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All these devices have at their disposal a wide range of possibilities to connect and exchange data.
For example, in embedded devices, the data that is stored and transferred can be ciphered by a secure cryptographic algorithm, but in some time, it could be broken by discovering the weaknesses or just by brute force attacks of new, more powerful computers.
For example, a point to point transfer protocol (MS-PPTP) used in TCP/IP networks has design errors discovered in time, and it uses the same key twice for transfers of the data in both directions: to a server and to a client.
What is more, it is often possible to reverse the results of that attack, using a backup copy of data.
FPGA-based Node receives a ciphered modulated signal from Proximity Sensor, maintains all the necessary processing of data and provides Control Center with information on sensed movements and likely errors which constitute possible breaches of the system.

The phases were identified through comparison with simulated diffractograms using the program Powdercell [14], inserting data of the a, w and b-Ti phases as well as space groups, lattice parameters and atomic positions [15].
This indicates a 33.5% reduction in the Young’s modulus of the alloy described in the present work.
The authors concluded, through the XRD, OM and TEM data, that the microstructure of the alloy is strongly dependent on their Nb content, once the volume fraction of α’ phase and athermal ω phase decreased for a higher Nb content.
Potentiodynamic polarization data show that both corrosion and passive current densities decrease when the Nb content increases.
Calvert: Pearson’s Handbook of Crystallographic Data for Intermetallic Phases.

The advantages of high speed machining components in their hardened states reported by the scientific literature [1, 2, 3] usually refers to: reduction of machining costs by diminishing process time and reduction of tool variety, improved surface integrity, burr free components, lower cutting forces, elimination of part distortion caused by heat treatment, elimination of the cutting lubricants, increased fatigue life of the workpiece, compressive residual stress and high removal rates.
Orthogonal arrays are an important tool of the Taguchi method that facilitate experiment data processing and reduce the numbers of the needed experiments.
In order to reduce testing and data processing time, Taguchi proposes plans of experiments in which the objective of the acquiring data are set in a controlled way.
The figure presents the mean effect plots obtained after processing the experimental data obtained with specialized software- Minitab.
The analysis of variance given for the regression Eq. 5 obtained from the experimental data is presented in Table 5.

It is important to highlight that the identification criteria correspond to the availability of energy data for the time period under study and willingness to allow the walkthrough audit.
At this stage, relevant operation data is obtained using appropriate measurement instruments such as thermometers, grid analysers, manometers, flowmeters and programmable logic controllers (PLC).
Once the production line has been divided into different points of study, the necessary energy data to calculate the energy consumption distribution by auxiliary processes has been extracted from the aforementioned sources.
Given that the total energy consumption is calculated from the sum of the elements of vector B , which can be determined from data provided in Table 1, as 645.94 Wh/cycle.
Thus, it will help to define goals and develop continuous energy-reduction programmes.

This article set the double-row pile as equal length, so that of the back pile is not a independent variable changing with the front; and considered 6 factors: the embed length of the front pile L1, the row distance B, diameters of the front and the back piles as d1, d2 respectively, the top beam h1, the coupling beam h2, and proposed a method that determining input data basing the UD and building the RS via nonparametric regression and through Monte Carlo simulation to generate large amount uniform distributive sample points to seek for global optimization solution.
To acquire the approximate function, there needs to design a series of representative sample points distributing in the high dimension space, thus the UD adopted to aid the experiment design can content the request of uniform and representative data and reduce the test number sharply.
Optimal Case and Analysis On the basis of the RS by nonparametric regression and the SVM technique, so the nonlinear mapping relationship between the input support parameters and the guideposts can be obtained; then get amount of random data generated Monte Carlo as the model input data, the RS output the corresponding response value, and search the minimum engineering quantity can obtain the globally optimal solution rapidly.
Table 3 Optimization results excerpts Listed design B [m] L1 [m] d1 [m] d2 [m] h1 [m] h2 [m] Qi [m3/m] Ks KQ Top [mm] Sett [mm] Original plan 2.5 7.5 0.6 0.4 0.4 0.4 6.789 1.357 1.231 23.00 22.00 Opt. 1 2.6 8.8 0.4 0.4 0.4 0.4 6.119 1.353 1.334 22.01 24.08 Opt. 2 2.5 8.9 0.4 0.4 0.4 0.4 6.126 1.353 1.259 23.25 23.70 Opt. 3 2.7 9.0 0.4 0.4 0.4 0.4 6.219 1.353 1.430 20.08 24.34 Opt. 4 2.6 9.2 0.4 0.4 0.4 0.4 6.262 1.353 1.332 22.19 24.54 Opt. 5 2.5 9.4 0.4 0.4 0.4 0.4 6.306 1.353 1.247 23.40 22.43 average relative error of predict value (%) 0.295 4.096 11.1 4.072 From the value in the table, optimal results present that guideposts meet the code requirements and engineering quantity have a reduction of 7.1%~9.8%.
In allusion to the reduction of overall stability coefficient with the increase of the front-pile embed depth, the sample data had already presented the similar characteristics, the reason why it occurred maybe the DSP computing model causes.

