Agent-based model of competition in a social structure

Incentive-Based Modeling and Inference of Attacker Intent,Objectives,and StrategiesPENG LIU and WANYU ZANGPennsylvania State UniversityandMENG YUMonmouth UniversityAlthough the ability to model and infer attacker intent,objectives,and strategies(AIOS)may dramatically advance the literature of risk assessment,harm prediction,and predictive or proactive cyber defense,existing AIOS inference techniques are ad hoc and system or application specific. In this paper,we present a general incentive-based method to model AIOS and a game-theoretic approach to inferring AIOS.On one hand,we found that the concept of incentives can unify a large variety of attacker intents;the concept of utilities can integrate incentives and costs in such a way that attacker objectives can be practically modeled.On the other hand,we developed a game-theoretic AIOS formalization which can capture the inherent interdependency between AIOS and defender objectives and strategies in such a way that AIOS can be automatically inferred.Finally, we use a specific case study to show how attack strategies can be inferred in real-world attack–defense scenarios.Categories and Subject Descriptors:C.2.0[Computer-Communication Networks]:Security and ProtectionGeneral Terms:Security,TheoryAdditional Key Words and Phrases:Attacker intent and strategy modeling,attack strategy infer-ence,game theory1.INTRODUCTIONThe ability to model and infer attacker intent,objectives,and strategies(AIOS) may dramatically advance the state of the art of computer security for several reasons.First,for many“very difficult to prevent”attacks such as DDoS,given the specification of a system protected by a set of specific security mechanisms, This work was supported by DARPA and AFRL,AFMC,USAF,under award number F20602-02-1-0216,and by Department of Energy Early Career PI Award.Authors’addresses:P.Liu and W.Zang,School of Information Sciences and Technology, Pennsylvania State University,University Park,PA16802;email:pliu@;M.Yu,De-partment of Computer Science,Monmouth University,West Long Branch,NJ07764. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or direct commercial advantage and that copies show this notice on thefirst page or initial screen of a display along with the full citation.Copyrights for components of this work owned by others than ACM must be honored.Abstracting with credit is permitted.To copy otherwise,to republish,to post on servers, to redistribute to lists,or to use any component of this work in other works requires prior specific permission and/or a fee.Permissions may be requested from Publications Dept.,ACM,Inc.,1515 Broadway,New York,NY10036USA,fax:+1(212)869-0481,or permissions@.C 2005ACM1094-9224/05/0200-0078$5.00ACM Transactions on Information and System Security,Vol.8,No.1,February2005,Pages78–118.Incentive-Based Modeling and Inference of AIOS•79 this ability could tell us which kind of strategies are more likely to be taken by the attacker than the others,even before such an attack happens.Such AIOS inferences may lead to more precise risk assessment and harm prediction.Second,AIOS modeling and inference could be more beneficial during run time.A big security challenge in countering a multiphase,well-planned,care-fully hidden attack from either malicious insiders or outside attackers is“how to make correct proactive(especially predictive)real-time defense decisions during an earlier stage of the attack in such a way that much less harm will be caused without consuming a lot of resources?”Although many proactive de-fense techniques are developed such as sandboxing[Malkhi and Reiter2000] and isolation[Liu et al.2000],making the right proactive defense decisions in real time is very difficult primarily due to the fact that intrusion detection during the early stage of an attack can lead to many false alarms,which could make these proactive defense actions very expensive in terms of both resources and denial of service.Although alert correlation techniques[Cuppens and Miege2002;Ning et al. 2002]may reduce the number of false alarms by correlating a set of alerts into an attack scenario(i.e.,steps involved in an attack)and may even tell which kind of attack actions may follow a given action[Debar and Wespi2001], they are limited in supporting proactive intrusion response in two aspects.(1) When many types of(subsequences of)legitimate actions may follow a given suspicious action,alert correlation can do nothing except for waiting until a more complete attack scenario emerges.However,intrusion response at this moment could be“too late.”(2)When many types of attack actions may follow a given(preparation)action,alert correlation cannot tell which actions are more likely to be taken by the attacker next.As a result,since taking proactive defense actions for each of the attack actions can be too expensive,the response may have to wait until it is clear what attack actions will happen next—perhaps during a later stage of the attack.However,late intrusion response usually means more harm.By contrast,with the ability to model and infer AIOS,given any suspicious action,we can predict the harm that could be caused;then we can make better and affordable proactive intrusion response decisions based on the corresponding risk,the corresponding cost(e.g.,due to the possibility of false alarms),and the attack action inferences.Moreover,the intrusion response time is substantially shortened.However,with a focus on attack characteristics[Landwehr et al.1994]and attack effects[Browne et al.2001;Zou et al.2002],existing AIOS inference tech-niques are ad hoc and system or application specific[Gordon and Loeb2001; Syverson1997].To systematically model and infer AIOS,we need to distin-guish AIOS from both attack actions and attack effects.Since the same attack action can be issued by two attackers with very different intents and objectives, AIOS cannot be directly inferred from the characteristics of attacks.Although the attacker achieves his or her intents and objectives through attacks and their effects,the mapping from attack actions and/or effects to attacker intents and/or objectives is usually not one-to-one but one-to-many,and more inter-estingly,the(average)cardinality of this mapping can be much larger than the mapping from attacker intents and/or objectives to attack actions and/or ACM Transactions on Information and System Security,Vol.8,No.1,February2005.80•P.Liu et al.effects.This asymmetry nature indicates that in many cases using AIOS mod-els to predict attack actions can be more precise than using the set of actions already taken by the attacker based on either their effects or the causal rela-tionship between them and some other attack actions.1As a result,although a variety of attack taxonomies and attribute databases have been developed, people’s ability to model and infer AIOS,to predict attacks,and to do proactive intrusion response is still very limited.Nevertheless,a good understanding of attacks is the foundation of practical AIOS modeling and inference.In this paper,we present a systematic incentive-based method to model AIOS and a game-theoretic approach to inferring AIOS.On one hand,we found that the concept of incentives can unify a large variety of attacker intents;the con-cept of utilities can integrate incentives and costs in such a way that attacker objectives can be practically modeled.On the other hand,we developed a game-theoretic AIOS formalization which can capture the inherent interdependency between AIOS and defender objectives and strategies in such a way that AIOS can be automatically inferred.Finally,we use a specific case study to show how attack strategies can be inferred in real-world attack–defense scenarios.The proposed framework,in some sense,is an economics-based framework since it is based on economic incentives,utilities,and payoffs.The rest of the paper is organized as follows.In Section2,we discuss the related work.Section3presents a conceptual,incentive-based framework for AIOS modeling.In Section4,we present a game-theoretic formalization of this framework.Section5addresses show to infer AIOS.In Section6,we use a specific case study to show how attack strategies can be inferred in real-world attack–defense scenarios.In Section7,we mention several future research issues.2.RELATED WORKThe use of game theory in modeling attackers and defenders has been addressed in several other research.In Syverson[1997],Syverson talks about“good”nodes fighting“evil”nodes in a network and suggests using stochastic games for rea-soning and analysis.In Lye and Wing[2002],Lye and Wing precisely formalize this idea using a general-sum stochastic game model and give a concrete ex-ample in detail where the attacker is attacking a simple enterprise network that provides some Internet services such as web and FTP.A set of specific states regarding this example are identified,state-transition probabilities are assumed,and the Nash equilibrium or best-response strategies for the players are computed.In Browne[2000],Browne describes how static games can be used to an-alyze attacks involving complicated and heterogeneous military networks.In his example,a defense team has to defend a network of three hosts against an attacking team’s worms.The defense team can choose either to run a worm 1To illustrate,consider a large space of strategies the attacker may take according to his or her intent and objectives where each strategy is simply a sequence of actions.An attack action may belong to many strategies,and the consequences of the action could satisfy the preconditions of many other actions,but each strategy usually contains only a small number of actions.ACM Transactions on Information and System Security,Vol.8,No.1,February2005.Incentive-Based Modeling and Inference of AIOS•81 detector or not.Depending on the combined attack and defense actions,each outcome has different costs.In Burke[1999],Burke studies the use of repeated games with incomplete information to model attackers and defenders in in-formation warfare.In Hespanha and Bohacek[2001],Hespanha and Bohacek discuss zero-sum routing games where an adversary(or attacker)tries to in-tersect data packets in a computer network.The designer of the network has to find routing policies that avoid links that are under the attacker’s surveillance. In Xu and Lee[2003],Xu and Lee use game-theoretical framework to analyze the performance of their proposed DDoS defense system and to guide its design and performance tuning accordingly.Our work is different from the above game theoretic attacker modeling works in several aspects.First,these works focus on specific attack–defense scenarios, while our work focuses on general AIOS modeling.Second,these works focus on specific types of game models,for example,static games,repeated games, or stochastic games;while our work focuses on the fundamental characteris-tics of AIOS,and game models are only one possible formalization of our AIOS framework.In addition,our AIOS framework shows the inherent relationship between AIOS and the different types of game models,and identifies the condi-tions under which a specific type of game models will be feasible and desirable. Third,our work systematically identifies the properties of a good AIOS for-malization.These properties not only can be used to evaluate the merits and limitations of game-theoretic AIOS models,but also can motivate new AIOS models that can improve the above game theory models or even go beyond standard game-theoretic models.In Gordon and Loeb[2001],information security is used as a response to game theoretic competitor analysis systems(CAS)for the purpose of protecting a firm’s valuable business data from its competitors.Although understanding and predicting the behavior of competitors are key aspects of competitor analysis, the behaviors CAS want to predict are not cyber attacks.Moreover,security is what our game theoretic system wants to model while security is used in Gordon and Loeb[2001]to protect a game-theoretic system.The computational complexity of game-theoretic analysis is investigated in several research.For example,Conitzer and Sandholm[2002]show that both determining whether a pure strategy Bayes–Nash equilibrium exists and de-termining whether a pure strategy Nash equilibrium exists in a stochastic (Markov)game are NP-hard.Moreover,Koller and Milch[2001]show that some specific knowledge representations,in certain settings,can dramatically speed up equilibriumfinding.The marriage of economics and information security has attracted a lot of in-terests recently(a lot of related work can be found at the economics and security resource page maintained by Ross Anderson at /∼rja14 /econsec.html).However,these work focuses on the economics perspective of security(e.g.,security market,security insurance),while our approach is to apply economics concepts to model and infer AIOS.In recent years,it is found that economic mechanism design theory[Clarke 1971;Groves1973;Vickrey1961]can be very valuable in solving a variety of Internet computing problems such as routing,packet scheduling,and web ACM Transactions on Information and System Security,Vol.8,No.1,February2005.82•P.Liu et al.work topology.caching[Feigenbaum et al.2002;Nisan and Ronan2001;Wellman and Walsh2001].Although when market-based mechanisms are used to defend against at-tackers[Wang and Reiter2003],the AIOS are incentive based,which is consis-tent with our framework,market-based computing does not imply an in-depthAIOS model.Finally,it should be noticed that AIOS modeling and inference are very differ-ent from intrusion detection[Lunt1993;McHugh2001;Mukherjee et al.1994].Intrusion detection is based on the characteristics of attacks,while AIOS mod-eling is based on the characteristics of attackers.Intrusion detection focuses onthe attacks that have already happened,while AIOS inference focuses on theattacks that may happen in the future.3.AN INCENTIVE-BASED FRAMEWORK FOR AIOS MODELINGIn this section,we present an incentive-based conceptual model of attackerintent,objectives,and strategies.Our model is quite abstract.To make ourpresentation more tangible,we willfirst present the following example,whichwill be used throughout the paper to illustrate our concepts.Example1.In recent years,Internet distributed denial-of-service(DDoS)attacks have increased in frequency,severity,and sophistication and becomea major security threat.When a DDoS attack is launched,a large number ofhosts(called zombies)“controlled”by the attackerflood a high volume of pack-ets toward the target(called the victim)to downgrade its service performancesignificantly or make it unable to deliver any service.In this example,we would model the intent and objectives and infer thestrategies of the attackers that enforce brute-force DDoS attacks.(Althoughsome DDoS attacks with clear signatures,such as SYNflooding,can be effec-tively countered,most DDoS attacks without clear signatures,such as brute-force DDoS attacks,are very difficult to defend against since it is not clear whichpackets are DDoS packets and which are not.)An example scenario is shownin Figure1where many zombies(i.e.,a subset of source hosts{S0,...,S64})are flooding a couple of web sites(i.e.,the victims)using normal HTTP requests.Here,Rx.y denotes a router;the bandwidth of each type of links is marked;andthe web sites may stay on different subnets.ACM Transactions on Information and System Security,Vol.8,No.1,February2005.Incentive-Based Modeling and Inference of AIOS•83 Although our modeling and inference framework can handle almost every DDoS defense mechanism,to make this example more tangible,we select pushback[Ioannidis and Bellovin2002],a popular technique,as the security mechanism.Pushback uses aggregates,that is,a collection of packets from one or moreflows that have some properties in common,to identify and rate limit the packets that are most likely to cause congestion or DoS.Pushback is a coordinated defense mechanism that typically involves multiple routers.To il-lustrate,consider Figure1again,when router R1.0detects a congestion caused by a set of aggregates,R1.0will not only rate-limit these aggregates,but also request adjacent upstream routers(e.g.,R2.1)to rate-limit the corresponding aggregates via some pushback messages.The effectiveness of pushback can be largely captured by four bandwidth parameters associated with the incoming link to the victims(i.e.,the link that connects R1.0and R0.0):(a)B N,the total bandwidth of this link;(b)B ao,the (amount of)bandwidth occupied by the DoS packets;(c)B lo,the bandwidth occupied by the legitimate packets;(d)B lw,the bandwidth that the legitimate users would occupy if there are no attacks.For example,pushback is effective if after being enforced B ao can become smaller and B lo can become larger.We build our AIOS models on top of the relationships between the attacker and a computer system(i.e.,the defender).In our model,the computer sys-tem can be any kind(e.g.,a network system,a distributed system,a database system).We call it the system for short.For example,in Example1the sys-tem consists of every router on a path from a zombie to a victim.The attacker issues attacks to the system.Each attack is a sequence of attack actions associ-ated with the system.For example,an action can be the sending of a message, the submission of a transaction,the execution of a piece of code,and so on.An attack will cause some effects on the system,that is,transforming the system from one state to another state.For example,in Example1the main attack effects are that many legitimate packets could not reach the victims.Part of the system is a set of specific security mechanisms.A mechanism can be a piece of software or hardware(e.g.,afirewall,an access controller,an IDS).A mechanism usually involves a sequence of defense actions associated with the system when being activated.For example,in Example1a router sending out a pushback message is a defense action,and this action can trigger the receiving router(s)to take further defense actions.A security mechanism is activated when an event arrives which causes a set of specific conditions to be satisfied.Many of these conditions are associated with the effects of an attack action in reactive defense,or the prediction of an incoming attack action in proactive defense.For example,in Example1a packet arriving at a router is an event.When there is no congestion at the router,this event will not activate any security mechanism.However,when this event leads to“the detection of a congestion”(i.e.,the condition),pushback will be activated.And it is clear that whether this condition can be satisfied is dependent upon the accumulated effects of the previous DoS packets arriving at the router.Finally,a defense posture of the system is defined by the set of security mechanisms and the ways they are activated.For example,in Example1,pushback may be configured ACM Transactions on Information and System Security,Vol.8,No.1,February2005.84•P.Liu et al.to stay at various defense postures based on such parameters as congestion thresholds and target drop rate,which we will explain in Section3.3shortly.The attacker-system relation has several unique characteristics(or proper-ties)that are important in illustrating the principles of our attack strategy inference framework.These properties are as follows.—Intentional Attack Property.Attacks are typically not random.They are planned by the attacker based on some intent and objectives.—Strategy-Interdependency Property.Whether an attack can succeed is depen-dent on how the system is protected.Whether a security mechanism is effec-tive is dependent on how the system is attacked.In other words,the capacity of either an attack or a defense posture should be measured in a relative way.We will define the notion of strategy shortly.And we will use concrete attack and defense strategies derived from Example1to illustrate this property shortly in Section3.3.—Uncertainty Property.The attacker usually has incomplete information or knowledge about the system,and vice versa.For example,in Example1the attacker usually has uncertainty about how Pushback is configured when he or she enforces a DDoS attack.3.1Incentive-Based Attacker Intent ModelingDifferent attackers usually have different intents even when they issue the same attack.For example,some attackers attack the system to show off their hacking capacity,some hackers attack the system to remind the administrator of a securityflaw,cyber terrorists attack our cyberspace for creating damage, business competitors may attack each other’s information systems to increase their market shares,just to name a few.It is clear that investigating the char-acteristics of each kind of intents involves a lot of effort and complexity,and such complexity actually prevents us from building a general,robust connec-tion between attacker intents and attack actions.This connection is necessary to do almost every kind of attacker behavior inference.We focus on building general yet simple intent models.In particular,we believe that the concept of economic“incentives”can be used to model attacker intent in a general way.In our model,the attacker’s intent is simply to maximize his or her incentives.In other words,the attacker is motivated by the possibility of gaining some incentives.Most,if not all,kinds of intents can be modeled as incentives such as the amount of profit earned,the amount of terror caused, and the amount of satisfaction because of a nice show-off.For an example,in Example1the incentives for the attacker can be the amount of DoS suffered by the legitimate users.For another example,the incentives for an attacker that enforces a worm attack can be the amount of network resources consumed by the worm’s scanning packets plus the amount of DoS caused on certain type of services.We may use economics theory to classify incentives into such categories as money,emotional reward,and fame.To infer attacker intents,we need to be able to compare one incentive with another.Incentives can be compared with each other either qualitatively or ACM Transactions on Information and System Security,Vol.8,No.1,February2005.Incentive-Based Modeling and Inference of AIOS•85 quantitatively.Incentives can be quantified in several ways.For example,prof-its can be quantified by such monetary units as dollars.For another exam-ple,in Example1,the attacker’s incentives can be quantified by two metrics: (a)B ao/B N,which indicates the absolute impact of the DDoS attack;and(b)B lo/B lw,which indicates the relative availability impact of the attack.Accord-ingly,the attacker’s intent is to maximize B ao/B N but minimize B lo/B lw.One critical issue in measuring and comparing incentives is that under different value systems,different comparison results may be obtained.For example,dif-ferent types of people value such incentives as time,fame,and differently.As a result,very misleading attacker strategy inferences could be produced if we use our value system to evaluate the attacker’s incentives.After an attack is enforced,the incentives(e.g.,money,fame)earned by the attacker are dependent on the effects of the attack,which are typically captured by the degradation of a specific set of security measurements that the system cares about.Each such measurement is associated with a specific security met-ric.Some widely used categories of security metrics include but not limited to confidentiality,integrity,availability(against denial-of-service),nonrepudia-tion,and authentication.For example,in Example1the major security metrics of the system are(a)B lo,which indicates the absolute availability provided by the system;and(b)B lo/B lw,which indicates the relative availability provided by the system.In our model,we call the set of security metrics that a system wants to protect the metric vector of the system.(Note that different systems may have different metric vectors.)For example,the metric vector for the system in Example1can be simply defined as B lo,B lo/B lw .At time t,the measurements associated with the system’s metric vector are called the security vector of the system at time t,denoted by V s t.As a result,assume an attack starts at time t1 and ends at t2,then the incentives earned by the attacker(via the attack)maybe measured by degradation(V s t1,V s t2),which basically computes the distance be-tween the two security vectors.For example,in Example1assume the securityvector is V s t1= 1000Mbps,100% before the attack and V s t2= 50Mbps,5%after the attack,then degradation(V s t1,V s t2)= −950Mbps,−95% .The above discussion indicates the following property of AIOS inference:—Attack Effect Property.Effects of attacks usually yield more insights about at-tacker intent and objectives than attack actions.For example,in Example1,a DoS packet indicates almost nothing about the attacker’s intent which canonly be seen after some DoS effects are caused.3.2Incentive-Based Attacker Objective ModelingIn real world,many attackers face a set of constraints when issuing an attack, for example,an attacker may have limited resources;a malicious insider may worry about the risk of being arrested and put into jail.However,our intent model assumes no constraints.To model attacker motivations in a more realistic way,we incorporate constraints in our attack objective model.In particular,we classify constraints into two categories:cost constraints and noncost constraints.(a)Cost constraints are constraints on things that the attacker can“buy”or “trade”such as hardware,software,Internet connection,and time.Such things ACM Transactions on Information and System Security,Vol.8,No.1,February2005.86•P.Liu et al.are typically used to measure the cost of an attack.In addition,risk is typically a cost constraint.(b)Noncost constraints are constraints on things that the attacker cannot buy such as religion-based constraints and top secret attacking tools that the attacker may never be able to“buy.”The cost of an attack is not only dependent on the resources needed to en-force the attack,but also dependent on the risk for the attacker to be traced back,arrested,and punished.Based on the relationship between incentives and costs,we classify attackers into two categories:(a)rational attackers have concerns about the costs(and risk)associated with their attacks.That is,when the same incentive can be obtained by two attacks with different costs,ratio-nal attackers will pick the one with a lower cost.(b)Irrational attackers have no concerns about the costs associated with their attacks.They only want to maximize the incentives.Given a set of(cost)constraints,inferring the attack actions of an irrational attacker is not so difficult a task since we need only tofind out“what are the most rewarding attack actions in the eyes of the attacker without violating the constraints?”By contrast,we found that inferring the attack actions of a rational attacker is more challenging.In this paper,we will focus on how to model and infer the IOS of rational attackers.In our model,an attacker’s objective is to maximize his or her utilities through an attack without violating the set of cost and noncost constraints associated with the attacker.The utilities earned by an attacker indicate a distance be-tween the incentives earned by the attacker and the cost of the attack.The dis-tance can be defined in several ways,for example,utilities=incentives−cost, utilities=incentives.Note that the cost of an attack can be measured by a set of cost values which captures both attacking resources and risk.To illustrate,let us revisit Example1.The attacker’s total incentives may be measured byαB ao/B N+(1−α)(1−B lo/B lw),whereαdetermines how the attacker weighs the two aspects of the impact of the DDoS attack.The attack’s costs in this example are not much,though the attacker needs a computer and Internet access to“prepare”the zombies and the needed controls.The cost will become larger when the risk of being traced back is included.Let us assume the cost is a constant numberη.Then the attacker’s utilities can be measured by αB ao/B N+(1−α)(1−B lo/B lw)−η,and the attacker’s objective can be quantified as MaxαB ao/B N+(1−α)(1−B lo/B lw).3.3Incentive-Based Attacker Strategy ModelingStrategies are taken to achieve objectives.The strategy-interdependency prop-erty indicates that part of a good attacker strategy model should be the defense strategy model because otherwise we will build our AIOS models on top of the assumption that the system never changes its defense posture,which is too restrictive.See that whenever the system’s defense posture is changed,the defense strategy is changed.In our model,attack strategies are defined based on the“battles”between the attacker and the system.Each attack triggers a battle which usually involves multiple phases.(For example,many worm-based attacks involve such phases ACM Transactions on Information and System Security,Vol.8,No.1,February2005.。

