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For analyzing the effect of a green roof on the thermal environment, this paper collects temperature and humidity data from two building roofs that have different greening levels and tries to analyze the thermal influence of a green roof on air temperature in Taipei City.
The results of this research can give citizens an idea what kind of thermal environment they can benefit from; moreover, it also can provide useful data to governments for calculating the environmental benefit if they carry out a green roof policy.
Although green roofs can cool the ambient air through consuming the solar heat that is gained from transpiration and photosynthesis, some quantitative data on its thermal benefits are desirable for exploring the thermal impacts of green roofs in the Taipei metropolitan area.
The comparators were also installed on non-green roofs (NG) near Site A and Site B to collate data for making comparative analyses.
Data analysis In this research, the green coverage ratio of Site A and Site B are 24.42% and 35.05% by calculating the greening area within a radius of 10 meters.

We will use this information for a dimension reduction of the parameter space in order to reduce the curse of dimensionality.
With the so constructed data base, we set up an interpolatory metamodel which can be evaluated much faster compared to simulation runs.
An RBF metamodel RNpar→RM is a linear combination of radial basis functions fx= j=1Nexpφx-xjcj (2) with Nexp the number of simulations and coefficients cj so that the interpolation condition holds, which means that all simulated functionals (original data) are predicted exactly.
Donoho, High-dimensional data analysis: The curses and blessings of dimensionality, AMS Conference “Math Challenges of the 21st Century”, 2000, available from http://www-stat.stanford.edu/~donoho/
Skillicorn, Understanding Complex Datasets: Data mining with matrix decompositions, Chapman & Hall / CRC, 2007

All the data recorded under the application of the magnet were analyzed and compared with the same collected under identical conditions during conventional machining process.
From the FFT plots of the vibration data (samples shown in Fig. 2 & 3) two peak acceleration amplitudes are identified in the wide frequency range from 0-7,500 Hz.
Fig. 5: Percentage Reduction of acceleration amplitude due to the application of magnet Effect of cutting parameters on percentage reduction of acceleration amplitude.
To evaluate the influence of the individual machining parameters on percentage reduction of acceleration amplitude, single factor plots of the percentage reductions were generated.
The maximum reduction of acceleration amplitude was 73.43% and an average reduction of 31.58%.

RFNN Detection Model The RFNN detection model detailed as follows: firstly, establish the sample data table; secondly, use the rough set theory to reduce the condition attribute values; then extract rules from the decision table to determine the initial fuzzy neural network topology; finally, use the original data to train the network and adjust its structure, and thus the optimal maneuverable events detection model is obtained.
The Establishment of Sample Data Table Rough set theory is established on the basis of equivalence classes, the main idea is to use known knowledge base to approximately depict the inexact or uncertain knowledge[8].
Each discrete data sample in the table can be regarded as a rule, confidence level of the rule is defined as: (3) is the jth rule in the formula，.
If is the independent subset of , and , then is called the reduction of .
As experiments have shown that the proposed method can reflect the good topology of data characteristics, it has simple structures and fast learning rate.

Simulation results have shown that the proposed model has merit and agrees with published experimental data.
However, the results they got were deviated from the experimental data.
Therefore, modal reduction is practical when calculations effort and noise rejection is crucial, for example when the model is used for switch vibration control purposes.
Modal reduction is based on excluding modes with lowest Hankel norms [8].
The technique allows for modal-model reduction based on Hankel norms of individual modes.

Data are shown as mean ± SD of 4 replications (3 batches of plants for 1 replicates per treatment).
Data are shown as mean ± SD of three replicates.
After 12 days of Cd treatment, significant reductions were observed in Pn (Fig. 4A), Gs (Fig. 4B) and E (Fig. 4D).
By day 12, reductions in Pn were 57% and 35% in the mutant and wild type rice under Cd treatments, respectively, reductions in Gs were 49% and 29%, respectively, and reductions in E were 31% and 19%, respectively (Fig. 4).
Conclusions Cd reduced plant height, dry mass and chlorophyll content, and the reduction became larger with increased Cd exposure time.

The FEM was applied to analyze the multi-pass drawing process within six steps in total that started from 10.2% to 52.7% reduction ratio from the initial to the highest reduction sample.
While bearing area was 4.06 mm and reduction cone approximately 8.58 mm.
Furthermore, the input data of the simulation of drawing material is shown in Table 1.
It decreased as increasing the reduction ratio, but the hardness value showed a raised value on the higher reduction ratio.
The hardness showed a peak of around 323 HV on the highest reduction ratio.

Finally, by measuring the process parameters in rolling production site and applying the optimized rolling schedule to the rolling production, many test data are obtained.
Before the experiment, post strain gauge on the foothold of the mill, then connect the data wire with test instrument, and record test data by testing software in the rolling process.
Use probe and instrument on hand to measure the temperature of aluminum plate, then record the data on handbook.
In width direction, plate thickness data shown in Tab.3 were get by measuring the thickness every 15mm, then draw the crown curve, comparison of plate crown between curve calculated with crown model and curve drawn from thickness data above is shown in Fig.7, the difference is very little, and the most difference is 8μm.
The optimum reduction of economization on energy.

Results of the design analysis carried out using computer software are presented for boundary data complying with the currently operating state-of-the-art arc steel furnace.
Precipitation degree is determined for the dust participating in scull generation on a wall water-cooled surface and significant reduction of dust effect on electrodes.
Aerodynamic angle of high velocity and high temperature torch divergence was taken as per experimental data [14].
The stated parameters and the boundary data were used for two design analysis and remained constant.
At such gas circulation in the working space periphery reduction of the directed impact of combustion product flow on the inside water-cooled surface of the furnace wall is observed (fig. 5b).

The fatigue limit of a shape memory alloy composite determined the volume ratio and reduction ratio.
In this process, the important parameters are the volume ratio and reduction ratio of fiber.
The test was conducted at the reduction ratio (Rr) of 0%, 10%, 20% and volume ratio (Vr) of 0%, 5.2%.
Because of the scatter of fatigue life data at any given stress level, it must be recognized that there is not only S-N curve for a given material, but a family of SN curves with probability of failure as the parameter.
Table 1 shows the fatigue limit by the volume ratio and reduction ratio.