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International Conference on Telecommunication 2009
FOREWORD ICTEL 2009
International Conference on Telecommunication (ICTel) is an annual event hosted by IT Telkom since the year of 2005. Thus today ICTel is its fifth, highlighting on the theme of “ICT Development for the Knowledge Based Society”. This theme is chosen as a response from our institution in seeing the current trend where ICT already enters various areas of human life. Those areas include education, health, banking and finance, mining, national defense, and many others. Most of business activities in those areas have been using ICT as their main assisting device. Therefore we can conveniently say that ‘ICT for life’ has become ‘a jargon comes to life’, in which lots of ICT applications are everyday phenomena.
Responding to that existing trend, ITTelkom as one educational institution is taking on active participation to link communication among people and communities in ICT development. The vast development in ICT has given more and more rooms to ideas and creative minds. This is exactly where ICTel is expected to facilitate communications and information exchanges, allowing faster and more integrated expansion of ICT knowledge. All ICTel participants coming from diverse background: academics, research and development, industry, and engineering are given widest opportunity to openly discuss the best solution for ICT for the society growing on pillars of knowledge.
Last but not least, since ICT development is not something to be built overnight, and that it needs continuous and sustainable communication, we hope that the discussions taken place in this event can be followed by real efforts to improve the quality of life of society. To all the participants, writers, committees, and all the contributing parties, we extend our sincere gratitude and appreciation. We hope that ICTel 2009 can give meaningful contribution to ICT development for society.
Yours, Director of Academic Support Suwandi
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International Conference on Telecommunication 2009
WELCOMING SPEECH
ICTel2009 is an annual international conference especially for researchers and academicians in the field of telecommunication to share and publish their works. ICTel2009 consists of plenary session featuring various presenters to expose their research and read condition of telecommunication world. The theme “ICT Development for the Knowledge Based Society” is chosen because, as a matter of fact, the role of ICT nowadays it expected to be more evolved for the development of sophisticated and advanced society. Moreover, ICT will also enable this society to have better information access to close the economical and social gap. Thus, eventually prosperity shall be achieved by their society. Mainly, the plenary session of ICTel2009 consists of presentations covering the topic of telecommunication industry, optic, radar, computer, communication system, artificial intelligence, and many others. There are 78 abstracts and papers sent to the committee and only 53 papers are accepted and to be presented. These include 4 international presenters, 16 national presenters, and 33 presenters from the IT Telkom. Participants and presenters of ICTel 2009 come from German, Malaysia, Korea, and Indonesia. Good luck to all people involved in ICTel 2009. I hope that all of you will enjoy and gain invaluable benefits from all agenda of ICTel 2009. Bandung, November 2009 Chair of Organizing Committee Iswahyudi Hidayat
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International Conference on Telecommunication 2009
ICTel 2009 COMMITTEE
ORGANIZER
Directorate of Academic Support, Institut Teknologi Telkom Bandung
TECHNICAL PROGRAM COMMITTEE
Josaphat Tetuko Sri Sumantyo (Chiba University) Joel Joseph Sacro Marciano (IEEE Phillipine Section Chair)
Toni Anwar (TGGS, Thailand) Marzuki Khalid (University Technology of Malaysia)
Heiko Schroder (Royal Melbourne Institute of Technology) Andrian Bayu Suksmono (Institut Teknologi Bandung)
Sugihartono (Institut Teknologi Bandung) Suhartono Tjondronegoro (Institut Teknologi Bandung)
Aly Muayyadi (Institut Teknologi Telkom) Deni Saepudin (Institut Teknologi Telkom) Rendy Munadi (Institut Teknologi Telkom) Rina Puji Astuti (Institut Teknologi Telkom) Ary M. Barmawi (Institut Teknologi Telkom) Heroe Wijanto (Institut Teknologi Telkom) Dharu Arseno (Institut Teknologi Telkom) Iwan Iwut TA (Institut Teknologi Telkom)
ORGANIZING COMMITTEE
Iswahyudi Hidayat Yuliant Sibaroni
Erwin Budi Setiawan Kinkin Kindawati
Leanna Vidya Yovita Shaufiah Adiwijaya
Iman Hedi Santoso Indra Chandra Deny Saepudin
Koredianto Usman Rian Febrian Umbara Florita Diana Sari
Istikmal Hetti Hidayati Heri Iman N.
