Lecture2
Lecture 2 全面质量管理
质量检验、 质量检验、统计质量控制与全面质量管理的特点对比
全面质量管理的工作程序
全面质量管理采用一套科学的、合乎认识论的办事程序, 也即是P、D、C、A循环法。PDCA由英文的计划(P1an)、 执行(Do)、检查(Check)、处理(Action)几个词的第一个 字母组成,它反映了质量管理必须遵循的4个阶段。
质量螺旋quality 质量螺旋quality
13个环节（质量职能） 13个环节（质量职能） 个环节
朱兰质量螺旋曲线
1.质量形成过程 1.质量形成过程 :
质量环
质量形成过程的另一种表达方式是“质量环”。这种质量 循环 不是简单的重复循环,它与质量螺旋有相同意义。
对质量有影响的主要活动
朱兰质量螺旋的内涵相当丰富，就其实质而言，产品质量的 全过程管理可以概括为三个管理环节，即： 质量计划； 质量控制； 质量改进； 这三个环节用来反映产品质量形成的客观规律和指导质 量管理全过程的实施，简洁明白，且重点突出。通常称 之为“朱兰三部曲”。
戴明14条 戴明14条（1） 14
戴明14 戴明14条：2 14条
2、采用新观念； Learn the new philosophy 采用新观念并采纳适于持续改进的计划。充分认识我们处在 一个全球竞争的新时代,顾客不再容忍不良质量。企业业主必 须认识到他们不能回避质量运动。他们应当树立管理新观念, 引导员工加入到持续改进产品和服务的无限循环中来,同时,员 工以其工作质量为骄傲。忽视质量企业将面临极大的风险。
全面质量管理
全面质量管理的特点 ：三全一多样
①全面的质量管理。 ②全过程的质量管理。 ③全员参加的质量管理。 ④全面质量管理采用的方法是科学的、多种多样的。
全面质量管理
lecture 2--听辨
听力训练 VS 听辨过程 1
英语听力训练中比 较注重语言层面， 即十分注意语音、 语调和语言的表达 及用法。
译员在听辨过程中 所注重的是意思， 或是讲话者的意图 而不是具体的词句 表达。所以译员在 听到一段话之后在 头脑中形成的是一 个有逻辑关系的语 意整体，而不仅仅 是词句的简单集合。
听力训练 VS 听辨过程 2
• 对照关系：like, similarly, in a similar manner, likewise • 对比关系：different from, unlike, by contrast, on the other hand, on the contrary, • conversely
• 解释关系： that is to say, in other words, this means
先后次序：first of all, next, before, after, previously, simultaneously, eventually, finally
Bugs in LCII 恼人的听辨“虫”
1. unknown words 生词 2. culturally-burdened phrases or idioms 英语中 的文化陷阱（容易望文生义） 3. illogical flow of thought逻辑混乱 4. heavy accent 口音浓重 5. unfamiliar topic 不了解主题知识 6. too quick a delivery speed 语速过快 7. blurred point of view 意思不明确 8.数字
逻辑关系和对应的标示词
并列关系：and, too, at the same time, meanwhile, in the meantime, as well • • • • • 递进关系：also, moreover, in addition, furthermore, besides, not only, on top of that, apart from 转折关系：but, however, though, whereas, nevertheless, in fact, instead 让步关系：in spite of, despite， although, even though 因果关系：so, thus, hence, as a result, consequently, reason, because, for, due to, accordingly
lecture_2（博弈论讲义GameTheory（MIT））
Last Time:Defined knowledge, common knowledge, meet (of partitions), and reachability.Reminders:• E is common knowledge at ω if ()I K E ω∞∈.• “Reachability Lemma” :'()M ωω∈ if there is a chain of states 01,,...m 'ωωωωω== such that for each k ω there is a player i(k) s.t. ()()1()(i k k i k k h h )ωω+=:• Theorem: Event E is common knowledge at ωiff ()M E ω⊆.How does set of NE change with information structure?Suppose there is a finite number of payoff matrices 1,...,L u u for finite strategy sets 1,...,I S SState space Ω, common prior p, partitions , and a map i H λso that payoff functions in state ω are ()(.)u λω; the strategy spaces are maps from into . i H i SWhen the state space is finite, this is a finite game, and we know that NE is u.h.c. and generically l.h.c. in p. In particular, it will be l.h.c. at strict NE.The “coordinated attack” game8,810,11,100,0A B A B-- 0,010,11,108,8A B A B--a ub uΩ= 0,1,2,….In state 0: payoff functions are given by matrix ; bu In all other states payoff functions are given by . a upartitions of Ω1H : (0), (1,2), (3,4),… (2n-1,2n)... 2H (0,1),(2,3). ..(2n,2n+1)…Prior p : p(0)=2/3, p(k)= for k>0 and 1(1)/3k e e --(0,1)ε∈.Interpretation: coordinated attack/email:Player 1 observes Nature’s choice of payoff matrix, sends a message to player 2.Sending messages isn’t a strategic decision, it’s hard-coded.Suppose state is n=2k >0. Then 1 knows the payoffs, knows 2 knows them. Moreover 2 knows that 1knows that 2 knows, and so on up to strings of length k: . 1(0n I n K n -Î>)But there is no state at which n>0 is c.k. (to see this, use reachability…).When it is c.k. that payoff are given by , (A,A) is a NE. But.. auClaim: the only NE is “play B at every information set.”.Proof: player 1 plays B in state 0 (payoff matrix ) since it strictly dominates A. b uLet , and note that .(0|(0,1))q p =1/2q >Now consider player 2 at information set (0,1).Since player 1 plays B in state 0, and the lowest payoff 2 can get to B in state 1 is 0, player 2’s expected payoff to B at (0,1) is at least 8. qPlaying A gives at most 108(1)q q −+−, and since , playing B is better. 