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Online since: June 2014
Authors: Yun Peng
With the development of memory carrier, data capacity is also growing [5].
Because RFID tags are bearing electronic information, whose data content can be protected by password, difficult to be forged and altered.
The current passive RFID system in widespread use has not very reliable security mechanism with poor data secrecy.
RFID data is vulnerable to attacks, mainly because the RFID chip itself as well as the process that the chip is reading or writing data are easy to be used by hackers [7].
In the process of IOT application, when there are two or more transponders sending data at the same time, data interference shall appear, which is known as collision and lead to data transmission failure [8].
Because RFID tags are bearing electronic information, whose data content can be protected by password, difficult to be forged and altered.
The current passive RFID system in widespread use has not very reliable security mechanism with poor data secrecy.
RFID data is vulnerable to attacks, mainly because the RFID chip itself as well as the process that the chip is reading or writing data are easy to be used by hackers [7].
In the process of IOT application, when there are two or more transponders sending data at the same time, data interference shall appear, which is known as collision and lead to data transmission failure [8].
Online since: August 2011
Authors: Xu Hua Pan, Zhao Ming Lei, Xiao Qin Su
With this scheduling, each node listens to see if any other node wants to transmit data to it in the listening period.
The RT class is assigned to high priority real time traffic such as alarm data or real time audio/video.
Fig. 3 illustrates a data transmission from the source node (A) to the sink (E).
Each node without data to send wakes up only at the scheduled listen period.
Illustration of data transmission The best effort traffic.
The RT class is assigned to high priority real time traffic such as alarm data or real time audio/video.
Fig. 3 illustrates a data transmission from the source node (A) to the sink (E).
Each node without data to send wakes up only at the scheduled listen period.
Illustration of data transmission The best effort traffic.
Online since: July 2013
Authors: Yang Xu, Hong Xing Lv, Ying Xie, Rong Xiao Yao
This course is trying to design a virtual frequency meter that based on NI ELVIS experimental platform and collecting data by NI PCI-6251 data acquisition card in order to let students know more about measuring principle and instrument circuit designing.
Software programming has to collect voltage signal by DAQ data acquisition card, and measure the number of pulses within a sampling period.
Program graph of virtual frequency meter Data acquisition module.
We use a dynamic data conversion control to convert the data collected by data acquisition card and send them into a for cyclic sentence.The number of loops is just as the sampling frequency(1500000) .We can judge whether it is a rising edge by the function of automatic indexing.We call it a rising edge If the pre value is less than zero and the next one is greater than zero, and the accumulator add 1 every time when this happened .
[5] Long Huawei,Gu Yonggang.LabVIEW 8.2.1 and DAQ data acquisition [M].
Software programming has to collect voltage signal by DAQ data acquisition card, and measure the number of pulses within a sampling period.
Program graph of virtual frequency meter Data acquisition module.
We use a dynamic data conversion control to convert the data collected by data acquisition card and send them into a for cyclic sentence.The number of loops is just as the sampling frequency(1500000) .We can judge whether it is a rising edge by the function of automatic indexing.We call it a rising edge If the pre value is less than zero and the next one is greater than zero, and the accumulator add 1 every time when this happened .
[5] Long Huawei,Gu Yonggang.LabVIEW 8.2.1 and DAQ data acquisition [M].
Online since: March 2013
Authors: Toshitsugu Ueda, Satoshi Ikezawa, Muneaki Wakamatsu
In the experiments, 100 laser shots were used to record data for each spectrum in ambient air.
The intensity of the signal was based on the data obtained for 100 laser pulse shots in ambient air.
Figs. 4 and 5 show the experimental data for the other spectrum from the pollucite.
The intensity of the signal was based on the data obtained for 100 laser pulse shots in ambient air.
Isotopic data of Cs Cs Isotopes Isotope data Half-life [s] Decay constant Radioactivity [Bq] Cs-134 6.51E+07 1.06E-08 4.79E+13 Cs-136 1.14E+06 6.10E-07 2.70E+15 Cs-137 9.51E+08 7.29E-10 3.20E+12 Tab. 2.
The intensity of the signal was based on the data obtained for 100 laser pulse shots in ambient air.
Figs. 4 and 5 show the experimental data for the other spectrum from the pollucite.
The intensity of the signal was based on the data obtained for 100 laser pulse shots in ambient air.
Isotopic data of Cs Cs Isotopes Isotope data Half-life [s] Decay constant Radioactivity [Bq] Cs-134 6.51E+07 1.06E-08 4.79E+13 Cs-136 1.14E+06 6.10E-07 2.70E+15 Cs-137 9.51E+08 7.29E-10 3.20E+12 Tab. 2.
Online since: September 2013
Authors: Mohd Mustafa Al Bakri Abdullah, M. Mazlan, A.M. Iqbal, Z.A. Zainal, M.S. Salim
Five series of tests data on each type of fuel were analyzed and compared.
