Home

海事技術マネジメント学科の学生における 海事志向性

Contents

1. VTS ME 3 2 3 2 1
2. 2 Fig l
3. 2 3
4. ClassB AIS Automatic Identification System ClassB AIS ClassB AIS ClassB AIS ClassB AIS 1 2 2 1
5. 5 1 BEBN p 110 2005 2 Vo1 125 pp 241 247 2011 3 Vol 124 pp 177 182 2011 11 0 1281 0 0 8 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 27
6. 1 1998 2013 2 HP EMA 2010 3 No 3074 2012 2 4 55 2006 5 58 2009 6
7. 5 D 4 4 Q 4
8. OT A a eae sani as M1 2 2 2
9. 5 AIS ROM AIS 5 1 AIS No 121 pp 103 109 2009 9 2
10. 1 Draft Survey Aim 2 1 Aa RE EEX 5 2 Surveyor
11. 73 2 4 1998 2008 217 70 2 1
12. AO TRV YAS HEB amp LTR DEAS AO 6
13. 5 1 HERRERO 1 128 2013 2 Seiichi KOSHIZUKA Yoshiaki OKA Breaking Waves Using the Moving Particle Atsushi NODA and Numerical Analysis of Semi inplicit Method Int J Numer Mech Fluids 26 pp 751 769 1998 3 MPS 124 pp 329 336 2010 K oD oO Ka D gt 0 20 40 60 80 10 0 12 0 Flow velocity m s Mooring tether break area Mooring tether danger area Mooring tether safety area F
14. FMEA Failure Mode Effects Analysis 4MSE FMEA 4MSE 1 15 2007 2011 20
15. 9 9 MLE
16. BC As 7 AO 25
17. 1 1 1 2 4 TEU 10 1996 10
18. Ww Ce DIXe 2 3 3 1 1 3 3
19. 2010 6 H 25 7 7 12 3 Simulator for 3 1 3 _ 1 CHATS 1 1
20. O O 10 2 1 Lpp 235m B 42m d 9 17m W 73 613ton
21. 614 507 500 1 130 WEL Rae 3 4 2 2 1 000 1 000 2 000 ER 500
22. 4 AIS AIS AIS 4 1 2 AIS
23. 2 2 FMEA FMEA FMEA 1
24. AIS 3 1 2 3 GPS cer 3
25. CO I CO CO BELA BOR ADC IC BAT 4 BE
26. 1 1655 pp 88 93 2007 9 2 82 SE pp 151 154 2007 RTK OTF GPS TSL GREY 95 pp 79 85 1996 9 K GPS OP 124 pp 273 280 2011 3 0 1281 0 0 08 20130 59 30 3100 C HHHHHHHHHH 1010 20131 27 HOG HOG Histogram of Oriented Gradient SVM Support Vector Machine HOG
27. 1 60 2 2 3 1
28. 5 1 IMO Standard Marine Communication Phrases IMO SMCP IMO 2002 http www2 karyodal ac D takag1 DweDb 2 index htm Naoyuki Takagi amp Yoko Uchida Phonetic Characteristics of Filipino Mariners English IMLA IMEC 23 Proceedings 193 199 2011 10 10 126 55 64 2011 3 4 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270 RE AFRABAR UDT H L BS AML HREOC aad Deas x A lt BRC A Aaa Raa DAA Ze ea Oo IRC OE she MOP ew LT AAA REAR HOR EBRA Z BAT AY BLED SAMY SHAT LY MOHD TO WERA CETHE TS MY OFM BI AAR EEO a VPH HEA OMSK SE FEORBERT FO HRANT RAMO DHE LW
29. 1 WR WR WR
30. 2 3 5 NNN ain eee ea 2 10 87 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 Q SSD Sum of Squared Differencey 3
31. CO Nm os zN ss 1 2010 O 152 147 TEU 2 2 1 1 2010 13 691 F TEU 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 6 817 FTEU 2 2
32. TRESCI OS TSF SSS ae oa L AIS AIS DBE bo ETA ETA BTA 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 ETA 4 2 ETA ETA
33. EN D com 1 95 2009 10 N Wen 2 2009 1 3 p 22 25 2008 2 4 a ATS 181 p 39 46 2012 7 5 E http www soumu go jp johotsusintok
34. 4 Ze 5 A 4 2 3 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27
35. AIS SOTDMA 1 AIS Automatic Identification System 1 VHF
36. 2 2 1 1 3 1 1000 3 1 19 BMI 25 3 A B C BMI Body Mass Index kg 4m 23 A 50 BMI 25 0 B 20 BMI 25 2 C 50 BMI 29 0 3 2 2
37. 0 0 7deg 1deg 0 0 5 0 6 2deg HER 1deg Sdeg HE 1deg 5 o 3 y 0 6183x 0 6817 2 ee a 1 deg 8 6 4 2 V l 2 4 6 8 y 0 4738x 0 7762 E etA PP al 60deg ae P mie 240deg 5 4 A kat Dy hEERD YY CHED ZY 4 2 4Lpp amp WE EIFS LA D Lpp
38. 10NM 2 2 AIS 9 5 2 2 10NM AIS Oo uw D WW N Receive Signal Strength dBu 100 Distance NM 5 AIS 3 2
39. 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 1 J Y Zheng Digital Route Panorama IEEE Multimedia pp 57 68 July Sept 2003 2 BRE ANE ERER vo1 94 pp 97 107 1996 3 vol 135 pp 131 136 1998 92 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270
40. fa Ly Fig 6 2 10m im y 7 95mm 1
41. 15 25 2 3 5 2000 3000 10 20 25 50 2000 3000 100 2010 4450 104 7 2
42. FEFE GM 5 1 Japan Captain Ship Handling AJSU pp82 85 2008 AS ZH pp 243 1974 12 RORO 2 RORO 2010 4 6 4 21 2010 3 s Association A Guide to All Japan Seaman s Union 2 3 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27
43. 1 2 3 4 5 6 AND OR 2 4
44. International Maritime Organization IMO DILAR FLHE SAE LU CH YO AHA Fe WR 3 0 1281 0 000 20130 50 307 300 HHHHHHHHHHH 1010 20130 4 27 2003 10 90 50
45. 3x3 0 1 0 1 4 0 1 0 ae 2 3 Fig 1 1 2
46. 1 IMO Formal Safety Assessment FSA 2
47. 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270 o Kan 1 42 ae ae D pea
48. Wh D A i 15 16 17ch 0 8W 2 2 AIS AIS AIS AIS ID AIS bse 3 AIS VHF
49. no Oe Os Bie EK 2 2 2011 6 9 10 2 046 A B C D E 1 310 1 1 A 1 043 79 6 B 267 20 4 1 310 2 A 1 263 20 1 B 2 568 43 4 C 3 479 36 6 3 A 286 21 8 B 324 24 7 C 354 27 0 D 234 17 9 E 112 8 5 4 A 634 48 4 B 218 16 6
50. 21 10 NM ie edie E A N nave 20 ATS 5kW VHF 2 VHF 100
51. 2 6 7 F k r pr 6 L el 7 Dt P m 2 3 VP 1 7
52. 8 1 Tzvika Libe Evgeny Gershikov Samuel Kosolapov Comparison of Methods for Horizon Line Detection in 2012 The Fourth Creative Sea Images International Conference on Content pp 79 85 2012 2 A Miranda Neto A Corr a Victorino I Fantoni Technologies and D E Zampieri Robust Horizon Finding Algorithm for Real Time Autonomous Navigation based on Monocular Vision Intelligent Transportation Systems TSC 2011 14th International IEEE Conference on pp 532 537 2011 3 aR TET Vo1 125 pp 25 31 2011 4 B Zafarifar H Weda and P de With Horizon detection based on sky color and edge features in Visual Communications and Image Processing 2008 SPIE W Pearlman J Woods and L Lu Eds vol 6822 2008 pp 1 9 2008
53. Full 9 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 Time min 2 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 V T S RA Baa SN Gan DMSO Se OO ie a SMCP RUAJ VTS
54. 4 2 RR 2 4 3 Direction Full Half PUSH Slow D Slow Stop D Slow PULL Slow Half 1 6 PULL 2
55. 3 000DWT MPS 2 MPS Moving Particle Semi implicit Method MPS MPS
56. 3 2 2 MR vessel 30 degrees on your port bow SMCP Stand by on channel 16 SMCP VTS 38 3 2 3
57. 2 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 3 3 1 MPS MPS Fig 1 Table 1 2 5m 2 RRS 0 11m 0 17m Fig 2 Floating model 2 5m
58. AIS 1 hin s dynaniic condition n 6 hp at anchor or moored and notm ovng faster than 3 knots le A ACN hp at anchor or moored and movng faster than 3 knots hp 0 14 knots a AIS hp 0 14 ee and changng course hp 14 23 knots 6 DULok LT RIERA FERED IE O SB hp 14 23 are and changing course 2 EE hp gt 23 knots 2 sec hp gt 23 knots and changng course Ro Sec 2 2 AIS 2 2 1 2 2 1 AIS
59. Eo Lico UG DTG T sii Wo Eo DX Zo TE 3 7 7 7 7 2cm 10 c m DATA eRe Sl UTES TRV 2 1 2 2 2 3 2
60. ClassB AIS LAL AIS ClassB AIS 2 ClassB AIS ClassB AIS ClassB AIS ClassA AIS UTC
61. LC AA 2 E Ha PY Se i 0oO10O18312 0 1281 O00 0 2013 50 307 300 HHHHHHHHHHH 1010 20130 4 27 3 2 o me 2 of of of po al ol sfs AT CAT TOJ 1 ER PARR ft Toe 2 AREER mea 9 of tf oft
62. 1 LLI 1 2 LLI 9 33
63. 4 RN ee 2012 Pe OR MO 5 1 ICC IMB International Chamber of Commerce International Maritime Bureau Piracy and Armed Robbery against Ships Report Annual Report 2012 pp 3 19 2013 1 EJER THIRETHEAE MAA JPRS No 128 2013 3 2 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 Ww Ei Be RORO
64. P Fig 1 Fig 3 Fig 1 500DWT 6 0m 5 0m Fig 3 10 000DWT 8 0m 10 0m 10 000DWT
65. 1679 877 082 6 ATCO Fano LOT Ve eam Fee 65 AIS C42 COA OI AT Vv ee
66. 3 3 AIS AIS 2 1 3 4 84 4 3 5 ETA ETA 86 77 ETA 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010
67. WAM WAM 2 3 O 2 WAM 2 1 SSR Secondary 1 WAM WAM Surveillance Radar SSR
68. 2 3 2 WAM 3 VDOP HDOP gt ee HDOP 1 8 16 24 32 dimensionless 2 HDOP 117 VDOP 1 8 16 24 32 dimensionless 3 VDOP VDOP 2 WAM
69. CO POMES 4 2 a YT Ope Ne Says 2 0 P D Es 227 fe Big Ee Ed P
70. 10 80deg KGPS 3 sm cm 0 1deg
71. CCO 20 30 110 m 2 10 H O N lt W see NA x 4 CO 32 30 m 8 10 Ht a 28 T O 26 24 N o N Co N wo o o oOo o o Oo o 5 5 8 6 5 5 6 J t CO CO ae N N N x CO R 1 Web 3 4 5 http www jccca org global_ warming knowledge kno03 html 2013 3 6 Web 7 b E029 http www env go jp press file_view php serial 19 005 amp hou id 14682 2012 4 20 Web CO A http ww
72. 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 165 deg 168 3 deg 3 3 deg Chore AIS 159 deg 171 deg 12 deg 1 46 deg sec AIS 0 67 deg sec GPS 2 0 deg sec 2 3 50m
73. 1 2 3 60 4 2 5
74. CO HE C0 474 529 CO 3 3 1 2 1 1006 LMIU 2010
75. No 127 pp181 188 2012 9 LMIU Lloyd s Marine Intelligence Unit HHA GT Z 2010 2011 Outlook for the Dry Bulk and Crude 011 Shipping Markets ie fap amp AH AO WoL pp 25 80 2011 10 2012 http www jsanet or jp data pdf 201 2data10 3 pdf RORO RORO No 494 2009 1 International Maritime Organization IMO Second IMO GHG Study 2009 2 3 4 5 6 7 8 9 0 1281 0 0 0O 0O 2013 50 300 370 HHHHHHHHHHH Wij 20130 41 27 OS se HA
76. I eR b d g lt NN T BERRE ON t k p t k p t k DVO k ec ok eens cand 39 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 PAR Hi OA Ole eo
77. 9 3 a om Wie ThE Va 3 12 GPS AIS AIS GPS A AIS
78. 10 0m L F WET SIL 12 0m 2 0m 12 0m 1 0m 0 90 2 1 0m 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 4 FHig 1 Fig 3 Fig 1 500DWT Fig 3 10 000DWT 3 000DWT Fig 2
79. 3 3 2 3 2 21 3 891 22 6 134 1 5 20 1 447 21 2 807 ALR 2 5 O 3 4 3 21 237 22 4 4 1050 O EX CE VHF 3 5
80. 0 1281 0 000 20130 50 307 300 HHHHHHHHHHH 1010 20130 4 27 TROTIS AET AZ bI Vr FNF LATITUDE deg LATITUDE deq 10S 10S 40E S0E 60E 7OE LONGITUDE deq 1 2010 06 25 0628 06 28 07 01 07 01 07 04 DD gt pp 281 1992 2 pp 274 1999 3 Chinmaya Prasad Padhy Debabrata Sen Prasad Kumar Bhaskaran Application of wave model for weather routing of ships in the North Vol 44 Indian Ocean Natural Hazards pp 373 385 2008 4 T K Panigrahi C P Padhly D Sen J Swain 98 5 0 Larsen Optimal ship tracking on a nav igation route between two ports a hydro dynamics approach J Mar Sci Technol Vol 17 pp 59 67 2011 Tolman H L documenta tion of WAVEWATCH III 2 22 NOAA NWS NCEP OMB Tech Note 222 133pp
81. BAET I ZAF Yy YRR A LKR Ze MEIRU ion nS 2 RAOK 3 ZED ERMEC TRH lee 67 3 1 47 2 1 2 47 2 1 47 2 15 2 26m 79 1m 4 0m 5 0m 4 0m 4 5m 5 0m 3
82. J Os 5 6deg u v r 0 4deg 5 6deg yy7 KO 4 3 ZZ Z lstOSA ba 2ndOSA 10 1stOSA 1stOSA 10 10Z 20 20Z 10 107 20 20Z dD CAVE AGAR CREE OS AOF 1stOSA 1stOSA 10 10Z 20 20Z 60 y 0 9604x 38 652 y 1 5696x 39 874 50 wm A gt lt 6 10deg ne a 5 10deg 1
