Exeley Inc.

ECKES, Anna

LANDSCAPE ARCHITECTURE IN PROTECTION OF PEDESTRIAN ZONES AGAINST ACTS OF TERRORISM

Jijun, Xue

2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
86 
 
A Research of Perforation Plan-decision Based on Grey Cluster Relation 
Xue Jijun 
Mechanical Engineering College 
Xi’an Shiyou University 
Xi’an, 710065, Shanxi, P.R.China 
e-mail: xue_jijun@163.com 
 
 
Abstract—Perforation completion in oil and gas wells is the 
most important way of completion engineering, the 
optimization of perforation completion’s designing is 
influenced by a variety of factors. In order to get the ideal 
effect of perforation operation, in this paper, a Perforation 
plan-decision based on Grey Cluster Relation is putted 
forward. It aims to provide a scientific guidance for the 
Perforation. The simulation experimental results show that 
new models are effective, which offer one kind of science 
decision-making foundation for petroleum Perforation. 
Keywords-Perforating Operation; Grey Cluster Relation; 
Perforation Plan-decision 
I. INTRODUCTION 
Perforated well completion As the most extensive and 
major method of the well’s completion, the reasonable 
selection of parameters for the program has great meaning of 
improving efficiency and reducing costs[1][2]. By 
establishing a quantitative regression model to study the 
relationship between the parameters of the perforation and 
the production ratio, this algorithm can also analysis how 
different factors (perforation elasticity, perforation 
penetration, shot density, perforation  diameter, perforation 
phase angle) act on the production ratio and casing strength 
coefficient. It provides a reliable theoretical basis for the 
perforation parameter optimization, and gives different 
perforation completion optimization schemes [3]. 
Due to the mutual restriction of different parameters, the 
current subjective decision-making for perforation program 
can’t make all the factors to achieve the best at the same 
time. In order to solve the above problems and reduce the 
subjective influence of the decision maker, maximize the 
productivity ratio[4], a Perforation Plan-decision Based on 
Grey Cluster Relations proposed[5-7]. 
II. PERFORATION PLAN-DECISION BASED ON GREY 
CLUSTER RELATION 
Perforation optimization needs to confirm a solution to 
maximize the production capacity. This solution depends on 
many factors and the main influencing factors are hole depth, 
pore size, pore density, phase angle, formation heterogeneity, 
drilling pollution degree and depth, perforation compaction 
thickness and degree. All these factors are acting on the 
decision-making of the solution on the same time. 
Perforation Plan-decision based on Grey Cluster has 
made the model of perforation parameters and the oil well 
productivity. Gray parameters are clustered in the 
parameters of the perforation scheme, and the evaluation 
function is established to design the optimal scheme [8-10]. 
A. Building of model 
First simulating and calculating the productivity ratio of 
oil and gas, then making a non-linear regression analysis, 
According to whether perforation penetration penetrate the 
drilling zone or not, an equation can be established, it 
indicates the relationship between perforating parameters 
and capacity. 
1) The regression equation when the perforation 
penetration does not penetrate the drilling zone: 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
87 
 

2 2 2 2
PR=0.000156Y -0.000452 +0.000000205 +0.319 -0.103 -0.0009512 +0.000002378
2 2 2
-0.25+0.00148 -0.00000123 +0.00958 -0.0000998 -0.00467 lg( )+0.0178 -0.000296
2
+0.00195 -0.00001 -2*
W W K K r r
h h h zr zr w w
K K K K X K K K
s s m m w zr j j
X X
w w
2 2
0.000828 *lg( )+0.4 g( )+0.3488 -0.1745 +0.69 -0.35
-0.00778
X K l K Y Y W W
w zr zr c c c c
Y
h 
2) The regression equation that perforation penetration has penetrated the contaminated zone of drilling： 

2 2
PR=-0.25+0.00191 -0.00000136 +0.01665 -0.000173 0.00856 lg(K )+0.0201
zr
2 2 2
-0.000335 +0.00211 -0.0000108 -0.001774 lg(K ) +0.5lg(K )+0.512 -0.253
zr zr
2
+0.3315 -0.168 -0.00963 +0.000193
K K K K K K
s s m m m j
K X X X Y Y cj w w w c
W W Y Y
c c h
2 2 2
-0.000841 +0.000000714 +0.406K -0.135K
zr zr
2
-0.0009736 +0.00000243  
W W
h h h
r r
w w 
The quantitative relationships between parameters 
(perforation penetration KS, perforation aperture Kj, 
perforation phase Xw, perforation compaction degree Yc, 
perforation compaction thickness Yh, drilling damage 
thickness Wh, drilling pollution degree Wc, shot density 
Km, borehole radius rw, formation permeability Kzr) and 
the oil production ratio PR is the basis for the 
optimization of perforating parameters. 
B. Perforation program base on Grey Cluster Relation 
The main factors in the decision-making of the 
perforation plan are six factors: perforation ratio, 
perforation phase angle, shot density, perforation 
penetration, perforation diameter and casing strength 
decreasing coefficient, which are expressed by attributes 
1x , 2
x
, 3
x
, 4
x
, 5
x
 , 6
x
 respectively. Initial feature 
object matrix D is made like this:  
11 12 13 1n
21 22 23 2
31 32 33 3
41 42 43 4
51 52 53 5
61 62 63 6
n
n
n
n
n
x x x x
x x x x
x x x x
D
x x x x
x x x x
x x x x
 
 
 
 
 
 
 
 
  
 







In the formula, ij
x
 represents  j th attribute of the 
ith scheme; in the j  scheme 1 j
x
 represents the 
productivity ratio, 2 j
x
 is the phase angle, 3 j
x
 is the 
perforation diameter, 4 j
x
 is the hole depth, 5 j
x
 is the 
aperture, and 6 j
x
 is the casing strength reduction coefficient. 
There are n  scheme and 6 attributes. 
As the different dimensions will have an impact on 
decision-making, so the formula (4) - (6) are used to D for 
normalization. 
The normalization of attribute data based on the different 
effects caused by different attributes, the formula (4) shows the 
method to normalize production ratio, which called upper limit 
method. Inherent properties such perforation phase angle, shot 
density, perforation penetration, perforation diameter are 
concluded by extreme conversion method, shown as formula 
(5). Casing strength decreasing coefficient, as a cost-type 
attribute, calculated by the lower limit method, shown as 
formula (6). 
1j
1
1
max( )j
j
x
r
x


max( ) min( )
ij
ij
ij ij
x
r
x x



6
6
6
min( )
j
j
j
x
r
x


2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
88 
 
In the formula, 2 5,i j n   , the normalized 
decision matrix can be calculated: 
6 n( )
ij
R r 
. 
The Grey Clustering analysis is used to classify the 
attributes and the similar factors can be classified and 
simplified. 
1) Initialize processing：  
1
2 5 ,
 
  
ij ij ir r r
i j n 
2) Calculate the gray absolute correlation degree ik

 
of any two parameter index data Ri and Rk sequence 
(1 ,1 6,k i j n    )： 
1
2
1
n
2
| | | 0.5 * |
| | | ( ) 0.5 * ( )|
1 | | | |
1 | | | | | |
n
i ij in
j
n
k i kj ij ij k in
j
i k
ik
i k i k
S r r
S S r r r r r
S S
S S S S






 


    

  
 
   



3) Establishing attribute correlative sequence matrix 
according to the above gray absolute correlation 
degree: 
12 13 14 15 16
23 24 25 26
34 35 36
45 46
56
1
1
1
1
1
1
    
   
  

 

 
 
 
 
 
 
 
 
 
  
The critical value 
 r 0,1
, in pursuit of  accuracy 
the value of r is higher than 0.5, the higher the r value, the 
more accurate the classification is , and the accurate value 
of r is determined by actual data, the Ri and Rk classified 
as similar attributes; when ij

 ≥ r. 
4) Several attributes can be merged by the calculation 
above, and an attribute can be chosen to instead of 
other similar attributes. 
A new feature matrix D’ and new normalization matrix 
' ，
m n( )
ij
R r 
 is established according to the Grey Clustering 
analysis, where m is the number of attributes and n is the 
number of schemes.   
5) Computing information entropy iE  and 
weight i

(1 ,i m j n   ): 
'' ''
1
'
''
'
1
1
ln( )
ln(n)
n
i ij ij
j
ij
ij m
ij
j
E r r
r
r
r



 









In particular, when
'' 0
ij
r 
, let 
'' ''ln( ) 0
ij ij
r r 
.  
1
1
1
(1 )
i
i m
i
i
E
i m
E



  


And 0 1i  , 1 2 m
1     
, 1 6m  . 
Establish an evaluation function Zk: 
'
i
1
, 1 , 1
m
k ik
i
Z r i m k n

    

When the evaluation function value Z(Rk) is larger, the 
corresponding scheme is better. The program has the largest 
value of Z(k) is chosen as the final construction program. 
III. SIMULATION EXPERIMENT 
White XX well in Chang-qing Oilfield, the reservoir depth 
of middle layer is 1 884.5m, the total thickness is 9.5 m, the 
thickness of the perforated zone is 3.0 m, the porosity is 
13.41%, reservoir drainage radius is 200m, well-bore radius is 
0.111 m, the pressure of formation is 13.073 MPa, the crude oil 
saturation pressure is 9.86 MPa, drilling pollution depth is 
69.5mm, the drilling pollution degree is 0.6. The casing 
strength is 47.8MPa, reservoir heterogeneity is 0.7( vertical 
permeability / horizontal permeability), the water saturation is 
30.21%, rock Poisson's ratio is 0.5, the inclination is 5º, the oil 
viscosity is 1.03 MPa.S, the perforation optimization scheme is 
shown as Table 1. 
 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
89 
 
