Assessing seasonal precipitation trends in India using parametric and non-parametric statistical techniques

This paper provides an insight into the long-term trends of the four seasonal and annual precipitations in various climatological regions and sub-regions in India. The trends were useful to investigate whether Indian seasonal rainfall is changing in terms of magnitude or location-wise. Trends were assessed over the period of 1954-2003 using parametric ordinary least square fits and non-parametric Mann-Kendall technique. The trend significance was tested at the 95% confidence level. Apart from the trends for individual climatological regions in India and the average for the whole of India, trends were also specifically determined for the possible smaller geographical areas in order to understand how different the trends would be from the bigger spatial scales. The smaller geographical regions consist of the whole southwestern continental state of Kerala. It was shown that there are decreasing trends in the spring and monsoon rainfall and increasing trends in the autumn and winter rainfalls. These changes are not always homogeneous over various regions, even in the very short scales implying a careful regional analysis would be necessary for drawing conclusions regarding agro-ecological or other local projects requiring change in rainfall information. Furthermore, the differences between the trend magnitudes and directions from the two different methods are significantly small and fall well within the significance limit for all the cases investigated in Indian regions (except where noted). © 2010 Springer-Verlag.

Microbial carbonate precipitation: Correlation of S-wave velocity with calcite precipitation

The use of microbial induced precipitation as a soil improvement technique has been growing in geotechnical domains where ureolytic bacteria that raise the pH of the system and induce calcium carbonate (CaCO3) precipitation are used. For many applications, it is useful to assess the degree of CaCO 3 precipitation by non-destructive testing. This study investigates the feasibility of S-wave velocity measurements to evaluate the amount of calcite precipitation by laboratory testing. Two sets of cemented specimen were tested. The first were samples terminated at different stages of cementation. The second were samples that went through different chemical treatments. These variations were made to find out if these factors would affect the S-wave velocity- cementation relationship. If chemical reaction efficiency was assumed to be constant throughout each test, the relationship between S-wave velocity (Vs) and the amount of CaCO3 precipitation was found to be approximately linear. This correlation between S-wave velocity and calcium carbonate precipitation validates its use as an indicator of the amount of calcite precipitation © 2011 ASCE.

Forecasting high-frequency futures returns using online langevin dynamics

Forecasting the returns of assets at high frequency is the key challenge for high-frequency algorithmic trading strategies. In this paper, we propose a jump-diffusion model for asset price movements that models price and its trend and allows a momentum strategy to be developed. Conditional on jump times, we derive closed-form transition densities for this model. We show how this allows us to extract a trend from high-frequency finance data by using a Rao-Blackwellized variable rate particle filter to filter incoming price data. Our results show that even in the presence of transaction costs our algorithm can achieve a Sharpe ratio above 1 when applied across a portfolio of 75 futures contracts at high frequency. © 2011 IEEE.