cohesive-frictional soil reinforced by geogrid strips. Experimental results are in good agreement with the theoretical predictions. A design example has been included to illustrate the design procedure.