110.02.24
I1435 (義大利) 1/72 Harrier GR.1
I1447 (義大利) 1/72 Fiat BR.20 Cicogna
I2801 (義大利) 1/48 FIAT CR.42 Falco
I2808 (義大利) 1/48 Opel Blitz Tankwagen
I7077 (義大利) 1/72 Sd. Kfz. 251/8 Ambulance
I7082 (義大利) 1/72 15 cm Field Howitzer / 10,5 cm Field Gun
I2797 (義大利) 1/48 A-7E Corsair II
I2756 (義大利) 1/48 F7F-3 TIGERCAT
I1446 (義大利) 1/72 P-38J Lightning
I2774 (義大利) 1/48 H-21C "Flying Banana" Gunship
I2807 (義大利) 1/48 Junkers Ju87B Stuka
I6569 (義大利) 1/35 Semovente M42 da 75/18
I7080 (義大利) 1/72 Sd. Kfz. 251/1 Wurfrahmen 40 Stuka zu Fuss
I040 (義大利) 1/72 UH-1B HUEY
I2798 (義大利) 1/48 MiG-23 MF/BN Flogger
I850 (義大利) 1/48 F/A-22 RAPTOR
I2736 (義大利) 1/48 HARVARD MK.IIA
I833 (義大利) 1/48 AH-1W SUPER COBRA
I2765 (義大利) 1/48 MACCHI MC.205 VELTRO
I2786 (義大利) 1/48 F-16 A Fighting Falcon
I0080 (義大利) 1/72 AH-64D Apache Longbow
I1247 (義大利) 1/72 Bell UH-1D Iroquois
I1340 (義大利) 1/72 歐洲 EF2000"颱風“雙座型戰鬥機
I1411 (義大利) 1/72 A-7E CORSAIR II
I1427 (義大利) 1/72 MiG-21bis "Fishbed
I2744 (義大利) 1/48 Wessex HAS.1
I2766 (義大利) 1/48 TORNADA IDS
I0160 (義大利) 1/72 AH-1 W Super Cobra
I1306 (義大利) 1/72 JAS 39 GRIPEN
I1385 (義大利) 1/72 F/A-18 HORNET SWISS AIR FORCES
I1426 (義大利) 1/72 F-86F Sabre "MiG Killer"
I189 (義大利) 1/72 F-117 Nighthawk
I1065 (義大利) 1/72 MH-53E Sea Dragon
I1246 (義大利) 1/72 NATO Pilots and Ground Crew
I1260 (義大利) 1/72 CR.42 Falco
I1308 (義大利) 1/72 MB326高級教練機
I1317 (義大利) 1/72 MB 339 A P.A.N.
I188 (義大利) 1/72 F-16 C/D Night Falcon
I0197 (義大利) 1/72 Sukhoi SU-27 D "Sea Flanker"
I1156 (義大利) 1/72 F-14A Tomcat
I1258 (義大利) 1/72 英國 威塞克斯 HAS.3 直升機
I1263 (義大利) 1/72 二戰意大利 CR.42AS戰鬥機
I1307 (義大利) 1/72 SPITFIRE Mk.VI
I1330 (義大利) 1/72 英國皇家空軍 WESSEX HAS.3 直升機
I1374 (義大利) 1/72 S.E 5A ALBTROS D.III
I1388 (義大利) 1/72 Savoia-Marchetti SM.81 Pipistrello
I1390 (義大利) 1/72 CAPRONI CA.311/311M
I1397 (義大利) 1/72 F-21A Lion/Kfir C.1
I1404 (義大利) 1/72 德軍 FW 189 A-1/A2
I1420 (義大利) 1/72 F-5E Swiss Air Force
I314 (義大利) 1/35 美軍 威利吉普
I322 (義大利) 1/35 US.MOTORCYCLES
I1384 (義大利) 1/72 TORNADO GR.1
I1389 (義大利) 1/35 SM.82 MARSUPIALE
I1392 (義大利) 1/72 A-6E TRAM
I1401 (義大利) 1/72 HARRIER GR.3