83. 5 CAR Sp A diag k 12 E 17 180 T 0 17 180 2 B t 2n 180 2 meter EYE PPS E 1400 Ht F al a 1100 ON 1000 A cals b BEA GPS d hk 1 a 900 800 600 500 400 100 E a ai E E a A in to im BS Vea veya vice 4 4 1 2013 3 6 35 1 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 160 deg PC I er NN P
84. Ed P OD Es Bs D Es Ed OP D 2 20b Ed E gt P W ec D gt E O gt Es Ed Ed gt ny Ore 0 Q 5 was Hees EQ2 r AEs pe eq BE r S Ed Ed gt P he Ed D gt P D Mo ta
85. 1 m 128x64 Ne 128 300m 10m HOG HOG SVM 0 1281 0 0 0O 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 a b X 5 128x64 7 1 M Enzweller
86. 10 4 NPR Non Photorealistic Rendering NPR NPR 11 12 r a EE witha 12 NPR 5
87. 128x64 64x32 32x16 16x8 2 18 2 0 1 5 128x64 Ye k fo1d CV 128x64 64x32 5 Fic 32x16 16x86 SVM 1 k k 1 k E la kA ka
88. 5 FHE 1 310 80 566 14 660 81 263 14 581 11 663 77 843 14 679 1 80 110 15 405 2 202 2 79 840 14 493 3 81 676 14 399 84 122 13 881 6 104 79 769 15 303 79 209 14 199 80 564 15 628 78 080 12 565 80 270 14 892 4 223 78 555 14 585 82 854 13 704 79 774 15 338 81 496 14 086 1 117 80 894 14 300 80 280 14 795 78 411 16 895 MER 83 271 15 469 15 746 80 546 13 338 77 676 14 680 2 81 908 14 886 1 873 80 549 14 385 79 482 15 113 85 822 14 014 99 957 77 483 12 107 73 811 14 229 p lt 0 05 p lt 0 01
89. 2 1 WAM 116 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 2 2 WAM co Ca aE H o DOP Dilution of Precision 0 Bete nm O p oa X DOP 1 o oa oallt 0 DOP HDOP Horizontal Dilution of Precision VDOP Vertical Dilution of Precision o DOP 2 HDOP
90. ELT SHI FSC ROR CHAR FV FMV KGPS FEP 0 1deg 0 3m KGPS 20 30m 4
91. 1 4 5 5 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27
92. 6 3 4 1 3 2 5 a 5 b KY AO AO
93. VHF 116m VHF 29m ait TADA 40n YHP 10m DSC Om DSC VHF DSC AIS 1 AIS VHE Me VH 100 tie ee A VHF
94. 2005 84 3 41 8 4 2010 1 1 2010 EE FTEU 13691 sot 1 68 84
95. 4 1 Fn 0 40 0 43 4 0 5 0m 47 2 15 L 10deg 0 Sdeg ie 42 3 2 4 6 Fn 0 40 80 Fn 0 43 E fez 4H 60 om AN 40 NN 20 is N 0 4 0 45 5 0 SEW mH s m 4 0deg S100 r E Fn 0 40 wa 80 E Fn 0 43 H 60 40 N T 20 N 0 D 4 0 4 5 5 0 5 3deg 100 fa Fn 0 40 te 80 E Fn 0 43 tH 60 om A 40 A P 20 m A
96. 5 AIS GPS 1 sec AIS GPS 2 sec A DAV Os GPSI k 6 BABA HTT 5
97. 1 BEE 150 pp 211 222 1981 12 See Atal C 10 2 pp 157 177 2010 Umeda N Matsuda A Hamamoto M and Suzuki S Stability assessment for intact ships in 2 Ne 3 the light of model experiments JMST 4 pp 45 57 1999 69 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 o ABS Pacific a a TE 2
98. 2010 1 1 12 31 1 99 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 UO2 2 o
99. 2009 1 4 5 IBD ON 1
100. CO 1 GHG IMO 8 5 3 1 CO MO 2013 1 CO 4 1
101. 15deg Fn 0 40 H 5 0m 60 10deg Fn 0 43 H 5 0m 80 15deg 77z 0 43 AH 5 0m 100 Sdeg Fn 0 35 H 4 0m PT ee oO 4
102. ate ae FES 1 310 645 49 2 529 50 7 7 450 116 43 4 1 109 41 4 49 239 2 246 43 3 cease 290 60 5 180 62 9 37 204 160 49 4 148 41 8 115 49 1 42 37 5 308 48 6 7 353 104 47 7 165 51 4 68 49 6 74 54 0 5 884 328 49 5 194 48 1 49 45 8 WER 246 56 0 16 165 224 48 4 175 42 9 2 155 61 8 27 375 359 47 2 131 43 8 x p lt 0 05 p 0 01 p lt 0 05 0 1281 0 000 20130 50 307 300 HHHHHHHHHHH 1010 20130 4 27 3 2 2 3 2 1 945 5 1
103. 1 _ ee ee MA 2 1 1 Zheng
104. AR 3 1 2010 3 2 BBU BOR 2011 aE AOA je 7c 0 105A T oae O 112 3
105. 2012 35 1 GIS System Geographic Information 2 2 1 ICC Commerce MB International Maritime Bureau 2012 D 1 2008 2012 International Cha
106. 50 REA 23 23 233 224 amp 96 161 5 173 amp 77 32 162 025MHz 19 14 16 7 CHS EK YE 5 24 2 9 C1assB AIS 4 ClassB AIS 23 GER 6
107. PC Bluetooth PC PC PC 1 1 TEORA EL 1 3 3 3 1 0 1281 0 0 0 20130 50 30 PIO HHHHHHHHHHH Wi 2013 4 27 1
108. PUSH PULL KF Direction 0 12 3 18 4 1 2 3 4 4 1
109. 1 1 1 1 3
110. 1TEU CO 0 1t CO BBU BOR 294 315 122 040kg 0 PID UCC BBU BOR 1 153 557 913 790 21 5 OCC co2 TEU CO2 t c02 4F t CO2 TEU UCC 859 242 426 008 UCC 913 790 477 019 6 BBU co2 CO2 ooo t c02 TEU t CO2 TEU mile 7
111. 3 2 gq 0 Fig 3 Hig 3 amp fig 3 b Ey Ex Eg D Fig 3 a Epy 22 E M ship gor ereerrorse or ey th giston f Collection and distribution Zone Ap
112. AIS AIS AIS AIS H 7 1 2009 3 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 2 Vo1 31 No 1 pp 31 38 2006 6 3 2005 http www tra
113. AIS aie 2 1 2 2 ITS ON OFF VICS 8 aioe M1
114. 1 4 3 3 1 0 fig 2 Ep M ship M 7 20 ship hr W 9 W 9 0 8IM 1 7 M 0 4 M Ep gt 16
115. 5 7 BE g 17 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 V gt 8 ek n jzi OF v g L E A ee 3 T2 J 7 ede 7 VA a a w 4 2 2 RERET MPS 1 MPS 5 ype 5
116. after in minute hour meter cable mile 1 5 minute 12 5 meter s 1 ao A minutes hours meters miles cables one n at Thank you report iE Thank you for reporting your report ERO for for reporting for your report 2 5 2 2 2 4 ORBIT S Zev BRA X Bo Os i Don t close IE Stay clear Don t close
117. 100 27MHz 1 VHF VHF DSC 5W 62 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 ae Gea eka 3 3 1 2 1 5W VHF 3 5W VHF BEA AEE Cm VHF 1 8
118. Class B AIS 2 3 2012 AIS 3 13 21 8 30 9 6 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 17 1 10 50 1 100 900 3 20 AIS 375 913 614 3
119. 0 1281 0 0 0 0O 20130 50 301 310 ODO 10 10 20130 4 27 3 1 2 3 5m 2 9m 0 9m s CR 0 9m s 0 6m s 0 9m s Fait 3 15 30 1 RE L THEE SK 3 5m 10 1 UL7 00 1800 2400 3000 3600 400 6000 66 2 2011 3 11 A 14 46 16 46 Sway 1 0 i Wl 0 5 ETT so Surge im ee ot TTT eee 10 0 ne Heave 8 0 0
120. 2002 2010 2 9 33 2 InformaPlc Lloyd s List Intel ligence LLI
121. 201 91 46 2 169 84 2 2 AIS ClassB AIS AIS ClassB AIS 2 24 6 8 ClassBAIS KEJL 24 9 12 A 10 22 A fe Uf AIS ClassB AIS AIS
122. Tai HOG SVM 1 JA a ene TROM EIER A TRAIT TEV CRS lt T 2 3 HOG SVM 4
123. 5 AIS 5 4 AIS 5 10 2 AIS 5 1 AIS ClassB AIS 3 53 4 ClassB AIS AIS ATIS ClassB AIS
124. 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 PC A B C 3 A C
125. 20 563ton 195 5m 29 4m 2 2 3 COE DICH AMER e HA ae m7 LICE 1 ICED OE RO Be al SR LTT PL 4F MP 16 20 3 0841 200058 ne HEME idee S EHe hop H fi ik AERC T MOUS Ferer Hm LED rd ED Ao 3 AY AF DCA aU teal IL 2ST ANZ EVLA FE SNERRE AFR ZI EB 74 Pi AVL
126. AIS A 1 2 15NM 20 ar 2 2 5 3 1 TIEC IEC61993 2 6dBu 20 20NM ele Cs 4 2 5 1 AIS KANRIN 47 2013 2 IIU Technical characteristics for an automatic identification system using time division multiple access in the
127. HAERA A E RA 16cm 0 1knot 0 6deg mn 1 Table 2 3mm
128. 5 6 3 2 2 1 1 p s 3 s x ifs fit AAH LEI Ri pity ad 98 6 detectObject O w A 1 O null initialize list of detected object for each scale s Is Scale 7 s scale the image with factor s for each horizontal position
129. ETA 2 ETA 4 3 500 9 AIS PC
130. 1 2 7 VTS UY CH 2 1 ame S Kia CIA ree CBS AR oo My ele ae A maru XY 72 E CRA VTS VTS 2 2 You A maru f
131. 2 2 1 1 X Y 9 Irad V m s 09 1 Pa tibet 1 y Vsin y V0 Ml TK 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 o rad s 2 0 w 2 1 K w w T T 1 i J T 7 21 sec K 0 18 V 6 17 m s ela
132. Oe ee cea OC deta ak 3 2 2010 6 6 2010 2 2010 Oa HX se aD kv am 986 1 28 233 12 io 06 149 4137 a 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 2010 DRHE 1 002 4 DIK RT
133. 1 5 ta 7 gt 1 2 AQ HHS EE LAA RA RD OS ERIC E V OBR 1 1 2 3 2 5 1 1 1
134. p p 0 01 3 3 AIS AIS 5 4 1 2 3 CPA 4 5 94 96 85 98 98 4 i m 2 32 a 3 a SHAE OMD T T 40 60 80 100 4 AIS 2 p 0 01 p 0 01 p 0 21
135. y L x y D x y W E EL Mi 353 2012 7 2013 3 4912X3264 1228X816 Integer ssd 0 for int x 0 x lt W x ssd L x D x E ssd W 3 CPU 3 3GHz4 12GB 6 353 1 264 9 5 E 76
136. 1997 2007 18 3 62 80 2 2 70 1 40
137. 15 9 3 500DWT 10 000DWT 500DWT 10 000DWT 500DWT 40 Om 7 0m 6 Om 3 0m 10 000DWT 131 0m 19 Om ZEX 16 Om 7 0m Line 1 Dine 4 line 2a LOPS BATU YZ lines line 5 Line 6 10 000DWT Line 7 Line 1 Line 4 4 Line 2 Line 3 Line 5 Line 6 Line 7 2 L 50
138. 2010 Lic 4 4 2 m X ee 2010 o s5 Ee eee 185 181 4 iat uae ee CO 3 1 st SAKA OT OE Vancouver CAN gt Busan CH 0 ZO ett 113 226 658TEU CE EA APL Hyundai MOL PNW Pacific Northwest Service PNW 6 479TEU 5 Kaohsiung HongKong Yantian Shanghai Busan Taco ma Seattle Vancouver Buan Kwangyang Kaoshuing PNW 1
139. e g Foxtrot 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 eg Foxtrot 4 vessel gt ves LFA Aho CALM ANE 3 3 3 1 eg November Victor a lhiny Cites 2 a 2 e g Bravo Charlie Echo Thirteen teen 3 4 BE 2 2 1 6 r 10
140. 239 pp 81 86 2003 3 KRAF RRI e AEIR 3 1 pp 59 60 2005 1 MPS 127 pp 51 56 2012 9 PTFE 12 2011S G5 24 2011 5 MPS B2G Vo 66 No l pp 46 50 2010 3 4 5 6 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270 OF W XE WMA Re
141. Vo1 42 pp 115 126 1995 12 8 A Bandura Self efficacy Toward a Unifying Focusing on s Learning Psychological 191 215 1977 Theory of Behavioral Change Review Vol 84 No 2 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 SAORI Be 3
142. 1 GE 2004 2004 2 No 121 pp 49 54 2009 3 DB PR GE No 117 pp 43 48 2007 4 0 0 No 115 pp 11 16 2006 5 AR IEBA RRRA RET JI OB No 116 pp 45 51 2007 0 1281 0 0 0O 0 20130 50 307 300 HHHHHHHHHH 1010 20130 4 27 Trip Distribution Modeling in Tokyo Bay based on AIS Data Student Member OEl Hocine Tasseda TUMSAT Member Ruri Shoji TUMSAT Abstract In traffic modeling a model is often assembled to simulate vessel streams within a
143. 2 42 ee ee ee e g SN TE a 3 0 FED ATCA AACA BERGE AGH EIB ELTA O ek JER iH BA Te AT PETE D DAMN ICOVYT HAP LTE HP Maritime English Initiative eee WP 7 1 Yoko UCHIDA Naoyuki TAKAGI What Did You Say Why Communication Failures Occur on the Radio The English
144. W 1 11 1 11 12 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27
145. OME Re WA HERS 1 S VLCC AIS
146. 0 4 1
147. AIS 24 KYO AIS ITS PCH AIS AIS AIS
148. 10NM AIS 3 3 20 2 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 2 3 20 1 648401 8527 17805 2 75 3 20 2 648492 7105 15928 2 46 3 20 3 648478 750 7811 16372 252 2 1
149. 2 Case 2 A B B C A C A B B C BA B A C 6 C HoH B A Oe 2 2 2 AIS AIS AIS
150. 20 DWT 3799 CO CO0 2 2456 CO 1 RK 2006 E 2009 12 CO 2004 9 No127 pp 181 188 2012 9 12 5m 2012 3 v ny 2 AIT No 560 S 3 4 5 0
