内战科技

　　2015复习正是强化复习阶段，在考研英语中占了40分，所以考研英语阅读是英语科目中重要的一项。名师老师曾建议过考研生需要坚持每天泛读10-15分钟的英文原刊。强烈推荐了杂志《经济学人》.杂志中的文章也是考研英语的主要材料来源.希望考研考生认真阅读，快速提高考研英语阅读水平。 　　The science of civil war 　　内战科技 　　What makes heroic strife 　　英勇斗争缘何而致 　　Computer models that can predict the outbreakand spread of civil conflict are being developed 　　可以预测内战的爆发和蔓延的计算机模型正在被开发出来。 　　FOR the past decade or so, generals commanding the world s most advanced armies havebeen able to rely on accurate forecasts of the outcomes of conventional battles. 　　在过去的十年中，对世界上最先进的军队的指挥依赖于对传统战争爆发的精确预测。 　　Given data on weather and terrain, and the combatants numbers, weaponry, positions,training and level of morale, computer programs such as the Tactical Numerical DeterministicModel, designed by the Dupuy Institute in Washington, DC, can predict who will win, howquickly and with how many casualties. 　　只要有关于气候和土地的数据信息，敌人的数目，武器，位置，训练以及道德水平，计算机程序，比如华盛顿Dupuy研究所设计的战术数值确定模型，可以预测哪一方会赢得战争，需要多少时间，以及会有多少人员伤亡。 　　Guerrilla warfare, however, is harder to model than open battle of this sort, and the civilinsurrection that often precedes it is harder still. 　　然而，游击战争是很难模拟的，在此之前的暴动也同样难模拟， 　　Which, from the generals point of view, is a pity, because such conflict is the dominantform of strife these days. 　　很不幸，从普遍观点看来，最近一段时候这类战争冲突占了大部分。 　　The reason for the difficulty is that the fuel of popular uprisings is not hardware, but socialfactors of a type that computer programmers find it difficult to capture in their algorithms. 　　预测困难的原因是激起暴动的因素并非硬性条件，而是一种社会因素，而这种社会因素是计算机程序很难计算的。 　　Analysing the emotional temperature of postings on Facebook and Twitter, or thetelephone traffic between groups of villages, is always going to be a harder task thananalysing physics-based data like a tank s firing range or an army s stocks of ammunitionand fuel. 　　分析facebook和微博上更新的情绪，或是分析村落之间的电话往来，总是一项比分析实实在在的数据，比如说一台坦克的射程或者一支军队的军火和燃料储备，要难得多的任务。 　　Harder, but not impossible. 　　很难，并不表示不可能。 　　For in the war-games rooms and think-tanks of the rich world s military powers, brightminds are working on the problem of how to model insurrection and irregular warfare. 　　对于富人世界的军事力量的战争模拟室和智囊团而言，正有智慧的大脑在解决这些问题，如何模拟暴动和非常规战争。 　　Slowly but surely they are succeeding, and in the process they are helping politicians andarmies to a better understanding of the nature of rebellion. 　　虽然很缓慢，但是可以确认他们正走向成功。在此过程中，他们帮助政治家们和军队更好地理解叛乱的本质。 　　SCARE tactics 　　SCARE战术 　　One of the best-known projects in this field is SCARE, the Spatio-Cultural Abductive ReasoningEngine, developed at the United States Military Academy at West Point by a team led byMajor Paulo Shakarian, a computer-scientist-turned-soldier. 　　本领域中最有名的项目之一是SCARE，全称为空间文化推导仪，是由设立在西点军校的美国军事科学院的Paulo Shakarian少校所领导的团队开发的。 　　SCARE operates at the most militarily conventional end of the irregular-conflictspectrum: the point where an army of guerrillas is already in being and is making life hardfor a notionally better-armed army of regular troops. 　　Paulo Shakarian少校是一名军事计算机科学家。SCARE在非常规的战争冲突中军事图谱上看来传统的结束时分运作，即游击队已经到来，让我们观念中装备精良的正规军陷入困境之时运作。 　　That, of course, has been the experience of American forces in Vietnam, Iraq andAfghanistan. 　　显然，那就是美军在越南，伊拉克和阿富汗的经历。 　　Major Shakarian and his team have analysed the behaviour of guerrillas in both Iraq andAfghanistan, and think they understand it well enough to build reliable models. 　　Shakarian少校和他的团队分析了伊拉克和阿富汗游击队的行为方式，并且认为他们已经足够了解他们的行为方式，可以建立可靠的模型。 　　Their crucial insight is the local nature of conflict in these countries. 　　至关重要的是，他们深刻洞察了这些国家冲突的地区本质特性。 　　In particular, bombs directed at occupying forces are generally planted close to the placewhere they were made, and on the territory of the bombmaker s tribal kin or co-religionists. 　　特别地来说，占领军的炸弹通常安装在离制造地很近的地方，就在炸弹制造者族亲或同教派人员的地盘上。 　　