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With that respect, low inclined orbits may lead to improvement of the satellite imaging accessibility to the target area per day or reduction of satellite revisit time compared to SSO.
Imagery data will consist of approximately 20 km swath at high resolution in panchromatic mode.
Data will be stored onboard the satellite and when available, the satellite will download the payload data using an X-band communication link to a particular ground station.
Command and control as well as telemetry data will be transmitted using S-band communication link.
Sun elevation angle is constrained to be between 30 - 70 degrees in order to obtain useful imagery data [8].

Introduction： Nonnegative matrix factorization (NMF) is a now popular dimension reduction technique, employed for non-subtractive, part-based representation of nonnegative data [1, 2].
The NMF decomposes the data matrix Y = [y(1),y(2),...
One set is synthetic Sendmail data which collected at the University of New Mexico (UNM) by Forrest et al, it contains UNM synthethic sendmail data and CERT synthethic sendmail data.
UNM data is training set, CERT date is testing set.
Other set is UNM live named data.

Increment of the spindle speed, reduction of the cut depth and decrease of the feed speed make the surface roughness value reduce.
The grinding forces were measured using the data acquisition system consisted of Kistler piezoelectric dynamometer, charge amplifiers, computer and A/D card.

INTRODUCTION Experiment project is an applied methodology in several areas, aiming at the improvement of the productivity and the reduction of the variability, seeking to generate information to guide the decisions during the research and the development of new materials [1,2].
Taguchi’s method is defined by two important parameters: (a) reduction in the variability, on the other hand, the use of the Quality Engineering in the product or process representing continuous improvement and aiming at smaller loss for the society; (b) application of strategic planning in an appropriate way, with the aim of reducing variation, in a general way.
The data were analyzed using the STATISTICA program, version 6.0 for Windows.

The function of collaboration medical monitoring platform includes receiving data from intelligent perception unit, TCP/IP protocol conversion, service scheduling, alarming when any data is over standard, managing and monitoring the whole system.
Function of service scheduling engine includes receiving data from intelligent perception unit, filtering of digital signal, creating service threads, normalizing data according to HL-7 format, scheduling monitor services.
Function of monitoring service engine includes capturing exception, setting operation parameters, monitoring system status, alarming when over-standard data occurs.
Online monitoring service: Two kinds of exception will be treated by online monitoring service, which are alarming for over-standard data and hint for operational failure.
Universal Description Discovery and Integration analysis configuration information of WSDL and computes measurement data and normalizes data.

Therefore, a reduction in both defects and cooling times would immensely benefit the injection molding manufacturing industry.
In addition to providing preliminary data for future numerical simulation research, validation was also done to confirm the accuracy and reliability of the simulation model relative to the experimental results.
Panitapu, High thermal conductivity mould insert materials for cooling time reduction in thermoplastic injection moulds, Mater.
Siregar, Increasing the company profit by reduction the production cost (Case study in an oil seal automotive manufacturing), Int.
Ahmad, Cycle time reduction in injection molding process by selection of robust cooling channel design, ISRN Mech.

Civil aircraft fuel tank flammability exposure level of typical data is shown in Fig. 1.
Combined with law of large Numbers, statistics on the N a random target value of the mean value, variance and other statistical parameter, thus get the approximate flammable exposure data.
The calculation model of the main consideration factors have the six parts: (1)Airplane Data; (2)Flight Data; (3)Fuel Tank Usage Data;(4)Body Tank Input Data; (5)Fuel Tank Thermal Data; (6)Multiflight Monte Carlo Data.
All the data is shown in Fig. 2.
Airplane Data 　 　 　 　 Maximum Range 　 1323 NM Number of Engines 　 2 　 Resultant Maximum Flight Time= 309 minutes OAT cutoff (AFM Limitation) OAT Limit= 160 Deg F 　 　 　 　 　 Flight data 　 　 　 　 Tank Ram Recovery 　 Cruise Mach Number 0.48 　 0.5 % of Ptotal 　 Cruise Altitude Steps 20000 　 ft 　 　 　 　 20000 　 ft 　 　 　 　 20000 　 ft 　 　 　 　 　 　 　 　 Fuel Tank Usage Data 　 　 　 　 　 　 Tank Full any time before 17 minutes before touchdown Tank empty any time after 0 minutes before touchdown Engines or equipment started at 30 minutes prior to takeoff　 Body Tank Input Data 　Set all values to zero if tank is not a body tank Tank in the fuselage with no cooling from outside air 0 1=Yes, 0=No Tank pressurized in flight 0 1=Yes, 0=No Pressure differential relative to ambient 0 psi Tank is pressurized 0 minutes before takeoff Temperature of compartment surrounding tank 0 Deg F Fuel Tank Thermal Data 　 　 The fuel is assumed to be loaded at ambient temperature 　 　 Tank Constants, Ground Conditions

