Search results

However, when physical properties depend on microstructural details (such as the spatial correlation of crystallite orientation, the shapes and dispersion of second phases, extremes of statistical distributions, or local anisotropies) such data reduction is often difficult or pointless [6,7].
The user starts with a digitized image of the microstructure and builds a data structure on top of it.
All the data plus any that can be inferred by the user is employed.
For OOF2, the microstructure is a data structure composed of image and property data[6].
Finally, for the OOF2 program, the microstructure has become a set of data consisting of images and properties.

Cutting temperature is sampled by data acquisition card Advantech PCI-1710.
After the temperature is sampled, the PC will handle the sampled data and create the input of fuzzy control system.
Data acquisition card PCI1714UL is applied to sample vibration and AE signal for further study.
The main modules include: human-machine interface, data acquisition, data filter, fuzzy control and output of control value.
AE sensor and two vibration sensors are applied to sample data for further study.

At present, the absolute position sequence has been completed via human-computer interactions including region selection and direction identification, and the data out of the selected region haven't been used for calibration.
During calibration, it requires to calculate based on image data of calibration target at different poses.
Conduct curve fitting to experiment data by applying least square method to get the optimal approximate solution.
Draw a straight line, designated as L, passing point B and point D, and designate the lesser of center data of B and D as R, the searching radius.
Reduction Algorithm for 3D Scattered Points Cloud Data Based on Clustering PlaneFeature [J].

The results are used as input data for the production planning and control (e.g. to create work plans or to allocate jobs to machines).
The focus was laid on the consistency of the data collected and the validity of the simulation model.
Regarding the validation of the simulation model, separate parts were checked isolated for validity using real production data from the MRO company.
Conclusively, the entire simulation model was validated by a comparison of the simulation results, such as cycle times, with real production data.
Nyhuis, Validation of data fusion as a method for forecasting the regeneration workload for complex capital goods, J.

Unfortunately the data are classified and quite sensitive.
Before presenting the results here data were de-sensitised and the results correspond with the reality in modified way.
Real data were recorded while performing live experiments.
The FPT distribution was modelled based on the real test data and above mentioned principles.
Chapman, Modelling Task Completion Data with Inverse Gaussian Mixtures.

Coal Output Prediction and Policy Implications of China’s Future Energy Supply Kejia Yang1, a, Jianping Ge1, b, Yalin Lei1, c 1 School of Humanities and Economic Management, China University of Geosciences (Beijing), Beijing, China aykj0411@gmail.com,bgejianping@cugb.edu.cn, cleiyalin@cugb.edu.cn Keywords: GM (1, 1) model, coal production prediction, carbon emission reduction Abstract.
The solution of the equation (6) is given by X(1)(k+1)=(x(0)(1)-b/a)e-ak+b/a(k=1,2,.,9) (7) Where x(0)(k+1)=x(1)(k+1)-x(1)(k)(k=1,2,…,9) (8) Data Raw coal output increased exponentially from 1990 to 2012 [1].
Hence, the data of raw coal output from 2002 to 2012 was used to predict future output of Chinese coal industry.

Though most of the existing methods are highly sensitive and reasonably safer to use but still there is the need of development of new green methodologies focusing on the reduction of solvent consumption, replacement of environmentally hazardous solvents with more benign alternatives, miniaturization of instrumentation and solvent- free sample preparation.
- Miniaturization of instrumental set-up - Reduction of analytical operations - Automation and integration of different operational steps.
Minicolumn techniques should not be used for quantitative purposes where accurate quantitative data are required.
Wild,  Reduction in exposure to carcinogenic aflatoxins by post-harvest intervention measures in West Africa: a community- based intervention study, Lancet 365 (2005) 1950-1956

The results were compared with empirical rules and experimental data and are used to estimate the mean 3-D dihedral angle.
The corresponding growth rate exponents are obtained by fitting a power law through the simulated data as a function of time.
The 2-D cross-sectional data from this experiment were used by Liu et al. [7] to reconstruct a 3-D microstructure employing a forwardtransformation method.
A Weibull distribution with shape factor 4.22 describes the 3-D reconstructed data best, which is in good agreement with the simulation results.
For comparison, experimental data obtained for a 78 wt% W alloy [7, 8] is added.

Commissioned by the group, collect the transport group traffic accident data from January, 2008 to December, 2012, then carry out statistic analysis of the traffic accidents data.
Data Statistics Road traffic system is a complex dynamic system consisted of four elements: person, vehicle, road, environment [2].
This paper analyzes the data combined with the four elements.
Fig.10 Distribution of liabilities Fig.11 Distribution of drivers’ driving-age Accident data analysis Time distribution analysis.
According to a lot of similar research data, 14:00-16:00 is also a high-risk period [6].

The sensor is interfaced to a notebook computer using a multipurpose data acquisition board and few custom made circuits.
Data collection, errors correction and calibration modules were written using LabVIEW programming language.
The data for board thickness corrections and for temperature corrections for the MC measurement system have been developed.
A production unit will need temperature hardened batteries, on-board storage of data, and intermittent operation to save battery life.
The training set is realized joining the subsets of measured (about 40) and simulated (about 80) data.