1/2q >Now look at player 1 at 1(1,2)h =. Let q'=p(1|1,2), and note that '1(1)q /2εεεε=>+−.Since 2 plays B in state 1, player 1's payoff to B is at least 8q';1’s payoff to A is at most -10q'+8(1-q) so 1 plays B Now iterate..Conclude that the unique NE is always B- there is no NE in which at some state the outcome is (A,A).But (A,A ) is a strict NE of the payoff matrix . a u And at large n, there is mutual knowledge of the payoffs to high order- 1 knows that 2 knows that …. n/2 times. So “mutual knowledge to large n” has different NE than c.k.Also, consider "expanded games" with state space . 0,1,....,...n Ω=∞For each small positive ε let the distribution p ε be as above: 1(0)2/3,()(1)/3n p p n ee e e -==- for 0 and n <<∞()0p ε∞=.Define distribution by *p *(0)2/3p =,. *()1/3p ∞=As 0ε→, probability mass moves to higher n, andthere is a sense in which is the limit of the *p p εas 0ε→.But if we do say that *p p ε→ we have a failure of lower hemi continuity at a strict NE.So maybe we don’t want to say *p p ε→, and we don’t want to use mutual knowledge to large n as a notion of almost common knowledge.So the questions:• When should we say that one information structure is close to another?• What should we mean by "almost common knowledge"?This last question is related because we would like to say that an information structure where a set of events E is common knowledge is close to another information structure where these events are almost common knowledge.Monderer-Samet: Player i r-believes E at ω if (|())i p E h r ω≥.()r i B E is the set of all ω where player i r- believesE; this is also denoted 1.()ri B ENow do an iterative definition in the style of c.k.: 11()()rr I i i B E B E =Ç (everyone r-believes E) 1(){|(()|())}n r n ri i I B E p B E h r w w -=³ ()()n r n rI i i B E B =ÇEE is common r belief at ω if ()rI B E w ¥ÎAs with c.k., common r-belief can be characterized in terms of public events:• An event is a common r-truism if everyone r -believes it when it occurs.• An event is common r -belief at ω if it is implied by a common r-truism at ω.Now we have one version of "almost ck" : An event is almost ck if it is common r-belief for r near 1.MS show that if two player’s posteriors are common r-belief, they differ by at most 2(1-r): so Aumann's result is robust to almost ck, and holds in the limit.MS also that a strict NE of a game with knownpayoffs is still a NE when payoffs are "almost ck” - a form of lower hemi continuity.More formally:As before consider a family of games with fixed finite action spaces i A for each player i. a set of payoff matrices ,:l I u A R ->a state space W , that is now either finite or countably infinite, a prior p, a map such that :1,,,L l W®payoffs at ω are . ()(,)()w u a u a l w =Payoffs are common r-belief at ω if the event {|()}w l w l = is common r belief at ω.For each λ let λσ be a NE for common- knowledgepayoffs u .lDefine s * by *(())s l w w s =.This assigns each w a NE for the corresponding payoffs.In the email game, one such *s is . **(0)(,),()(,)s B B s n A A n ==0∀>If payoffs are c.k. at each ω, then s* is a NE of overall game G. (discuss)Theorem: Monder-Samet 1989Suppose that for each l , l s is a strict equilibrium for payoffs u λ.Then for any there is 0e >1r < and 1q < such that for all [,1]r r Î and [,1]q q Î,if there is probability q that payoffs are common r- belief, then there is a NE s of G with *(|()())1p s s ωωω=>ε−.Note that the conclusion of the theorem is false in the email game:there is no NE with an appreciable probability of playing A, even though (A,A) is a strict NE of the payoffs in every state but state 0.This is an indirect way of showing that the payoffs are never ACK in the email game.Now many payoff matrices don’t have strictequilibria, and this theorem doesn’t tell us anything about them.But can extend it to show that if for each state ω, *(s )ω is a Nash (but not necessarily strict Nash) equilibrium, then for any there is 0e >1r < and 1q < such that for all [,1]r r Î and [,1]q q Î, if payoffs are common r-belief with probability q, there is an “interim ε equilibria” of G where s * is played with probability 1ε−.Interim ε-equilibria:At each information set, the actions played are within epsilon of maxing expected payoff(((),())|())((',())|())i i i i i i i i E u s s h w E u s s h w w w w e-->=-Note that this implies the earlier result when *s specifies strict equilibria.Outline of proof:At states where some payoff function is common r-belief, specify that players follow s *. The key is that at these states, each player i r-believes that all other players r-believe the payoffs are common r-belief, so each expects the others to play according to s *.