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LMV, MCWG TRANS, LMV, MCWG CMVNT. MCYL CMVNT TRANS, LMV, MCWG LMVTR. LMV, MCWG LMV NAGAR, DIBRUGARH JORHAT . st. No 17 18 24 Name of the applicant BISWAJIT SRI DAS GOGOI Father''s Name KANAK HAZARIKA THAKESWAR SIDDHA LATE Present Address NIMATI ROAD. RONGDOI P.o.
Annexure ‐A
Beldar 05.08.1976 01.01.2003 10th 01.04.2014 Bolero Camper No HP 51 1293LMV Trans MCWG PSVBus HP 51 dated 05.11.2009 valid 04.08.2026 SRD Dhami 28 Sh. Dev Raj S/o Sh. Nand Ram Beldar 20.04.1978 01.01.2003 10th 01.10.2017 HP 66 3427 LMV MCWG TRANS HP 49 valid 22.12.2025 Banjar Division
Licence No Name of the Driver NT Val From To SIGN OF
LMV MCWG SOITENG LASJAN SRINAGAR KASHMIR 0 32 18/01/2014 17/01/2034 B+ 18/01/2014 Below 10th Rs.250 /AA/ M S/W BY NATIONAL INFORMATICS CENTRE. Licence No Name of the Driver Receipt Details Vehicle Class 9 NT Val From To SIGN OF AUTHORITY TR Val From To Temporary Address.
ANNEXURE A JKSSB
MCWG(NT), LMV(NT), TRANS(TR), PSVBUS(TR) 23.02.2012 29.11.2013 3 6 86.8438 JKBoSE 2006/ 2009 Recommendation withheld and is subject to clarification with regard to date of endorsement 1 151 REASI 621 TANVEER HUSSAIN FAZAL HUSSAIN VILLAGE KUNDRA TEHSIL REASI DISTICT REASI 8/10/1985 OM 194 500 227 600 MCWG(NT), LMV(NT), TRANS
Driving License – Indian News
MCWG – Motor Cycle with Gear Driving License: This License category enables you to drive both motorcycles with gear and without gear. LMV Driving License: The full form of LMV is Light Motor Vehicle driving License, LMV driving license authorizes to operate cars, vans, delivery vans, jeeps, Taxi. LMV
Types of Driving Licence in India: Validity Period
MC Without Gear or M/CYCL.WOG (Motorcycle Without Gear) — Motorcycles and Scooters without gears. Motorcycles or Scooters of any engine capacity, with or without gears with an engine capacity of 50cc or more. MC With Gear or M/CYCL.WG (Motorcycle with Gear) — Motorcycles. LMVNT (Light Motor Vehicle—NonTransport) — Used for only personal
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【知识图谱】——8种Trans模型 汤庆CSDN博客 trans模型
知识图谱对实体和它们丰富的关系的结构化信息编码。虽然一个典型的知识图谱可能得到数百万的实体和数以亿计的关系事实，但离补全还很远。知识图谱补全旨在通过现有知识图谱来预测实体之间的关系。知识图谱补全能够找到新的关系事实，这是对从纯文本进关系抽取的重要补充。