Search results

School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China; 2 Jiaozuo Teachers College, Jiaozuo 454003, China aemail: xiaoxiaotuan@163.com Keywords: emergency shelter; urban disaster reduction; green space system; Jiaozuo Abstract: Urban green space system has a strong function of disaster prevention and reduction.
In addition, the three types of shelters are functional uniform that is urban green space shelter for emergency shelter also can be used for temporary and long-term shelters if possible. 2.3 Landscape pattern index and disaster reduction function of greenbelt of urban The landscape pattern is a set of landscape elements, which are arranged from a series of different sizes and different shapes landscape elements [6, 7].
The performance of landscape patterns determine the various ecological processes, as well as determine effective green space for disaster reduction and shelter (Table 1).
Table 1 List of green patterns analysis indicators Structure index of green space Formulas Sign of the effect on disaster shelter Sign of the effect on ecology function Diversity index /H + + Evenness index /E + + Fragmentation index/ C - - Dominance index/ D - - Fractal dimension index/ FD - - Note: Pi is the proportion of i type green landscape in the total; k is the total types of green landscape; Ni is number of patches in type i ; N is total green patches; L is average perimeter of green patches; A is average area of green patches. 2.4 Data Collection and analysis The statistical program SPSS for Windows version 15.0, GIS (Geographic Information System) and erdas 8.4 program were used to perform the data analysis.
All the data are come from statistical yearbook of Jiaozuo (1999-2008), Spot images and field survey in years of 2004-2008.

Taking advantage of the strong ability of RS theory in processing large data and eliminating redundant information, this method can remove irrelevant factors from the original fault data and reduce the dimension of processing data which helps to overcome fuzzy clustering algorithm's defect when process large database.
RS provides a series of tools for data analysis and reasoning from imprecise and ambiguous data[5].
Definition 2): Reduction and Core: In decision system ( , , , ) S U A V f= ,let b B∈ and B A⊆ , if { } ( ) ( ) B B b pos D pos D−= , attribute b is redundant to B, which relatives to D ,otherwise the attribute b is indispensable .If {} ( ) ( ) B B b pos D pos D−≠ , then B is called a reduction for information system S , are denoted as ( )RED A ; the intersection of these reduction sets is called core ,denoted as ( ) CORE RED A= ∩ Fuzzy Clustering Analysis Algorithm Cluster analysis is a multivariate statistical procedure that begins with a data set containing information about a sample of entities and attempts to reorganize these entities into relatively homogeneous groups[6].Clustering analysis is helpful when a researcher tries to classify or group data into categories or groups when neither the number of groups nor the members of the groups are known.
Clustering has been proven as a useful technique in exploratory data analysis when the sample is known to be non-homogeneous.
A CASE STUDY In this section, take the data of oil-immersed power Transformers fault diagnosis in reference as an example for illustrating our methodology.

If we want to use these data in geographic information system, the above-mentioned data must be converted into data of GRID format.
The header file of satellite remote sensing data is first loaded to get projection type, data resolution, data width, data length, maximum latitude and longitude, minimum latitude and longitude and other data information of satellite data when data is converted.
Then resolution, data width, length and other data information of grid file is set by IRawPixels method.
Ground observation data have Shapefile, Coverage, INFO Table, dBase Tables and other data format.
Superposition of monitoring data and geographical background data.

Nanocontacts between fibrils and charge currents scattering features in strongly disordered polymers lead to essential change of character of low-temperature electric conductivity that allow from the data on electric conductivity to take the information on parameters of materials on the basis of conductive polymers.
The MIL matrix structure consists of two types of cages of 2.9 and 3.4 nanometer size, connected through a smaller windows (ca. 1.4 nm).[6] Our data confirms that the polyaniline is confined within MIL structure so the size of the conducting phase is limited to an order of several nanometers.
The powder X-ray diffraction data of MIL-101 (green), polyaniline (blue), aniline-impregnated MIL (pink), polyaniline@MIL composite (black).
The gas adsorption data and the pore size distribution analysis also confirm that the polyaniline in the composite sample is entrapped inside the MIL pores as we found the noticeable reduction of the pores sizes after the aniline polymerization, compared to the starting MIL-101 compound.
As can be seen from the data, the dependence of resistivity from current for all materials was observed.

