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Methodology The methodology is divided into several stages includes preliminary stage of study, data collection and analysis, discussions and conclusion.
The review from the PLUS Expressway record on energy consumption for the energy usage had been carried out.The data collection is in the form of questionnaire survey.
All the data from questionnaire survey is analysed using SPSS (Statistical Package for the Social Sciences) software.
From the data gathered, the potential retrofits to reduce energy consumption at the RSAs have been identified.
USA: Reed Construction Data (2006)

The Optimization of Calciothermic Reduction-Diffusion Process for Preparation of High-Performance Sm2Fe17Nx Magnetic Powder J.
Calciothermic reduction-diffusion (CRD) method was employed to prepare the Sm2Fe17 powder.
Different processes such as melting [1], mechanical alloying [5], calciothermic reduction-diffusion (CRD) [6-8] have been used for the preparation of the parent Sm2Fe17 alloy.
This result indicates that complete reduction of samarium oxide by calcium took place and the whole iron reacted with the samarium to form the Sm2Fe17 phase without forming undesirable phases such as α-Fe and SmFe3 which is difficult to completely remove by melting method [1,6].
The data shows that the coercivity and residual magnetization of the powder are 0.12kOe and 13.7 emu g-1.

The data in Table 1 show that Reynolds number Re < 2300 in the main vessels, where all flow is laminar, with only weak turbulence possible at small structures in the wall or at vascular lesions.
As can be seen from the data in the table, when the number of grids reaches 479248, the error between the numerical simulation results and the theoretical value is approximately 3.3%.
Comparison of drag reduction rates of three micro-structure grooves 3.2 Analysis of Model Drag Reduction Effect.
The authors confirm contribution to the paper as follows: study conception and design: Wenting Wang, Yunqing Gu; data collection: Wenting Wang and Lingzhi Yu; analysis and interpretation of results: Lingzhi Yu, Wenting Wang, Zhuofan Yin; draft manuscript preparation: Wenting Wang, Zhou Li; methodology: Denghao Wu, Shuihua Zheng; resources: Jiegang Mou.
F., Bock, J. et al. 3D MR flow analysis in realistic rapid-prototyping model systems of the thoracic aorta: comparison with in vivo data and computational fluid dynamics in identical vessel geometries.

The reduction jar, as a core device of the reduction furnace, has many disadvantages, such as easy to wear, short service life, and high cost accounting for about 25% of the total cost[4].
The thermodynamic data of the reactants and the resultants in Eq. 1 can be referred in relative data manual[21].
Reduction Reaction by Adding SiO2.
[16] Hongxiang Liu, The experimental research and the equipment test of reduction magnesium by vacuum-aided carbothermal reduction, Dissertation of Kunming University of Science and Technology, Kunming, 2008
[21] Ihsan Barin, Thermochemical Data of Pure Substance, Science Press, Beijing, 2003

The development of seawater batteries has constraints on oxygen reduction reactions in the battery discharge process that runs slowly.
Based on research data, N and Fe doped carbon aerogels have better seawater battery performance than N-doped carbon aerogels without Fe.
Slow oxygen reduction reactions must be resolved by using an electrocatalyst to improve the performance of seawater batteries.
The Fe3O4 was used as an electrocatalyst of oxygen reduction reactions [12], [13].
Jiang, “Recent progress of electrocatalysts for oxygen reduction in fuel cells,” J Colloid Interface Sci, vol. 607, pp. 791–815, 2022, doi: 10.1016/j.jcis.2021.09.008

Transcription of the X-ray patterns was made using the PDF data base [8].
According to the differential thermal and mass spectrometric analysis data (Fig. 3) when heating the ore at a rate of 10 °C /min in argon flow a weight loss of the sample (TG data) had already appeared at the initial stage of heating and came up to 12.2 % at 1100 °C.
Thermogram (argon, 100 C/min,) ore and mass spectrometric analysis of waste gas data.
The experimental data obtained for the ore sample under the study correspond to those presented in the literature [23].
Diffusion and Defect Data.

