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(1) We fill the absent ratings with a novel smooth method to address the problem of data sparsity
Experimental Evaluations Data sets.
There is a data set including 100,000 ratings from 943 users on 1682 movies.
The details of the three data sets are shown in Table 2.
The details of the experimental data sets Data set # of users # of movies #of categories # of ratings sparsity level TD200 200 500 9 6962 0.930 TD400 400 500 9 14317 0.928 TD800 800 500 9 22274 0.944 Evaluation metrics.

Data Acquisition.
In the step of data acquisition, we use Wacom's pressure sensitive tablet and pen to capture handwriting data.
Its main advantage is the reduction in computational complexity
The characters for each writer are stored in one data file.
Fig. 4 shows some examples of the numeric characters in the data set.

DD aims the reduction of transmission counts of data relay for power management.
The collected data is transmitted only if the collected data fits the query from the destination node, hence the power consumption of transmission is reduced.
The grade value is meaning how many numbers of the data relay from the current node to destination node when the current send the data.
If the number of the data relay is over 20 already, the data will be the loss.
Hence, the numbers of the data relay are more than 20 easily in the DD algorithm and its data loss rate is high than GD and LD algorithm.

This requires a large number of high-speed data acquisition and data buffering.
(6) When transferring data after the trigger point is set the amount of data to be transferred
(7) Set noise threshold for data averaging function, data can be limited when the average noise threshold, below this threshold at zero all the data records.
Responsible for the completion of data acquisition card collection, Use of data archiving command saves the current data txt format files.
The braking deceleration, where m is the width of the discrete interval (how much actual time interval represents the average rate of demand reduction).

Building energy efficiency is base for achieving green reduction and energy conservation is the key point to green building design.
A good assessment system will describe, in a quantitative and objective way, the impact on the environment, such as energy saving effect, water saving rate, greenhouse gases reduction, and at the same time provide evaluation on the ecological environment performance of "3R" materials and economic performance of a green building.
Data estimated by the relevant agencies of the United States of America shows that initial costs account for only 5-10% of the housing life cycle cost, energy consumption and maintenance costs account for 60-80%.

In the sample deposited at 1210 and 1268 K, high-temperature aging treatment at 1273 K for 10 h remarkably promoted the reduction of the strain tolerance.
The growth of thermally grown oxide (TGO) layer generated at the interface between topcoat and bondcoat layers was the principal reason for this strain tolerance reduction.
However, there are a few quantitative data concerning the strain tolerance of the TBCs [10]-[11].

A study on Heat transfer analysis and Experiment of Reinforced concrete columns using 500℃ Isotherm method In-Hwan, Yeo, a,Kyu-Jae, Hwang,bJae-Hong, Anc and Jong-Ho, Lee,d Korea Institute of Construction Technology, Republic of Korea ayeo@kict.re.kr, bhkjthink@kict.re.kr, crehong@kict.re.kr, dljh84@kict.re.kr Keywords:unstressed tests, axial load ratio, assessment of fire resistance performance, RC columns Abstract.This study aims to assess heat transfer analysis of RC columns and unstressed test by applying 500℃ isotherm method, which is the strength deterioration estimation method of Eurocode, inorder to use it as basic data for fire engineering design.
Also, it aims to evaluate strength alleviation of RC column members, which are exposed fire, in order to use it as basic data to establish fire engineering design system, by adopting the simple method described in Eurocode for the axial load ratio affected on column members.
Annex B of EN 1992-1-2, in which fire resistance design method is described, suggests a simple method, which can be easily applied, and use of data by experiments are available for.[1] Figure 1.
The analysis results of the adopted model of RC columns showed an error range of at least 0.2% but no higher than 20%. 2) As the distance from concrete surface grew farther 10mm to 45mm while cross-sectional size increased based on 3 hours of fire resistance time, temperature reduction effect occurred up to 53.2% and 56.2% respectively. 3) Axial load ratio was calculated through remaining strength ratio estimated by experiment and analysis results.

The final section of the paper presents the results of the experimental research, which are compared to data existing in specialty literature.
(2) Experimental measurements led to the following data: ; H-height of the water layer above the FBG; H=0.5 m; ro-inner radius of a nozzle; ro=0.25·10-3m; σ-surface tension coefficient of the water; σ =73·10-3N/m By replacing these values in relation (2), one obtains: (3) The pressure loss established experimentally was obtained for an air flow equal to =600 l/h; this pressure loss will be compared with data from specialty literature [12].
Environmental Protection Agency Office of Research and Development Center for Environmental Research Information Risk Reduction Engineering Laboratory Cincinnati, OH 45268, EPA/625/1-89/023, Design Manual fine pore aeration systems, September 1989

Based on multiple experimental researches the paper presents graphics and mathematical models obtained by data processing using modern software of wear dependence and cumulate thermal deformations according to the number of controlled number of pieces and dimension of the gauge.
Experimental results after 1000 pieces verified Pieces verified External diameter 25h6 [mm] 46.1h6 [mm] 52s6 [mm] 0 25.040353 46.10175 52.058748 50 25.041341 46.1038 52.058749 100 25.040955 46.10862 52.058628 150 25.042708 46.1038 52.058623 200 25.04131 46.10615 52.058745 250 25.040472 46.10007 52.058739 300 25.04309 46.1068 52.058803 350 25.0412 46.10878 52.058783 400 25.040962 46.1024 52.058803 450 25.040986 46.10862 52.058799 500 25.043789 46.10019 52.058793 550 25.042386 46.10387 52.05847 600 25.040802 46.10771 52.058869 650 25.043744 46.10967 52.058867 700 25.041163 46.10316 52.058857 750 25.043973 46.10708 52.058847 800 25.04124 46.10797 52.058843 850 25.041191 46.10985 52.058841 900 25.041266 46.10934 52.058885 950 25.041339 46.10956 52.058901 1000 25.041275 46.10998 52.058904 By processing the data from the Table 1 and by using specific software it was concluded the next graphical dependences, Fig.2, Fig.3, Fig. 4 and mathematical models of the wear and thermal deformation by
Logistic Model: y=a1+be-cx (7) Coefficient Data: a = 3.72256352808E-002 b = 2.38584671457E+001 c = 3.15144287703E-002 .
This methodology permits the optimization of the parameters values z1, y1 by taking into consideration the production plan against minimization of the gauges number, especially the shaft gauge, what gives reduction to the product cost by cutting down the gauges fabrication costs [6].

Engineers record their time and defect data on the time and defect logs.
At the end of the job, they summarize the time and defect data from the logs, measure the program size, and enter these data in the plan summary form, and deliver the finished product along with the completed plan summary form.
(2) Data gathering: In the PSP, engineers use data to monitor their work.
They gather data on the time, the size of the products and the quality of these products, and use logs and forms for recording
By comparing and analyzing the actual data and planning data, they check the gap between their actual work and plan, and update historical data such as program size, development time, development productivity, defect density and so on, and track software process improvement.