I1406 (義大利) 1/72 EF-2000 100th Ann. "Gruppi Caccia"
I1418 (義大利) 1/72 MB-339A P.A.N. 2018 Livery
I1422 (義大利) 1/72 "Top Gun" F-14A vs. A-4F
I6447 (義大利) 1/35 M47 Patton
I6564 (義大利) 1/35 Sd.Kfz.173 Jagdpanther
I6575 (義大利) 1/35 Opel Blitz Radio Truck
I6034 (義大利) 1/72 二戰英國傘兵
I6078 (義大利) 1/72 越戰中的美國特種部隊
I6096 (義大利) 1/72 德國PAK 40反坦克炮及炮兵
I6120 (義大利) 1/72 WWII US Infantry
I6151 (義大利) 1/72 德國 二戰冬季作戰步兵
I6168 (義大利) 1/72 現代美國步兵
I6485 (義大利) 1/35 二戰美國 M10 坦克殲擊車
I6567 (義大利) 1/35 LEOPARD 2A6
I6121 (義大利) 1/72 德軍摩托車兵
I6076 (義大利) 1/72 二戰德國 北非軍團士兵
I6079 (義大利) 1/72 越南步兵
I6097 (義大利) 1/72 二戰蘇軍ZIS3反坦克炮連炮兵
I6099 (義大利) 1/72 DAK北非德軍
I6133 (義大利) 1/72 美國 二戰冬季作戰步兵
I6164 (義大利) 1/72 二戰日軍 M92榴彈炮及炮兵組
I6189 (義大利) 1/72 Free French Infantry
I6190 (義大利) 1/72 Warsaw Pact Troops
I7008 (義大利) 1/72 T-34/76 M1942
I7028 (義大利) 1/72 SJagdpanzer IV Ausf. F Sd.Kfz. 162
I1409 (義大利) 1/72 F-35 A LIGHTNING II CTOL version
I2666 (義大利) 1/48 MH-60K Blackhawk SOA
I2638 (義大利) 1/48 JAS 39 A Gripen
I6191 (義大利) 1/72 NATO troops
I7012 (義大利) 1/72 Sd. Kfz. 184 PanzerJg. Elefant
I7040 (義大利) 1/72 JS-2 Stalin
I2805 (義大利) 1/48 Bf 109 K-4
I1425 (義大利) 1/72 Lockheed Martin F-35B Lightning II
I2796 (義大利) 1/48 Dassault/Dornier Alpha Jet A/E
I2671 (義大利) 1/48 A-4 E/F/G SKYHAWK
I6195 (義大利) 1/72 Battle for the Reichstag
I6569 (義大利) 1/35 Semovente M42 da 75/18
I189 (義大利) 1/72 F-117 Nighthawk
I1156 (義大利) 1/72 F-14A Tomcat
I1390 (義大利) 1/72 CAPRONI CA.311/311M
I1397 (義大利) 1/72 F-21A Lion/Kfir C.1
I6196 (義大利) 1/72 Battle Set Gladiators Fight Ludus Gladiators
I1404 (義大利) 1/72 德軍 FW 189 A-1/A2
I7027 (義大利) 1/72 Morris Quad Tractor/25 PDR. Gun
I322 (義大利) 1/35 US.MOTORCYCLES
I6447 (義大利) 1/35 M47 Patton
I6068 (義大利) 1/72 German Elite Troops
I6170 (義大利) 1/72 日本陸軍 步兵組
I1422 (義大利) 1/72 "Top Gun" F-14A vs. A-4F
I314 (義大利) 1/35 美軍 威利吉普
I7022 (義大利) 1/72 美國 DUKW 兩棲運輸車
同時也有1部Youtube影片,追蹤數超過23萬的網紅Trevmonki,也在其Youtube影片中提到,Country Eraser? HopScotch? Power Rangers? I would say it's mostly based on my experience (my top 10), hope you guys can relate! More towards the 90's ...
