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Temperature of concretion nucleation and binary eutectic reaction was increased after a reduction, whereas the time was presented dynamically, both the minimum value which were obtained at 715 ℃are 23.48s and 89.24s respectively.
Cooling curves was tested by K-type thermocouple, which was located in the center position of castings, test data was recorded by XSR 70 color paperless logger, the input signal is 4～20 mA and the recording frequency is 0.1s, as shown in the Figure 2.
Through the test results, it was found that in the filling temperature range from 750℃ to 715℃, cooling rates were rose constantly with the reduction of pouring temperature, the peak point which was emerged at 715℃ is 5.93℃/min, along with a decline to 4.23 ℃/min at 705℃ subsequently, the changing trend of cooling rates with the pouring temperature from 705℃ to 675℃ is mimetic as the circumstances discussed above, the maximum value is 5.24℃/min, which was attained at the pouring temperature of 675℃, as shown in the Figure 8.
Through the analysis of mathematical formula, it was found that with the reduction of pouring temperature and binary eutectic reaction temperature, followed with a ascension of cooling rate and solidification nucleation temperature, the grain size was decreased successively.

In order to take full advantage of high precision information of star sensor, many scholars use inertial equipment to provide horizontal datum to realize autonomous positioning of star sensor.
Because of limitations of inertial equipment components and platform control method, it is difficult to realize platform datum completely horizontal by dynamic control, which leads to a precision reduction in horizontal datum.
Furthermore, the precision reduction in horizontal datum will lead to a precision reduction in navigation system.
Horizontal datum limit has become a bottleneck of star sensor navigation.

Obtained neutron data showed that all studied samples contain coexisting Mg and MgH2 phases.
Using the Rietveld method obtained data were refined and the phase composition of the samples was determined.
Obtained neutron data and phase composition of the samples are shown in Figs.1, 2 and in Table 1.
Analyses of neutron diffraction data of the first and second samples show that the ratio of the Mg and MgH2 phases is similar to percentage, obtained by the X-ray data (60% of Mg and 40% of MgH2).
Neutron diffraction data of the partly desorbed samples of MgH2.

In the context of Industry 4.0, the interest towards the additive manufacturing processes is growing due to their numerous advantages, such as the possibility to prototype, the reduction of waste material, the inferior time to market, ad so on.
Introduction Industry 4.0 is based on nine core pillars that affect the manufacturing growth [1]: big data, autonomous navigation [2,3], simulation [4–6], additive manufacturing [7], internet of things [8], cloud computing, augmented reality, horizontal and vertical integration and cyber security [9].
It is particularly interesting for industrial applications because of the reduction in material waste, the fact that material is only used where it is desired.
In conclusion, only one single wall has respected the design data and reached the desired height in combination with an acceptable shape; it is shown in Fig. 6 and it has been obtained with a layer thickness equal to 0.6.
Specifically, for the H13, it has been assessed a reduction of 100 W for each layer starting from the 4th layer in the single walls.

Base on the missing of some specific structure modal shapes and reduction of the frame horizontal stiffness, it can be revealed that the interior slab-column connection cannot transfer the unbalance moment well.
This system is highly advantageous because of the formwork costs reduction, fast execution and easy installation.
This paper reports the modal experimental data and analysis of FEM (ANSYS 10.0).
(3) Base on the dynamic test data, the temperature changes (8.5℃) during the experiment show little effect to the changes of frequency of flat plate frame in horizontal/vertical direction
(4) With the horizontal direction dynamic test data and FE model analysis, it is found that the lateral stiffness of experimental interior column replaced by the mechanical jack reduce to 10%.

The convergence graphs have been plotted in Minitab software to justify the reduction in iterations.
They have used ANOVA method for the analysis of the data and conclusion of results.
The next step is to calculate the data from the experiments by analysis and then measuring the different responses.
These mathematical relations are formed by using factorial fit analysis of the data from experimental work.
The output (response) data for MRR and Surface Roughness is shown in Table 3.

After data collection was done, it was analyzed by using descriptive statistics.
Two versions of self-administered questionnaires were used in data collection.
Data collection Data was collected from two parts both before and after formulation in capital district of Nakhon Pathom province.
Data was collected by self-administered questionnaire and analyzed using descriptive statistics.
SurveyResults General data of participants During 1st-15th November 2019, the data were collected from five distinct groups of total 30 participants which were tourists, dental patients, pharmacy students at Silpakorn University, office workers and dentists.