考研英语阅读真题全文翻译考研英语阅读真题全文翻译众所周知,英语几乎是所有考生最头疼、难度最大的科目,而阅读理解又是英语各题型中的重中之中。

下面是店铺给大家准备的考研英语阅读的真题及全文翻译，欢迎大家阅读练习!Being a man has always been dangerous. There are about 105 males born for every 100 females, but this ratio drops to near balance at the age of maturity, and among 70-year-olds there are twice as many women as men. But the great universal of male mortality is being changed. Now, by babies survive almost as well as girls do. This means that, for the first time, there will be an excess of boys in those crucial years when they are searching for a mate. More important, another chance for natural selection has been removed. Fifty years ago, the chance of a baby (particularly a boy baby)surviving depended on its weight. A kilogram too light or too heavy meant almost certain death. Today it makes almost no difference. Since much of the variation is due to genes one more agent of evolution has gone.There is another way to commit evolutionary suicide: stay alive, but have fewer children. Few people are as fertile as in the past. Except in some religious communities, very few women has 15 children. Nowadays the number of births, like the age of death, has become average. Most of us have roughly the same number of offspring. Again, differences between people and the opportunity for natural selection to take advantage of it have diminished. India shows what is happening. The country offers wealth for a few in the great cities and poverty for the remaining tribal peoples. The grand mediocrity of today ---everyone being the same in survival and number of offspring---means thatnatural selection has lost 80% of its power in upper-middle-class India compared to the tribes.For us, this means that evolution is over; the biological Utopia has arrived. Strangely, it has involved little physical change No other species fills so many places in nature. But in the pass 100,000 years--- even the past 100year ---our lives have been transformed but our bodies have not. We did not evolve, because machines and society did it for us. Darwin had a phrase to describe those ignorant of evolution: they "look at an organic being as a savage looks at a ship, as at something wholly beyond his comprehension." No doubt we will remember a 20th century way of life beyond comprehension for its ugliness. But however amazed our descendants may be at how far from Utopia we were, they will look just like us.5. What used to be the danger in being a man according to the first paragraph?[A]A lack of mates. [B]A fierce competition.[C]A lower survival rate. [D]A defective gene.6. What does the example of India illustrate?[A]Wealthy people tend to have fewer children than poor people.[B]Natural selection hardly works among the rich and the poor.[C]The middle class population is 80% smaller than that of the tribes.[D]India is one of the countries with a very high birth rate.7. The author argues that our bodies have stopped evolving because____ .[A]life has been improved by technological advance[B]the number of female babies has been declining[C]our species has reached the highest stage of evolution[D]the difference between wealth and poverty is disappearing8. Which of the following would be the best title for the passage?[A]Sex Ration Changes in Human Evolution [B]Ways of Continuing Man's Evolution[C]The Evolutionary Future of Nature [D]Human Evolution Going Nowhere>>>>>>答案解析<<<<<<重点词汇：1.maturity (成熟)←matur(e)+ity，mature(成熟的v.成熟)，-ity 名词后缀。

