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Online since: February 2014
Authors: Miloš Kalousek, Lukáš Chuchma
This value is deduced from data about solar radiation impinging on horizontal surface Ihor.
Solar irradiation data (Ihor) were available in 15 minutes steps, therefore they were aggregated by Eq. 4.
Ipan = Isun Ipan = 0 for c > 0 for c ≤ 0 (14) Input data Horizontal irradiation data were provided by weather station of Institute of Landscape Water Management (Brno University of Technology, Faculty of Civil Engineering).
Therefore more accurate data provided by weather station were used for simulation.
House electricity consumption data were known only in total day sum only.
Solar irradiation data (Ihor) were available in 15 minutes steps, therefore they were aggregated by Eq. 4.
Ipan = Isun Ipan = 0 for c > 0 for c ≤ 0 (14) Input data Horizontal irradiation data were provided by weather station of Institute of Landscape Water Management (Brno University of Technology, Faculty of Civil Engineering).
Therefore more accurate data provided by weather station were used for simulation.
House electricity consumption data were known only in total day sum only.
Online since: March 2015
Authors: Gao Feng Zhan, Peng Tian, Lei Nai
The main idea is to interpret the original data in the most variables with fewer variables.
The principal components can be used to explain the comprehensive index of original data.
The data of gradation plan and asphalt-aggregate ratio in the experiments is shown in table 1.
In this research, the deviation normalization method will be used to normalize the data, according to Eq.1.
Principal components analysis of protein structure ensembles calculated using NMR data.
The principal components can be used to explain the comprehensive index of original data.
The data of gradation plan and asphalt-aggregate ratio in the experiments is shown in table 1.
In this research, the deviation normalization method will be used to normalize the data, according to Eq.1.
Principal components analysis of protein structure ensembles calculated using NMR data.
Online since: December 2012
Authors: Sai Qun Chen, Wang Run Wu, Jian Keng Zhang, Qian Hong Wu
Spatial Information Management
This module can realize the enlargement, the reduction, the remove, the edition, the revision, the refresh as well as the flash and centralization of element on the map, and the interactive operation between graphs and attribute data.
According to it, the function gains the related data from the database, and uses the MapGIS component for automatic mapping on corresponding line layer (objLineArea).
Application Example Take actual data of the lead-zinc-silver ore in Zhijiadi, Shanxi Province as the example.
The interface is shown in Figure 5, and its left half part for geological data processing, right half part for graph interactive display.
They provide the data and requirements of frontline workers.
According to it, the function gains the related data from the database, and uses the MapGIS component for automatic mapping on corresponding line layer (objLineArea).
Application Example Take actual data of the lead-zinc-silver ore in Zhijiadi, Shanxi Province as the example.
The interface is shown in Figure 5, and its left half part for geological data processing, right half part for graph interactive display.
They provide the data and requirements of frontline workers.
Online since: December 2011
Authors: Gyung Hyun Choi, Nyeon Sik Choi
Data Acquisition.
Survey was performed on a total of 163 corporations to produce meaningful data for IT utilization.
We have also performed correlation analysis over the data obtained from survey using SPSS to see the utilization on layer by processes.
While Table 4 simply notes the system name, in fact a detailed path map can be obtained after applying utilization data for each system.
Of course, such data needs to be applied differently by industry.
Survey was performed on a total of 163 corporations to produce meaningful data for IT utilization.
We have also performed correlation analysis over the data obtained from survey using SPSS to see the utilization on layer by processes.
While Table 4 simply notes the system name, in fact a detailed path map can be obtained after applying utilization data for each system.
Of course, such data needs to be applied differently by industry.
Online since: December 2014
Authors: Heng Zhang, Lei Meng, Miao Miao Huo, Xiao Shi An
They show very prominent effect in vibration attenuation and noise reduction.
In order to reduce errors, the vibration acceleration data caused by the same train when it respectively passes through the two cross sections at the same moment is taken for data analysis. 10 groups of such data are selected for analysis in order to ensure reliability of the data.
Fig. 3 Time domain waveform of vibration Fig. 4 Time domain waveform of vibration acceleration of steel spring floating slab track acceleration of general track 10 groups of data are respectively taken from samples with the waveforms like Fig. 3 and Fig .4 for time domain analysis.
Table 1 Statistical Result of Test Data Vibration Attenuation Structure Location of Test Point Effective Value of Acceleration(m/s2) Acceleration Level(dB) Steel spring floating slab track On vertical direction of steel rail 21.75 146.61 On vertical direction of tunnel walls 0.03 88.99 General ballast bed track On vertical direction of steel rail 31.30 149.28 On vertical direction of tunnel walls 0.37 111.35 It is shown in time domain waveforms in Fig.3 and Fig.4 that the vibration acceleration amplitude of the steel spring floating slab track is obviously smaller than the vibration acceleration amplitude of the general track in steel rails and tunnel walls.
