Sort by:
Publication Type:
Open access:
Publication Date:
Periodicals:
Search results
Online since: June 2014
Authors: Ze Qin Liu, Ge Li, Ze Yang Bai
When the particle was considered as a spherical particle, the mean diameter could be expressed by D [p, q].The general calculation formula was shown as follows, where the total number of particles that diameter was di was ni
Number mean diameter D [1, 0] was based on the number of particles.
The total length was and the total number was when particles were aligned.
Hence, D50 of the number mean diameter was selected as the reference diameter.
In Chinese: Comparison of Lake Sediment Grain Size Results Measured by Two Laser Diffraction Particle Size Analyzers.
Number mean diameter D [1, 0] was based on the number of particles.
The total length was and the total number was when particles were aligned.
Hence, D50 of the number mean diameter was selected as the reference diameter.
In Chinese: Comparison of Lake Sediment Grain Size Results Measured by Two Laser Diffraction Particle Size Analyzers.
Vibration-Based Terrain Identification for Planetary Exploration Robots Using Support Vector Machine
Online since: November 2012
Authors: Kai Xue, Wen Lin Pan, Qiang Li, He Xu, Zhi Xu Li
Facing to the same number of votes, we propose a new algorithm.
Because objective of classification is to adjust control strategy and ensure the robot safely travel through the terrain, sequence numbers of the terrains arranged in order of difficulty level that small sequence number terrain is traveled easier than the big.
To each terrain, there were fifty-four samples, and where odd numbers of samples were trained, so there were twenty-seven training samples.
It reduces number of dimensions and improves classification efficiency.
Prior to classify, sequence numbers of the terrains arranged in order of difficulty level that small sequence number terrain is traveled easier than the big.② if isn’t the first of classifying samples, it belongs to the terrain which is the previous sample.
Because objective of classification is to adjust control strategy and ensure the robot safely travel through the terrain, sequence numbers of the terrains arranged in order of difficulty level that small sequence number terrain is traveled easier than the big.
To each terrain, there were fifty-four samples, and where odd numbers of samples were trained, so there were twenty-seven training samples.
It reduces number of dimensions and improves classification efficiency.
Prior to classify, sequence numbers of the terrains arranged in order of difficulty level that small sequence number terrain is traveled easier than the big.② if isn’t the first of classifying samples, it belongs to the terrain which is the previous sample.
Online since: September 2013
Authors: Huai Yuan Wang, Yuan Li
As a result of constant development of catering industry in mainland China, a considerable number of restaurants, hotels and families directly discharge swill into the sewer or sell them to the unqualified or even illegal recycling workshop.
According to some statistical data, it is estimated that top 100 cities in China discharge roughly one million tons of swill every year and the annual discharge of the whole food industry in China is 20 million tons. [1] [2]Also many experts believe that the real number is far more than that.
Objective function: (1) Constraints: (2) (3) (4) (5) Xis=0 or 1 i,j=1,…,k s=1,2…m (6) Yis=0 or 1 i,j=1,…,k s=1,2…m (7) In the model above: the serial number of the recycling center is o, while the serial number of station is 1,2…k; the number of recycling station is i and j; s is the number of truck; gi is the weight of swill that need to be recycled; m is the total number of the trucks; q is the capacity of carriage of the trucks; Cij is the transportation cost from point i to point j.
Xijs is a control variable, which means whether truck(number s) would go from point i to point j, in that case, the value of Xijs is 1, conversely the value is 0.Yis is also a control variable, which means whether truck (number s) would collets the swill of point i, in that case, the value of Yis is 1, conversely the value is 0.
Table 4.1 The ordinates of the consumers and the average demands Number 1 2 3 4 5 6 7 8 9 10 11 Horizontal ordinate x 136 371 705 633 151 392 587 183 601 721 876 Vertical ordinate y 154 75 66 189 304 296 339 393 461 536 509 Quantity demanded q(t) 4.5 2 1 3.5 2.5 1 3 3 3.5 4.5 4 Fig 4.2 The screen shot of the program Figure4.2 The sketch map of the consumer distribution and the final solution Table 4.4 The final arrangements The numbers of consumers Truck 1 5→6→7→11→10→9→8 Truck 2 4→3→2→1 Conclusions and Future Research In this paper, the framework of a multilevel network of swill recycling logistics has been outlined according to the limitation of city policies and consumers’ requirements.