*ΩRegardless of play in the other states, playing this way is a best response, where k is a constant that depends on the set of possible payoff functions.4(1)k −rTo define play at states in */ΩΩconsider an artificial game where players are constrained to play s * in - and pick a NE of this game.*ΩThe overall strategy profile is an interim ε-equilibrium that plays like *s with probability q.To see the role of the infinite state space, consider the"truncated email game"player 2 does not respond after receiving n messages, so there are only 2n states.When 2n occurs: 2 knows it occurs.That is, . {}2(0,1),...(22,21,)(2)H n n =−−n n {}1(0),(1,2),...(21,2)H n =−.()2|(21,2)1p n n n ε−=−, so 2n is a "1-ε truism," and thus it is common 1-ε belief when it occurs.So there is an exact equilibrium where players playA in state 2n.More generally: on a finite state space, if the probability of an event is close to 1, then there is high probability that it is common r belief for r near 1.Not true on infinite state spaces…Lipman, “Finite order implications of the common prior assumption.”His point: there basically aren’t any!All of the "bite" of the CPA is in the tails.Set up: parameter Q that people "care about" States s S ∈,:f S →Θ specifies what the payoffs are at state s. Partitions of S, priors .i H i pPlayer i’s first order beliefs at s: the conditional distribution on Q given s.For B ⊆Θ,1()()i s B d =('|(')|())i i p s f s B h s ÎPlayer i’s second order beliefs: beliefs about Q and other players’ first order beliefs.()21()(){'|(('),('))}|()i i j i s B p s f s s B h d d =Îs and so on.The main point can be seen in his exampleTwo possible values of an unknown parameter r .1q q = o 2qStart with a model w/o common prior, relate it to a model with common prior.Starting model has only two states 12{,}S s s =. Each player has the trivial partition- ie no info beyond the prior.1122()()2/3p s p s ==.example: Player 1 owns an asset whose value is 1 at 1θ and 2 at 2θ; ()i i f s θ=.At each state, 1's expected value of the asset 4/3, 2's is 5/3, so it’s common knowledge that there are gains from trade.Lipman shows we can match the players’ beliefs, beliefs about beliefs, etc. to arbitrarily high order in a common prior model.Fix an integer N. construct the Nth model as followsState space'S ={1,...2}N S ´Common prior is that all states equally likely.The value of θ at (s,k) is determined by the s- component.Now we specify the partitions of each player in such a way that the beliefs, beliefs about beliefs, look like the simple model w/o common prior.1's partition: events112{(,1),(,2),(,1)}...s s s 112{(,21),(,2),(,)}s k s k s k -for k up to ; the “left-over” 12N -2s states go into 122{(,21),...(,2)}N N s s -+.At every event but the last one, 1 thinks the probability of is 2/3.1qThe partition for player 2 is similar but reversed: 221{(,21),(,2),(,)}s k s k s k - for k up to . 12N -And at all info sets but one, player 2 thinks the prob. of is 1/3.1qNow we look at beliefs at the state 1(,1)s .We matched the first-order beliefs (beliefs about θ) by construction)Now look at player 1's second-order beliefs.1 thinks there are 3 possible states 1(,1)s , 1(,2)s , 2(,1)s .At 1(,1)s , player 2 knows {1(,1)s ,2(,1)s ,(,}. 22)s At 1(,2)s , 2 knows . 122{(,2),(,3),(,4)}s s s At 2(,1)s , 2 knows {1(,2)s , 2(,1)s ,(,}. 22)sThe support of 1's second-order beliefs at 1(,1)s is the set of 2's beliefs at these info sets.And at each of them 2's beliefs are (1/3 1θ, 2/3 2θ). Same argument works up to N:The point is that the N-state models are "like" the original one in that beliefs at some states are the same as beliefs in the original model to high but finite order.