Vibration attenuation effect is gradually increased with increase in frequency. 2.3 Result analysis of Z weighted vibration acceleration level In view of that vibration data of tunnel walls can directly reflect the vibration isolation effect of a track vibration isolator, while human bodies’ subjective feelings to each vibration frequency band are also involved in environmental vibration, so that the measured data in tunnel walls is analyzed according to GB 10071-88 Standard and ISO2631-1:1985 Vertical (Z direction) Weighing Manner (1-80 Hz) in order to obtain maximum Z weighted vibration acceleration level in the tunnel walls.
In order to reduce errors, the vibration acceleration data caused by the same train when it respectively passes through the two cross sections at the same moment is taken for data analysis. 10 groups of such data are selected for analysis in order to ensure reliability of the data.
Fig. 3 Time domain waveform of vibration Fig. 4 Time domain waveform of vibration acceleration of steel spring floating slab track acceleration of general track 10 groups of data are respectively taken from samples with the waveforms like Fig. 3 and Fig .4 for time domain analysis.
Table 1 Statistical Result of Test Data Vibration Attenuation Structure Location of Test Point Effective Value of Acceleration(m/s2) Acceleration Level(dB) Steel spring floating slab track On vertical direction of steel rail 21.75 146.61 On vertical direction of tunnel walls 0.03 88.99 General ballast bed track On vertical direction of steel rail 31.30 149.28 On vertical direction of tunnel walls 0.37 111.35 It is shown in time domain waveforms in Fig.3 and Fig.4 that the vibration acceleration amplitude of the steel spring floating slab track is obviously smaller than the vibration acceleration amplitude of the general track in steel rails and tunnel walls.
Vibration attenuation effect is gradually increased with increase in frequency. 2.3 Result analysis of Z weighted vibration acceleration level In view of that vibration data of tunnel walls can directly reflect the vibration isolation effect of a track vibration isolator, while human bodies’ subjective feelings to each vibration frequency band are also involved in environmental vibration, so that the measured data in tunnel walls is analyzed according to GB 10071-88 Standard and ISO2631-1:1985 Vertical (Z direction) Weighing Manner (1-80 Hz) in order to obtain maximum Z weighted vibration acceleration level in the tunnel walls.
The Effect of Bearing Simulation on Vibration Characteristics of a Steel Box Girder Footbridge Model
Online since: October 2014
Authors: Ying Zou, Xian Zhang, Ju Bing Zhang
At the same time, the simulation of bridge should be as close to the reality as possible to obtain more accurate data.
(unit: mm) In the text, vibration pickup 941b and 891-II were used to collect the bridge vibration acceleration data.
The results of longitudinal data at 9 point. (16 channel) The Fig. 4 is the time domain chart and frequency domain chart of longitudinal measured data (16 channel) at 9 point after filtering.
The probable reason is that longitudinal stiffeners are not considered in modeling leads to the reduction of structural stiffness
(unit: mm) In the text, vibration pickup 941b and 891-II were used to collect the bridge vibration acceleration data.
The results of longitudinal data at 9 point. (16 channel) The Fig. 4 is the time domain chart and frequency domain chart of longitudinal measured data (16 channel) at 9 point after filtering.
The probable reason is that longitudinal stiffeners are not considered in modeling leads to the reduction of structural stiffness
Online since: October 2012
Authors: Qiang An, Lu Lin, Yuan Yuan Liu, Ning Qiu Huang, Bin Zhao
Ten variables including CODMn, PO43--P, SiO3-Si, NO3--N, NO2--N, NH4+-N, TN, TP, TOC and chl-a were analyzed by exploratory data analysis.
Principal components analysis (PCA) is a useful tool in the examination of multivariate data [15].
The first principal component is the linear combination of the variables that accounts for a maximum of the total variability of the data set.
Data was determined using the statistical package SPSS (Release 10.0).
[15] Zitko V (1994) Principal Component Analysis in the evaluation of environmental data.
Principal components analysis (PCA) is a useful tool in the examination of multivariate data [15].
The first principal component is the linear combination of the variables that accounts for a maximum of the total variability of the data set.
Data was determined using the statistical package SPSS (Release 10.0).
[15] Zitko V (1994) Principal Component Analysis in the evaluation of environmental data.
Online since: November 2012
Authors: Jan Wawryszczuk, Bożena Zgardzińska, Tomasz Goworek, Marek Pietrow
A review of data about positron annihilation lifetime in normal alkanes is presented.
As an example of typical o-Ps lifetime dependence on temperature and pressure the data for nonadecane C19 are shown in Fig.1 [4].
The data marked by circles were collected by increasing the temperature in 1 K steps (1 h per spectrum).
It is seen that both, lifetime and intensity, reach the values expected from extrapolation of the data for the rotator phase.