The convergence of experimental data and calculations is shown.
Analysis of the `equation system (1) shows that for its solution apart from reference data some individual values are necessary from experiments carried out expressly.
In particular data for the mass of welding bath are presented at Fig. 1 and described by relationship (2): ▲ – UONI 13/45; ● – UONI 13/55; ■ – MR-3 Fig. 1.
Comparison of calculated and experimental data shows their concordance.
The disagreement between calculations and experimental data averages 15%, which is comparable with the experiment error and is generally accepted for such models [1].

There are various applications of cost reduction through quality improvement in electronics as shown by failure analysis of ultrasonic pitting and carbon voids on magnetic recording disks [1] aimed to reduce carbon voids and ultrasonic power for improve disks quality, defect reduction of patterned media templates and disks [2] with respect to inspection methodology of hard disk pattern using jet and flash imprint lithography and characteristic and reduction of a new particle defect mode in sub-0.25 µm semiconductor process flow [3].
From the data collection during July 2011 to June 2012, almost 380,000 drives from this process have been found to be defective.
Process capability of the defective rate With the data collection during July 2011 to June 2012, the average defective rate with respect to the spiral scratch is 6.03% as shown in Fig. 4.
Sreenivasan: Defect Reduction of Patterned Media Templates and Disks, The International Society for Optics and Photonics, Japan, Vol. 7748 (2010)
Simmons: Characterization and Reduction of a New Particle Defect Mode in Sub-0.25 um Semiconductor Process Flows, Nuclear Instruments and Methods in Physics Research, USA, Vol. 237 (July 2005), p. 330-335

SEM images of nickel particles obtained by the reduction of nickel formate in benzyl alcohol (а) and doped with Ag (0.1%) (b) as well as the reduction of nickel caprylate (c) and stearate (d).
From the resulting data it was found that that doping with silver has a substantial effect on thermal decomposition of nickel formate under isothermal conditions starting from the concentration of 0.03 mol. %.
Reduction is over after about an hour of boiling.
Two salts, copper caprylate and formate, were subjected to reduction.
A part of copper particles formed in the further reduction of the oxide conserves the same shape and size.

Data collection.
Attribute data measurement from the inspection of porous defects shows the measurement data at position 1.
Fig. 5 The result of the attribute data measurement system analysis Variable data measurement system data was collected by the ANOVA method as shown in Fig. 6.
Fig. 6 The result of the variable data measurement system analysis Analyze Phase.
The data set is normally distributed, Versus Fits graph shows the data set has stability of variance, Versus Order is distributed in a certain pattern, and the residuals have similar values.

Introduction Coupling refers to a series of complex processes produced by the information parameters controlled each other and the data information transmitted each other between two information modules and data modules.
Common coupling requires multiple modules to use a common data set.
Control coupling controls other modules through transmitting data information [9,10].
Stamp coupling transmits data information through the module parameters.
Data coupling that is similar to stamp coupling transmits data information through the module parameters too.

., cjuntakantawîkun@yahoo.com Keywords: Vertical Green, Heat Gain Reduction, and Building Energy Code Abstract.
The data-logger connected to the thermo couple type k for measuring the temperature and humidity of ambient, the inside and outside wall, and the temperature of the front and back of the vertical green is set as in Fig. 1.
The air conditioners in both room and data logger is operated for 3 days to record the data.
From the recorded data, the equivalent plant conductivity under the assumption of steady state one dimension heat transfer can be calculated as Eq. 1, 2, and 3 respectively under the assumption of one dimension steady state heat transfer.
Efficiency of Climbing Plant in the Reduction of Heat Gain through Building Envelope.