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On November 16, 1998, at 12: 00 p.m., the "Changsheng Wheel" carried a ship of coal cinders to Malaysia's port of birth. Sony took Jia Hongwei and others to the high seas in the rented boat. Weng Siliang was responsible for giving advice on the shore and did not go to sea. At this time, their ship happened to meet the "Changsheng Wheel". The "Changsheng Wheel" was inserted with the Panamanian flag and the water line was very deep. Sony knew at a glance that the ship was full of cargo, which was to his liking. So he drove the ship to track the "Changsheng" and soon caught up with the big cargo ship. They stepped onto the deck, disguised themselves as anti-smuggling personnel in uniforms, motioned the "Changsheng" to stop, fooled the captain of the "Changsheng", and boarded the ship. 　　虽然通篇马屁飞扬，虽然嘉靖愉悦，却还不至于被拍晕。杨寿全也咽了口吐沫，望向儿子，长帆，这风铃当真如此值钱？杨长帆点头道：借着县考正热乎，值几个钱，后面指定不成了，还是要种海。抗美援朝战争期间，志愿军某部侦察排长严伟才（宋玉庆 饰）和安平村的崔大娘（栗敏 饰）一家结下深厚友谊。但不久后，崔大娘和部分村民被抓去给美李匪帮修工事，敌人得知崔大娘的儿子参加了人民军，便将她惨忍杀害了。严伟才闻听，怒火中烧，发誓为大娘报仇。正在这时，严伟才接到任务，王团长（方荣翔 饰）要他率领一个尖刀班，在朝鲜联络员的协助下，化装成美李伪军，奇袭李伪首都师“白虎团”，严伟才向团首长表示：请祖国人民放心，请朝鲜人民放心，坚决取得胜利！深夜，严伟才带尖刀班向敌占区行进，他们穿越雷区密布的死亡之谷，拂晓时分，接近至敌阵地前沿......诡异之屋，怪事横生。怪事屋第二季依旧由6个故事组成，有奇怪的楼梯、过分热情的女友、诡异的雇主、高明的计划、智能的弊端，以及你自己创造出来的世界。但这些离奇的表象之下，是令人胆寒的真相......祁风（黄晓明 饰）经营着一家小型快递公司，和独身的母亲（顾纪筠 饰）勉强度日。这天，前女友Laura（邓肇欣 饰）电话约见，她想用祁风做挡箭牌摆脱富少郑富强（吴嘉龙 饰）的追求。郑少爷不尽相貌堂堂，还是香港的奥运选手，多少美女难入法眼，偏偏看上了Laura。旧情难忘的祁风也看不惯飞扬拨扈的郑少爷，决定为旧情人出头，不料遭曾是空手道冠军的郑富强痛殴，并利用父亲的权力及影响，很快使祁风的快递公司倒闭，他放出狠话，若祁风能打赢他，Laura和公司一并奉还。罗拔（洪天明 饰）是祁风的好友，他采用激将法鼓励惨败的祁风，祁风这时想起与母亲长久分居的父亲祁龙（洪金宝 饰），他乃是有名的武术家，正可谓打虎亲兄弟，上阵父子兵......This article is the fourth and last in a series on how to use artificial intelligence to build a robust anti-abuse protection system. The first article explains why AI is the key to building a robust protection system, which is used to meet user expectations and increasing complex attacks. After introducing the natural process of building and starting an AI-based defense system, the second blog post covers the challenges related to training classifiers. The third article discusses the main difficulties in using classifiers to prevent attacks in production.