Competition in Two-Sided MarketsMark ArmstrongDepartment of EconomicsUniversity College LondonAugust2002:revised May2005AbstractThere are many examples of markets involving two groups of agents who need to interact via“platforms”,and where one group’s bene…t from joining a platform dependson the number of agents from the other group who join the same platform.This paperpresents theoretical models for three variants of such markets:a monopoly platform;amodel of competing platforms where each agent must choose to join a single platform;and a model of“competing bottlenecks”,where one group wishes to join all platforms.The main determinants of equilibrium prices are(i)the relative sizes of the cross-groupexternalities,(ii)whether fees are levied on a lump-sum or per-transaction basis,and(iii)whether a group joins just one platform or joins all platforms.1Introduction and SummaryThere are many examples of markets where two or more groups of agents interact via inter-mediaries or“platforms”.Surplus is created—or perhaps destroyed in the case of negative externalities—when the groups interact.Of course,there are countless examples where…rms compete to deal with two or more groups.Any…rm is likely to do better if its products appeal to both men and women,for instance.However,in a set of interesting cases,cross-group network e¤ects are present,and the bene…t enjoyed by a member of one group depends upon how well the platform does in attracting custom from the other group.For instance,a heterosexual dating agency or nightclub can only do well if it succeeds in attracting business from both men and women.This paper is about such markets.An early version of this paper was presented at the ESEM meeting in Venice,August2002.I am grateful to the editor and two referees,to the audiences at many seminar presentations,to Simon Anderson,Carli Coetzee, Jacques Crémer,Xavier Vives and especially to Julian Wright for discussion,correction and information.1A brief list of other such markets includes:credit cards(for a given set of charges,a consumer is more likely to use a credit card which is accepted widely by retailers,while a retailer is more likely to accept a card which is carried by more consumers);television channels (where viewers generally prefer to watch a channel with fewer adverts,while an advertiser is prepared to pay more to place an advert on a channel with more viewers);and shopping malls (where a consumer is more likely to visit a mall with a greater range of retailers,while a retailer is willing to pay more to locate in a mall with a greater number of consumers passing through).See Rochet and Tirole(2003)for further examples of such markets.As this paper will argue in more detail,there are three main factors that determine the pattern of relative prices o¤ered to the two groups in equilibrium.Relative sizes of cross-group externalities:If a member of group1exerts a large positive externality on each member of group2,then group1will be targeted aggressively by platforms. In broad terms,and especially in competitive markets,it is group1’s bene…t to the other group that determines group1’s price,not how much group1bene…ts from the presence of group2 (see Proposition2below).In a nightclub,if men gain more from interacting with women than vice versa then we expect there to be a tendency for nightclubs to o¤er women lower entry fees than men.Unless they act to tip the industry to monopoly,positive cross-group network externalities act to intensify competition and reduce platform pro…ts—see expression(13)below.In order to be able to compete e¤ectively on one side of the market,a platform needs to perform well on the other side(and vice versa).This creates a downward pressure on the prices to both sides compared to the case where no cross-group network e¤ects exist.This implies that platforms would like to…nd ways to mitigate network e¤ects.One method of doing this is discussed next.Fixed fees or per-transaction charges:Platforms might charge for their services on a lump-sum basis,so that an agent’s payment does not explicitly depend on how well the platform performs on the other side of the market.Alternatively,if it is technologically feasible,the payment might be an explicit function of the platform’s performance on the other side.One example of this latter practice is where a TV channel or a newspaper makes its advertising charge an increasing function of the audience or readership it obtains.Similarly,a credit card network levies(most of)its charges on a per-transaction basis,while the bulk of a real estate agent’s fees are levied only in the event of a sale.The crucial di¤erence between the two charging bases is that cross-group externalities are weaker with per-transaction charges,since a fraction of the bene…t of interacting with an extra agent on the other side is eroded by the extra payment incurred.If an agent has to pay a platform only in the event of a successful interaction,then that agent does not need to worry about how well that platform will do in its dealings with the other side.That is to say,to attract one side of the market,it is not so important that the platform…rst gets the other side“on board”.Because network e¤ects are lessened with per-transactions charges,it is plausible that platform pro…ts are higher when this2form of charging is used.1(See Propositions3and5for illustrations of this e¤ect.)Finally,the distinction between the two forms of tari¤only matters when there are competing platforms. When there is a monopoly platform(see section3below),it makes no di¤erence to outcomes if tari¤s are levied on a lump-sum or per-transaction basis.Single-homing or multi-homing:When an agent chooses to use only one platform it has become common to say that the agent is“single-homing”.When an agent uses several platforms he is said to“multi-home”.It makes a signi…cant di¤erence to outcomes whether groups single-home or multi-home.In the broadest terms,there are three main cases to consider:(i)both groups single-home;(ii)one group single-homes while the other multi-homes,and(iii)both groups multi-home.If interacting with the other side is the primary reason for an agent to join a platform,then we might not expect case(iii)to be very common—if each member of group2joins all platforms,there is no need for any member of group1to join more than one platform—and so this con…guration is not analyzed in the paper.Con…guration(i)is discussed in section4.While the analysis of this case provides many useful insights about two-sided markets,it is hard to think of many markets that…t this con…guration precisely.By contrast,there are several important markets that look like con…guration(iii),and in section5these cases are termed“competitive bottlenecks”.Here,if it wishes to interact with an agent on the single-homing side,the multi-homing side has no choice except to deal with that agent’s chosen platform.Thus,platforms have monopoly power over providing access to their single-homing customers for the multi-homing side.This monopoly power naturally leads to high prices being charged to the multi-homing side,and there will be too few agents on this side being served from a social point of view(Proposition4).2By contrast,platforms do have to compete for the single-homing agents,and high pro…ts generated from the multi-homing side are to a large extent passed on to the single-homing side in the form of low prices(or even zero prices).Before embarking on this analysis in more detail,in the next section there is a selective literature review,followed in section3by an analysis of the monopoly platform case.1An exception to this occurs when the market tips to monopoly.In that case the incumbent’s pro…ts typically increase with the size of the network e¤ects since entrants…nd it hard to gain a toehold even when the incumbent sets high prices.This partly explains one conclusion of Caillaud and Jullien(2003),which is that equilibrium pro…ts typically rise when platforms cannot use transaction charges.2This tendency towards high prices for the multi-homing side is tempered somewhat when the single-homing side bene…ts from having many agents from the other side on the platform,for then high prices to the multi-homing side will drive away that side and thus disadvantage the platform when it tries to attract the single-homing side.However,this point is never su¢cient to undermine the basic result that the price charged to the multi-homing side is too high.32Related LiteratureI discuss some of the related literature later,as it becomes most relevant in the paper(especially in section5below).However,it is useful to discuss two pioneering papers up front.Caillaud and Jullien(2003)discuss the case of competing matchmakers,such as dating agencies,real estate agents,and internet“business-to-business”websites.3There is potentially a rich set of contracting possibilities.For instance,a platform might have a subscription charge in combination with a charge in the event of a successful match.In addition,Caillaud and Jullien allow platforms to set negative subscription charges,and to make their pro…t from taxing transactions on the platform.Caillaud and Jullien…rst examine the case where all agents must single-home.(I provide a parallel analysis in section4below.)In this case,there is essentially perfect competition,and agents have no intrinsic preference for one platform over another except insofar as one platform has more agents from the other side or charges lower prices.Therefore,the e¢cient outcome is for all agents to use the same platform. Caillaud and Jullien’s Proposition1shows that the only equilibria in this case involve one platform signing up all agents(as is e¢cient)and that platform making zero pro…ts.The equilibrium structure of prices involves negative subscription fees and maximal transactions charges,since this is the most pro…table way to prevent entry.Caillaud and Jullien go on to analyze the more complicated case where agents can multi-home.They analyze several possibilities,but the cases most relevant for this paper are what they term“mixed equilibria”(see their Propositions8and11).These correspond to the“competitive bottleneck”situations in this paper,and involve one side multi-homing and the other side single-homing.They…nd that the single-homing side is treated favourably(indeed,its price is necessarily no higher than its cost)while the multi-homing side has all its surplus extracted.I discuss the relationship between the two approaches in more detail in section5.5below.The second closely related paper is Rochet and Tirole(2003).The‡avour of their analysis can be understood in the context of the credit card market(although the analysis applies more widely).On one side of the market are consumers and on the other side is the set of retailers,and facilitating the interaction between these two groups are two competing credit card networks.For much of their analysis,the credit card platforms levy charges purely on a per-transaction basis,and there are no lump-sum fees for either side.Suppose that one credit card o¤ers a lower transaction fee to retailers than its rival.A retailer choosing between accepting just the cheaper card or accepting both cards faces a trade-o¤.If it accepts just the cheaper card then its consumers have a stark choice between paying by this card or not using a card at all.Alternatively,if it accepts both cards then(i)more consumers will choose to pay by some card but(ii)fewer consumers will use the retailer’s preferred lower-cost card.If a credit card reduces its charge to retailers relative to its rival,this will“steer”some retailers which previously accepted both cards to accept only the lower-cost card.In a symmetric equilibrium,all retailers accept both credit cards(or neither),while consumers always use 3See also van Raalte and Webers(1998).4their preferred credit card.The share of the charges that are borne by the two sides dependson how closely consumers view the two cards as substitutes.If few consumers switch cardsin response to a price cut on their side,then consumers should pay a large share of the totaltransaction charge;if consumers view the cards as close substitutes,then retailers will bearmost of the charges in equilibrium.Rochet and Tirole also consider the case where there are…xed fees as well as per-transaction fees,under the assumption that consumers use a singlecard.This is essentially the same model as the competitive bottleneck model in this paper,and I discuss this part of their paper in more detail in section5.5below.There are a number of modelling di¤erences between the current paper and Rochet andTirole(2003)which concern the speci…cation of agents’utility,the structure of platforms’fees,and the structure of platforms’costs.4In both papers agent j has gross utility from usingplatform i of the formu i j= i j n i+ i j:Here n i is the number of agents from the other side who are present on the platform, i j is the bene…t that agent j enjoys from each agent on the other side,and i j is the…xed bene…t the agent obtains from using that platform.Rochet and Tirole assume that i j does not dependon i or j(and can be set equal to zero),but that i j varies both with agent j and platformi.In section3and4of the current paper,by contrast,I assume that i j does not depend on i or j but only on which side of the market the agent is on,while i j depends on the agentand on the platform.(In section5I suppose that the interaction term for one side does vary.)The decision whether to make agents’heterogeneity to do with the interaction term or the…xed e¤ect has major implications for the structure of prices to the two sides in equilibrium.For instance,with a monopoly platform the formulas for pro…t-maximizing prices look verydi¤erent in the two papers.Moreover,when i j depends on the platform i,an agent caresabout on which platform the transaction takes place(if there is a choice):this e¤ect plays amajor role in Rochet and Tirole’s analysis but is absent in the present paper.5Turning to the structure of the platforms’fees,for the most part Rochet and Tirole assumethat agents pay a per-transaction fee for each agent on the platform from the other side.Ifthis fee is denoted i then agent j’s net utility on platform i is u i j=( i j i)n i(when is set equal to zero).This con…rms the discussion in section1above that per-transactionscharges act to reduce the size of network e¤ects.In the monopoly platform case,an agent’sincentive to join the platform does not depend on the platform’s performance on the otherside,and she will join if and only if i j i.The present paper,especially in section4, 4The assumptions in Caillaud and Jullien(2003)to do with utility and costs are closer to the current paper than to Rochet and Tirole.Caillaud and Jullien do not have any intrinsic product di¤erentiation between the platforms.However,there is a bene…t to join two platforms rather than one since they assume that there is a better chance of a match between buyers and sellers when two platforms are involved.5A recent paper that encompasses these two approaches with a monopoly platform is Rochet and Tirole (2004),where simultaneous heterogeneity in both and is allowed.However,a full analysis of this case is technically challenging in the case of competing platforms.5assumes that platform charges are levied as a lump-sum fee,p i say,in which case the agent’s net utility is u i j= n i+ i j p i.The…nal modelling di¤erence between the two papers is with the speci…cation of costs:Rochet and Tirole assume mainly that a platform’s costs are incurred on a per-transaction basis,so that if a platform has n1group1agents and n2group 2agents its total cost is cn1n2for some per-transaction cost c.In the current paper costs are often modelled as being incurred when agents join a network,so that a platform’s total cost is f1n1+f2n2for some per-agent costs f1and f2.Which assumptions concerning tari¤s and costs best re‡ects reality depends on the context.Rochet and Tirole’s model is well suited to the credit card context,for instance,whereas the assumptions in the current paper are intended to better re‡ect markets such as nightclubs,shopping malls and newspapers.3Model I:A Monopoly PlatformThis section presents the analysis for a monopoly platform.This framework does not apply to most of the examples of two-sided markets that come to mind,although there are a few applications.For instance,yellow pages directories are often a monopoly of the incumbent telephone company,shopping malls or nightclubs are sometimes far enough away from others that the monopoly paradigm might be appropriate,and sometimes there is only one newspaper or magazine in the relevant market.Suppose there are two groups of agents,denoted1and2.A member of one group cares about the number of the other group who use the platform.(For simplicity,I ignore the possibility that agents care also about the number of the same group who join the platform.) Suppose that the utility of an agent is determined in the following way:if the platform attracts n1and n2members of the two groups,the utilities of a group1and a group2agent are respectivelyu1= 1n2 p1;u2= 2n1 p2;(1) where p1and p2are the platform’s prices to the two groups.The parameter 1measures the bene…t that a group1agent enjoys from interacting with each group2agent,and 2measures the bene…t a group2agent obtains from each group1agent.Expression(1)describes how utility is determined as a function of the numbers of agents who participate.To close the demand model I specify the numbers who participate as a function of the utilities:if the utilities o¤ered to the two groups are u1and u2,suppose that the numbers of each group who join the platform aren1= 1(u1);n2= 2(u2)for some increasing functions 1and 2.Turning to the cost side,suppose that the platform incurs a per-agent cost f1for serving group1and per-agent cost f2for group2.Therefore,the…rm’s pro…t is =n1(p1 f1)+ n2(p2 f2).If we consider the platform to be o¤ering utilities f u1;u2g rather than prices f p1;p2g,then the implicit price for group1is p1= 1n2 u1(and similarly for group2).6Therefore,expressed in terms of utilities,the platform’s pro…t is(u1;u2)=[ 1 2(u2) u1 f1] 1(u1)+[ 2 1(u1) u2 f2] 2(u2):(2) Let the aggregate consumer surplus of group1be v1(u1),where v1satis…es the envelope condition v01(u1) 1(u1),and similarly for group2.Then total welfare,as measured by the unweighted sum of pro…t and consumer surplus,isw= (u1;u2)+v1(u1)+v2(u2):It is easily veri…ed that the…rst-best welfare maximizing outcome involves utilities satisfying:u1=( 1+ 2)n2 f1;u2=( 1+ 2)n1 f2:From expression(1)the socially optimal prices satisfyp1=f1 2n2;p2=f2 1n1:As one would expect,the optimal price for group1,say,equals the cost of supplying service to a type1agent adjusted downwards by the external bene…t that an extra group1agent brings to the group2agents on the platform.(There are n2group2agents on the platform, and each one bene…ts by 2when an extra group1agent joins.)In particular,prices should ideally be below cost if 1; 2>0.From expression(2),the pro…t-maximizing prices satisfyp1=f1 2n2+ 1(u1)01(u1);p2=f2 1n1+ 2(u2)02(u2):(3)Thus,the pro…t-maximizing price for group1,say,is equal to the cost of providing service(f1), adjusted downwards by the external bene…t( 2n2),and adjusted upwards by a factor related to the elasticity of the group’s participation.The pro…t-maximizing prices can be obtained in the more familiar form of Lerner indices and elasticities,as recorded in the following result: Proposition1Write1(p1j n2)=p1 01( 1n2 p1)1( 1n2 p1); 2(p2j n1)=p2 02( 2n1 p2) 2( 2n1 p2)for a group’s price elasticity of demand for a given level of participation by the other group. Then the pro…t-maximizing pair of prices satisfyp1 (f1 2n2)p1=11(p1j n2);p2 (f2 1n1)p2=12(p2j n1):(4) 7It is possible that the pro…t-maximizing outcome might involve group1,say,being o¤ereda subsidised service,i.e.,p1<f1.From(4),this happens if the group’s elasticity of demandis high and/or if the external bene…t enjoyed by group2is large.Indeed,the subsidy mightbe so large that the resulting price is negative(or zero,if negative prices are not feasible).This analysis applies,in a stylized way,to a market with a monopoly yellow page directory.Such directories typically are given to telephone subscribers for free,and pro…ts are made fromcharges to advertisers.The analysis might also apply to software markets where one type ofsoftware is required to create…les in a certain format and another type of software is requiredto read such…les.(For the analysis to apply accurately,though,there needs to be two disjointgroups of agents:those who wish to read…les and those who wish to create…les.It does notreadily apply when most people wish to perform both tasks.)4Model II:Two-Sided Single-HomingThis model involves competing platforms,but assumes that,for exogenous reasons,each agentfrom either group chooses to join a single platform.4.1Basic ModelThe model extends the previous monopoly model in a natural way.There are two groups ofagents,1and2,and there are two platforms,A and B,which enable the two groups to interact.Groups1and2obtain the respective utilities f u i1;u i2g from platform i.These utilities f u i1;u i2g are determined in a similar manner to the monopoly model expressed in(1):if platform iattracts n i1and n i2members of the two groups,the utilities on this platform areu i1= 1n i2 p i1;u i2= 2n i1 p i2;(5) where f p i1;p i2g are the respective prices charged by the platform to the two groups.When group1is o¤ered a choice of utilities u A1and u B1from the two platforms,and group2is o¤ered the choice u A2and u B2,suppose that the number of each group who go to platformi is given by the Hotelling speci…cation:n i1=12+u i1 u j12t1;n i2=12+u i2 u j22t2:(6)Here,agents in a group are assumed to be uniformly located along a unit interval with the two platforms located at the two end-points,and t1,t2>0are the product di¤erentiation(or transport cost)parameters for the two groups that determine the competitiveness of the two markets.8Putting(6)together with(5),and using the fact that n j1=1 n i1,gives the following implicit expressions for market shares:n i1=12+1(2n i2 1) (p i1 p j1)2t1;n i2=12+2(2n i1 1) (p i2 p j2)2t2:(7)Expressions(7)show that,keeping its group2price…xed,an extra group1agent on a platformattracts a further 2t2group2agents to that platform.Suppose that the network externality parameters f 1; 2g are small compared to the dif-ferentiation parameters f t1;t2g so that I can focus on market-sharing equilibria.(If network e¤ects were large compared to brand preferences then there could only be equilibria where one platform corners both sides of the market.)It turns out that the necessary and su¢cient condition for a market-sharing equilibrium to exist is the following:4t1t2>( 1+ 2)2(8) and this inequality is assumed to hold in the following analysis.Suppose that platforms A and B o¤er the respective price pairs(p A1;p A2)and(p B1;p B2). Solving the simultaneous equations(7)implies that market shares are determined by the four prices as:n i1=12+121(p j2 p i2)+t2(p j1 p i1)t1t2 1 2;n i2=12+122(p j1 p i1)+t1(p j2 p i2)t1t2 1 2:(9)(Assumption(8)implies that the above denominators t1t2 1 2are positive.)Thus,assuming 1; 2>0,a platform’s market share for one group is decreasing in its price o¤ered to the other group.As with the monopoly model,suppose that each platform has a per-agent cost f1for serving group1and f2for serving group2.Therefore,pro…ts for platform i are(p i1 f1)"12+12 1(p j2 p i2)+t2(p j1 p i1)t1t2 1 2#+(p i2 f2)"12+12 2(p j1 p i1)+t1(p j2 p i2)t1t2 1 2#:This expression is quadratic in platform i’s prices,and is concave in these prices if and only if assumption(8)holds.Therefore,platform i’s best response to j’s prices is characterized by the…rst-order conditions.Given assumption(8),one can check there are no asymmetric equilibria.For the case of a symmetric equilibrium where each platform o¤ers the same price pair(p1;p2),the…rst-order conditions for equilibrium prices arep1=f1+t1 2t2( 1+p2 f2);p2=f2+t2 1t1( 2+p1 f1):(10)Expressions(10)can be interpreted in the following manner.First,note that in a Hotelling model without network e¤ects,the equilibrium price for group1would be p1=f1+t1.In9this two-sided setting the price is adjusted downwards by the factor 2t2( 1+p2 f2).Thisadjustment factor can be decomposed into two parts.The term( 1+p2 f2)represents the “external”bene…t to a platform of having an additional group2agent.To see this,note…rst that the platform makes pro…t(p2 f2)from each extra group2agent.Second, 1measures the extra revenue the platform can extract from its group1agents(without losing market share)when it has an extra group2agent.6Thus( 1+p2 f2)indeed represents the external bene…t to a platform of attracting the marginal group2agent.Finally,as shown in expression(7),a platform attracts 2t2extra group2agents when it has an extra group1agent.In sum,the adjustment factor 22( 1+p2 f2)measures the external bene…t to the platform fromattracting an extra group1agent;in other words,it measures the opportunity cost of raising the group1price enough to cause one group1agent to leave.I summarize this discussion by an annotated version of formula(10):p1=f1|{z}cost of service+t1|{z}market power factor 2t2|{z}extra group2agents( 1+p2 f2)|{z}pro…t from each extra group2agent(11)Finally,solving the simultaneous equations(10)implies that p1=f1+t1 2and p2= f2+t2 1:This discussion is summarized as:Proposition2Suppose that assumption(8)holds.Then the model with two-sided single-homing has a unique equilibrium which is symmetric.Equilibrium prices for group1and group2are given byp1=f1+t1 2;p2=f2+t2 1:(12) Thus,a platform will target one group more aggressively than the other if that group is (i)on the more competitive side of the market and/or(ii)causes larger bene…ts to the other group than vice versa.7While expressions(12)are certainly“simple”,they are not intuitive,and this is why I focussed the discussion on(10).The fact that,say,group1’s price does not depend on its own externality parameter 1is surely an artifact of the Hotelling speci…cation for consumer demand.In particular,the fact that the total size of each group is…xed,so that when platforms set low prices they only steal business from the rival rather than expand the overall 6An extra group2agent means that the utility of each group1agent on the platform increases by 1,while the utility of each group1agent on the rival platform falls by 1.Therefore,the relative utility for group1 agents being on the platform increases by2 1and each of the agents can bear a price increase equal to this. Since in equilibrium a platform has half the group1agents,the extra revenue it can extract from these agents is 1,as claimed.7It is possible given our assumptions that one price in the above expression is negative.This happens if that side of the market involves a low cost,is competitive,or causes a large external bene…t to the other side. In many cases it is not realistic to suppose that negative prices are feasible,in which case the analysis needs to be adapted explicitly to incorporate the non-negativity constraints—see Armstrong and Wright(2004)for this analysis.10。