According to some statistical data, it is estimated that top 100 cities in China discharge roughly one million tons of swill every year and the annual discharge of the whole food industry in China is 20 million tons. [1] [2]Also many experts believe that the real number is far more than that.
Objective function: (1) Constraints: (2) (3) (4) (5) Xis=0 or 1 i,j=1,…,k s=1,2…m (6) Yis=0 or 1 i,j=1,…,k s=1,2…m (7) In the model above: the serial number of the recycling center is o, while the serial number of station is 1,2…k; the number of recycling station is i and j; s is the number of truck; gi is the weight of swill that need to be recycled; m is the total number of the trucks; q is the capacity of carriage of the trucks; Cij is the transportation cost from point i to point j.
Xijs is a control variable, which means whether truck(number s) would go from point i to point j, in that case, the value of Xijs is 1, conversely the value is 0.Yis is also a control variable, which means whether truck (number s) would collets the swill of point i, in that case, the value of Yis is 1, conversely the value is 0.
Table 4.1 The ordinates of the consumers and the average demands Number 1 2 3 4 5 6 7 8 9 10 11 Horizontal ordinate x 136 371 705 633 151 392 587 183 601 721 876 Vertical ordinate y 154 75 66 189 304 296 339 393 461 536 509 Quantity demanded q(t) 4.5 2 1 3.5 2.5 1 3 3 3.5 4.5 4 Fig 4.2 The screen shot of the program Figure4.2 The sketch map of the consumer distribution and the final solution Table 4.4 The final arrangements The numbers of consumers Truck 1 5→6→7→11→10→9→8 Truck 2 4→3→2→1 Conclusions and Future Research In this paper, the framework of a multilevel network of swill recycling logistics has been outlined according to the limitation of city policies and consumers’ requirements.
Online since: December 2016
Authors: Sergey Grigorievich Psakhie, Konstantin Petrovich Zolnikov, Aleksandr Vyacheslavovich Korchuganov, Dmitrij Sergeevich Kryzhevich
Each conductor consisted of two grains.
The cluster size was defined by the number of atoms in it.
The change of the cluster number in the simulated system depending on time is shown in Fig. 1a.
The total number of formed clusters and number of bicomponent clusters depending on the distance between the wires after relaxation process are shown in Fig. 1b.
The number of clusters versus time for distance between the wires 80 lattice parameters (a).
The cluster size was defined by the number of atoms in it.
The change of the cluster number in the simulated system depending on time is shown in Fig. 1a.
The total number of formed clusters and number of bicomponent clusters depending on the distance between the wires after relaxation process are shown in Fig. 1b.
The number of clusters versus time for distance between the wires 80 lattice parameters (a).
Online since: June 2011
Authors: Bing Suo Pan, Xiao Hong Fang, Ming Yuan Niu
Binding layers have three kinds of thickness: 0.25 mm, 0.37 mm and 0.45 mm, corresponding to the number of binding layers of 13, 11 and 10, respectively.
Working layers and binding layers were preformed by cold pressing, then assembled according to designed layer number and then hot pressed in vacuum.
The cutter samples were numbered S1, S2, …, S6 as in Table 1.
Table 1 Sample numbering Sample number S1 S2 S3 S4 S5 S6 Number of working layers 13 11 10 13 11 10 Number of binding layers 13 11 10 13 11 10 Binding layer formula 1# 1# 1# 2# 2# 2# The friction and wear properties of bit cutters were investigated using a pin-on-disc friction and wear tester (MG-2000A).
Discs were machined from blackmica contained medium-fine grained monzonitic granite as tribopair, whose compressive strength is 169.39 MPa.
