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As illustrated in Figure 1 that how these objectives are connected with more widely accepted measures for car travel reduction [17].
Figure 1: The role of park-and-ride in car travel reduction [17] Factors that influence choice of travel mode.
Although, discrete choice models can be established on either observed behavior (Revealed Preferences data) or on hypothetical choice surveys (Stated Preference data).

The results were compared with experimental data for some cases such as vertical plate and horizontal circular cylinder, the agreement was excellent.
Good agreement with other experimental data was achieved.
The stream function (y) and vorticity (w) in the governing equations are defined as follows, Anderson [10] and Petrovic[11]: (6) (7) Or The stream function formulation satisfies continuity equation and substituting these in equation (1) yields: (8) By suitable manipulation, the pressure terms in the governing equations may be eliminated, yielding: (9) (10) In the stream function-vorticity formulation, there is a reduction in the number of equations to be solved in the y-w formulation, and the troublesome pressure terms are eliminated in the y-w approach.
Decreasing the enclosure width reduces the convergence time of Nu and mass flow rate due to the reduction in the enclosed mass and hence inertia within the enclosure.

Further the reduction of accrual of body weight, reduction of food intake and decline of red cells were proved [8,9,10]. 1.2 Advanced oxidation processes Processes involving the use of ozone, UV radiation, and hydrogen peroxide, characterized by the generation of short-lived chemical species of high oxidation power, mainly the hydroxyl radical (•OH), are classified as advanced oxidation processes (AOPs).
undecanal 7,117 2000000 184 6175-49-1 C12H24O 2-dodecanone 7,277 1100000 184 112-54-9 C12H24O dodecanal 7,418 1400000 200 1731-86-8 C12H24O2 Methyl undecanoate 8,260 200000 198 1534-26-5 C13H26O 3-tridecanone 8,551 1900000 198 10486-19-8 C13H26O tridecanal 8,711 350000 214 111-82-0 C13H26O2 methyl laurate 9,910 1200000 212 2345-27-9 C14H28O 2-tetradecanone 10,380 1700000 228 1731-88-0 C14H28O2 Methyl tridecanoate 11,476 210000 187 6190-65-4 C6H10ClN5 desethylatrazine (DEA) 12,402 200000 242 124-10-7 C15H30O2 Methyl myristate 14,006 300000 188 1719-06-8 C14D10 anthracene-D10 (1µg l-1) 14,156 450000 240 18787-63-8 C16H32O 2-hexadecanone 14,612 260000 208 unidentified compound m/z 70, 208 14,768 700000 256 7132-64-1 C16H32O2 Methyl pentadecanoate 16,056 230000 229 83364-15-2 C8H12ClN5O 2-chloro-4-acetamido-6-(isopropylamino)-s-triazine (CDIT) 21,290 150000 270 506-12-7 C17H34O2 Heptadecanoic acid 24,948 25000 312 74484-77-8 C20H40O2 methyl 11-methyloctadecanoate On the base of measured data
WHO/FAO Data Sheets on Pesticides No. 82 : Atrazine [online].

Nutrients The required concentration [mg/L] N2 6 (on 1000 COD) P 1,25 (on 1000 COD) Mg 10 Fe 2 Mn 0.150 Co 0.060 Mb 0.050 Ni 0.050 Se 0.010 Summing the intermediate results, it should be noted that there are following things to create granules of activated sludge and to have a high degree of cleaning effect: • the temperature is about 30 °C; • pH ≅{TTP}8773 7,0; • the content of Ca2+ in the wastewater is optimally 100 mg/L; • decrease the residence time of wastewater in the reactor for obtaining methane; • a sufficient amount of nutrients (mainly nitrogen and phosphorus); • reduction of suspended solids (sand, clay, diatomaceous earth) in the incoming waste water.
Table 5 presents critical content data of toxic components.
Due to the resulting gas it is reduction of organic matter.
Bezrukih, Spravochnik po resursam vozobnovlyaemyh istochnikov energii Rossii i mestnym vidam topliva (pokazateli po territoriyam) [Handbook of renewable energy sources in Russia and local fuels (data about areas)], IATS Energiya, Moscow, 2007

The SHPB with a high-strength silver steel rod diameter of 12 mm and striker bar, incident bar, transmitter bar, testing sample, and data acquisition system was set up.
Finally, the signals were transferred to the computer for data processing.
By contrast, a systematic reduction in strength is observed with the increase in FRA replacement percentage above this level.
The rate reductions in comprehensive strength are approximately 15%, 17%, and 35% for samples R50, R75, and R100, respectively, when compared with the reference sample.

