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It is used for delivery of data to support assessment of losses, and in evaluation as well as formulation of rehabilitation plans.
The sources of the data will include scholarly journals, government documents, and case studies.
Data Collection The data collection for this part will be done through surveys and documents, reports, journal papers and publications about infrastructure development and disaster risk management.
Data Analysis The collected qualitative data shall be analyzed via the thematic analysis approach in order to reveal the key themes and insights concerning infrastructure resilience and DRM.
• Utilization of Geographic Information Systems (GIS) and data analytics is much needed.

The data come from SQL Server 2000 and create the structure of data warehouse.
Building the Data Warehouse.
Data Warehousing: Bringing It All Together.
Data warehousing fundamentals, 2nd Edition.
Current Practices in Data Warehousing.

Local linear embedding is one of the main algorithms in the manifold learning, which is also a new dimension reduction technique of the nonlinear data.
Fig. 1 Swissroll examples of dimension reduction For the high-dimensioned in a D-dimensioned group Xi∈RD,i=1,…,N, if a nonlinear f:Y→X, Yi∈Rd,i=1,… ,N,d≤D is implied, the main goal of LLE algorithm is to search for a reflecting relation between Xi and Yi, then to realize the dimension reduction and identification of the data, which provides a useful tool for the data analysis.
The data Xi and its neighbor can be represented by the weight coefficient of the neighbor data.
We use the LabVIEW software writing data acquisition procedure to accomplish the data collection.
1.2446 The three states of the AE signal phase space reconstruction, reconstruction of the experience of 12 selected embedding dimension, delay time 1, the reconstructed three sets of data locally linear embedding dimension reduction, After the dimension reduction of data as the feature vectors, and then the tool will be reflected in three different states of the feature vector into the support vector machine support vector machine training, the training data shown in Table 1.

Sulfur Oxidation and Coupled Iron Reduction at Low Temperatures Daniel Kupka1,a, Mark Dopson 2,b and Olli H.
Tuovinen3,c 1 Institute of Geotechnics, Slovak Academy of Sciences, Watsonova 45, 043 53 Košice, Slovakia 2 Department of Molecular Biology, Umeå University, SE-901 87 Umeå, Sweden 3 Department of Microbiology, Ohio State University, 484 West 12th Avenue, Columbus, Ohio 432104 a dankup@saske.sk, bmark.dopson@molbiol.umu.se, c tuovinen.1@osu.edu Keywords: Acidithiobacillus ferrooxidans, psychrotrophic, iron, sulfur, oxidation, reduction jarosite, schwertmannite.
Upon sulfur oxidation, sulfate formation was associated with a decrease in the pH, and the concentration of Fe 3+ decreased because of its concurrent reduction to Fe 2+ in elemental sulfur media.
The data indicated that the Fe 3+/Fe 2+ redox pair could compete with the O2/H2O couple as an alternative acceptor of electrons from the bacterial sulfur oxidation.

In this report, the Zr-MCM-41 catalyst prepared by the grafting method was investigated on the MPV reduction of acetophenone.
The surface areas were evaluated with the BET methods by the N2 adsorption-desorption data at 77 K using BELSORP mini (BEL Japan, Inc.).
Results and discussion The catalytic activity of Zr supported MCM-41 have been evaluated in the liquid phase MPV reduction of acetophenone.
Figure 2 indicates the effect of reaction temperature on MPV reduction over Zr supported MCM-41 catalysts prepared by the grafting and impregnation method.
Fig. 2 Effect of reaction temperature on MPV reduction over Zr supported MCM-41 catallyst: (■) 4.6 wt% Zr-MCM-41-graft and (●) 5 wt% Zr/MCM-41-imp. 20 K Fig. 1 Effect of Zr loading on MPV reduction over Zr supported MCM-41 catallyst: (■) Zr-MCM-41-graft and (●) Zr/MCM-41-imp.

With the development of the society, has formed a mass of confused high-dimensional data, and urge people to obtain effective knowledge ability.
The researchers tried some solutions, such as zhang yan equal [1] of the multidimensional data model based on granular computing method is discussed.
Clustering analysis is a kind of commonly used information granulation method[2], it will be the object of a given data set organically together, form a mutually disjoint partition results.
Results The EEG data used in this paper is the BCI Laboratory of Jiangxi Institute of technology through the EEG acquisition of College students.
The granulating mechanism of complex data and data modeling [D].

This article from the biodegradation, microbial sulfate reduction, thermal decompositionchemistry, chemical sulfate reduction and magmatic 5 aspects to analyze the formation mechanism of hydrogen sulfide gas in coal mine, a coal mine combined with field data, analysis of hydrogen sulfide gas in the coal mining the transport mechanisms.
Our most serious, the data show that China's high-sulfur coal accounted for 36.6%, while hydrogen sulfide influx Face coal mining, to cause serious harm to human health[5]-[6].
Thermo-chemically decomposed and thermochemical sulfate reduction of organic sulfur.
The Huaying Mountain geological data show that the higher the content of the mining area of soluble carbonates, and a large area exposed, showing the direction of NNS distribution region, in particular the Department of Yang Miocene limestone stack thickness, quality of pure, karst development, the formation of many caves, dissolved bucket, sinkholes, ground temperature of the heat demand less than a chemical reaction.
Microbial sulfate reduction.

Compared with some other methods applied in data parallelism that can parallelize reduction operations on a force-array, our method achieves high performance especially when the simulation system is characterized by irregular geometry or by inhomogeneous atom densities.
Newton’s third law brings loop-carried data dependences in the force-computing loop.
Some strategies can be used to remove possible data dependence on force-array of MD simulations, which can be applied in data parallelism [6-7].
But too many blocks incur worse data locality.
The kind of data structure simplifies the communication between producer and consumer.

Then CO2 emission is calculated in the RHF—EAF flow for treating V-Ti magnetite according to data from the pilot plant in Pangang Group.
Based on the data from design and real production the text calculated the quantum of CO2 emissions.
According to these data above we can calculate the ratio of blast furnace gas and coke oven gas and the result is that among the gas mixture blast furnace gas accounts for 60% ,of course the rest is coke oven gas.
The carbon content of metallized pellets is about 5% and the carbon content in the hot metal is around 2%.According to the mass balance calculation we can get the data of CO2 emissions to produce one ton hot metal.
The calculation is based on the energy consumption which is different from the calculation of the RHF-EAF process and all of the data come from the real production.

It shows the presence of single trigonal phase, FeTiO3, space group #148, with lattice periods a = 5.0816 Å, c = 14.051 Å corresponding well to literature data [10].
Numerous data on hydrogen sorption performances of AB2-type hydrogen storage materials (A = Ti, Zr; B = Cr, Mn, Fe, Ni, Cu, V) were published since late 1970s.
The reference data were fitted using the simplest linear regression according to the formula: 3.1 Seven independent fitting variables X1…X7 are listed in Table 1.
Figure 5: Relations between experimental (calculated using Van’t Hoff equation from the reference ΔH and ΔS data) and calculated (eqn. 3.1) values of equilibrium hydrogen pressures for AB2-type intermetallic hydrides at various temperatures The values of equilibrium hydrogen pressures for AB2-type intermetallic hydrides at various temperatures calculated from the reference thermodynamic data show very good correlation with the corresponding values calculated from the alloy’s compositions using Eq. 3.1 (Figure 5).
Geological Survey Data Series 140, available online at http://pubs.usgs.gov/ds/2005/140/