TABLE I. PERFORATION TABLE OF WHITE XX  
   Attributes      
 
Program 
productivity 
ratio 
perforation 
phase angle
（degree） 
shot density 
（holes/m） 
perforation 
penetration
（mm） 
perforation 
diameter 
（mm） 
casing strength 
decreasing 
coefficient（%） 
A1 0.5193 120 26 328.68 10.68 5.00 
A2 0.5188 90 26 328.68 10.68 6.10 
A3 0.5152 120 32 328.68 10.68 5.70 
A4 0.5150 60 26 328.68 10.68 5.70 
A5 0.5147 90 32 328.68 10.68 5.30 
A6 0.5108 60 32 328.68 10.68 5.00 
A7 0.5071 120 36 328.68 10.68 4.50 
A8 0.5065 90 36 328.68 10.68 4.20 
A9 0.5045 120 26 267.55 9.42 4.60 
A10 0.5039 90 36 267.55 9.42 4.30 
A11 0.5024 60 26 328.68 10.68 4.00 
A12 0.5001 120 32 267.55 9.42 4.00 
A13 0.4998 60 36 267.55 9.42 4.10 
A14 0.4995 90 32 267.55 9.42 3.80 
A15 0.4952 60 32 267.55 9.42 3.60 
A16 0.4912 120 26 267.55 9.42 3.10 
A17 0.4905 90 26 267.55 9.42 3.00 
A18 0.4874 120 16 328.68 10.68 2.60 
A19 0.4867 90 16 328.68 10.68 2.50 
A20 0.4861 60 26 267.55 9.42 2.90 
A21 0.4821 60 16 328.68 10.68 2.40 
A22 0.4695 120 16 267.55 9.42 1.80 
A23 0.4688 90 16 267.55 9.42 1.80 
A24 0.4637 60 16 267.55 9.42 1.70 
 
The initial feature matrix
6 24(x )
ij
D 
 can be 
constructed from the data in Table 1 and the results are 
shown in Table 2. 
The feature object matrix 6 24( )ijR r   is 
established by the above equation (4) - (6) and the initial 
feature matrix D, is shown as table 3. The index data 
association matrix is established by the above equations 
(7) and (8): 
1 0.9953 0.9499 0.9937 0.9937 0.9976
1 0.5841 0.8571 0.8571 0.9176
1 0.7747 0.7747 0.9602
1 1 0.9696
1 0.9696
1

 
 
 
 
  
 
 
 
 
 
According to the correlation degree matrix, take the critical 
value 0.8r , R2, R4 and R5 can be regarded as same class, 
then take R2 represent this class. Then the influencing 
attributes of perforation program are adjusted to: productivity 
ratio R1, perforation phase angle R2, shot density R3, casing 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
90 
 
strength decreasing coefficient R6. Establishing new 
normalization matrix R’=(rij)4×24, shown as table 4. 
TABLE II. ESTABLISH THE INITIAL FEATURE MATRIX D 
0.5193 120 26 328.68 10.68 5.50
0.5188 90 26 328.68 10.68 6.10
0.5152 120 32 328.68 10.68 5.70
0.5150 60 26 328.68 10.68 5.70
0.5147 90 32 328.68 10.68 5.30
0.5108 60 32 328.68 10.68 5.00
0.5071 120 36 328.68 10.68 4.50
0.5065 90 36 328.68 10.6
D 
8 4.20
0.5045 120 26 267.55 9.42 4.60
0.5039 90 36 267.55 9.42 4.30
0.5024 60 26 328.68 10.68 4.00
0.5001 120 32 267.55 9.42 4.00
0.4998 60 36 267.55 9.42 4.10
0.4995 90 32 267.55 9.42 3.80
0.4952 60 32 267.55 9.42 3.60
0.4912 120 26 267.55 9.42 3.10
0.4905 90 26 267.55 9.42 3.00
0.4874 120 16 328.68 10.68 2.60
0.4867 90 16 328.68 10.68 2.50
0.4861 60 26 267.55 9.42 2.90
0.4821 60 16 328.68 10.68 2.40
0.4695 120 16 267.55 9.42 1.80
0.4688 90 16 267.55 9.42 1.80
0.4637 60 16 267.55 9.42 1.70


T

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
TABLE III. ESTABLISHMENT OF FEATURE OBJECT MATRIX R 
1 2 1.3 5.3767 8.4762 2.9412
0.9990 1.5 1.3 5.3767 8.4762 3.5882
0.9921 2 1.6 5.3767 8.4762 3.3529
0.9917 1 1.3 5.3767 8.4762 3.3529
0.9911 1.5 1.6 5.3767 8.4762 3.1176
0.9836 1 1.6 5.3767 8.4762 2.9412
0.9765 2 1.8 5.3767 8.4762 2.6471
0.9
R 
754 1.5 1.8 5.3767 8.4762 2.4706
0.9715 2 1.3 4.3767 7.4762 2.7059
0.9703 1.5 1.8 4.3767 7.4762 2.5294
0.9675 1 1.3 5.3767 8.4762 2.3529
0.9630 2 1.6 4.3767 7.4762 2.3529
0.9624 1 1.8 4.3767 7.4762 2.4118
0.9619 1.5 1.6 4.3767 7.4762 2.2353
0.9536 1 1.6 4.3767 7.4762 2.1176
0.9459 2 1.3 4.3767 7.4762 1.8235
0.9445 1.5 1.3 4.3767 7.4762 1.7647
0.9386 2 0.8 5.3767 8.4762 1.5294
0.9372 1.5 0.8 5.3767 8.4762 1.4706
0.9361 1 1.3 4.3767 7.4762 1.7059
0.9284 1 0.8 5.3767 8.4762 1.4118
0
T
.9041 2 0.8 4.3767 7.4762 1.0588
0.9028 1.5 0.8 4.3767 7.4762 1.0588
0.8929 1 0.8 4.3767 7.4762 1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
TABLE IV. DEALS WITH THE FEATURE MATRIX BY GREY CLUSTER 
RELATION R’ 
'
1 2 1.3 2.9412
0.9990 1.5 1.3 3.5882
0.9921 2 1.6 3.3529
0.9917 1 1.3 3.3529
0.9911 1.5 1.6 3.1176
0.9836 1 1.6 2.9412
0.9765 2 1.8 2.6471
0.9754 1.5 1.8 2.4706
0.9715 2 1.3 2.7059
0.9703 1.5 1.8 2.5294
0.9675 1 1.3 2.3529
0.9630 2 1.6 2.3529
R
0.

9624 1 1.8 2.4118
0.9619 1.5 1.6 2.2353
0.9536 1 1.6 2.1176
0.9459 2 1.3 1.8235
0.9445 1.5 1.3 1.7647
0.9386 2 0.8 1.5294
0.9372 1.5 0.8 1.4706
0.9361 1 1.3 1.7059
0.9284 1 0.8 1.4118
0.9041 2 0.8 1.0588
0.9028 1.5 0.8 1.0588
0.8929 1 0.8 1







T






 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The attribute weight vectors  =(0.0036,0.2826, 
0.2797,0.4340) are calculated according to formulas (10) and 
(11).  
Then the evaluation function Z is established according to 
(12): 
Z={2.2090,2.2348,2.4716,2.1051,2.2282,2.0103, 
2.2211,2.0032,2.1068,2.0288,1.6710,2.0375,1.8364,1.8451,1.6
527,1.7238,1.5569,1.4562,1.2894,1.3900,1.1225,1.2519,1.1105
,0.9437}. The optimal scheme is A3 because the Z value of 
scenario A3 is the largest. It means under the existing 
formation conditions, the best perforation program is: 
perforation bullet SYD127-1, phase angle 120º, hole density 
32m, wearing depth 328.68mm, aperture 10.68mm. 
IV. CONCLUSION 
In this paper, a Perforation plan-decision based on Grey 
Cluster Relation is putted forward. This method can be widely 
used to predict the productivity of wells under different 
perforation conditions, determine the perforating efficiency of 
perforated bombs, and study how different factors (the 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
91 
 
perforation elasticity, perforation penetration, shot density, 
perforation diameter, perforation phase angle) impose 
influence to productivity ratio, and casing strength 
decreasing coefficient. According to the pending reservoir, 
it also let the oil production capacity to achieve the higher 
perforation operating parameters and process of excellent 
combination. It also saves a lot of manpower, materials 
and time cost, and provide the theoretical basis for the 
design of completion perforation construction. 
 
REFERENCES: 
[1] Deng Guang-yong. Application of Optimized Perforation 
Technology in Oilfield Production[J]. New Technology & New 
Products of China, 2015(17):90-90. 
[2] Tian Xin-ru. Influence of Optimization Design of Perforation 
Scheme on Oil and Gas Well Productivity[J]. China Petroleum 
and Chemical Standard and Quality, 2017, 37(3):22-23. 
[3] Cuan Ying, Wang Li-fan.Selection of Perforation Plan Based on 
MOPSO and TOPSIS Decision Making[J]. Science Technology and 
Engineering, 2013, 13(25):7302-7306. 
[4] Wang Zhong. The Application of Fuzzy Multiple Attribute Decision 
Making to Optimization of perforated completion[D]. Xi’an Shiyou 
University, 2008. 
[5] Chou J R. Kansei Clustering Using Fuzzy and Grey Relation 
Algorithms[J]. Journal of Interdisciplinary Mathematics, 2015, 
18(6):719-735. 
[6] Gong Y C, Ren Z Y, Fei D, et al. Grey relation-projection pursuit 
dynamic cluster method for multiattribute decision making assessment 
with trapezoidal intuitionistic fuzzy numbers[J]. Control & Decision, 
2015. 
[7] Xiao-Jing L I, Liu L J. Comprehensive Quality Evaluation of 
Intersections Based on Grey Relation Degree Clustering[J]. Journal of 
Shandong Jiaotong University, 2013. 
[8] GUO San-dang,WANG Ling-ling,LIU Si-fen et al.Grey Cluster Analysis 
Base on the Biggest Relational Grades[J]. Mathematics in Practice and 
Theory, 2013, 43(6):195-201. 
[9] LI Xue-mei; DANG Yao-guo; WANG Jun-jie.Grey relational clustering 
model for panel data clustering on indicators and its application[J]. 
Control and Decision, 2015, 30(8):1447-1452.  
[10] Li Xue-mei. Grey multivariable modeling and its application[D]. 
Nanjing University of Aeronautics and Astronautics The Graduate 
School College of Information Science and Technology, 2015. 
 