(Beliefs at other states are very different- namely atθ or 2 is sure the states where 1 is sure that state is2θ.)it’s1Conclusion: if we assume that beliefs at a given state are generated by updating from a common prior, this doesn’t pin down their finite order behavior. So the main force of the CPA is on the entire infinite hierarchy of beliefs.Lipman goes on from this to make a point that is correct but potentially misleading: he says that "almost all" priors are close to a common. I think its misleading because here he uses the product topology on the set of hierarchies of beliefs- a.k.a topology of pointwise convergence.And two types that are close in this product topology can have very different behavior in a NE- so in a sense NE is not continuous in this topology.The email game is a counterexample. “Product Belief Convergence”:A sequence of types converges to if thesequence converges pointwise. That is, if for each k,, in t *i t ,,i i k n k *δδ→.Now consider the expanded version of the email game, where we added the state ∞.Let be the hierarchy of beliefs of player 1 when he has sent n messages, and let be the hierarchy atthe point ∞, where it is common knowledge that the payoff matrix is .in t ,*i t a uClaim: the sequence converges pointwise to . in t ,*i t Proof: At , i’s zero-order beliefs assignprobability 1 to , his first-order beliefs assignprobability 1 to ( and j knows it is ) and so onup to level n-1. Hence as n goes to infinity, thehierarchy of beliefs converges pointwise to common knowledge of .in t a u a u a u a uIn other words, if the number of levels of mutual knowledge go to infinity, then beliefs converge to common knowledge in the product topology. But we know that mutual knowledge to high order is not the same as almost common knowledge, and types that are close in the product topology can play very differently in Nash equilibrium.Put differently, the product topology on countably infinite sequences is insensitive to the tail of the sequence, but we know that the tail of the belief hierarchy can matter.Next : B-D JET 93 "Hierarchies of belief and Common Knowledge”.Here the hierarchies of belief are motivated by Harsanyi's idea of modelling incomplete information as imperfect information.Harsanyi introduced the idea of a player's "type" which summarizes the player's beliefs, beliefs about beliefs etc- that is, the infinite belief hierarchy we were working with in Lipman's paper.In Lipman we were taking the state space Ω as given.Harsanyi argued that given any element of the hierarchy of beliefs could be summarized by a single datum called the "type" of the player, so that there was no loss of generality in working with types instead of working explicitly with the hierarchies.I think that the first proof is due to Mertens and Zamir. B-D prove essentially the same result, but they do it in a much clearer and shorter paper.The paper is much more accessible than MZ but it is still a bit technical; also, it involves some hard but important concepts. (Add hindsight disclaimer…)Review of math definitions:A sequence of probability distributions converges weakly to p ifn p n fdp fdp ®òò for every bounded continuous function f. This defines the topology of weak convergence.In the case of distributions on a finite space, this is the same as the usual idea of convergence in norm.A metric space X is complete if every Cauchy sequence in X converges to a point of X.A space X is separable if it has a countable dense subset.A homeomorphism is a map f between two spaces that is 1-1, and onto ( an isomorphism ) and such that f and f-inverse are continuous.The Borel sigma algebra on a topological space S is the sigma-algebra generated by the open sets. (note that this depends on the topology.)Now for Brandenburger-DekelTwo individuals (extension to more is easy)Common underlying space of uncertainty S ( this is called in Lipman)ΘAssume S is a complete separable metric space. (“Polish”)For any metric space, let ()Z D be all probability measures on Borel field of Z, endowed with the topology of weak convergence. ( the “weak topology.”)000111()()()n n n X S X X X X X X --=D =´D =´DSo n X is the space of n-th order beliefs; a point in n X specifies (n-1)st order beliefs and beliefs about the opponent’s (n-1)st order beliefs.A type for player i is a== 0012(,,,...)