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Online since: December 2012
Authors: Ming Tian, Ju Long Lan, Han Mo
Traditional IP multicast utilizes a multicast tree to transmit data packets.
Fig. 1 illustrates the implementation model of CSRA scheme, which is constructed by management plane, control plane and data plane.
So there will always be public data delivery paths among multicast trees, which are called shared links.
(2) State Reduction Ratio(SRR) Since multicast state in edge nodes (incoming and exiting nodes) cannot be reduced in any state reduction scheme, we only consider the state in core routers.
Large number of multicast groups and large bth led to high Aggregated Degree and high State Reduction Ratio.
Fig. 1 illustrates the implementation model of CSRA scheme, which is constructed by management plane, control plane and data plane.
So there will always be public data delivery paths among multicast trees, which are called shared links.
(2) State Reduction Ratio(SRR) Since multicast state in edge nodes (incoming and exiting nodes) cannot be reduced in any state reduction scheme, we only consider the state in core routers.
Large number of multicast groups and large bth led to high Aggregated Degree and high State Reduction Ratio.
Online since: June 2010
Authors: Paul Koltun, Ambalavanar Tharumarajah
It provides the basic life cycle impact
data on REEs for ascertaining the environmental impact of intermediate and final products that use
them [3].
The last part models the subsequent reduction of individual REOs to produce REEs.
Nominal representative data is used in this study.
The data have been sourced from review of technological processes [5-8], environmental data pertaining to materials and chemicals from LCA databases in SimaPro [9], and combined with modelling and estimation.
The environmental impacts from reduction of only those RE elements used in Mg-RE alloys are considered in this study.
The last part models the subsequent reduction of individual REOs to produce REEs.
Nominal representative data is used in this study.
The data have been sourced from review of technological processes [5-8], environmental data pertaining to materials and chemicals from LCA databases in SimaPro [9], and combined with modelling and estimation.
The environmental impacts from reduction of only those RE elements used in Mg-RE alloys are considered in this study.
Online since: February 2014
Authors: Jun Ling Zhao, Xue Min Zhang, Fu Wei Kang
Isothermal compression of superalloy GH4169 has been conducted on Gleebe-1500D hot simulation at the deformation temperatures ranging from 950℃ to 1100℃,the strain rates ranging from 0.01s-1 to 10s-1, and the height reduction of 50%.
Constitutive equation of superalloy GH4169 was established by experimental data.
Error analysis showed that calculated stress values by the established constitutive equation were coincident with experimental data well, and it provided the theory basis to optimize forging processing of superalloy GH4169.
The hot compressive tests were conducted on Gleeble-1500D simulator at deformation temperature of 950℃, 1000℃, 1050℃ and 1100℃, at strain rate of 0.01s-1, 0.1s-1, 1s-1 and 10s-1 ,and the height reduction of 50%, followed by water quenching, to preserve the hot-deformed structure.
On the basis of experimental data, the hot deformation constitutive equation of superalloy GH4169 was established as following: 3.
Constitutive equation of superalloy GH4169 was established by experimental data.
Error analysis showed that calculated stress values by the established constitutive equation were coincident with experimental data well, and it provided the theory basis to optimize forging processing of superalloy GH4169.
The hot compressive tests were conducted on Gleeble-1500D simulator at deformation temperature of 950℃, 1000℃, 1050℃ and 1100℃, at strain rate of 0.01s-1, 0.1s-1, 1s-1 and 10s-1 ,and the height reduction of 50%, followed by water quenching, to preserve the hot-deformed structure.
On the basis of experimental data, the hot deformation constitutive equation of superalloy GH4169 was established as following: 3.
Online since: July 2022
Authors: Rodolfo Fernandez-Martinez, M. Belén Gomez-Mancebo, Laura J. Bonales, Cesar Maffiotte, Alberto J. Quejido, Isabel Rucandio
Another well-established reduction method is the solvothermal reduction that combines simplicity and effectiveness [25].
Reduction of graphene oxide.