 
 
 
 


A Research of Perforation Plan-decision Based on Grey Cluster Relation

Wang, Qinqin

Su, Xiaohui

Research and Application of SO2 Concentration Monitoring Algorithm in Flue Gas

Bo, Xing

2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
122 
 
The Reform and Innovation of Ideological and Political Teaching Under the 
Multimedia 
Xing Bo 
Ideological and Political Department 
Xi’an Peihua University 
Xi’an, 710125, Shaanxi, China 
e-mail: 932587282@qq.com 
 
 
Abstract—With the continuous development of modern 
information technology, Computer network and multimedia 
technology have been used more and more widely. Due to the 
diversity, integration, control, interactivity, and real-time 
characteristics of multimedia technology, the application of 
multimedia technology in teaching has greatly changed the 
traditional teaching mode of instilling knowledge to students in 
a single way and in a simple manner. It used its super 
integrated management of text, text, graphics, images, video, 
sound etc., making teaching intuitive, novelty, diversity and 
vivid characteristics, can give full play to the students' thinking 
ability, cognitive ability and the ability to analyze problems, 
greatly improve the quality of teaching. Applying multimedia 
technology to the ideological and political course in colleges 
and universities can help improve the expressiveness and 
appeal of teaching content, inspire students' interest in 
learning, increase the credibility and timeliness of teaching 
content, and create a multidimensional interactive ideological 
and political classroom model. This will enable the teaching of 
ideological and political courses in universities to be carried 
out more effectively. Therefore, we should effectively use 
multimedia technology to assist our teaching in ideological and 
political education. 
Keywords-Multimedia Technology; Ideological and Political 
Courses in Colleges and Universities; Reform Strategy 
 
I. INTRODUCTION 
With the extensive application of multimedia technology 
in the teaching class, the ideological and political teaching in 
Colleges and universities has radiate new vitality and vitality, 
from the traditional chalk into today's participatory teaching, 
from the traditional single teaching mode into today's 
multi-dimensional interactive teaching mode, greatly 
improve the efficiency of ideological and political course 
teaching. But at the same time, it may inevitably bring about 
many problems, for these exist in the ideological and 
political class multimedia technology problems, the author 
puts forward some solving strategies, believe that such a tool 
as long as reasonable use of multimedia technology, the 
ideological and political education in colleges and 
universities can become more productive. 
 
 
 
 
 
Figure 1. Network multimedia technology assisted teaching map 
 
II. THE ROLE OF MULTIMEDIA TECHNOLOGY IN THE 
TEACHING OF IDEOLOGICAL AND POLITICAL COURSES 
A. Motivate students' interest in learning 
In traditional ideological education courses, teachers 
often use sermon teaching mode, which makes classroom 
teaching boring and boring, so that class becomes a teacher's 
"one-man show", so that students lack enthusiasm and 
initiative, and classroom participation is extremely low. 
Those students often do not know after class, so the quality 
and efficiency of teaching can not be achieved well. 
The famous Chinese educator Confucius once said, 
"people who understand it are not as good as those who love 
it, and those who love it are not as good as those who enjoy 
it." The interest of learning can awaken the students' thirst 
for knowledge and thus improve the students' learning 
efficiency. Therefore, the ideological and political classroom 
with a relatively dull content should pay more attention to 
improving the students' interest and stimulating the curiosity 
of the students. With the use of new media technology, 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
123 
 
teachers can transform teaching contents into images, sounds 
and characters by making PPT and so on. This relatively 
more novel and lively teaching methods, to help students use 
all kinds of sense organs participate in teaching activities, 
passively accept to active learning, make the ideological and 
political education is more interesting and stimulate the 
students interest in learning for ideological and political 
education. 
B. Enhancing the credibility and timeliness of teaching 
content 
In the traditional ideological and political education class, 
because most of the teachers adopt the way of oral teaching, 
many of the views in the textbook are not so convinced by 
the students. But the multimedia can go beyond the 
limitations of time and space, make originally not intuitive 
knowledge of ideological and political teaching illustrated, 
by taking advantage of the news, documentaries, the chart 
data added the textbook knowledge, make both organically, 
let the students "seeing is believing", greatly increase the 
credibility of the teaching content. The ideological and 
political course in Colleges and universities is a curriculum 
which pays great attention to timeliness. However, textbook 
reprinting is a very time-consuming and laborious process. 
This leads to the fact that only by learning textbooks cannot 
be made of the effect of ideological and political education 
to keep pace with The Times .However, in the era of 
information technology, this situation has a new method of 
improvement, that is, the use of multimedia technology to 
innovate ideological and political education class. Because 
multimedia has the dynamic function of spreading the 
political, economic, cultural and social situations in the 
world, so teachers can take all kinds of current hot topics on 
the Internet as examples, keep pace with the social reality, 
and make ideological and political education advance with 
the times. 
C. Deepening students' understanding of ideological and 
political issues 
A large part of the ideological and political problems are 
very abstract, and it is often difficult to be understood by the 
students immediately through the teacher's explanation. For 
example, it is very difficult for students to understand the 
"law is the inevitable connection of things, phenomena and 
processes", but by listing some occasional events by pictures, 
it is easy to deepen students' understanding of this concept 
through asking and answering questions with students. In 
fact, many abstract problems in Ideological and political 
education can be solved by similar multimedia technology. 
Because of the intuitive features of the multimedia 
technology itself, it can easily establish the connection 
between the content and life, and create a life situation 
related to the teaching content. It enables students to better 
understand some abstract ideological and political problems, 
so that students can master the difficult points in the 
ideological and political process without difficulty, and 
improve the teaching quality and efficiency of teachers. 
 
 
 
Figure 2. Multimedia technology assisting the teaching process of 
Ideological and Political Course 
D. Improving students' memory of teaching content 
The so-called memory "is the process of encoding, 
storing and extracting the input information of the outside 
world, which is divided into three types: instantaneous 
memory, short-term memory and long-term memory." In the 
process of ideological and political teaching, how to make 
the students' memory of teaching content disappear in the 
darkness after the "registration" in the mind, and even to the 
point that they have not forgotten for a long time, it has been 
the common pursuit of all teachers. The new media 
technology using the echoism tone even dynamic video 
several angles to promote the students' memory in teaching 
content, and there is conducive to students through a variety 
of ways to extract content. Let students "bind" what they 
have learned in various ways to common knowledge, 
increase the retention rate of students' knowledge, and 
improve the efficiency of education teaching. 
III. THE PROBLEMS OF THE APPLICATION OF NEW MEDIA 
TECHNOLOGY IN THE IDEOLOGICAL EDUCATION COURSE 
A. The content of multimedia courseware is not closely 
related to the teaching material 
Teaching materials are a basic basis for teachers' learning, 
so the courseware made by teachers should be based on 
teaching materials. However, in the college ideological 
education class, some teachers pay too much attention to the 
novelty of courseware, so that they ignore the basic 
principles of teaching materials. Multimedia technology is 
only a supporting tool for teaching, and it is a means for 
teachers to better illustrate the viewpoint of teaching 
materials. Making courseware out of teaching materials is 
not only a kind of behavior that is not only to the end of the 
book, but also may affect the students' attention to the 
teaching content and hinder the students' understanding of 
the teaching material. In addition, in ideological education 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
124 
 