Attention-based LearningS. Kasderidis & J. G. TaylorDepartment of Mathematics, Kings College London, Strand, WC2R 2LS, UK stahis@, john.g.taylor@/Abstract-We apply an attention-based framework in the creation of an autonomous robot control system. We use a specific task, that of route planning for a robot in a dynamic environment, to present the general control architecture, and finally we show how it can be applied to the problem. Initial results of a simple simulation are presented with focus on the learning aspects.I. I NTRODUCTIONAttention is arguably the highest-level control system in the human brain. It allows a system possessing it to be able to reduce the problems presented by distracters in a noisy environment, and to prioritise tasks to be solved so that less important ones, elicited by distracting cues, can be avoided. An important component of such attention control is the creation of suitable goal structures, regarded as representations in the human frontal lobes. Much research has been recently contacted in attention [1, 2].A human attention-processing model was based on an engineering control framework ideas [3, 4, 5]. We have also extended the notion of attention processing from a model of the human brain to the more general context of attentive agents [6, 7, 8]. These have both a ‘personalised’ internal attention control system, as well as an overall attention control system able to handle agent-to-agent interactions. Attention is used in the latter framework in a multitude of ways. It serves as the learning generator, as a local control system in a modality level and as a global competition system among conflicting goals.In this paper we apply the notion of attention control to a robot in a complex environment. We present the various roles of attention and explain the main ideas. Our focus is on the learning aspects. In section 2 we present a specific task environment we think appropriate to test the architecture. In section 3 the attention architecture is presented. Results are presented in section 4, and a discussion is given in section 5.II. G ENERAL PROBLEMS AND A SPECIFIC TASKENVIRONMENTThere are a number of problems that must be solved before robust autonomous agents can be achieved. Most of the difficulties arise from the fact that the agents must operate in an open environment. To handle such a case one needs to equip the agent with a number of faculties. On the one hand the agent must operate in an effortless manner when no unexpected conditions arise in its environment, while on the other hand it should be able to learn dynamically in cases where a decreasing performance is realised. The first mode uses the idea of creating and automating appropriate schemata for the solution of the corresponding problems. The second mode is based in the assumption that in a dynamic open environment perfect performance could never be achieved. Erroneous performance will be realised due to novelties, other structural changes in the current environment and the goal oriented behaviour of other agents (limited information). The solution to this problem is to enable the agent to learn dynamically corrections to its poor actions and eventually automate the corrected behaviour. Attention is the ultimate generator of knowledge as attention itself controls the switching from the automated mode to learning modes.To make these ideas more concrete we consider a specific problem. This is the case of robot route planning. In simple words, we try to find an appropriate path for the robot’s movement in an environment where a number of stationary and moving objects exist. Stationary objects typically include household items such as furniture and moving objects include other robots, humans sharing the environment and other less ‘intelligent’ but mobile equipment.There are two main factors that generate errors and thus threats for the robot in such an environment. On the one hand novelties could appear and thus suddenly change the conditions of the environment. On the other hand, the assumption of possessing accurate motion models for the other agents does not hold. This is due to the fact that the other agents may also exhibit goal-oriented behaviour and thus introduces difficulty in acquiring their goals and ‘motivations’ through external observation alone. A degree of uncertainty will always remain. The situation is not uncommon to that of humans walking in a busy street.Let us now describe a simple scenario that would implement the task environment. Assume that a worker robot is inside a factory floor and its job is to move some item of interest from a point A to a point B. Assume further that these two points are at two distant sides of the floor and that the floor is of rectangular shape and it is divided in a X-Y grid (GridWorld). The robot moves in this grid in a forward direction. When the robot wants to change direction it performs a turn around its z-axis by 45 degrees. The turn could be either left or right (to the localsystem of coordinates). The robot carries a number of sensors. They are: a power sensor for detecting the power level, an overall proximity sensor (with a 360 degrees view of the environment), and one position/speed sensor for knowing its own coordinates and speed. In addition an actuator exists which controls the speed and the direction of the robot. The GridWorld is shown in figure 1.Fig. 1. Factory floor layout.Terminal C is the recharging station for the robot. Sobj x is the name of a stationary object. Mobj x is the name of a moving object. The figure shows a possible configuration of the GridWorld with three stationary objects and two moving ones. Realisations for the trajectories of the moving objects are also shown with dashed lines.The problem that we face is how to move from point A to point B and possibly C avoiding collisions both with static and moving objects.III. A RCHITECTUREThe architecture we use is based on that extracted from the human brain, in terms of a goal system with an attention control mechanism (the details appear in [7, 8]). An agent possesses a number of goals represented as a tree structure (with higher importance goals positioned nearer the root, less important ones further apart). Each goal is associated with a service procedure (a schema that satisfies the goal, given as a template with adaptive elements). The general schema template with local attention control is shown in figure 2 (more detail in [8]).The architecture has four processing levels: level one has sensors and actuators, level two has pre-processing facilities, level three has schemata (services) for atomic goals, and level four has schemata for composite goals. Figure 2 represents the service of an atomic goal, which tries to achieve a target state. A composite goal has a different structure than the one shown in figure 2, due to the fact that its service function manages and produces an overall result from a number of children goals. We will not extend our discussion at this level further, but focus on level 3 atomic goals.In figure 2 seven main modules appear: the State, Observer, Goals, Monitor, Attention Controller, Rules and Forward Models modules. The State module collects sensor signals and constructs representations, using three distinct representations, of which only one is used here, the Native one, which is the Cartesian product of the incoming signals. The Observer module is a state predictor for estimating the next sensory state and building an “expected state”, to be compared, in the Monitor module, with the currently observed state (coming from the State module) to determine if major deviations exist. If a deviation threshold is crossed, an attention event is created and sent to the Attention Controller; it carries an Attention Index, a monotonically increasing function of the observed deviation in the Monitor module, bounded in the interval [0, 1]. The Attention Controller module is conceptually a stack/queue that determines the priority with which the dispatched attention events will be handled. In the simplest case the identity function can be used to determine the priority. The Rules module is the action generator component of the schema, using typically a symbolic model, i.e. rules, to produce appropriate responses, with input the current state classification and any attention event present. The Forward Models module produces predictions of the next state of the agent, given the realization of the action proposed by the Rules module. The Goals module serves as a database where a number of adaptive models necessary in the scope of the schema are necessary. It also includes the required target state that must be achieved.We assume that the robot carries three sensors, and an actuator. In figure 2, the robot uses a number of sensors: the power sensor, the proximity sensor and the position/speed sensor. For simplicity we assume that the proximity sensor provides information for both the current position and speed of the other objects. In addition a single actuator exists which controls the speed and the direction of the robot. Inside the robot only one user defined goal is executed: the Move Item goal. The purpose of this goal is to have the robot move an item from a point A to point B. It has two children goals: the Transport and Collision Avoidance (CA) goals. The transport goal is decomposed in four sub-goals: Goto A, Get Item, Goto B, Leave Item. The interesting goal to discuss here is the Goto x. It is further decomposed into the Route Planning (RP) and Move goals.The Move goal accepts a newly calculated position from the Route Planner and acts on the actuator. The State module collects information about the current position and speeds of the other agents and itself. It evaluates the current trajectories of the other moving objects through the Observer module. The module uses a motion model for each of the other moving objects,realised as a suitable neural network. If the observed positions/speeds of other agents differ enough from the expected ones,Fig. 2. Level 3 schema architecture.then an attention event is created. The attention index is calculated as:(where vectors X obs and X exp represent the observed and expected position of a given moving object respectively). T is a suitable threshold, which measures the proximity of the two locations; Step(•) is the step function; it outputs 1 if the argument is positive, else it is zero. the vector X uses the x and y coordinates of a GridWorld cell. Given the information about the current positions of the various agents, the Rules module suggests a new position closer to the target position, which is then checked against the prediction of the Forward Models so as to make sure that in the next step the other objects and the robot will not collide or that it is not is otherwise occupied. If no problem is detected then the suggested new position is accepted and it is forwarded for execution to the Move goal.There are two sources of problems. On the one hand, mechanical problems may not allow the proper actuator commands to be performed or alternatively the executed commands may not result in bringing the agent in the desired state that the planner system intended. In both cases we have failures of the Move goal. This goal uses another type of attention, which is called motor attention (in contrast with the sensory attention described above in (1)). It also observes and compares the expected and the occurred (internal) states of the agent: it makes sure that the agent is brought to the required state so as to conform to the overall environmental state (which includes the other agents) according to the plan of the RP.During the execution of the planned motor action (i.e. moving to the next cell) we may find that the other agents did not really move according to prediction of the motion model. The Collision Avoidance goal will capture this deviation and create an appropriate attention event, which will result in taking corrective action: simply moving away in the opposite direction to an approaching object. We assume the existence of a safety zone around the agent, with radius R. If the boundary of the safety zone is crossed then an attention event is created with the following attention index:The idea behind (2) is that the event is more severe as we enter further into the safety zone. X obs is the observed position of another agent, whereas X agent is the agent’s own position. The action that is created as a response to an attention event is twofold: First, it leads to the update of the current motion model for the corresponding other agent. Second, it takes averting action so as to avoid a collision. The structure of the Collision Avoidance goal follows the template of figure 2. The Observer is used for ‘following’ in runtime the path of the other objects.It should be made clear at this point that the CA-Observer, RP-Observer and RP-Forward Models modules all use the same underlying motion model for a given observed (other) agent. This is a neural network model that has as inputs the current position, current speed and previous positions (up to some lag time K) of the other agent. The model is updated dynamically as a result of Collision Avoidance’s attention control. This is the role of attention as learning initiator. At this point the second role of attention is highlighted: that of a global competition for conflict resolution. We have explained previously that if a collision is detected, corrective action is taken. This is achieved because the CA goal effectively suppresses the sub-tree starting at the Transport goal, which belongs to the same level as itself. The mechanism with which this result is achieved is based on Action Indices (a generalisation of the Attention Index concept). The details are given in [8]. We just provide the relevant formula here:Where S-AI and M-AI are the sensory and motor attention indices and W is the goal’s intrinsic weight (available through learning of a value system). A child is considering as contributing if any kind of attention event is created in its scope (at the given time) or if it posses itself a contributing child. Formula (3) introduces a mechanism, which can be used for comparing ‘importance’ of execution among conflicting goals. WithS-AI-RP=Step(||X obs-X exp ||-T)*(2/[1+exp(-(||X obs-X exp||-T)]-1) (1)S-AI-CA=exp(-||X obs-X agent ||), if||X obs-X agent || <R,S-AI-CA=0, if ||X obs-X agent || ≥ R(2)Action Index=(W+S-AI+M-AI + ∑jδ(j, contribut.))/ (3+# Contributing Children)(3)appropriate weighting the Collision Avoidance goal can be made to take precedence over the Transport goal. Thus suppression of the Transport sub-tree is achieved and its execution is stopped for the given processing step. The only action that will be generated is this originating from the CA goal. In normal circumstances the Collision Avoidance is suppressed from the Transport goal. Local attention control in figure 2 is achieved by changing sampling rates or otherwise of appropriate sensors. Control is needed in this level in order to minimise the power requirements of enhanced resolution information (in time and space) against the need for higher service times of the robot.Finally we must observe that the attention indices, (1) and (2), can be used as modulators of the learning rates present in the motion models. In particular a suitable formula is given by (4):Where ε is a permanent small rate, say 10-4, AI is a suitable attention index and r is the learning rate used in the neural network motion model. Learning is assumed to take place in the background continually, using in (4) as attention index formula (2).IV. S IMULATION & RESULTSWe use the GridWorld of figure 1 to perform a number of simulations. The size of the grid is 50x50. The stationary objects are located as in the figure. A number of moving objects were used. The motion model was implemented using a neural network approach to the target cell. The network used as inputs the positions from current time up to K steps in the past and the current speed. K was varied from 0 to 5. We assumed also infinite sensing range. The speed of the robot is either set to one or zero. The target of the simulations is to study the effectiveness of the proposed architecture in detecting a danger and learning effective motion models.The simulation was setup as follows: We have used a varying number of moving objects for checking the agent’s effectiveness on avoiding a collision. We used 5, 10, 15, 20 and 25 moving objects. All the other agents were given fixed but unknown trajectories to follow. Randomness in the trajectories was introduced in two ways. On the one hand, the trajectory was formed by selecting random start and end service points for a given moving object. This had the effect of covering the whole floor with intersecting trajectories. On the other hand, small random movements around the main calculated trajectory were introduced at random points. The trajectory was calculated using a linear approach to the target cell and taking corrective steps when approaching a stationary object. When another moving object was approaching, no special action was taken, so collisions were possible. In this way we had a population of simple moving agents, which collided with each other and with our own attention-based agent. The statistic of interest was the number of collisions taking place per step. This was calculated as follows: We assumed a fixed simulation duration of 350 steps; we used 10 different trajectory configurations so as to average the randomness in the experiment’s initial configuration and we studied three cases. A baseline case (dummy agent), a predictive agent and an attention-based predictive agent. All of them were using the same basic route-planning algorithm. The difference was introduced in the way that the three types of agents were using the suggestions of the route planning system. The dummy agent simply accepted the suggestions. The predictive agent was using its motion model for forecasting future collisions. If a collision was predicted, then another call to the route planner was made so as to calculate a new position given the new information. The same approach was used by the attention-based agent. The predictive and attentive agents were also updating their motion models (in the next step) if an unsuccessful prediction was made. For these experiments we used a back-propagation method. The resulting network had as inputs the current x and y coordinates of the GridWorld cell, the current heading vector, expressed as a value out of a fixed set of directions and possibly x and y coordinates of previous positions. We used up to K=5 lag vectors of x/y coordinates in the motion models. Typically, the higher the number of the lag steps the better the prediction accuracy of the model. However, all models suffered, naturally, when discontinuities in the path were realised due to a sudden turn due to random variations or due to route planner’s calculated trajectory at that point.The predictive type of agent had a fixed learning rate of r=0.05, whereas the attentive agent used formula (4) for learning rate modulation.In figure 3 we show a number of series. The labels of Dummy, Smart and Smart-Att correspond to the dummy, predictive and attentive agents respectively. The first sub-graph describes the severity of the collisions while the second one describes the number of collisions suffered. Both figures describe average numbers per step of the trajectory. The results were also averaged over 10 different floor configurations per case of agent, i.e. dummy, predictive and attentive. The calculation of collision was made as follows: We assumed the existence of a safety zone around the agent of interest. The radius of the zone was variable. In figure 3 we used a radius of 6 cells. If during its movement from one cell to another the agent experienced the crossing of its safety zone from another agent, this was counted as a collision, i.e. the route planning system failed to provide a safe enough movement direction. Clearly, the entrance in the safety zone introduces a varying degree of danger, with the highest being an impact by moving on the same grid cell. This could be thought as a hazard function (severity inr t+1=r t*AI+ε(4)the figure). We used a scheme where we assigned 10 ‘danger’ units per cell crossed in the safety zone. For example, assume a radius of 6 cells in every direction and another moving object having entered two cells inside the boundary, i.e. four cells away from our agent, then a value of 20 units was assigned.Fig. 3. Simulation results.The results that are presented in figure 3 show that the predictive agent performed better than the dummy one, and the attentive one better than the predictive one. This observation was confirmed for varying sizes of the safety zone, training time for online model fitting, learning rates (in the case of the predictive agent) and number of training epochs. We used a fixed number (per experiment) of training epochs, typically 150, for updating the motion models. This procedure is equivalent to early stopping so as to avoid over fitting problems. No cross validation or similar approaches were used, as this simulation was intended to study expected “online” performance where not all necessary computational resources are assumed to be available. We used a batch version of the standard gradient descent back-propagation algorithm for this “online” training.V. C ONCLUSIONS & DISCUSSIONThe simulation results seem to indicate the validity of our assumption that attentive control should speed up the learning of corrections in the motion models. This coupled with the fact that the attentive agent has also used a pure reflexive response when attention levels were high, thus discarding the normal route planning process, indicate that the attention-based framework is a natural way to integrate online learning with normal (i.e. automated) processing when no events are present.Clearly one can argue that a more sophisticated learning algorithm for the motion model, possibly with modulation of the learning rate parameter, can be applied so as to further increase the performance of the predictive agent. The point that is made here is that the goal-oriented attention-control framework is a natural way to integrate processing and learning aspects in run-time. The attentive type of agent is already a superset of the predictive agent and thus any performance increase in the latter will also benefit the former. In our framework, we do not make any explicit assumptions regarding the nature of the underlying prediction (motion) models. They can be implemented by using many approaches. The Kalman filter approach is a useful tool in many applications, but it is not applicable in systems that do not assume a linear observation function or linear evolution of the underlying dynamical system. In our example, one can express the equations of motion in a Kalman filter formulation, but what remains unclear is the fact if this is a suitable framework in order to model the goals and “intentions” of the other agents, which eventually lead to the lack of information so as to establish a mean path. In other words, it is not immediately clear if the underlying generating mechanism of goals / sub-goal structures follows a linear generation scheme / evolution.Inclusion of reinforcement type of learning is also possible. This would allow us to further increase the usefulness of the attentive agent by using multiple learning paradigms in an integrated way. These aspects and verification of the current results by using additional configurations and different experimental setups are the next steps to be followed. Variations of the modulating scheme of formula (4) will also be considered.There is much further work to be done to extend the system beyond the level of simulation described here. We have already mentioned the manner in which training should be extended, as well as consideration needed of the Goals module. The further extensions, already under consideration in the ORESTEIA attention agent project [6, 7, 8], are to develop more general control with greater flexibility still. This could be by using a multi-modal system, so that sensor information in a given modality can be properly assessed at a low level (level 3 in our above discussion) but then combined with other modalities at level 4. This requires careful discussion and development of fused state representatives as well as thehigher-level goal, forward and observed models as well as developing overall rules for the system. Even greater flexibility can be inserted by enabling the system to create its own goals and response rules, most efficiently by reward learning (the rewards arising form the environment), as considered earlier. We hope to develop, and report on, these aspects elsewhere.Closing this discussion we note the fact that it is possible to use this framework in order to decompose a task in a set of competing goal families; our global attention mode. Local attention control is present in the form of sensor and actuator control. What is not currently present is the implementation of a third mode of attention, which is related with the signal enhancement process, i.e. amplifying suitable features and discarding distracting ones. This can be considered essentially as a feature selection process and it will be integrated in the existing framework in a future stage.VI. A CKNOWLEDGMENTSThe work presented here was originated and developed during the EU IST ORESTEIA project (IST-2000-26091). We kindly acknowledge their support to our work.R EFERENCES[1] Miall R. and Walpert D. M. (1996). Forward models forphysiological motor control. Neural Networks 9, 1265-1279.[2] Rushworth M. F. S. et al (1997). The left parietal cortex and motorattention. Neuropsychologia 33, 1261-1273.[3] Taylor J. G. (2000). Attentional movement: the control basis forConsciousness. Soc. Neuroscience Abstracts 26, 2231, #893.3[4] Taylor J. G. (2001). Attention as a neural control system. Proc. Int.Joint Conf. Neural Networks, pp 262-276, IJCNN ’01.[5] Taylor J. G. (2003). Paying attention to Consciousness. Progress inNeurobiology 71:305-335[6] Kasderidis S. & Taylor J.G. (2003). Drawing attention to thedangerous. ICANN 2003 Conference, Istanbul, 27-29 June 2003, Springer.[7] Kasderidis S. & Taylor J.G. (2003). Attention-based Robot Control.KES 2003 Conference, Oxford, 10-12 September 2003, Springer. [8] Kasderidis S. & Taylor J.G. (2003). Attentional Agents and RobotControl. KES Journal, IOS Press, 2003. (submitted).。