Diffraction data were collected by using a PANalytical X´Pert Pro diffractometer operating in θ-θ configuration, with CuKα radiation (45 kV-40 mA), in the angular range of 5° < 2θ < 80° with a 0.017° step size.
Regarding Tour method is evident that the combination of reduction methods increases the percentage of carbon and therefore the degree of reduction.
Evolution of Raman spectra at the different reduction methods.
Reduction of graphene oxide.
Diffraction data were collected by using a PANalytical X´Pert Pro diffractometer operating in θ-θ configuration, with CuKα radiation (45 kV-40 mA), in the angular range of 5° < 2θ < 80° with a 0.017° step size.
Regarding Tour method is evident that the combination of reduction methods increases the percentage of carbon and therefore the degree of reduction.
Evolution of Raman spectra at the different reduction methods.
Online since: September 2013
Authors: Ya Jun Li, Li Zhang, Yan Miao Ma, Bin Liu
This paper provides a valuable reference for noise reduction of the sewing machine.
The test data are processed by LMS Test.
The result shows that the vibration of the system is caused by the harmonic frequencies, and the good consistence of the two curves shows that the tested data is accurate.
Study on Vibration and Noise Reduction of Industrial Sewing Machines [D].
[2] Wang Kaihe, Guo Yangkuan, Xu Wei..Noise and Vibration Reduction Analysis of the High Speed Sewing Machine[J].
The test data are processed by LMS Test.
The result shows that the vibration of the system is caused by the harmonic frequencies, and the good consistence of the two curves shows that the tested data is accurate.
Study on Vibration and Noise Reduction of Industrial Sewing Machines [D].
[2] Wang Kaihe, Guo Yangkuan, Xu Wei..Noise and Vibration Reduction Analysis of the High Speed Sewing Machine[J].
Online since: September 2013
Authors: Mohamad Almaoui, Mohamad Saouli, Bhaskar Sinha
To collect required data for subsequent analyses, closed-ended questionnaire items were developed.
The research instrument, a questionnaire, was used to collect the data.
The questionnaire was designed as the basis for primary data collection.
The collected data was analyzed to answer the research question and test the hypothesis using SPSS.
Table 7 contains the data of the regression analysis performed for the hypothesis related to product rework.
The research instrument, a questionnaire, was used to collect the data.
The questionnaire was designed as the basis for primary data collection.
The collected data was analyzed to answer the research question and test the hypothesis using SPSS.
Table 7 contains the data of the regression analysis performed for the hypothesis related to product rework.
Online since: May 2014
Authors: Thidarat Cotanont, Chalong Buaphan, Kamonporn Kromkhun
Single well pump test data from 17 wells in the Phu Phan aquifer (30-120 m depth) were analyzed to obtain transmissivity (T) and K.
Required data are the discharge, Q, a set of drawdowns, s, and times, t, from the start of pumping.
From the measurement data, we obtained a set of pairs of s and t.
The values of K were evaluated from these data using the Jacob method as mention above.
The empirical probability [6], Fs, was calculated by Fs = m/(n+1), m is rank of data, and n is number of data.
Required data are the discharge, Q, a set of drawdowns, s, and times, t, from the start of pumping.
From the measurement data, we obtained a set of pairs of s and t.
The values of K were evaluated from these data using the Jacob method as mention above.
The empirical probability [6], Fs, was calculated by Fs = m/(n+1), m is rank of data, and n is number of data.
Online since: September 2005
Authors: Jürgen Hirsch
Quantitative ODF data
evaluation methods have been applied to derive volume fractions of the texture components
involved by adapting gaussian scattering functions /5/.
Furthermore, these quantified earing profiles can easily be correlated with texture data from ODF series expansion coefficients by a method of multiple linear regression [8].
The combination of both methods allows the prediction of complete finish gauge earing profiles from experimental (or simulated) texture data.
This is also a useful tool to predict and compare anisotropy properties from texture data when actual deep drawing tests are not possible (e.g. for thick plates) or when other (e.g. on-line) texture data are provided that need to be correlated with material anisotropy.
A new method of profiles (and texture data) by series expansion methods can be used for a quantitative correlation and precise prediction of earing profiles with rolling strain.