151. 299 uate gt Song DIZ DEATHLY T L b EROE PAE 1 a 3 HED 3
152. BE OF e g boatswain 6 IV fr gt Ec 1 ACL e g light right 7 v gt b e g vessel b 8 f gt p e g foxtrot p 9 z gt ds e g zoo zero ds5 10 7 s e g sea she sip ship 11 6 gt s e g thruster s lt 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 speed 2 su pii do speed TROD 3 1 d tl speed 2 d d 3 d 2 DD 3 CE 3
153. SSR WAM Wide Area Multilateration WAM WAM TDOA Time Deference of Arrival WAM 3
154. ADS 5 Ground Truth 3 HOG
155. E029 Sf DE AE 107 20 30 CO P H Ft Fae eS e 1 eV erp lcae ie x Co C2aY7 7 OF yz 3 CO 3
156. EH 2
157. 228 305 91 396 AIS ETA AIS th fiat AIS B AIS 4 AIS AIS AIS
158. 1 9 10deg Ap Lpp DLpp 2 R 8 10deg 4p7p DLpp 9 10deg Ap Lpp DLpp 8 10deg 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 3 5deg 0 4deg 1 5deg 5 6deg 5 Y Lpp 5 10deg 3 5deg 0 4dedq 1 5deg 5 6deg X Lpp 4 Y Lpp 6 6 35deg X 6 35Sdeg 5 LT Ap Lpp DLpp 35deg 4p7pp DolLpp
159. 2 GS 7 MEZZ 5 6 kts 2 2 HEZ 7 3 He 2 7 Wa 7 gt 4 Ha 2 7 eS ee WR 7 1 33 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27
160. Fig 5 Fig 6 MPS MPS Fig 5 MPS 0 01m 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27
161. 2 4 3 27k fix OD FE step Z72777 4VayVe7 VAS Ca 2 E Edge Imase E Edge Image Fig 1 a Input image 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH WW 20130 4 27 c E Edge Image Fig 1 Sea surface estimation by integration of Laplacian step2 E y 2 y DL Draft Line Fig 2 DL c DL Draft Line image Fig 2 Draft Line Detec
162. 23 63 3 8 lt gt PC 1 lt AIS gt AIS 45 AIS
163. 2 3 AIS MAA AIS 3 2 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 Be BR 2011 3 400 2012
164. A40 8 20 8 40 11 29 5 AO 5 62 5 10 50 0 6 75 0 A40 9 81 8 22 R 75 9 4 80 0 Ce Tes 5 N E A A40 1 aE AARS OD ES CB
165. sp s WUC pr Bl AR 3 31 Be tre ICA LEO BREA O RAMS ICI 8 4 4 7 lies 1 53 2 SMCP e g My flag state is Korea My last port of call was Busan My cargo is crude oil 126 3 2 3 2 HY SHITE LEAARA HE AO Rex HY OME UROL 2 Onhe NA
166. ETA ETA AIS ETA ITU Rec ITU R M 1371 4 ETA AIS ETA ETA ITU AIS
167. if LY when 36 a Your officer already bring to the hospital iE Your officer has already been brought to the hospital already CUO oO Cl IAS all ay HAN After overtake follow her iE After overtaking follow her after overtake Don t hoist destination flags iE You are not flying destination flags Your destination flags are not visible Don t hoist Cli BE OMRLC 2 hoist
168. 2 2 CO2 CO2 IU CVS BRERA LER SA EDS 30 60 2 2010 z 1 tod Be E BP oo oo at oo irs oe World steel World crude steel output increases by 6 8 in 2011 http www worldsteel org media centre press releas es 2012 2011 world crude steel production html 2013 35 1 1 mm FF 46 2 2010
169. 8 35deg EE Ap Lpp DLpp 5 35deg 7 D7 Lpp 8 Ap Lpp 71 7 y 0 2369x 3 895 eo 0 1446x 3 8329 2 i E a 5 10deg _
170. WR Padhy et al Panigrahi et al WR WR WR WR 2 2 1 NOAA NCEP National Oceanic and Atmospheric Administration National Centers for Environmental Prediction 3 WAVEWATCHIII Tolman 97 Va MSSG A Multi Scale the Geo environment Atmosphere component Takahashi et al CU 2 2
171. x 1 P R1 X 100 50 X y R2 X 0 4 1 y 0 2 0 4 0 6 3 A1 A2 0 1 109 T M MHE B Time 0 Cost X3 SA R1 R2 HA la CO 8
172. amp LEMAR EMS eV GREDS 3 2 1 645 Scheffe sF test 3 3 3 2 3
173. R L MRO SESERKEMY Ice Me Soe lore on Sader Fecal Cis 3 O 3 2 4 ASV SSeS CH 4 VTS
174. 1 eic Each message includes A a reserve slot information i a ReReserved slot 1 SOTDMA M20 Case 1 A B C A B A BB C A B 6 A slot0 12345 6 7 mi wy ALLA t a we i el lia eS whe Ship positions Slot images Case 1 slotU 12345 67 aod we WLLL Sy ft 4 F cl lel XL wy f wy c le Ship positions Slot images Case 2 2
175. 4 1 24 http www e stat go jp SG1 estat NewList do tid 000001011528 2013 3 11 2 SUA 20 3 p 43 1995 2 3 PRIA LCA Vol 126 pp 173 179 2010 9 4 Vo1 124 pp 185 192 2011 3 5 Masaya YUKIHIRA Hisaaki TAKAYAMA Kenichi SHIMIZU and Masaji GODA Study on the Sea Ship and Seaman Orientation of Japanese Fisheries High School Students the Relationship of Student Attitudes Proceeding of Asia Navigation Conference 2011 pp97 104 2011 11 6 Vol 55 pp 65 72 2006 2 7
176. ae 3 2 2 6 7 CC 6 7 IIZ EREZA 8 9 X8 9 ROM 10 7 91
177. Eig 3 MPS MPS MPS Fig 4 MPS MPS 9 0sec MPS
178. 2 2 1 2 2 1 1 OR o Ee 89 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27
179. 25m 25 30 1 MV Rea 4 C0 4 1 CO CO Ox 1 1 CO 1 CO C0 c4 DST v CO CO kg CO 4F c4 CO kg CO 4F DST v 1 4 2 4 2 1 CO C02 DWT 1 MT CC CO 2987 8 kg CO kl
180. 4 ME D mm 5 0 1 2 4 0 1 0 0 8 3 0 os 0 4 r 2 0 J 0 2 1 0 0 0 F Z j2 A 2k amp ae ie 1 ClassB AIS o ee 2 549 14 1
181. 3 AIS Message ID 6 Weather Information 20 13 O OSAKA MARTIS OHA OSAKA VTS TOMOGAHIMA TInformation 20 1 6 Warning 20 3 EO AIS MessageID 8 MessageID 12 MessageID 14 BISAN MARTIS KANMON MARTIS
182. fly show SMCP 4 is are not visible Your destination flags are not visible ht 2 4 RA Stand by Channel 16 IE Stand by on Channel 16 16 16 on SMCP 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 Keep starboard over the fairway Ha IE Keep to the starboard side of the fairway to over the fairway Keep to the starboard side of the fairway i You will meet A maru after 30 minute IE You will meet A maru in 30 minutes MHOENI SDD X
183. 6 ane 6 2 2 000 2 000 2 000 4 5 oc HL Here
184. ClassB AIS 5 1 ATS Vol 122 pp 35 43 2010 3 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 AIS ml im a AIS AIS AIS
185. ee Aue ine 6 1 He Cee Hh 1991 2 ASR p 102 2008 3 p 126 2000 4 2004 5 Kouhei HIRONO Wataru SERA Masaki FUCHI and Kinzo INOUE A Theoretical Study of the Draft Reading Device No 114 pp 165 170 2006 3 3 p 783 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH WW 20130 4 270 OIRE Be eS
186. An ww ps a 1 4 3 5 8 9 12 nO DAE a HE A e g bat bet bet 4 work g gz gt o sg e g work walk ei OK Frid
187. 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270 HERE RA
188. 1 Lep m Bria m Dua m V kt 10 50 2 1 0O XoYoZ C xyz 2 G 3 1 3 5deg 0 4deg 1 5deg 5 6deg zig zag Z 2 2 BIR V A GEA 6 10deg 35deg 6 10deg 20deg 3 2 Ze 3 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 2012 16 1 5deg 5 6degM 2012 17 3 5deg 0 4deg 2 GPS
189. 3 000DWT MPS ee gt GRR BR CREE MPS 1
190. AIS AIS Receive stronger message p Garble AIS DIZ AIS AIS jee CG AIS 2 2 1 Cue AIS
191. RPN Risk Priority Number 2 3 4MSE 4MSB 4M Man Machine ax Media Be Management SE Education Engineering Enforcement Example Environment 3 FMEA 4MSBE Dl 115 0 1281 0 0 0O 0O 20130 50 301 310 0 0 HHHHHHHHHHH Ww 20130 4 27 3 TDOA WH
192. Table 1 Principal dimensions of KAMSARMAX By PEDEL LIV ERE L ORERERE OEE Loa RTK GPS 2 Fig 1 Side View of KAMSARMAX 2010 8 A 30 Table 2 Camera Specifications Angle of View 75 x 60deg 20 0m Optical Size Table 1 Fig 1 1294 x 964pix 79 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 Y
193. b d g bw bu u u 2 b b pubu eT 2 2 FH CHEICHANOBe Bit Y 2 2 1 Lee a LO ERARO 20 1 oo 9 gt or e g boat bought 2 a gt a e g cut cot cot 3 ee gt e 12 8 gt d e g the they d 2 2 2 pita
194. 6 8 14 16 69 72 73 77 86ch 3 5 2 4 VHF 25W VHF CA HX851JL 1 it DSC Digital Selective Calling System LAF DSC 1 j D DSC HX851JL 5 4 2 5 1W DSC JHS 770S JHS 7 mm
195. DER DEF VK 3 IN o TN CX er e FC FO x 1073 x 1 852 x DIS x f FO 6 87 x 10 5 x DSP 1 0 65 x LF x DWT x DSP 1 3 x V DSP 1 37 x DWT 1660 DWT 10 8 x CAP 12400 TN CO HEME Ca CO t C0 t FC t R FO kg km DI S nm 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 f DSP t DWT t LF V km h CAP 099 25g CO ton km TEU mile 6 CO 4 5 5 7 5 UCC PNW CO PEM ett 869 242 fee Seles PIV Ee es eee
196. a zig zag GPS 2deg 1deg GPS 1 x lt z y y
197. 2 3 20 cm sec cm sec 0 cm sec D Slow 1 4 D Slow 1 2 4 EJE D Slow 1 4 D Slow 1 44
198. BLS TeV 12 CMRE 3 30 4 2 1 1 RER D OD 0 1281 0 000 20130 50 307 300 HHHHHHHHHHH 1010 20130 4 27
199. 1024 17 2048 34 1 USB a Raspberry Pi 1 0 1 CHS PC PDA Raspberry Pi 3G 10 PC Web 0 1281 0 0 0 20130 50 30 PIO HHHHHHHHHHH Wil 2013 4 27 deg amp Haiti Jal HA sec 3 2013 2 3 1
200. 3 5 1 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 7 000 6 000 5 000 4 000 3 000 a 2 000 1 000 me ies ERA Em lt at S x E gor Pare yy Pai Le SH SI AS x x K pa 2 1500 1000 500 500 1000 1500 2000 2500 3000 mse ERRNO Ys Ds Ry ed Dd 7 3 77ch HKJ 86ch 16ch
201. co2 t c02 UCC BBU BOR UCC BBU BOR 913 79 239 767 114 7 BAD Fr MAMON ES CO 21 1TEU CO 1 2011 pp 9 2011 11 CO No 497 2009 1 CO No 124 pp 1 9 2011 3
202. MPS MPS MPS i FAR CREAR 1 MPS MPS 2
203. RORO eum Oe kare AO F ERU TTR PEE ARERR 1 GRAS 2009 RORO G M
204. 1720 0 1 17 7 1 15 6 Fn 0 35 0 40 0 43 1 13 1 29 1 43m s CHS 781 Fn 0 43 10 1Sdeg 3 3 2 2 Pitch Roll Yaw Yaw 7 4
205. VHF Vo1 49 1 2 pp 21 32 2005 11 Vol 123 pp 111 117 2010 9 12 CF 20 2 2011 http genome ib sci yamaguchi u ac jp wlan2 xoops 13 3 RRRS PREZ URE HER WHA 49 pp44 49 http wwwl kaiho mlit go jp GIJUTSUKOKUSAI KENKYU report rhr49 rhr49 a03 pdf 2013 3 10 14 Recommendation ITU R Rediocommunication Sector of ITU M 1371 4 2010 4 5 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 POMERS o PF Yyyy OH AIS GPS ATR
206. wna F a 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 3 1 1 AIS AIS 3
207. DAHER CH L TORDO AIA CO 18 6 63 3 1 68 am 3 2 4 WEM 4 LF 3
208. 0 01m Fig 6 MPS 3 0rad sec 20 0rad sec Wave height m Time sec Fig 3 Comparison of time history of wave height 5 7 N 7 I I a j NANNAN Y N 1 1 IN J 2 ny i i NW WM MW MM D V vw YS g Y 1 D 1 Exp J 0 Traditional MPS 1 E a New MPS 4 ws 1 1 1 1 l 1 1 1 3 10 15 Time sec Fig 4 Comparison of time history of mooring tether tension 10 104 10 Exp New MPS Traditional MPS Powerspectrum m sec 1 5 10 50 Angular frequency rad sec 100 Fig 5 Comparison of spectra of wave heigh
209. 20 1 2 97 1 3 B 63 38 47 4 1 13 2 M2 92 1 23 7 1 3 C 105 43 3 X1 3 31 0 X2 2 97 7 1 37 2 3 A C A 6 1 2 C 1 2 10 35 er Ow 31
210. HEV BR 142 138 3 AIS 3 20 3 3 1 5NM 19 SNM 4 100 0 ees 32 r ef 10 0 wis 1 0 A 0 1 L 5 1 10 100 Distance NM 4 49
211. PC 4 4 AIS CHAD AIS 3 16 AIS
212. 4 6 AIS AIS AIS AIS AIS
213. lt Java 1 2 2 2 3
214. 2 X 2 2 64x32 HOG 128 32 HOG 128x9 1152 PIETE O HOG Je CCl RE 3 2 SVM HOG No SAE SVM Pia SVM OpenCV NO 0 1 0 5 4