The data from XRD is then analyzed by using Expert High Score Plus.
Table 4 is the tabulated data of response (percent crytallinity).
Saiyid Hashim, Bamboo sawdust as a reduction agent in leaching applications: Characterization studies, vol. 620. 2013
Saiyid Hashim, “Bamboo Sawdust as a Reduction Agent in Leaching Applications: Characterization Studies,” Adv.

In the past, data-based prediction models for Ec’ of concrete were difficult to obtain due to the lack of large data sets in the available literature, in addition to the lack in efficient prediction models.
Methodology and Methods Data Collection and Preprocessing.
Standard deviation and mean values of Ec’ data are 8.52 and 35.74 GPa, respectively.
Data Availability Codes, models and collected data in this study are available upon request from the corresponding author.
Data set of approximately 200 experimental concrete Ec’ results were collected from the literature.

Aiming at the phenomenon of generator air gap magnetic potential asymmetry and effective fundamental magnetic reduction after the fault, paper [7] has calculated the unbalanced magnetic pull force by rotor winding inter-turn short circuit fault.
In order to accurately calculate the unbalanced electromagnetic force by the rotor winding inter-turn short circuit fault, this paper proposes to analyze generator magnetic field by finite element method, and magnetic field data before and after failure is got by accurate calculation, and further the unbalanced electromagnetic force is calculated.
By calculation, the magnetic field data in no-load state is obtained, which can be used to further calculate the radial magnetic force of the rotor outer surface, seeing in equation (2) [13-14]
After modeling and loading, the nonlinear Poisson equations and boundary conditions are used for solution, then generator magnetic field data are got.
Conclusion This article compares the analytical and mathematical calculating methods for turbine generator unbalanced electromagnetic force by rotor winding inter-turn short circuit fault, proposes to use the numerical method for unbalanced electromagnetic force calculation, generator magnetic field variation are analyzed after rotor winding inter-turn short circuit fault, magnetic field data are obtained to calculate the distributed electromagnetic force, the final results show that the numerical simulation can more accurately express the electromagnetic force state that generator rotor suffered, which provides the basis for further composite force analysis.

Therefore, it has important significance of guiding practical production to conduct quantitative and qualitative tests for surface characteristics of the paper and analyze the test data.
Table 1 Data of glossiness test Sample Glossiness (average value) Gold card paper 31.2 Coated paper 3.9 Vacuum aluminized paperboard 45.2 2.1.3 Analysis on test results Data in Table 1 show that glossiness of vacuum aluminized paperboard is the highest, far greater than that of gold card paper and coated paper.
Table 2 Data of smoothness test Sample Smoothness (average value) (s) Gold card paper 920 Coated paper 365 Vacuum aluminized paperboard 1820 2.2.3 Analysis on test results Data in Table 2 show that smoothness of vacuum aluminized paperboard is extremely high, which is several times more than that of other paper.
Table 3 Data of ink absorbency test Sample Ink absorbency value (%) Gold card paper 12 Coated paper 20 Vacuum aluminized paperboard 10 2.3.3 Analysis on test results Data in Table 3 show that K&N value of vacuum aluminized paperboard is quite low and almost has no absorption capacity.
Conclusion Through test data about paper surface characteristics, this paper analyzed particularity of surface characteristics of vacuum aluminized paperboard in detail.

Introduction Frequent itemset mining is a traditional and important problem in data mining.
Second, we split the stream data into sections, and build data synopsis with a 3-tuple data structure, through which we can merge partial results into the final results; thus, an incremental update is implemented. 3.
AMFIoDS Algorithm In this section, we will introduce the data structure and the detailed algorithm. 3.1 Data Structure We employ a 3-tuple list to store the data synopsis, in which i represents the itemset, s is the support, and t refers to the itemset type.
[5] D.Lee, and W.Lee, Finding Maximal Frequent Itemsets over Online Data Streams Adaptively, in: Proc.
Online Mining(Recently) Maximal Frequent Itemsets over Data Streams, in: Proc.