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Online since: March 2018
Authors: Remigius Chidiebere Diovu, John Terhile Agee
With respect to data storage and cluster server processing, data aggregation in AMI network for secure transfer of energy user-consumption data must take cognizance of congestion control and user data privacy.
Firstly, aggregated metered noisy or fake data will not amount to exactly the aggregated real metered data due to the added randomness to each SM data.
This scheme is robust to data loss particularly during congestion scenario as it can prevent the leakage of the sensed data during data aggregation.
Once verified, the data image is then sent to the local concentrator for overhead reduction.
Figure 2 illustrates typical data flow in a secure data aggregation RTCA model.
Firstly, aggregated metered noisy or fake data will not amount to exactly the aggregated real metered data due to the added randomness to each SM data.
This scheme is robust to data loss particularly during congestion scenario as it can prevent the leakage of the sensed data during data aggregation.
Once verified, the data image is then sent to the local concentrator for overhead reduction.
Figure 2 illustrates typical data flow in a secure data aggregation RTCA model.
Online since: June 2013
Authors: Hao Kang, Wei Tian, Ming Qian Wang, Wen Ju Gao
Such matrix data can free download from the GEO database.
The other is the real gene expression data.
The data includes more than 6,000 genes, Spellman data in G1 process in cell is selected in this paper.
Simulation data.
Church, "Biclustering of expression data," Proceedings / ...
The other is the real gene expression data.
The data includes more than 6,000 genes, Spellman data in G1 process in cell is selected in this paper.
Simulation data.
Church, "Biclustering of expression data," Proceedings / ...
Online since: September 2013
Authors: David John Smith, Matthew J. Peel, Danie G. Hattingh, Thomas Connolley, Greame Horne, Shu Yan Zhang, Joe Kelleher, Michael Hart
The data did not suggest any
local texture but was dominated by spottiness, particularly in the region not disturbed by the friction
stir-weld tool.
The DIC strain data were averaged longitudinally over a distance of 50 mm in the area around the HEDXD line scans.
This was confirmed when the full-field DIC data was viewed and angled fronts of localised plasticity could be seen traversing the specimen.
The stresses are from HEDXD data and deformation strains from the DIC data.
Figure 6 shows the plastic strain distribution across the specimen combining the data from HEDXD, Fig. 3 (the elastic strain reduction, that is residual stress reduction/E, must first be calculated from this data, shown by the HEDXD arrow), and DIC, Fig. 4.
The DIC strain data were averaged longitudinally over a distance of 50 mm in the area around the HEDXD line scans.
This was confirmed when the full-field DIC data was viewed and angled fronts of localised plasticity could be seen traversing the specimen.
The stresses are from HEDXD data and deformation strains from the DIC data.
Figure 6 shows the plastic strain distribution across the specimen combining the data from HEDXD, Fig. 3 (the elastic strain reduction, that is residual stress reduction/E, must first be calculated from this data, shown by the HEDXD arrow), and DIC, Fig. 4.
Online since: August 2017
Authors: Yasuhiro Konishi, Toshiyuki Nomura, Norizoh Saitoh
We recognized that the reduction potential of Fe(III) ions is almost equal to the potential for the reduction of precious metals ions such as Pd(II) and Pt(IV).
Microbial reduction of soluble Pd(II) by S. algae cells at pH 7 and 25ºC.
Figure 1 shows typical kinetic data for the microbial recovery of Pd(II) ions.
This marked decrease in the aqueous Pd(II) concentration reflected the reduction of Pd(II) ions to metallic nanoparticles through microbial reduction by S. algae.
Figure 4 and Figure 5 show typical kinetic data for the microbial recovery of precious metal ions from the leaching solutions.
Microbial reduction of soluble Pd(II) by S. algae cells at pH 7 and 25ºC.
Figure 1 shows typical kinetic data for the microbial recovery of Pd(II) ions.
This marked decrease in the aqueous Pd(II) concentration reflected the reduction of Pd(II) ions to metallic nanoparticles through microbial reduction by S. algae.