2022—2023衡水中学下学期高三年级五调考试英语本试卷8页。

总分150分。

考试时间120分钟。

第一部分听力（共两节，满分30分）第一节（共5小题；每小题1.5分，满分7.5分）听下面5段对话。

每段对话后有一个小题，从题中所给的A、B、C三个选项中选出最佳选项。

听完每段对话后，你都有10秒钟的时间来回答有关小题和阅读下一小题。

每段对话仅读一遍。

1．When will Cathy start?A．At 6:00. B．At 6:10. C．At 10:00.2．How does the woman feel about her life?A．Bored. B．Worried. C．Tired.3．Where does the conversation most probably take place?A．In a food market. B．In a music concert. C．In a cafe.4．How much will the woman pay?A．$25．B．$30．C．$35．5．What's the possible relationship between the speakers?A．Workmates. B．Classmates. C．Teacher and student.第二节（共15小题；每小题1.5分，满分22.5分）听下面5段对话或独白。

每段对话或独白后有几个小题，从题中所给的A、B、C三个选项中选出最佳选项。

听每段对话或独白前，你将有时间阅读各个小题，每小题5秒钟；听完后，各小题将给出5秒钟的作答时间。

每段对话或独白读两遍。

听第6段材料，回答第6、7题。

6．What day is it today?A．Tuesday. B．Wednesday. C．Friday.7．Why is the man calling Maria?A．To tell her good news. B．To say goodbye to her.C．To invite her to go with him.听第7段材料，回答第8至10题。