courses in colleges and universities, the classroom teaching 
is only through the courseware is very serious, teachers 
control the multimedia courseware to recite, rather than lead 
students to comprehend teaching materials, the teaching 
process is completely out of teaching materials. In this way, 
not only the teacher's subjective status in the teaching is 
weakened, but also the humanistic care in the ideological and 
political teaching material can not be read. In the long run, 
the harm is great. 
B. The concept of teachers is old and multimedia becomes 
formalism 
Contrary to the multimedia as the center, the ideological 
education in colleges and universities also exist such 
teachers, they ignore the role of multimedia in modern 
teaching. They always insist on teaching by preaching. They 
believe that the traditional way of teaching is simpler and 
easier to write and say. A survey shows that there is such a 
general situation in Colleges and universities that some 
teachers never use multimedia technology in the normal 
teaching process. Only when public courses are exchanged, 
can they open multimedia in the classroom for a long time. 
In this case, multimedia technology is reduced to a 
formalism. This situation is particularly prominent in the 
ideological and political teaching. In addition, the imperfect 
multimedia facilities in Colleges and universities are also 
one of the reasons for this phenomenon. 
C. Teachers become manipulators of machines, weakening 
students' subjectivity 
In the process of using ideological and political education 
with multimedia technology, because the courseware is 
prepared in advance, the teacher pays great attention to the 
whole context of the courseware, which leads to the teacher 
in the teaching process only pay attention to control the 
multimedia to complete the rigid teaching process and 
neglected the interaction with students. Students often focus 
on copying the contents of courseware onto their notebooks, 
and often neglect their teacher's explanation. This is not 
conducive to the student's thinking in the teaching process, 
weakening the student's dominant position, resulting in the 
student's rational thinking can not be good development of. 
Under such circumstances, multimedia is completely 
reduced to "instilling knowledge machine to students". It not 
only plays a positive role in promoting ideological and 
political teaching, but also hinders the emotional 
communication between teachers and students, making 
classroom teaching more dull and boring. 
IV. EFFECTIVELY USING MULTIMEDIA TO REFORM 
IDEOLOGICAL AND POLITICAL EDUCATION 
A. The multimedia courseware should be combined with 
the content of the textbook 
As a form of better performance of the content of 
teaching materials, multimedia courseware must obey the 
contents of the teaching material and can not be divorced 
from the textbook. In order to stimulate students' interest and 
arouse students' curiosity, some teachers cite a lot of video 
and audio in multimedia courseware, blindly seeking novelty, 
ignoring the content of textbooks, and losing the humanistic 
care that should be contained in teaching. Therefore, teachers 
must constantly explore how to organically combine 
multimedia courseware and teaching materials. The 
multimedia technology is applied to the teaching material 
and the living situation which is closely related to the content 
of the teaching material and the thinking characteristics of 
the students. Teachers should use the textbook as the basis, 
supplemented by the life situation closely related to the 
content of the teaching materials, and follow the thinking 
characteristics of the students to use the multimedia 
technology. Only in this way, the instrumental role of 
multimedia technology in university ideological and political 
education can be truly displayed. 
B. Teachers should make full use of multimedia 
technology to cultivate modern talents 
In the modern era of information technology 
development, teachers should make full use of multimedia 
technology to improve the quality and efficiency of 
ideological and political teaching in colleges and universities. 
The teachers of the ideological and political education 
curriculum should get rid of the constraints of the profession 
and actively learn how to use a lot of media technology in 
the teaching class. Schools should also pay attention to the 
popularization of multimedia classrooms, make effective use 
of resources, and train teachers in multimedia operations so 
that teachers can better use multimedia technology for daily 
teaching. In addition, teachers should also be practiced to use 
multimedia technology to teach and reasonably allocate time 
for use of courseware, so that multimedia can be effectively 
used without distracting students' attention. 
C. Teachers should combine multimedia technology with 
teaching 
“Classroom is a powerful interactive environment 
composed of teachers, students, and the environment. It is a 
systematic form of education and a unique social 
organization.” No matter how much multimedia technology 
can play a role in the ideological and political class, we can 
never ignore the dominant position of teachers and students. 
After all, multimedia technology is only used as an auxiliary 
tool to help teaching, which is doomed it can only be a 
medium to connect teachers, students and teaching materials, 
rather than the main body of teaching activities. Especially in 
the teaching of ideological education, for the elaboration of 
viewpoints in the teaching materials, teachers cannot only 
use theories to convince people, and often they must also 
allow students to get the sublimation of their thoughts 
through emotional communication with students. The 
interaction and communication between teachers and 
students is an indispensable requirement for a qualified 
teaching activity. Teachers' language and body movements, 
even their eyes, play an indispensable role in multimedia 
technology. Therefore, we must not regard multimedia as 
omnipotent, and we must not let multimedia replace the 
status of teachers in teaching activities. 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
125 
 
V. CONCLUSION 
To sum up, multimedia technology plays an active role in 
improving teaching activities, which is an important way to 
improve teaching quality and stimulate students' interest in 
learning. The application of multimedia technology in 
teaching has changed the form of traditional teaching, 
showing the teaching contents in the form of comprehensive 
multimedia information, deepening the students' 
understanding of knowledge, and promoting the diversified 
and comprehensive development of teaching methods. It 
fully reflects the cooperative relationship between teaching 
and learning and arouses students' interest in learning. 
However, as a means of auxiliary teaching, multimedia 
technology is not a master key, it has its inevitable "double 
edge", if it is treated reasonably and used effectively, It can 
greatly improve the quality and efficiency of ideological and 
political education, on the contrary, it will only hinder the 
development of ideological and political teaching activities 
in colleges and universities. Only by studying deeply, 
reasonably designing, developing and using multimedia 
technology, and combining it with other teaching methods, 
can we optimize classroom teaching and embody the real 
value of multimedia technology assisted teaching. 
 
REFERENCES 
[1] Wang Hongmei and Zhang Jianlong, “Research on The Combination 
of Multimedia Technology and Traditional Teaching Methods”, 
Journal of Xinjiang Medical University, 2007(11). 
[2] Zhang Song, “Research on Construction and Application of 
Ideological and Political Education Network System Based on Video 
on Demand in Colleges and Universities”, Shenyang Normal 
University, 2011. 
[3] Ma Dandan and Bai Jing, “Design and Implementation of the 
Comprehensive Information Platform for Smelting Enterprises”, 
International Journal of Advanced Network Monitoring and Controls. 
Volume 2, No.4, 2017. 
[4] Han Dameng and Hu Wanqing, “On the Problems and 
Countermeasures of Multimedia Teaching in Ideological and Political 
Courses in Universities”, Professional technology, 2014(01). 
[5] Zhang Haiyan, “A Survey of the Status Quo of College Multimedia 
Network Teaching and Strategies of Optimizing Modes”, Journal of 
Changchun University of Science and Technology, 2011(12). 
[6] Li Yihu, “Research of Integration Technology between CATIA and 
TOOLMANAGER Based on CAA”, International Journal of 
Advanced Network, Monitoring, and Controls. Vol. 1, No. 1, 2016 . 
[7] Wei Zhang, “Fuel Cell Test System Based on AVR Single-Chip 
Computer”, International Journal of Advanced Network, Monitoring 
and Controls. Volume 2, No.4, 2017. 
[8] Jie Huang, “Research on Balanced Energy Consumption of Wireless 
Sensor Network Nodes Based on Clustering Algorithm”, International 
Journal of Advanced Network, Monitoring and Controls. Volume 2, 
No.4, 2017. 
[9] Jingwen Chen and Hongshe Dang, “The Design of Two Phase 
Chopping Regulation Voltage Soft Starter”, International Journal of 
Advanced Network Monitoring and Controls.Volume 02, No.2, 2017
.
 


The Reform and Innovation of Ideological and Political Teaching Under the Multimedia

Jing, Mu

Changyuan, Wang

2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
10 
 
Levenberg-Marquardt Method Based Iterative Square Root Cubature Kalman 
Filter and its Applications to Maneuvering Re-entry Target Tracking 
 
Mu Jing 
School of Computer Science and Engineering 
Xi’an Technological University 
Xi’an, 710032, China 
e-mail: mujing1977@163.com 
 
 
 
Wang Changyuan 
School of Computer Science and Engineering 
Xi’an Technological University 
Xi’an, 710032, China  
e-mail: cyw901@163.com 
 
 
 
Abstract—Levenberg-Marquardt (abbr.L-M) method based 
iterative square root cubature Kalman filter (abbr. 
ISRCKFLM) inherits the numerical stability of square root 
Cubature Kalman filter and effectively suppresses the 
influence of the larger initial estimation error and the 
nonlinearity of the measurement equation on the state 
estimation in the nonlinear state estimation due to obtaining 
the optimal state and variance estimates using the latest 
measurement through L-M method. We apply the ISRCKFLM 
algorithm to the state estimation of maneuvering re-entry 
target tracking, the simulation results demonstrate that the 
ISRCKFLM algorithm has better accuracy of state estimation, 
comparable to Unscented Kalman filter and square root 
Cubature Kalman filter, according to estimation error analysis 
of the position, velocity, drag coefficient, turn coefficient and 
climbing force coefficient, and has fast convergence rate. 
Keywords-Nonlinear Filtering; Square Root Cubature 
Kalman Filter; Levenberg-Marquardt Method; Maneuvering Re-
entry Targets Tracking 
I. INTRODUCTION  
The state estimate of maneuver re-entry target is highly 
non-linear filtering problem and has been much attention in 
the academic and engineering domain [1, 2]. Up to now, the 
commonly used non-linear filtering is the extended Kalman 
filter (EKF) [3]. The EKF is based on first-order Taylor 
approximations of state transition and observation equation 
about the estimated state trajectory under Gaussian 
assumption, so EKF may introduce significant bias, or even 
convergence problems due to the overly crude approximation 
[4]. Especially, for highly nonlinear problems such as state 
estimation of maneuver re-entry target, EKF may produce 
large filtering errors and even divergence. Based on the 
Unscented Transformation (UT), the Unscented Kalman 
filter (UKF) use a set of deterministic sampling points to 
approximate the posterior probability distribution of the 
system state, that is, the Sigma points are used to capture the 
mean and variance information of the state [5]. 
Recently, as a new way to solve the nonlinear estimation 
problem, cubature rules based cubature Kalman filter (CKF) 
proposed in [6] uses numerical multi-dimensional integral to 
approximate the recursive Bayesian estimation integrals 
under the Gaussian assumption. The CKF can solve high-
dimensional nonlinear filtering problems with minimal 
computational effort. Then the square root cubature Kalman 
filter algorithm (SRCKF) was proposed in order to improve 
the numerical stability [6]. 
On the other hand, in order to decrease the effect of 
initial estimation error and nonlinearity of measurement 
equation, Levenberg-Marquardt method based iterative 
square root cubature Kalman filter (ISRCKFLM) was 
developed on the basis of the SRCKF in [7]. In this paper, 
we apply the ISRCKFLM algorithm to state estimation of 
maneuver re-entry target. Simulations demonstrate that the 
ISRCKFLM algorithm can greatly improve the tracking 
accuracy of maneuver re-entry target and obtain fast 
convergence, compared with the UKF and SRCKF 
algorithms. 
The rest of the paper is organized as follows. We begin 
with a description of the ISRCKFLM algorithm in Section 2. 
Then we apply the ISRCKFLM algorithm to track re-entry 
ballistic target (RBT) with unknown ballistic coefficient and 
discuss the simulation results in Section 3. Finally, we draw 
conclusion in Section 4. 
II. L-M BASED ITERATIVE SQUARE ROOT CUBATURE 
KALMAN FILTER 
Consider the following non-linear dynamics system: 
 1 1( )k k k  x f x w  
 ( )k k k z h x v . 
where f and h are some known nonlinear functions; 
xn
k x and z
n
k z  is state and the measurement vector, 
respectively; 1kw  and kv  are process and measurement 
Gaussian noise sequences with zero means and covariance 
1kQ and kR , respectively, and 1{ }kw  and { }kv  are mutually 
uncorrelated. 
Suppose that the state distribution at k-1 time 
is
1 1 1 1
ˆ( , )Tk k k k   x x S S , Levenberg-Marquardt based 
Iterative square root cubature Kalman filter (ISRCKFLM) is 
described as follows. 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
11 
 
A. Time Update 
1) Calculate the cubature points and propagate the 
cubature points through the state equation 

, 1 1 1
ˆ
i k k i k   X S ξ x . 