Figure 4 and Figure 5 show typical kinetic data for the microbial recovery of precious metal ions from the leaching solutions.
Online since: January 2012
Authors: Comondore Ravindran, Sophie Lun Sin
Schematic of the permanent mould designed to produce hot tears
Thermal data of the solidifying casting were recorded using K-type thermocouples inserted into the mould cavity at three locations: in the vicinity of the downsprue, in the middle of the casting bar and by the end restraint (shown in Fig. 1).
It can be observed that the addition of silicon led to the reduction of the UTS and the elongation of AZ91E, while the yield strength remained relatively constant.
Further addition of silicon (up to 1.5 wt.%) resulted in a slight reduction in the hot tearing susceptibility of AZ91E.
Further addition of silicon resulted only in a slight reduction of the grain size (53 ± 10 μm and 38 ± 4 μm for AZ91E with 1.0 and 1.5 wt.% Si respectively).
However, addition of silicon resulted in reduction of the hot tearing susceptibility of AZ91E.
It can be observed that the addition of silicon led to the reduction of the UTS and the elongation of AZ91E, while the yield strength remained relatively constant.
Further addition of silicon (up to 1.5 wt.%) resulted in a slight reduction in the hot tearing susceptibility of AZ91E.
Further addition of silicon resulted only in a slight reduction of the grain size (53 ± 10 μm and 38 ± 4 μm for AZ91E with 1.0 and 1.5 wt.% Si respectively).
However, addition of silicon resulted in reduction of the hot tearing susceptibility of AZ91E.
Online since: January 2015
Authors: Yan Dong Zhao
In order to ensure the least possible to change data of the color lookup table in the process of ICC profiles, different systems should choose their default Gamma value.
Then, Eye-One Pro spectrophotometer to measure the 294 color block on the monitor, get the CIELAB color data.
Printing the color code file by C6501 digital press, and using X-Rite Eye-One Pro spectrophotometer to measure the 294 color block on display, obtained the corresponding CIELAB color data.
Comparing the proof color data and the display color data one by one, concluding the color aberration data.
Generally, the printing color tolerance for deltaE is less than or equal to 5, therefore, from the objective data, the color aberration between display color and actual proof color is acceptable.
Then, Eye-One Pro spectrophotometer to measure the 294 color block on the monitor, get the CIELAB color data.
Printing the color code file by C6501 digital press, and using X-Rite Eye-One Pro spectrophotometer to measure the 294 color block on display, obtained the corresponding CIELAB color data.
Comparing the proof color data and the display color data one by one, concluding the color aberration data.
Generally, the printing color tolerance for deltaE is less than or equal to 5, therefore, from the objective data, the color aberration between display color and actual proof color is acceptable.
Online since: February 2012
Authors: Somnath Chattopadhyaya, Sanjeev Kumar, Vinay Sharma
The data were then analyzed using statistical package for the social sciences is used as a path analysis model to verify the hypothetical construction of the study.
It tells how likely it is that sample data have responded even if the null hypothesis is true.
DEV.) t p Waste discharge methodology for reducing cost 2.514 (0.853) 17.437 0.00 Reduction in cost for materials purchasing without affecting the quality of the product 2.342 (1.186) 11.679 0.00 Reduction in cost of energy consumption 2.714 (0.893) 17.972 0.00 Effective waste treatment management for reducing cost 2.571 (1.037) 14.668 0.00 Reduction of the fine for environmental accidents 2.285 (0.987) 13.696 0.00 “Economic Performance”, which has 5 underlying dimension.
In industry the most important dimension is Reduction in cost of energy consumption (2.714) followed by Effective waste treatment management for reducing cost (2.571), and the least important dimension is Reduction of the fine for environmental accidents (2.285) followed by Reduction in cost for materials purchasing without affecting the quality of the product (2.342).
To attain even greater cost savings from waste reduction, meet comprehensive social and environmental responsibility targets and find new products with smaller ecological footprints, industries must extend their goals for environmental performance into their suppliers’ operations.