215. 5 HDOP HDOP 1 8 16 24 32 Dimensionless 5 HDOP 4 4 1 3 2 RMS O CBE GPS Global Positioning System GPS 4 2
216. Galant aa came 9 6 th 5 p cabin b r 2 3 a hune se 2 HB 2 sea si ship fp speed spi d fast feest oa b d g m n D r 7
217. 2 WOR URRRE CO 14 46 16 46 7200s 12 Tsunami 1 HOR RENE OT TII 7 ARE 0 6 0 8 1 0 1 2 fF Oton 5ton 10ton 15ton 20ton 20ton ANGE TI ORES COV CRRA Ue Aiur CHIR 1 L11 15 16
218. 20 DWT 90 95 92 59 2 5 3 2 75 1 3 5 4 2 5 2010 F LMIU Wess LMIU 2010 Se BOW AREY ee vies
219. 60 3 Dla 2004 4 2006 4 AO AO 30 2008 4 BAS Aree 2 2 3 A0O 3 arg E We aM ON RIFE MIDE LAR 2 T ACO Ce ENTO Hie BE Coq ee es 4 4 3 3 DARIO 3 ORX
220. 1 ClassB AIS VDO VHF data link Own vessel report VDM VHF data link Message ID18 ID24 Ship type30 AIS 51 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 3 3 1 26 C1lassB AIS 52 1 1 1 9 0N 1 5 5
221. GPS GPS NMEA GPRMC 600m 1200m AIS GPS GPS 1 1 3 AIS GPS ATs O lo Jo mani O o x saro o x X 2 3 oe ATA ARIE GPS ARV MEISE AIS 2 2 GPS
222. LTE 2 2 1 DTI Digital Terrain Model
223. Table 3 KGPS 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 3 KGPS
224. Ep 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 TV 20 ship hr W W 9 0 30 L L 5 M 0 L 7 M L 0 4 M E E Mship 0 8 0 6 0 4 0 2 0 C 4 0 6 7 8 1 1 2 1 4 D M a One way Route E TV 20 ship hr W W 9 6 30 _ h L 3M 0 L 7 M L 0 4 M OMe T a es Ps as L a ne 2 0 8 D M b Two way Route Fig 3 Effect of the Route Width 0 6 Hig 4 Tig 4 a o 60 g 60 g 4 D 4 9 D8 60 60 Ep Ep E M ship E M ship 23 l TV 20 ship h
225. 1 24 2 24 1 0
226. AIS 22
227. Be lees AWH E BIR 3 RCOEED NS aT MLDS BE S TeV RSE DS 2 2 1 3 1 2 1 5 BS eV RSI PORE
228. F AIS GPS AIS 3 ae TK 3 AIS GPS 1 ATIS
229. 1 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 SA 1 SA 3 Metropolis T sae aS
230. vessel o ka GAZE VTS o NN ee ee ema opposite course vessel same course vessel a 35 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 vessel on the opposite course vessel on the same course SMCP 2 3 VIS IS PCY Berl Day Jer Cle LG eC
231. 0 LS ALD ERE OBEE BROAD HERA E o THERM LTEC 2 2 1 rave 7 e a 9 0 u w t 19 OF b p T j t g k y s o d3 tf C h r m n g EC I A ve UT lax b d g s d3 aspirated p t k oe SN ee tf iE tense n 6 y o See cua
232. AIS AIS No 87 pp 11 16 2011 9 0 1281 0 0 0O 0O 20130 50 301 310 OOO 1010 20130 4 27 AIS FRA RE HA AIS AIS ATR AIS AIS AIS BED 2 AIS
233. lt AIS gt lt gt 4 4 AIS AIS SR 4 1 BETA AIS
234. Fig 7 KGPS amp b KGPS KGPS 60m 8l KGPS LY R lt S 10m my eo AU i J o 30 eo 90 Miz 80 fisd 210 240 hi Pi 4 05 1 uKGPS 0 300 time s ulimage v KGP5 viimape a Forward and lateral speed r deg min b Yaw rate Fig 7 Compere with image processing and KGPS Table 3 Accuracy of image processing Differences between image processing and KGPS Required accuracy fom KGPS KGPS
235. 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 2001 18 2009 65 j 8 SE HO gt AMR 8 3 NS or Y 5 2002 2004 2005 2008 i 2000 2010 3 2001 2009 2 3
236. 2 AIS 1 AIS 5 AIS 5 1 AIS AIS AIS 4 2 AIS AIS GoogleMaps 1 2
237. 3 710 3 482 1 256 1 734 1 000 DER AF EA EURA MEHE NA SA mK OC RU 17 664 TEU 10 000TEU 2010
238. 7 5 3799 CO 7 7 5 C0 2456 CO 106 8 7 F b fa 8 it 4 3 F gt 1 U 0 50000 100000 150000 200000 250000 bi DW 7 CO A 6 KO CO CO 40 DWT 1 3206 DCO
239. 1 410mm 1 010mm 1 220mm HS 4 040kef 12ton 3 EAT W Gon X2 GPS 4 4 1 3 CHEILE OD CBbLT HERO 0 AARC RE X Lpp 10 3 5deg 5 6deg 76 EAAOKE SICIZIELEPIL TWH 4
240. 2 3 2 5 10NM 3 3 AIS AIS 6 100 0 y nR 10 0 1 0 y m const Untransmitted rate 0 1 1 10 100 Distance NM 6 AIS
241. 2 3 8 0 n 0 Vp o i va 8 dt dt ge 1S30 0 2 2 4 MPS 9 ij i vab hei eK 9 1 ly
242. AIS AIS AIS 1 AIS TTS AIS AIS
243. AIS AIS AIS AIS AIS AIS AIS AIS AIS RTO
244. KI 2 2010 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 4 2 4 2 1 9 33 X3 4 5 500 50 500 150 2 648 2 421 6 7 13 CN
245. 3 1 eee ee eae Men aay dl aie ree cack 2 1 VTS No need position report 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 VTS
246. 645 3 918 0 876 3 926 0873 0 273 3 879 0 896 1 3 844 0 884 1 797 2 3 866 0 863 3 3 990 0 882 3 944 0926 2 451 x 3 844 0 836 3 851 0 860 4122 0 870 3 762 0 821 3 906 0 859 1 317 3 837 0 871 4024 0 890 3 838 0 924 3 946 0 874 0 495 3 881 0 864 3 943 0 871 4 020 0 989 nts 4 069 0 880 6 143 3 844 0 846 3 800 0 884 2 3 994 0879 1 324 3 919 0 882 3 824 0 855 x p lt 0 05 p lt 0 01 F 645 2 580 0 594 2597 0 586 2 563 2 500 0 626 1 2633 0 572 5 756 2 2 480 0 631 3 2 645 0 559 2 689 0510 2 975 x 2 556 0 642 2527 0 600 2 478 0 626 2 667 0 570 2 549 0 605 0 661 2 596 0 566 2 600 0 613 2 647 0 540 2595 0 639 0 476 2 558 0 618 2 619 0 547 2 551 0 542 nes 2 638 0 574 2 482 2 571 0 610 2 509 0 596 2 2 652 0 554 4438 2 518 0 629 2 664 0 521 x p
247. 3 WAM 3 1 4 WAM 8 WAN Wide Area Network SSR 500MHz 2 GPS Common View WAM 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 W A J RIE 68 4 WAM 3 2 SEBO
248. 40 Seely AO 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 6 2 2
249. f Fettet AS ho ote FREE T o PBR 0 100 200 300 400 500 met 4 6 1 Vo1 117 pp 183 189 2007 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 ea ERRORE B 100 VHF VHF 21 10 VHF
250. 35 13 313mile BBU 1 124 FRY bok Z 5 14 59 712DWT 4 93 TEU ISO 20 1 22 040kg DROME HE 1 35g EL 5 CO CO CO
251. 4 2 D 0 P OOS SI Es BEd ODD PDO Ed gt Es 3 Ed Es 3 1 5 5 1 ED D Es ISAK Ed 4 10 40 20 80 30 120 3 4
252. 59 2010 7 BWE 55 6 A pp 359 367 2010 6 8 642 2011 2011 6 9 WEK 689 2012 2012 6 GOHAR NAVIGATION 182 pp 39 49 2013 10 11 pp 166 169 2007 12 pp 80 86 2010 13 SER pp 238 2007 14 Wen Chih HUAN Hsu His CHANG and Ching Tsyr WU A MODEL OF CONTAINER TRANSSHIPME NT PORT COMPETITION AN EMPIRICAL STUDY 0 F INTERNATIONAL PORTS IN TAIWAN Journal of Marine Science and
253. BRIE SVM 3 1 HOG HOG 1 Hea HIE Ta 128x64 479 938 64x32 1134 2240 32x16 1952 3862 16x8 2280 4496 1 HOG HOG sinha abavet an hi 2x2
254. 16 20ton 1 2 4 2m 1 Surge m Surge 10 0 _max m preOt urge_min m preOt 5 0 _max m pre5t urge_min m pre5t 0 0 _max m pre 10t urge_min m pre10t 5 0 ur i in Api T m pre20t 10 0 e_min m pre20t 15 0 20 0 0 0 0 2 0 4 0 6 0 8 1 0 1 2 1 4 4 Ara SIC HL Shae Be Surge 10 0 2u 8 Surge_max m Hx1 2 m A amp Surge_min m Hx1 2 5 0 Surge_max m Hx1 0 amp Surge_min m Hx1 0 0 0 Surge_max m Hx0 8 amp Surge_min m Hx0 8 5 0 Surge_max m Hx0 6 amp Surge_min m Hx0 6 10 0 15 0 20 0 0 5 10 15 20 25 ton 5 Surge m Surge 15 0 Surge_max m pre0t 10 0 A Surge_min m pre0t 5 0 Surge_max m pre20t Surge mi
255. 2 3 3 1 67 33 1 AIS 2 86 CH 2 2 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 eA Ki 67 i X1 E Gy 390306 Sm ER 24F AC ii 86 m 2 2 AIS 3 2 AIS AIS PF BBA EVI 3 52 86 0 20 40 60 80 100 X3 AIS HEF FA 8 5 2 2
256. P 7 Es Ne Ed Ed b 2 0 0 0D PO0 0 0 Es Ed Es Ed CO COs PHB 4 4 1 EE Simulated Annealing SA
257. WAM 3 2 VDOP 2 3 6 7 1 ICAO Aeronautical Surveillance Manual DOC 9924 AN 474 First Edition 2010 2 K Pourvoyeur A Mathias R Heidger Investigation of Measurement Characteristics of MLAT WAM and ADS B Proceedings of ESAV 11 2011 09 3 NAVIGATION 182 pp 80 86 24 10 H 4 GPS pp 42 46 2003 fF 5 G Galati P Magaro V Paciucci Target Lo
258. 0 LAL BRAT RA ZITO 2 CAS TSS 1 35 135GT 1 6 1 1735
259. E E HA WAM Wide Area Multilateration tk TDOA Time Deference of Arrival 3 2 2 3 TDOA WAM 1 WAM FDS EO ABI ZEEE Cll VRE OPPS Obs x 2 3
260. 40 7200 s 0 3 2 0ton 5ton 10ton 15ton 20ton 0 6 0 8 1 0 1 2 4 5 Surge 5ton 1 0 3 5m 10ton 1 2 4 2m 3 5m 13 3 16 6 7
261. BE Xp 3 5 2 4 CO 5 CO 8 10 CO gt CO Co HEH CO2 CO gt 6
262. OO s 2deg 1deg Eo A 6 1 A a 1068 2012 3 2 17 2013 6 3 K GPS OP Ra 124 2011 3 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27
263. VHF 3 5 6 0 8W 5W 5 VHF 5 3 YVHF 5W 5 1 VHF 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 2 10m DSC 9m VHF VHF
264. 10 2 1km CO 3 Oo VK Sr Du il Bae BE Wx 1 10 XEF x 1 10 XCVXCEFXCO C 2 SG X YEr rRAV aT TAR 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 ec e ZH BE x 1km CO EH t CO2 km W kg EF x km kl C GJkD CEF C PEMA t C GJ CO C CO t CO7 t C CO BEM BIS CO XZz
265. 13 11 ClassB AIS 52 1 eRM2 t5BHE 3 4 5 44 15 _ 2 8 34 12 Ky ak AB ida X2 AIS GPS 24 E 92 3 AIS 10 38 5 ClassB AIS AIS 3 2 ClassB AIS 129 30 1 Tok
266. Ee eee ae eh a OCIS KEROS a DOS LT BOSS 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 2 EN 0
267. 7 s 7 w b 11 76 s 3 ee gt je 8 f gt p 9 z gt dz 12 gt dd PAHO HO DHS Lb fats w b d g ptk Pil Julieta Julie_ Foxtrota Foxtro_ seas isin visiting THAR Cb ARR ihe ean
268. AIS AIS 1 AIS 2250 2 AIS AIS SOTDMA 2 2 47 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27
269. EA 25 no a T BHAE Lie O70 mm 10 E 5 2 35 R 3 835 8 3 8 5 E g u 8 g t au E gp a K ig GM u oOo wm X a u gh e E E E E fF amp FS E H A 1 nli E F EDY YE AmA ob M PoE TAE m i o D M fA il A iE BIB pic X2 35 1 30 sida ae s T 20 is gt 5 lalaialll Wis 82 391 81 3S3 82 39 8213 8 3 SEER 85538 See eee EEE a i m i a i bs a at at A 3 C 1 2 3 1 2 1 4 ER 3 ho PR ke
270. X ia You now return to X Traffic Route IE You have returned to X Traffic Route You are now back in X Traffic Route You now return to X Gla X You are overrun eastbound lane JE You have left the eastbound lane You are overrun be overrun overrun You have left the eastbound lane You are now outside the eastbound lane a If you will meet her pass astern of her IE When you meet her pass astern of her when will
271. W amp Zev RSE IC EO RRR TeV OBA 3 2 1 945 pees FAY TREATED 2 1 EE LA UE Vics Bie cl teen 0 3 2 1 645 3 2 2 4 3 2 4 OL OBES TeV ARSE OEE OBAR AR amp OP 3 5 FHE
272. 1 2 0 1281 0 0 0 0O 20130 50 30 3100 HHHHHHHHHHH Wi 20130 4 27 o A oo FIV A HOG a H Pa 3 4 k fold CV Cross Validation 4 1 2012 7 24 26 A 2013 1 25 27 3 6 8 2158 4912x3264 APS C 23 6mmx15 6mm 18mm
273. 2 4 4 1 1 500 100 8 996 8 551 500 5 599 5 248
274. 3 44 5 AIS AIS 1 2008 10 2008 AIS AIS 2010 7 AIS 2012 10
275. sae off ee 2 0 0 0 1 0 0 1 5 1 s 6 2 llololol of 0 5 a smmm SB air MZ oO CCE i 5 b ee 6 BO Reena Al Al Neekin 4 el sl elel i 1 MRTE 4 OAC Ce 1 MM 5 op 4 a sl spe O A 6 6 1 1 AO
276. x WERA g Y GPS 1 Dl 3