The direct consequences of desertification include dramatic increase in number of dust storms, decrease in the land’s ability to produce food, increased social costs, decline in the quantity and quality of fresh water, increased poverty and political instability, reduction in the land’s resilience, and decreased land productivity [2,3].
Data analysis Statistical analysis (ANOVA with least-significant-difference (LSD) tests, correlation analysis, regression analysis, path analysis and PCA) was carried out using the SPSS 13.0 software for Windows.
Therefore, some researchers have suggested that identifying a minimum data set could provide some sensitive, reliable, and meaningful information for soil quality assessment.
Unfortunately, which basic indicators should be included in this minimum data set and how many measurements are required are still being debated.
This multivariate statistical method results in a data reduction that aims to explain the majority of the variance in the data while reducing the number of variables to a few uncorrelated components.

However, the results of the experimental data fitted by Langmuir-Hinshelwood equation show that linear correlation coefficient is also less than 0.90.
Fig.4 shows the fitting results of experimental kinetic data for COD removal by pseudo-first-order kinetic model, pseudo-second-order kinetic model and liquid film diffusion model.
Fig. 4 Kinetic fits for COD removal As shown in Fig. 4a and 4b, the results of the pseudo-second-order kinetic model fitting for experimental data are better than the pseudo-first-order kinetic model.
Data, Vol. 55(2010), p.4614 [2] S.
Data, Vol.58(2013). p.2248 [26] X.

A step size of 0.1 mm was used for EBSD data collection.
Also rolling direction of the specimen was maintained parallel to the beam direction during EBSD data acquisition.
Further, increase of annealing time to 180s (a multiple of 3 x 45s) led to a rapid increase in the fraction of grains larger than sub-micron size, shown with green colour data points in Fig. 2(b).
Nearly 50% of grains were of very fine size (< 2mm) when numbers of annealing repetitions, as shown by black and red data points in Fig.4, were less.
Formation of dislocations or subgrain evolution are expected to influence the local orientation of the grains and to elucidate this, an inverse pole figure analysis of the EBSD data was carried out.

This paper adopts additive model of LMDI method to do a decomposition analysis on factors of carbon emissions of industrial energy consumption from 2003 to 2012 in Nanning urban area, so that Nanning could scientifically establish industrial carbon emission reduction strategy and realize coordinate development between environment and economy.
Model and Data 2.1.
Data sources and processing Industrial energy consumption data sources 2004-2013 Statistic Yearbook of Nanning.
According to the "2006 IPCC National Greenhouse Gases List Handbook"[6], the carbon emission data in each industry have been accounted, and the specific calculation formula is as follows: . (13) In the formula: C means CO2 discharge amount of consumed energy, and i is type of energy.
Among them, data of emission factors of thermal power and electric power come from the 2012 statistics of IEA[9].

Figures 3 (a) and 3(b) show the T dependence of Kab (H || ab plane), Kc (H ||c axis) and nQ for the two As sites, together with the corresponding data for x = 0 and 0.049.
These data also suggest that Ni substitution up to 4.9% does not produce significant change in the density of states at the Fermi energy N(EF).
Figure 3(c) shows the temperature dependenc of Bint, together with the data for the 4.9%Ni-CaK1144 sample with TN = 52 K.
The Kc and Kab data for x = 0 and 0.049 are from Refs. [18] and [24], respectively.
The data for x = 0.049 are from Ref. [24].