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In this algorithm, the signal subspace is obtained using MSWF, which avoids the known expected signal, the estimation of the virtual data autocorrelation matrix and eigen-decomposition.
However, it would decrease the virtually extended array aperture; it also needs to estimate the data autocorrelation matrix and eigen-decompose it, which involves a large amount of computational cost when the virtual sensor array is large.
According to the theorem 1 of [8], we know that if the cross-correlation between the observation data and the desired signal lies in the signal subspace, the signal subspace can be constructed by adopting the forward recursions of the MSWF: (4) To begin with, let (5) be the observation data and (6) be the desired signal.
Then the cross-correlation between the observation data and the desired signal can be calculated as (7) where .
Partitioning the observation data with the matched filter in a manner similar to that of the MSWF, we can obtain the desired signal and the observation data at the ith stage by (9) (10) Then the matched filter is calculated by (11) From (6)-(11), it is easy to prove that the matched filters are orthogonal to each other, so can form the signal subspace.

After data collection was done, it was analyzed by using descriptive statistics.
Two versions of self-administered questionnaires were used in data collection.
Data collection Data was collected from two parts both before and after formulation in capital district of Nakhon Pathom province.
Data was collected by self-administered questionnaire and analyzed using descriptive statistics.
SurveyResults General data of participants During 1st-15th November 2019, the data were collected from five distinct groups of total 30 participants which were tourists, dental patients, pharmacy students at Silpakorn University, office workers and dentists.

Local damages such as knots, d ecay, and cracks can be translated into a reduction of service life due to mechanical and environmental loadings.
These local damages result in reduction of system performance, structural safety and integrity.
It results in reduction of modal parameters such as natural frequencies, damping, and mode shapes.
Then the data were dumped from FFT analyzer to personal computer for post processing.

The decrease of the eutectic microstructures causes a reduction of the tensile strength.
Ten joints were measured under each test condition and the average of the maximum shear force was evaluated by the data except maximum and minimum values.
Reduction of ball shear force occurred due to the reduction of strength of the solder by aging.

Then, we discussed the economic efficiency of HDSG used for heavy oil recovery and concluded that although the pressurization of fuel and oxygen would cost as much as the energy saved by utilizing the flue gas heat, using HDSG for heavy oil recovery has other incalculable benefits such as miscible flooding, waste water treatment and reduction of heat loss through injection well.
From Wellig’s experiment data, we noticed that the extinction temperature had decreased to 81oC when using 28 wt. % methanol solution, but the inlet temperature of oxygen was set at 400 oC along all those experiments.
Reduction of heat loss through injection well.
Although the pressurization of fuel and oxygen would cost as much as the energy saved, HDSG using for heavy oil recovery have other benefits such as miscible flooding, waste water treatment and reduction of heat loss through injection well.

Temperature of concretion nucleation and binary eutectic reaction was increased after a reduction, whereas the time was presented dynamically, both the minimum value which were obtained at 715 ℃are 23.48s and 89.24s respectively.
Cooling curves was tested by K-type thermocouple, which was located in the center position of castings, test data was recorded by XSR 70 color paperless logger, the input signal is 4～20 mA and the recording frequency is 0.1s, as shown in the Figure 2.
Through the test results, it was found that in the filling temperature range from 750℃ to 715℃, cooling rates were rose constantly with the reduction of pouring temperature, the peak point which was emerged at 715℃ is 5.93℃/min, along with a decline to 4.23 ℃/min at 705℃ subsequently, the changing trend of cooling rates with the pouring temperature from 705℃ to 675℃ is mimetic as the circumstances discussed above, the maximum value is 5.24℃/min, which was attained at the pouring temperature of 675℃, as shown in the Figure 8.
Through the analysis of mathematical formula, it was found that with the reduction of pouring temperature and binary eutectic reaction temperature, followed with a ascension of cooling rate and solidification nucleation temperature, the grain size was decreased successively.

The maximum reduction in OTR and WVTR of that nanocomposite film with Perkalite loading of 3 pph are 76% and 37%, respectively compared with neat PLA film.
Data were recorded in 2θ range of 2-30˚ at the scan rate of 2˚/min.
Fig. 4a and 4b show that increasing content of Perkalite clay from 1 to 3 pph led to a reduction of bubble phase (PEG phase) appearance.
This is due to the fine particle of Perkalite clay was well dispersed in PLA matrix causing a reduction in PEG phase appearance.

Initial preprocessing facilitates the classification task by reduction the number of data classes either by removing not relevant classes, or by making particular classes more concise in the multidimensional input data space e.g. by noise removal.
All neurons have common inputs, whose number, n, forms a n-dimensional data space.
Such model is suitable for analysis of complex data like for example the biomedical signals.
Example training data files.
Three example data files are shown in Fig. 2.

In this control unit data is classified and the best decision will be made based on the received data.
Data transfer by this model takes place via internet or GSM.
Observing and collecting data 2.
Decision making Observing and collecting data.
Also vehicles’ data is being updated continuously and finally all data is recorded and it is ideal for officials since they can access to full and precise data about owners of vehicles.

The main result of the implementation of this proposal is the improvement of productivity based on the reduction of the total picking time of 22.38%.
The main result is a reduction of the total retrieval time by 40% [32].
In the pilot study, a score of 93 points was obtained, which improved the initial of 29. 2.3 Demand forecasting The data considered for the demand prediction covers the company's customer market, mainly spare parts for mining projects, which are located in Peru.
However, this does not represent more than 3 minutes of variation, unlike the activities mentioned above, which had a reduction of up to 54 minutes.
Singh, Warehouse optimisation using demand data analytics - A case study-based approach, International Journal of Business Information Systems, 35(4) (2020) 519-538