Graphical method to include temperature variation of activation energy in Hall data analysis

A graphical method is presented for Hall data analysis, including the temperature variation of activation energy due to screening. This method removes the discrepancies noted in the analysis of recently reported Hall data on Si(In).

An innovative clustering technique for unsupervized learning in the context of remotely sensed earth resources data analysis

A new clustering technique, based on the concept of immediato neighbourhood, with a novel capability to self-learn the number of clusters expected in the unsupervized environment, has been developed. The method compares favourably with other clustering schemes based on distance measures, both in terms of conceptual innovations and computational economy. Test implementation of the scheme using C-l flight line training sample data in a simulated unsupervized mode has brought out the efficacy of the technique. The technique can easily be implemented as a front end to established pattern classification systems with supervized learning capabilities to derive unified learning systems capable of operating in both supervized and unsupervized environments. This makes the technique an attractive proposition in the context of remotely sensed earth resources data analysis wherein it is essential to have such a unified learning system capability.

Land Surface Temperature with Land Cover Dynamics:Multi-Resolution, Spatio-Temporal Data Analysis of Greater Bangalore

Bangalore is experiencing unprecedented urbanisation in recent times due to concentrated developmental activities with impetus on IT (Information Technology) and BT (Biotechnology) sectors. The concentrated developmental activities has resulted in the increase in population and consequent pressure on infrastructure, natural resources, ultimately giving rise to a plethora of serious challenges such as urban flooding, climate change, etc. One of the perceived impact at local levels is the increase in sensible heat flux from the land surface to the atmosphere, which is also referred as heat island effect. In this communication, we report the changes in land surface temperature (LST) with respect to land cover changes during 1973 to 2007. A novel technique combining the information from sub-pixel class proportions with information from classified image (using signatures of the respective classes collected from the ground) has been used to achieve more reliable classification. The analysis showed positive correlation with the increase in paved surfaces and LST. 466% increase in paved surfaces (buildings, roads, etc.) has lead to the increase in LST by about 2 ºC during the last 2 decades, confirming urban heat island phenomenon. LSTs’ were relatively lower (~ 4 to 7 ºC) at land uses such as vegetation (parks/forests) and water bodies which act as heat sinks.

Network Reconstruction from dynamic data

Over the past decade, many powerful data mining techniques have been developed to analyze temporal and sequential data. The time is now fertile for addressing problems of larger scope under the purview of temporal data mining. The fourth SIGKDD workshop on temporal data mining focused on the question: What can we infer about the structure of a complex dynamical system from observed temporal data? The goals of the workshop were to critically evaluate the need in this area by bringing together leading researchers from industry and academia, and to identify promising technologies and methodologies for doing the same. We provide a brief summary of the workshop proceedings and ideas arising out of the discussions.

Pseudo-Static and Pseudo-Dynamic Stability Analysis of Tailings Dam Under Seismic Conditions

In this paper the seismic slope stability analyses are performed for a typical section of 44 m high water retention type tailings earthen dam located in the eastern part of India, using both the conventional pseudo-static and recent pseudo-dynamic methods. The tailings earthen dam is analyzed for different upstream conditions of reservoir like filled up with compacted and non-compacted dumped waste materials with different water levels of the pond tailings portion. Phreatic surface is generated using seepage analysis in geotechnical software SEEP/W and that same is used in the pseudo-static and pseudo-dynamic analyses to make the approach more realistic. The minimum values of factor of safety using pseudo-static and pseudo-dynamic method are obtained as 1.18 and 1.09 respectively for the chosen seismic zone in India. These values of factor of safety show clearly the demerits of conventional pseudo-static analysis compared to recent pseudo-dynamic analysis, where in addition to the seismic accelerations, duration, frequency of earthquake, body waves traveling during earthquake and amplification effects are considered.

Damage Detection Sensitivity, Specificity and Classification Data Analysis for SHM Systems Design, Verification and Validation

In this paper, we consider applying derived knowledge base regarding the sensitivity and specificity of damage(s) to be detected by an SHM system being designed and qualified. These efforts are necessary toward developing capabilities in SHM system to classify reliably various probable damages through sequence of monitoring, i.e., damage precursor identification, detection of damage and monitoring its progression. We consider the particular problem of visual and ultrasonic NDE based SHM system design requirements, where the damage detection sensitivity and specificity data definitions for a class of structural components are established. Methodologies for SHM system specification creation are discussed in details. Examples are shown to illustrate how the physics of damage detection scheme limits particular damage detection sensitivity and specificity and further how these information can be used in algorithms to combine various different NDE schemes in an SHM system to enhance efficiency and effectiveness. Statistical and data driven models to determine the sensitivity and probability of damage detection (POD) has been demonstrated for plate with varying one-sided line crack using optical and ultrasonic based inspection techniques.

