排序方式： 共有13条查询结果，搜索用时 15 毫秒
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Seba Susan Achin Saxena Anuvart Budhwar Akshay Takhi Abhishek Varshney 《Journal of the Indian Society of Remote Sensing》2017,45(5):899-901
A fast cyclone frame prediction is proposed in this paper that fits a Gaussian Mixture model on the spatio-temporal data extracted from the three penultimate time-lapse frames, prior to fuzzy regression. Unlike the previous work in Verma and Pal (In: Applied Imagery Pattern Recognition Workshop (AIPR), pp. 1–8, 2010) that models the entire history on a per pixel basis, a single Gaussian mixture is used for fitting the spatio-temporal data within the time-span of the last three frames, making the process faster and more accurate. The increase in accuracy is attributed to the fact that cyclones evolve over time and thus the recent frames give a more meaningful insight into the predictions for the next frame. The number of components in the Gaussian mixture is determined from the occurrence of equally likely modes that correspond to high entropy peaks. Our results on satellite videos of recent cyclones that hit the Indian seas show a high accuracy of frame prediction. 相似文献
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The elastic and thermodynamic properties of Li2O for high pressures are presented. For cubic Li2O, model effective interatomic interaction potential incorporating long-range Coulomb, charge transfer interactions, covalency effect, Hafemeister and Flygare type short-range overlap repulsion extended up to the second neighbor ions and van der Waals interactions is formulated. Both charge transfer interactions and covalency effect apart from long-range Coulomb are important in revealing high-pressure-induced associated volume collapse, elastic, and thermodynamical properties. The elastic constants, Debye temperature, and thermal expansion coefficient obtained are in good agreement with the available experimental data and other theoretical results. The Li2O is mechanically stiffened, thermally softened, and brittle in nature as inferred from the pressure-dependent elastic constants behavior. To our knowledge, this is the first quantitative theoretical prediction of the pressure dependence of elastic, thermal, and thermodynamical properties of Li2O and still awaits experimental confirmation. 相似文献
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Experiments on integral length scale control in atmospheric boundary layer wind tunnel 总被引：2，自引：1，他引：1
Accurate predictions of turbulent characteristics in the atmospheric boundary layer (ABL) depends on understanding the effects of surface roughness on the spatial distribution of velocity, turbulence intensity, and turbulence length scales. Simulation of the ABL characteristics have been performed in a short test section length wind tunnel to determine the appropriate length scale factor for modeling, which ensures correct aeroelastic behavior of structural models for non-aerodynamic applications. The ABL characteristics have been simulated by using various configurations of passive devices such as vortex generators, air barriers, and slot in the test section floor which was extended into the contraction cone. Mean velocity and velocity fluctuations have been measured using a hot-wire anemometry system. Mean velocity, turbulence intensity, turbulence scale, and power spectral density of velocity fluctuations have been obtained from the experiments for various configuration of the passive devices. It is shown that the integral length scale factor can be controlled using various combinations of the passive devices. 相似文献
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Artificial neural network (ANN) modeling has been performed to predict turbulent boundary layer characteristics for rough terrain based on experimental tests conducted in a boundary-layer wind tunnel to simulate atmospheric boundary layer using passive roughness devices such as spires, barriers, roughness elements on the floor, and slots in the extended test section. Different configurations of passive devices assisted to simulate urban terrains. A part of the wind tunnel test results are used as training sets for the ANN, and the other part of the test results are used to compare the prediction results of the ANN. Two ANN models have been developed in this study. The first one has been used to predict mean velocity, turbulence intensity, and model length scale factor. Results show that ANN is an efficient, accurate, and robust modeling procedure to predict turbulent characteristics of wind. In particular, it was found that the ANN-predicted wind mean velocities are within 4.7%, turbulence intensities are within 6.2%, and model length scale factors are within 3.8% of the actual measured values. In addition, another ANN model has been developed to predict instantaneous velocities that enables calculating the power spectral density of longitudinal velocity fluctuations. Results show that the predicted power spectra are in a good agreement with the power spectra obtained from measured instantaneous velocities. 相似文献