()n i i i i n t X d d d =¥=δD0T .Now there is the possibility of further iteration: what about i's belief about j's type? Do we need to add more levels of i's beliefs about j, or is i's belief about j's type already pinned down by i's type ?Harsanyi’s insight is that we don't need to iterate further; this is what B-D prove formally.Coherency: a type is coherent if for every n>=2, 21marg n X n n d d --=.So the n and (n-1)st order beliefs agree on the lower orders. We impose this because it’s not clear how to interpret incoherent hierarchies..Let 1T be the set of all coherent typesProposition (Brandenburger-Dekel) : There is a homeomorphism between 1T and . 0()S T D ´.The basis of the proposition is the following Lemma: Suppose n Z are a collection of Polish spaces and let021201...1{(,,...):(...)1, and marg .n n n Z Z n n D Z Z n d d d d d --´´-=ÎD ´"³=Then there is a homeomorphism0:(nn )f D Z ¥=®D ´This is basically the same as Kolmogorov'sextension theorem- the theorem that says that there is a unique product measure on a countable product space that corresponds to specified marginaldistributions and the assumption that each component is independent.To apply the lemma, let 00Z X =, and 1()n n Z X -=D .Then 0...n n Z Z X ´´= and 00n Z S T ¥´=´.If S is complete separable metric than so is .()S DD is the set of coherent types; we have shown it is homeomorphic to the set of beliefs over state and opponent’s type.In words: coherency implies that i's type determines i's belief over j's type.But what about i's belief about j's belief about i's type? This needn’t be determined by i’s type if i thinks that j might not be coherent. So B-D impose “common knowledge of coherency.”Define T T ´ to be the subset of 11T T ´ where coherency is common knowledge.Proposition (Brandenburger-Dekel) : There is a homeomorphism between T and . ()S T D ´Loosely speaking, this says (a) the “universal type space is big enough” and (b) common knowledge of coherency implies that the information structure is common knowledge in an informal sense: each of i’s types can calculate j’s beliefs about i’s first-order beliefs, j’s beliefs about i’s beliefs about j’s beliefs, etc.Caveats:1) In the continuity part of the homeomorphism the argument uses the product topology on types. The drawbacks of the product topology make the homeomorphism part less important, but theisomorphism part of the theorem is independent of the topology on T.2) The space that is identified as“universal” depends on the sigma-algebra used on . Does this matter?(S T D ´)S T ×Loose ideas and conjectures…• There can’t be an isomorphism between a setX and the power set 2X , so something aboutmeasures as opposed to possibilities is being used.• The “right topology” on types looks more like the topology of uniform convergence than the product topology. (this claim isn’t meant to be obvious. the “right topology” hasn’t yet been found, and there may not be one. But Morris’ “Typical Types” suggests that something like this might be true.)•The topology of uniform convergence generates the same Borel sigma-algebra as the product topology, so maybe B-D worked with the right set of types after all.。
【托福听力备考】TPO3听力文本——Lecture 2
【托福听力备考】TPO3听力文本——Lecture 2对于很多学生来说，托福TPO材料是备考托福听力最好的材料。
相信众多备考托福的同学也一直在练习这套材料，那么在以下内容中我们就为大家带来托福TPO听力练习的文本，希望能为大家的备考带来帮助。
