scholarly journals EVALUATION OF CELERITY AND VELOCITY FOR TSUNAMI PROPAGATION INTO RIVERS

2012 ◽  
Vol 1 (33) ◽  
pp. 12
Author(s):  
Min Roh ◽  
Hitoshi Tanaka ◽  
Mohammad Bagus Aditaywan ◽  
Akira Mano ◽  
Keiko Udo
Keyword(s):  
Flow Velocity ◽  
Image Data ◽  
Conservation Equation ◽  
Video Data ◽  
Video Image ◽  
Physical Parameters ◽  
Tsunami Propagation ◽  
The Pacific ◽  
Real Phenomenon ◽  
Tohoku Tsunami

Tsunami propagation into river is one of important real phenomenon. During this process, tsunami celerity and flow velocity are significant physical parameters to understand tsunami behaviors. However, the availability of observation was not sufficient in the 2011 off the Pacific Coast of Tohoku Tsunami, whereas several video data can be used to assess the physical parameters such as tsunami celerity and flow velocity. In this study, as a video image analysis method, Particle Image Velocimetry(PIV) and Particle Tracking Velocimetry(PTV) were used to estimate the tsunami flow velocity. Furthermore, the analysis result of video image data was verified by using the conservation equation. Tsunami physical parameter was successfully estimated by the comparison analysis.

Using Motion Detection to Measure Social Polarization in the U.S. House of Representatives

2020 ◽  
pp. 1-10
Author(s):  
Bryce J. Dietrich
Keyword(s):  
Motion Detection ◽  
House Of Representatives ◽  
Social Science Research ◽  
Image Data ◽  
Science Research ◽  
Video Data ◽  
Social Scientists ◽  
Wide Range ◽  
Party Voting ◽  
The Many

Abstract Although previous scholars have used image data to answer important political science questions, less attention has been paid to video-based measures. In this study, I use motion detection to understand the extent to which members of Congress (MCs) literally cross the aisle, but motion detection can be used to study a wide range of political phenomena, like protests, political speeches, campaign events, or oral arguments. I find not only are Democrats and Republicans less willing to literally cross the aisle, but this behavior is also predictive of future party voting, even when previous party voting is included as a control. However, this is one of the many ways motion detection can be used by social scientists. In this way, the present study is not the end, but the beginning of an important new line of research in which video data is more actively used in social science research.

Effects of the Tohoku tsunami of March 11, 2011 on the Pacific coast of Russia

2012 ◽  
Vol 48 (2) ◽  
pp. 124-143 ◽  
Author(s):  
V. M. Kaistrenko ◽  
G. V. Shevchenko ◽  
T. N. Ivel’skaya
Keyword(s):  
Pacific Coast ◽  
The Pacific ◽  
Tohoku Tsunami

Seismically Derived Ground Tilts Related to the 2010 Chilean Tsunami

2021 ◽  
Author(s):  
Jui-Chun Freya Chen ◽  
Wu-Cheng Chi ◽  
Chu-Fang Yang
Keyword(s):  
Deep Ocean ◽  
Propagation Model ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Tsunami Propagation ◽  
Ground Tilt ◽  
Tsunami Waves ◽  
The Pacific ◽  
Seismic Networks ◽  
Back Azimuth

Abstract Developing new ways to observe tsunami contributes to tsunami research. Tidal and deep-ocean gauges are typically used for coastal and offshore observations. Recently, tsunami-induced ground tilts offer a new possibility. The ground tilt signal accompanied by 2010 Mw 8.8 Chilean earthquake were observed at a tiltmeter network in Japan. However, tiltmeter stations are usually not as widely installed as broadband seismometers in other countries. Here, we studied broadband seismic records from Japan’s F-net and found ground tilt signals consistent with previously published tiltmeter dataset for this particular tsunamic event. Similar waveforms can also be found in broadband seismic networks in other countries, such as Taiwan, as well as an ocean-bottom seismometer. We documented a consistent time sequence of evolving back-azimuth directions of the tsunami waves at different stages of tsunami propagation through beamforming-frequency–wavenumber analysis and particle-motion analysis; the outcomes are consistent with the tsunami propagation model provided by the Pacific Tsunami Warning Center. These results shown that dense broadband seismic networks can provide a useful complementary dataset, in addition to tiltmeter arrays and other networks, to study or even monitor tsunami propagation using arrayed methods.

