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The 2Ɵ angle is similar to the characterization pattern of standard TiO2 anatase crystal XRD analysis from ICDD (International Center of Diffraction Data) data with No. 01-070-7348 ie with an angle of 2Ɵ: 25.315o ; 37.851o ; 48.050o ; 55.080o ; 62.737o ; 68,849o ; 70.311o and 75.115o.
The graphite carbon on graphene nanoplatelets-TiO2 composite crystal calcined at a temperature of 400, 500, 600o C for 3 hours at an angle of 2Ɵ: 26.5231° ; corresponds to the characterization pattern of the standard graphite XRD analysis from ICDD (International Center of Diffraction Data) no. 01-089-8487 with 2θ=26.555 from hkl (002).
XRD Characterization Results of Graphene Nanoplatelets-TiO2 Nanocomposites XRD characterization data can also be used to calculate the crystal size of the graphene nanoplatelet-TiO2 composite material, using the Scherrer equation [25].
Obalová, Effect of calcination temperature and calcination time on the kaolinite/TiO2 composite for photocatalytic reduction of CO2.
Kaner, A One-Step, Solvothermal Reduction Method for Producing Reduced Graphene Oxide Dispersions in Organic Solvents: ACS Nano (2010), 4, 3845

The sections of the Spanish standard that concern timber and roof (UNE 41805-8 IN and UNE 41805-9 IN) end with a long descriptive table defining the pathologies, their symptoms, the possible localization, the cause and how to collect the data.
Even if the descriptions are good and reliable, the illustrated process of data gathering only concerns qualitative kind of data, like visual localization, extension and intensity of damage.
The measurement of wood moisture content was done near each one of the bearing walls because they are the most important source of moisture absorbed directly by wood. 20% is usually considered as the threshold because only up to this condition rot can develop and cause the reduction of joists sections.
However, as sapwood in pine is a considerable percentage of the section, this surface attack has to be regarded with the greatest attention in structural analysis, because it caused a section reduction higher than 1 cm.
More specifically, an intervention directed to the reduction of moisture due to capillary action in the walls of the ground floor will be necessary and the waterproofness of balconies and southern terrace needs to be checked and re-established.

One is the kinematic variation caused by the machining imperfection in fixtures and datum surfaces.
From the measure scheme and history data, we get the covariance matrices of sensor noise v=0.01×I3×3, natural variation of the locators η=0.005×I18×18 and process noise w=0.
From the above calculation, we can get the specification of these data, as shown in Table 1.
Specification of the quality data Item USL Target LSL μP σP Value 5.1 5 4.9 5 0.0479 So we can use Equation (6) to calculate the CP *is: Cp*=USL-LSL6σp=USL-LSL6ΨwΨT+v t2+Γ[η+i-1a]ΓT2=0.696 Step 3.CPI improvement by process parameters sensitivity analysis: According to the sensitivity analysis Eqs (7) and (8), the sensitivity indices of the total 18 process parameters are shown in Table 2.
Dimensional errors of fixtures, locating and measurement datum features in the stream of variation modeling in machining.

So as to achieve the effect of energy conservation and emissions reduction, let our bathroom more human
(5) Wash bath temperature real-time control and audio playback circuit module Using high-performance DHT11 real-time data acquisition of temperature sensor for the bathroom to single-chip computer for data processing to the data, when the remote control to the master control system a signal when the relay driver module will drive heating chy-tech opens, is in a state of heating at the same time open audio playback function.
And the initial value to main control system sets the stage, through the single-chip microcomputer data processing after the control of the relay driver module, changing the heating chy-tech group number to achieve heating energy saving effect
Main controller subroutines including A/D conversion subroutine, keyboard processing and display subroutine, heating control subroutine (using the output compare function), infrared reception subroutine (using the input capture function), Zigbee wireless temperature and humidity control, acquisition subroutine, LCD module hammer calendar program, data save subroutine, delay subroutine, etc.

To solve the linearization problem of QTTS, the traditional method of using the calibration data is to perform a third- or fourth-order polynomial curve-fit by means of a least-squares regression technique, or use of a multidimensional look-up table[7].
The calibrating data is obtained by a calibration unit that is necessary for the training and the testing of the ANN.
(a) Geometry and vibration mode of tuning fork (b) Crystallography of a ZYtw-cut tuning fork Fig. 1 Quartz tuning fork temperature sensor block diagram Fig. 2 Measurement Instrument black diagram In the operation phase, the output signal of QTTS is generated and optimized by OC which its output is connected to HP5334A and transferred to PC via IEEE-488 where data reduction and optimization is implemented.
The PC-based instrument is controlled by the software written in both operation and calibration phases, which is used to acquire the data from ANN training phase and to show the calculated temperature in operation phase.
Therefore, the other data set of 50 QTTS temperatures that is uniformly distributed between -200 and 200 C is used in the test process.

However, the need exists since, for example, investigations on noise reduction in gear units is an essential field of research in the automotive industry.
Unfortunately, it almost always leaves out of consideration that the utilisability of FFT algorithms is bound to strict preconditions and that the spectra which are determined by applying the FFT to measurement data are, by no means, always identical to the really existing spectra.
The application of the FFT algorithm to the measured gear data yields the spectrum shown in Figure 4.
The spectrum determined is the correct FFT spectrum which must be attributed to the corresponding data.
The method applied to the data is, under the given conditions, not suitable for determining the actual spectrum. 0,000 0,002 0,004 0,006 0,008 0,010 0,012 0 10 20 30 40 50 wavelength in mm amplitude in mm 0,000 0,002 0,004 0,006 0,008 0,010 0,012 0 10 20 30 40 50 wavelength in mm amplitude in mm Figure 4 Spectral assessment by means of a) FFT algorithm b) Bayes' statistics In the case of these measurement data, the conditions stated for the application of the FFT for the waviness analysis were not fulfilled so that another assessment method had to be used.