*
, , 1( )i k i kX f X  
where 2[1] , 1 , 1, 2i i i xm m i m n   ξ ,the [1]i is a 
xn dimensional vector and is generated according to the way 
described in [2]. 
2) Evaluate the predicted state and square root of the 
predicted covariance 

*
,
1
m
k i i k
i


x X  

*
, 1([  ])k k Q kTria S χ S  
here,
, 1Q kS denotes a square-root factor of 1kQ and Tria() is 
denoted as a general triagularization algorithm. The matrix 
*
kχ is defined as: 
 * * * *1, 2, ,1 [   , , ]k k k k k m k km   χ X x X x X x  
3) Evaluate the modified covariance: 

1
1T T T
k k k k k k k
i
  
    
   
P I S S S S I S S  
where i is adjusting parameter. 
B. Measurement update 
1) Set the initial value as:
(0)ˆ
k kx x . 
2) Assuming the i-th iterate
( )ˆ i
kx , calculate the matrix 

1
( ) ( ) ( ) ( )ˆ ˆ ˆ( ) ( ) ( )i T i i T ik k h k h k k h k k

   
 L P J x J x P J x R  
3) Calculate the i-th iterate 
  
 
( 1) ( )
( ) ( ) ( )
( ) ( ) ( )
ˆ
ˆ ˆ( ) ( )( )
ˆ ˆ( ) ( )
i i
k k k
i i i
k k h k k k
i i i
i k h k k k k
  
  
  
x x L
z h x J x x x
I L J x P x x
 
4) Calculate the iteration termination condition 
 ( 1) ( )ˆ ˆi i
k k 
  x x or maxi N  
 and maxN are predetermined threshold and maximum iterate 
number, respectively. If the termination condition meets, the 
iterate return to 5); otherwise, set ( ) ( 1)ˆ ˆ=i ik k

x x , continue to 2). 
5) Calculate the state estimation at time instant 
 ( )ˆ ˆ N
k kx x  
6) Evaluate the cross-covariance and square root of 
innovation covariance at k time 
 ( )ˆ( )T T Nxz k k h kP S S J x  
 ( )
,
ˆ( ( ) )Nzz h k k R kChol    S J x S S  
7) Calculate the square root of covariance at k time 
 / /Tk xz zz zzK P S S  
 ( )
,
ˆ( ( ) )Nk k k h k k k R kChol    S S K J x S K S  
where symbol “/ ” represents the matrix right divide operator. 
III. APPLICATIONS TO MANEUVERING REENTRY TARGET 
TRACKING 
In the simulation, the trajectory of the maneuvering re-
entry generated in [8] is used with the same parameters, 
initial state and covariance estimation. To compare the 
performance of the ISRCKFLM with the UKF and SRCKF 
algorithms, we obtain the root mean square errors (RMSEs) 
in the position, velocity, drag coefficient, turn coefficient and 
climb coefficient showed in the Figure 1-5. All performance 
curves were obtained by averaging over 100 independent 
Monte Carlo runs. Table.1 lists the accumulated root mean 
square errors (ARMSEs). 
05101520253035
0
50
100
150
200
250
Altitude/km
R
M
S
E
 i
n
 p
o
s
it
io
n
/m
 
 
UKF
SRCKF
ISRCKFLM
 
Figure 1.  RMSE in Position 
From Figur.1-2, we can see the ISRCKFLM’s RMSEs in 
positon and velocity are lower than those of UKF and 
SRCKF algorithms, especially, the RMSEs of ISRCKFLM 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
12 
 
algorithm are effectively suppressed, and those of UKF and 
SRCKF algorithms have a big jump when the target 
experiences the high maneuver at altitude 23km and 10km. 
05101520253035
0
100
200
300
400
500
600
700
800
900
1000
Altitude/km
R
M
S
E
 i
n
 v
e
lo
c
it
y
/m
 s
-1
 
 
UKF
SRCKF
ISRCKFLM
 
Figure 2.  RMSE in Velocity 
05101520253035
0
0.2
0.4
0.6
0.8
1
1.2
Altitude/km
R
M
S
E
 i
n
 d
ra
g
 c
o
e
ff
ic
ie
n
t(
1
0 
-3
)/
k
g
m
-2
 
 
UKF
SRCKF
ISRCKFLM
 
Figure 3.  RMSE in Drag Coefficient 
05101520253035
0
0.5
1
1.5
2
2.5
3
Altitude/km
R
M
S
E
 i
n
 t
u
rn
 c
o
e
ff
ic
ie
n
t(
1
0 
-3
)/
k
g
m
-2
 
 
UKF
SRCKF
ISRCKFLM
 
Figure 4.  RMSE in Turn Coefficient 
As for the estimate on drag coefficient, turn coefficient 
and climbing coefficient of maneuver re-entry target, from 
Figure.3-5we can see the RMSEs of three algorithms 
decrease between 35km-30km at altitude, and the RMSEs of 
three algorithms reach the smallest at about 30km at altitude. 
Then the RMSEs of three algorithms increases when a dive 
and turn maneuver occurs on re-entry target, however, the 
ISRCKFLM’s RMSEs are lower than those of the other two 
algorithms. The RMSEs of all filters gradually increase when 
the target experiences an increased climb force at altitude 
16km-10km, but the ISRCKFLM’s RMSE increases slightly 
slower. After the maneuver was withdrawn, the RMSE of the 
three algorithms began to decline. 
05101520253035
0
1
2
3
4
5
6
Altitude/km
R
M
S
E
 i
n
 c
li
m
b
in
g
 c
o
e
ff
ic
ie
n
t(
1
0 
-3
)/
k
g
 m
-2
 
 
UKF
SRCKF
ISRCKFLM
 
Figure 5.  RMSE in Climbing Coefficient 
TABLE I.  ARMSES IN THREE FILTERS 
Algori-
thms 
ARMSEp
/m 
ARMSEv
/ms-1 
ARMSEd/
kgm-2 
ARMSEt
/kgm-2 
ARMSEc
/kgm-2 
UKF 42.3763 202.0984 
0.000277
31 
0.001000
4 
0.001468
8 
SRCKF 38.9467 184.3961 
0.000251
65 
0.000982
07 
0.001386
5 
ISRCKF
LM 
22.4556 141.8943 
0.000218
02 
0.000899
5 
0.001186
1 
Moreover, the ARMSEs of the ISRCKFLM in the 
positon, velocity, drag coefficient, turn coefficient and 
climbing coefficient are lower than those of UKF and 
SRCKF algorithms from Table.1. 
Therefore, on the basis of the simulation results presented 
in Figure.1-5, we can draw a conclusion that the ISRCKFLM 
yields on the superior performance over the UKF and 
SRCKF on the state estimation of maneuvering re-entry 
target. 
IV. CONCLUSION 
In this paper we apply the ISRCKFLM algorithm to 
maneuvering re-entry target tracking. The latest 
measurement are fully used in the ISRCKFLM algorithm, 
and innovation covariance and cross-covariance are 
improved in the iterative process, so we can obtain the 
optimal state estimation and covariance estimation.  
Simulation results demonstrate that the performance of 
ISRCKFLM algorithm is superior to UKF and CKF 
algorithms by analysis of errors in position, velocity, drag 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
13 
 
coefficient, turn coefficient and climbing coefficient, and has 
the faster convergence rate. 
ACKNOWLEDGMENT 
The authors would like to thank the support of fund of 
the State and Local Joint Laboratory of Advanced Network 
and Monitoring Control Engineering (No.GSYSJ201603); 
Natural Science Basic Research Program of Department of 
science and technology of Shaanxi Province - Youth 
Foundation (No.2017JQ6056); The Key Project of 
Department of Education of Shaanxi Province (No.16JF012). 
 
REFERENCES 
[1] Li XR, Jilkov VP. A survey of maneuvering target tracking - part II: 
ballistic target models.  Signal and Data Processing of Small Targets, 
2001, 4473:559-581. 
[2] Farina A, Ristic B, Benvenuti D. Tracking a ballistic target: 
comparison of several nonlinear filters. IEEE Transactions on 
Aerospace and Electronic Systems, 2002, 38(3):854-867. 
[3] Bar-Shalom Y, Li XR, Kirubarajan T. Estimation with Applications 
to Tracking and Navigation. New York: John Wiley &Son, Inc, 2001. 
[4] Athans M, Wishner RP, Bertolini A. Suboptimal state estimation for 
continuous-time nonlinear system from discrete noisy 
measurements[J]. IEEE Transactions on Automatic Control, 1968, 
13(5):504-514. 
[5] Julier SJ, Uhlmann JK. Unscented filtering and nonlinear estimation. 
Proceedings of the IEEE, 2004, 92(12):1958-1958. 
[6] Arasaratnam I, Haykin S. Cubature Kalman filters. IEEE 
Transactions on Automatic Control, 2009, 54(6):1254-1269. 
[7] Mu. J.; Cai. Y.; Wang. C.Y. L-M Method Based Iteration Cubature 
Kalman Filter and its Applications, Journal of Xi’an Technological 
University, 2013, 33(1):1-6. 
[8] Jing Mu, Yuanli Cai, Changyuan Wang. State estimation of 
Maneuvering Reentry Target Using Likelihood Based Iterated 
Divided Difference Filter, Journal of Xi’an Technological University, 
32(5): 349-354, 2012.5. 
 
