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For grain interior measurements, a load of 200 g was chosen, and each datum point referred to an individual grain.
For grain boundary measurements, a load of 50 g was used, and each datum point referred to different grain boundaries.
In contrast to this, the Dy-doped NiAl alloys show apparent reduction in the grain size.
Each hardness value is based on the average of 10 datum points.
However, over-doped sample (0.5Dy doped case) led to reduction of hardness.

Results The experimental data of mechanical and physical performance of all studied ACC specimens are presented in Table 1.
The characteristics of ACC specimens during autoclave treatment: 1 – compressive strength; 2 –density; 3 – carbonation degree In accordance with the data (Fig. 1) the intensive carbonation for all ACC specimens was observed over first 2 months followed with concurrent increase of density.
The reaction product of carbonation can lead to reduction of mechanical performance [22, 23] as was observed in this study.
However, all the studied compositions did not exceed the limit of strength reduction of 25 % recommended by standard [].

Among them, Prussian blue nanoparticles (PBNPs) have been increasingly noted in the field of mimetic enzyme, it is usually considered as an “artificial enzyme peroxidase” because of its high surface activity and selectivity towards the reduction of hydrogen peroxide and oxygen, it has been extensively used in the construction of electrochemical biosensors [4-5].
Catalytic parameters were determined by fitting the absorbance data to the Michaelis–Menten equation as equation (1), which describes the relationship between the rates of substrates conversion by PB-Ft NPs and the concentration of the substrates
The data were fitted to the Michaelis–Menten model to obtain the parameters (Table 1).
[3] Susan Boland, Frederic Barriere and Donal Leech, Designing Stable Redox-Active Surfaces: Chemical Attachment of an Osmium Complex to Glassy Carbon Electrodes Prefunctionalized by Electrochemical Reduction of an In Situ-Generated Aryldiazonium Cation, Langmuir24(12)(2008), 6351-6358

A retro-reflecting marker was placed on each accelerometer and the parameters used for filtering both the accelerations recorded by the accelerometers and the displacements recorded by the 3DVision were calibrated by comparing the data provided by the two systems in the same points.
A slight reduction of the stiffness can also be observed in the horizontal bending response for the last test (Fig. 4a), which could be associated with the development of concentrated damage in the upper portion of the façade subjected to the forces transferred by the roof.
The shape of the response curves also indicate that damage progressively accumulated with a gradual reduction of stiffness and without sudden ruptures, suggesting that the retrofitted structure may exhibit some energy dissipation capacity.
Roselli, Passive 3D motion optical data in shaking table tests of a SRG-reinforced masonry wall, Earthq.

DTs and WAMS Principles The DTs technique is an effective supervised data mining tool to solve the classification problems in a large database.
This approach served the industry well but lacks the ability of observing measurements across the whole system because the data was not time synchronized.
Entropy is a measure that enables to compare attributes with each other and then be able to decide to put ones that split the data more purely higher up the tree.
This probability measure gives us an indication of how uncertain we are about the data.
The approach (Fig. 2) to constructing decision trees usually involves using greedy heuristics, Entropy reduction (7), that can over-fit the training data and can lead to poor accuracy in future predictions.

Step 4-Data collection.
In this step, all of the data regarding the selected elements and sub elements must be gathered.
In this research, these data are gathered from different reliable sources such as experts’ opinions, lifecycle inventory of Portland and slag cement concrete, and existing data in the literature[9-12].
The data shown in Table 2 and Table 3 are gathered from the reliable sources in the literature [9-12].
Input data and ranking of color, initial time set and energy saving percentage Process type Input data for color Input data for initial time set Input data for energy saving percentage Type 1 4 1 1 Type 2 2 3 3 Type 3 1 4 4 Type 4 3 2 2 Table 3.

In the project, the team assumes the reduction of the percentage of nonconformities, from 1.67% to 0.87%.
Information was gathered with the help of a “Scrap part sheet” which contributed to having actual and trustful data. 1.
The data collecting staff was previously trained. 2.
Measurement lies in collecting “historic” data, previously acquired, going on during the project running with the collection of “present” data.
Data should be relevant and in a sufficiently large amount to lead to proper conclusions.

Experiment Method Data collection.
It's crucial for feature extraction, data redundancy reduction, and model accuracy.
Xscaled is the normalized data.
The dataset was split into train data and test data using the train-test-split method (ratio, 8:2).
The bar chart in Fig.3 illustrates the average R2 values of these models on both the train data and test data.

Design of the system consists of three layers C/S (client/Server) framework. and its system structure is shown in figure 1 .The data center control system is the core of data processing system, and exchanges data with the remaining subsystem.
e) data local-storage The system will store traffic records in the local storage to avoid data lose when network disconnects occasionally .If network disconnects temporarily, it can store data temporarily in local and make a logo, when network connections go back to normal that will put these data that are not uploaded to upload to the data center again .
System log data are stored in local and are sent to data center when while network connection is normal.
Camera video data will also be in the local store [6], the data received from data center will also save in local.
f) data interaction Data exchange is done between ETC system and data center.

The sampled data were then analyzed with the method described in Chapter 3.
Then a filtering process was done for reduction of disturbance by use of the phase difference of the data from two microphones, and the relationship between the data from two microphones was analyzed.
Next we describe the related evaluation on power spectrum for data comparison.
Here the distribution of standard deviation and average value are made into graphs by assuming that the related values for same conditions (normal data-normal data, and wearing data-wearing data) and those for different conditions (normal data-wearing data) follow the normal distribution.
Areas demonstrated by dotted line indicate the data with 95.4% reliability.