As energy is limited in wireless sensor networks, how to effectively manage and use energy of WSNs, and how to maximize the reduction of power consumption in WSNs and extend the lifetime of WSNs become a key problem faced by wireless sensor networks.
Clustering routing typically consists of three phases: cluster head election, select members, stable data transmission[5].
Select members and stable data transmission.
When the clustering process is completed, network enters the stable data transmission.
Assume p is the optimal ratio of cluster head, we improved algorithms for clustering p(i,r)=p*η (i, r), the cluster head selection in low-power algorithms is described as follows: (10) Simulation and analysis We present a simulation scenario: Eo =0.5J, =10pJ/bit/m2, = 0.0013pJ/bit/m4,node number n=100, data fusion energy cost Eda=5nJ/bit/message, data transmission 4000bytes/round.

He Keqiang, etc.,(2005) found rainfall was the most important dynamic factor among the six factors controlling displacements, using the monitoring data of displacements of Xintan landslide, China [5].
Sun X R, Ma F H, etc., (2012) proposed the main influence factors on dam deformation, based on Factor Analysis Method and monitoring data [9].
Bi J L, Liu X, etc., (2010) identified the main factors affecting seepage around the dam based on Factor Analysis Method to analyze monitoring data [11].
This paper studied the data until April 2012, which are shown in Fig. 2.
Fig.1 Geological profile Liangshuijing landslide Fig.2 Monitoring data of rainfall, reservoir water level and displacement of landslide Factor Analysis on The Professional Monitoring Data of Landslide Based on the monitoring data and the previous research results, the data were mainly selected from May 2009 to April 2012, considering seven influence factors: accumulative displacement of monitoring point ZJC09(x1), cumulative displacement of monitoring point ZJC11(x2), accumulative displacement of monitoring point ZJC13(x3), rainfall of the current month(x4), cumulative rainfall of anterior two months(x5), monthly change in elevation of reservoir water level(x6), monthly average reservoir water level (x7)(table 1).

In accordance with the relevant standards, 45MnMoB Chemical composition and mechanical properties of steels meet the following requirements ( See tables 1 and 2) : Tab.1   45MnMoB Steel composition requirements ( % ）in YB/T5052-93 C Mn Si S P Mo B Cu 0.41-0.49 0.90-1.20 0.17-0.37 ≤ 0.04 ≤ 0.04 0.20-0.30 0.001-0.005 ≤ 0.030 Tab. 2  45MnMoB Steel mechanical property requirements in YB235-76 Steel grades Mechanical properties Yield strength R0.2 [Mpa] Tensile strength Rm [Mpa] Elongation A [％] Reduction of cross sectional area Z [％] Notched bar impact strength Akv [J/cm2] Hardness [HRC] 45MnMoB ≥ 650 ≥ 800 ≥ 12 ≥ 40 ≥ 40 24-32 Check test 42CrMo Chemical composition of steel and related data tables 3And table 4 。  
Tab. 3 Component on 42CrMo in the standard GB/T 3077-1999 (%) C Cr Mo Mn Si S P Cu 0.38-0.45 0.90-1.20 0.15-0.25 0.50-0.80 0.17-0.37 ≤ 0.035 ≤ 0.035 ≤ 0.030   Table4 Mechanical property on 42CrMo in the standard GB/T 3077-1999 Steel grades Mechanical properties Yield strength R0.2 [Mpa] Tensile strength, Rm [Mpa] Elongation A [％] Reduction of cross sectional area ψ [％] Notched bar impact strength Akv [J/cm2] Hardness [HRC] 42CrMo ≥ 930 ≥ 1080 ≥ 12 ≥ 45 ≥ 63 28-32   Performance analysis of heat treatment of materials.
Tab. 6 Mechanical property of three kind samples Number Tensile strength MPa Yield strength MPa Elongation% 30CrMnSiA 1# 904 823 6 30CrMnSiA 2# 932 854 4 42CrMo 1# 980 887 12 42CrMo 2# 1060 885 11.5 45MnMoB 1# 998 901 14 45MnMoB 2# 966 891 15   Performance data for three materials make graphics such as figure2 .
Comparison of three kinds of material property data.
Test data description, 45MnMoB have High steel-plastic reserve. 1 30CrMnSiA After the steel will increase in intensity levels, elongation data problems.