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109.07.03 義大利到貨
I36515 (義大利) 1/35 Carro Armato P26/40
I36509 (義大利) 1/35 World of Tanks T34/85
I6574 (義大利) 1/35 M110 Self Propelled Howitzer
I1326 (義大利) 1/72 航母飛行甲板
I1425 (義大利) 1/72 Lockheed Martin F-35B Lightning II
I1427 (義大利) 1/72 MiG-21bis "Fishbed"
I1430 (義大利) 1/72 Fokker F27 Friendship
I1436 (義大利) 1/72 Heinkel He 111H
I2795 (義大利) 1/48 P-40 E/K Kittyhawk
I2797 (義大利) 1/48 A-7E Corsair II
I2799 (義大利) 1/48 F-86E Sabre
I6554 (義大利) 1/35 M978 FUEL SERVICING TRUCK
I1414 (義大利) 1/72 F-14A Tomcat
I1426 (義大利) 1/72 F-86F Sabre "MiG Killer"
I1429 (義大利) 1/72 F/A-18 Hornet
I1434 (義大利) 1/72 McDonnell Douglas FG.1 Phantom
I2791 (義大利) 1/48 Boeing F/A-18E Super Hornet
I2796 (義大利) 1/48 Dassault/Dornier Alpha Jet A/E
I2798 (義大利) 1/48 MiG-23 MF/BN Flogger
I2802 (義大利) 1/48 Hawker Hurricane Mk.I
I6190 (義大利) 1/72 Warsaw Pact Troops
I6564 (義大利) 1/35 Sd.Kfz.173 Jagdpanther
I6571 (義大利) 1/35 M1A2 Abrams
I6575 (義大利) 1/35 Opel Blitz Radio Truck
II083 (義大利) 1/72 F/A-18E
I1065 (義大利) 1/72 MH-53E Sea Dragon
I1374 (義大利) 1/72 S.E 5A ALBTROS D.III
I1376 (義大利) 1/72 A-10 A/C
I6191 (義大利) 1/72 NATO troops
I6568 (義大利) 1/35 M4A1 Sherman with US Infantry
I6573 (義大利) 1/35 38cm RW 61 auf Sturmmöser Tiger
I7078 (義大利) 1/72 T-34/76 Model 1943
I4633 (義大利) 1/9 Vespa 125 "Primavera"
I188 (義大利) 1/72 F-16 C/D Night Falcon
I1357 (義大利) 1/72 英"美洲虎"Gr.3攻擊機(特別塗裝)
I1375 (義大利) 1/72 RB-66B DESTROYER
I1377 (義大利) 1/72 MIG-29A FULCRUM
I1378 (義大利) 1/72 B-52G Stratofortress
I1392 (義大利) 1/72 A-6E TRAM
I014 (義大利) 1/72 MIL-24 "Hind" D/E
I1373 (義大利) 1/72 F-4 C/D/J
I1388 (義大利) 1/72 Savoia-Marchetti SM.81 Pipistrello
1408 (義大利) 1/72 IAI Kfir C.2
I833 (義大利) 1/48 AH-1W SUPER COBRA
I2622 (義大利) 1/48 V-22 Osprey
I2667 (義大利) 1/48 F-14A Tomcat
I1379 (義大利) 1/72 SU-34/SU-32
I1422 (義大利) 1/72 "Top Gun" F-14A vs. A-4F
I0080 (義大利) 1/72 AH-64D Apache Longbow
I1385 (義大利) 1/72 F/A-18 HORNET SWISS AIR FORCES
I1398 (義大利) 1/72 F-100F Super Sabre
I1415 (義大利) 1/72 F-15C EAGLE
I849 (義大利) 1/48 UH-1D IROQUOIS
I2638 (義大利) 1/48 JAS 39 A Gripen
I2692 (義大利) 1/48 NATO UH-1N
I2766 (義大利) 1/48 TORNADA IDS
I2769 (義大利) 1/48 JU 87 B-2/R-2 Stuka "Picchiatello"
I2784 (義大利) 1/48 Arado Ar 196 A-3
I2790 (義大利) 1/48 bye-bye Mirage F.1
I2673 (義大利) 1/48 美國 SBD-5"無畏"俯沖轟炸機
I2702 (義大利) 1/48 CR.42 FALCO ACES
I2721 (義大利) 1/48 NESHER/DAGGER
I2737 (義大利) 1/48 RF-4E PHANTOM II
I503 (義大利) 1/720 美國 Nimitz CV-68
I5522 (義大利) 1/720 U.S.S KITTY HAWK CV-63
I5533 (義大利) 1/720 美國 RONALD REAGAN CV-76
I2783 (義大利) 1/48 Tornado GR.1/IDS - Gulf War
I2786 (義大利) 1/48 F-16 A Fighting Falcon
I2794 (義大利) 1/72 Messerschmitt Bf 110C/D
I2688 (義大利) 1/48 Israeli IAI KFIR C1/C2
I2709 (義大利) 1/48 JU 87 D-5 STUKA
I2736 (義大利) 1/48 HARVARD MK.IIA
I2781 (義大利) 1/48 F-4J PHANTOM ll
I5521 (義大利) 1/720 美軍 CV-66“美國號" 航空母艦
I5531 (義大利) 1/720 美國航空母艦 USS CV-71 羅斯福號
I508 (義大利) 1/720 ADMIRAL SCHEER
I3640 (義大利) 1/24 Mercedes-Benz G230
I3645 (義大利) 1/24 Mercedes-Benz 300 SL "Gullwing"
I3647 (義大利) 1/24 Fiat 500 2007