Lecture 2 Film historyNarrator：Listen to part of a lecture in a film history class.Professor：Okay, we’ve been discussing films in the 1920s and 30s, and how back then film categories, as we know them today, had not yet been established. We said that by today’s standards, many of the films of the 20s and 30s would be considered hybrids, that is, a mixture of styles that wouldn’t exactly fit into any of today’s categories. And in that context, today we are going to talk about a film-maker who began making very unique films in the late 1920s. He was French, and his name was Jean Painlevé.Jean Painlevé was born in 1902. He made his first film in 1928. Now in a way, Painlevé’s films conform to norms of the 20s and 30s, that is, they don’t fit very neatly into the categories we use to classify films today. That said, even by the standards of the 20s and 30s, Painlevé’s films were a unique hybrid of styles. He had a special way of fusing, or some people might say, confusing, science and fiction. His films begin with facts, but then they become more and more fictional. They gradually add more and more fictional elements. In fact, Painlevé was known for saying that science is fiction.Painlevé was a pioneer in underwater film-making, and a lot of his short films focused on the aquatic animal world. He liked to show small underwater creatures, displaying what seemed like familiar human characteristics – what we think of as unique to humans. He might take a clip of a mollusk going up and down in the water and set it to music. You know, to make it look as if the mollusk were dancing to the music like a human being – that sort of thing. But then he suddenly changed the image or narration to remind us how different the animals are, how unlike humans.He confused his audience in the way he portrayed the animals he filmed, mixing up our notions of the categories human and animal. The films make us a little uncomfortable at times because we are uncertain about what we are seeing. It gives him films an uncanny feature: the familiar made unfamiliar, the normal made suspicious. He liked twists, he liked the unusual. In fact, one of his favorite sea animals was the seahorse because with seahorses, it’s the male that carries the eggs, and he thought that was great. His first and most celebrated underwater film is about the seahorse.Susan, you have a question?Student 1：But underwater film-making wasn’t that unusual, was it? I mean, weren’t there other people making movies underwater?Professor：Well, actually, it was pretty rare at that time. I mean, we are talking the early 1930s here.Student 1：But what about Jacques Cousteau? Was he like an innovator, you know, with underwater photography too?Professor： Ah, Jacques Cousteau. Well, Painlevé and Cousteau did both film underwater, and they were both innovators, so you are right in that sense. But that’s pretty much where the similarities end.First of all, Painlevé was about 20 years ahead of Cousteau. And Cousteau’s adventures were high-tech, with lots of fancy equipment, whereas Painlevé kind of patchedequipment together as he needed it. Cousteau usually filmed large animals, usually in the open sea, whereas Painlevé generally filmed smaller animals, and he liked to film in shallow water.Uh, what else? Oh well, the main difference was that Cousteau simply investigated and presented the facts – he didn’t mix in fiction. He was a strict documentarist. He set the standard really for the nature documentary. Painlevé, on the other hand, as we said before, mixed in elements of fiction. And his films are much more artistic, incorporating music as an important element.John, you have a question?Student 2：Well, maybe I shouldn’t be asking this, but if Painlevé’s films are so special, so good, why haven’t we ever heard of them? I mean, everyone’s heard of Jacques Cousteau.Professor： Well, that’s a fair question. Uh, the short answer is that Painlev é’s style just never caught on with the general public. I mean, it probably goes back at least in part to what we mentioned earlier, that people didn’t know what to make of his films – they were confused by them, whereas Cousteau’s documentaries were very straightforward, met people’s expectations more than Painlevé’s films did. But you true film history buffs know about him. And Painlevé is still highly respected in many circles.。
Lecture2
=have an effect on... =have an influence on...
e.g. Forgiveness and encouragement can make a great difference to a
child's future.
□ embarrassed embarrassing
□ forgive
v.原谅
e.g. We are always told to forgive and forget, for there is a saying “to err is
human, to forgive divine”.
□ make a difference to...
