The Interface Segmentation Principle (ISP) means that it is better to use multiple specialized interfaces than to use a single total interface. That is to say, don't let a single interface take on too many responsibilities, but should separate each responsibility into multiple specialized interfaces for interface separation. Too bloated an interface is a kind of pollution to the interface.
史诗大剧讲述了“ 两弹一星”及其信念 ﹐记录了贫困经济条件、薄弱的技术基础和艰苦的工作条件下﹐60年代的科学家们以惊人的智慧与毅力﹐创造出“两弹一星”的民族奇迹。
Public User (Mediator mediator) {
不过化很清楚，这可以说是越国的最高机密，既然越王尹旭不说出来，自然是时机未到。
Defense Methods: The most effective and reliable defense methods against consumptive Flood attacks, such as SYN Flood, ACK Flood and UDP Flood, are:
作为tvN5月期待作的《Abyss》确定了朴宝英、安孝燮、李成宰、李时言、韩素希、权秀贤的演员阵容。
你才无耻。
全台湾最大茶叶出口商的独生女薏心（连俞涵 饰），邂逅因美援任务重返台湾的失意战俘KK（温升豪 饰），她决定不顾父亲吉桑（郭子乾 饰）反对，介入债台高筑的家族事业，即使身份与使命相差甚远，背负忧伤过往的KK仍深深吸引著薏心，诡变的时代危机环伺，少女薏心如何在茶叶商战中，带领摇摇欲坠的日光茶公司走向世界？ 电视剧《茶金》由金钟导演林君阳执导，故事灵感源自真实人物与历史。
古装穿越电视剧《绾青丝》改编自波波创作的同名穿越小说，讲诉了叶海花，一个从二十一世纪穿越到不同的时间、空间的古代的人物，她希望找到一个可以为自己绾青丝的人。她的前世受了太多的伤害，可她始终未放弃寻找心中的挚爱，寻找心里的真正的归宿。在小冥王的帮助下，几近魂飞魄散的她通过借尸还魂的方法附着在古代大奸臣的女儿蔚蓝雪身体上。于是，一场腥风血雨在蔚府展开。究竟她能否逃离世俗的纷争，寻得可以为自己绾青丝的人，寻得心中的挚爱吗?
就在何萱与泽铭开始打造蓝屋顶的梦想时，泽铭却罹患了怪病，他渐渐无法控制自己的肢体，视线也变得模糊起来。泽铭的母亲黎凤莲（刘瑞琪饰），是一个个性坚韧、颇负盛名的教育专栏作家。过去， 她一直以为丈夫是意外身亡；但如今，大儿子的怪病让她明白：原来丈夫的家族藏有小脑萎缩症的基因，而长子泽铭居然中奖了
‘男女授受不亲乃礼之大防，然医者父母心，行的是治病救人的善事，自然另当别论。
最让人哭笑不得的死，杜殇本来就要得手时，被自己的人误会，乌龙的结果沉重的让人无法接受。
陈扬离开了姨妈的家徘徊在青岛街道,一辆飞驶而来的轿车,将陈扬撞出街道,而驾车人正是陈扬和绵绵所要寻找的绵绵的姐姐苏盈。当然,这一点,谁也不知道。
当日在尹旭营帐之中和龙且发生了那般冲突，当时只有楚越两国的人在。
怎么天下有如此倒霉的人。
Update 20171009
80后的婚姻为何不被看好，提起80后的婚姻，很多人的第一反应可能是恐婚、闪婚、离婚这些贬义词语，80后这一代的婚姻如此不被看好，可能更多的原因在于大部分80后都是独生子女，他们从小在众多人的宠爱下长大，很少经历挫折，他们可以说是“集万千宠爱于一身”的一代人。
Common protocols and their magnification:
Sorry to force a wave of chicken soup. Originally, I planned to write a machine learning series last year, but after writing three articles for work and physical reasons, there was no more. In the first half of this year, I was tired to death after doing a big project. In the second half of this year, I just took a breath of relief, so the follow-up that I owed before will definitely continue to be even more. In order not to let everyone worship blindly, I decided to write a series of in-depth study, one article per week, which will end in about three months. Teach Xiaobai how to get started. And finished! All! No! Fei! ! It is not simply to write demo and tuning parameters that are available on the Internet. Reject demo, start with me! If you don't understand, please leave a message under my article. I will try my best to reply when I see it. This series will mainly adopt the in-depth learning framework of PaddlaPaddle, and will compare the advantages and disadvantages of Keras, TensorFlow and MXNET (because I have only used these four frameworks, there are too many people writing TensorFlow, and I am using PaddlePaddle well at present, so I decided to start with this). All codes will be put on github (link: https://github.com/huxiaoman7/PaddlePaddle_code). Welcome to mention issue and star. At present, only the first article () has been written, and there will be more in-depth explanation and code later. At present, I have made a simple outline. If you are interested in the direction, you can leave me a message, and I will refer to the addition ~