 
 
 
 


Levenberg-Marquardt Method Based Iterative Square Root Cubature Kalman Filter and its Applications to Maneuvering Re-entry Target Tracking

Sen, Yang

Leiping, Xi

Quadrotor Formation Control Method Based on Graph and Consistency Theory

Jing, Ma

Yanfang, Fu

Penghui, Tian

2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
62 
Research on Digital Holographic 3D Reconstruction Software  
Ma Jing 
School of Computer Science and Engineering 
Xi’an Technological University 
Xi’an, 710021, Shaanxi, China 
e-mail: majing_majing@qq.com 
Fu Yanfang, Tian Penghui 
School of Computer Science and Engineering 
Xi’an Technological University 
Xi’an, 710021, Shaanxi, China 
 
 
 
Abstract—Digital holography has a wide range of applications 
in displaying the surface morphology of three-dimensional 
objects. There have been many studies on the physical methods 
and implementation methods of digital holography. One of the 
main problems at present is to design a stable and fast 
reconfiguration software. This paper analyzes the basic 
principle of convolution based off-axis digital holographic 
reconstruction, and presents the process of 3D reconstruction 
of off-axis digital holography. The 3D reconstruction software 
of digital holography is designed and developed according to 
the basic principle and the process of reconstruction, and the 
parallel operation of 3D reconstruction is realized by OpenMP. 
Results show that the software can help researchers 
conveniently realize digital holographic three-dimensional 
reconstruction. The reconstructed parameters can be adjusted 
according to the requirements, and the spectra, intensity maps, 
phase maps and other information required in the 
reconstruction process can be obtained. The software meets the 
needs of digital three-dimensional reconstruction. 
Keywords-Digital Holography; Three-dimensional 
Reconstruction; Parallel Computing; Software Design 
I. INTRODUCTION 
Digital holography has wide application prospects in the 
field of three-dimensional surface deformation measurement 
[1], particle field test [2], flow field measurement [3], 
biological sample microscopic measurement [4-5]. 
At present, a lot of research on the algorithms and 
applications of digital holography has been carried out. In 
the early stage, the single Fourier transform algorithm is 
widely used, and this algorithm can reproduce the pixel size 
and the reproduction distance. Now based on the Fast 
Fourier Transform convolution, angular and Fresnel methods 
for phase unwrap and numerical compensation for a lot of 
improvements [6-7]. 
In order to carry out the required reconstruction in the 
research of digital holography conveniently and quickly, in 
this paper, based on the reconstruction principle used in 3D 
reconstruction of digital holography, a digital holographic 
3D reconstruction software is designed and developed 
according to the reconstruction process. 
II. RECONSTRUCTION PRINCIPLE 
The principle of digital holography is the same as that of 
traditional optical holography. It is divided into the recording 
and reproducing process of matter and light wave, which are 
realized by the interference principle and diffraction 
principle of light. Digital holographic reconstruction is to 
process the digital hologram to obtain the object information. 
For off-axis holography, we need to record the object 
information in the form of interference fringes by off-axis 
physical optical path, and use the interference principle to 
record the object information in the form of an image 
through a CCD camera to form a hologram.  
According to different measurement objects and 
recording conditions, digital holographic methods mainly 
include convolutional reconstruction algorithm and Fresnel 
diffraction integral reconstruction algorithm. The software 
uses a convolution method. 
According to convolution theory, the complex amplitude 
of the object light,  ,U x y  can be expressed in the 
following formula according to the intensity of interference 
fringes, the intensity of reference light and the impulse 
response function.  
    1, { [ ( , ) ( , )] [ ( , , , )]}u x y F F H x y C x y F h x y  
In the formula,  ,H x y is a hologram,  ,C x y is a 
reference light,   , , ,h x y is a impulse response function, 
which is related to a specific physical optical path. The 
calculation method is as follows： 
 
 
 
  
 
   

   
  
2 2 2
0
2 2 2
0
exp( ( ) ( )
, , ,
( ) ( )
( , )
jk z x y
h x y
j z x y
h x y
 
In the formula, λ is wavelength. 
The block diagram of the algorithm is shown in Figure 1. 
H（x，y） C（x，y）
X Fourier 
transform
F(h(x，y))
X
Fourier inverse 
transform
u（x，y）
 
Figure 1. Block diagram of convolution 
The complex amplitude of the object light can be 
obtained by the above method. The complex amplitude of 
the object light carries the three-dimensional information of 
the object. If the object fluctuates beyond the wavelength 
range, it needs to be unwrapped to extract the three-
dimensional distribution information of the object. 
In the process of digital holographic reconstruction, there 
are usually three ways:(1) Fresnel transform diffraction 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
63 
method (2) Fourier transform filter method (3) Fresnel 
wavelet transform method. The software uses the method (2). 
Fourier transform filter method directly to digital 
hologram Fourier transform, and then in the Fourier domain 
using filtering, frequency shift and other methods to remove 
the zero-order spectrum and the spectrum of conjugation, 
and then inverse Fourier transform.  
Phase unwrapping is to achieve an important part of 3D 
reconstruction of digital holography. The minimum norm 
method is a kind of algorithms which are widely used at 
present, of which there are four typical algorithms. (1) Least 
square method based on fast Fourier transform (2) Least 
square method based on discrete cosine transform (3) Least 
square method based on transverse shear interference (4) 
Preconditioned conjugate gradient method. The software 
uses the method (1) to unwrap the phase diagram. 
The least square method based on Fast Fourier Transform 
The basic steps are as follows:  
(1) The package phase 
,i j
 even periodic extension, 
get y 
,i j
； 
(2) calculated 

 
          
, , 1, , , 1
( ) ( )x x y y
i j i j i j i j i j
， among them 
 

  
, 1, ,
x
i j i j i j
，  

  
, , 1 ,
y
i j i j i j
； 
(3) Perform a two-dimensional FFT on 
,i j
  to get 
,iˆ j
P ； 
(4) Find 
   
, ,
ˆ ˆ / [2 cos( / ) 2 cos( / ) 4]
i j i j
F P i M j N
 
(5) Perform the two-dimensional IFFT transform on 
,iˆ j
F
 to obtain the true phase value 

,iˆ j  after the period 
extension, take 

  ,
,
ˆ
4
i j
i j
 
III. SOFTWARE DESIGN 
A. Refactoring Process 
Digital holographic reconstruction software 
reconstruction process shown in Figure 2. The object of 
digital holographic processing is the hologram collected by 
reconstructing the hardware system. According to the 
different components of the reconstructed hardware system, 
the first need to multiply the hologram with the reference 
light. For the case of reference light for plane light, this step 
can be omitted. 
After getting the spectrum, You will find the spectral 
distribution of the information contained in the spectrum 
near the center of the positive and negative level, the 
strongest in the image center of the zero-level there is no 
object information. Therefore, the need for frequency 
selection and frequency shift. Frequency selection is to 
choose a positive or negative level of the spectrum area. The 
frequency shift is to move the positive first-order or 
negative-order spectrum center to the image center.    
According to the need to reconstruct the hologram, 
frequency spectrum processing for frequency shift. Besides 
shifting the frequency spectrum to the center of the circle, we 
can see clearly that there is another advantage besides the 
image frequency distribution. It can separate the periodic 
interference signals.  
After the frequency-shifted image is obtained, the 
transfer function is multiplied with the frequency shifted 
image, and the product of the two is inverse Fourier 
transformed. The inverse transform image is a complex 
image. The phase contains the information of the object. In 
this case, the phase 0-2pi needs to be unwrapped. 
 
Hologram
Reference 
light
X
Fourier 
transform
Spectrum 
diagram
Frequency shift
Frequency shift after 
frequency shift
Transfer 
function 
diagram
Inverse Fourier 
transform
X
Plural function 
diagram
Unwrapping
Phase 
diagram
Unwrap the phase 
diagram
Object elevation data
Linear 
transformation
 
Figure 2. Digital holographic 3d reconstruction process 
After unwrapping the phase represents the actual object 
elevation, the phase information of the object can be 
obtained according to the calibration value. The 
reconstruction algorithm of the three dimensional digital 
holography is a complicated and time-consuming process. In 
addition, in the process of reconstruction, the user is 
generally required to select the appropriate spectrum area 
and set the reconfiguration parameters such as the 
reconfiguration distance and wavelength. Therefore, in the 
design of software, multi-threaded design ideas. Work 
interface using interface thread, reconstruction algorithm for 
worker threads. 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
64 
B. Parallel processing algorithm 
In the process of 3D reconstruction of digital holography, 
a lot of image processing is needed. Parallel processing 
algorithm is needed to improve the speed of operation, so as 
to improve the real-time performance of 3D reconstruction 
of digital holography.  
This paper uses OpenMP technology to realize parallel 
operation. OpenMP is led by the OpenMP Architecture 
Review Board and is widely accepted. t is a set of guiding 
compilation and processing scheme (Compiler Directive) for 
multi thread programming for shared memory parallel 
system. 
Because the reconstruction process of digital holography 
for every image needs sequential execution, it can not 
parallel operation of different stages of reconstruction 
process. The task of each process can only be processed in 
parallel. From the processing flow, it can be seen that the sub 
tasks are basically the processing of the complex number or 
the real image. Therefore, this paper uses the parallel 
processing method for the loop operation, and only needs to 
add the following OpenMP compilation instructions before 
the for statement which needs parallel operation: 
#pragma omp parallel for schedule(kind,[size]) 
Among them kind represents a pattern, and there are 
three patterns in all ， They are static 、 dynamic and 
guided。The static mode for each thread to allocate size 
cycle tasks, according to the number of threads to complete 
the task allotment. If the size value is too large, it may cause 
some heavy kernel tasks, and some kernels do not have the 
task. 
In dynamic mode, the size cycle task is also assigned to 
each kernel on the surface, but the allocation process is 
dynamic. Which kernel is idle to give it a size distribution 
cycle tasks. 
In guided mode, each kernel is assigned tasks in 
descending order, allocating more tasks first, and then 
gradually reducing the tasks, the minimum task size cycle. If 
no size is specified in all the above modes, the default value 
is 1. 
In order to detect the running speed of parallel algorithm 
and all kinds of parallel operation modes, the running time of 
software is tested on desktop equipped with AMD Phenom II 
X6 1055T six core processor. The resolution of the hologram 
is 1024x768. The 400 reconstruction of holograms is done 
during the test, and the mean and variance of the 
reconstructed time are calculated, as shown in Table 1. 
TABLE I. RECONFIGURATION TIME FOR DIFFERENT PARALLEL 
MODES 
Parallel mode Times Variance 
None 0.369 0.0075 
Static,2 0.236 0.0080 
Dynamic,2 0.233 0.0055 
Guided,2 0.233 0.0051 
Static,8 0.242 0.0160 
Dynamic,8 0.236 0.0075 
Guided,8 0.238 0.0057 
From the above test results, we can see that when the 
parallel processing algorithm is not adopted, the average 
time of each reconstruction is 0.369s, which is about 1.56 
times parallel algorithm. For different parallel algorithm 
patterns, the average reconfiguration time is almost the same 
and the variance has small difference. 
IV. PROCESSING RESULTS 
Based on the above reconstruction algorithm, the 3D 
reconstruction software of digital holography is developed 
by using C++ language. In order to verify the effect of the 
software, a part of the hologram is reconstructed. 
As shown in Figure 3, the main parameters of the 
microlens array hologram are as follows: 
wavelength(532nm), Pixel size(4.65um), Sample refractive 
index(1.461), Reconstruction distance(0mm) 
 