That is not a surprise, of course. Kin and co-religionists are the most reliable allies in warswhere different guerrilla groups may not always see eye to eye about objectives, beyond theimmediate one of driving out foreign troops. 　　这当然不足为奇。亲属和同教派是不同游击队出没的战争中最为可靠的同盟。这些游击队除了立刻赶走外国军队以外，可能无法总是有统一的目标。 　　But it does give Major Shakarian and his team a convenient way in. 　　这给了Shakarian少校和他的团队一个方便的切入口。 　　Using the co-ordinates of previously bombed sites, data from topographical and streetmaps, and information on an area s ethnic, linguistic and confessional human terrain,SCARE is able to predict where guerrillas munition dumps will be to within about 700metres. 　　利用以前的炸弹安装地的坐标，来自地理和街道地图的信息数据，以及当地民族的信息，语言，和人类地域的自白，SCARE能够在大约700米内预测出游击队的军需存放处。 　　That is not perfect, but it is close enough to be able to focus a search in a useful way. 　　那并非完美，但是已经足够接近有效地集中搜索了。 　　Moreover, SCARE s focus should soon become more precise. 　　此外， SCARE的焦点很快会更加精准。 　　Major Shakarian s latest trick is to include data on phone-traffic patterns in the calculations. 　　Shakarian少校最新的计划将包括计算电话通路的模式。 　　An upgraded version of the program, employing this trick, will be created next month. 　　本计划的升级版将会使用这项策略，未来的几个月就将实现。 　　All of which is useful for dealing with a conflict once it has started. 　　一旦开始，所有的这一切都有利于处理冲突。 　　But it is better, if possible, to see what may happen before things get going. 　　然而，如果可能的话，最好看到在事情继续以前，有什么可能会发生。 　　And for that, America s navy has a project called RiftLand. 　　为此，美国海军，有一个项目名为分裂的土地。 　　RiftLand is being developed on the navy s behalf by Claudio Cioffi-Revilla, a professor ofcomputational social science at George Mason University in Virginia. 　　分裂的土地是由维吉尼亚的乔治梅森大学的计算社会科学教授Claudio Cioffi-Revilla为代表开发的。 　　It is specific to the part of East Africa around the Great Rift Valley. 　　它尤其针对东非地区大裂谷一带。这也是它名称的由来。 　　That this area includes Congo, Ethiopia, Rwanda, Somalia and Uganda, each of which hasbeen the scene of present or recent civil strife, is no coincidence. 　　这一地区包括刚果，埃塞俄比亚，路万达，索马里，和乌干达，每一个国家目前或者最近都经历了内战，这并非偶然。 　　But the ideas involved could be generalised to other parts of the world, with due alteration forlocal conditions. 　　然而，这个说法经过根据当地条件的少许变动，也可以推及世界其他地区， 　　Broadly, RiftLand works by chewing its way through a range of data collected by charities,academics and government agencies, and uses these to predict where groups of people willgo and with whom they may clash in times of drought or armed conflict. 　　广义上来说，分裂的土地通过精细分析由慈善组织，学术机构和政府收集来的数据，由此来预测哪一伙人会行动，又会跟谁发生武装冲突。 　　Dr Cioffi-Revilla gives the example of a tribe of nomadic herders known for sharing itsnotions of veterinary medicine with others. 　　Cioffi-Revilla博士以一个对外出口兽医药品的游牧部落举了一个例子。 　　This tribe, the model predicts, will reckon it safer to cross the lands of groups who also relyon keeping their animals healthy. 　　模型预测，这个部落将会估计它将安全地穿过那些依赖于动物健康的群落的土地， 　　Another point is that tribes who own a radio or mobile phone will steer clear of roads afternews reports of government atrocities against their kin. 　　另外一个观点是那些拥有收音机或者手机的群落在资讯中说政府对他们的亲属施暴以后会避开大路。 　　A third is that much of the movement of herdsmen can be predicted from satellite data onthe condition of pasture lands, modified by knowledge of what Dr Cioffi-Revilla calls thecomplex network of IOUs between tribes: which are currently hostile to one another, andwho owes whom favours. 　　还有一个是牧者们的行动可以由卫星根据草原的状况预测出来，再加上这些部落之间Cioffi-Revilla博士称之为复杂的借贷关系网的观点。他们，目前彼此敌对，也彼此相欠。 　　Hostile sentiments 　　敌对情绪 　　The sort of conflict dealt with by RiftLanda war of all against all in countries where centralgovernment is light or non-existenthas been particularly characteristic of this part ofAfrica in recent years. 　　这类由分裂的土地处理的战争冲突，也是在那些中央政府弱势或者无政府的国家出现的一种混战，已经成为非洲这一局部地区近年来战争的特点。 　　