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In order to achieve the objective of this research, the following steps were taken: (1) Preparation/administration of questionnaires; (2) Data collection for a 5-year period (2002-2006); (3) Identification of performance measures from the information produced; (4) Plotting of Graphs and utility curves of the performance measures.
Data Classification and Analysis Data on production and maintenance activities obtained from 2002-2006 are: (1) Production Output; (2) Operating Time; (3) Downtime; (4) Total Maintenance Cost; (5) Planned Maintenance Hours; (6) Total Maintenance Hours.
The following performance measures were identified on the basis of available data: equipment availability, routine service worked, cost of maintenance hour, maintenance cost component, and cost of reduction.
Computation of Performance Measures The performance measures that were computed on the basis of available data obtained from the manufacturing company are (1) Equipment Availability (EA); (2) Emergency Failure Intensity Ratio (EFIR); (3) Cost of Maintenance Hour (CMH); (4) Routine Service Worked (RSW); (5) Maintenance Cost Component (MCC); (6) Cost of Reduction (COR).
Cost of Reduction (COR): The year 2005 shows a relatively good performance of COR.

Maximum Cr(VI) uptake of the biosorbent was evaluated to be 195.6 mg/g in this study (data not shown).
In this study, however there was no redox reaction between Cr(VI) and the biosorbent (data not shown).
When 1 mM of sulfate ion was added to the solution, the removal rate and amount of Cr(VI) by the biosorbent decreased significantly (data not shown).
Maximum As(V) uptake of the biosorbent was evaluated to be 62.3 mg/g in this study (data not shown).
In addition to the data of As(V) and Cr(VI), the removal behavior of Mn(VII) by the biosorbent was also examined.

Second, the HJ-1 CCD data and MODIS data are preprocessed and analyzed.
The geographic location of Taihu Lake Data Sources The data of the study were extracted from HJ-1 CCD on 13rd Aug. 2010, at 02:42 am (GMT), and from TERRA-MODIS of the same area 2 minutes earlier.
The HJ-1 CCD data were obtained from the National Disaster Reduction Center (NDRCC), and the MODIS data were provided by MODIS Data Receiving Station in Wuhan University.
Data Preprocessing Both of the HJ-1 CCD data and MODIS data were calibrated and geometric corrected respectively using the software ERDAS (version 9.1).
Thanks to National Disaster Reduction Center(NDRCC) for providing HJ-1 CCD data.

Challenges of Logistics Cost Reduction in China under the Background of Low-carbon Economy Logistics Cost Reduction is Facing Tremendous Challenges in China Because of Backward Technology.
Data show that the general fuel consumption of truck is up to 0.05kg / t, 8 times higher than water transport.
Therefore, water transport has a greater advantage in the reduction of transport cost.
Logistics information technology will use Bar Code Technology, Smart Cards, Artificial Intelligence, Automatic Identification System, Automatic Scanning, EDI (Electronic Data Interchange), EOS (Electronic Ordering System), INTERNET, GPS / GIS (Global Positioning System / Geographic Information Systems) and other support of information technologies to collect, process and analysis large quantities of information timely and effectively, and finally to achieve accurate, timely delivery, a steady supply chain and other objectives of low-carbon logistics management[5].
Obviously, the development of low-carbon reverse logistics plays an important role in energy conservation and emission reduction, which provides opportunities for logistics cost reduction.

The reduction rate is 39%.
Zhang Guangxue’s[2] test data showed that total suspended particles (TSP for short) emission concentrations is 66.87 mg/Nm3 from cement upstream kilns and 41.69 mg/Nm3 from downstream kilns.
Analysis on primary PM2.5 emission reduction from cement kilns and steel sintering machines In 2011, the production of cement clinker was 1.28 billion tons, and the production of steel was 695.5 million tons.
Table 4 The primary PM2.5 emission estimates from cement kilns and steel sintering machines in 2020 Unit: tons Industry Year cement kilns steel sintering machines In total 2020 313,500 135,600 449,100 2011 595,400 145,000 740,400 Reduction amount 281,900 9,400 291,300 Reduction Rate 47% 6% 39% As can be seen from Table 4: (1) For cement industry, when the backward kiln progress is eliminated, NSP is adopted, and the efficient PM removal technology is used, PM2.5 emission reductions are 281,900 tons, and the reduction rate is 47%, which is very remarkable
(2) For steel industry, when the backward progress is eliminated, and the efficient PM removal technology is used, PM2.5 emission reductions are 9,400 tons, and the reduction rate is 6%