Mediana Mayang Kencana Ani Yuliani Warsino
Aris Hartaman Yanuar Firdaus AW
Chandra Purna Darmawan
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International Conferece on Telecommunication 2009
LIST OF PARTICIPANT PAPERS A. Social and Technical aspect of Computer Network
Performance Comparison Of Scheduling Algorithm: Round Robin (RR), Weighted Round Robin
(WRR) and Deficit Round Robin (DRR) on WIMAX Network With NS-2 Simulator ................................... 1
Analysis Performance Congestion Control Algorithm on Mobile Adhoc Network (MANET) .................... 11
Performance Evaluation of Multi-Radio AOVD in Hybrid Wireless Mesh Networks Based on
Manhattan Mobility Model ............................................................................................................................ 20
Analysis of Delay Bound in IEEE 802.11g WLAN Over Fiber Networks .................................................... 27
Mobile Banking: Safe, at Least for Now ....................................................................................................... 31
Design and Implementation of SMS Gateway as a Learning Support Tool .................................................. 35
Eastern Cyberlaw Exposed : The Port Scanning Way ................................................................................... 39
Optimize QOS of Metro Ethernet Network with Packet Scheduller Using Weight Round Roubin
Algorithm (WRR) .......................................................................................................................................... 45
Performance Analysis of H.264/AVC Video Streaming Over Wireless LAN with IEEE 802.11e
Enhanced Distributed Channel Access QOS Support ................................................................................... 49
Content Provider Server for Wireless Mobile Device ................................................................................... 56
Improved Flooding Protocol with Gravity Analogy in Wireless Sensor Network ........................................ 62
An Application to Support TDM-to-Softswitch-Based NGN Migration on OPNET IT Guru®
Network Planner ............................................................................................................................................ 69
A Comparison Between FUSC and PUSC Sub-channelization Techniques for Downlink Mobile
WiMAX IEEE 802.16e Performance ............................................................................................................ 73
Analysis Performance of Bandwidth Request-Grant Mechanisms in WiMAX Networks ............................ 80
Design on Information Technology Strategic Planning Framework by Activity Values Identification ........ 86
B. Computer Sience and Intelligent System Particle Swarm Optimization Algorithm to Optimize Project Resource Scheduling .................................. 100
Visualization Comparison Self Organizing Mapping (SOM) Analysis to Linearity Correlation Based
on Region Power Transmission Path in JMB .............................................................................................. 105
Reconstruction of Phylogenetic Tree Using Ant Colony Optimization ....................................................... 110
Corporate Information Factory Planning in Telecommunication Operator ................................................. 115
Design and Implementation of Communication Between Virtual World and Real World Based on
Croquet in 3D Virtual World ....................................................................................................................... 119
Performance Test of Statistical Translation Machine at Translating English to Indonesian Language ....... 126
Development of Social Security Card Case on Monitoring Malnutrition Patients in NTT Area ................. 130
Analysis of Indonesian News Document Classification Using Centroid Based Classifier Method ............ 133
Similarity Measurement in Digital Music File Base on Chroma-Based Representation ............................. 138
Design and Software Implementation for Wireless Automation in PLC Based Using Java Platform ......... 143
Caricari Game Design and Implementation as a Web Based Mini Game ................................................... 152
Hardware Description Language Comparison Systemc to Verilog Case Study: Least Common
Multiple ....................................................................................................................................................... 155
C. Communication System, Optics, Radar, and Applied Physics Hanle Eeffect Modeling on Silicon Based Spintronic Semiconductor Devices .......................................... 160
PON Extender: Controlling System for GPON with optional EDFA .......................................................... 164
Bidirectional Optical Add/Drop Multiplexer (OADM) For CWDM PON System ..................................... 166