I3701 (義大利) 1/24 Mercedes Benz 540K
I3708 (義大利) 1/24 VW Beetle Coupe
I322 (義大利) 1/35 US.MOTORCYCLES
I273 (義大利) 1/35 M998 Command Vehicle
I6551 (義大利) 1/35 Kangaroo
I6068 (義大利) 1/72 German Elite Troops
I6125 (義大利) 1/72 十字軍聖殿騎士
I3646 (義大利) 1/24 Porsche 944S Cabrio
I3648 (義大利) 1/24 PORSCHE 956
I3703 (義大利) 1/24 Rolls-Royce Phantom II
I317 (義大利) 1/35 KS750 WITH SIDECAR
I419 (義大利) 1/35 野戰車輛維修設備
I418 (義大利) 1/35 瞭望站
I6047 (義大利) 1/72 Roman Infantry
I6078 (義大利) 1/72 越戰中的美國特種部隊
I6151 (義大利) 1/72 德國 二戰冬季作戰步兵
I6168 (義大利) 1/72 現代美國步兵
us top 40 radio 在 國立陽明交通大學電子工程學系及電子研究所 Facebook 的最佳解答
【演講】2019/11/19 (二) @工四816 (智易空間),邀請到Prof. Geoffrey Li(Georgia Tech, USA)與Prof. Li-Chun Wang(NCTU, Taiwan) 演講「Deep Learning based Wireless Resource Allocation/Deep Learning in Physical Layer Communications/Machine Learning Interference Management」
IBM中心特別邀請到Prof. Geoffrey Li(Georgia Tech, USA)與Prof. Li-Chun Wang(NCTU, Taiwan)前來為我們演講,歡迎有興趣的老師與同學報名參加!
演講標題:Deep Learning based Wireless Resource Allocation/Deep Learning in Physical Layer Communications/Machine Learning Interference Management
演 講 者:Prof. Geoffrey Li與Prof. Li-Chun Wang
時 間:2019/11/19(二) 9:00 ~ 12:00
地 點:交大工程四館816 (智易空間)
活動報名網址:https://forms.gle/vUr3kYBDB2vvKtca6
報名方式:
費用:(費用含講義、午餐及茶水)
1.費用:(1) 校內學生免費,校外學生300元/人 (2) 業界人士與老師1500/人
2.人數:60人,依完成報名順序錄取(完成繳費者始完成報名程序)
※報名及繳費方式:
1.報名:請至報名網址填寫資料
2.繳費:
(1)親至交大工程四館813室完成繳費(前來繳費者請先致電)
(2)匯款資訊如下:
戶名: 曾紫玲(國泰世華銀行 竹科分行013)
帳號: 075506235774 (國泰世華銀行 竹科分行013)
匯款後請提供姓名、匯款時間以及匯款帳號後五碼以便對帳
※將於上課日發放課程繳費領據
聯絡方式:曾紫玲 Tel:03-5712121分機54599 Email:tzuling@nctu.edu.tw
Abstract:
1.Deep Learning based Wireless Resource Allocation
【Abstract】
Judicious resource allocation is critical to mitigating interference, improving network efficiency, and ultimately optimizing wireless network performance. The traditional wisdom is to explicitly formulate resource allocation as an optimization problem and then exploit mathematical programming to solve it to a certain level of optimality. However, as wireless networks become increasingly diverse and complex, such as high-mobility vehicular networks, the current design methodologies face significant challenges and thus call for rethinking of the traditional design philosophy. Meanwhile, deep learning represents a promising alternative due to its remarkable power to leverage data for problem solving. In this talk, I will present our research progress in deep learning based wireless resource allocation. Deep learning can help solve optimization problems for resource allocation or can be directly used for resource allocation. We will first present our research results in using deep learning to solve linear sum assignment problems (LSAP) and reduce the complexity of mixed integer non-linear programming (MINLP), and introduce graph embedding for wireless link scheduling. We will then discuss how to use deep reinforcement learning directly for wireless resource allocation with application in vehicular networks.
