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Amorphous Computation Material, or ACM, is a concept of an active material that has the capacity to sense its immediate environment and process that data for intelligent actuation–actuation where the applied force is based on the type of material handled.
ACM poly mer sensors and actuators, and wireless data communication are part of our long-term vision, but are not addressed in here.
Because of our finding that only the points closest to the end of the valve have a noticeable effect on the direction of propulsion (section comparison of Simulation and experimental Data )a minimally-sized, yet functional architecture for the network – was determined to be 4 input neurons, 4 hidden neurons, and a single output neuron.
The data used for this training was a rough approximation of the shapes generated for water hammer experiment (section Experimental Setup ).
Our approach is based on a much simpler design, motivated by a reduction of the complexity of both the individual neurons and the entire network.

Experimental data is mostly analyzed for the induction time and pressure drop.
The results of two groups show that the induction time and pressure drop does not significantly reduction.
b a Fig. 1 Initial pressure 6.4 MPa pressure-time curve (a:without activated carbon, b:with active carbon) Table 2 The specific data analysis of activated carbon hydrogen storage reaction under 6.4 MPa Without activated carbon With activate carbon Percentage increase Pressure drop 0.028[MPa] 0.030[MPa] 7.14% Induction time 300[min] 400[min] -33.33% Density 0.0026wt% 0.0041wt% 57.69% The influence at pressure of 7.4MPa.
Therefore, the data demonstrates that the higher reaction pressure can improve the density of hydrogen hydrate.
a b Fig.2 Initial pressure 7.4 MPa pressure-time curve (a:without activated carbon, b:with active carbon) Table 3 The specific data analysis of activated carbon hydrogen storage reaction under 7.4 Mpa Without activated carbon With activate carbon Percentage increase Pressure drop 0.035MPa 0.040 MPa 14.28% Induction time 300min 300min 0% Density 0.0033wt% 0.0048wt% 45.45% The influence at pressure of 8.4MPa.

It should be noted that the number of data points at 40 bars operating pressure is very limited, especially at liquid load of 10% by mass.
Thus, this limits the amount of data collected at the lower range of liquid load and gas velocity at operating pressure of 40 bars.
Figure 1 - 3 shows that the difference between the maximum and minimum value of all data range is very marginal with standard deviation ranging from a minimum value of 0.21 up to a maximum value of 1.35 as shown in Table 1.
Although the separation performance at lower liquid load is comparable to the separation performance at the higher pressure, there is a significant reduction in separation performance at higher liquid load, even at higher gas velocity as shown in Figure 3.
Considering the very small variance for the experimental data at 50 and 60 bars as given in Table 1, it can be concluded that the separation performance of the horizontal, inline swirl tube separator is fairly consistent.

The optical data were determined with PERKIN ELMER UV/VIS/NIR LAMBDA 900 spectrophotometer.
In the lights of optical data no substantial difference between the two sides were observed.
Therefore, optical data were given without considering air or tin side of coated glasses.
The transmission data obtained at 550 nm after these tests are given in Table 3.
On the other hand, the mechanical and chemical properties of coated glasses with Solution A and C were satisfactory but their transmission data were not as good as coated glasses with Solution B.

Creep model is based on the experimental data with small size specimens.
But the data indicate the hydration heat problem is getting serious with the increasing bridge span.
This paper discussed the accuracy of the hydration heat formulae with the measurement data from the construction site and carried on the research of the hydration heat effect on creep base on the discussion results.
With the statistics and regression methods and the data from the construction sites, literature 5 and literature 6 proposed empirical formulas for calculating the hydration heat of the center and the surface of the concrete plate.
Validation of the method mentioned above has been taken based on the data from Xiangjiang bridge in Baishui, Qiyang.

For example, face image data is two-dimensional, the two dimensional face images must be transformed into one dimensional vectors, the size of the obtained vector space is very big.
Finally, paper conclusions are drawn in section 4 Face recognition algorithm DCT Algorithm 2D DCT is defined as[9][10]: (1) Where (2) The corresponding inverse transform is defined as: (3) For face image data is two dimensional, apply 2D-DCT to face image, then select some coefficients to restructure image.
It indicates that the part coefficients of DCT contain the primary information of the original image, and DCT can realize the effective data reduction.
In the experiments, we select some images from face images data to construct the training data set, the remaining images to be used as the test images.