Anthropogenic aerosol fraction over the Indian region: model simulations versus multi-satellite data analysis

Anthropogenic aerosols play a crucial role in our environment, climate, and health. Assessment of spatial and temporal variation in anthropogenic aerosols is essential to determine their impact. Aerosols are of natural and anthropogenic origin and together constitute a composite aerosol system. Information about either component needs elimination of the other from the composite aerosol system. In the present work we estimated the anthropogenic aerosol fraction (AF) over the Indian region following two different approaches and inter-compared the estimates. We espouse multi-satellite data analysis and model simulations (using the CHIMERE Chemical transport model) to derive natural aerosol distribution, which was subsequently used to estimate AF over the Indian subcontinent. These two approaches are significantly different from each other. Natural aerosol satellite-derived information was extracted in terms of optical depth while model simulations yielded mass concentration. Anthropogenic aerosol fraction distribution was studied over two periods in 2008: premonsoon (March-May) and winter (November-February) in regard to the known distinct seasonality in aerosol loading and type over the Indian region. Although both techniques have derived the same property, considerable differences were noted in temporal and spatial distribution. Satellite retrieval of AF showed maximum values during the pre-monsoon and summer months while lowest values were observed in winter. On the other hand, model simulations showed the highest concentration of AF in winter and the lowest during pre-monsoon and summer months. Both techniques provided an annual average AF of comparable magnitude (similar to 0.43 +/- 0.06 from the satellite and similar to 0.48 +/- 0.19 from the model). For winter months the model-estimated AF was similar to 0.62 +/- 0.09, significantly higher than that (0.39 +/- 0.05) estimated from the satellite, while during pre-monsoon months satellite-estimated AF was similar to 0.46 +/- 0.06 and the model simulation estimation similar to 0.53 +/- 0.14. Preliminary results from this work indicate that model-simulated results are nearer to the actual variation as compared to satellite estimation in view of general seasonal variation in aerosol concentrations.

Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method

Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. (C) 2015 Elsevier B.V. All rights reserved.

On-line Dynamic Security Assessment: Determination of Critical Transmission Lines

The main objective of on-line dynamic security assessment is to take preventive action if required or decide remedial action if a contingency actually occurs. Stability limits are obtained for different contingencies. The mode of instability is one of the outputs of dynamic security analysis. When a power system becomes unstable, it splits initially into two groups of generators, and there is a unique cutset in the transmission network known as critical cutset across which the angles become unbounded. The knowledge of critical cutset is additional information obtained from dynamic security assessment, which can be used for initiating preventive control actions, deciding emergency control actions, and adaptive out-of-step relaying. In this article, an analytical technique for the fast prediction of the critical cutset by system simulation for a short duration is presented. Case studies on the New England ten-generator system are presented. The article also suggests the applications of the identification of critical cutsets.

A Legendre spectral element model for sloshing and acoustic analysis in nearly incompressible fluids

A new spectral finite element formulation is presented for modeling the sloshing and the acoustic waves in nearly incompressible fluids. The formulation makes use of the Legendre polynomials in deriving the finite element interpolation shape functions in the Lagrangian frame of reference. The formulated element uses Gauss-Lobatto-Legendre quadrature scheme for integrating the volumetric stiffness and the mass matrices while the conventional Gauss-Legendre quadrature scheme is used on the rotational stiffness matrix to completely eliminate the zero energy modes, which are normally associated with the Lagrangian FE formulation. The numerical performance of the spectral element formulated here is examined by doing the inf-sup test oil a standard rectangular rigid tank partially filled with liquid The eigenvalues obtained from the formulated spectral element are compared with the conventional equally spaced node locations of the h-type Lagrangian finite element and the predicted results show that these spectral elements are more accurate and give superior convergence The efficiency and robustness of the formulated elements are demonstrated by solving few standard problems involving free vibration and dynamic response analysis with undistorted and distorted spectral elements. and the obtained results are compared with available results in the published literature (C) 2009 Elsevier Inc All rights reserved

Local structure in LaMnO3 and CaMnO3 perovskites: A quantitative structural refinement of mn K-edge XANES data

Hole-doped perovskites such as La1-xCaxMnO3 present special magnetic and magnetotransport properties, and it is commonly accepted that the local atomic structure around Mn ions plays a crucial role in determining these peculiar features. Therefore experimental techniques directly probing the local atomic structure, like x-ray absorption spectroscopy (XAS), have been widely exploited to deeply understand the physics of these compounds. Quantitative XAS analysis usually concerns the extended region [extended x-ray absorption fine structure (EXAFS)] of the absorption spectra. The near-edge region [x-ray absorption near-edge spectroscopy (XANES)] of XAS spectra can provide detailed complementary information on the electronic structure and local atomic topology around the absorber. However, the complexity of the XANES analysis usually prevents a quantitative understanding of the data. This work exploits the recently developed MXAN code to achieve a quantitative structural refinement of the Mn K-edge XANES of LaMnO3 and CaMnO3 compounds; they are the end compounds of the doped manganite series LaxCa1-xMnO3. The results derived from the EXAFS and XANES analyses are in good agreement, demonstrating that a quantitative picture of the local structure can be obtained from XANES in these crystalline compounds. Moreover, the quantitative XANES analysis provides topological information not directly achievable from EXAFS data analysis. This work demonstrates that combining the analysis of extended and near-edge regions of Mn K-edge XAS spectra could provide a complete and accurate description of Mn local atomic environment in these compounds.