 
Figure 3. Microlens array hologram 
The reconfiguration of the hologram is based on the 
above reconfiguration parameters, and the result of the 
reconfiguration is shown in Figure 4. 
 
 
Figure 4. Reconstructed image of microlens array 
Figure 5 shows a hologram of a cross object with a 
wavelength of 632.8nm, a pixel size of 4.65um, and a 
reconfiguration distance of 105.9mm. 
2018 International Conference on Sensor Network and Computer Engineering (ICSNCE 2018) 
65 
 
Figure 5. Cross structure hologram 
The reconstructed 3D image is shown in Figure 6. 
 
Figure 6. Cross structure reconstructed image 
The 3D reconstruction software of digital holography can 
not only display the 3D reconstruction map, but also display 
the original phase map, frequency spectrum, intensity map, 
phase map and 3D reconstruction map according to the 
requirements. Users can set reconfiguration parameters 
according to needs, select positive and negative primary 
centers and reconstructed areas in the center of spectrum, 
and reconstruct results and process data can be saved in 
images or data. The software interface is shown in Figure 7. 
 
Figure 7. Software interface 
V. CONCLUSION 
This paper analyzes the basic principle of the 
reconstruction of off-axis digital holography based on 
convolution. According to this principle, the 3D 
reconstruction process of off-axis digital holography is given, 
and the 3D reconstruction software of digital holography is 
designed and developed. In order to improve the running 
speed of 3D reconstruction, the parallel operation of 3D 
reconstruction is realized by using OpenMP Technology. 
The various implementations of OpenMP parallel computing 
methods were analyzed comparatively. The results show that 
the average time is basically the same as the reconstruction 
of various parallel mode, but the variance of guided model is 
relatively smaller. Finally, the partial hologram is 
reconstructed by using this software. The result shows that 
the software can fulfill the requirement of 3D reconstruction 
of digital holography, and has good practicability. It solves 
the functional integration needed in digital holography 
reconstruction, and facilitates the process of digital 
holography. 
ACKNOWLEDGMENTS 
The work described in this paper was fully supported by 
Special scientific research project of Shaanxi Provincial 
Education Department(16JK1379), and Shaanxi Province 
New Network and Testing and Control Engineering 
Laboratory project. And State and Provincial Joint 
Engineering Laboratory of Advanced Network and 
Monitoring Conrrol(ANMC) fund project(GSYSJ2017011). 
 
REFERENCE 
[1] Kim Myung K, Parshall Daniel Phase imaging digital holography for 
biological microscopy. Proc of SPIE,2004,5324:94~101 
[2] C.  B.  Lefebvre,  S.  Coëtmellec,  D.  Lebrun,  et  al.  Application  of  
wavelet  transform  to  hologram analysis: three dimensional location 
of particles[J]. Opt. Laser Eng., 2000, 33(6): 409-421 
[3] J. Desse, P. Picart, P. Tankam. Digital three-color holographic 
interferometry for flow analysis[J]. Opt. Express, 2008, 16(5): 5471-
5480. 
[4] M.K. Kim. Application of digital holography in biomedical 
microscopy. J.Opt. Soc.Korea, 2010, 14(2):77-89. 
[5] U. Schnar and W. Juptner, Digital recording and numereical 
reconstruction of holograms, Meas. Sci. Technol, 2002,13:R85-R101. 
[6] Zhang  yi  Zhuo, Wang da  Yong, Zhao  jie, Wan  yu Hong, Jiang zhu  
Qing, Tao shi  Quan. Research on practical phase unwrapping 
algorithm in digital holography [J]. Journal of Optics.2009.29(12)：
3323-3327. 
[7] Zhang zhi  Hui, Wang hua  Ying, Liu zuo  Qiang, HuangMin, Liu  fei  
Fei, Yu  Meng  Jie, Zhao  bao  Qun. Phase Unwrapping Algrithms 
Based on Fast  Four Transform.  Laser & Optoeelectronics Progress, 
2012, 120902(49):120902-1~7. 
 


Research on Digital Holographic 3D Reconstruction Software

Chao, Wan

Pingping, Liu

Bo, Hong

Research on Bounding Volume Boxes Collision Detection Algorithm in Virtual Reality Technology

GUAN, CUI-PING

LUO, HUI-XIA

FANG, H.E.

