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Application of crystallization refining provides the following advantages in comparison with the traditionally used PUREX-process: - relative simplicity of remote control; - reduction of organic diluent volume during extraction; - reduction of expenses on equipment and hot cell dimensions; - reduction of liquid radioactive wastes volume; - adherence to the principle of the non-proliferation due to nonseparation of uranium and plutonium (during co-crystallization of uranyl nitrate and plutonyl nitrate hexahydrates) during SNF processing.
Dependence of UN concentration in fluid phase (full linear) and UN saturation concentration (dash-and-dot linear) on dimensionless coordinate The data on incoming and calculated flows of various products with the mentioned above parameters are presented in table 1.

Distributed generation network connection The following analysis is based on real power system operation data.
That means that distributed generation integration will favour 35-110 kV transformer equipment loading reduction, providing additional reserve capacities.
Power transformer loading reduction is urgent for “bottleneck” power transmissions with insufficient current-carrying capacities.
If installed in such a network, distributed generation will enhance power supply reliability and efficiency by means of transmission equipment load reduction [2].

If not for the optimization design, it is impossible to realize real-time software receiver on PCS. 2 Process optimization and computational based on pipeline Coherent integration software receivers belonging to accumulate data-intensive computing processing, in order to meet a lot of intensive computing, software design common Single Instruction Multiple Data (Single instruction multiple data, SIMD) technique, SIMD technology is a multi-processing using a single instruction channel data stream CPU execution mode, that is, within a CPU instruction execution cycle is completed with one instruction multiple data processing operations, can give full play to the processing performance of the CPU, to improve software execution efficiency.
SSE4 is an important improvement in one instruction cycle while performing 128 multiplications , 128 additions, 128 and 128 data loading data restore , or four 32-bit single- precision floating-point multiply and four 32 single- precision floating point adder .
Let ( or ) A 16-bit value exists in, PN code data 16 in the presence of B, in particular Table 2.
Since mm0 to have been used to store the results, so only another seven when optimizing MMX registers can be used, each cycle data throughput can only be 56 bytes.
Corresponds to sampling data.

Matlab programming is used for data processing.
Introduction It is important to for a sonar device to identify an object from the tons of data.
When this distance is small enough, the appropriate size of window will be found, which can to use to for future data partitioning.
The toughness of applying ANNs lies in the design of neurons and the data that are passed in between these neurons.
Mitchell, Despeckling SRTM and other topographic data with a denoising algorithm, Geomorphology, vol. 114, no. 3, pp. 238-252, 2010

The results indicate that: water loop heat pump unit, due to investment recovery period with only 2.9 years and carbon emission reduction up to 22.68%, has significant economy and environmental protection, which is followed by water source heat pump; the screw chilled water units plus gas boiler is poor.
The data above were used while calculating the energy consumption of different cold heat source.
The data of annual energy consumption of alternatives are shown in Table 2.
According to the data of literature [19] and [20], CO2 emissions generated from the unit electrical energy of coal power could be calculated about 0.822 kg / kWh.
For decreasing the greenhouse impact of refrigeration and air conditioning equipment to environment, the reduction of energy consumption of refrigeration and air conditioning equipment and the improvement of its performance coefficient should be done first.

In order to research the effects of every factor of evaluation system of accounting, method of Data Envelopment Analysis (DEA) in operational research is suggested to evaluate the economic effectiveness of resources invested in developing nanomaterials.
The Data Envelopment Analysis (DEA) evaluates Decision Making Units (DMU) by using the mathematical programming pattern comparing relative efficiency between DMUs [3].
The necessary data for method of Data Envelopment Analysis (DEA) comes from the financial data chose carefully from accounting information.
Fig. 1 Flow chart of DEA method for accounting system of economical assessment Suggestion of System of Accounting Data for Models.
There are I kinds of input factors of accounting data and J kinds of outputs in every decision-making unit.

The present work focuses on computation of incubation time tinc for static recrystallization using laboratory hot deformation data and on extrapolation the results to industrial conditions.
Once tinc is computed from Eq. (4) using the laboratory data for σDRX,c and the dependences of tinc on T, e, are established, then, for given pass strain and strain rate, Tnr is defined as the temperature, at which the characteristic rolling time (e.g., interpass time tip for given strip dimensions and rolling speed) is equal to the SRX incubation time tinc.
Simulated pass temperature profiles Pass # Tpass Reduction Strain Total Exit gauge Exit speed Strain rate tip, oC % strain mm m/sec 1/sec sec Crop Shear 1050 34.040 0.69 - - 1 1029 51.9 0.731 0.731 16.388 1.44 13.4 4.167 2 1007 37.7 0.473 1.204 10.212 2.31 27.3 2.600 3 986 28.5 0.335 1.539 7.305 3.23 45.1 1.858 4 964 21.3 0.239 1.778 5.752 4.10 64.6 1.463 5 943 16.7 0.183 1.961 4.790 4.92 85 1.220 6 921 14.2 0.153 2.114 4.110 5.74 106.9 1.045 7 (FM exit) 900 13.2 0.141 2.255 3.570 6.60 132.1 1.818 tip – time after the pass; interstand distance – 6m; Distance between FM exit after pass #7 and the beginning of accelerated cooling – 12 m.
The main reason is that in hot strip rolling mills the interpass times, rolling speeds and pass reductions are interdependent in contrast to laboratory mechanical tests.

Classification rule is composed by nine features chosen from the network audit data.
The selected sample data is KDD CUP1999 database [8] which is authoritative test data in intrusion detection field at present.
This database provides a total of 4900000 data, including intrusion data with 4 major categories and 24 small classes.
Then, the training data and the testing data are tested with these rules respectively.
In addition, the correlation of different attack types and each feature of network data is not the same, so reduction of rule set and optimal coverage of rule still need to be further researches.

Comparison among experimental data, simulation data and the results of other predictive models [5]. a) Experimental data, b) Simulation data with 22500 nodes, c) Mori-Tanaka l/t=57, d) Mori-Tanaka l/t=97, e) Halpin-Tsai l/t=57, f) Halpin-Tsai l/t=97.
Comparison among experimental data, simulation data and the results of other predictive models [6]. a) Experimental data, b) Simulation data with 22500 nodes, c) FEM model, d) Improved Staggered model.
Comparison among experimental data [7], simulation results and the ones of other predictive models. a) Experimental data, b) Simulation data with 22500 nodes, c) Mori-Tanaka model, d) Halpin-Tsai model.
Fig. 5: Young’s modulus as a function of the filling fraction f. a) Experimental data [9], b) Simulation data with 12100 nodes, c) Simulation data with 22500 nodes.
Fig. 6: Young's modulus trend as a function of the filling fraction f. a) Experimental data [11], b) Simulation data.

Logical structure diagram of system 2.3 Data structure design Data structure and data model are important research directions in the field of GIS, but mature data structures in GIS are mainly for personal computers or workstations, which are not suitable for mobile GIS systems running on Pocket PC.
Data used in alteration survey includes the latest information of land use alteration and work base map (current land use database or the image data), which means that the PDA needs to store data both of vector form and raster form.
Block structure refers to the use of vector data reduction method, which subdivides the space vector data into N parts, and reads just part of graphical data whenever PDA displays graphical data to meet the requirements of rapid image display and data storage.
Hierarchical structure means to read the graphical data of a small scale vector image first when PDA space data is read, and display the overall picture.
The data content read by PDA every time is cumulated on the previous object data, so it will not incur the repeated reading of redundant data.