Energy Flow Analysis and Energy Conservation and Emission Reduction in Sichuan Province, China LIU Wei*, FENG Xiyu, HUANG Guan, HUAN Hanqing Chengdu University of Information Technology, Chengdu 610225, China E-mail: weling9@163.com Keywords: energy flow analysis; energy conservation and emission reduction; scenario analysis; Sichuan Province Abstract: Based on the relative data and materials, the energy flowchart of Sichuan province in 2008 was drew at first, then the energy input, output, consumption, corresponding pollutants emission of Sichuan province from 2000 to 2008 were analysed simultaneously.
Finally, suggestions of energy conservation and emission reduction in Sichuan province are proposed.
How to optimize the regional energy flow and how to implement energy conservation and emission reduction has become the urgent work.
(3) Optimizing energy consumption structure, accelerating technology research and develop of energy conservation and emission reduction
(4) Strengthening the energy conservation and emission reduction of transportation sector and building sector.

First, we got the data from the database, transformed the corresponding decision table, then got the data in decision-making table for further simplification, generated the final decision rules. and got good results, experimental results showed that the method provided some practical value.
Customer Classification Model Construction Data acquisition The initial decision table method using NS discrete discrete data: where, D = {d} is decision attribute set, said the types of customers, divided into 3 categories; 1 Gold customers, 2 for Silver customers, 3 copper Card.
Get customer attributes discretization results: Table 1 The initial decision table U a1 a2 a3 a4 a5 d X1 3 1 1 2 1 1 X2 3 1 1 2 3 2 X3 3 2 1 2 1 1 … … … … … … … X8 2 1 2 2 2 2 X9 1 1 3 1 1 1 X10 2 3 1 3 1 1 Attribute Reduction of Decision Table Improved attribute reduction algorithm based on logic operations Demand reduction algorithm： get DNF by conjunctive above expression : By logical operation converte disjunctive to CNF That is to say: For, First calculate,get， so valueis necessary.
Similarly, get overview Table of Value Reduction Table 3 Overview Table of Value Reduction UOB a2 a3 a5 d X1 — — 1 1 X2 — 1 3 2 X3 — — — 1 … … … … … X8 1 — — 2 X9 1 — 1 1 X10 — 1 — 1 Get from Table 3： (1) In terms of decision rules: , first consider for decision rules ,whether it is necessary relative to D (whether as the core values)?
References [1] Wang Xing, Niu Yugang, rough set theory based on customer relationship management, Shanghai: East China University of Information Science and Engineering, 2008 [2] David Hand, Heikki Mannila, Padhraic Smyth, Principles of Data Mining, Machine Press Society, April 2003 [3] He Rongqin, CRM principles, design, practice, Electronic Industry Press, January 2003 [4] Newell, Frederick.Loyalty.com: Customer Relationship Management in the New Era of Internet Marking.New York: McGraw-Hill, 1999 [5] Wang Biao, Duan Lun Chan, Wu Hao, Song Yonggang, rough sets and fuzzy sets and its application, Beijing: Electronic Industry Press ,2008,59-62, 1-2, 2 -6,172-173, 8-10

The vibration amplitude data for the two conditions were compared to identify the influence of magnet on chatter reduction.
In the present paper a novel chatter control method has been tried for reduction of chatter in turning.
The software FFT module was used to obtain the frequency data from the time domain input.
For the remaining runs there were different degrees of reduction due to magnet application, however, the average of all the reduction is 49.44% or approximately 50%.
Experiment with magnet provided a maximum and average reduction of 87% and 50% respectively. 2.

Porosity Defect Reduction Reduction of Gas Porosity.
Cycle Time Reduction.
Fig. 6 shows the property data of 226 alloy as a representative.
Strength and elongation data of the 226 alloy produced by SDC and GISS processes.
Other benefits such as the cycle time reduction of 16%, rejection reduction to about 1%, energy reduction of 18%, and die lube reduction of 73% have also been reported.