ZHOU, XUE-ZHANG

Polish Journal of Microbiology
2018,  Vol. 67,  No 2,  223–226
DOI: 10.21307/pjm-2018-024
SHORT COMMUNICATION
* Corresponding author: X.Z. Zhou, Department of College of Life Science, Ningxia University, Yinchuan, Ningxia, China; e-mail: 
zhouxuezhang@nxu.edu.cn 
S. epidermidis is an opportunistic pathogen; however, 
it is capable of storing and transmitting drug-resistant 
genes (Bloemendaal et al., 2010; Otto, 2013). The abil-
ity of S. epidermidis to form biofilms in vivo allows it to 
be highly resistant to chemotherapeutics and can ulti-
mately lead to chronic disease (Cerca et al., 2005). Some 
Chinese medicinal herbal products have been found to 
prevent biofilm formation in bacteria (Guan et al., 2013; 
Wang et al., 2015; Yang et al., 2016). Total alkaloids of 
S. alopecuroides (TASA) are an alkaloid mixture that has 
demonstrated a better inhibitory effect on the late stage 
of S. epidermidis biofilm thickening than ciprofloxacin 
(CIP), and erythromycin (ERY) (Li et al., 2016).
In order to investigate the inhibitory mechanism 
of TASA, the global transcriptome changes of biofilm-
forming S. epidermidis (ATCC 35984) in response to 
TASA were analysed in this study. Some pre-experi-
ments were performed to determine the transcriptome 
sequencing conditions. In the pre-experiments, the 
rela tive expression quantity of four main biofilm forma-
tion related genes (ica, sigB, agr and fbe) were compared 
after the S. epidermidis treatment by TASA in different 
sub-MIC (1/2 MIC and 1/4 MIC) and time periods 
(6 h, 12 h, and 24 h). The results showed that these 
four genes were down-regulated significantly when the 
S. epidermidis was treated by 1/2 MIC (12.5 mg/ml) of 
TASA for 12 h. Based on the pilot experiment results, 
the transcriptome sequencing was used to investigate 
the trans criptional differences of S. epidermidis ATCC 
35984 in a blank-medium control group and the treat-
ment group, cultured with 1/2 MIC of TASA for 12 h. 
The inhibitory mechanism of Chinese medicine TASA 
was examined through the bioinformatic analyses.
S. epidermidis ATCC 35984 was cultured overnight 
at 37°C, 120 rpm. The resulting suspension was diluted 
to 0.5 McFarland with TSB medium and 3 ml of the 
diluted suspension was seeded into a six-well plate. The 
plate was sealed with an aseptic glass cover and placed 
in the incubator upside down. After 12 h of incuba-
tion at 37°C, the liquid in each well was removed and 
washed twice with PBS. The biofilm bacteria adhered 
to the glass cover in the blank control samples were col-
lected with 1 ml TSB, and centrifuged at 12000 r/min 
for 10 min at 4°C. For TASA-treated samples, the bio-
film bacteria on the glass covers were incubated for an 
additional 12 h in the presence of TASA at 12.5 mg/ml 
(1/2 MIC) prior to the bacteria harvesting, which fol-
lowed the same methodology as the blank control. Total 
mRNA extraction was performed with RNAprep pure 
Cell/Bacteria Kit (TianGen), according to the manufac-
turer’s instructions, then stored at –80°C, and prepared 
for transcriptome sequencing. 
Standard sequencing procedure and data analysis 
were performed by using Illumina HiSeq 2500 high-
throughput sequencing platform from Biomarker 
Techno logies Co., Ltd (China). Separate sequence read 
Global Transcriptome Changes of Biofilm-Forming Staphylococcus epidermidis
Responding to Total Alkaloids of Sophorea alopecuroides
CUI-PING GUAN, HUI-XIA LUO, FANG H.E. and XUE-ZHANG ZHOU*
Key Laboratory of the Ministry of Education for the Conservation and Utilization of Special Biological Resources
in Western China, Ningxia University, Yinchuan, Ningxia, China
Submitted 6 July 2017, revised 25 August 2017, accepted 3 December 2017
A b s t r a c t
Transcriptome changes of biofilm-forming Staphylococcus epidermidis response to total alkaloids of Sophorea alopecuroides was observed. 
Bioinformatic analyses were further used to compare the differential gene expression between control and the treated samples. It was found 
that 282 genes were differentially expressed, with 92 up-regulated and 190 down-regulated. These involved down-regulation of the sulfur 
metabolism pathway. It was suggested that inhibitory effects on Staphylococcus epidermidis and its biofilm formation of the total alkaloids 
of S. alopecuroides was mainly due to the regulation of the sulfur metabolism pathways of S. epidermidis.
K e y  w o r d s: Staphylococcus epidermidis, sulfur metabolism, total alkaloids of Sophorea alopecuroides, transcriptome
Guan C.P. et al. 1224
dataset was used as inputs into DESeq2 package (Love 
et al., 2014) to analysis the unigenes expression based 
on RPKM (reads per kilobase transcriptome per mil-
lion mapped reads). A fold change of ≥ 2 and a mini- 
mum false discovery rate (FDR) of < 0.01 were accepted 
as indicators of the differentially expressed genes 
(DEGs) after Benjamini-Hochberg post hoc correc-
tion. The DEGs were BLASTX against the Kyoto Ency-
clopedia of Genes and Genomes (KEGG), Clusters 
of Ortho logous Group (COG) and Gene Ontology 
(GO) to identify their predicted biological function. 
In order to verify the RNA-Seq results, the expression 
levels of selected DEGs were quantified by RT-qPCR. 
First, Nano drop 2000 (Thermo Scientific, Wilming-
ton, USA) was used to measure the concentration of 
total mRNA and 500 ng of RNA was reverse-trans-
cribed into cDNA with PrimeScriptTM RT Master 
Mix (TaKaRa). RT-qPCR was performed with an iQ5 
light cycler (Bio-Rad) by using SYBR® Premix EX 
TaqTM II (TaKaRa) in a 20 μl reaction volume, which 
consisted of 0.25 mM of each primer, 10 μl of SYBR 
Premix Ex Taq II and 1 μL of template cDNA. PCR 
conditions were as follows: 30 s at 95°C followed by 
40 cycles of 5 s at 95°C and 30 s at 58°C. The reference 
gene was 16S rRNA, data were acquired through Bio-
Rad and analyzed by using the 2–ΔΔCT method (Livak 
and Schmittgen, 2001). All experiments were perfor- 
med in triplicate.
282 unigenes were differentially expressed under 
the screening criteria (fold change ≥ 2 and FDR < 0.01). 
Within these DEGs, 92 unigenes were significantly up-
regulated and 190 unigenes were significantly down-
regulated. The DEGs were searched against the KEGG 
database to identify their biological pathways. The 
20  greatest enriched pathways were listed in Fig. 1. 
Pathways (represented by symbols) in the upper left 
quadrant of Fig. 1 contain DEGs with more significant 
and reliable enrichment levels, therefore the sulfur 
metabolism pathway ranked first. In sulfur metabolism 
pathway, there are nine DEGs which were all down-
regulated significantly, corresponding to the encoded 
enzymes included serine acetyltransferase (CysE, 
EC 2.3.1.30), phosphoadenosine phosphosulfate reduc-
tase (CysH, EC 1.8.1.2), sulfite reductase (CysI and CysJ, 
EC 1.8.4.8), cystathionine beta-lyase (Cbl, EC 2.5.1.48), 
cysteine synthase (CysK and CysM, EC 2.5.1.47), sulfate 
adenylyl transferase (Sat, EC 2.7.7.4) and adenylylsul-
fate kinase (CysC, EC 2.7.1.25) (Fig. 2). These enzymes 
directly affect the content of sulfur metabolites such as 
cysteine (Cys), methionine (Met), glutathione (GSH), 
etc. RT-qPCR results further demonstrated that all nine 
genes showed similar expression patterns to those of 
Fig. 1. KEGG pathway scatter diagram of differentially expressed genes. Each pattern represents a KEGG pathway with its name listed in 
the right. X-coordinate represents the enrichment factor showing the ratio of all genes annotated in the pathway, in contrast to the dif-
ferentially expressed genes annotated in the same pathway. The smaller the enrichment factor, the enrichment level of the differentially 
expressed genes was more significant in this pathway. Y-coordinate represents log10(Q_value). The higher the absolute Q_value, the 
enrichment level of the differentially expressed genes was more significant and reliable in this pathway.
Short communication1 225
RNA-seq, confirming the RNA-seq based transcrip-
tome datasets were accurate and robust (Fig. 3).
In this research, according to the analysis of trans-
criptome data, the sulfur metabolism pathway in 
S. epidermidis was greatly influenced by TASA. Sul-
fur meta bolism is an important metabolic pathway 
in bacteria and its metabolites are involved in many 
physiological and biochemical processes in cells (Zeng 
et al., 2013). Cysteine (Cys), methionine (Met) and 
glutathione (GSH) are associated with bacterial acti-
vity and biofilm formation (Murillo et al., 2005; Gales 
et al., 2008; Soutourina et al., 2009; Li et al., 2013; Solis 
et al., 2016). A link between sulfate assimilation, Met 
biosynthesis and biofilm formation have been found in 
Candida albicans (Murillo et al., 2005). Deletion of the 
ecm17 gene encoding the sulfite reductase beta subunit 
resulted in reduced adhesion and poor biofilm forma-
tion in C. albicans (Li et al., 2013). Additionally, dele-
tion of the master regulator of Cys metabolism cymR in 
S. aureus also results in diminished biofilm formation 
(Soutourina et al., 2009). A recent research has pro-
vided further evidence of a role for sulfate assimila-
tion and Cys/Met biosynthesis in S. epidermidis ATCC 
35984 (RP62A) biofilm formation (Solis et al., 2016). 
According to the comparison of non-biofilm form-
ing S. epidermidis ATCC 12228 and biofilm-forming 
ATCC 35984, Solis et al. (2016) showed that the sul-
fate assimilation and cysteine/methionine biosynthe-
sis pathways in ATCC 35984 contained elevated levels 
(~25% increase) of methionine that were likely linked 
to biofilm formation. GSH, another important sul-
fur metabolite, which is associated with intracellular 
reactive oxygen species (ROS) and hydrogen sulfide 
(H2S) also played an important role in biofilm forma-
tion (Gales et al., 2008; Klare et al., 2016; Ooi and Tan, 
2016). In this study, TASA significantly influenced the 
sulfur metabolism by down-regulation of nine impor-
tant genes in this pathway. The concentration of Cys, 
Met and GSH were directly affected, and most prob-
ably finally disrupted the biofilm formation of S. epider­
midis. This result also validated the above-mentioned 
relationship between sulfur metabolism and biofilms. 
In the pre-experiments, the relative expression of 
biofilm-related genes including ica, sigB, agr and fbe in 
S. epidermidis was measured. Results showed that these 
four genes were differentially expressed after treatment 
Fig. 2. Distribution of the differentially expressed genes in a sulfur metabolism pathway. Compared to the control group, the enzyme 
marked by a green frame is related to a drown-regulated gene product. The number in the frame represents the enzyme code.
Fig. 3. Comparison of folds changes detected by RNA-seq 
(RPKM) and q-PCR.
Bars represent the log2 value of the fold changes of the gene expressions 
between the control and TASA treatment groups. On the top of the bars 
are the abbreviations of enzymes encoded by the nine genes.
Guan C.P. et al. 1226
with TASA at 1/2 MIC for 12 h. However, these four 
genes did not appear in the 282 DEGs obtained by 
transcriptome sequencing due to the DEGs screening 
criteria (fold change ≥ 2 and FDR < 0.01). It was sug-
gested that genes related to biofilm formation did have 
differential expression, but they may not be directly 
regulated by TASA. Instead, their expression may be 
indirectly affected by the changes of other metabolic 
pathways (i.e. sulfur metabolism). 
For a long time, the formation of biofilm has been 
widely recognized as a dynamic process and regulated 
by some genes including ica, sigB, agr and fbe etc. Now, 
it was shown that there is a relationship between sul-
fur metabolism and biofilm formation in S. epidermidis. 
Based on the results of transcriptome analysis, it was 
suggested that TASA’s inhibitory effects on S. epider­
midis and its biofilm formation is mainly due to the 
regulation of the sulfur metabolism pathway. 
 The regulatory mechanism of TASA has not been 
analyzed due to its multi-channeled and multi-targeted 
actions. In the study, the effect of TASA on S. epider­
midis was comprehensively analyzed by using RNA-seq. 
The enrichment of DEGs showed that metabolism, 
genetic information processing and environmental 
information processing were greatly influenced by 
TASA. The sulfur metabolism pathway was the most 
significant with all of the key enzymes in this pathway 
being down-regulated. Given the important physiologi-
cal role of sulfur metabolism in bacteria and its effect 
on biofilm formation, it is concluded that the inhibitory 
effect of TASA on S. epidermidis and its biofilm forma-
tion are mainly due to its actions on this pathway.
In conclusion, according to the analysis of differen-
tial expression and metabolic pathway enrichment, the 
molecular mechanism of TASA regulation of patho-
genicity, virulence and metabolism of S. epidermidis was 
further characterized. The sulfur metabolism pathway 
was identified and results could provide valuable infor-
mation for follow-up studies to examine the regulatory 
mechanism of TASA on S. epidermidis, and could serve 
as the basis for exploring potential drug targets.
Acknowledgements
This study was supported by the National Natural Science 
Foundation of China (No. 31460676) and Major Innovation Pro-
jects for Building First-class Universities in China’s Western Region 
(ZKZD2017001). Thanks to Laura Beamish at the University of Bri-
tish Columbia for the review of the English writing style and gram-
matical editing of the manuscript.
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Global Transcriptome Changes of Biofilm-Forming Staphylococcus epidermidis Responding to Total Alkaloids of Sophorea alopecuroides

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