scholarly journals THE DETERMINATION METHOD OF EXTREME EARTHQUAKE DISASTER AREA BASED ON THE DUST DETECTION RESULT FROM GF-4 DATA

2018 ◽  
Vol XLII-3 ◽  
pp. 309-312
Author(s):  
A. Dou ◽  
L. Ding ◽  
M. Chen ◽  
X. Wang
Keyword(s):  
The Other ◽  
Detection Methods ◽  
Dust Particles ◽  
Earthquake Disaster ◽  
Intensity Assessment ◽  
Disaster Area ◽  
Area Basis ◽  
Dust Detection ◽  
Disaster Intensity ◽  
Spectrum Characteristics

The remote sensing has played an important role in many earthquake emergencies by rapidly providing the building damage, road damage, landslide and other disaster information. The earthquake in the mountains often caused to the loosening of the mountains and the blowing of the dust in the epicentre area. The dust particles are more serious in the epicentre area than the other disaster area. Basis on the analysis of abnormal spectrum characteristics, the dust detection methods from medium and high resolutions satellite imagery are studied in order to determinate the extreme earthquake disaster area. The results indicate the distribution of extreme disaster can be acquired using the dust detection information from imagery, which can provide great help for disaster intensity assessment.

The Practical Research of Engineering Materials for the Temporary House after Earthquake

2014 ◽  
Vol 978 ◽  
pp. 27-30
Author(s):  
Si Ru Qian
Keyword(s):  
Wenchuan Earthquake ◽  
Large Scale ◽  
Earthquake Disaster ◽  
The Wenchuan Earthquake ◽  
Disaster Area ◽  
Practical Research ◽  
Engineering Materials ◽  
First Time ◽  
Large Scale Project

After the WenChuan earthquake in may 12,2008,Many province government built the temporary houses for earthquake disaster area.For the first time, they initiate such large scale project, there are many problems emerged during the process of construction such problem like economy ,environment, engineering materials and technology. In this article, we collect problems and analysis them ,seek for the possible measures of construct the temporary house and the effective way to rebuilt the disaster area.

scholarly journals Maternal Anxiety 16 Months after the Great East Japan Earthquake Disaster Area: First Report

Health ◽  
2014 ◽  
Vol 06 (10) ◽  
pp. 870-878
Author(s):  
Hatsumi Yoshii ◽  
Hidemitsu Saito ◽  
Saya Kikuchi ◽  
Takashi Ueno ◽  
Kineko Sato
Keyword(s):  
Great East Japan Earthquake ◽  
Maternal Anxiety ◽  
Earthquake Disaster ◽  
First Report ◽  
Disaster Area

scholarly journals Dust detection in solar panel using image processing techniques: A review

2020 ◽  
Vol 9 (8) ◽  
pp. e321985107 ◽  
Author(s):  
Gabriel Moura Dantas ◽  
Odilon Linhares Carvalho Mendes ◽  
Saulo Macêdo Maia ◽  
Auzuir Ripardo De Alexandria
Keyword(s):  
Image Processing ◽  
Monitoring And Evaluation ◽  
Dust Particles ◽  
Solar Panels ◽  
Photovoltaic Panel ◽  
Future Studies ◽  
Image Processing Techniques ◽  
Dust Detection ◽  
Two Parameters ◽  
Processing Techniques

The performance of a photovoltaic panel is affected by its orientation and angular inclination with the horizontal plane. This occurs because these two parameters alter the amount of solar energy received by the surface of the photovoltaic panel. There are also environmental factors that affect energy production, one example is the dust. Dust particles accumulated on the surface of the panel reduce the arrival of light to the solar modules, reducing the amount of generated energy. The cleaning or mitigation of the modules is important and, to optimize these processes, constant monitoring and evaluation must be carried out. In order to increase the efficiency of photovoltaic panels, the use of image processing methods can be considered for the detection of dust. Therefore, the creation of a document that gathers and analyzes the results of different works developed to solve this problem facilitates access to information, allowing a better understanding of what has already been done and how it can be improved. The objective of this article is to review researches that uses image processing techniques to detect dust on solar panels, in order to compile information to assist research in the area and provide inspiration for future studies.

