Search results

The Kalman filter can be applied to remove noise or artifacts without affecting other crucial data [12] [13].
Numerical data analysis and computation are done with this application.
The Kalman filter is used to eliminate distortions and noise from a signal without compromising other crucial data.
The Kalman filter is capable of foretelling and examining relationships between various sorts of data.
Zhao et al., “Localized Motion Artifact Reduction on Brain MRI Using Deep Learning with Effective Data Augmentation Techniques,” Proc.

Sequentially, the COD reduction data efficiency includes B 20% (88.65%), L 20% (84.2%), A 10% (80%), A 20% (79.92%), ABL 10% (72.3%), B 10% (25.67%), ABL 20% (-10.87%), with the greatest efficiency occurring in the L10% treatment at 89.76%.
COD Levels Data.
The data presented, shows that an increase in graphical data corresponds to a higher percentage reduction in COD levels, while a decrease in graphical data, corresponds to a lower percentage reduction.
Overall, the data graph shows different COD reduction data, with some data experiencing a significant decrease and others showing no significant decrease.
Based on analysis data from the 16S rRNA gene sequence, it was discovered that the third isolate used isolates A, B, and L, was identified as Alcaligenes ammonioxydans.

X-ray diffraction (XRD) data of AuNi alloy was acquired by a Bruker D8 advanced X-ray diffractometer using Cu Kα1 radiation (λ = 1.5406 Å) at a step rate of 0.02 °/s.
Compared with the fcc Au data (JCPDS, No. 4-0784), the diffraction peaks shifted to higher 2q values.
These data were agreement with the initial compositions of Au and Ni.
Methanol tolerance is an important criterion for selection of cathode materials for the DMFCs, which can be determined by comparing the data obtained from the solutions with and without methanol.
The sample data for plotting were taken from Fig. 4c at the potentials of -0.6, -0.7, and -0.8 V, respectively.

Therefore the isolation technology for high-rise structure also has better reduction vibration effect.
Test Data Analysis Acceleration time history analysis.
Due to sensors placed the top failed in test, the data collected were abnormal amplification, so they are not in the table.
Layer displacements of model structure concentrated in the isolation laye mostly, it is consistent with principles of isolation and reduction vibration.
Therefore, the isolation technology for high-rise structure also has better reduction vibration effect.

As one cycle sampling has accomplished, arrange the sampling data according to the sampling order the digitization data is obtained [4], as showed in Fig. 1.
Both processing is the function of data processing unit.
In addition, AD9480 also outputs a synchronous clock DCO + and DCO-, which can be used to expand bit wide of LVDS outputs 250MH data stream and achieve frequency reduction.
Differential ADC data transmission and processing technology greatly improves the reliability of data transmission and processing.
High Speed Data Acquisition System Designed for Lidar.

When the data are linearly inseparable, a non-linear kernel that maps the data into the feature space non-linearly can handle the data better than the linear kernels.
The computer assisted screening dataset for lung cancer is a large data set.
The data set has 53,200 training data points and 81,260 testing data points, each record has 24 attributes.
Fig. 3(b) shows “training time” vs “training data size”.
On the basis of this framework,it is more suitable for classification of large data sets.

With the data of Jiangmen as objective, this study investigates driving factors of Jiangmen’s CO2 emission using STIRPAT model that is effective in environment pressure studies.
Since carbon emission statistical data is deficient, the current carbon emission state of Jiangmen is mainly analyzed by the energy data in 2011 statistical yearbook.
Original data is in J unit.
To be consistent with statistical data, energy unit is converted into standard coal.
The STIRPAT model based on ridge regression The original data used in the calculation of each factor of Jiangmen are mostly derived from Jiangmen statistical yearbook over years.

Drag is usually an undesirable effect and the reduction of drag is associated with the reduction of pumping power requirement in transporting system.
They also suggested that not all drag reduction surfactant caused by viscoelastic since they found drag reduction as non-viscoelastic drag reducing surfactants.
Experimental procedures The pressure drop data in the pipe for water before the addition of anionic surfactants are initially used in the calculations of the drag reduction in which the drag reduction in the pipes is defined as: 1001(%) Reduction       −= b a ∆P ∆P Where ∆Pb and ∆Pa is the pressure drop before and after the addition of the surfactant solution.
At the highest concentration as 600 ppm, the lowest drag reduction was obtained are 4 % at Re = 78645 and the highest drag reduction was obtained are 8 % at Re from 44940 to 56175.
In 400 ppm, the lowest drag reduction is 3 % and the highest is 4 %.

Because the vibration signals of the centrifugal fan contains a variety of complex signal noise.Effective extracting fault vibration signal characteristic information is a prerequisite for correct diagnosis.With the development modern signal processing and analysis technology, more and more fault information needs to be extracted.How to choose the most effective fault characteristic is an important and difficult problem to solve[1].MLM is a kind of reduction method of nonlinear data dimension[2~3].It can effectively find links and regularity of high-dimensional data and fully exploit the data of useful information and features.
Typical fault vibration of centrifugal fan The experimental data from the Huadian Electric Power Research Institute of Fluid Machinery Laboratory.
Feature extraction of centrifugal fan vibration Manifold learning is such a dimension reduction tool, that can be saved under the condition of nonlinear information to compress feature information.In this paper, experimental results for the raw data, these samples will be treated as an input LLE algorithm.Embedding dimension were taken as 1, 2, 3, 4 learning and studied.
Format learning samples and make the classifier for training. 20 sets of data extracted from the characteristics of each sample in a failed state after completion of training.
Nonlinear dimensionality reduction by locally linear embedding [J].

With the rapid development of the motion capture technology, MoCap data are constantly accumulated.
Above all, they are very robust to variations in the motion capture data stream.
Dimension reductionbasedmotion retrieval MoCap data are very high dimensional data both in the spatial domain and in the temporal domain.
SOM.Self-Organizing Map (SOM) is a kind of dimension reduction technique for the visualization of high-dimensional data.
PCA-based walking engine using motion capture data[C].