Search results

The data collection rate was automatically set by the controlling program supplied by SETARAM to store the maximum number of data points.
Successive reduction followed by carburization.
Reduction.
This would correspond to the complete reduction of WO3 to WO2 (f = 8.35), indicating that at relatively low temperatures reduction of WO2 to W start before WO3 is reduced before the reduction of WO2 to W takes place.
According to thermodynamic data [32, 33], decomposition of methane into carbon and hydrogen is possible above 823 K.

With this system the user can know the forecasting data and decomposition results so as to make corresponding guiding policy.
Data Structure.
The data structures of “predicting the future carbon intensity” and “target decomposition” contain input and output data structure.
The input data of “predicting the future carbon intensity” is the specific year, the output data is the estimated carbon emission and carbon intensity in that year.
The input data of “target decomposition” is carbon intensity and the current year, the output data is the decomposed carbon emission and the target usage of coal, oil, natural gas and non-fossil fuel.

The paper presents the problem of vibration reduction in designed discrete mechanical systems.
The passive vibration reduction based on the synthesis method by using the Synteza application.
Entering the dynamical properties of the system searched By confirming the assumed data, the values of inertial and elastic parameters of the fixed branched system, presented in the figure, are obtained (fig.4).
The result of passive vibration reduction performed Conclusion The paper presents a passive vibration reduction based on the synthesis method by using the Synteza application.
Dzitkowski, Reduction vibration of mechanical systems, Applied Mechanics and Materials. 307 (2013) 257-260

With consideration of the field geological conditions and practical construction, by strength reduction finite element method (FEM) and discrete element method (DEM), the process of collapse is simulated, which is compared with the field monitoring data.
In this paper, with consideration of the field geological conditions and practical construction, by strength reduction FEM and DEM, the process of collapse is simulated, which is compared with the field monitoring data.
The monitoring data obtained after blasting excavation is consistent with the deformation displacement value obtained from the numerical simulation.
Because the deformation value obtained by FEM is computed exactly after the excavation, but the displacement value obtained by monitoring is recovered after the collapse, the monitoring data will delay, which will result in the difference of displacement between monitoring data and computation result. 6.
(4) The displacement obtained by monitoring data is consistent with that obtained by numerical simulation method during excavation

In order to make the system equation have the consistent results with test data, R.
Model Reduction.
From Eq.13, we can obtain the following equation: (14) So, the reduced dynamic stiffness matrix of satellite structure can be expressed as follows: (15) After the dynamic reduction, the model can be updated with measured response data.
The vibration test data is used to update its dynamic model.
Ewins, “finite element model updating using frequency response function data-1.

Data collection The secondary data including their energy use, energy generated and implemented energy efficiency improvement measures were collected from power plants case study.
Emission reductions due to the reduction in no-load losses only are claimed.
The calculation results for each measure are presented in terms of the GHG reduction as shown in Eq. 2.
Intensity of energy saving and emission reduction The results of ESI and ERI displayed the most effectiveness in the same measure of TF01.
To quantify the potential of energy saving and emission reduction, the secondary data of power plants case study were collected.

Moreover, for training the sample data mingled with outlier data in the relatively class of sample, it often can not improve the classification capability.
Data preprocessing.We put a pedal on the stair of the bus.
Fig.1 The system frame diagram of data gathering Feature extraction.
Because the max value of the A/D is 1024, every data can be divided by 1100.
Of SIAM International Conference on Data Mining，Lake Buena Vista, FL, USA,2004

Outdoor SVG “overheat capacity reduction” control strategy Overheat capacity reduction control strategy means to reduce output capacity, limit input current of power unit, thus reducing the overall heat radiated in order to keep the equipment functioning stably when the internal temperature exceeds the safety limit.
The key of the control strategy is to get humidity and temperature data timely and correctly, thus ensuring that the SVG control system can make correct judgment, preventing falling into “overheat capacity reduction” mode by mistake, and enabling initiation of “overheat capacity reduction” mode before overheat failure.
The entire unit consists of the embedded micro-computer, the bluetooth transceiver and the LCD, with input data and operating command keyboard, as well as USB interface and R-485 interface for data transmission.
Temperature and humidity wireless monitor collects temperature and humidity data of different points in real time.
At the end, SVG control system determines whether to enter “overheat capacity reduction” mode and sends alarm signal to the system at the upper level.

Symbolic aggregate approximation is data dispersed dimension reduction method.
Time series data mining is an important research branch of data mining, has a wide application value.
SAX methods in the study of time series similarity is a transformation function with many advantages, such as high compression ratio, retain the local information of the data, effective implementation of the data dimension reduction, solve the problem of high dimension.Have higher tolerance to noise data, the segmentation process is realized to eliminate noise and implements the data smoothing processing;Visual intuitive concise;Multi-resolution characteristics, etc.Therefore, in the time series data mining in the many fields have a wide range of applications[9].
Generally, the dimensions of the new sequence are far less than the original time dimension data sequences, also achieved the purpose of dimension reduction.
There are 100 sample series ECG data set, is divided into two categories, each time sequence of length 96 （http://www.cs. ucr.edu/~eamonn/time_series_data/）.

The 30-day operation data indicated that 10mg/L 2,6-DCP can also effectively reduced the sludge production about 17.9% with the COD removal efficiency decreased about 6.99% and nitrification inhabitation was about 30.91%.
In our previous study, 2,6-DCP was selected as the metabolic uncoupler for sludge reduction, its distribution variation and its effect on sludge reduction were investigated[23].
This showed that the sludge reduction effect of 2,6-DCP depended greatly on pH.
Fig.2 Effect of 2,6-DCP on sludge reduction and nitrification inhibition Fig.3 Reduction of NH4-N, COD removal efficiency and sludge yield and nitrification inhibition Fig. 2 showed the effect of 2,6-DCP concentration on the reduction of sludge yield and nitrification inhibtion.
These 30-day operation data in Fig. 3 had further confirmed that 10 mg/L 2,6-DCP can effectively cut down the sludge production.