Predication of River Water Quality Based on Gray Dynamic Model Group in Wenchuan Earthquake Disaster Area

2013 ◽  
Vol 316-317 ◽  
pp. 599-605
Author(s):  
Feng Qian ◽  
Wei Lin ◽  
Bo Hu ◽  
Jing Jun Liu ◽  
Ming Biao Xiong
Keyword(s):  
Water Quality ◽  
River Water ◽  
Wenchuan Earthquake ◽  
Water Loss ◽  
River Water Quality ◽  
Total Hardness ◽  
Earthquake Disaster ◽  
Soil And Water Loss ◽  
Disaster Area ◽  
Soil And Water

“5.12 Wenchuan earthquake”triggered floods, landslide, collapse and secondary geological disaster, trigger a new soil and water loss, having the significant influence to the local river water quality.This article through the statistical analysis of minjiang river and jiangyou wenchuan, beichuan station 2006 ~ 2011 water conditions material, discussing the before and after the earthquake disaster areas of river water quality change characteristics. The results showed From ammonia nitrogen source analysis, urban sewage and industrial waste water, agricultural non-point source pollution and earthquake that triggered the new soil and water loss is the main pollution source. Based on the hydrological site total hardness concentration prediction, we can find wenchuan earthquake disaster area total hardness concentration significantly increase trend.

scholarly journals A lectin-coupled porous silicon-based biosensor: label-free optical detection of bacteria in a real-time mode

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mona Yaghoubi ◽  
Fereshteh Rahimi ◽  
Babak Negahdari ◽  
Ali Hossein Rezayan ◽  
Azizollah Shafiekhani
Keyword(s):  
Fourier Transform ◽  
Porous Silicon ◽  
Real Time ◽  
Limit Of Detection ◽  
Principal Component ◽  
The Other ◽  
Detection Methods ◽  
Carbohydrate Binding ◽  
Label Free ◽  
E Coli

Abstract Accuracy and speed of detection, along with technical and instrumental simplicity, are indispensable for the bacterial detection methods. Porous silicon (PSi) has unique optical and chemical properties which makes it a good candidate for biosensing applications. On the other hand, lectins have specific carbohydrate-binding properties and are inexpensive compared to popular antibodies. We propose a lectin-conjugated PSi-based biosensor for label-free and real-time detection of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) by reflectometric interference Fourier transform spectroscopy (RIFTS). We modified meso-PSiO2 (10–40 nm pore diameter) with three lectins of ConA (Concanavalin A), WGA (Wheat Germ Agglutinin), and UEA (Ulex europaeus agglutinin) with various carbohydrate specificities, as bioreceptor. The results showed that ConA and WGA have the highest binding affinity for E. coli and S. aureus respectively and hence can effectively detect them. This was confirmed by 6.8% and 7.8% decrease in peak amplitude of fast Fourier transform (FFT) spectra (at 105 cells mL−1 concentration). A limit of detection (LOD) of about 103 cells mL−1 and a linear response range of 103 to 105 cells mL−1 were observed for both ConA-E. coli and WGA-S. aureus interaction platforms that are comparable to the other reports in the literature. Dissimilar response patterns among lectins can be attributed to the different bacterial cell wall structures. Further assessments were carried out by applying the biosensor for the detection of Klebsiella aerogenes and Bacillus subtilis bacteria. The overall obtained results reinforced the conjecture that the WGA and ConA have a stronger interaction with Gram-positive and Gram-negative bacteria, respectively. Therefore, it seems that specific lectins can be suggested for bacterial Gram-typing or even serotyping. These observations were confirmed by the principal component analysis (PCA) model.

Performance Comparison of Wideband Radar Target Detection Methods

2014 ◽  
Vol 971-973 ◽  
pp. 1680-1683
Author(s):  
Miao He ◽  
Li Yu Tian ◽  
Xiong Jun Fu ◽  
Yun Chen Jiang
Keyword(s):  
Target Detection ◽  
Pulse Train ◽  
Performance Comparison ◽  
The Other ◽  
Detection Methods ◽  
Radar Target ◽  
Random Parameters ◽  
Related Model ◽  
Performance Curves ◽  
Wideband Radar

In wideband radar situation, target-spread and all scattering points back wave could be considered as the pulse train of random parameters. The wideband radar target and built the related model. Then it gave two methods of target detection, one is Energy Accumulation and the other is the IPTRP. It also presented the simulation result of these two methods performance curves. It showed that the IPTRP improved by more than 3dB in the same SNR.