Working layers and binding layers were preformed by cold pressing, then assembled according to designed layer number and then hot pressed in vacuum.
The cutter samples were numbered S1, S2, …, S6 as in Table 1.
Table 1 Sample numbering Sample number S1 S2 S3 S4 S5 S6 Number of working layers 13 11 10 13 11 10 Number of binding layers 13 11 10 13 11 10 Binding layer formula 1# 1# 1# 2# 2# 2# The friction and wear properties of bit cutters were investigated using a pin-on-disc friction and wear tester (MG-2000A).
Discs were machined from blackmica contained medium-fine grained monzonitic granite as tribopair, whose compressive strength is 169.39 MPa.
Online since: November 2011
Authors: Hong Bin Wang
First, the nodes exchange the typical distance vector protocol, each node makes the network access to the anchor minimum number of hops between nodes.
Anchor node density are discussed below, node density, node communication radius and the location of the number of circulating modified the traditional DV-Hop algorithm and the improved positioning accuracy of the algorithm.
Fig.2 is a 100m × 100m region of the random distribution of nodes, each node randomly generated coordinates, in which the number of anchor nodes and unknown nodes, respectively: 20 and 180, respectively, with circles and black dots.
From the figure we can see, with the total number of nodes increases, the average location error of two algorithms are gradually reduced.
Dynamic fine grained localization in Ad-Hoc sensor networks[C].
Anchor node density are discussed below, node density, node communication radius and the location of the number of circulating modified the traditional DV-Hop algorithm and the improved positioning accuracy of the algorithm.
Fig.2 is a 100m × 100m region of the random distribution of nodes, each node randomly generated coordinates, in which the number of anchor nodes and unknown nodes, respectively: 20 and 180, respectively, with circles and black dots.
From the figure we can see, with the total number of nodes increases, the average location error of two algorithms are gradually reduced.
Dynamic fine grained localization in Ad-Hoc sensor networks[C].
Online since: August 2013
Authors: Yun Zhang, Guang Ming Liang, Ren Ren Liu, Dong Hua Liu
This system calculate the number of the " 0 " by comparing with the difference in frequency with the DDS, which be shown in fig.4. fi, i=1,2, ...
So the number of “0” that must be removed is calculated by the received frame frequency ( FI ) and standard frequency ( F0 ) in DDS.
For example, if Ft is 74.25MHz,corresponding to that nx=n0.If the Ft has changed, then the number of “0” obtain by equation (2).
Drawing a conclusion, if the input frequency (Ft) changed from 74.17MHz to 74.32MHz,the number of “0” appending to the end of frame change from 14363 to 17212.
[4] Elson J,Girod L,Estrin D.Fine-Grained network time sychroniztaion using broadcasts[C].the 5th Symp.on Operating Systems Design and Implementation.ACM Press,2002.147-163
So the number of “0” that must be removed is calculated by the received frame frequency ( FI ) and standard frequency ( F0 ) in DDS.
For example, if Ft is 74.25MHz,corresponding to that nx=n0.If the Ft has changed, then the number of “0” obtain by equation (2).
Drawing a conclusion, if the input frequency (Ft) changed from 74.17MHz to 74.32MHz,the number of “0” appending to the end of frame change from 14363 to 17212.
[4] Elson J,Girod L,Estrin D.Fine-Grained network time sychroniztaion using broadcasts[C].the 5th Symp.on Operating Systems Design and Implementation.ACM Press,2002.147-163
Online since: August 2013
Authors: Yu Xian Zhang, Jing Hai Zhou, Xian Hong Meng, Rui Xu
Use block molding, vibrating close-grained, after 24h bosses.
The main purpose of this study is to establish the surplus compressive strength and fatigue cyclic number relationship (except for special instructions, this article mentioned in the residual strength shall mean residual static load strength).