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requirement purchasing arrangement 年度采购需求计划anticipatory positioning 预见性定位anti-pollution legislation 反污染立法anti-trust legislation 反托拉斯立法Apple Computers 苹果电脑area structure 地区结构aspiration/expectation level 渴望/期望水平aspirations of consumers 消费者渴望assurance 保证AT&T 美国电报公司ATM <automatic teller machine> 银行自动柜员机attitudes of consumers 消费者态度attributes 属性audiences 受众auto repair 汽车维修automation services 自动服务automobile industry 汽车产业autonomy 自主权availability 可获得性/供货能力avante guardian 前卫派Avon 雅芳awareness 〔产品知晓度/知名度Bbaby boomers 婴儿潮出生的一代人backward channels for recycling 回收的后向渠道backward integration 后向垂直一体化banner advertisements 横幅标语广告bar codes 条形码barter 实物交易basic physical needs 基本生理需要Bausch & Lomb 博士伦BCG Grow-Share Matrix 波士顿增长-份额矩阵before tests 事前测试Behavior Scan Information Resources Inc. 行为扫描信息源公司behavioural analysis 行为分析behavioural hierarchies 行为层级benchmarking 基准benefit clusters 利益群体benefits 利益Benz 奔驰billing 帐单biological revolution 生物革命birth rate 出生率blanket purchase order 一揽子采购合同blind-paired comparison testing 双盲比较测试Blockbusterblue collars 蓝领BMW 宝马Boeing 波音bottom line 底线/盈亏一览结算线brand awareness 品牌意识/认知brand extensions 品牌扩展brand loyalty 品牌忠诚度brand mark 品牌标志brand name 品牌名称brand positioning 品牌定位brand recognition 品牌识别brand strategies 品牌战略brand 品牌branding strategy 品牌化战略branding 品牌化brand's equity 品牌的价值break-even analysis 盈亏平衡分析break-even volume 盈亏平衡产量breath of product assortment 产品线的宽度breath or diversity of product lines 产品线的宽度或多样性bribery 贿赂British Airways 英国航空公司brokers 经纪人budgeting 预算bundle 捆绑Bureau of Census 人口统计局Burger King 汉堡王busines strength rating 商业能力评分business plan 商业计划business position 经营地位business sector 商业部门business services markets 商业服务市场business strategies 经营战略business unit strategy 经营单位战略Business Week 《商业周刊》buyback allowances 回购折让buyback arrangements 产品返销buyers' bargaining power 买方的讨价还价能力buyers 采购者buying behavior 购买行为buying center 采购中心buying inertia 购买惯性buying intention 购买意图buying offices 连锁商店的进货中心buying power indes <BPI> 购买力指数buying situation 采购情况/类型buying task 采购任务Ccable TV 有线电视Cadillac 凯迪拉克Campbell's Soup 金宝汤业公司capital gains 资本收益capital invested in product 产品投入资本Carnival 嘉年华cash cows 现金牛类cash discounts 现金折扣catalogue sales 目录销售categorization of perception 感知分类categorization 分门别类Caterpillar Tractor 卡特皮勒公司Cathay Airlines 国泰航空公司CBS Records 唱片公司CBS 哥伦比亚广播公司centralization 集中化chameleons/followers 变色龙/跟随者channel alternatives 可选择的营销渠道channel conflicts 渠道冲突channel decisions 渠道决策channel functions 渠道功能channel institutions 渠道组织结构channel management 渠道管理channel objectives 渠道目标channel of distribution 分销渠道channel power 渠道权力channel-control strategies 渠道控制战略channel-design decisions 渠道设计决策channel-management decisions 渠道管理决策channels of communication 传播渠道Charles Snow 查尔斯·斯诺Cherokee 切诺基chevrolet 雪佛莱choice criteria 选择标准Christian Dior 克里斯汀·迪奥〔世界著名时装品牌Chrysler 克莱斯勒Citi Corp 花旗银行closing a sale 结束销售clothing retailers 服装零售商CNN 美国有线新闻网co-branding 联合品牌code of ethics 〔职业道德标准coercive power 强制权cognitive dissonance 认识的不协调Colgate-Palmolive 高露洁collection of data 数据收集collection 收款co-marketing alliances 联合营销联盟combination compensation plan 结合式薪酬方案Comdex 计算机展销会commercialization 商业化commitment 承诺communication channels 传播渠道communication process 传播过程communication 信息交流/沟通communications media 传播媒体company personnel 公司员工Compaq 康柏comparative advertisements 比较广告comparison of brands 品牌比较compensation deals 补偿处理compensation plan 酬金方案compensation/rewards 酬金/奖励compensatory 补偿性的competition and industry evolution 竞争和行业演变competition-orientated pricing 竞争导向定价法competitive advantage 竞争优势competitive <supply-side> evolution 竞争〔供方演变competitive factors 竞争因素competitive intelligence 竞争情报/信息competitive parity promotion budgeting 竞争均势促销预算法competitive strategy 竞争战略competitive strength 竞争优势/能力competitor analysis 竞争者分析complaint handling 投诉处理component materials and parts markets 组成材料和零部件市场computerized ordering 计算机化的订购conclusive research 确定性研究conditions of demand 需求情况conflict and resolution strategies 冲突和解决战略conformance to specifications 与规格一致conformance 一致性confrontation strategy 对抗战略conjoint measurement 联合测度法conjunctive model 联合模型consumer decision-making 消费者〔购买决策consumer goods channels 消费品分销渠道Consumer Goods Pricing Act, USA 美国消费品定价法案consumer goods 消费品consumer markets 消费品市场consumer needs 消费者需求consumer packaged-goods firms 消费者包装食品公司consumer promotion 消费者促销consumer tests 消费者测试consumer/household market 消费者/家庭市场consumers' perceptions 消费者感知consumption 消费contests 竞赛contingency planning 权变计划contract construction 契约建筑业contract manufacturing 契约制造业contraction/strategic withdrawal strategy 收缩/战略性撤退战略contractual entry modes 契约式进入模式contractual vertical marketing systems 合约式垂直营销系统contribution margin analysis 边际贡献〔贡献毛利分析contributrion margin 边际贡献control strategies 控制战略convenience food stores 便利食品商店convenience goods 便利品convenience 服务的便利性Cool Whip 清凉维普co-operative advertising 合作性广告co-ordination and conflict resolution 协调与冲突解决co-production 合作生产core benefit proposition <CBP> 核心利益方案/提议corollary-data method 推定数据法corporate HQ 公司总部corporate scope 公司〔经营围corporate strategy 公司战略corporate vertical marketing systems 公司式垂直营销系统corporate/institutional advertising 团体/社会公共机构广告corrective action 矫正行动cost analysis 成本分析cost effectiveness 成本有效性cost leadership strategy 成本领先战略cost of capital 资本成本cost of goods sold <COGS> 产品销售成本cost reductions 降低成本产品cost-and-volume relationship 成本-数量关系cost-oriented pricing 成本导向定价法cost-plus/mark-up pricing 成本加成/溢价定价法costs and benefits of marketing functions 营销职能的成本和效益costs of competitors 竞争者成本costs of distribution 分销成本countertrade 对等贸易coupons 优惠券courtesy 礼貌coverage of geographic market 地域性市场的围coverage of relevant retailers 相关零售商的销售围credibility 信誉credit terms 信贷条款critical assumptions 关键假设cross-elasticity 交叉弹性customary pricing 习惯性定价法customer analysis 顾客分析customer contact 顾客接触customer demand 顾客需求customer intimacy 顾客亲密度customer loyalty 顾客忠诚度customer need 顾客需要customer organization of sales force 按客户组织销售队伍customer retention 顾客维系/保留customer satisfaction 顾客满意度customer segment pricing 顾客细分市场定价customer service 顾客服务customer-oriented pricing 顾客导向定价法customers' perception 顾客感知customers' preferences 顾客偏好customers' price sensitivity 顾客的价格敏感度customizing 定制Ddata collection 数据收集data confidentiality 数据data research 数据研究data sources 数据来源dealers 经销商deceptive advertisements 欺骗性广告deciders 决策者declining markets 衰退市场decoding 解码defect rate 缺陷率defender strategy 防御型战略defensive new-product development strategy 防御性新产品开发战略defensive positioning 防御性定位delivery time 交付时间delivery 配送Dell Computers 戴尔计算机公司Delta Airlines 三角洲航空公司demand characteristics 需求特征demand curve 需求曲线demand-oriented pricing 需求导向定价法demographic environment 人口统计环境department stores 百货商店dependability 可靠性deregulation 放松管制derived demand 衍生需求descriptive research 描述性研究design decisions 设计决策desired percentage mark-up on retail 预期零售利润率desired percentage return 预期回报率determinant attributes 关键属性determinants 决定因素different responses 差别反应differentiated defender strategy 差异化防御战略differentiated marketing 差异化营销differentiation over time 不同时间的差异differentiation strategy 差异化战略differentiation 差异化diffusion of innovation theory 创新扩散理论dimension 因素dimensions of quality 质量维度direct costing profitability analysis 直接成本盈利性分析direct mail 直接邮寄direct marketing via advertising media 通过广告媒体的直接营销direct marketing 直接营销direct product profitability <DPP> 直接产品盈利性/利润率direct selling 直销discount rate 贴现率discount stores 折扣商店discount 折扣discount/premium price policies 折扣/溢价策略discriminant analysis 差异分析法discriminatory adjustments 歧视价格调整discriminatory pricing adjustments 歧视定价调整disjunctive model 分离模型display space 列空间disposable income 可支配收入dissonance-attribution hierarchy 不和谐-归属层次结构distribution channel designs 分销渠道设计distribution channel objectives 分销渠道的目标distribution channel 分销渠道distribution decisions 分销决策distribution policies 分销策略distribution 分销distributor/store <private lables> brands 分销商/私有品牌distributors 分销商diversification 多元化divest 撤退divest 出让divestment or liquidation 收回投资或清算dividend 红利dogs 瘦狗类domestic target marketing strategies 国目标市场定位的营销战略dropping products 放弃产品dry cleaning 干洗dual/two channel distribution systems 双重分销系统duplication 〔媒体重复DuPont 杜邦公司durability 耐用性Eearly vs late adoption 早期采购与后期采购earnings per share 每股收益economic and technological factors 经济技术因素economic power 经济权economies of scale 规模经济education services 教育服务effectiveness 有效性efficiency 效率Electrolux 伊莱克斯emergency goods 急需品Emerson Electric 爱默生电气emotional appeals 情感诉求empathy 移情作用empirical evidence 经验性实例empowerment 授权encoding 编码end use 最终使用endorsement 赞同engineering 〔产品工程设计entrepreneurial strategy 企业家战略entry strategies 进入战略environment and packaging disposal 环境与包装处理environment factors 环境因素environmental scanning 环境扫描/分析environmental strategy 环境战略establishment 机构ethical audit 〔公司伦理审计ethics of marketing 营销伦理道德ethnic composition 种族构成European Community 欧共体evaluation and reward systems 评估与奖励体系evaluation and selection of supplier 评估和选择供应商evaluation of alternatives 评估替代品/各种选择evaluation of brands 品牌评估event sponsorship 事件赞助event 活动everyday low-price <EDLP> 天天低价evoked set 引发的组合evolution of market 市场演变exchange 交换exclusive dealing 独家销售exclusive distribution 独家分销executive summary 执行摘要exhibition media 展示广告媒体existing market 现有市场exit barriers 退出壁垒expansion path 扩途径expectation measures 〔顾客预期测度expectations of customers 顾客期望expected unit sales 预计产量expected value 期望价值experience curve 经验曲线experimental research 实验性研究expert power 专长权exploratory research 探索性研究export agents 出口代理〔商export jobbers 出口批发商export management company 出口管理公司export merchants 出口贸易商export 出口exporting 出口商品extended use strategy 扩大使用战略extending volume growth 扩大市场份额external data sources 外部数据来源external environment 外部环境extrapolation of past sales trends 过去销售趋势推测法Ffacilitating agencies 辅助/中介机构factor analysis 因素分析法fads 时尚family branding 家族品牌family life cycle 家庭生命周期family structure 家庭结构farm products 农产品fast-moving consumer goods <FMCG> 快速变动的消费品fear appeals 恐惧/顾虑诉求features 特征Federal Department Stores 联邦百货商店Federal Trade Code 〔FTC> 联邦贸易法案FedEx <Federal Express> 联邦快递feedback data 反馈数据field test marketing 实地市场测试financing 融资fisheries 渔业fit and finish 结实度与外观fixed costs 固定成本fixed salary 固定工资flanker strategy 侧翼进攻战略flanker/fighting brand 战斗品牌flanking and encirclement strategies 侧翼进攻与围堵战略flat organizational structure 扁平的组织结构FOB origin pricing FOB产地定价法focus strategy 集中战略followers 追随者Ford 福特公司foreign middlemen 国外中间商forestry 林业formalization 形式/规化formulate 制定fortress/position-defence strategy 防御堡垒战略Fortune 《财富》杂志forward integration 向前一体化franchise systems 特许系统franchising 特许经营free call numbers 免费free goods 免费商品freight-absorption pricing 免收运费定价法fringe benefits 小额津贴frontal attack strategy 正面进攻战略full costing profitability analysis 全成本盈利性分析full-service wholesalers 全方位服务的批发商functional competencies and resource allocation职能能力与资源分配functional efficiency 职能效率functional organization of sales force 按销售职能组织销售队伍functional organizational structure 职能型组织结构functional performance 功能性能functional strategy 职能战略Ggames 比赛gap 差距gatekeepers 信息传递者general behavioral descriptors 一般行为变量General Electric <GE> 通用电气General Foods Corporation 通用食品general merchandise discount chains 大众商品折扣连锁店General Motors 通用汽车geodemographics 区域人口统计特征geographic adjustments 地理调整geographic distribution 地理分布geographical organization of sales force 按地区组织销售队伍Gillette 吉列剔须刀global adjustments 全球调整global elite consumer segment 全球精英消费品市场global expansion 全球扩global marketing control 全球营销控制global markets 全球市场global niche strategy 全球机会战略global standardization strategy 全球标准化战略global teenage segment 全球青少年市场globalization 全球化global-market expansion 全球市场扩goals 总目标going-rate/competitive parity pricing 竞争性平价定价法goods producers 产品制造商Goodyear 固特异轮胎government agencies 政府机构government buyers 政府采购者government market 政府市场government regulation 政府管制greenhouse effect 温室效应grey market 灰色市场gross domestic product <GDP> 国生产总值gross margin 毛利gross national product <GNP> 国民生产总值gross profit 毛利gross rating points <GRPs> 总级别指数group/category product manager 类别产品经理growing markets 成长市场growth rate of market 市场增长率growth stage of product life cycle 产品生命周期的成长阶段growth-extension strategies 增长扩战略growth-market strategies for market leaders 市场领导者的市场增长战略growth-market strategy 成长性市场战略growth-market targeting strategy 成长性市场定位战略guarantee/warranty 保证/担保guarantees 保证Gucci 古琦〔世界著名时装品牌HHaagen-Dazs 哈根达斯hard technology 硬技术Harvard Business Review 《哈佛商业评论》harvest 收获harvesting pricing 收获定价法harvesting strategy 收获战略health care 医疗保健health maintenance organizations <HMOs> 〔美国卫生保健组织heavy buyer 大客户Heileman Brewing CompanyHeinz 亨氏食品helpfulness 有益性Henkel 汉高Hertz 赫兹〔美国汽车租赁巨头Hewlett-Packard 惠普公司hierarchy of strategy 战略的层次high margin/low-turnover retailers 高利润/低周转率的零售商high market share global strategy 高市场份额全球战略high-contact service system 高接触服务系统high-involvement product 高参与产品high-involvement purchase 高参与购买hight market share 高市场份额战略Hilton 