277. 2 3 3 4 93 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 2 1 2 2 2 2 2 2 eo w mM M w M m 1 w2 2 3 FEO Rig 3 2 3 2
278. 3 3 HY OME 3 3 1 2 2 1 Cad 1 12 A B es O 2 Atte TWH EEL 41 Bravo 1 0 Bravo 5 D o 7 oo o 5 A E A 0 1 ou 2 gt ox Bravo 5 1 0 Echo 5 1 0 Kilo 5 2 0 Romeo 5 1 0 Tango 5 2 3 boat 3 1 0 2 a gt a 3 gt e Alpha 7 0 1 Tango 5 2 5 ladder 3 0 1 anchor 3 1 2 last 3 1 2 fast 3 0 1 4 ox 78V La 5 8 5 Bravo 5 2 0 Delta 5 1 0 Golf 5 1 0 Juliet 5 2 0 Five 5 0 2 Twelve 5 0 2 above 3 0 1 degrees 3 0 2 use 3 0 6 r gt ec I Bravo 5 1 0 Charlie 5 1 0 Golf 5 1 0 a pea Lima 5 3 0 Romeo 5 1 0 Sierra 5 1 0 Three 10 4 0 Eleven 5 1 0 flag 5 1 0 last 5 1 0 rig 3 1 0 7 v gt b November 7 3 0 8 f gt p A
279. 20 DWT ee eee ee eee CO Do CO 4 CO 196825DWT 35000DWT lt B Bye Ci a Fee 400000DWT 100000DWT b OFORO 4 5 2 KO CO CO HE 2 1081 8 999 10 2080 CO 1486 5415 6901 A A 5 3 C0 R CO 5 6 KI 5 6 CO PT
280. a gt 0 b 0 c r 0 d 7 lt 0 a b c d 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 3 3 4 3 5deg 100 X 10deg N E 50 1Sdeg OMI Hs 5 0 Hs 4 0m 3
281. iw 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 pa Canny Hough Canny SSD 1 3 10 5 SAD sum of absolute difference 4
282. AIS BtoB BtoG AIS 4 AIS AIS 1 Ala CHS LE AHO AIS ATS 4 LAN
283. IGM GM T 0 8B GM T sec B m RORO 2 1 Web BREL BAT JOS a3 Raspberry Pi 3 36 Analog Devices ADXL335 1
284. VDOP VDOP 1 1 VDOP 20NM 2 3 20NM 2 2 VDOP 3 WAM VDOP 1 8 16 24 32 Dimensionless B i EY IETS 10 000ft 1 VDOP 2 ee A 3 1 40 2m 32 5m 361m 545m 118 0 1281 0 000 20130 50 307 300 HHHHHHHHHHH 1010 20130 4 27 5
285. VHF 5W VHF 5W 0 8W 25W 1W DSC DSC 25W 25W 17 20 12 3 17 29m 20m A 3 VHF AIS 2013 3 9 D F D i i 150MHz AIS 86 4 74 2 32 0 1454 37 665 30 462 31 3 85 VHF VHF
286. c Two way Route Vessel on the Opposite Course Fig 6 Near Miss Map 7 gt 25 W 2 3 5 7 20 ship hr W 9 Fig 6 50 Im Fig 6 a DA Fig 6 b Fig 6 c 24 4
287. 2 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 3 I 2011 2012 i aauane 3 4 3 2011 4 2012 72
288. 8 5 C0 CO 3 CO2 CO2 2009 9 62 65 O02 CO2 CO2 2 2 1 1 2010 6 27 44 7
289. Eu 39 0 0 6 3 0 V 0 0 1 0 ai T 0 0 4 K X FX G6 4 ZO CHR ITRF aA MB aT AREA 6 S J OTSA oe XTAX BS dt 5 5S A B 2 0 TK 2 2 2013 1 22 35 ag ey aa AIS 1
290. klous close FAC A EVO 37 Stay clear Keep clear SH HAN I You are dangerous course You are steering a dangerous course AIERZA TT SMCP a Call me again when you arrival X line IE Call me again when you arrive at X line arrival when you upon your arrival at X line when passing X line when you arrive at X line at No need position report any more iE There is no need to report your position any more no need position report o Ni i No further gt There is no need to don t have to report your position any more position reporting is necessary Di 3
291. 0 oO 4 0 4 5 5 0 KINE iA m 6 Sdeg 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 4 KY 5Sdeg 0deg 4 6 Sdeg aay Acar 5deg H 4 0m Fn 0 35 ie
292. 1 CO Tes 4 2 2 BLM Shipping 1 1 4 2 3 LMIU 2010 DWT 2 2 5 3 5 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 2 KALUR ARES O ESAN DWT BRESAN 228954 196823 4 2 4 14 3 14 3 ie
293. 3 7 43 38 13 46 15 7 40 30 13 21 12 7 39 46 12 21 55 10 48 58 14 18 01 2 AIS AIS 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 5 2 AIS AIS 3 AIS F SFR a E KAGOSHIMA MARTIS 2 6 PRILIL M AIS AIS 3 es EE 4 AIS 3 2012 8 30 9 1 9 4 9 6 AIS AIS 5 1 AIS
294. 6 10deg 3 Q 5 35deg i i m 5 35deg y 0 0052x 2 0456 y 0 0187x 1 9644 0 8 6 4 2 0 2 4 6 8 deg 7 DLprp 7 y 0 2136x 4 6954 es amp y 0 1171x 4 4828 eS e o 4 eo 5 10deg a 5 10deg lt I E 6 35deg m 5 35deg y 0 0096x 2 8176 y 0 0331x 2 8432 1 0 8 6 4 2 0 2 4 6 8 deg 8 Ap Lpp E 3 5deg u m s Time s 100 a z 100 200 b v 4 A eM OW AKA YA rn i ff Time s ol 100 200 c rO 5 4 Time S 100 200 d 9 10deg 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 8 10deg 6 35deg 9 35deg DLpp 8 7 9 3 9 10deg
295. Conference IMEC 24 pp 170 179 2012 Naoyuki TAKAGI Yoko UCHIDA characteristics of Filipino mariners English The International Maritime Phonetic 2 International Maritime English Conference IMEC 23 pp 193 199 2011 pp 55 64 126 2012 1 2007 PM an ee ay PT NN http www coelang tufs ac jp modules index html 2013 3 Jung Ae LEE Korean speakers Learner English 3 4 5 6 Second Edition Cambridge University Press pp 325 342 2001 pp 147 157 1996 J JENKINS The phonology of English as an international language Oxford Oxford University Press 2000 Maritime English Initiative 7 8 9 Se eS ee http www2 2 katyodai ac jp takagi mei index html 2013 3 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270 RAND Db R TAISRAOHRAIR I RA W mA PH RA AIS
296. Fig 2 Original photo before image S 21 Fig 2 Fig 3 Convert to bird view and detect edge of the berth Fig 4 Measure distance from F P and A P to the berth Fig 3 Fig 2 OER HR CAL Fis 4 EP AP mig 3 EP AP 3 AO
297. Lpp 37 00m 1 057m B 7 90m 0 226 D 3 22m 0 092m d 2 90m 0 083m A 483 t 11 056kg GM 1 47m 0 034m 1 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 2 1 a b _ c d e D 6 x y E Roll Pitch Yaw ff Roll Pitch Yaw 24002 mio C7 AFN LL GM 2 2 2
298. OJAL li TAO REE h DWT 2 14 2 23 CHa Lk 2010 3 091 a her 105 3 eee TP 986298 Ain a o a r eam 5 C0 oT ws CO 30 DWTT 40 DWT 10 DWT
299. eae ly 1 1 3 3 1 3 BMI A B C A 4200 2360 B 4447 2831 C 787244221 ARCH 2 7 3 2 oA a analai 1 3 MR 3 A 78 70
300. 1
301. AIS 8 VDO VDM 4 3 3 E a eee 0 1281 0 0 0O 0 20130 50 307 300 HHHHHHHHHH 1010 20130 4 27 3 10 4 4 3 10 AIS 5 2 3 7 AIS amp RM T N Up GND a MP2 Transmit 4 2 3 10 O ClassB AIS 99 2 3 4
302. C 321 24 5 D 137 10 5 5 A 137 10 5 B 663 50 6 C 403 30 8 D 107 8 2 6 A 439 33 5 B 463 35 3 C _ 408 31 1 7 A 2 251 19 2 B 760 58 0 C 299 22 8 3 1 es 3 2 3 2 1 2 e SS Ne NO Ga sol arent VY CIS FCs 3 2 2
303. H 4 36 AA F Ye DC 2010 OR ST Or 185 on BBU BOR 2010 BBU BOR 3 3 2010 BBU 1523 BBU 152 3 BOR GR Say HF One eve BBU BOR 7 2010 8 938 BBU BOR 7 528 3 152 7 181
304. M LM 21 A Zabar HEITE 30 990 deg R 70 M a b f h j k d e TV ship hr
305. MPS 2 1 MPS KORE MPS Navier Stokes MPS Moving Particle Simulation Koshizuka et 1 D 1 D O 1 ee MM MPS Dp DCE HOR Lo CRANTHED RASNE 9 2 MIR MPS MPS PITA EZ MET TE MPS See ere oon ed
306. N O O EN 12 0m Fix end IOELU 9ABAA Fig 1 Calculation 2D tank model Table 1 Calculation conditions Particle numbers 125 829 Particle distance ml 0 01 Time step sec 5 0 107 Simulation time sec 15 0 Kinematic viscosity m sec 8 9 10 Wave height m 0 06 0 08 0 10 Wave period sec 0 9 1 0 1 1 Length of floating model m 1 56 Depth of floating model ml 0 2 Draft of floating model m 0 04 Spring length m 0 11 Spring constant N m 127 5 Particle of floating model Fix point Fix point 0 17m 0 17m 1 56m Fig 2 Mooring system 19 3 2 0 08m 1 0sec Fig 3 Fig 4 Fig 5 Hig 6 Fig 3 Fig 4 AEE E EOE Bik AICO MPS MPS
307. PRES EOE MR aT OIL MEMO EDERICOW CUE 4X2 FOKI AZ LAW AAAS OD se e WPO ECTE NEN TST AlLIDV 8 A 1 2 a8 ant na MA a
308. and origin issues an algorithm is developed to extract the Origin TAZ and Destination TAZ data from historical ships tracks The algorithm tracks all ships sailing from one TAZ to another and excludes any other ship that is not provided with an Origin TAZ and or a Destination TAZ The results of the Trip Distributions analysis show that the traffic is conserved between every Origin and Destination TAZ respectively In addition to trip combinations excluded by the constraint 13 trip combinations are negated with certainty In addition the results also show that the most attractive port is Yokohama Port and it alone generates and receives more that 20 of traffic without constraint and around 15 of traffic with constraint of the total traffic in Tokyo Bay Furthermore the results show that around 70 of traffic without constraint and around 60 of traffic with constraint is originating from within Tokyo Bay The results of this paper provides an effective tool for evaluating the distribution of vessel traffic streams loads and appraising the level of disorder caused in Tokyo Bay Furthermore the model formalizes the trip distribution into a matrix that can be used as a metric for traffic generation and evaluating the fluctuation in traffic and or TAZ traffic load assignment Nevertheless further research is needed to assess the traffic within the same TAZ by breaking down every TAZ into Sub TAZs 9 References 1 Hasegawa K et a
309. designated traffic analysis zone hereafter referred to as TAZ such as harbors and straits The traffic model usually consists of sub models concerned respectively with traffic generation and trip distribution In this paper the underlying behavior and distribution of ships navigating from an Origin TAZ to a Destination TAZ are analyzed to assess the parameters behind the destination attribution based on the amount of the generated traffic at the origin Then the uncertainty associated and randomness with the traffic movements is estimated based on the concept of Entropy Keywords trip distribution traffic modeling entropy traffic simulation 1 Introduction Trip distribution analysis is the process by which ships sailing from one TAZ to another TAZ are analyzed The trip distribution model is used to distribute the generated traffic from an Origin TAZ to a Destination TAZ Compared to land traffic trip distribution analysis where many models are developed based on traffic purpose route and costs related to every destination maritime traffic is constrained by the choice of the route the destination based on vessel type and cargo type and above all the capacity of the TAZ 2 Analysis Data Tokyo Bay historical AIS data collected from the TUMSAT Advanced Navigation System covering a period from the 11th of November 2011 to the 20th of November 2011 is used for this analysis 3 Analysis Areas Tokyo Bay w
310. em m o es psC JHS 32B 29m VHF 2013 2 14 0 Om U SHALA SAPERE OERI OE fe ALAA R AEL LT 2 VHF 4 1 2 6m