The effect of transition to the rigid phase is seen as a reduction of count number.
As an example of typical o-Ps lifetime dependence on temperature and pressure the data for nonadecane C19 are shown in Fig.1 [4].
The data marked by circles were collected by increasing the temperature in 1 K steps (1 h per spectrum).
It is seen that both, lifetime and intensity, reach the values expected from extrapolation of the data for the rotator phase.
The effect of transition to the rigid phase is seen as a reduction of count number.
Online since: July 2020
Authors: T. Paul Chow, Alexander Bolotnikov, Collin W. Hitchcock, Reza Ghandi, Gyanesh Pandey, Xiang Zhou
Based on the observed electrical characteristics, a subcircuit SPICE model for the experimental devices is proposed and validated against the data.
Method Using experimental data from prototype 3kV diodes fabricated at GE Global Research [1,2], we have formulated a SPICE model which accurately represents the static and dynamic behavior of these CB-diodes.
Unlike the SPICE diode with its smoothly decreasing capacitance, the CB diode exhibits successive reductions in capacitance as reverse bias is increased.
Using LTSpice’s built in table characteristics, this capacitor can be built from experimental data using a piecewise linear table.
Figure 10: CB diode reverse-bias capacitance-voltage characteristics forward recovery Conclusion Using experimental and device-level simulation data for CB diodes, we have formulated a preliminary SPICE model.
Method Using experimental data from prototype 3kV diodes fabricated at GE Global Research [1,2], we have formulated a SPICE model which accurately represents the static and dynamic behavior of these CB-diodes.
Unlike the SPICE diode with its smoothly decreasing capacitance, the CB diode exhibits successive reductions in capacitance as reverse bias is increased.
Using LTSpice’s built in table characteristics, this capacitor can be built from experimental data using a piecewise linear table.
Figure 10: CB diode reverse-bias capacitance-voltage characteristics forward recovery Conclusion Using experimental and device-level simulation data for CB diodes, we have formulated a preliminary SPICE model.
Online since: June 2018
Authors: D. Okechukwu Onukwuli, K. Akinpelu Babayemi, O. Akindele Okewale
The model accuracy is confirmed by the values of R2 >0.99 and is validated by the closeness of the experimental data to the predictions.
1.
The obtained optimum coag-flocculation process parameters will also be used as data for process design and development in wastewater treatment.
[14] Chizoba Chinelo Agu, Matthew Chukwudi Menkiti, Bernard Ibezim Okolo, Patrick Chukwudi Nnaji, Evaluation of the level and impact of selected physiochemical parameters of fertilizer effluent on Obinna river, Adani, Enugu State, Nigeria, Journal of Water Resourses and Protection,vol.6 (2014) 722-730 [15] Menkiti M.C, Aneke M.C, Ogbuene E.B, Onukwuli O.D, Ekumankama E.O, Optimal Evaluation of Coag-Flocculation Factors for Alum-Brewery Effluent System by Response Surface Methodology, Journal of Minerals and Characterization & Engineering,vol.11 (2012)543-558 [16] Marko Racar, Davor Dolar, Ana Spehar, Ana Kras, Kresimir Kosutic, Optimization of coagulation with ferric chloride as apretreatmentfor fouling reduction during nanofiltration of rendering plant secondary effluent, Chemosphere, vol.181(2017) 485-491) [17] Wang F, Lu S, Wei Y, Ji M, Characteristics of anaerobic granule and nitrogen and phosphorus removal in a SBR, Journal of Hazardous Materials, vol. 164 (2009) 1223-12 27 [
The obtained optimum coag-flocculation process parameters will also be used as data for process design and development in wastewater treatment.
[14] Chizoba Chinelo Agu, Matthew Chukwudi Menkiti, Bernard Ibezim Okolo, Patrick Chukwudi Nnaji, Evaluation of the level and impact of selected physiochemical parameters of fertilizer effluent on Obinna river, Adani, Enugu State, Nigeria, Journal of Water Resourses and Protection,vol.6 (2014) 722-730 [15] Menkiti M.C, Aneke M.C, Ogbuene E.B, Onukwuli O.D, Ekumankama E.O, Optimal Evaluation of Coag-Flocculation Factors for Alum-Brewery Effluent System by Response Surface Methodology, Journal of Minerals and Characterization & Engineering,vol.11 (2012)543-558 [16] Marko Racar, Davor Dolar, Ana Spehar, Ana Kras, Kresimir Kosutic, Optimization of coagulation with ferric chloride as apretreatmentfor fouling reduction during nanofiltration of rendering plant secondary effluent, Chemosphere, vol.181(2017) 485-491) [17] Wang F, Lu S, Wei Y, Ji M, Characteristics of anaerobic granule and nitrogen and phosphorus removal in a SBR, Journal of Hazardous Materials, vol. 164 (2009) 1223-12 27 [