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We set the derivative ofin (6) on to be zero: (7) Multiplying (7) by , we have (8) Thus may be expressed as (9) Due to (7) and (9), we have (10) That is to say (11) Similarly, we get on dataset B through (12) (12) In order to eliminate correlation of discriminant transform between data set C and data set A, and between data set C and data set B. we construct the objective function and constraint: (13) replacerespectively, (4) convert into(13).
In order to eliminate data the correlation of discriminant transform between set A and B data set.
We set , where is discriminant transform through the Local projection preserve criterion in data set A,so we construct following objective function and constraint: (17) Where is training samples of data set B, is a diagonal matrix,,is a similarity matrix, ,it is a Laplacian Matrix.
Similarly, we get through (26): (26) In order to eliminate correlation of discriminant transform between data set C and data set A, and between data set C and data set B, we construct the objective function and constraint: (27) is training samples of dataset C, replace respectively.(28)is converted into (27).
We scaled the intercepted images to 60× 48 on three face data set.

The former is related with the network establishing, the node joins and data transmission; the latter responsible for data validation, data analysis and data storage.
In turn, if a long single, sink node working in data processing and data storage singly and centralized will also consume energy.
Aggregation part was responsible for data transmission, and processing part for data parsing and filter.
Therefore reduction of energy loss each working cycle of dynamic node can effectively extend the working time of it. 4.
The test data is follow.

An attempt is made to correlate the data with sites occupied by iron in the framework as derived from Mössbauer studies.
The data collection chains on the LT spectrometer consisted of standard ORTEC and TENNELEC units. 16k Oxford Microfast multichannel PC card was used for data collection.
For better visual comparison the data are shown in double logarithmic plots.
These data show that the microporous structure is rather dense, the effect of presence of iron and even the distinction among the influence of FW and EFW siting is not obvious from the present data.
More general conclusions can also be drawn by comparing the obtained data.

Verification is based on comparison with data from industrial processes.
Shown are experimental data from dilatometer experiments (exp. data), the fit of the constitutive equation employed within the framework of this work (new fit) and the Zerilli-Armstrong model parameterized by Chen et al.
The model is purely phenomenological, but describes the experimental data for the full range of temperatures and strain rates fairly well.
The computed rolling forces are in reasonable agreement with the measured results only for these two cases of material models, which were fit to experimental data recorded at conditions similar to the conditions during rolling.
Cook, A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures, 7th International Symposium on Ballistics, 21 (1983)

This paper aims to analyze the values obtained in these situations and interpret the data to determine the influence that each factor has on the acoustic power compared with the values obtained (permissible) according to Directive regarding noise emission D 2000/14/EC.
Fig. 1 Flywheel SDG 3500 CLE Generator The equipment used to determine the sound power level is a measurement and analysis system based on PC - "System Type 3569 C PULSE multi-analysis" produced by Bruel & Kjaer, wich consists in 12 microphones with preamp, amplifier and signal conditioning module with 12 measuring channels, assisted by a notebook computer and software required for the acquisition, processing, interpretation and presentation of data in tabular form. [7, 10] Also, includes a calibration module type 4231 wich generates on the frequency of 1 kHz, a noise level of 94 dB or 114 dB.
After the last measurement channel calibration, the calibration program is closed and the data acquisition program is opened, according to the number of measuring channels.
After its execution, we need to run another program that takes the data from the previous one and processes them according to SR EN ISO 3744 which refers to the determination of sound power levels of noise sources using sound pressure.
This phenomenon occurs because of the existence of reflective planes that fosters reflection and amplify the two physical quantities analyzed; - Using the experimental data of the kind presented in this paper, together with the theoretical interpolation function adapted to the specific measurements, may give clues on identifying areas with high levels of pressure and sound power, helping to optimize noise reduction solutions in these areas.

