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With these, the product design and manufacturing cycle has shown time reduction [1].
Registration of CMM and optical scanning data In a combined method, data collection using a touch probe and an optical scanning probe must be transformed into one common coordinate system.
Data merging When the registration has been performed, the data from a touch probe overlaps with the triangular mesh model.
When the weight of the smallest edge is larger than a given threshold, this graph reduction ends.
The sampled data of cylinder is used to simulate the data acquired by CMM (sparse data at left) and optical scanner (dense data at right), as shown in Fig. 2(a).

The information can be represented by one data structure and we call this information structured data such as number, symbol and etc.
Actually, structured data is a special case of unstructured data.
The problem with unstructured data.
Customer Preference Analysis Based on SNS Data.
A Parameter Reduction Based Technique For Automatic Analysis of Database Systems.

To date no experimental data is available about the dynamic temperature profile for refinery sludge gasification in an updraft gasifier.
In order to measure the temperature profile inside the gasifier and classify the gasification reactions zones, five type-K thermocouples connected to data logger (USB TC-08) and the readings of the temperature are logged in the computer.
In gasification, reduction reaction is the prefered.
Combustion is also important as it sustain the endothermic reduction reaction.
Obrenberger, “Updraft- Fixed Bed gasification of Softwood Bellets: Mathematical Modelling and Comparison with experimental data,” in European biomass Conference and Exhibition, 2009, no.

By data-mining through large amounts of datasets, we showed that CNTs with small diameter, large number of walls, and crosslinks between walls can have high nominal tensile strength.
Data Mining with SOM With the ability of visualizing and categorizing information of materials, SOM is an integrated tool for material research [20].
The data mining approach with SOM aims to decrease the complexity of high-dimensional data, and reduce the high-dimension data to two-dimensional data.
To further understand the overall relation between geometrical properties of chirality, diameter, wall, crosslink and geometrical properties, we use SOM to dig on our data shown as Fig. 7.
Summary The relationship between mechanical properties and geometrical properties of CNTs were investigated by high-throughput molecular simulation and data mining technique.

Data mining analyze the great amount data of CRM to make reactions in electronic commerce.
It is a platform based on C/S mode, which contains data pretreatment, the building of data warehouse, data mining and management of the content of E-mail.
Data pretreatment is to clean the data, to do the integration and transformation, and to do data reduction.
After data pretreatment, data is stored in data warehouse for data mining.
Data mining: For the data source provided by data warehouse, we build the mathematical model, train the data and finally get the rules for the website platform according to the target of the system and the paper.

However, few reports can be found focusing on the study of high-solid anaerobic digestion of sewage sludge, and no data were available on the start-up performance of high-solid anaerobic digestion at mesophilic temperatures.
The performance data of the first 20 days indicated that starting OLR should be controlled to avoid VFA accumulation above 3 g/l.
With OLR increased from 2.0 to 3.0 kg VS m-3d-3, the methane yield decreased from 0.266 (average of the data in Fig.1 a from day 50 to 59) to 0.231 l CH4 g-1 VSadded-1 d-1 and the VS reduction decreased from 42.2% (average of the data in Fig.1 a from day 70 to 85) to 33%.
a b c Fig.1 Performance data of semi-continuous reactors with designed fed-sludge TS of 10%(a), 15%(b) and 20%(c).
As focusing on start-up period, there is shown the performance data at the same OLR but different TS in Fig.4.

Furthermore, thermodynamic analysis results coincide well with the experiment data.
(11) (12) Table 1 -T data sheet of the reactions (2)-(9).
Equation (2) (3) (4) (5) (6) (7) (8) (9) (KJ) 25℃ 125.6 380.3 126.0 -254.7 -0.4 5.96 260.3 5.5 480℃ 29.7 214.8 37.2 -185.1 -7.6 -1.7 175.8 -9.3 560℃ 12.9 186.6 22.1 -173.7 -9.2 -2.68 161.8 -11.9 630℃ -1.4 162.5 9.2 -163.9 -10.6 -3.19 150.0 -13.8 700℃ -15.7 138.4 -3.7 -154.0 -12.0 -3.77 138.3 -15.8 800℃ -35.9 104.3 -22.0 -140.1 -13.9 -4.5 121.7 -18.4 1000℃ -75.6 37.0 -58.1 -112.6 -17.5 -5.8 89.3 -23.3 According to Eq. (11) and Eq. (12) and looking up the data table, the thermodynamic data of several compounds involved in (2) ~ (9) reactions can be obtained.
According to Gibbs-Helmholtz equation (10), the data of (2) ~ (9) reactions at the different temperature listed in Table 1 is calculated, and the curves of relationship between and the reaction temperature shown in Figure 1 are created.
For lack of the thermodynamic data of Sn(OH)4, the curve of the reaction (1) is not created.

The residual Young’s modulus data are presented in terms of normalized quantities.
Furthermore, establishing and interpolating of constant life diagram data using these methods is a tedious task, since they require a large collection of stress-life data to suit various wire rope designs.
These much-needed fatigue-life data are usually based on the data taken from available standards such as DNV OS-E301 [13], and the available literatures which are very limited.
The life data of the steel wire ropes at the various fatigue loading conditions is shown in Fig. 6.
The fatigue strength-life (S-N) data of the drawn steel wires is shown in Fig. 8.

With the great volume of operation data, an fuzzy rough set (FRS) –based big data analytics were introduced to build the intelligent energy-saving decision-making model.
Big data-driven energy-saving decision-making model of thermal power units 3.1.
Energy-saving decision making model The proposed intelligent energy-saving decision making model are based on the great volume of practical operation data with big data analytics.
Such a method emphasizes the huge volume of data and implies that the collected data set covers almost the whole population as well.
Remote data center monitoring and management.

Decode circuit in chip decompresses the compressed data from the ATE and applies them to ICs during testing.
Let counter 1 decrease by 1 and the circuit latch data on the bit_in.
This indicates that the proposed test-bit rearrangement algorithm is successful and effective in improving compression effect of test data.
This indicates that the run-length assignment strategy is effective in improving compression effect of test data.
Reduction in average power consumption is .