311. in a disturbance in the test data One important test criteria is the transverse landing speed and this can easily be deducted from these tests The use of rudder and engine force can say something of the decision taker s sense of control during the operation and also an indication of the effectiveness 6 REFERENCES 1 Husjord D and Pedersen E Operational Aspects on Decision making in STS Lightering Proc of the 19th International Offshore and Polar Engineering Conference and Exhibition ISOPE 21 26 June 2009 Osaka Japan 2009 OCIMF amp ICS Ship To Ship Transfer Guide Petroleum 4th Ed 2005 pp 3 50 M R Assessment 2 Situation Awareness Global SAGAT Technical Report Hawthorne CA pp 789 795 1997 Husjord D Pedersen E and ritsland T A Integration and Testing of an STS Decision Full Mission Ship 2nd International Conference on Ship Manoeuvring in Shallow and Confined Water RINA Trondheim Norway May 18 20 2011 3 Endsley Technique Northrop 4 Support System in a Maneuvering Simulator 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 BS
312. lt 0 05 p lt 0 01 0 1281 0 000 20130 50 307 300 HHHHHHHHHHH 1010 20130 4 27 3 3 30 5 3 2 2 got COLI EMbS MEK REOARILER F
313. 0 FMEA 4MSE 2 FMEA 2 1
314. 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270 Bat HAA BAHAR 4
315. 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 Be BU CO 1 CO gt 9
316. 2 2 E 2 27 6 27 6 To FRUYT VAC SF Ey Pie Oo ORE 3 70 io 7 Canny 1 260 SR
317. 2002 User manual and system version 6 Takahashi K X Peng K Komine M Ohdaira 7 K Goto M H Fuchigami T Sugimura Non hydrostatic atmospheric GCM Yamada development and its computational perfor mance Use of High Performance computing in meteorology Walter Zwieflhofer and George Mozdzynski Eds World Scientific pp 50 62 2005 No 127 pp 197 203 2012 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 2002 BRO 2
318. 20130 4 27 42 FAD 66 ETA ETA JST 50 90 3 6 AIS 3 7 2010 7 AIS 8 AIS RAAT Sa PREV
319. ABCA CAAT PRPS RF Ze ORJ 2 FF LSR J lt RACBADIVAs 4
320. C 4 2 AIS GPS 4 AIS GPS GPS AIS GPS
321. CO 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 40 CO HE 8 8874 1 3206 CO CO0 20 CO 3102 3799 CO 170 110 n gt mn gt gt MER OO BR A W gt 100000 200000 gga D WT j jint Ba 300000 400000 SU0000 HL Rotha ogs 5 CO A 7 E r I a E 4 it 4 Fa 3 i i 0 0m 1o000 150000 700000 250000 RCW cee Le A ee A me SU Re Cb eat 6 CO 5 4 CO 2 12 5m 7 5
322. D M Gavrila Pedestrian Detection Survey and Experiments Monocular on Pattern Analysis and vol 31 no 1l2 pp 2179 IEEE Transactions Machine Intelligence 2195 2009 2 N Dalal Oriented Gradients Proc IEEE Intl Conf CVPR pp 886 893 2005 3 KEDEZ vo1 117 pp 175 182 2007 4 vo1 113 pp 107 113 2005 of B Triggs Histograms for Human Detection 86 5 PEMA OX Ee IER HSV vo1 116 pp 69 76 2007 6 C Burges Machines for Patter Recognition A Tutorial on Support Vector Data Mining and Knowledge Discovery 2 pp 121 167 1998 LE
323. Ek MM H 4 ee ara ne 4 150 Fig 5 Draft line estimated by proposed method Fig 1 289 8cm 2 5 PE EAN rN JAED Oka Oe Ol dla a i a NAA
324. KGPS Fig 5 b EP KGPS 0 24m 0 16m Image 10 Qn KGPS ry ae 2 a a N ee 4 ee el 2 0 SS Co 0 30 60 90 120 150 180 Time s a Distance between F P and the berth Image 10 SSL KGPS au a7 E ii t a 6 So 4 b Distance between A P and the berth Fig 5 Measure distance by image processing and KGPS 2 2 0 1281 0 0 0O 0O 20130 50 301 310 0 0 HHHHHHHHHHH Ww 20130 4 27 Fig 6 Coordinate system for motion measurement
325. Technology Vol 16 No 1 pp 19 26 2008 15 Dong Wook SONG Photis M PANAYIDES MARIT IME LOGISICS pp 195 199 Kogan Page 201 16 42 4 pp 41 62 2011 Me HF TAA 0 1281 0 0 0 20130 50 30 PIO HHHHHHHHHHH Wil 2013 4 27 FERRO K PRTR 8 5 t CO2 CO 3 BEA FJI CO HE COZ tA 2010 CO 1 2007 IMO
326. VHF maritime mobile band ITU R M 1371 4 2010 http www itu int dms_pubrec itu r rec m R REC M 1371 4 201004 I PDF E pdf 3 AIS 6 2007 4 AIS AIS Class B AIS 117 7 2007 5 fe EE AIS NAVIGATION 151 pp 73 78 6 IEC International Standard Maritime navigation and radiocommunication equipment and systems Automatic identification systems AIS Part 2 Class A shipborne equipment of the universal au tomatic identification system AIS Operational and performance requirements methods of test and required test results http read pudn com downloads 145 doc comm 633510 Documents Class 20A 1ec61993 2 7Bed1 0 7Den pdf 0 1281 0 0 0 0O 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 270 AIS ik Fh ME i HA
327. a natural operational environment in a navigation simulator Affords have been made to simplify the structure of the user interface and not overload the short term memory with information In the development of the graphical GUIs and various user interfaces questionnaires interactive interviews graphical proposals for information parameters were discussed with several groups of experienced mooring masters The mooring master is on the bridge wing in the final decisive phase An immobile device inside the bridge will be inaccessible but a hand held device can communicate the information needed Relative speeds distances and the angle between the two vessels are parameters mooring masters use as references in their decision making process This information is considered to be key parameters in the process Different paper prototype displays and mock ups presenting this key information in a simple way were further integrated and tested in a simulator setting 4 2 1 THE DSS The Master PC processes data collected from GPS and AIS sensors or in this case from the simulator The size of both vessels and the positions of their GPS antenna must be entered into the Master PC before start up The portable Tablet PC receives data wirelessly from the Master PC and presents the result as GUIs Figure 2 Tablet PC Mooring Master Figure 2 System structure with wireless connection 3 TESTING THE DECISION SUPPORT SYSTEM A
328. addition to trip combinations excluded by the constraint 13 trip combinations are confirmed with certainty to be improbable Traffic Generation No Constraint w with Constraint Tokyo Bay Yokohama Tokyo Chiba Kisarazu Yokosuka Funabashi Line Kawasaki Anegasaki Traffic Attraction St m No Constraint m with Constraint 0 1 5 i mm Bm Tokyo Bay Yokohama Anegasaki Chiba Kawasaki Tokyo Kisarazu Funabashi Yokosuka Line Fig 4 Illustration of Traffic Generation and Attraction Distributions Fig 4 shows that the most attractive port is Yokohama Port and it alone generates and attracts more that 20 of traffic without constraint and around 15 of traffic with constraint of the total traffic in Tokyo Bay Furthermore the results show that around 70 of traffic without 0 1281 0 000 20130 50 307 300 HHHHHHHHHHH 1010 20130 4 27 constraint and around 60 of traffic with constraint originated from within Tokyo Bay 8 Conclusion This paper introduces a review of the Trip Distribution theory and its fundamentals The Trip Distribution theory is then used to model vessel traffic streams navigating between different TAZs in Tokyo Bay based on AIS data In addition to the origin port which is not provided within the AIS data a data review also reveals that the destination port provided within the AIS data is not accurate and the AIS data entry non compliance rate is high Therefore to solve the destination
329. aki Port and 9 Kisarazu TAZ Area delimited by Kisarazu Port 4 Research Method AIS destination data is one of the dynamic data that every ship should update after departure All ships sailing into a port or in the vicinity of its boundary for the purpose of entering the port to which the Act on Port Regulation applies should enter the destination code designating the destination port in the column for information on destination as summarized in Table 1 Table 1 AIS Codes for Tokyo Bay Port Destinations AIS AIS Destination Destination code code Port Port Chiba JP CHB Yokohama JP YOK Port Port Kawasaki JP KWS Anegasaki JP ANE Port Port Tokyo Port JPTYO JP KZU Port Following the above port destination data is extracted from the AIS data Unfortunately the data is not accurate and the rate of non compliance with the entry method is high In addition AIS data does not include the origin port necessary for our analysis Due to this it has been concluded that the AIS data is not suitable for extracting destinations and origins 5 Tracking Algorithm To solve the destination and origin issues described previously an algorithm is developed to extract the Origin TAZ and Destination TAZ data from the ships tracks The algorithm is built on the assumption that every ship sailing in Tokyo Bay has a start position where the ship appears on data screen and an end position where the ship lays still in the
330. b 5 4 p YAN H bh TAN a r il A 1 S G 1 4 S 85 0 6 0 2 03 A 05 06 OF Tue Positive 06 09 1 4 True Positive False Positive n SVM 1 1 PURER SZ ay hve oO CHS 128x64 98 6 SVM 6 HOG SVM
331. cation in Wide Area Multilateration Using the Elevation Angle Proceedings of ESAVS 2007 2007 03 6 EUROCAE Technical Specification for Wide Area Multilateration WAM System Version 1 0 ED 142 2009 10 7 ICAO Aeronautical Telecommunications Annex10 Volume IV Fourth Edition 2007 07 8 RTCA Minimum Operational Performance Standards for 1090MHz Extended Squitter ADS B and TIS B RTCA DO 260B 2009 12 119
332. ei fi eld denpa04 html 2013 3 9 6 4 http www soumu go jp johotsusintokei fi eld denpa02 html 2013 3 9 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 A
333. erse relative Pos DSS a Longitudinal relative Pos STD Transverse relative Pos STD Distance in meters 75 Time in seconds From starting of the landing phase Figure 5 Longitudinal Relative Positions Figure 6 give information about the rudder orders from the start to the landing both for the DSS test and for the STD test The amount and the frequency of these orders can give an indication of the decision maker s control of the vessel In Figure 7 the different transverse speeds of the DSS test during landing can be seen The VLCC runs on autopilot and is affected by the interaction effect in the landing phase 0 1281 0 0 0O 0O 20130 50 301 310 0 0 HHHHHHHHHHH Ww 20130 4 27 Vessels Rudder order Rudder order DSS deg VLCC Rudder order DSS deg Rudder order STD deg Port deg 1 IL 1 hi Hil HHT ja 0 42 08 00 54 08 01106 08 ims i l St board deg Time hh mm ss Running from start to the landing Figure 6 Rudder order for both DSS and STD test Transverse relative and true speeds in the landing phase Transverse relative speed DSS kts Transverse true speed VLCC kts Transverse true speed DSS kts St board kts Port kts Time in secounds From starting of the landing phase Figure 7 Transverse speeds in the DSS test In Figure 8 the transverse distance and speed at bow are compared in the