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Anthony Astoul Christopher Filliter Eric Mason Andrew Rau-Chaplin Kunal Shridhar Blesson Varghese Naman Varshney 《Bulletin of Earthquake Engineering》2013,11(6):1973-2005
An automated, real-time, multiple sensor data source relying and globally applicable earthquake loss model and visualiser is desirable for post-event earthquake analysis. To achieve this there is a need to support rapid data ingestion, loss estimation and integration of data from multiple data sources and rapid visualisation at multiple geographic levels. In this paper, the design and development of the Automated Post-Event Earthquake Loss Estimation and Visualisation (APE-ELEV) system for real-time estimation and visualisation of insured losses incurred due to earthquakes is presented. A model for estimating ground up and net of facultative losses due to earthquakes in near real-time is implemented. Since post-event data is often available immediately from multiple disparate sources, a geo-browser is employed to facilitate the visualisation and integration of earthquake hazard, exposure and loss data. The feasibility of APE-ELEV is demonstrated using a test case earthquake that occurred in Tohoku, Japan (2011). The APE-ELEV model is further validated for ten global earthquakes using industry loss data. 相似文献
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P. Jain S. Varshney S. Srivastava 《International Journal of Environmental Science and Technology》2016,13(12):2893-2904
In present work, fabrication of functionally tailored nanobiomaterials paraben-modified nanocellulose (PNC) and (2,3-epoxypropyl) trimethylammonium chloride-modified nanocellulose (EPTMAC-NC) for the remediation of trivalent and hexavalent chromium, respectively, from water streams has been done. The resulting PNC and EPTMAC-NC were characterized before and after sorption of chromium using spectroscopic and microscopic techniques. The sorption performance of PNC (23.92 mg/g; 95.67 %) and EPTMAC-NC (23.99 mg/g; 95.94 %) was evaluated for trivalent and hexavalent chromium, respectively, at 0.5 g biosorbent dose; 500 mL sample volume; 25 mg/L chromium conc.; 40 min kinetic time; pH (6.5 for trivalent and 2.5 for hexavalent chromium) and 298 K temperature. From isothermic, kinetic and thermodynamic modeling, the sorption of trivalent and hexavalent chromium was physisorption, spontaneous, feasible and endothermic in nature. These findings expose new path in the line of high performance, scalable and economic nanobiomaterials for the abatement of toxic metals from water streams. 相似文献
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Logistic Regression for Feature Selection and Soft Classification of Remote Sensing Data 总被引：2，自引：0，他引：2
Feature selection is a key task in remote sensing data processing, particularly in case of classification from hyperspectral images. A logistic regression (LR) model may be used to predict the probabilities of the classes on the basis of the input features, after ranking them according to their relative importance. In this letter, the LR model is applied for both the feature selection and the classification of remotely sensed images, where more informative soft classifications are produced naturally. The results indicate that, with fewer restrictive assumptions, the LR model is able to reduce the features substantially without any significant decrease in the classification accuracy of both the soft and hard classifications 相似文献
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Kapil Varshney 《Theoretical and Applied Climatology》2013,111(3-4):427-435
Helical tip vortices in the wake of a wind turbine have been investigated in this study. To elucidate the near-wake flow field of the wind turbine, the wake has been explored in the Reynolds number (Re) range 1000 ≤?Re?≤?5000 using qualitative dye flow visualization and quantitative digital particle-image velocimetry techniques. Flow visualization showed the dye getting trapped in the shape of spirals surrounding the helical vortex cores. It was found that the helical vortex core size was increasing with downstream distance. It was also found that the normalized stream-wise component of the wake velocity decreased with increasing tip-speed ratios. The results indicate that vorticity peaks at the center of the core and it decays as the vortex moves downstream, showing that the viscous dissipation is active even at length scales of approximately 5 diameters. 相似文献