对......产生影响
Useful Words
□ forgiveness
n.宽恕；饶恕
ask forபைடு நூலகம்beg for forgiveness 请求/乞求原谅
e.g. The little boy begged me for forgiveness when he learned what he did
hurt me badly.
a.感到尴尬的 a.令人尴尬的
e.g. I felt very embarrassed when I found my students making fun of me,
for this was very embarrassing.
□ keep/stay calm 保持冷静； calm/cool down 冷静下来
所有（三者以上） 任何一个（三者以上） 没有一个（三者以上）
e.g. All of the apples are small. You can take any of them. None of them is ripe.
lecture 2 英译汉的技巧
众所周知，过度肥胖或消瘦都肯定是
不健康的。 He acts a lot older than his years. 他年纪轻轻，做事却相当老练。
The
young girl thumbed her way to the passing cars.
那个年轻的姑娘站在路边不停地向来往的
汽车摆动着竖起的拇指表示她要搭车.
2.直译加注
(literal translation + annotation)
音译加注：音译后附加解释性注释。
1.
词语翻译
比萨饼 丰田车 撒哈拉沙漠 艾滋病 爵士乐
Pizza Toyota Sahara AIDS Jazz
2.
句子翻译 He did it a Jordon. 他投篮像飞人乔丹那样棒。 I’m Peter Darwin. Everyone asks, so I may as well say at once that no, I’m not related to Charles. 我叫彼得.达尔文。谁都会对我的名字产生疑问， 我不妨当下说个明白：我与进化论创始人查尔斯 没有关系。 A dead leaf fell in Soapy’s lap. That was Jack Frost’s card. 一片枯叶飘落到苏贝的膝头。那是杰克.弗罗斯 特的名片。（杰克.弗罗斯特：英文里对“寒霜” 的拟人称号。）
释义（paraphrase)
定义：舍弃原文的具体表达形式和比喻形
象，采取解释性的办法译出原文。在翻译 一些具有鲜明民族色彩的词语（如成语、 典故、超常规搭配）时，如果直译不能使 译文读者明白其意思，而加注又使译文太 啰嗦时，可采用释义法，将原文的意思传 达出来。
最优化方法Lecture2_LP基本性质
"" " "设P1, P2 , , Pk线性无关, 则k m.
P1 x1 P2 x2 Pk xk b
若k m,则B P1, P2 , , Pk 就是基.
若k m,则可从其余列向量中再挑出m k个列向量Pk1,
使P1, P2 , , Pk , , Pm线性无关。令B P1, P2 , , Pm
j 1
j 0, j 1, , l.
代入标准形
min
k
l
jcx j jcd j f x
j 1
j 1
k
s.t.
j 1, j 0, j 1, , k
j 1
j 0, j 1, , l.
1
若存在j, 使得cd j
0，则f
x
,即该问题无界.
2 对任意j, cd j 0,令 j 0, j 1, ,l得
4
5 2 5
基本解为x1
24 5
,
2 5
,
0,
0
T
.
或 B1 X B1 b
1 1
3
-2
x1 x2
6 增广矩阵
4
1 1
3 -2
6 4
初等变换
1
0
3 -5
6 -2
1 3
0
1
6 2
5
1
0
0 1
24 5 2 5
x1 24 5
x2
2 5
x(1)
24 5
x3
令
x1
x | 2
x
|
x2
|
x
| x 2
x3
y | 2
y|
x4
|
lecture 2
A landmark decision yesterday by an industrial tribunal on pension equality could leave the UK pension industry facing extra costs of £13 billion a year. 昨天一行业纠纷审理委员会作出一项史无前 例的裁决。此举可能使英国的养老金管理事 业每年要多支出130亿英镑。
But public outrage over abuse of privilege continued to mount, fueled by allegations of dope dealing at the House Post Office, unpaid bills at the exclusive members’ dining room and extravagant junketeering at taxpayers’ expense. 公众对国会议员滥用特权的义愤有增无减。 有些议员被指利用国会邮政所从事毒品交易， 有的被指控在专门餐厅用餐不付帐，有的被 指控华纳税人的钱公费旅游，这些更使公众 怒不可遏。
Foreign firms have increasingly turned to China to supply parts or make products, and such deals have been a hot political topic in the run-up to the US presidential elections as industry groups worry about losing ground to low-cost Chinese competitors. 外国企业越来越多地转向中国，或提供部件， 或制造产品。而这类交易成了美国总统竞选 前期的一个热门话题，因为一些行业担心在 中国低成本的竞争者面前处于下风。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
义勇军进行曲写于1935年，于1982年12月4日被全国 人民代表大会正式选作中国人民共和国国歌。
National Capital
