Seismic activity prediction using computational intelligence techniques in northern Pakistan

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar’s statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.     

Screening Indian Mustard Genotypes for Phytoremediating Arsenic‐Contaminated Soils

Ten Indian mustard (Brassica juncea L.) genotypes were screened for their phytoremediation potential for arsenic (As) contaminated water under laboratory‐controlled conditions. The genotypes were grown in a hydroponic chamber for 20 days in 250‐mL beakers containing As‐contaminated water. During plant development, changes in plant growth, biomass, and total As were evaluated. Of the 10 genotypes (Pusa Agrani, BTO, Pusa Kranti, Pusa Bahar, Pusa Bold, Pusa Basant, Pusa Jai Kisan, Arka Vardhan, Varuna, and Vaibhav) Pusa Jai Kisan was the most effective in phytoremediating As‐contaminated water under hydroponic conditions. This will provide new information for Indian mustard genotypes for phytoremediating As‐contaminated soils.     

A simulation study of microstructure evolution inside the shear band in biaxial compression test

We study the development of microstructure inside the shear band in granular media consisting of elliptical‐shaped particles. Plane strain biaxial compression test was simulated using two‐dimensional distinct element method. The generation of large voids and concentration of excessive particle rotation inside a shear band are found in a quite similar manner to those observed in natural soils. Evolution of the microstructure inside and outside the shear band is studied. The magnitude and direction of particle rotation inside the shear band is influenced by orientation of long axes of elliptical particles. Because of such particle rotations inside the shear band, the preferred alignment of particles becomes horizontal in the residual state, which results in a more anisotropic contact normal distribution oriented along the major principal stress axis. Copyright © 2010 John Wiley & Sons, Ltd.     

Enhanced MEMS-IMU/odometer/GPS integration using mixture particle filter

Dead reckoning techniques such as inertial navigation and odometry are integrated with GPS to avoid interruption of navigation solutions due to lack of visible satellites. A common method to achieve a low-cost navigation solution for land vehicles is to use a MEMS-based inertial measurement unit (IMU) for integration with GPS. This integration is traditionally accomplished by means of a Kalman filter (KF). Due to the significant inherent errors of MEMS inertial sensors and their time-varying changes, which are difficult to model, severe position error growth happens during GPS outages. The positional accuracy provided by the KF is limited by its linearized models. A Particle filter (PF), being a nonlinear technique, can accommodate for arbitrary inertial sensor characteristics and motion dynamics. An enhanced version of the PF, called Mixture PF, is employed in this paper. It samples from both the prior importance density and the observation likelihood, leading to an improved performance. Furthermore, in order to enhance the performance of MEMS-based IMU/GPS integration during GPS outages, the use of pitch and roll calculated from the longitudinal and transversal accelerometers together with the odometer data as a measurement update is proposed in this paper. These updates aid the IMU and limit the positional error growth caused by two horizontal gyroscopes, which are a major source of error during GPS outages. The performance of the proposed method is examined on road trajectories, and results are compared to the three different KF-based solutions. The proposed Mixture PF with velocity, pitch, and roll updates outperformed all the other solutions and exhibited an average improvement of approximately 64% over KF with the same updates, about 85% over KF with velocity updates only, and around 95% over KF without any updates during GPS outages.     

Spectral analysis of local climatic fluctuations

This paper employs spectral analysis to detect regular cyclical patterns or periodicities of local climate parameters of five major cities of Pakistan. Our calculations show that the temperature of all major climate stations may be affected by ENSO or QBO or Sunspot Cycles. As for the rainfall, what we find is that Pakistan summer monsoon exhibits a fairly similar bienniality with that of the Indian monsoon.     

