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From the mud rheology test, it was found that the specific gravity does not affected by the increasing concentration of apple skin and only a slight reduction in pH value to the acidic condition of the apple skin.
Introduction In petroleum exploration and development, drilling activities have been identified as the main activities which are performed in order to obtain information and data from the field of interest.
This data matched with the filtrate volume data and it can be concluded that the filtrate volume was also reduced due to the increase thick of mud cake accumulation.

Due to the original data contained many interference data from measurement system, such as the noise of the environment and interference signals from data transfer process.
This algorithm is a kind of independent learning methods, reducing the data dimensions and realizing data visualization.
This algorithm has the ability to handle incomplete data.
The real-time data measured by sonic information of Power transformer belongs to high dimensions, and the relation of these data and transformer fault types is non-linear.
Therefore the data become more complex and the dimension of data becomes larger.

In section 4, application to bearing fault data will be presented.
Data set A consists of 320 data samples of four different operating conditions with the fault defect size of 0.007 inches under four various loads (0, 1, 2 and 3 hp), where each of four operating condition includes 80 data samples.
Data set B also contains 320 data samples.
Data set C comprises 800 data samples including three different defect sizes of 0.007, 0.014 and 0.012 inches under four different loads.
Table 3 gives the classification performance on various data sets.

The main terms used are: · “undamaged data” – refers to Lamb wave responses acquired from the undamaged plate; · “damaged data” – refers to Lamb wave responses acquired from the damaged plates (1, 3 and 5 mm hole); · “undamaged data on undamaged data” – means projecting the “undamaged data” on the cointegrating vectors obtained from the “undamaged data”; · “damaged data on damaged data” – means projecting the “damaged data” on the cointegrating vectors obtained from the “damaged data”.
It is important to note that the same “damaged data” was used in creating cointegrating vectors as well as in projecting data, e.g. projecting “1 mm hole” data on the cointegrating vectors obtained from the “1 mm hole” data.
Fig. 1a shows the results for the “undamaged data on undamaged data” projection case for the undamaged plate.
Fig. 1b shows the results for the “damaged data on damaged data” projection case for the damaged plate with 5 mm hole.
Damage introduced into the plate caused this stationary reduction.

But it’s difficult to get such data traces since network traffic data is very privacy-sensitive, especially when it contains payloads or IP addresses.
Identifying the true-positive anomalies requires combing through vast amounts of data that are sometimes of poor quality due to data-reduction techniques such as sampling.
A researcher might wish to (1) verify published results by evaluating the same algorithm on the same data, (2) investigate the robustness of a published algorithm by applying it to different data, or (3) compare a novel algorithm against the published one by using the same data.
Data traces Data traces with manual labeling or attack traffic injection can be directly used for evaluation of anomaly detectors.
Therefore, anomalies in the data were identified using available manual labeling methods: visual inspection of timeseries and top-n queries directly on the flow data.

The literature adopts the scoring matrix dimension reduction technique to improve the data sparsity, but the method has higher time complexity in some large-scale recommendation systems.
The data set scoring data structure is shown in Table 1. 3.2.
The experiment adopts the five-fold cross-validation method, randomly selecting of the data set as the training set andof the data as the test set.
The filled data set are shown in Table 2.
Data Analysis and Knowledge Discovery, 2018, 2(6):102-9

The results of local electron density calculated using positron annihilation data show that the local electron density of the systems is strongly changed by the Fe doping, and the local electron density vary noticeably at the range of O-T phase transition.
It can be seen from the XRD data that all samples have a single phase of orthorhombic structure.
When the doping content is so high (x ≥ 0.15), the Cu(2) in CuO2 plane will be substituted by Fe ion. on one hand, the number of clusters in Cu-O chain region increases[12], because oxygen cannot meet the coordination requirements, oxygen vacancies are increasing; on the other hand, some Fe3 + ions doped to the Cu (2) position, will increase oxygen vacancies in the CuO2 plane as well, can also cause reduction of valence electron density of the CuO2 plane.
The results of local electron density calculated using positron annihilation data show that the oxygen deficiency density of the systems is strongly changed by the Fe doping, and the positrons annihilate mainly around the Cu-O chains at low doping level, the positrons annihilate mainly around the CuO2 planes at high doping level.

The cutter location point data is the original data that generates the NC trajectory and the precision of the part is determined significantly by the distribution accuracy of the cutter location point.
Table3 shows the key cutting parameters and key data for the milling experiment.
As can be seen from the test results in Table 4, the reduction of the tool-path interval can reduce the roughness value.
R1-R3 are three tool-paths consisted by the location data, whose sampling points are P1-P6.
After statistics, the maximum error between the optimized tool position data and the coordinate measurement data is 0.0033mm, and this error is less than the maximum error required for surface shape requirements 0.005mm.

With proper design strategy, these materials offer a great opportunity for both weight reduction and crashworthiness.
Geometrical data of the crack propagation test Table 2.
Geometrical data Value [mm] Plate length a 10.0 Notch radius RC 1.0 Upper notch radius R1 2.0 Lower notch radius R2 2.5 Split Hopkinson Tension bar simulation The second example is a Split Hopkinson Tension bar test, smooth or notched.
Results are compared with experimental data and with numerical results obtained with the explicit LS-DYNA code as presented in [4].

It is evident that little rainfall could bring forward water shortage of soil which restrained the growth of plant and eventually caused the reduction of crop yield.
Based on the updated landuse data of the research area, statistics have been carried out according to 7 types of landuse, namely dry land, paddy field, forest land, grassland, water body, bottomland and construction land so as to analyze and evaluate the effect of drought and its factors.
Firstly, the drought situation, the happening characteristic of disaster could be analyzed based on the data of hydrology, meteorology, agriculture, social economic and history data concerning drought disaster in NWLN.