Table.1 Experimental result of uncorroded specimens group stress level result average 1 number 1-1 1-2 1-3 32.1 σ0(MPa) 37.3 29.4 29.6 2 S1=0.75 number 2-1 2-2 2-3 13560 Nf 14581 10339 15761 3 S1=0.75 number 3-1 3-2 3-3 31.1 σr(MPa) 35.6 28.7 28.9 Table.2 Experimental result of corroded specimens group stress level result average 4 number 4-1 4-2 4-3 26.5 σ0(MPa) 28.8 28.1 22.6 5 S1=0.75 number 5-1 5-2 5-3 9007 Nf 7460 10835 7726 6 S1=0.75 number 6-1 6-2 6-3 25.8 σr(MPa) 27.7 20.9 28.8 Data processing.
In practical engineering, magnesium ion on concrete corrosion should not ignore, should consider the corresponding protective measures, to ensure the project can achieve the desired use fixed number of year.
The main purpose of this study is to establish the surplus compressive strength and fatigue cyclic number relationship (except for special instructions, this article mentioned in the residual strength shall mean residual static load strength).
Table.1 Experimental result of uncorroded specimens group stress level result average 1 number 1-1 1-2 1-3 32.1 σ0(MPa) 37.3 29.4 29.6 2 S1=0.75 number 2-1 2-2 2-3 13560 Nf 14581 10339 15761 3 S1=0.75 number 3-1 3-2 3-3 31.1 σr(MPa) 35.6 28.7 28.9 Table.2 Experimental result of corroded specimens group stress level result average 4 number 4-1 4-2 4-3 26.5 σ0(MPa) 28.8 28.1 22.6 5 S1=0.75 number 5-1 5-2 5-3 9007 Nf 7460 10835 7726 6 S1=0.75 number 6-1 6-2 6-3 25.8 σr(MPa) 27.7 20.9 28.8 Data processing.
In practical engineering, magnesium ion on concrete corrosion should not ignore, should consider the corresponding protective measures, to ensure the project can achieve the desired use fixed number of year.
Online since: July 2016
Authors: Yi Xiang Gan, Wei Jing Dai, Dorian Hanaor
The thermo-mechanical properties of granular materials with macroscopic particle sizes (above 1 mm) have been investigated experimentally and theoretically, but knowledge remains limited for materials consisting of micro/nano-sized grains.
An approximation based on the Knudsen number is used to predict the gas phase heat conductance.
In such situation, the contact region consists of a finite number of nanoscale contact spots.
In ABAQUS, the gap conductance is varied with Knudsen number Kn to simulate the gas heat transport at different gas pressure.
The Knudsen number has been incorporated in the gas conduction model to include the influence of gap distance, gas pressure and temperature.
An approximation based on the Knudsen number is used to predict the gas phase heat conductance.
In such situation, the contact region consists of a finite number of nanoscale contact spots.
In ABAQUS, the gap conductance is varied with Knudsen number Kn to simulate the gas heat transport at different gas pressure.
The Knudsen number has been incorporated in the gas conduction model to include the influence of gap distance, gas pressure and temperature.
Online since: June 2014
Authors: Zbyněk Keršner, Libor Topolář, Pavel Rovnaník, Pavel Schmid
Quartz sand with a maximum grain size of 2.5 mm was used as aggregate.
‘Number of overshoots’ refers to the number of pulses emitted by circuitry measuring the signal amplitude that exceed the threshold number for a given time interval.
The presence of a higher number of microcracks in the specimen can be inferred from the higher acoustic emission activity.
Fig. 3 shows the number of overshoots and the load vs. deflection of the samples.
It is evident in the case of the V samples that at the beginning of loading the number of overshoots was affected mainly by the drying of the AAS matrix.
‘Number of overshoots’ refers to the number of pulses emitted by circuitry measuring the signal amplitude that exceed the threshold number for a given time interval.
The presence of a higher number of microcracks in the specimen can be inferred from the higher acoustic emission activity.
Fig. 3 shows the number of overshoots and the load vs. deflection of the samples.
It is evident in the case of the V samples that at the beginning of loading the number of overshoots was affected mainly by the drying of the AAS matrix.