The results were compared with the experimental data [1-3].
This process is considered by the model through the reduction of carbon deposit intensity beside the actual carbon flux
The factors are selected to obtain the best fit with the experimental data (see below).
The cluster surface concentration temperature dependence obtained from the computer simulation was compared with the experimental data.
The result obtained within this model appeared to be in good agreement with the experimental data.

The establishment of the finite element model Take type of XB1-120-100 harmonic gear drive for example, the reduction ratio i=100, the modulus m=0.6mm and the pressure angle α=20°.
Recording the value of input torque Tin corresponding to the value of output torque Tout, whereby the efficiency curve shown in Fig.2, the experimental data in Table 1. 2) In the case of maintaining the output torque (Tout=100N·m), the input rotational speed nin is increased until the value up to the rated speed.
Recording the value of the input torque Tin corresponding to the value of input rotational speed , whereby the efficiency curve shown in Fig.3, the experimental data in Table 2.
Table 1 The experimental data of harmonic gear drive efficiency when the input rotational speed (nin =3000rpm) unchanged nin(rpm) nout(rpm) Tin(N·m) Tout(N·m) Pin (kW) Pout(kW) μ(%) 3000 30 0.4 8.21 0.125 0.025 20.4 3000 30 1.26 90.76 0.398 0.285 71.5 3000 30 1.57 118.11 0.49 0.37 74.8 3000 30 2.21 177.69 0.697 0.558 80.0 3000 30 2.97 246.63 0.933 0.774 83.0 3000 30 3.58 305.67 1.125 0.960 85.3 3000 30 4.22 364.15 1.326 1.143 86.2 3000 30 4.75 414.08 1.490 1.300 87.0 3000 30 5.14 448.27 1.610 1.615 87.1 Fig.2 The curve of the relationship between output torque and efficiency when the input rotational speed is nin =3000rpm The data obtained from the Table 1 shows that, when the input rotational speed unchanged, with the output torque increase the efficiency of the harmonic gear drive increased.
Table 2 The experimental data of harmonic gear drive efficiency when the output torque (Tout=100N·m) unchanged nin(rpm) nout(rpm) Tin(N·m) Tout(N·m) Pin (kW) Pout(kW) μ(%) 68.4 0.68 1.51 100 0.476 0.314 65.8 968.4 9.68 1.36 100 0.429 0.314 73.0 1256.4 12.5 1.36 100 0.429 0.314 73.1 1552.8 15.5 1.39 100 0.437 0.314 71.7 1741.2 17.4 1.36 100 0.430 0.314 73.0 2071.2 20.7 1.40 100 0.440 0.314 71.3 2370 23.7 1.38 100 0.433 0.314 72.4 2679.6 26.7 1.38 100 0.433 0.314 72.4 2955.6 29.5 1.36 100 0.429 0.314 73.1 Fig.3 The curve of the relationship between input rotational speed and efficiency when the output torque is Tout=100N·m The date from the Table 2 shows that when the output torque unchanged, with the input and output rotational speed increasing, the input and output power increased, therefore the transmission efficiency of harmonic gear drive almost no change.

In this paper, experimental research has been made about parabolic trough solar water heater,which provided basic data for design and installation of water heaters and had a major push and reference to the development of solar collector.
The time interval between the adjacent test is set to 30min.Instantaneous efficiency of different moments in every day can be calculated by the test data and Formula (1).Figure2 shows the change in temperature of water in tank during the day .
As can be seen from Figure3, Figure4and Figure5,the instantaneous efficiency was changing with time,but on the whole,the instantaneous efficiency increased first and then decreased,the instantaneous efficiency reached the maximum at about 12:00.Meanwhile,during the time of 9:00am to 3:00 pm,the instantaneous efficiency was relatively stable.The unsteady equation of the solar hot water heaters can be concluded with the method of least squares by data obtained in several tests [5]
The heat loss coefficient was calculated by Formula (5), the measurement data is shown in table 3
（5） Where:—Capacity of water tank ,kg;—Heat capacity of water,; —initial temperature at night, ˚C; —end temperature at night, ˚C; A — volume of water tank,L; —average temperature in the water tank at night, ˚C; —average temperature of the around environment at night, ˚C;—test interval, s Tab.3 The heat loss coefficient measurement data table Date Initial temperature of the water (˚C) Final temperature of the water (˚C) Average temperature of the water (˚C) Ambient temperature (˚C) (W/(m2•˚C)) 2013.4.7 52.9 48.8 50.85 8.1 1.017674 2013.4.18 35.8 33.1 34.45 7.6 1.067039 Conclusions (1)The overall trend of the instantaneous average efficiency changes of the parabolic trough solar water heater is firstly and then decreased.

With the rapid increase of image data, how to retrieve has become more and more important.
Lots of image data are stored and transmitted in compressed format, but the study of image retrieval technologies are mostly not based on the data of image compression at present.
When we retrieve the compressed image data, we need the “full decompression operation”.
They. transformed DCT domain coefficients for the Mandala domain data.
Because when the ratio increases to a certain degree, the coefficient in retrieval behind process will lose the function, which is equivalent to the reduction of DCT coefficients in the number when retrieving, to some extent, will weaken the descriptions of the image information.