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Data gathering.
Starting point are highly aggregated data on factory level.
Separate value trees are set up for input (energy, material, manufacturing equipment, and personnel), throughput (machine times, machine states, and order data) and output data (products, emissions), compare [8].
The separate data trees are connected by horizontal calculation rules.
This level requires mainly technical data, e.g. processing and setup times, tool life, and electrical power per machine state.

For e.g. in TELNET, a typical packet contains 1 byte of data.
In large packets the header overhead becomes negligible as its size would be appreciably small when compared with the size of data encapsulated.
Data encapsulation takes place at each layer in terms of control information added as headers and uses a set of protocols to send data down to the next layer.
For e.g., 90% of TELNET and RLOGIN packets carry less than 10 bytes of user data.
Now the datagram with the customized IPv6 header is encapsulated into a frame by the data link layer and sent to the destination host.

Introduction In case there is no index the great amount of multi-dimensional data with, data querying is quite slow.
The data object region of leaf node stores the information of index data, and the data object region of non-leaf node stores child nodes.
Thus it ensures the sequence ordering of index records in leaf node and a reduction of overlap between non-leaf nodes.
Two data sets are used in the experiments, Intel data set and Bio_Train data set.
N attributes in the data set are selected as the experimental data and converted into FloatStream a data type of VegeBam2.0, and imported into the database.

Data of CO2 emission and absorption in full life cycle could be obtained through market and literature research.
The initial interface of system includes “Input Data” and “Analysis Results” (Fig.1), according to the real-time information from dynamic display of CO2 emission, CO2 absorption and net CO2 emission.
The owner can input the corresponding data in the system according to the actual operation stage.
The input data of property come from two ways, one is construction drawing and corresponding acceptance records, the other is operational data acquired from daily management.
CO2 factor comes from reliable research, providing scientific data for the operation of the evaluating model.

Mathematical dependences (σpl -T i σpl - ἐ) and compression data were used to determine material constants.
Flow stress vs. deformation temperature and strain rate dependence σpl=f(,T) was determined based upon both literature equations and experimental data (Fig. 4 and 5).
Decreasing the value of strain rate from 4x10-4 to 10-4s-1 results in a 15% flow stress reduction.
Increase of deformation temperature was found to have a greater influence on the flow stress value reduction.

,control-flow, data-flow, and transactional dependencies).
Generally we assume that each service is specified by its preconditions and effects in the planning context, which can be explained in two ways: Firstly, a Web service is a software component that takes the input data and produces the output data.
Definition5（Reduction）as for the generated composite service, some concepts may appear in its input and output parameter lists (）, reduction is defined to adjust its relative vector.
After reduction operation, the relative vector of the generated composite service is as + + 。

LA was established mainly by Beremin group for solution of tasks associated with statistical size effect, scatter of experimental data and prediction of temperature dependence for fracture toughness [1, 2].
Temperature dependence of the main mechanical characteristics of iron: is a fracture stress, is yield stress, is reduction in area Figure 2.
The value of average strain in cross-section of notched specimen was estimated as follows: , (4) where - reduction in cross-sectional area, is a diameter of neck after fracture, - is initial diameter of a specimen.
For our RPV 15Ch2NMFAA steel the similar analysis is based on the standard CT specimen data.
The results are very close to literature findings, m parameter for 2 parametric local approach was determined to be 7.4, for 3 parametric local approach and data in temperature range <-90, -130> oC the shape parameter gains the value m = 1.9 (at = 1260 MPa).

The average reduction ratio was 1.066.
The reduction ratio for each cycle was calculated using the formula (1) [11].
The overall reduction ratio determined using the formula Кoverall. = К1 × К2× К3×...× Кn (2) where К1, К2, К3,…Кn are the reduction ratio per cycle of deformation.
The magnitude of the overall reduction ratio was Кoverall. = 1.90 and the total amount of deformation was 65 – 68 %.
The effect of the quenching temperature for 0.5 h and subsequent annealing at 600 °C for 1 h on the microstructure of hot-rolled sheet steel 10 (3 mm thick) made with a preliminary thermal-cyclic forging: a - 880 °C; b - 900 °C; c - 920 °C; d - 940 °C Data in Table 5 shows that the most optimal combination of strength and plastic characteristics of sheet steel 10 made using the preliminary thermo-cyclic forging mode is provided by hardening heat treatment: quenching, 900 °C, 0.5 hours, water and tempering 600 °C, 1 h.

The collected data were analysed using correlations analysis to determine the effects of familiarity with office equipment on human errors and accidents.
Method Surveys were used to obtain the relevant data for this study.
However, the correlation between familiarity and the reduction in the occurrence of accidents is not significant (RAccidents=0.000, p>0.01).
Carelessness of workers can also be another reason why familiarity does not correlate with the reduction in the occurrence of accidents in the workplace.
However, the correlation between familiarity and the reduction in the occurrence of accidents is once again not significant (RAccidents=0.000, p>0.01).

The Matrix Method for Data Evaluation and its Advantages in Comparison to the sin2ψ and Similar Methods Balder Ortner1, a, 1Schillerstraße 34, 8700 Leoben, AUSTRIA aBalder.Ortner@aon.at Keywords: X-ray stress measurement, X-ray elastic factors, matrix method, sin2ψ method.
This article gives an overview of different methods for data treatment in x-ray stress measurement, and how these methods should be replaced with the matrix method, which in general is more versatile, more accurate and, in most cases, also easier to handle.
Accuracy of the results – how strong is the correlation between measurement errors and errors of other input data and errors of the results.
The loss in accuracy by using one of the older methods is quantified by a number AR (accuracy reduction), which means (ΔσS – ΔσM)/ΔσM in percent.
Simplicity – whether data evaluation is a straightforward or a complicated procedure.