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The results for different datum precedence are summarized in this paper.
The functional tolerancing is now widely accepted by industry for contributing to a reduction of manufacturing costs while improving product quality [2].
However, the researches on the influences of datum precedence are still few.
If the datum precedence is plane | cylinder, the tolerance specifications for each part are specified with ISO tolerance language, as shown in Fig. 5.
While the datum precedence is changed, the final result is .

For our case study, we will choose the LSC as a generic strategy of the SC for the following purposes: - Cost reduction; - Flexibility; - Reduction or elimination of all waste.
- Logistics e-information, the request of information related to logistics data to determine the optimal use of transportation resources, warehousing and maximize the value of customer satisfaction
- The product and process e-information, which is a web-based tool and takes care of performance tasks and synchronization of product design content, linking the design teams of different members of SC, product data management as well as direct customer configuration flows and design software
Demand Management In its purest form, such a system would developed from point-of-sale data, which would then be transmitted upstream to all SC members, point to point, with no change in volume, with requirements of the end user for the finished product.
The progressive and dynamic influences that allow the improvement of the SC such as: - The reduction of the cost; - The reduction of Lead-time; - The improvement of quality.

This was done assuming that the efficiency of OTEC is proportional to the temperature difference between the warm surface seawater and the cold deep seawater [12] and using data from [2,7].
Table 1 shows the input data for selected important electricity generation technologies other than non-biomass renewables, while Table 2 shows the global technical potential of seven non-biomass renewable electricity technologies at different cost categories.
Data for selected important electricity generation technologies other than non-biomass renewablesa.
Nevertheless, this study is novel and significant in that it has quantified the competitiveness of OTEC technologies in regional detail using currently available data and has identified world regions where the potential market scale of OTEC technologies is large.
Mai: ReEDS Model Documentation: Base Case Data and Model Description (National Renewable Energy Laboratory, USA 2009)

Data reduction is a consequence of the fact that the number of end-members presents in the scene is usually much smaller than the number of bands.
Dimensional reduction is categorized in two ways: Feature Extraction is done by mapping the correlation of high dimensional data onto uncorrelated low dimensional data.
Unmixing of hyperspectral data is usually carried out the two steps.
Initializing the data by eliminating noise [2].
Ihsan Ul Haq and Qaisar Mushtaq, “Hyperspectral Data Dimensional Reduction and Source Separation Using MAD and Maximum Log-Likelihood”, not published but submitted to journal, June 2011

The high temperature of Pd reduction was observed for Pd/CeO2 and Pd-Ag/CeO2 catalysts.
Hydrogen absorption peaks with the maxima at 60 and 95оС may be assigned to the reduction of PdO fine particles, and the shift of palladium oxide reduction peak into the area of higher temperatures may be associated with both the small size of oxide particles (by XRD data, the coherent-scattering region for PdO phase is 4.2 nm) and strong interaction with the carrier.
The peak of hydrogen absorption at 405оС is presumably associated with the reduction of palladium silicate.
A similar pattern of silver and palladium reduction is observed for the samples based on aluminum oxide.
It is important to note that in the temperature area above 300°С the reduction of CeO2 is not observed in all bimetallic catalysts and sample Ag/CeO2, which is indicative of its reduction together with silver and palladium.

AQDS stimulated bacterial iron reduction and Fe 2+ concentration in solution was higher than Fe 3+.
The reduction of Fe(III) for incorporation into biomolecules is assimilatory iron reduction.
Fe(III) reduction in samples was tested in media with and without 0,1mM AQDS and 2mM NTA.
X-ray and EDS analysis (data not shown) showed that quartz sands sample composed a brown ultra-fine smectite phase and amorphous iron oxide coatings over quartz grains.
[7] Lovley, D.R., Dissimilatory Fe(III) and Mn(IV) reduction.

Multivariate statistical analysis explains the huge and complicated current situation of the original data efficiently, concisely, and explicitly.
It simplifies the original data into representative factors, or bases on the similarity between data to cluster and identify clustering outcome.
This implies that high accuracy can be obtained when discriminant and cluster analyses are applied for data evaluation.
This study provided a novel thought of applying statistical diagnosis approach on anatomizing groundwater monitoring data.
Before subjecting to data processing, data selection and data standardization were the essential steps of data pre-processing.

We find that the curved shape is inverted ‘‘N’’ in static panel data model and dynamic panel data model, rather than inverted “U”.
So we apply panel data set of china for the period 1990- 2008 and dynamic panel data model, to reveal the differences and dynamics effects.
Section 3 describes data and model...
So we use a dynamic panel data model and static panel data model to analysis Model and Data Model.
Data Used.

Rough point cloud data Point Cloud Data Processing A. noise reduction and smoothness.
Effective noise reduction and smoothness algorithm should remove the noise points and retain the sharp feature of the point cloud to prevent that the point cloud data was over-smoothing.
In the past years, Most noise reduction and smoothness algorithm were about the 3D mesh, very few were about the 3D point cloud data.
The point cloud data was separated into the detail data and the foundation data.
The foundation data was taken noise reducing and smoothing, and the detail data was retained.

An analysis of X-ray diffraction, XRD data using refinement method shown both x = 0 and x = 0.02 samples were in single phased and crystallized in rhombohedral structural with Pnma space group.
The experimental resistivity data for metallic and insulating regions are further analysed by fitting with the scattering and hopping models, respectively, and the data are presented to elucidate the possible mechanism involved on the observed resistivity behaviour.
The phase purity and crystal structure of samples were confirmed by Rietveld refinement of XRD data using the GSAS-EXPGUI software.
The solid line plotted on the graph, which represents the SPH model, fits the resistivity data, thus indicating that the electrical behaviour of La0.7Ba0.3Mn1-xFexO3 (x = 0 & 0.02) is governed by the SPH mechanism.
The solid line indicates the best fit SPH model to the resistivity data The Ea values obtained from the slope of the ln (ρ/T) vs. 1000/T are found to increase from 66.61 meV (x = 0.0) to 80.68 meV (x = 0.02) under applied current of 10 mA due to Fe substitution.