By identifying the complete shape of the signals and taking into account a larger quantity of data, it becomes possible to ascertain the three-dimensional location of damage sources from AE sensor records.
The leading-edge equipment adopted by the authors consists of six units USAM®, that can be synchronized for multi-channel data processing.
The damage level of a structure can be obtained from AE data of a reference specimen (subscript r) extracted from the structure and tested up to failure.
With increasing specimen scale, instead, we observe an appreciable reduction in failure stresses.
Furthermore, from a statistical analysis of the experimental data reported in Table 1, parameters D can be quantified (Eq. 2) [6].

DIMS-CS system itself still needs to do data and business exchange with other systems.
Its architecture is shown in Fig. 2: Fig. 2 Architecture of the DIMS-CS While the explanation of each layers is as follows: (1) Data acquirement: includes the current basic data of the disastrous area (such as spatial geographic data, population, juridical person information, socioeconomic data, etc.); data collected in the live site and uploaded by mobile equipment or Internet; data acquired by data mining from the Internet, including web portals, social network, and the business data from other systems, such as delivery status of relief material, in-time location of medical rescue teams, etc.
(2) Database: manages various kind of data, including the existing basic data of the disastrous are, various disaster information (UGC-DI, PGC-DI, M-DI), users information (profession and public) and management data of system (such as log)
(3) Platform: deploys the primary platform management functions, including GIS platform (digital map update, disaster information labeling and spatial analysis), data merging (PGC-DI and UGC-DI), data exchange (with other systems), and data mining
All these data is merged on the platform and released to the public users, professionals and SNS websites through the data release module.

Q Li[11] using the data of major cities in the Zhu-river delta region of pollutants concentration and the weather data, analysis the Zhu-river delta region weather types and the qualitative relationship between the ground concentration of air pollutants.
Guilin is now construction international tourism resort, so control haze weather is the goals of environment construction, haze research must be strengthened. 2 Data and methods The statistical analysis is made on total of 50a (1964-2013) of haze observation records of 13 stations; Gather the haze date of counties around Guilin adjacent in recent five years.
Guilin 13 station haze day changes in each year of total average data. 3.2 The monthly variation Statistical the haze days in each months respectively, it is in figure 2.
Wind speed decreased is favor to formation of haze. 6.3 The influence of the inversion According to analysis on Guilin upper air meteorological data in recent 10a, it basically every day all the year round has different thickness of inversion layer in different height.
Meteorology and Disaster Reduction Research.

The honing head uses spring instead of the inflation core mechanism connection of oilstone bed for the constant pressure honing.[3] Honing Head for the Internal Surface of Blind Hole. 1.Basal body；2.Pivot bush unit；3.Sliding nut；4.Inflation pulp core；5.Oilstone bed；6.Oilstone Fig. 3 Structure of the inner bore honing head In Fig. 3 the inner bore honing head has four oilstone grooves and eight empty grooves for weight reduction.
Data Processing and Results Discussion.
Using the common oilstone honing processing for the workpiece, the data is showed in Table 1;Using the different oilstones honing processing in common honing dosage, the data is presented in Table 2.

Stage 7 develops to stage 8 very quickly during the test, and because of the limited capacity of test power, the actual flashover test data can be obtained only from stage 1 to stage 7.
Table1 Process of insulator XP-70 flashover test Fig. 6 Flashover state recognition result using fractal HMM Discharge stage Discharge characteristics 1 No significant Discharge 2 Violet Mars, purple small discharge, silenced 3 Brush discharge purple, yellow, white small Mars 4 Orange short arc, pulse-intensive, continuous discharge, loud 5 Pulse frequency reduction, 1 / 3 of leakage distance 6 Pulse interval lengthened, bright orange-red main arc, many small arcs in groove 7 Strong discharge, almost through leakage distance, able to suffer 8 Red arc, flashover may occur at any time From Fig. 6 we can see: with fully humidified pollution layer during the flashover development, the spark discharges into a small arc, flashover comes into stage 4.
Thus the corresponding recognition from stage 4 to stage 3, as shown in the data segments9-10,12-13,18-19,21-22,24-25.
Similarly, in later flashover development, for various reasons the orange-red main arc (stage 6) is also possible changing into one third of the discharge distance (stage 5), corresponding changes as data segments42-43,46-47,50-51,54-55.