Building a Radar From The Scratch: ISRA LIPI Radar Experience ........................................................... 171
Simulation Of Sequentila Fast ADC For Ground Penetrating Radar (GPR) Applications .......................... 181
Performance Analysis of MIMO-STBC System in HSDPA Over Fading Rayleigh Channel ..................... 186
The Performance Analysis of Combined Mud Decorrelator and PIC in DS-CDMA .................................. 194
Design of Yagi Antenna on Wireless Local Area Network 2,4 GHz .......................................................... 199
Analyzing Influence of Earth Station Antenna Pointing to Receiving Signal Parameter at Down Link
Power Budget .............................................................................................................................................. 203
Cooperative Signal Detection With Different Channel Fading ................................................................... 209
Design of Dispersion Shifted Fiber (DSF) to Increase The Performance of Optical Fiber
Communication System ............................................................................................................................... 214
Design and Realization Pulse Generator for Ground Penetrating Radar Application Using Timing
Switched Method ......................................................................................................................................... 221
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International Conferece on Telecommunication 2009
D. Data Mining, Applied Mathematics, Image Processing and ICT Contens of Gold and Silver Estimation Using Ordinary Kriging Method (Case Study : PT Aneka
Tambang) ..................................................................................................................................................... 227
Scheduling Replacement of Hydraulic Pump Component Software Using Weibull Distribution (Case
Study : PT Inco, Tbk) .................................................................................................................................. 233
Space-Time Analysis of Product−Sum Semivariogram Model (Case Study : Oil Product) ........................ 238
Churn Prediction of Cellular Telecommunication Customer with Cost-Sensitive Learning Approach ...... 247
The Analysis and Application of Classification Methods for Software Development Non-Tulis
University Student Enrollment System (Case Study at IT Telkom) ............................................................ 252
3D Reconstruction Extraction and Equation of Calibration Parameters Using Simple Sckewed
Chessboard Pattern on Stereo Vision........................................................................................................... 258
Training Set with Enhancement TSVQ Method for Medical Image Based Super-Resolution .................... 264
Building an Indonesian Digital Forensic Laboratory ................................................................................... 268
The Effects of VAK Learning Style on Learning Outcomes in Powerpoint-Based Teaching ..................... 274
Cybercrime from Islamic Shariah Law Point of View ................................................................................ 281
Implementation of Particle System Using Smoothed Particle Hydrodynamics (SPH) for Simulating
Lava Flow .................................................................................................................................................... 284
Analysis and Design of E-procurement PT. Adhi Jaya ............................................................................... 290
Analysis of Propagation Channel Using Walfisch-Ikegami Model On Mobile Wimax System ................. 296
Performance Analysis Of Zigbee Protocol On Wireless Personal Area Network (WPAN) ........................ 304
International Conference on Telecommunication 2009
VISUALIZATION COMPARISON SELF ORGANIZING MAPPING (SOM) ANALYSIS TO LINEARITY CORRELATION BASED ON REGION POWER
TRANSMISSION PATH IN JMB
Iriansyah BM Sangadji 1, Subanar 2 , Retantyo Wardoyo 3, Sri Hartati 4
1 Informatics, STT PLN 2,3,4, Natural Science and Mathematics Faculty, Gadjah Mada University
1iriansyach@sttpln.ac.id , 3r_wardoyo@mailcity.com, 4shartati@ugm.ac.id
Abstract Electricity transmission path function is connecting numbers of power plant in the large covering area. Its mean the system needs handling when the power plant must active or not. Decision is taking by consider analytic behavior and relation between power plant in each region. Knowledge about relation pattern and behavior of power need are important. Neural network (SOM) and scatterplot methods can use in this paper. Comparison of form graph between scatter plot and SOM visualization mean will be investigated. Results of this paper will showing and explain behavior relationships pattern between region 1 to region 4. Comparison method between 2 approaches will showed.