Further north, where states are stronger, urban insurrection of the sort seen at the beginningof the Arab spring is a more common threat. 　　再往北，那些国家政府相对强势，这种城镇叛乱在阿拉伯的春天之初是比较常见的威胁。 　　Politicians faced with such uprisings may thus be interested in yet another piece of software,known as Condor, which has been developed by Peter Gloor of the Massachusetts Institute ofTechnology. 　　政治家们面临着，这些暴乱势力可能对另一个软件叫做秃鹰感兴趣。它是由麻省理工的Peter Gloor开发的。 　　Dr Gloor is certainly not in the business of saving the jobs of Middle-Eastern dictators. He isactually a consultant to the Christian Democratic Union, Germany s largest political party. 　　Gloor博士绝不是要为中东的独裁者们保住工作。事实上他是德国最大政党基督教民主联盟的顾问。 　　But all politicians in power, whether democrats or dictators, share a distaste fordemonstrations and protests on the streets. 　　不过所有当权的政治家们，无论是民主主义者还是独裁者，都不会喜欢大街上的示威抗议活动。 　　Condor works by sifting through data from Twitter, Facebook and other social media, andusing them to predict how a public protest will evolve. 　　秃鹰筛选来自微博，facebook和其他社会媒体的数据信息，利用他们预测公众抗议将如何发展。 　　It does so by performing what Dr Gloor calls sentiment analysis on the data. 　　秃鹰是通过对信息进行Gloor博士所说的情绪分析做到这一点的。 　　Sentiment analysis first classifies protesters by their clout. 　　情绪分析首先将抗议者们根据他们的影响力分类， 　　An influential Twitter user, for instance, is one who has many followers but follows fewpeople himself. 　　比如说，一位具有影响力的微博用户拥有很多粉丝，但是他自己却只关注极少数人。他的发言往往是欢快的，包含着太好了，真有趣，太有趣了，真开心，有趣的电影，你会喜欢的等等诸如此类的词语或短语。 　　His tweets are typically upbeat, are rapidly retweeted, and appear to sway others. 　　这些微博很快会赢得回复，明显影响其他人。 　　In a nod to the methods developed by Google, Dr Gloor refers to this process as PageRankingfor people. 　　为了和谷歌开发的技术相匹配，Gloor博士将这一过程称为人物网页等级搜索。 　　Having thus ranked protesters, Condor then follows those at the top of the list to see howtheir output changes. 　　有了这些分级的抗议者，秃鹰接下来会关注表单上排位最高的几位，看他们的发言如何变化。 　　Dr Gloor has found that, in Western countries at least, non-violent protest movementsbegin to burn out when the upbeat tweets turn negative, with not, never, lame, I hate, idiotand so on becoming more frequent. 　　Gloor博士发现，至少在西方国家，当欢快的发言变得消极， 不，从不，蹩脚的，我讨厌，傻瓜等频繁出现的时候，非暴力的抗议行动就开始爆发了。 　　Abundant complaints about idiots in the government or in an ideologically opposed group area good signal of a movement s decline. 　　大量对政府的傻瓜们或者假想敌团体的抱怨的出现都是行动落幕的标志。 　　Complaints about idiots in one s own movement or such infelicities as the theft of beer by afellow demonstrator suggest the whole thing is almost over. 　　对自身行动中傻瓜们的抱怨或者其他示威者遭遇的偷窃啤酒的不幸标志着整个事情几乎快结束了。 　　Condor, then, is good at forecasting the course of existing protests. 　　然后秃鹰擅长预测剩下的抗议者的行动。 　　Even better, from the politicians point of view, would be to predict such protests before theyoccur. Not surprisingly, several groups of researchers are trying to do this too. 　　从政治家的观点看来，最好能在抗议活动爆发之前就能做出预测。不足为奇，有很多研究小组也在尝试这么做。 　　Aptima, a firm based in Woburn, Massachusetts, is one. 　　Aptima，在马萨诸塞州沃本市的一家公司就是其中之一。 　　Its program, called E-MEME uses sentiment analysis to see how opinions and states of mindflow across entire populations, not just activists. 　　它的项目叫做E-MEME利用情绪分析法来看观点和说明是如何再人群中蔓延的，而不仅仅是在活跃分子中。 　　It employs data from online news sources, blogs and Twitter, and attempts to rank thesusceptibility of certain parts of the populace to specific ideas. 　　它利用来自在线资讯，博客，微博的信息数据，尝试将这一部分民众对特殊观点的敏感度进行排位。 　　According to Robert McCormack, the project s chief technologist, E-MEME can determinethings as different as which places in Egypt contain people who will care a lot about a borderincident with Israel, and which parts of a country most need water in times of drought. 　　据本项目的主要技术负责人Robert McCormack所说，E-MEME能够判定埃及哪些地方的某一群人对和以色列边境冲突比较关心，哪些地方在干旱时特别需要水，这些不同之处。