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The miscibility gap in the pseudo-binary ZnFe2O4/NiFe2O4 system was modeled using equilibrium solution data.
We investigate this pseudo-binary system for which thermodynamic activity data exists [11].
These observations were quantified using fits to the EXAFS data.
Magnetization data from two different samples sintered under identical conditions confirmed this anomaly.
This happens at relatively low temperatures, as is clearly supported by the miscibility gap data.

The primary structure is assumed to be linear on account of substantial reduction of seismic forces due to the installation of SDBs for which a bilinear hysteretic model is considered.
The primary structure is assumed to be linear on account of the reduction in seismic forces due to the SDBs.
Using the first set of data for and Eq.(11), we define the partial measure-of-fit as (14) The values of and are obtained by simultaneously solving , (15) Similarly, application of the second data set for and Eq.(12) produces another partial measure-of-fit as (16) extremization of Eq.(17) with respect to the unknowns yields , , (17) from which the values of , and are obtained.
Moreover, parameters identified from different set of data are somewhat different.
The acceleration responses contaminated with an artificial white noise signal of 5% noise-to-signal ratio are considered in the system identification analysis to simulate the measured data in a more realistic manner.

They might present a better alternative for detecting both distributed and localised damage, but the calculation of their curvature and/or any characteristics involving derivatives from measured data can incur significant inaccuracies.
The smallest damage considered is 10% stiffness reductions and this increases to 50% reduction.
The idea of PCA is to transform the original multidimensional data to new vector variables c with a smaller dimension k, pk << .
PCA may have very advantageous properties especially when applied to categorical data since it decreases the inter-class variance in the same time increasing the between-class variance.
In the case of a large number of training data the 1-NN rule gives a rather low error probability, which is less than the error probability of the q-NN rule and is close to the Bayesian one.

To collect the data corresponding to the objective of research, a disc on disc testing instrument construction was designed.
In the experiment without graphite treatment, the following data is obtained.
The experiment conducted with graphite polishing in 5-minute time interval in 8 cycles provides the data shown in Table 3.
Graphite use and wheel weight reduction in testing with 5-minute polishing time interval Material Size [mm] Reduction [mm] Prior length of graphite 11.8 1.05 Final length of graphite 10.75 Material Size [gram] Reduction [gram] Prior weight of wheel specimen 140.2 0.03 Final weight of wheel specimen 140.17 Data shown in Fig. 4.a, when communicated with Table 3, suggests that the graphite length decreases by 1.05 mm after the wheel surface polishing.
The data obtained is presented in Table 4.

In addition, HPDC is poised for expansion well into the future as a result of the conversion from ferrous castings to light alloy versions through the mass-reduction programs implemented by the automotive industry.
More emissions of CO2 and other GHGs are experienced in aluminium production during the electrolytic reduction of alumina into aluminium (Hall-Heroult process) and, in magnesium production, either in the silicothermal reduction of dolomite (Pidgeon process) considered in this work or the alternative leaching of magnesite (electrolytic process).
Since it was not possible to locate an Australian foundry that produced a similar automotive component using magnesium, typical data for a magnesium plant in the United States (US) were used.
The data used in the present study were derived from previous investigations for both aluminium [3-5] and magnesium [6-8].
Accordingly, it can be seen from Table 6 that yield increase had an overwhelming effect on GHG emissions, whilst QA reject rate reduction was a distant second and cycle time reduction having the least influence.

Yet few of these data are measured or estimated, collected, and published by China.
CO2 is the CO2 emissions (tons); Intensityj is the carbon content of fuel j (by mass). 3 Data collection and analysis For our analysis, we use data from Beijing Transport Annual Report 2003-2013.
Table 1 Fuel economy data for car, taxi and bus[5].
We obtained mode split data of Beijing where travel surveys were taken over the past seven years.
It should be noticed that we haven’t obtained the data of station to station.

With analyzing of test data and searching the cause of abnormal noise and vibration, improvement measures were put forward and confirmed by bench test. 2 Noise and vibration test of rear axle Noise and vibration test of rear axle was conducted on automobile electrically controlled power-transmission system test-bed manufactured by Burkee of USA.
In this condition the meshing frequency of final reduction gear was 563.49 HZ and second harmonic was 1126.98 HZ, which was coincident with twice frequency of gear meshing.
In fact, the surface roughness of this drive gear and driven gear was twice lower than normal gear when checked, which should be strictly controlled when manufactured. 3 Improvement measures and test verification With analysis of the bench test data of rear axle, three improvement measures were put forward as follows: (1) Reduce the surface hardness of driven gear of main reducer from 60±2 HRC to 58±2HRC
With making sure the test conditions were coincident with previous test conditions, verification test of improved rear axle was done, and the test data was compared with previous data.
As the test conditions coincident with previous test conditions, verification test of improved rear axle was done, and the test data indicates that noise and vibration of rear axle was extremely weakened.

Smart Grid framework to achieve clean energy friendly access, to achieve energy conservation and reduction of environmental pollution, is to build the smart grid hallmark.
This paper studied the distribution network load power constant, take the time section data flow calculation, combined IEEE13 node test system, using forward and backward substitution method flow calculation.
Table3.4 The data of photovoltaic power supply capacity and the system total access network loss Number Injection capacity （kVA） Power loss （kW） Number njection capacity （kVA） Power loss （kW） 1 0 205 6 390+ j 170 145 2 45+j20 190 7 510+ j 230 135 3 90+ j 40 185 8 670+ j 300 125 4 150+ j 60 175 9 1400+ j 670 135 5 210+ j 80 165 10 1500+ j 730 145 Flow calculation results shown in Figure 3.3.
A New Algorithm for the Reconfiguration of Distribution Feeders for Loss Reduction.
Distribution Feeder Reconfiguration for Loss Reduction.

The powder produced by the continuous sodium reduction of titanium tetrachloride has a coral-like morphology and low tap density.
Based on data collected from previous milling trials, a model was constructed to predict the expected increase in oxygen, nitrogen and hydrogen as milling time increases.
Another technique, wet-attritor milling, was evaluated in order to minimize the oxygen pickup associated with overall particle size reduction.
Starting particle size distribution data is presented in the table below: Table 2.
The material saw a 44-49% thickness reduction to approximately 0.70-0.90mm.

The combination of Hall effect data with optical and structural results ensured a holistic understanding of how annealing governs defect states, carrier dynamics, and the overall figure of merit.
The data include films in their as-deposited state and those subjected to air annealing at 300 °C and 500 °C.
To obtain a more comprehensive understanding of the annealing effects, the XRD data were further analyzed through Rietveld refinement using the Maud software to extract precise microstructural parameters [26].
In this study, second-derivative plots of the transmission data were produced as a function of photon energy, as depicted in Fig. 8.
Analysis of the data reveals a distinct trend: the FOM increases as the annealing temperature rises from 300 to 500 °C.