2.Deep Learning in Physical Layer Communications
【Abstract】
It has been demonstrated recently that deep learning (DL) has great potentials to break the bottleneck of the conventional communication systems. In this talk, we present our recent work in DL in physical layer communications. DL can improve the performance of each individual (traditional) block in the conventional communication systems or jointly optimize the whole transmitter or receiver. Therefore, we can categorize the applications of DL in physical layer communications into with and without block processing structures. For DL based communication systems with block structures, we present joint channel estimation and signal detection based on a fully connected deep neural network, model-drive DL for signal detection, and some experimental results. For those without block structures, we provide our recent endeavors in developing end-to-end learning communication systems with the help of deep reinforcement learning (DRL) and generative adversarial net (GAN). At the end of the talk, we provide some potential research topics in the area.
3.Machine Learning Interference Management
【Abstract】
In this talk, we discuss how machine learning algorithms can address the performance issues of high-capacity ultra-dense small cells in an environment with dynamical traffic patterns and time-varying channel conditions. We introduce a bi adaptive self-organizing network (Bi-SON) to exploit the power of data-driven resource management in ultra-dense small cells (UDSC). On top of the Bi-SON framework, we further develop an affinity propagation unsupervised learning algorithm to improve energy efficiency and reduce interference of the operator deployed and the plug-and-play small cells, respectively. Finally, we discuss the opportunities and challenges of reinforcement learning and deep reinforcement learning (DRL) in more decentralized, ad-hoc, and autonomous modern networks, such as Internet of things (IoT), vehicle -to-vehicle networks, and unmanned aerial vehicle (UAV) networks.
Bio:
Dr. Geoffrey Li is a Professor with the School of Electrical and Computer Engineering at Georgia Institute of Technology. He was with AT&T Labs – Research for five years before joining Georgia Tech in 2000. His general research interests include statistical signal processing and machine learning for wireless communications. In these areas, he has published around 500 referred journal and conference papers in addition to over 40 granted patents. His publications have cited by 37,000 times and he has been listed as the World’s Most Influential Scientific Mind, also known as a Highly-Cited Researcher, by Thomson Reuters almost every year since 2001. He has been an IEEE Fellow since 2006. He received 2010 IEEE ComSoc Stephen O. Rice Prize Paper Award, 2013 IEEE VTS James Evans Avant Garde Award, 2014 IEEE VTS Jack Neubauer Memorial Award, 2017 IEEE ComSoc Award for Advances in Communication, and 2017 IEEE SPS Donald G. Fink Overview Paper Award. He also won the 2015 Distinguished Faculty Achievement Award from the School of Electrical and Computer Engineering, Georgia Tech.
Li-Chun Wang (M'96 -- SM'06 -- F'11) received Ph. D. degree from the Georgia Institute of Technology, Atlanta, in 1996. From 1996 to 2000, he was with AT&T Laboratories, where he was a Senior Technical Staff Member in the Wireless Communications Research Department. Currently, he is the Chair Professor of the Department of Electrical and Computer Engineering and the Director of Big Data Research Center of of National Chiao Tung University in Taiwan. Dr. Wang was elected to the IEEE Fellow in 2011 for his contributions to cellular architectures and radio resource management in wireless networks. He was the co-recipients of IEEE Communications Society Asia-Pacific Board Best Award (2015), Y. Z. Hsu Scientific Paper Award (2013), and IEEE Jack Neubauer Best Paper Award (1997). He won the Distinguished Research Award of Ministry of Science and Technology in Taiwan twice (2012 and 2016). He is currently the associate editor of IEEE Transaction on Cognitive Communications and Networks. His current research interests are in the areas of software-defined mobile networks, heterogeneous networks, and data-driven intelligent wireless communications. He holds 23 US patents, and have published over 300 journal and conference papers, and co-edited a book, “Key Technologies for 5G Wireless Systems,” (Cambridge University Press 2017).
us top 40 radio 在 Trevmonki Youtube 的最佳解答
Country Eraser? HopScotch? Power Rangers? I would say it's mostly based on my experience (my top 10), hope you guys can relate! More towards the 90's kids side but generally I think anyone can relate to this :) I know I missed out some points here and there but if you guys want me to do a part 2, do let me know by commenting on this video! Do let me know what's your favourite childhood memories by commenting on this video too! :)
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