334. fter several tests and iterations different screenshots of the GUI s were programed on the Tablet PC Figure 3 4 When the vessels are very close the longitudinal distance between the hose connection points are visualized with a square box containing a grey and a blue triangle 7 5m Figure 3 The GUI vessels getting close to landing The next step in the development of the DSS for STS operations is to validate the system To see if the performance and the safety is improved Tests are performed at in the simulator center at University of Troms The test group is divided in two and half of this group will use normal standard decision making artefacts as radar gyro and Doppler log together with visual observation called the STD test group The other part the DSS test group will use only the DSS observing the GUI on the Tablet PC and used this information in the decision making to adjust the propulsion and the course of the Service Ship The whole group will be screened so test subjects with the same skills and experience will be compared To clarify the appropriate setup for this test and to establish possible parameters to compare a pilot test wave been conducted In this pilot the test subjects were two officers with approximately the same skill level The test began with an introduction to the lightering operation Including a short film showing the preparation and execution of the operation guided by a skilled mooring
335. ig 1 Chart of mooring tether break SOODWT oQ os oO lt S D gt gt 0 20 40 60 80 10 0 12 0 Flow velocity m s Mooring tether break area Mooring tether danger area Mooring tether safety area Fig 2 Chart of mooring tether break 3 000DWT K bn oO K oO gt gt Ship type 10 000 DW Incident angle 90 de 0 20 40 6 0 8 0 10 0 Flow velocity m s Mooring tether break area Mooring tether danger area Mooring tether safety area Fig 3 Chart of mooring tether break 10 000DWT 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 MPS W H THK Ou A 36 A HA KER CILE FARC EAT O 2 MPS MPS 2 MPS
336. ith its 1320 km is selected as an analysis area There are eight port areas in Tokyo Bay namely Yokosuka Port Yokohama Port Kawasaki Port Tokyo Port Funabashi Port Chiba Port Anegasaki Port and Kisarazu Port as shown in Fig 1 a Based on the port limits introduced above nine TAZs are determined for this analysis as shown in Fig 1 b any w 1 Bee Edogawa tu Bunabashi Shiniy ka ku funabash Q a Funabashi TAZ oe Miage al Q vias Funabashi Sm Port pee Chiba Port Chiba TAZ Mars m Tokyo Bay Line TAZ a a Port Limits b TAZ Limits Fig 1 Illustration of Tokyo Bay Ports and Traffic Analysis Zones TAZ Limits The defined TAZs are as follows 1 Tokyo Bay Line TAZ Area between the Tokyo Bay Line and Line A 2 Yokosuka TAZ Northern area of Yokosuka Port The southern part is excluded from the analysis because of the ferry traffic and traffic around the Uraga Pilot Station which do not have any relevance to this analysis 3 Yokohama TAZ Area delimited by Yokohama TUMSAT Tokyo University of Marine Science and Technology 25 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 Port 4 Kawasaki TAZ Area delimited by Kawasaki Port 5 Tokyo TAZ Area delimited by Tokyo Port 6 Funabashi TAZ Area delimited by Funabashi Port 7 Chiba Port TAZ Area delimited by Chiba Port 8 Anegasaki TAZ Area delimited by Anegas
337. l Intelligent Marine Traffic Simulator for Congested Waterways Proceedings 7th IEEE International Conference on Methods and 28 Models in Automation and Robotics pp 632 636 2001 8 Hasegawa K Knowledge based automatic navigation system for harbour manoeuvring Proceedings of Tenth Ship Control Systems Symposium pp 67 90 1993 Hasegawa K An intelligent marine traffic evaluation system for harbour and waterway designs Proceedings of 4th International Symposium on Marine Engineering Kobe 90 ISME KOBE 90 pp G 1 7 14 1990 R Kar S K Mazumder Entropy and utility based trip distribution model African Journal of Mathematics and Computer Science Research Vol 4 12 pp 375 378 2011 11 S Christodoulou K Lukas Entropy Based Traffic A Borrmann Impact Analysis and Optimization of Roadway Maintenance Proceedings of the 14th International Conference on Computing in Civil and Building Engineering Moscow Russia 2012 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 DEVELOPMENT AND SIMULATOR TESTING OF A DECISION SUPPORT SYSTEM FOR STS OPERATIONS Dagfinn Husjord University of Troms Department of Engineering Science and Safety Norway Egil Pedersen University of Troms Department of Engineering Science and Safety Norway Abstract As part of the ongoing development of a navigation support and guidance system for ship to ship operations interviews and a q
338. last 30 seconds of the landing phase In the DSS test the bow is moving away from the VLCC before closing in again The DSS test had a lower transversal speed at bow in the landing than the STD test around cm s and 3 4 cm s respectively Transverse Distance and Speed at Bow in the Landing Phase Distance Bow VLCC DSS m Distance Bow VLCC STD m Transverse Speed Bow DSS cm s Transverse Speed Bow STD cm s 6 Time in secounds Figure 8 Test data during landing are compared 32 5 Conclusion The objective of the pilot test was to evaluate the performance in order to establish suitable methods and procedures for later larger evaluation of the DSS Analysis of time series plots can show the quality and the manoeuvring time of each STS approach manoeuvre The degree of control in the landing phase is of high importance In the STD test the service ship landed with a heading difference to the VLCC of 4 degrees resulted in a landing on the forward fender only It is apparently a problem to observe distances and angles between the vessels only by visual measurements A screening of the test subjects before commencing the test is therefore of significant importance to ensure that the performance are compared at the same level of skill and experience It is however a reason to expect a certain difference in the decision taker s human variation For instance just a little too late helm orders can result
339. llowable dimensions and allowable type of cargo Unfortunately such information is not available and so the uncertainty associated with the traffic movements is estimated based on the concept of Entropy The Entropy H is defined as the uncertainty associated with the traffic distribution with in a specific area and it is related to the probability distribution of generated trips between the origin and destination For the above mentioned trip distribution model the Entropy H is defined as H Xij Pij In Pij 6 where Pij 0 gt H 0 Pij 1 gt H 0 7 0 lt p lt 1 gt H gt 0 Entropy H is generally thought of as a metric of a system s state of disorder as the higher a system s entropy is the more disordered the system is And generally systems tend to move toward higher entropy values at which system stabilization is sought 7 Results Analysis results show that traffic originating from TAZ towards a destination TAZ where i j accounts for a trip probability p 0 34868 Fig 3 shows two similar cases for Yokohama TAZ and Tokyo TAZ The traffic between same TAZs is attributable to service boats leisure passenger ships and the like 27 a Yokohama TAZ b Tokyo TAZ Fig 3 Illustration of Same TAZ Trips Yokohama TAZ and Tokyo TAZ Traffic trip distribution with a constraint excluding trips within the TAZs shows the conservation of traffic for every Origin and Destination TAZ respectively In
340. lpha 7 4 8 Foxtrot 5 0 2 Golf 5 1 1 Uniform 5 2 4 Five 5 0 1 Fifteen 5 1 4 Fifty 5 1 5 flag 3 1 2 after 3 1 1 aft 6 2 4 9 z gt dg Zulu 5 3 3 zero 6 4 4 10 MADR REBA Of E s N Sierra 5 1 0 Six 5 2 0 Sixteen 5 1 0 sinking 3 1 0 11 0 gt s Three 10 4 0 Thirteen 8 2 0 Thirty 9 3 0 12 gt d this 3 3 0 the 30 6 0 3 3 2 e g Foxtrot gt Foxtlulrotlu X ray gt ekslul ray Mike gt Miklul eight gt eightlul aft gt aftlal eks u ray A Mik u 600 7 00 Jao A RED hy Foxtlulrotlu eightlu ed gt Foxtro_ Juliet gt Jule Quebec gt Quebe eight gt eight Titanic gt Titani
341. master A normal track to follow in the lightering scenario was then presented to the test subjects Figure 4 The subjects were then asked to follow this planned route within the framework which these figures provide The service ship started up seven cables astern of the STBL on her starboard side 3 cables off 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 Information regarding the interaction effects between the vessels during landing was given In particular the transversal forces on their own ship bow were pointed out The vessels specifications were reviewed The service ship was a shuttle tanker of 124 000 dwt in ballast This vessel had good manoeuvrability with two propellers and two high effect Schilling rudders Length of the ship is 265 meters The STBL was a super tanker VLCC of 386 000 dwt with a LOA of 353 meters The VLCC was equipped with Yokohama fenders The test subjects operated with manual steering control controlling both the rudder and the engine themself The test person who used radar inserted the parallel index and used this together with the VRM to control the voyage 1 Starting point 2 Parallel and same speed HDT 222 HDT 222 VLCC SS VLCC HDT 2229 SOG SOG SOG 5kn 0 1 nm 5kn 5kn 3 Heading 3 5 on the VLCC 0 7 nm HDT 222 HDT 217 219 lt 3 5 SOG7 kn p gt VLCC SS 0 3 nm a06 SOG 5kn 5kn 4 Landing phase Max trans