Spatio-temporal landscape modelling for natural hazard vulnerability analysis in select watersheds of Central Western Ghats

Natural hazards such as landslides are triggered by numerous factors such as ground movements, rock falls, slope failure, debris flows, slope instability, etc. Changes in slope stability happen due to human intervention, anthropogenic activities, change in soil structure, loss or absence of vegetation (changes in land cover), etc. Loss of vegetation happens when the forest is fragmented due to anthropogenic activities. Hence land cover mapping with forest fragmentation can provide vital information for visualising the regions that require immediate attention from slope stability aspects. The main objective of this paper is to understand the rate of change in forest landscape from 1973 to 2004 through multi-sensor remote sensing data analysis. The forest fragmentation index presented here is based on temporal land use information and forest fragmentation model, in which the forest pixels are classified as patch, transitional, edge, perforated, and interior, that give a measure of forest continuity. The analysis carried out for five prominent watersheds of Uttara Kannada district– Aganashini, Bedthi, Kali, Sharavathi and Venkatpura revealed that interior forest is continuously decreasing while patch, transitional, edge and perforated forest show increasing trend. The effect of forest fragmentation on landslide occurrence was visualised by overlaying the landslide occurrence points on classified image and forest fragmentation map. The increasing patch and transitional forest on hill slopes are the areas prone to landslides, evident from the field verification, indicating that deforestation is a major triggering factor for landslides. This emphasises the need for immediate conservation measures for sustainable management of the landscape. Quantifying and describing land use - land cover change and fragmentation is crucial for assessing the effect of land management policies and environmental protection decisions.

Torque Angle Loop Analysis of Synchronous Machines

This paper reports the dynamic stability analysis of a single machine infinite bus system through torque angle loop analysis and forms an extension of the work on Block diagrams and torque angle loop analysis of synchronous machines reported by I. Nagy [3]. It aims to incorporate in the machine model, the damper windings (one on each axis) and to compare the dynamic behaviour of the system with and without damper windings. The effect of using different stabilizing signals (viz. active power and speed deviations) on the dynamic performance is analysed and the significant effect of damper windings on the dynamic behaviour of the system is highlighted.

A Diffusion-Based Processor Reallocation Strategy for Tracking Multiple Dynamically Varying Weather Phenomena

Many meteorological phenomena occur at different locations simultaneously. These phenomena vary temporally and spatially. It is essential to track these multiple phenomena for accurate weather prediction. Efficient analysis require high-resolution simulations which can be conducted by introducing finer resolution nested simulations, nests at the locations of these phenomena. Simultaneous tracking of these multiple weather phenomena requires simultaneous execution of the nests on different subsets of the maximum number of processors for the main weather simulation. Dynamic variation in the number of these nests require efficient processor reallocation strategies. In this paper, we have developed strategies for efficient partitioning and repartitioning of the nests among the processors. As a case study, we consider an application of tracking multiple organized cloud clusters in tropical weather systems. We first present a parallel data analysis algorithm to detect such clouds. We have developed a tree-based hierarchical diffusion method which reallocates processors for the nests such that the redistribution cost is less. We achieve this by a novel tree reorganization approach. We show that our approach exhibits up to 25% lower redistribution cost and 53% lesser hop-bytes than the processor reallocation strategy that does not consider the existing processor allocation.

Fabrication of a novel biomaterial with enhanced mechanical and conducting properties

Conducting polymers have the combined advantages of metal conductivity with ease in processing and biocompatibility; making them extremely versatile for biosensor and tissue engineering applications. However, the inherent brittle property of conducting polymers limits their direct use in such applications which generally warrant soft and flexible material responses. Addition of fillers increases the material compliance, but is achieved at the cost of reduced electrical conductivity. To retain suitable conductivity without compromising the mechanical properties, we fabricate an electroactive blend (dPEDOT) using low grade PEDOT: PSS as the base conducting polymer with polyvinyl alcohol as filler and glycerol as a dopant. Bulk dPEDOT films show a thermally stable response till 110 degrees C with over seven fold increase in room temperature conductivity as compared to 0.002 S cm(-1) for pristine PEDOT: PSS. We characterize the nonlinear stress-strain response of dPEDOT, well described using a Mooney-Rivlin hyperelastic model, and report elastomer-like moduli with ductility similar to fives times its original length. Dynamic mechanical analysis shows constant storage moduli over a large range of frequencies with corresponding linear increase in tan(delta). We relate the enhanced performance of dPEDOT with the underlying structural constituents using FTIR and AFM microscopy. These data demonstrate specific interactions between individual components of dPEDOT, and their effect on surface topography and material properties. Finally, we show biocompatibility of dPEDOT using fibroblasts that have comparable cell morphologies and viability as the control, which make dPEDOT attractive as a biomaterial.