Dust detection by antenna instruments

2020 ◽  
Author(s):  
Zoltan Sternovsky ◽  
Ming-Hsueh Shen ◽  
Michael DeLuca ◽  
Åshild Fredriksen ◽  
Mihály Horányi ◽  
...  
Keyword(s):  
Sampling Rate ◽  
Laboratory Data ◽  
Quantitative Description ◽  
High Rate ◽  
Dust Particles ◽  
Electric Signal ◽  
Accelerator Facility ◽  
Spacecraft Potential ◽  
Dust Detection ◽  
The Impact

<p>Antenna instruments on space missions have been used to detect dust particles and characterize dust populations. The antennas register the transient electric signal generated by the expansion of the impact plasma from the dust impact on the spacecraft body or the antenna. Given the large effective sensitive area, antenna instruments offer an advantage over dedicated dust detectors for dust populations with low fluxes. The dust accelerator facility operated at the University of Colorado has been employed to investigate the physical mechanisms of antenna signal generation. The dominant mechanism is related to the charging of the spacecraft (or antenna) by collecting some fraction of electrons and ions from the impact plasma. We have carried out a number of experimental campaigns in order to characterize the dust impact charge yields from relevant materials, the effective temperatures of dust impact plasmas, and variations of the antenna signals with spacecraft potential, or magnetic field. Here we report on a physical model that provides a good qualitative and quantitative description of the antenna waveforms recorded in laboratory conditions. The model is based on the separation of the electrons from the ions in the impact plasma and their different timescales of expansion. The escaping and collected fractions of charges are driven by the spacecraft potential. Fitting the model to the laboratory data revealed that the electrons in the impact plasma have an isotropic distribution, while ions are dominantly moving away from the dust impact location. Identifying the fine details in the antenna signals requires a relatively high sampling rate and thus not commonly resolved for past instruments. The high-rate mode of the FIELDS instrument on the Parker Solar Probe, however, can be used to verify the proposed model.</p>

In situ dust measurements in the solar wind from S/WAVES TDS instrument on STEREO mission

2020 ◽  
Author(s):  
Kristina Rackovic Babic ◽  
Karine Issautier ◽  
Arnaud Zaslavsky
Keyword(s):  
Solar Wind ◽  
Mass Density ◽  
Dust Particles ◽  
S Waves ◽  
Stereo Mission ◽  
Monopole Antennas ◽  
Dust Detection ◽  
The One ◽  
Electric Signals

<p>Dust particles represent an important fraction of the matter composing the interplanetary medium. At 1 A.U. dust mass density is comparable to the one of the solar wind. The large number and broad diversity of dust particles detected by the radio instrument on the STEREO satellites recommend this mission for a closer dust investigation. In situ dust measurements are based on the detection of the charges generated by dust impacts, recorded by the S/WAVES instrument near 1 A.U. since the beginning of the STEREO mission. We study the electric signals produced by these impacts, using the waveform sampler data produced by the TDS subsystem of the radio instrument, connected to three monopole antennas. For this study, we concentrate on macroscopic dust particles (~0.1 microns) whose impact generated nearly simultaneous pulses on the antennas. In particular, we present statistics of typical shapes and features of these signals based on the TDS electric potential time-series and compare the data to a theoretical model of how pulses are generated by charge collection.<br>These results will have implications on dust detection from Parker Solar Probe and Solar Orbiter missions.</p>

Learning Factorial Codes by Predictability Minimization

1992 ◽  
Vol 4 (6) ◽  
pp. 863-879 ◽  
Author(s):  
Jürgen Schmidhuber
Keyword(s):  
Unsupervised Learning ◽  
Supervised Learning ◽  
General Principle ◽  
Novelty Detection ◽  
The Other ◽  
Detection Methods ◽  
Local Algorithm ◽  
The Novel ◽  
Abstract Concepts ◽  
Internal Representations

I propose a novel general principle for unsupervised learning of distributed nonredundant internal representations of input patterns. The principle is based on two opposing forces. For each representational unit there is an adaptive predictor, which tries to predict the unit from the remaining units. In turn, each unit tries to react to the environment such that it minimizes its predictability. This encourages each unit to filter "abstract concepts" out of the environmental input such that these concepts are statistically independent of those on which the other units focus. I discuss various simple yet potentially powerful implementations of the principle that aim at finding binary factorial codes (Barlow et al. 1989), i.e., codes where the probability of the occurrence of a particular input is simply the product of the probabilities of the corresponding code symbols. Such codes are potentially relevant for (1) segmentation tasks, (2) speeding up supervised learning, and (3) novelty detection. Methods for finding factorial codes automatically implement Occam's razor for finding codes using a minimal number of units. Unlike previous methods the novel principle has a potential for removing not only linear but also nonlinear output redundancy. Illustrative experiments show that algorithms based on the principle of predictability minimization are practically feasible. The final part of this paper describes an entirely local algorithm that has a potential for learning unique representations of extended input sequences.

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