Regarding the iron filing as PRB padding media, this experiment researched the repair effect of iron filing to the groundwater polluted by Cr+6 on condition that different initial concentration of Cr6+ and different flow velocity, and then with the help of the data regression analysis software SPSS, 1stOpt, Excel etc, it studied the regression analysis of Cr6+ removal rate with binary linear and binary nonlinear of the initial concentration and the flow velocity.
So far, some filling dielectrics in PRB system are being studied which include the adsorption reaction medium activated carbon, zeolite; and reduction reaction medium iron filing [5]; mixed reaction medium zero-valent iron filing and activated carbon mixed medium, zero-valent iron and compost mixed medium [6] etc.
Using the data regression analysis software SPSS, 1stOpt and Excel etc., the test data has studied the regression analysis of Cr6+ removal rate with binary linear and binary nonlinear of the initial concentration and the flow velocity and so on, finally define the best regression model.
We make the binary linear regression analysis with the data analysis software SPSS, and here are the results below: The optimal degree coefficient of this model is 0.908,the F-statistics of setting detection of this model is 42.494, and its significance degree P is 0, which suggests the linear relationship between Cr6+ removal rate and its initial concentration and flow velocity is significant after this model passed the setting detection.The model regression coefficient table shown in table 2 and the expression is: Y=（－0.001X1－0.021X2+1.114）×100% In this expression, Y stands for Cr6+ removal rate with its unit %; X1 stands for flow velocity with its unit ml/min; X2 stands for the initial concentration with its unit mg/L; Table 2 Regression coefficient table Model Non-standardized coefficients t Sig.
Because this test hasn’t determine the binary nonlinear regression model and initial value, we adopt the data analysis software 1stOpt to build the binary nonlinear regression model of Cr6+ removal rate with the change of initial concentration and its flow velocity, here are the results below： The analogy equation of binary nonlinear regression is below: z=(p1+p3*x+p5*Ln(y)+p7*x^2+p9*(Ln(y))^2+p11*x*Ln(y))/(1+p2*x+p4*Ln(y)+p6*x^2+p8*(Ln(y))^2+p10*x*Ln(y)) In this expression: z stands for Cr6+ removal rate with its unit %; y stands for the initial concentration with its unit mg/L； x stands for the flow velocity with its unit ml/min； p1, p2, p3, p4, p5, p6, p7, p8 and p9 stand for the parameters of analogy equation, and the concrete parameter values are below: Table 3 The simulation equation parameter table Parameter p1 P2 P3 P4 P5 P6 P7 P8 P9 Parameter values 0.8527 0.0138 -0.0030 -0.2419

The evaluation of actual mechanical properties of the in-service structures after some time of operation or determination of local properties for detailed FEM simulation yields the necessity to obtain relevant material data with high accuracy from small volume of the experimental material.
There can be also visible very small data scatter of SFT specimens confirming reliable testing set up and testing procedure.
Above about 3 000 000 cycles to break, almost identical results were obtained for both data sets.
However, the evaluated fatigue strength values were almost identical for both data sets.
Nevertheless, data scatter and trends of fatigue behaviour at early stages is better described by specimens machined by milling and thus rather this procedure can be recommended.

This method gives good prediction of both the deformation of the soil retaining structures and the settlement of the soils behind the wall after comparing with measured datas.
M-C model uses Young Modulus E for compression modulus and unloading modulus while elastic modulus is attained by the inversion of monitoring data based on a great number of similar projects.
Use a reduction coefficient Rinter to describe the relations among the strength parameter of contact surface, friction angle and cohesion for simulating the feature of the surface in lower parameter.