342. mber of 500 450 445 439 410 400 350 2 297 300 i 250 200 Year 2008 2009 2010 2011 2012 Number of attacks 1 2009 2011 3 400 2012 200 293 2011 150 2012 2 2 2009 2012 104 35 2 2008 2012 Straits of Malacca and Singapore O Malaysia E Indonesia O Philippines 90 80 70 60 50 40 30 20 10 0 Year 2008 2009 2010 2011 2012 Number of attacks
343. n m pre20t 0 0 aN NN 10 0 15 0 0 0 0 2 0 4 0 6 0 8 1 0 1 2 1 4 6 AB SIC L Sasa se Surge 16 100 Surge m Surge_max m Hx1 2 5 0 amp Surge_min m Hx1 2 0 0 DRS E Surge_max m Hx1 0 Surge_min m Hx1 0 5 0 10 0 15 0 20 0 0 5 10 15 20 25 ton 7 Surge 16 0 1281 0 0 8 20130 50 301 30 HHHHHHHHHHH 1010 20130 4 27 4 1 R AGH A AEE TP Ht eA REEF OAR VLCC 127 pp 57 68 2012 2 GE 2011 No 549 2011 5 14 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 FARRER BIT Oe BIAS S11 hA 2 Be PA
344. nsport iis u tokyo ac jp PDFs 2005 2005 007 pdf 2013 2 10 4 AIS http www kaiho mlit go jp syoukai soshiki toudai ais ais_index htm 2009 10 5 24 http wwwl kaiho mlit go jp GIJUTSUKOKUSAI KENKYU happyo 2012 h24o02 pdf 13 3 10 6 ICT 2012 3 7 21 ITS Vo1 145 pp 29 32 2000 9 8 24 http members j navigation org doc JIN127 1 pdf 2013 3 10 9 2 EY REE http www ymf or jp wp content uploads 60 8 pdf 2013 3 10 AIS
345. ollow Ahead vessel you overtake IE You follow A maru A SME TIL WILMA ORI CHO VIS SVO 1 You A maru follow IMO Standard Marine Communication Phrases SMCP a ahead vessel IE vessel ahead of you starboard abeam vessel JIE vessel on your starboard beam ers KI 300 oR Tie OCS bo ya On aS SIG MES RR a
346. proach Zone a Fig 1 Schematic diagram of Simulation Model TV 20 ship hrl W W 9 D 0 8 M 0 0 30 L 7 M L 0 4 M 15 20 L E MI Fig 2 Effect of the Route Distance in the Route Field Ep AI Ez A Ey PILZ Fig 30b Ey OF Ep Er 3 3 fe LHL
347. r 6 30 1D 0 8 M W W 9 L 7 M L 0 4 MI 0 0 20 40 60 80 10C DEFLECTION ANGLE deg a One way Route TV 20 ship hr 0 30 D 0 8 M W W 9 L 7 M L 0 4 M 100 8C DEFLECTION ANGLE deg b Two way Route Fig 4 Effect of the Route Deflection Angle 0 20 40 60 3 4 7Iship hr 4 M ship WANT Hig 5 Ed VL av 2 W 1 7 10 7 20 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 E M ship L D 0 8 M 0 30 0 L 7 M 1 0 4 M 25 20 TV ship hr Fig 5 Effect of the Number of Ways a One way Route b Two way Route Vessel on the Same Course
348. s a Pilot and advising the Captain and his crew on how to navigate and maneuver Experienced and trained officers are needed to minimize the risk of miscommunication between the ships 1 In a normal STS lightering operation at open sea one ship is required to maintain speed and course and is referred to as the Ship to be Lightered STBL The Service Ship SS will approach until it is parallel with the STBL before commencing the final approach phase which is to maneuver until the ships are moored and transfer of cargo can commence Figure 1 2 Navigation Instruments 29 STS Lightering Decision support Display Figure 1 The approach phase of a lightering operation A user survey among European and US mooring masters has revealed potential improvement to the overall safety in such operations Real time information about distances between the two vessels and their relative movement when presented graphically in an understandable way and relayed to the decision maker on the bridge could speed up the decision making process 3 2 DESIGN AND DEVELOPMENT OF THE DECISION SUPPORT SYSTEM DSS The mooring masters as end users have been involved in the design of the Decision Support System DSS and given feedback and comments especially on the user interface It has been a conscious choice to place 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 the user at the centre of the design in
349. stOSA deg 208 e m 5 20deg a e oO g pa aN 10 E 5 20deg y 0 5365x 18 524 0 8 6 4 2 0 2 4 6 8 deg 10 y 1 9403x 23 764 1stOSA 11 2ndOSA X 10 2ndOSA 2ndOSA 78 y 1 6349x 46 561 70 60 y 1 735x 45 769 5 o F Ss ip e p f 5 10deg 8 30 a e 6 10deg e e pen m 6 20de e 20 y 2 0083x 31 034 y 4 1707x 38 207 85 20deg 10 0 8 6 4 2 0 2 4 6 8 deg ASE 11 2ndOSA Za a e GPS
350. t O D x 10 ep 10 4 P 10 z 10 3 D pee Exp 10 New MPS z 10 gt Traditional MPS ri 1 1 1 ose ep r B 1 I 1 5 10 50 100 Angular frequency rad sec Fig 6 Comparison of spectra of mooring tether tension 20 4 1 MPS MPS MPS Cece lt a es MPS MPS Sas 020 oe 2 5 1 Seiichi KOSHIZUKA Atsushi NODA and Yoshiaki OKA Numerical Analysis of Breaking Waves Using the Moving Particle Semi implicit Method Int J Numer Mech Fluid 26 pp 751 769 1998 3
351. tion step3 2 2 B Binarized Image KE HE BR Binarized Rivese Image HFHig 3 BR Binarized Riverse Image a Sea surface segmentation based on probability of horizontal component Fig 3 BR Binarized Riverse Image step4 B amp BR 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 DML Draft Mark Lensth stepS Ey ZET DML step6 B amp BR C Combined Image L steps Fig 4 C Combined Image Fig 4 C Combined Image step7 DL LEER DML
352. uestionnaire survey among ship officers in charge of lightering operations with crude oil tankers has revealed what kind of information that is required to improve the decision making process during the approach between two vessels that aim to get alongside with forward speed in open waters Graphical user interfaces GUIs tailored for the typical approach phases in ship to ship operations have been proposed developed and tested on experienced ship officers in a full mission ship handling simulator to assess the potential for enhancing operational safety To evaluate the operational improvement of the decision support system DSS a deeper test in a realistic lightering operation in a simulator wave been carried out Keywords Information Support 1 INTRODUCTION A ship to ship STS lightering operation typically involves two tankers maneuvering in close proximity at a speed range of 4 6 knots in order to come alongside and commence cargo transfer This is a challenging task for the officer in charge of the operation the mooring master whose decision making process during the approach is commonly based on radar measurements until the vessels are approx 0 1 n mil apart The final approach phase is carried out using visual observations only In an STS lightering operation the Captains are as always In charge of their respective ships However it is industry standard to have a mooring master on board the maneuvering ship acting a
353. versal speed 0 2 kn Landing with manifolds at level gt On all four fenders at same time HDT 222 HDT 222 VLCC SS SOG SOG 5 kn 5 kn Figure 4 The optimum track to follow in the test scenario with the criteria presented in the sketches from Position to Position 4 as it was presented to the test subjects before the test 31 4 ANALYSIS 4 1 EXPECTATIONS The ideal outcome of the introduction of the DSS is that the real time information of the vessels relative movement can improve the decision making process The input from a dedicated DSS goes faster through the steps in the decision making process and does not need to be selected or filtered A good GUI will provide more exact information especially through situation awareness and less time will be spent on selecting and comparing information with the internal memorized experiences of the decision maker This will hopefully give a safer and more efficient performance 4 2 RESULTS OF THE TEST During each test run several parameters were logged from the Kongsberg Maritime KM simulator and from the decision support system DSS Based on the data logged from the DSS different graphical representations of the parameters are presented Figure 5 shows longitudinal relative positions differences between the DSS test and the STD test from Position 2 parallel to the landing Relative Position during the landing Longitudinal relative Pos Transv
354. w enecho meti go jp policy images 060518pamph pdt Imai A Nishimura E Current J A Lagrangian relaxation based heuristic for the vehicle routing with full container load European Journal of Operational Research Vol 176 1 87 105 2007 Sadiq M Sait Habib Youssef 46 48 2002 0 1281 0 0 0 0O 20130 50 301 310 0 0 HHHHHHHHHHH 1010 20130 4 27 BWO CO MO
355. water after 26 berthing or anchoring The algorithm tracks every ship sailing from one TAZ to another and excludes any other ship that is not provided with an Origin TAZ and or Destination TAZ Fig 2 shows the result of some trip analysis carried out for the AIS data on the 11 of November 2011 The red pushpins indicated the Origin TAZ while the green pushpins indicate the Destination TAZ b Fig 2 Illustration of the Origins and Destinations a Tracking Algorithm 6 Trip Distribution Model Assuming S is the number of ships calling the analyzed area and N is the number of traffic analysis zones ships departing from TAZ are indexed as A with a probability u and ships arriving at TAZ are indexed as B with a probability v Ships sailing from TAZ to TAZ are represented by with a trip probability pi dy fig Ai 1 dif Bj 2 j B i Aj S 3 As for the probability of happening it is defined as Pj g A u 4 S B J V 1 S where Diui ZiV Ay Py 1 5 0 lt Pij lt 1 0 1281 0 0 0 0O 20130 50 30 310 0 0 HHHHHHHHHHH Ww 20130 4 27 Table 2 Trip Distribution Model Table Destination TAZ bo ZVI usuQ N om evel emf om w Dew va ve ef wf ot The uncertainty on the destination and origin can be reduced provided that the constraints imposed on every TAZ are known beforehand such as the type of ships allowed the maximum a
356. x in in Is for each vertical position y in Js fv calculateFeature s x y w MW if determine fv gt th push Q s x y 1 2 1 ere 1 determine Haar like SIFT HOG SVM HOG SVM HOG SVM 2 2 idiot a Dike OW 3 4 Oo 83 0 1281 0 0 0 0O 20130 50 301 310 ODO 10 10 20130 4 27 TEETE

Download Pdf Manuals

Related Search

Related Contents

Manuel d`utilisation  Bomba OK_Bomba OK.qxd  Samsung PL42P3S User Manual  HP Smart Array 5300 Controller Benutzerhandbuch  Windows 2000 用プリンタドライバ取扱説明書  Porter-Cable PCFP12656 Installation Guide  Philips 80719600 energy-saving lamp  説明内容    

Copyright © All rights reserved. Failed to retrieve file