This absolutely leads to the reduction of productivity and excessive dependence on the service engineer [1].
It can realize resources and data sharing, and be helpful for enterprises to the diagnosis knowledge and diagnostic data communication.
When alarms occurred on CNC, corresponding data such as alarms, warnings, sensor data, can be retrieved by remote server.
Fig.5 The process of CBR diagnosis 2.3 Single-alarm diagnosis with RBR System analyses one single alarm combined with signal and data from machine, to confirm the root-cause with the largest probability of occurrence.

In this study the reduction of the DOF is also analyzed for various legs added between the moving platform and the ground.
Table 1: Assigned data for three poses translation Rotation (deg) No X Y Z X Y Z 1 -1.00 5.00 3.00 5 -20 -95 2 -3.00 6.00 3.00 20 -15 -105 3 -4.00 6.00 3.00 30 -5 -110 Table 2: Coordinates for Three Points at Assigned Poses Pose 1 Pose 2 Pose 3 D (3.5503, 5.8604, 9.3682) (-0.2016, 6.2191, 10.3567) (-2.8614, 5.2393, 10.7540) E (-0.5611, 2.5865, 8.1944) (-4.1391, 3.4040, 7.9963) (-6.3103, 2.9680, 7.2976) F (-0.2906, 6.6780, 7.7625) (-3.4065, 7.4595, 7.8687) (-5.3915, 6.9544, 7.8117) The design of the S-R leg begins with freely assigning the pivot on the moving platform at :(0, 0, -1).
The data for the other solution are : (0.4411, -2.0387, -0.5050), :(0.9814, -0.1543, -0.1146) and =7.4256.

Application of heat pump technology is a effective way to achieve energy saving and emission reduction.In order to propose the heat pump system suitable for marine air conditioning,this paper takes a bulk carrier as the research object,calculates the annual dynamic cool and heat loads of ship,proposes five kinds of cold and heat source optional schemes and selects the equipments.On this basis,five optional schemes are evaluated by using the method of AHP from the following aspects:economic, energy consumption, environment, weight and size.The result shows that comprehensive properties of adopting double stage coupling water source heat pump in ship are better than other schemes.
BIN method is a simplified energy consumption calculation method proposed by ASHRAE[4].According to the local meteorological parameters,we divide the outdoor dry bulb temperature at regular intervals,and add up the time the temperature interval typically occurs during the year or a period of time.In this paper, according to hourly weather data provided by Weather Tool software,2 °C temperature difference as a temperature interval,we average the BIN meteorological parameters of Tianjin and Dalian as BIN meteorological parameters of the ship,as shown in Table 1.
[6] L.O.Degelman,P.E.Bin Weather Data for Simplified Energy Calculations and Variable Base Degree-Day Information.ASHRAE Transactions.1985,91(1):3-13

This data are of important to the model.
Normally, this data was explored and collected by various organizations.
In this paper, the data collected by the Office of Nation Resources and Environmental Policy and Planning of Thailand is utilized and can be shown in Table 2 [10].
Table 3 The input data to the model Legend Tree Absorption CO2 (Ton per year) Expense ($) Trading price ($) Area Si (m2) L (MTonCO2 ~) a Nutmeg 98.62 600.00 11.00 16 16.05 b Bermese 68.04 588.43 c Bengal Almond 89.162 595.34 d Copper pod 107.39 564.67 e Iron Wood 1 83.25 608.50 f Cananga 166.50 614.00 g Afzelia xylocarpa 126.15 598.44 h Iron wood 2 138.75 615.10 i Lagerstroemia loudonii 101.51 598.84 j Bullet wood 121.34 598.50 k Mesawa 91.39 621.34 l Alexandrian Laurel 90.01 600.34 m Java Plum 77.26 615.07 n Kayu 88.32 591.77 Result Using data in Table 3, the optimal solution is obtained and shown in Table 4.
Prombanpong(2010).”The Research Framework for a Reduction of Global Warming Through Efficient Afforestation and Reforestation in Thailand”, 11th Asia Pacific Industrial Engineering and Management Systems Conference 2010, 6-9 December, 2010, pp. 115-119