Keywords: Self Organizing Map(SOM), Linear Correlation , Region, JMB electricity transmission path. 1. Introduction
In operation electricity power handling system
that the power plants , transmission path is
connected in a big electricity complex system. The
area of this system covering increase will correlate
with integrated new numbers kind of power plants.
Roles of addition or develop its system have
feedback in positive or negative values to system.
To constitute a new power plants have to
consider much aspects from the handling system
itself to social and environment impacts. Now the
question is how to make interactive between power
plants unit in harmony of transmission balancing
system. Balancing system has a few conditions. One
condition is have to know behavioral active power
from power plant and consumption in customer .
JMB (Jawa, Madura Bali) electricity
transmission system is the one of complex network
handling system. Its constitute from four convergent
regions division power. Operating power JMB
system have to based on region1 to region 4.
Figure 1. JMB electricity Transmission System
Modeling and mapping behavioral power per
region areas will explain behavioral of dynamic
region power.
There are many approaches and models to
identify, recognize behavior pattern of electricity
consume in region1 to region4. Statistically method
is the most popular in using today.
This paper tray to explain compare about
correlation linearity from statistically with scatter
plot and neural network methods. Self Organizing
Map is the one of Neural network approach. Results
will show visualization of linearity as graph. Reason
of linearity behavioral found is to modeling the next
purpose in controllability study. It’s a part of
handling system
1.1 Self Organizing Map
The SOM is an unsupervised neural network,
based on competitive learning, that implements a
non linear smooth mapping of high dimensional
input space onto low dimensional output space. The
neurons of the SOM form a topologically ordered
low- dimensional lattice that is an outstanding
visualization tool to extract knowledge about the
nature of the input space data.
The SOM is widely used as a data mining and
visualization method for complex data sets.
Application areas include, for instance, image
processing and speech recognition, process control,
economical analysis, and diagnostics in industry and
in medicine.
The SOM algorithm implements its mapping in
two stages. First the best matching unit (BMU) of
the input vector is selected by means of a
competitive process.
c= arg mini || x – mi (t) || , i = 1, 2, ...,N (1)
Then a cooperative step is performed, where the
winning unit and its neighbors are adapted
mi(t+1) = mi(t) + (t) hci (t)[x(t) - mi (t)] (2)
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International Conference on Telecommunication 2009
1.2 Scatter Plot
A scatterplot matrix is a matrix of scatterplots
where each column contains the same X axis and
each row the same Y axis. A scatterplot matrix is
useful for visualizing how a dataset is distributed
through multiple variables. all of the scatterplots in
the matrix the same way, you can see how the same
clusters of points change shape from one scatterplot
to another
2. Methodology
Figure 2. Analysis Methodology
2.1 Scatter Plot Vusualization
Data Prepocessing
Each regions consumption data will be correlating to
another except the region itself as figure above.
