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A Study on Bore-sighting for the Error Reduction of the XK11 Woon-Joo Yeo1, a , Je-Wook Chae 1, b, Chan Lee 1, c , Eui-Jung Choi1, d and Jun-Ho Lee 1, e 1 Agency for Defense Development, Yuseong P.O.
Image processing method with Charged Coupled Device camera is chosen for the Error reduction of bore-sighting.
� Noise Reduction Erosion Erosion is used to get rid of the remained noises after Binary-Coded work
So dilation is used to restore the laser points reduced by the erosion for noise reduction
{ }ˆ( )z A B z B A ⊕ = ∩ ≠ ∅ (3) Labeling The work dividing the data cognized two laser points to only one color called Labeling.

A novel adaptive image feature reduction approach for object tracking using vectorized texture feature is proposed in this paper.
The dimension reduction has advantages of reducing the computational cost in classification stage. 3) An adaptive learning rate was proposed to handle drifts caused by long term occlusion.
The definition is given as follows: (1) where The is given by least square loss which measures how much the training data is different from an assumed distribution.
(Fig.1 shows how the dimension reduction affects the image quality) is the labeled sign denoting which class the belongs to.
The 15% reduction rate is almost the highest that we could restore the image without noticeable visual quality loss.

Reduction of anatase started just below 900ºC whilst rutile underwent reduction below 800ºC.
Positions of the peaks were taken from the ICDD database, however, peaks for the mixed valance TinO2n-1 phases where n>3 were only present up to 2θ = 50.2º and the data for these has taken from the paper by Bowden et al [16].
The onset of reductive mass loss in rutile system occurs at ~770ºC, about 100ºC lower than for anatase system Beyond the initial mass loss due to desorption, it is difficult to compare the curves in Fig.1, therefore the data has been differentiated so that the stages become more clearly defined.
Further heating to 1380ºC resulted in completing the reduction.
The reduction of rutile started at ~770ºC whereas reduction of anatase began about 900ºC.

Its calculation procedure is shown as below: Step1: Confirm the reference sequenceas a record in standard fault sets and comparative sequence, process the data being dimensionless.
Step2: calculate difference sequence, whereas comparative sequence which is unknown pattern, as reference sequence, which is history diagnosis data sequence.
Select the record in reduced diagnosis knowledge database as reference sequence, the data observed which transform to reduced space as comparative sequence.
Part of the data that sampled repeatedly and modeled by AR time-series in normal and wear state is shown in Table1.
Use 10 of 20 data acquainted with known state construct the learning samples data sets, the other 10 data as test data, after the original data normalized, Use respectively the grey relational analysis(method 1)and rough set based weighted grey diagnosis method(method 2) to recognize their status.

In recent years, a variety of manifold-based learning dimensionality reduction techniques have been proposed, which attempt to project the original data into a lower dimensional feature space by preserving the local neighborhood structure.
But, when the data is distributed in a nonlinear way, LDA may fail to discover essential data structures.
LPP can preserve the intrinsic geometry of data and yield an explicit linear mapping suitable for training and testing samples.
In order construct the objective function using labeled and unlabeled data, we give total-scatter matrix and the local scatter matrix , respectively.
As a result, OSMFA is more effective and efficient in face recognition.Experiments on face data show that the proposed algorithm has more discriminative power in comparison with SDA, MFA and ODLPP.

The collected vibration signal can be used for data mining as well as obtaining fault rule based on the rough set theory.
Vibration data mining based on Rough Set theory 60 vibration signal of the rotor experimental platform sample data were analyzed, and the normalized energy as condition attributes, using fault types as decision attribute to form fault diagnosis data tables.
So we chose 80% of the data as training samples, 16 samples of each fault samples, and take the remaining 20% of the data as a test sample.
Data partition is obtained according to the above method(Table 3).
The table 4 shows that the reduction produces 37 diagnosis rules. 

Data for CDM projects were found in the database of the United Nations Framework Convention on Climate Change (UNFCCC), and the projects used were obtained from the National Agency of Electric Energy and a geo-referenced information system of the power sector.
Installed capacity, capacity factor, and reservoir area were data of interest, found in thegeo-referenced information system of the ANEEL (SIGEL) [5].
These data were for 1401 enterprises located on the Brazilian interconnected power system.
The average emission factor (Ef) of the interconnected system was calculated according to the data available at the MCT [6] website.
These data take into account the methodologies ACM0002 and AMS ID from the UNFCCC.

China, 650500 a1139257776@qq.com, b15808867407@163.com Keywords: Foundation break; Vehicle test; Parallel acquisition and data transmission; Large data processing Abstract.
The system design concept and concrete implementation of the key technologies such as parallel acquisition and data transmission, large data processing and time-frequency noise reduction were all introduces in detail.
When collecting external host computer, each data acquisition module picked by CRIO-9862 after the summary to be uploaded to the PC for further analysis, while the external LCD display critical data speed, brake temperature; otherwise CRIO temporary hard disk data to be tested after the upload. 3.3.
Conclusion Based on the parallel acquisition and data transmission, large data processing technology, designs out a portable car braking performance-based multichannel detection system.
The Design of Data Acquisition System Based on LabVIEW.

The microphone data were collected using a two-channel B&K analyzer 2144.
Measurement of these parameters were performed using pressure transducers, temperature and humidity sensors and recorded and processed by the data acquisition station - SAD-2, equipped with the ADAM modules 4000+, an integrated PC with the application GeniDAQ, equipped with a Visual Basic language [43].
In each measured points the data were recording by 10s with resolution 0,1s.
All figures present the data from 100 Hz to 10 kHz (Fig. 5).
It could offer the data basis and bionic model for the application of owl silent flight in engineering.

How to manage energy consumption appropriately and energy saving and emission reduction are becoming crucial issue of the problem.
Research on energy consumption, conservation and emission reduction system of Beijing 1.3 Factor analysis of the system First, comparative analysis of raw coal consumption intensity has been made and shown in Figure 3.
A: Structure share B: Efficiency share On the basis of the analysis theory it could be found out that the raw coal consumption intensity analysis result is like the data shown in Table 1.
Table 1 Energy intensity of Beijing Year Structure share Primary Industry Secondary Industry Tertiary Industry 2006 -0.9336 0.0434 -0.6256 -0.3514 2007 -0.2675 -0.034 -0.4108 0.1773 2008 0.1738 0.0139 0.2541 -0.0942 2009 0.1582 0.014 0.2277 -0.0835 2010 -0.1491 -0.0198 -0.2097 0.0804 Year Efficiency share Primary Industry Secondary Industry Tertiary Industry 2006 1.9336 -0.086 0.0222 1.9974 2007 1.2675 -0.005 0.3278 0.9447 2008 0.8262 0.0075 0.4608 0.3579 2009 0.8418 0.0123 0.4653 0.3642 2010 1.1491 -0.0212 -0.6413 1.8116 Seeing from the data from Table 1, structure share reflects unreasonable industrial structure.
The data is normalized by using Min-max method.