Table 3 : Fuel properties of cooking palm oil-diesel blend Sample Density kg/m³ Calorific value (kJ/kg) Viscosity at 27oC (mm²/s) Viscosity reduction (%) P100 P60 P40 P20 Diesel 904 882 863 855 840 39,027 41,184 41,558 42,840 43,379 84.99 45.90 27.32 24.55 13.95 `- 45.99 67.86 71.12 - Engine Performance Engine test were carried out separately using diesel and its blends with palm oil at varying load.
The CO emission data support correlation between density and atomization process.
Table 3 : Fuel properties of cooking palm oil-diesel blend Sample Density kg/m³ Calorific value (kJ/kg) Viscosity at 27oC (mm²/s) Viscosity reduction (%) P100 P60 P40 P20 Diesel 904 882 863 855 840 39,027 41,184 41,558 42,840 43,379 84.99 45.90 27.32 24.55 13.95 `- 45.99 67.86 71.12 - Engine Performance Engine test were carried out separately using diesel and its blends with palm oil at varying load.
The CO emission data support correlation between density and atomization process.
Online since: January 2015
Authors: Shu Ping Dang, Joseph Ridge, Min Zhang, Jordan Bristow, Amin Gholamzadeh
Once a theft occurs, the computation center will instantaneously obtain the data related to this behavior and assess its authorization and then determine to report or ignore it.
After the data of the protected terminal is obtained, the algorithm to process and analyze it is critical.
[2] Sheley, J.F. and Bailey, K.D., New directions for anti-theft policy: Reductions in stolen goods buyers, Journal of Criminal Justice, Vol.13 (5), pp.399-415, 1985
After the data of the protected terminal is obtained, the algorithm to process and analyze it is critical.
[2] Sheley, J.F. and Bailey, K.D., New directions for anti-theft policy: Reductions in stolen goods buyers, Journal of Criminal Justice, Vol.13 (5), pp.399-415, 1985
Online since: June 2010
Authors: Yong Feng Li, Yi Sun, Zi Rui Guo, Xiao Ye Liu
The most relevant
parameters were calibrated with lab-scale experimental data.
Granules with diameter 1-3mm. 6.Due to higher biogas yield and operation as low as 24 h of HRT, the UASB reactor seemed to be a better choice for continuous methane fermentation and wastewater reduction.
The obtained results provided useful data for biological methane production on a large scale. 7.The results of this study showed that the COD removal rate was high, which implied that at present we can achieve the bio-methane production and wastewater treatment, simultaneously.
Granules with diameter 1-3mm. 6.Due to higher biogas yield and operation as low as 24 h of HRT, the UASB reactor seemed to be a better choice for continuous methane fermentation and wastewater reduction.
The obtained results provided useful data for biological methane production on a large scale. 7.The results of this study showed that the COD removal rate was high, which implied that at present we can achieve the bio-methane production and wastewater treatment, simultaneously.
Online since: June 2013
Authors: Jao Hwa Kuang, Chun Ho Yin, Chao Ming Hsu, Ping Shen Su
The simulated residual strain variation data is incorporated into the hole-drilling strain-gage method to derive the possible residual stress components.
In 1966, Rendler and Vigness[5] used experimental data of through hole drilling theory and blind hole drilling method as proved that through hole drilling theory was applicable in the blind hole drilling method.
Following numerical analysis, the error rate of the von Mises Stress was significantly improved over that produced by the calculation of ASTM Standards, with an average error rate reduction of approximately 10%.
In 1966, Rendler and Vigness[5] used experimental data of through hole drilling theory and blind hole drilling method as proved that through hole drilling theory was applicable in the blind hole drilling method.
Following numerical analysis, the error rate of the von Mises Stress was significantly improved over that produced by the calculation of ASTM Standards, with an average error rate reduction of approximately 10%.
Online since: July 2013
Authors: Fu Lei Chu, Qin Kai Han, Yong Gui, Zheng Li, Zhi Ke Peng
Comparison of simulating and experiment data.
Fig. 12(a) shows the RMS of experiment and simulating data with different speeds, the RMS of experiment data much larger than simulating data, but the overall trend are consistent.
The kurtosis values of experiment data and simulating data are showed in Fig. 12(b).
(a)Simulation data, (b) Experiment data.
Fig. 12.Experiment and simulating data.
Fig. 12(a) shows the RMS of experiment and simulating data with different speeds, the RMS of experiment data much larger than simulating data, but the overall trend are consistent.
The kurtosis values of experiment data and simulating data are showed in Fig. 12(b).
(a)Simulation data, (b) Experiment data.
Fig. 12.Experiment and simulating data.
Online since: December 2013
Authors: Jing Gao
It also reduces the ability in classifying and predicting the coming data.
Therefore, it is widely applied to pattern recognition, machine learning, data mining.
It also reduces the ability of classification and prediction in further data.
It also reduces the ability of classification and prediction in further data.
And it is suit for data process, in which time is very critical.
Therefore, it is widely applied to pattern recognition, machine learning, data mining.
It also reduces the ability of classification and prediction in further data.
It also reduces the ability of classification and prediction in further data.
And it is suit for data process, in which time is very critical.