Table 1. Sample Behavior Power Region in October 2006
Sum Of Power Plants Region
I Region
II Region
3 Region
4
AVG AVG AVG AVG
4465 666 1969 4062
4840 678 2084 4834
4876 679 2285 4971
5101 678 2124 4954
5000 656 2318 4943
5122 655 2222 4855
5029 645 1862 4586
4993 689 1420 3948
5652 600 1894 4332
5463 560 2177 4646
5363 592 2192 4736
5359 593 2165 4702
5346 621 2022 4671
5226 612 1944 4328
5020 596 1736 3959
5553 583 2039 4417
5802 568 1644 4695
5668 576 1728 4714
5565 577 1787 4512
5340 582 1484 4370
5004 581 1237 3653
4563 595 1015 3201
4142 631 969 2827
3679 649 1000 2566
3886 640 1019 2503
3926 604 923 2957
3974 592 1034 3240
4224 590 976 3340
4472 600 1100 3138
5220 586 1341 3773
5408 608 1553 3948
Data prepared from daily operations sheet in
Pusat Pengatur dan Penyaluran Beban (P3B) PT
PLN (persero) from October 2006 – December
2006. Its repsenting regular days and few of holiday.
Region 1 Region 2
Region 3 Region 4
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International Conference on Telecommunication 2009
R e g io n I
3 5 0 0
4 0 0 0
4 5 0 0
5 0 0 0
5 5 0 0
6 0 0 0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 3 1 3 2
T a n g ga l
R e gio n 2
5 5 0
5 7 0
5 9 0
6 10
6 3 0
6 5 0
6 7 0
6 9 0
7 10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 2 2 1 2 2 2 2 2 2 2 2 3 3 1
T a n g ga l
R e g io n 3
900
1100
1300
1500
1700
1900
2100
2300
2500
1 2 3 4 5 6 7 8 9 10 11 12 13 1 4 15 16 17 18 19 20 21 22 23 24 25 26 27 28 2 9 30 31
T a n g g a l
R e g ion 4
2400
2900
3400
3900
4400
4900
5400
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 6 17 1 8 19 20 21 22 23 24 25 2 6 27 28 29 30 31
T a n g g a l Figure 3. Region Power behavior pattern
Region 1 ↔ Region 2
Figure 4. Scatter Plot Correlation Between Region 1 and Region 2
Figure 4 showing that there is no linear correlation
between region 1 and region 2 .
Region 1 ↔ Region 3
Figure 5 Scatter Plot Correlation Between Region 1 and Region 3
Figure 5 showing that there is a linear correlation
between region 1 and region 3
Region 1 ↔ Region 4
Figure 6 Scatter Plot Correlation Between Region 1 and Region 4
Figure 6 showing that there is a linear correlation
between region 1 and region 4
Region 2 ↔ Region 3
Figure 7. scatter plot correlation between Region
2 and Region 3
Figure 7 showing that there is no linear correlation
between region 2 and region 3
Region 2 ↔ Region 4
Figure 8. Scatter Plot Correlation Between Region 2 and Region 4
Figure 8 showing that there is no linear correlation
between region 2 and region 4
Region 3 ↔ Region 4
Figure 9 Scatter Plot Correlation Between Region 3 and Region 4
Figure 9 showing that there is a linear correlation
between region 3 and region 4
400
500
600
700
800
900
1000
1100
1200
1300
1400
3 5 0 0 3 6 0 0 3 7 0 0 3 8 0 0 3 9 0 0 4 0 0 0 4 10 0 4 2 0 0 4 3 0 0 4 4 0 0 4 5 0 0 4 6 0 0 4 7 0 0 4 8 0 0 4 9 0 0 5 0 0 0 5 10 0 5 2 0 0 5 3 0 0 5 4 0 0 5 5 0 0 5 6 0 0 5 7 0 0 5 8 0 0 5 9 0 0 6 0 0 0 6 10 0
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
2100
2200
2300
2400
2500
2600
2700
3 5 0 0 3 6 0 0 3 7 0 0 3 8 0 0 3 9 0 0 4 0 0 0 4 10 0 4 2 0 0 4 3 0 0 4 4 0 0 4 5 0 0 4 6 0 0 4 7 0 0 4 8 0 0 4 9 0 0 5 0 0 0 5 10 0 5 2 0 0 5 3 0 0 5 4 0 0 5 5 0 0 5 6 0 0 5 7 0 0 5 8 0 0 5 9 0 0 6 0 0 0 6 10 0
2000
2100
2200
2300
2400
2500
2600
2700
2800
2900
3000
3100
3200
3300
3400
3500
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4600
4700
4800
4900
5000
5100
5200
3 5 0 0 3 6 0 0 3 7 0 0 3 8 0 0 3 9 0 0 4 0 0 0 4 10 0 4 2 0 0 4 3 0 0 4 4 0 0 4 5 0 0 4 6 0 0 4 7 0 0 4 8 0 0 4 9 0 0 5 0 0 0 5 10 0 5 2 0 0 5 3 0 0 5 4 0 0 5 5 0 0 5 6 0 0 5 7 0 0 5 8 0 0 5 9 0 0 6 0 0 0 6 10
900
1000
1100
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1300
1400
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2100
2200
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2700
400 500 600 700 800 900 1000 1100 1200 1300 1400
2000
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400 500 600 700 800 900 1000 1100 1200 1300 1400
2000
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3000
3100
3200
3300
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3700
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4000
4100
4200
4300
4400
4500
4600
4700
4800
4900
5000
5100
5200
900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700
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International Conference on Telecommunication 2009
2.2 Self Organizing Map Visualizations
Region 1 ↔ Region 2
4.82
5.22
5.62
d
0.556
0.757
0.958
d
Color code
Figure 10. Correlation
Between Region 1 and Region 2
Figure 10 showing that there is no linear correlation
between region 1 and region 2 .