Cell voltage was measured at different amperages by lowering amperage in steps and then plotting the voltage versus current data.
At every stage a waiting time of about 2 minutes was provided for acquisition of considerable amount of data by the system.
Figure 1: Cell voltage data indicating metal rolling with frequency < 0.1 Hz and amplitude 0.5 Figures 2 shows cell voltage and current data plotted with time during current sinking measurement.
Extrapolation of the voltage data to zero current for estimating Ve is plotted in Figure 3.
Theoretical value of counter electromotive force was calculated based on the plant data and given in Tables 2 and 3.

Abstract：In the face of climate change, city development should take into account the concept of energy saving and carbon reduction.
According to the average temperature from 1981-2010 meteorological statistics data issued by Taiwan's Central Weather Bureau, this study had calculated the warmest day & the coldest day as the time for simulation.
The green building rating System using four categories- Ecology, Energy saving, Waste reduction, Health (EEWH) and seven indicators include Greenery, Soil Water Content, CO2 Emission Reduction, Construction Waste Reduction, Water Conservation ,Sewage and Garbage Improvement form 1999 in Taiwan.
According to its average temperature from 1981-2010 meteorological statistics data, theaverage temperature range in summer is 23.3°C-24.8°C, winter 9.2°C-11.7°C; the average relative humidity(RH) is 80-90%.
Meteorological data: This research had used the data provided by Taiwan Central Weather Bureau from 1981-2010 to calculate the needed parameters for the research by Weather Tool of Ecotect Analysis.

The growth technique uses a modified carbothermal reduction at 900 °C to produce ZnO nanowires.
It employs reduction of the oxide material by carbon at certain temperature and transport the vapor to the substrates placed at the upstream of the tube furnace by carrier gas.
A computer with suitable software and program interface handled all controls and data acquisition.
Rapid mass production of ZnO nanowires by a modified carbothermal reduction method.
Investigation of Nucleation Mechanism and Tapering Observed in ZnO Nanowire Growth by Carbothermal Reduction Technique.

Taking advantage of the strong ability of RS theory in processing large data and eliminating redundant information, this method can remove irrelevant factors from the original fault data and reduce the dimension of processing data which helps to overcome fuzzy clustering algorithm's defect when process large database.
RS provides a series of tools for data analysis and reasoning from imprecise and ambiguous data[5].
Definition 2): Reduction and Core: In decision system ( , , , ) S U A V f= ,let b B∈ and B A⊆ , if { } ( ) ( ) B B b pos D pos D−= , attribute b is redundant to B, which relatives to D ,otherwise the attribute b is indispensable .If {} ( ) ( ) B B b pos D pos D−≠ , then B is called a reduction for information system S , are denoted as ( )RED A ; the intersection of these reduction sets is called core ,denoted as ( ) CORE RED A= ∩ Fuzzy Clustering Analysis Algorithm Cluster analysis is a multivariate statistical procedure that begins with a data set containing information about a sample of entities and attempts to reorganize these entities into relatively homogeneous groups[6].Clustering analysis is helpful when a researcher tries to classify or group data into categories or groups when neither the number of groups nor the members of the groups are known.
Clustering has been proven as a useful technique in exploratory data analysis when the sample is known to be non-homogeneous.
A CASE STUDY In this section, take the data of oil-immersed power Transformers fault diagnosis in reference as an example for illustrating our methodology.

., cjuntakantawîkun@yahoo.com Keywords: Vertical Green, Heat Gain Reduction, and Building Energy Code Abstract.
The data-logger connected to the thermo couple type k for measuring the temperature and humidity of ambient, the inside and outside wall, and the temperature of the front and back of the vertical green is set as in Fig. 1.
The air conditioners in both room and data logger is operated for 3 days to record the data.
From the recorded data, the equivalent plant conductivity under the assumption of steady state one dimension heat transfer can be calculated as Eq. 1, 2, and 3 respectively under the assumption of one dimension steady state heat transfer.
Efficiency of Climbing Plant in the Reduction of Heat Gain through Building Envelope.