Video Semantic Analysis

2021 ◽  
Vol 11 (2) ◽  
pp. 1-21
Author(s):  
Daniel Danso Essel ◽  
Ben-Bright Benuwa ◽  
Benjamin Ghansah
Keyword(s):  
Dictionary Learning ◽  
Semantic Analysis ◽  
Learning Algorithm ◽  
Recognition Rate ◽  
Image Data ◽  
Video Data ◽  
The Novel ◽  
Video Feature ◽  
Novel Approach ◽  
Video Semantic Analysis

Sparse Representation (SR) and Dictionary Learning (DL) based Classifier have shown promising results in classification tasks, with impressive recognition rate on image data. In Video Semantic Analysis (VSA) however, the local structure of video data contains significant discriminative information required for classification. To the best of our knowledge, this has not been fully explored by recent DL-based approaches. Further, similar coding findings are not being realized from video features with the same video category. Based on the foregoing, a novel learning algorithm, Sparsity based Locality-Sensitive Discriminative Dictionary Learning (SLSDDL) for VSA is proposed in this paper. In the proposed algorithm, a discriminant loss function for the category based on sparse coding of the sparse coefficients is introduced into structure of Locality-Sensitive Dictionary Learning (LSDL) algorithm. Finally, the sparse coefficients for the testing video feature sample are solved by the optimized method of SLSDDL and the classification result for video semantic is obtained by minimizing the error between the original and reconstructed samples. The experimental results show that, the proposed SLSDDL significantly improves the performance of video semantic detection compared with state-of-the-art approaches. The proposed approach also shows robustness to diverse video environments, proving the universality of the novel approach.

scholarly journals Composition, Analysis and Display of Video Image Data of Boring Core and Borehole

1982 ◽  
Vol 1982 (7) ◽  
pp. 67-80
Author(s):  
Kunio MORI ◽  
Shinji MASUMOTO ◽  
Kiyoshi WADATSUMI
Keyword(s):  
Image Data ◽  
Video Image ◽  
Composition Analysis

Video Image Segmentation Using Gaussian Mixture Models Based on the Differential Evolution-Based Parameter Estimation

2011 ◽  
Vol 474-476 ◽  
pp. 442-447
Author(s):  
Zhi Gao Zeng ◽  
Li Xin Ding ◽  
Sheng Qiu Yi ◽  
San You Zeng ◽  
Zi Hua Qiu
Keyword(s):  
Image Segmentation ◽  
Differential Evolution ◽  
Mixture Models ◽  
Clustering Algorithms ◽  
Gaussian Mixture Models ◽  
Expectation Maximization Algorithm ◽  
Image Data ◽  
Gaussian Mixture ◽  
Parameters Estimation ◽  
Video Image

In order to improve the accuracy of the image segmentation in video surveillance sequences and to overcome the limits of the traditional clustering algorithms that can not accurately model the image data sets which Contains noise data, the paper presents an automatic and accurate video image segmentation algorithm, according to the spatial properties, which uses the Gaussian mixture models to segment the image. But the expectation-maximization algorithm is very sensitive to initial values, and easy to fall into local optimums, so the paper presents a differential evolution-based parameters estimation for Gaussian mixture models. The experiment result shows that the segmentation accuracy has been improved greatly than by the traditional segmentation algorithms.

Pulsatile Blood Flow Through a Constricted Porous Artery

2020 ◽  
Vol 17 (2) ◽  
pp. 743-749
Author(s):  
Salah Uddin ◽  
Obaid Ullah Mehmood ◽  
Mahathir Mohamad ◽  
Mahmod Abd Hakim Mohmad ◽  
D. F. Jamil ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Blood Flow ◽  
Flow Velocity ◽  
Nonlinear Differential Equations ◽  
Fluid Velocity ◽  
Volumetric Flow Rate ◽  
Physical Parameters ◽  
Porosity Parameter ◽  
Arterial Blood ◽  
Flow Through

In this paper a speculative study of an incompressible Newtonian blood flow through a constricted porous channel and pulsatile nature is inspected. Porosity parameter λ is incorporated in the momentum equation. Governing nonlinear differential equations are numerically evaluated by employing the perturbation method technique for a very small perturbation parameter ε 1 such that ε ≠ 0 and with conformable boundary conditions. Numerical results of the flow velocity profile and volumetric flow rate have been derived numerically and detailed graphical analysis for different physical parameters porosity, Reynolds number and stenosis has been presented. It is found that arterial blood velocity is dependent upon all of these factors and that the relationship of fluid velocity and flow is more complex and nonlinear than heretofore generally believe. Furthermore the flow velocity enhanced with Reynolds number, porosity parameter and at maximum position of the stenosis/constriction.

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