Region 1 ↔ Region 3
4.82
5.22
5.62
d
1.48
1.84
2.2
d
Figure 11. correlation between Region 1 and Region 3
Figure 11. Showing that There is a Linear Correlation Between Region 1 and Region 3
Region 1 ↔ Region 4
4.82
5.22
5.62
d
3.68
4.01
4.34
d
Figure 12. Correlation Between Region 1 and Region 4
Figure 12 showing that there is a linear correlation
between region 1 and region 4
Region 2 ↔ Region 3
0.556
0.757
0.958
d
1.48
1.84
2.2
d
Figure 13. Correlation Between Region 2 and Region 3
Figure 13 showing that there is no linear correlation
between region 2 and region 3
Region 2 ↔ Region 4
0.556
0.757
0.958
d
3.68
4.01
4.34
d
Figure 14. Correlation Between Region 2 and Region 4
Figure 14 showing that there is no linear correlation
between region 2 and region 4.
Region 3 ↔ Region 4
1.48
1.84
2.2
d
3.68
4.01
4.34
d
Figure 15. Correlation Between Region 3 and Region 4
Figure 15 showing that there is a linear correlation
between region 3 and region 4
Figure 16. Mapping Between Region 1 - Region 4
0.258
0.71
1.16
U-matrix
November
November
Oktober
Oktober
November
Oktober
Oktober
Oktober
Desember
Desember
Desember
Desember
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International Conference on Telecommunication 2009
3. Result Region 1 and region 2 based on statistically or
SOM results show that power behavior have no
linear correlation. Its mean that each region have
independent relationships in power consume.
Region 1 and region3 based on above data
indicate that power behavior have a linear
correlation. Its mean that each region especially
region 1 needs power from region3.
Region 1 and region 4 show that region 1 need
more power from region 4 because there is a linear
correlations.
Region 2 and region 3 show there is no linear
correlation. Its mean that each area is independent
for power preparing.
Region 2 and region 4 show there is no linear
correlation.
Region 3 and region 4 show there is a linear
correlation and each area is dependent for power.
Figure 16 showing correlation each region to
others. Its mean that region 1 have using power a lot
in December. The other side region1 also have great
less power in last December. Region 2 in peak
power at October but not much than peak in region
1. Region 3 almost likely than region 2 in middle
October. Region 4 have most less power in
November.
4. Conclusion
Statistically(scatterplot) and neural networks
are the same method of visualization its showed
correlation linearity sets of data.
Neural networks have a colorfully visualization
than scatter plot. Its can be show details the
information needs.
Electricity power behavior at each region are
different in peak of power and region relationship.
Power plant interactive with transmission lines
path to achieve balance system with centralized
operator.
Relationship happen between region 1, 3 and
region
Based on data indicated that region 2 relative
independent in transmission system.
Analysis result can be use to make mapping
model in intelligence study area.
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