• Beijing is not only the nation’s political centre, but also serves as its economic, scientific and cultural heart. Being one of the famous ancient capital cities in China, Beijing has gone through great development and changes since the founding of the PRC in 1949. There are many places of historic interest and scenic beauty in Beijing, such as: Forbidden City, Temple of Heaven, Summer Palace, Ming Tombs and the world-renowned Badaling section of the Great Wall. 北京不仅是中国的政治中心，也是经济、 科学和文化中心。作为中国最著名的古都之一， 北京自1949年中国人民共和国成立以来历经伟 大的发展和变化。在北京有很多历史古迹与风 景名胜，如：紫禁城、天坛、颐和园、明十三 陵和世界闻名的八达岭长城。
National Flag
• Chinese People’s Political Consultative Conference • CPPCC • 中华人民共和国政治协商会议 • Communist Party of China
• CPC
• 中国共产党
National Emblem
Tian’anmen Rostrum 天安门城楼
May 4th Movement 五四运动
National Anthem
Maቤተ መጻሕፍቲ ባይዱch of the Volunteers was written in 1935 and was officially adopted as the national anthem of the PRC on December 4, 1982, by the National People’s Congress (NPC).
Geography
Located in the east of the Asian continent, on the western shore of the Pacific Ocean, the PRC has a land area of about 9.6 million sq km, and is the third largest country in the world, next only to Russia and Canada.
Chapter 1: An Overview
Sunny
Brief introduction to Chinese Symbols
• National Day
中国人民将10月1 日定为国庆节，以此 纪念中华人民共和国 在1949年10月1日成 立。
Chinese celebrate October 1 as National Day in honor of the founding of the People’s Republic of China (PRC) on October 1, 1949.
• The State Council, or the Central People’s Government, of the People’s Republic of China is the executive body of the highest organ of state power and the highest organ of state administration. • 国务院，或称中央人民政府，是中华人民共和国的最高 国家权力机关的执行机关，也是最高国家行政机关。 • The CPPCC is a united front organisation under the leadership of the CPC. • 中华人民共和国政治协商会议是中国共产党领导下的统 一战线组织。
中国幅员辽阔，地理结构复杂。陆地面积约占960 万平方公里，仅次于俄罗斯和加拿大，是世界第三大国 家。中国有很多的名山大川，其中最著名的要数“三山 五岳”及包括长江在内的七大水系。
China has a vast territory with a complicated geographical structure. Its land is about 9.6 million square kilometers, and it is the third largest country in the world, only next to Russia and Canada. There are many great mountains and rivers in China. The most famous ones must be “Sanshanwuyue”, and seven major rivers, including the Yangtze River.
中国位于亚洲大陆东部，太平洋西岸，陆地面积约 960万平方公里，是世界第三大国家，仅次于俄罗斯和 加拿大。
Administrative Divisions
• one country, two systems • 一国两制 • special administrative region • 特别行政区
Population
• National Bureau of Statistics • 国家统计局 • the policy of family planning • 计划生育政策 • one child policy • 独生子女政策
The Political System
• The Constitution of the People’s Republic of China is the fundamental law of the state. • 中华人民共和国宪法是国家的基本法。
课堂翻译练习
很多中国人爱唱这样一首歌：“古老的东方有一条 龙，它的名字就叫中国；古老的东方有一群人，他们全 都是龙的传人……” 这里所说的“龙”是中华民族的 象征。
Many Chinese people like to sing a song: “There is a dragon in the ancient orient whose name is China. There is a group of ancient oriental people there too, who are all the descendants of the dragon…” Here the word “dragon” is the symbol of Chinese nation.
• The NPC is the highest organ of state power. • 全国人民代表大会是国家的最高权力机关。 • The Communist Party is the sole party in power in China. • 共产党是中国的唯一执政党。
The Political System