It tells how likely it is that sample data have responded even if the null hypothesis is true.
DEV.) t p Waste discharge methodology for reducing cost 2.514 (0.853) 17.437 0.00 Reduction in cost for materials purchasing without affecting the quality of the product 2.342 (1.186) 11.679 0.00 Reduction in cost of energy consumption 2.714 (0.893) 17.972 0.00 Effective waste treatment management for reducing cost 2.571 (1.037) 14.668 0.00 Reduction of the fine for environmental accidents 2.285 (0.987) 13.696 0.00 “Economic Performance”, which has 5 underlying dimension.
In industry the most important dimension is Reduction in cost of energy consumption (2.714) followed by Effective waste treatment management for reducing cost (2.571), and the least important dimension is Reduction of the fine for environmental accidents (2.285) followed by Reduction in cost for materials purchasing without affecting the quality of the product (2.342).
To attain even greater cost savings from waste reduction, meet comprehensive social and environmental responsibility targets and find new products with smaller ecological footprints, industries must extend their goals for environmental performance into their suppliers’ operations.
Online since: February 2012
Authors: Jing Zhao Li, Xing Zhu Liang, Yue Lin
LDA is a classical technique for linear dimension reduction.
But, when the data is distributed in a nonlinear way, LDA may fail to discover essential data structures.
LPP can preserve the intrinsic geometry of data and yield an explicit linear mapping suitable for training and testing samples.
Existing methods use PCA to preprocess the high-dimensional data, which may destroy the integrity of the original data.
DOFMA can avoid PCA pre-processing step and directly extract the optimal matrix from the original data.
But, when the data is distributed in a nonlinear way, LDA may fail to discover essential data structures.
LPP can preserve the intrinsic geometry of data and yield an explicit linear mapping suitable for training and testing samples.
Existing methods use PCA to preprocess the high-dimensional data, which may destroy the integrity of the original data.
DOFMA can avoid PCA pre-processing step and directly extract the optimal matrix from the original data.
Online since: December 2006
Authors: Yeon Sun Choi, Hyeon Ki Choi, Ja Choon Koo, Dong Ho Oh, Nam Hoon Lee
One of the major technological
challenges for the spindles to be successfully employed in the applications is the reduction of power
consumption since the most of the mobile applications operate with a limited power source at
relatively lower voltage.
Introduction As the generaton of the information-oriented society has proceeded rapidly, the functional requirement of massive digital information storage devices are on a trend for the higher data transfer rate and lower cost.
The cost of the higher data density requirements has been always prohibitive for the development engineers due to the radical reduction of the TMR budget.
Introduction As the generaton of the information-oriented society has proceeded rapidly, the functional requirement of massive digital information storage devices are on a trend for the higher data transfer rate and lower cost.
The cost of the higher data density requirements has been always prohibitive for the development engineers due to the radical reduction of the TMR budget.
Online since: June 2012
Authors: Ai Dong Tang, Duo Wang
There are some data about properties of the isomorphic series in the literature [3, 4].
The first discharge-charge data indicated the batterie with Cu2SO3·CuSO3·2H2O as working electrode had poor cycle reversible, and subsequent charge-discharge profiles had no obvious platform.
The two reduction peaks at 1.4 and 1.2 V correspond to the reduction process of Cu2+→Cu+ and Cu+→ Cu, respectively.
The 1.2 V reduction peak is stronger due to double Cu+ change to Cu.
The middle reduction peak between 1.0 and 0.02 V correspond to S4+ reduction to S.
The first discharge-charge data indicated the batterie with Cu2SO3·CuSO3·2H2O as working electrode had poor cycle reversible, and subsequent charge-discharge profiles had no obvious platform.
The two reduction peaks at 1.4 and 1.2 V correspond to the reduction process of Cu2+→Cu+ and Cu+→ Cu, respectively.
The 1.2 V reduction peak is stronger due to double Cu+ change to Cu.
The middle reduction peak between 1.0 and 0.02 V correspond to S4+ reduction to S.