希尔顿Holiday Inns 假日旅馆homogeneous market 同质市场Honda 本田household/family life cycle 家庭生命周期household 家庭hybrid technology 混合技术IIBM 国际商用机器idea generation 创意的产生/生成ideas for new products 新产品创意/构想idea-screening process 创意筛选过程identification of segments 识别细分市场Illinois Tool Works 伊利诺斯工具厂image pricing 形象定价imitative positioning 模仿定位imitative strategy 模仿战略impact evaluation 影响评估impersonal sources 非个人的信息来源implementation and control of marketing programs营销计划的执行和控制implementation 实施improvements in or revisions of existing products现有产品的改良或修正impulse buying 冲动购买impulse goods 冲动购买品incentives 激励income 收入increased penetration strategy 增加渗透战略indirect costing profitability analysis 间接成本盈利性分析individual brand 个别品牌individual value 个人价值industrial goods & services 工业产品和服务industrial goods channels 工业品分销渠道industry attractiveness 行业吸引力industry attractiveness-business position matrix行业吸引力-业务地位矩阵industry dynamics 产业动态industry evaluation 产业评估industry evolution 产业演变inelastic 缺乏价格弹性influencers 影响者infocommunications industry 信息通信行业infomercials 商业信息广告information age 信息时代information search 信息搜集information technology 信息技术information 信息informative 告知性的ingredient 成份in-home personal interview 个人家庭访谈in-house use tests 部使用测试innovation 创新innovativeness 创新性installation 设施in-store display 店展示in-store positioning 店布局in-store promotion 店促销intangibles 无形integrated marketing communication plan <IMC> 整合营销传播计划integration of perception 感知整合integration 整合Intel 因特尔intensity of market position 市场地位的集中程度intensity 集中程度intensive distribution 密集型分销interactions across multiple target markets 多目标市场间的相互作用interactive media 交互式媒体interest rates 利率internal data sources 部数据来源internal marketing 部营销internal organizational structure 部组织结构international advertising 国际广告international channels 国际分销渠道international division 国际分部international marketing 国际营销international organizational design 国际组织设计internationalization of services 服务的国际化introductory stage of product life cycle 产品生命周期的推出阶段inventory level 库存水平investor relations advertising 投资关系广告issue advertising 观点广告JJaquar 美洲豹Jell-O 吉露jobbers 批发商Johnson & Johnson 强生joint ventures 合资jury of executive opinion 行政管理人员群体意见法just noticeable difference <JND> 恰巧注意到的差异just-in-time <JIT> management system 准时制管理体系just-in-time purchasing arrangements 及时采购安排KKao 花王Keiritsu 凯莱通Kellogg 凯洛格公司Kentucky Fried Chicken <KFC> 肯德基key account management 主要客户管理key accounts 关键客户key benefits 核心利益key environmental issue identification 确定主要的环境问题key variables 关键变量key/house accounts 关键/机构客户Kmart 凯玛特Kodak 柯达Komatsu 小松公司Kraft 卡芙Llaboratory tests 实验室测试leapfrog strategy 蛙跳战略learning hierarchy 学习层级结构legal services 法律服务legislation 立法legitimate power 法定权level of compensation 酬金水平level of technical sophistication 技术的复杂程度Levi Strauss 维·史特劳斯Levi's 列维斯〔全球最大的牛仔服制造商lexicographic model 词典编纂模型lifestyle 生活方式limited-service wholesalers 有限服务的批发商line extension 产品线扩展line filling 产品线填充line stretching 产品线延伸list price 订价Lloyd's of London 伦敦劳埃德保险公司localizaiton strategy 本地化战略location pricing 场所定价location 位置lodging 房屋出租logistical alliances 后勤联盟long-term memory 长期记忆lost customer 失去的顾客Louis Vuitton 路易·威登〔法国著名时尚品牌low-contact service system 低接触服务系统low-cost defender 低成本防御型low-cost position 低成本地位low-involvement hierarchy 低参与程度层级结构Lucent Technologies 朗讯科技Mmacro risks 宏观风险macroenvironment 宏观环境macrosegmentation 宏观细分mail-order retailers 邮购零售商maintaining market share 保持市场份额maintenance strategy 保持战略management overhead 管理费mandatory adaptation 强制性适应manufacturer brand 制造商/全国性品牌manufacturers' agents/representatives 生产商的代理商/销售代表manufacturers' export agents <MEA> 制造商出口代理manufacturers' sales offices/branches 生产商的销售办事处/分支机构manufacturing process 制造过程manufacturing 制造业market aggregation strategy 整体市场战略market attractiveness factors 市场吸引力因素market attractiveness 市场吸引力market attractiveness/business position matrix 市场吸引力/业务地位矩阵market circumstances 市场环境market demorgraphics 市场人口分布/统计特征market dimension 市场量度market entry strategies 市场进入战略market exclusion 市场排斥market expansion strategy 市场扩战略market factors 市场因素market followers 市场跟随者market growth rate 市场增长率market hirarchy 市场等级market inclusion 市场纳入market leaders 市场领导者market measurement 市场测量market opportunity analysis 市场机会分析market oriented 以市场为导向的market position factors 市场地位因素market positioning analysis 市场定位分析market potential measurements 市场潜力测度market research 市场研究market segment 细分市场market segmentation 市场细分market share 市场份额market targeting 目标市场选择market 市场marketability 市场开拓能力market-entry strategies 市场进入战略marketing action plan 营销行动计划marketing audit 营销审计marketing channel 营销渠道marketing codes of conduct 营销行为规marketing communication 营销沟通/传播marketing concept 营销观念marketing control 营销控制marketing decision support systems <MDSS> 营销决策支持系统marketing environment audit 营销环境审计marketing flows and functions 营销过程和职能marketing function area audit 营销功能领域的审计marketing implications of 对营销的影响marketing information system 营销信息系统marketing institutions 营销机构marketing management 营销管理marketing message 营销信息marketing mix 营销组合marketing policy 营销策略marketing productivity area audit 营销生产力领域的审计marketing program components 营销计划容marketing program 营销计划/方案marketing relationship 营销关系marketing research 营销研究marketing strategy 营销战略market-management organizational structure 市场管理组织结构mark-up price 产品/溢价价格Marlboro 万宝路Marriott Hotel 万豪酒店mass-market penetration strategy 大规模市场渗透战略mass-market strategy 大市场战略matrix organizational structure 矩阵组织结构Matsu****a 日本松下电子mature conformists 成熟的随大流者mature markets 成熟市场mature stage of product life cycle 产品生命周期的成熟阶段McDonald's 麦当劳McDonnell Douglas 麦道公司MCI电讯公司〔前世界通信公司MDSS <Marketing-Decision Support System> 市场决策支持系统measurability 可测度性measure or index 测量指标measurement criteria 计量标准media audiences 媒体受众medical and health services 医疗卫生服务Medico Containm''ent Servicesmemory of consumers 消费者记忆Mercedes-Benz 梅赛德斯-奔驰Mercer Management Consulting 美国美智管理顾问公司merchandising 推销merchant middlemen 国贸易中间商merchant wholesalers 商业批发商message structure 信息结构Michael Porter 迈克尔-波特micro risks 微观风险microsegmentatioin 微观细分Miller Tyding ACT, USA 米勒·泰丁法案minging 矿业Minnesota Mining and Manufacturing Company <3M>明尼达矿业和制造公司Minolta 美能达miscellaneous sources 多方面来源mission 宗旨missionary selling 推销式销售Mitsubishi Heavy Industries 三菱重工modified rebuy 调整再购monosegment positioning 单一细分市场定位Monsanto 孟山都农业生物技术公司moral appeals 伦理/道德诉求morals 道德Motorola 摩托罗拉multichannel distribution 多渠道分销multidimensional scaling 多维等级法multilevel selling 多级销售multinational coporations <MNCs> 跨国公司multiple test markets 多测试市场multiple-brand strategy 多品牌战略multiple-factor index 多因素指数法multisegment positioning 多重细分市场定位mutual trust 相互信任NNabisco Biscuit 纳贝斯克饼干公司national account management 全国性客户管理national market 国市场National Semiconductor 美国国家半导体公司natural products 天然产品NEC 日本电子Nescafé雀巢咖啡Nestlé雀巢net sales 净销售额network computer <NC> 网络计算机new business selling 新业务销售new buy 购入新产品new entrants 新进入者new markets 新市场new materials 新材料New Prod screening model 新普罗德筛选模型new product lines 新产品线new products 新产品new-product development 新产品开发new-product ideas 新产品创意Newsweek 《新闻周刊》new-task buying 全新采购new-to-the-world products 世界性新产品niche penetration strategy 壁龛/机会市场渗透战略niche-market strategy 壁龛市场战略Nike 耐克Nissan 尼桑no-brand brand name 无品牌的品牌名称no-frills product 无虚饰产品noise in communication system 传播系统中的噪音non-financial rewards 非物质性奖励措施non-probability sampling 非概率抽样non-profit organization 非盈利组织non-store retailing 无店铺零售业number of stockouts 迟滞数目Oobject-and-task method of promotion budgeting 目标-任务促销预算法objectives and strategy area audit 目标与战略领域的审计objectives 具体目标observation 观察法occupancy costs 房屋占用成本occupation/position 职业/职位odd pricing 奇/余数定价法OEM <original equipment manufacturer> 原始设备制造商oeverall quality 总体质量off-invoice discounts 发票之外的折扣offsets 抵消交易Omega 欧米加on-air testing 广播测试OPEC <Organization of Petroleum Exporting Countries>欧佩克〔石油输出国组织opening relationships 建立关系operating supplies 生产供应品operational excellence 运作管理水平opinion leaders 意见领导者opportunity cost 机会成本opportunity identification 机会识别opportunity/threat matrix 机会/威胁矩阵order cycle time 订货周期order processing 订单处理organisational level 组织层次organizaitonal requirement planning 组织需求计划organization area audit 组织领域的审计organization buying center 组织采购中心organizational customer 组织顾客organizational direct selling 组织直销organizational markets 组织市场organizational purchasing 组织采购organzational structure 组织结构outdoor enthusiasts 户外运动爱好者out-of-home media 户外广告媒体overall cost leadership 全面成本领先overheads 日常开支overseas direct investment 海外直接投资ownership of new product 新产品所有权PPacific Electric 太平洋电气packaging 包装panel of experts 专家小组parentage 渊源parties involved 交换中的各方payment terms 支付条款pay-off control 支出控制penetration pricing 渗透定价Pepsi-Cola 百事可乐perceived customer value 顾客感知价值perceived quality 感知到的质量perceived value 感知到的价值percentage of sales promotion budgeting method销售额百分比促销预算法perceptions of consumers 消费者感知/理解perceptual <product> pisitioning 感知〔产品定位perceptual map 感知图perceptual organization 感知组织perceptual vigilance 感性的警惕performance dimension 业绩标准performance evaluation 业绩评估performance measures 表现/业绩测度performance objective 绩效目标performance standards 绩效标准performance 功能perishability 非持久性personal selling 人员推销personal sources 个人的信息来源personnel development 人力资源开发persuasive 说服性的pharmaceuticals industry 医药行业physical <product> positioning 物理〔产品定位physical descriptors 物理变量physical distribution 实物分销Pillsbury 皮尔斯博瑞pioneers 先入者Pizza Hut 必胜客place utility 地点效用planning and control system area audit 计划与控制系统领域的审计point of sale information 销售点信息point-of-purhcase <POP> promotion 采购点促销point-of-sales <POS> data 销售点数据pontificator 保守派popularity 通用性population trends 人口趋势portfolio models for resource allocation 资源配置的资产组合模式position intensity 地位集中程度positioning 定位possession utility 拥有效用post-purchase dissonance 购买后的不协调post-purchase evaluation 购买后评估post-purchase/after-sale service 售后服务potential advantages 潜在优势potential customer 潜在顾客potential market 潜在市场potential target market 潜在目标市场power in distribution 分销权力power of buyers 购买者能力power of suppliers 供应商能力predatory pricing 掠夺性定价法pre-empting scarce resources 先占稀缺资源preferential treatment 特惠待遇premiums 额外奖励present competitors 现有的竞争者presenting sales message 提供销售信息pre-test market research 测试前市场研究price discrimination 价格歧视price elasticity of demand 需求的价格弹性price fixing 价格设定price leaders 价格领导者price lining 价格排列定价法price promotion 价格促销price quotation 报价price sensitivity 价格敏感度price structure 价格结构price 价格price/earnings ration 价格/收益比price-off promotions 降价促销price-setting process 定价过程pricing adjustments 定价调整pricing policies 价格策略pricing 定价primary demand 基本需求primary sources 第一类/主要数据print media 印刷媒体private/for-profit organization 私营/盈利性组织PRIZM <Potential Rating Index for Zip Markets>按邮政区划为基础的潜力等级指数proactive new-product development strategy 进取型新产品开发战略probability sampling 概率抽样problem formulation 界定问题problem identificatioin 确定问题process management 过程管理Procter & Gamble <P&G> 宝洁公司product line 产品线product availability 产品的可获得性product category 产品类别product class 产品类别product decisions 产品决策product design 产品设计product development 产品开发product dimension or attributes 产品维度/属性product evolution 产品演变product features 产品特征product intent share 产品倾向份额product leadership 产品领导能力product life cycle <PLC> 产品生命周期product life cycle curve 产品生命周期曲线product line 产品线product manager audit 产品经理审计product offering 供应品product organizaiton of salesforce 按产品组织销售队伍product policies 产品策略product positioning 产品定位product quality 产品质量product scope 产品围product space 产品位置product specifications 产品规格product systems 产品体系product type 产品类型product usage 产品用途product 产品product<ion>-oriented organization 产品/生产导向型组织production 生产product-line pricing adjustments 产品线定价调整product-management organizational structure 产品管理组织结构product-market entry control 产品－市场进入控制product-related behavioral descriptors 与产品相关的行为变量product's market characteristics 产品的市场特征product-use testing 产品使用测试pro-environment 环保profit impact of market strategy <PIMS> 市场战略的利润影响profitability analysis 盈利性分析profitability 盈利性/盈利能力profitable survivor strategy 有利可图的生存者战略project-company resource compatibility 项目与公司资源的协调性projected profit-and-loss statement 预计损益表projective tests 投影测试promotion decisions 促销决策promotion mix 促销组合promotion policies 促销策略promotion 促销promotional allowance 促销折让promotional effort 促销努力promotional pricing 促销定价promptness 及时性propector strategy 探索型战略prospecting for customers 寻找顾客psychographics 心理统计特征psychological cost 心理成本psychological pricing 心理定价法public organization 公共组织public relations 公共关系public utilities 公共设施publicity 公共宣传pull strategy for control of distribution channels分销渠道控制的拉式战略pupil dilation 瞳孔扩purchase predisposition 购买倾向purchasing agent 采购代理purchasing contract 采购合同purchasing manager/agent 采购经理／代理purchasing power perity <PPP> 购买力平价指数push money/spiffs 佣金push stragtegy for control of distribution channels分销渠道控制的推式战略Qqualifying prospects 审查潜在顾客资格quality dimensions 质量维度quality 质量quantity discount 数量折扣question marks 问题类questioning 询问法quotas 定额R。