Furthermore, these quantified earing profiles can easily be correlated with texture data from ODF series expansion coefficients by a method of multiple linear regression [8].
The combination of both methods allows the prediction of complete finish gauge earing profiles from experimental (or simulated) texture data.
This is also a useful tool to predict and compare anisotropy properties from texture data when actual deep drawing tests are not possible (e.g. for thick plates) or when other (e.g. on-line) texture data are provided that need to be correlated with material anisotropy.
A new method of profiles (and texture data) by series expansion methods can be used for a quantitative correlation and precise prediction of earing profiles with rolling strain.
Online since: August 2020
Authors: Siam Thongnak, Sakhob Khumkoa, Jirapracha Thampiriyanon, Piamsak Laokhen, Kitti Laungsakulthai
Data augmentation is a technique that enables the diversity of data applied to training dataset images in order to prevent network from overfitting and memorizing the exact details from very limited number of datasets [6, 13,14] by randomly rotation (horizontally or vertically flipped).
From the result we can confirm that data augmentation can help network get a small increase of their accuracy by enabling diversity of training data and the classification accuracy obtained from BSE images higher than SE images.
Training progress of the best approach, DenseNet201 with data augmentation, shows the plot of accuracy curve of and loss curve against iteration.
Confusion matrix of the best approach, DenseNet201 with data augmentation, shows the number of samples for each class predicted by system.
A survey on Image Data Augmentation for Deep Learning, Journal of Big Data, Vol. 6 no.60 (2019).
From the result we can confirm that data augmentation can help network get a small increase of their accuracy by enabling diversity of training data and the classification accuracy obtained from BSE images higher than SE images.
Training progress of the best approach, DenseNet201 with data augmentation, shows the plot of accuracy curve of and loss curve against iteration.
Confusion matrix of the best approach, DenseNet201 with data augmentation, shows the number of samples for each class predicted by system.
A survey on Image Data Augmentation for Deep Learning, Journal of Big Data, Vol. 6 no.60 (2019).
Online since: October 2013
Authors: Meng Yu Zhang, Wan Qing Zhou, Feng Qi Gao
(1)
(2)
According to the actual project, the data of the pile is shown in Table 1.
Data of the pile Category Intensity Quantity Longitudinal bar HRB400 725 Stirrup HRB300 10@100 Concrete C30 Diameter of pile 600mm The ultimate loading capacity of piles with no buried pipes is listed in Table 2.
In Table 3, the reduction and the reduction percentage of Acor with single u pipe and with double u pipe are listed.
Reduction of Acor with different buried pipe Buried pipe diameter (mm) reduction of Acor with single u pipe (mm2) reduction of Acor with double u pipe (mm2) 20 628 1257 25 982 1963 40 2513 5027 50 3927 7854 Buried pipe diameter (mm) reduction percentage of Acor with single u pipe (mm2) reduction percentage of Acor with single u pipe (mm2) 20 0.22% 0.44% 25 0.35% 0.69% 40 0.89% 1.78% 50 1.39% 2.78% Table 4.
According to the calculation, the reduction of inertia moment of the Double u-shape buried pipe is less than 1%.
Data of the pile Category Intensity Quantity Longitudinal bar HRB400 725 Stirrup HRB300 10@100 Concrete C30 Diameter of pile 600mm The ultimate loading capacity of piles with no buried pipes is listed in Table 2.
In Table 3, the reduction and the reduction percentage of Acor with single u pipe and with double u pipe are listed.
Reduction of Acor with different buried pipe Buried pipe diameter (mm) reduction of Acor with single u pipe (mm2) reduction of Acor with double u pipe (mm2) 20 628 1257 25 982 1963 40 2513 5027 50 3927 7854 Buried pipe diameter (mm) reduction percentage of Acor with single u pipe (mm2) reduction percentage of Acor with single u pipe (mm2) 20 0.22% 0.44% 25 0.35% 0.69% 40 0.89% 1.78% 50 1.39% 2.78% Table 4.
According to the calculation, the reduction of inertia moment of the Double u-shape buried pipe is less than 1%.