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The magnetic α-Fe nanoparticles were carried out using two-preparation methods that include solution phase metal salt reduction and organometallic precursor decomposition.
In this respect, the well-known reduction methods [6] display limitations due to their lack of variability.
Reduction of transition metal salts is the oldest, easiest and still a widely used method for the preparation of metal nanoparticles.
The crystal size determined by Debye-Scherre equation with XRD data are 15 nm and 45 nm, which are close to the particle sizes calculated from TEM images (12.5 nm and 40 nm for Fig.2.

The program tracking mode needs no highly precision tracking system but depends on a two-line element set (TLE) data format specified by North American Aerospace Defense Command (NORAD) that can be used by the SGP4 models to forecast and produce the antenna pointing coordinates, which is more economical and efficacious.
By tracking the TLE data of FORMOSAT-2 satellite, the experimental results have proven the better performance and feasibility of the proposed PSO-PI satellite antenna controller.
In Fig. 3, is the error between ephemeris TLE data and plant angular, PSO is adopted for variable selection and optimization for the parameters kp and ki of PI controller [7].
Pointing coordinate of three axes testing results Pointing coordinate Axis Maximum Positive Error Maximum Negative Error Position Control Elevation 0.481º -0.272º Azimuth 0º -1.398º Vertical TLE Data (75.556º), Mechanism (75.828º) Speed Control Elevation 0.159º -0.258º Azimuth 0.454º -0.249º Vertical TLE Data (102.48º), Mechanism (102.371º) PSO-PI Control Elevation 0.052º -0.052º Azimuth 0.22º -0.252º Vertical TLE Data (102.48º), Mechanism (102.448º) 4(a).
Although this research mainly depends on TLE data for tracking satellite, but it provides a simple and economical method to capture targets with high accuracy.

Strength is improved through the Hall-Petch effect [2] whist good ductility arises from a reduction in twinning as grain size is reduced [3].
To determine the annealing time to 50 % completion of restoration (t50) the modified Avrami equation is fitted to the data [9,10].
To determine the value of t50 the values of ∆σmax, n and t50 are changed until Eq. 1 fits the measured data.
It can be seen from the t50 data (Fig. 3) the binary alloys have the fastest restoration rate.
The greatest reduction in the restoration kinetics occurs when Gd is present and the Zn content is low.

In this paper, we propose a genetic algorithm (GA) based MCS for microarray data classification.
The design of GA-1 The design of Chromosome Filter feature selection methods are efficient techniques for the reduction of the dimension of microarray data.
The breast cancer data set contains missing values.
No further preprocessing is applied to the prostate data set.
(a).Breast cancer data set (b) Prostate cancer data set Fig. 2.

At 1100 °C (Fig.2), it was possible to observe a significant reduction in porosity in the samples with increased content of Ti-Al, mainly in relation to the macropores.
The density analysis proved the reduction of porosity and increased densification due to increased content of Ti-Al in the samples, a trend previously demonstrated in the microstructural analyses.
Fig.5 presents graphics with the data of density for samples sintered at 1100° C and 1400° C.
Fig. 5- Density datas of Ti-10V-2Fe-3Al samples sintered at 1100°C and 1400°C.
Microstructural and density analyses indicated the reduction of porosity and increased densification due to increased content of Ti-Al pre-alloyed powder in the samples.

Data from sensor array are often arranged in three-dimension as sample × time × sensor.
Traditional methods are mainly used for two-dimension data.
They are mainly used for two-way data.
The preprocessed response data were analyzed by PARAFAC with two components.
Taking into account the complexity of the data, the use of PARARAC as a feature extraction technique to perform a data reduction from a three-way array is studied.

At a power input of 6.0W, reductions in the evaporator wall temperature of about 32.3℃ and 24.4℃ were obtained for the micro-PHP at vertical and horizontal orientations, respectively.
Fabrication of a silicon-based micro pulsating heat pipe Experiments Fig. 3 illustrates the experimental system, which was composed of the test section, heating unit, data acquisition system, water cold bath, and a video recording system.
The output signals from the thermocouples were collected through a computerized data acquisition system.
As a result of these reductions, significant improvement in the silicon wafer’s reliability may be possible.
The maximum temperature reductions of the evaporator wall between the empty and FC-72 charged micro-PHP were presented.

Therefore, to deal with these massive data the feature extraction becomes extremely critical in order to keep the data interested and reduce its dimension.
When data system is high-dimensional and severely non-linear, the method becomes ineffective.
To evaluate the performance of dimension reduction, some researchers proposed residual variance according to Input/Output mapping quality, and that is the description effectiveness of the original data in higher dimensional space.
Nonlinear dimensionality reduction by locally linear embedding[J].
Locally Linear Embedding for dimensionality reduction in QSAR[J].

The results reveal an increment of number density, whereas the reduction in the size of precipitates with decrease in the aging temperature for the varying aging times.
The statistical data of continuous precipitates was determined using the Image J software with considering ~ 1000 precipitates, whereas ~ 100 precipitates from were chosen for the analysis of grain boundary precipitates and average value with standard deviation were reported.
Moreover, reduction in solid solubility of solute (Al) in the Mg matrix with decreasing temperature as basis to the phase diagram of Mg-Al alloy system [6], increases the driving force for the nucleation of precipitates.
Nevertheless, the increment in the size of continuous precipitates from 250°C to 330°C for the different aging times (Fig. 5 a) is compensated with the reduction in the number density for the same aging conditions (Fig. 4 a).
This culminates in the finer distribution of continuous precipitates within grain with reduction in inter-particle spacing (Fig. 3).

Data obtained from image analysis process were statistically analyzed.
Data obtained from image analysis process were statistically analyzed [5].
It allows to obtain a smooth distribution with reliable imputed data.
Results Raw Data Classification.
After this cleaning, the data set size was 4544 records.