Comparison of rockfall susceptibility assessment at local and regional scale: a case study in the north of Beijing (China)

This study shows a rockfall susceptibility assessment at local scale in north Beijing of China, including the identification of rockfall sources onsite by terrain and rock discontinuities analysis and run-out distance prediction by Rocfall^? simulation. Two types of rockfall were defined including one type on the cliffs with long inclined slopes and another type on the road slopes with low height. Two historical rockfall events were used to back-calibrating the parameters used for run-out distance simulation. Based on the work, rockfall susceptibility map at local scale was created in GIS, which was compared with the map obtained at regional scale (entire Huairou district scale). Due to the difference of approaches applied, procedure of assessment and types of source data acquired, the two resulting rockfall susceptibility maps are proved to be different. Still, both of them are useful and could be used at different level’s decision for rockfall prevention and mitigation. Different types of uncertainties exist in the study of rockfall susceptibility assessment. To reduce the uncertainties, studies on both approaches and techniques are suggested.     

Adaptive state estimation of groundwater contaminant boundary input flux in a 2-dimensional aquifer

In many circumstances involving heat and mass transfer issues, it is considered impractical to measure the input flux and the resulting state distribution in the domain. Therefore, the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes imperative. Adaptive state estimator (ASE) is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique, thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman filters. The ASE is particularly designed for a system that encompasses independent unknowns and /or random switching of input and measurement biases. The present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE, which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10% in 2-dimensional problems. Numerical simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux scenarios. Results also show that ASE enjoys a better estimation performance than its competitor, Recursive Least Square Estimator (RLSE) due to its larger error tolerance in greater process noise regimes. ASE’s inherent deficiency of being slower than the RLSE, resulting from the complexity of algorithm, was also noticed. The chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location.     

Dominant impact of South Asian low heat on summer monsoon rainfall over Central India

Although previous literature have considered Southern Oscillation Index (SOI), Indian Dipole, and SST as the major teleconnection patterns to explain the variability of summer monsoon rainfall over India. South Asia low pressure and Indian Ocean high are the centers of action that dominates atmospheric circulations in Indian continent. This paper examines the possible impact of South Asian low pressure distribution on the variability of summer monsoon rainfall of India using centers of action approach. Our analysis demonstrates that the explanation of summer monsoon rainfall variability over Central India is improved significantly if the SOI is replaced by South Asian low heat. This contribution also explains the physical mechanisms to establish the relationships between the South Asian low heat and regional climate by examining composite maps of large-scale circulation fields using NCEP/NCAR Reanalysis data.     

Short‐term variability in isotopic composition of precipitation: A case study from the Midwestern United States

Oxygen and deuterium isotopes in precipitation were analysed to define local isotopic trends in Iowa, US. The area is far inland from an oceanic source and the observed averages of δ¹⁸O and δ D are ? 6·43‰ and ? 41·35‰ for Ames, ? 7·53‰ and ? 51·33‰ for Cedar Falls, and ? 6·01‰ and ? 38·19‰ for Iowa City, respectively. Although these data generally follow global trends, they are different when compared to a semi‐arid mid‐continental location in North Platt, Nebraska. The local meteoric water lines of Iowa are δ D = 7·68 δ¹⁸O + 8·0 for Ames, δ D = 7·62 δ¹⁸O + 6·07 for Cedar Falls, and δ D = 7·78 δ¹⁸O + 8·61 for Iowa City. The current Iowa study compares well with a study conducted in Ames, Iowa, 10 years earlier. The differences between Iowa and Nebraska studies are attributed to a variable climate across the northern Great Plains ranging from sub‐humid in the east to semi‐arid in the west. Iowa being further east in the region is more strongly influenced by a moist sub‐humid to humid climate fed by the tropical air stream from the Gulf of Mexico. The average d‐excess values are 10·06‰ for Ames, 8·92‰ for Cedar Falls and 9·92‰ for Iowa City. Eighty seven percent of the samples are within the global d‐excess range of 0‰ and 20‰. The results are similar to previous studies, including those by National Atmospheric Deposition Programs and International Atomic Energy Agency. It appears that the impact of recycled water or secondary evaporation on δ¹⁸O values of area precipitation is minimal. Copyright © 2008 John Wiley & Sons, Ltd.