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J. Comput. Sci. Eng.
Vol. 40 (2019) 1041-1050 |
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Statistical inference on repeated regular two-level
factorial experiments |
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Yuran Zu, Xinmin Li |
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J. Comput. Sci. Eng. 40 (2019) 1041-1045！Published
10 Aril 2019 |
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Abstract:
In this paper, we proposed two methods for hypothesis tests on the active
effect that effect the mean of the response in the
replicated regular two-level factorial experiments. The
first method was proposed based on bootstrap, and the
second method was proposed based on student's t test.
Simulation results show that the two approaches have
better control rate under the small sample size. |
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Keywords:
Bootstrap; Student's t test; Control Rate; Factorial
experiment.
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CSE-PDF |
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NOx sensing on pure and Al doped g-C3N4
surfaces |
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Zhenze Liu, Yuan Liang, Juan Feng, Fenghui Tian |
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J. Comput. Sci. Eng. 40 (2019) 1046-1050！Published
10 April 2019 |
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Abstract:
In this work, we studied pure and Al doped
graphitic carbon nitride (g-C3N4)
for NOx sensing using density functional theory (DFT)
calculations. The calculation results show that pure g-C3N4
can achieve high-efficiency sensing of NO and NO2,
and the charge transfer amounts are 0.291e and 0.226e,
respectively. NO2 adsorbed to the surface of
Al-doped g-C3N4, chemical
adsorption occurs, and Al-O bonds were formed with Al
atoms. The charge transfer reaches 0.469e, and the
sensing effect is doubled. Therefore, pure g-C3N4
can achieve high-efficiency sensing for both NO and NO2,
while Al-doped g-C3N4 is a
promising material forNO2 ultra-high sensing. |
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Keywords:
NOx sensing; g-C3N4 surface; Al
doped; Density functional theory.
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CSE-PDF |
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Particle Swarm
Optimization for Dynamic Differential-Algebraic Equations of
Multibody Systems |
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Xiaoxiao Zhang, Jieyu Ding |
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J. Comput. Sci. Eng. 40 (2019) 1051-1055！Published
20 April 2019 |
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Abstract:
Aiming at solving the differential-algebraic equations of
multi-body system dynamics, the solution method based on
particle swarm optimization is studied. Firstly,
Lagrange interpolation is performed on generalized
coordinates and generalized velocity, and the Gauss
numerical integration method is combined to transform
the problem of solving differential algebraic equations
into solving optimization problems. Then the particle
swarm algorithm is used to solve the problem optimally.
Finally, through the multi-body system simulation
experiment of the planar two-link manipulator, it is
verified that the particle swarm optimization algorithm
not only maintains the constraint but also guarantees
the energy precision in solving the dynamic equation.
The results show that the intelligent optimization
algorithm has a good application prospect in solving
multi-body dynamics problems. |
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Keywords:
Multibody system dynamics; Differential algebraic
equations; Particle swarm optimization.
:
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CSE-PDF |
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！！ from ACSS |