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A walk-through motor energy audit is carried out in a typical type of industry in Indonesia to collect some important data.
Data needed to estimate energy savings thus the payback period include: motor average usage hour, average electricity cost, motor efficiency under various load condition, incremental price for VSD, and average installation cost for capacitor per kVAR.
Several data including electricity energy consumption during a year, amount of sandals produced in term of tons, and monetary value of total sandals produced in a year are required.
Required data in terms of technical as well as operational and electricity consumption pattern is collected through a walk-through motor energy audit.
The important findings include a 10% reduction in total annual kWh exclude losses minimization getting from the installation of capacitor bank, a reduction on SEC and EI, and threefold on emission reduction obtained at least 47.13 tons of CO2.

Therefore, “energy conservation and emission reduction” has got to be significant.
In 2007, 2008, and 2009, the energy consumption per unit GDP of Wuhan is 12.6, 11.9, 11.1 thousand ton coal equivalent per ten thousand Yuan respectively, which are higher than the national average data, i.e. 11.6, 11.02, 10.77 year-on-year.
Then the ten expertises give grades to the current situation of energy saving and emission reduction on transportation in this city.
According to the values, the current situation of energy saving and emission reduction in Wuhan is evaluated scientifically and factually.
The total point of energy saving and emission reduction is 79.1085.

A data wrangling methodology is proposed to clean and organize the data for suitable analysis through Exploratory Data Analysis.
In the final stage of the analysis, an Exploratory Data Analysis (EDA) is conducted to summarize and visualize the dataset to identify patterns, trends, and relationships that may exist within the data.
Exploratory Data Analysis.
Data from the production system were processed, combined, and examined using visualization tools to help understand the data.
Drilling process monitoring: A framework for data gathering and feature extraction techniques.

Test Case Optimization Based on State Transition Reduction Xi Guo1, Jianyong Wang1,a 1Department of Computer Science, College of Science, Huazhong Agriculture University, Wuhan 430070, China awjy01@mail.hzau.edu.cn Keywords:status reduction, test case generation, predicate abstraction, equivalence class Abstract.Due to the large number of status transition of large scale software system, an efficient test case generation method based on predicate abstraction is proposed aiming to the problem of status space explosion.
System State Reduction and Equivalent Class As for the software system, the ideal test case should have a smaller size and satisfy the test requirements.
If one test case cannot satisfies every state in the equivalent class, then the above reduction rules should be used, and this process can reduce the scale of test cases.
Data flow testing as model checking.
On the completeness of a test suite reduction strategy.

In Copenhagen meeting, china set a clear goal for carbon dioxide emission reduction 40% -45%, which needs reasonable urban energy system planning.
Then calculates the carbon dioxide emission reduction by using renew Energy [7].
The energy consumption is based on the actual data of Tianjin Binhai New Area in 2008.
From above calculating data, by taking appropriate energy-saving measures and reasonable energy planning, the entire district can save standard coal 154742t, which is about 15.1% of the whole basic energy consumption.
to 1250598t. 2) Make full use of renewable energy on the basis of adopt some energy-saving measures, and the carbon dioxide emission reductions can be achieved for the 744070t. 3) As public and residential building is the focus of energy- saving, energy consumption can be significantly reduced after taking energy saving measures to the public and residential building that also have a greater contribution to CO2 emissions reductions.

The data recovery availability of the client is the main design goal of data dispersal algorithms.
According to technological details, there are mainly three design routines: data backup or mirror, data partitioning or data striping, erasure code et. al.
Data partitioning and Striping technology Data partitioning is to divide the original data into several segments, and store them on physically different storage devices.
Piece P: The original data D is partitioned into smaller data units with the same length.
Fragment F: It’s the atomic unit of redundant data.

This paper describes the technical problems for upgrading efficiency by core loss reduction on high speed motor.
These characteristic data is useful for magnetic characteristic analysis.
Design Technique – Vector Magnetic Characteristic Analysis In order to develop the high efficiency high speed motor, computer simulation technology is used for the design of core loss reduction by vector magnetic characteristic analysis as shown in Fig.11 It is very difficult to design the shape construction for core loss reduction on motor.
Fig. 12 Parameter for reduction of core loss.
Vector magnetic characteristics is useful and should be utilize for core reduction of motors.

The GO and rGO samples structure were indentified from XRD data and SQUID data for magnetic characteristics.
By evaluating SQUID measurement data, the magnetic susceptibility value of sample was determined and plotted as shown in Fig. 2.
XRD characteristic of GO sampel and rGO sample with various reduction times at 200 oC.
Magnetic susceptibility characteristic of GO sample (black circle) and rGO sample (red fill-circle) evaluated from FC and ZFC SQUID data in H = 500 Oe.
Magnetic susceptibility characteristic of GO and rGO amples versus χ/T from FC SQUID data in H = 500 Oe and temperatures below 200 K.

The success of these techniques is also affected by the presence of noise in experimental data.
The methodology is completely data driven; the evolution of the data is estimated without information of physical processes [12].
The data processing phase for damage detection will be discussed in this work.
Data processing Moving Principal Component Analysis (MPCA).
Dubes: Algorithms for Clustering Data, Prentice Hall (1988)

The measured data of CO, CO2 and waste heat expelling to environment were keeping the same, but actually they were low down when considering the total volume of inlet air diminished by 10%.
In this study, the average fuel consumption as well as combustion exhaust emissions will be measured, all positive effects of burning efficiency and emission reduction will be perceived from those related data.
The main purpose of this study is to confirm the reduction of fuel consumption after the spoiler was installed.
In order to let the measuring data have conjunction with real, the furnace with a light duty burner for zinc alloy casting is used.
When measuring the fuel consumptions for burner with different types of spoiler, the emissions including CO, CO2, O2, SOx, NOx and the tail pipe temperature are measured at the same time, from those data, the reduction of waste gas as well as waste heat emissions can be obtained to compare with the fuel saving trend for burners with and without installing the spoiler.