什么是社会感知计算随着嵌入式设备、无线传感网络、移动计算等技术的快速发展，集成感知、计算和通信能力的普适智能系统已经逐步融入到人类的日常生活中。

普适计算技术，确切地说是传感技术和情境感知（Conte x t Aware）技术，以前所未有的方式增强了人们收集、分析和利用数据的广度和深度。

生活在由通信网、互联网、传感网等相互融合所形成的混合网络环境中的人类，留下的数字足迹汇聚成为一幅复杂的个体和群体行为图景，这些图景对于理解并支持人类的社会活动[1]具有重要的帮助作用。

2005年美国MIT科学家亚历克斯·彭特兰（Ale x Pentland）在IEEE Computer杂志上发表了题为“So-cially Aware Computation and Communication”的论文[2]，首次提出了社会感知计算的思想。

文章通过对人际交往中的社会情境（Social Conte x t），如说话声调、面部动作和姿势进行量化，并以可视化呈现，以此促进人们的社会交往。

2009年2月彭特兰和哈佛科学家大卫·拉泽（David Lazer）等在美国《科学》杂志（Science）上撰文阐述了通过收集和分析海量现实生活数据流理解个体、组织和社会[1]，其思路和目标与社会感知计算不一而同，但是更侧重于计算和分析。

迄今社会感知计算已经得到学术界的广泛关注，并研究开发出一些系统和应用，但还没有统一明确的定义。

我们在此给出一般性定义。

社会感知计算（Socially Aware Computing）是通过人类社会生活空间日渐部署的大规模多种类传感设备，实时感知识别社会个体的行为，分析挖掘群体社会交互特征和规律，辅助个体社会行为，支持社群的互动、沟通和协作，从而高效地支持社会目标的实现。

社会感知计算的核心在于“感知”二字，有两层涵义，首先感知物理世界（Sensing），然后觉察并做出响应（Aware）。

与基于单一万维网数据或用户调查数据的社会计算（Social Computing）[3]或社会网络分析（Social Network Analysis）[4]不同，社会感知计算强调利用先进计算机科学技术感知现实世界个体行为和群体交互，理解人类社会活动模式，并为个体和群体交互提供智能辅助和支持。

英文论文投稿信Cover?letter模板qiusuo BY - 2006-1-17 8:59:00Dear Editor,We would like to submit the enclosed manuscript entitled "GDNF Acutely Modulates Neuronal Excitability and A-type Potassium Channels in Midbrain Dopaminergic Neurons", which we wish to be considered for publication in Nature Neuroscience.GDNF has long been thought to be a potent neurotrophic factor for the survival of midbrain dopaminergic neurons, which are degenerated in Parkinson’s disease. In this paper, we report an unexpected, acute effect of GDNF on A-type potassium channels, leading to a potentiation of neuronal excitability, in the dopaminergic neurons in culture as well as in adult brain slices. Further, we show that GDNF regulates the K+ channels through a mechanism that involves activation of MAP kinase. Thus, this study has revealed, for the first time, an acute modulation of ion channels by GDNF. Our findings challenge the classic view of GDNF as a long-term survival factor for midbrain dopaminergic neurons, and suggest that the normal function of GDNF is to regulate neuronal excitability, and consequently dopamine release. These results may also have implications in the treatment of Parkinson’s disease.Due to a direct competition and conflict of interest, we request that Drs. XXX of Harvard Univ., and YY of Yale Univ. not be considered as reviewers. With thanks for your consideration, I amSincerely yours,case2Dear Editor,We would like to submit the enclosed manuscript entitled "Ca2+-binding protein frequenin mediates GDNF-induced potentiation of Ca2+ channels and transmitter release", which we wish to be considered for publication in Neuron.We believe that two aspects of this manuscript will make it interesting to general readers of Neuron. First, we report that GDNF has a long-term regulatory effect on neurotransmitter release at the neuromuscular synapses. This provides the first physiological evidence for a role of this new family of neurotrophic factors in functional synaptic transmission. Second, we show that the GDNF effect is mediated by enhancing the expression of the Ca2+-binding protein frequenin. Further, GDNF and frequenin facilitate synaptic transmission by enhancing Ca2+ channel activity, leading to an enhancement of Ca2+ influx. Thus, this study has identified, for the first time, a molecular target that mediates the long-term, synaptic action of a neurotrophic factor. Our findings may also have general implications in the cell biology of neurotransmitter release.[0630][投稿写作]某杂志给出的标准Sample Cover Letter[the example used is the IJEB]Case 3Sample Cover Letter[the example used is the IJEB]Dear Editor of the [please type in journal title or acronym]:Enclosed is a paper, entitled "Mobile Agents for Network Management." Please accept it as a candidate for publication in the [journal title]. Below are our responses to your submission requirements.1. Title and the central theme of the article.Paper title: "Mobile Agents for Network Management." This study reviews the concepts of mobile agents and distributed network management system. It proposes a mobile agent-based implementation framework and creates a prototype system to demonstrate the superior performance of a mobile agent-based network over the conventional client-server architecture in a large network environment.2. Which subject/theme of the Journal the material fitsNew enabling technologies (if no matching subject/theme, enter 'Subject highly related to [subject of journal] but not listed by [please type in journal title or acronym])3. Why the material is important in its field and why the material should be published in [please type in journal title or acronym]The necessity of having an effective computer network is rapidly growing alongside the implementation of information technology. Finding an appropriate network management system has become increasingly important today's distributed environment. However, the conventional centralized architecture, which routinely requests the status information of local units by the central server, is not sufficient to manage the growing requests. Recently, a new framework that uses mobileagent technology to assist the distributed management has emerged. The mobile agent reduces network traffic, distributes management tasks, and improves operational performance. Given today's bandwidth demand over the Internet, it is important for the [journal title/acronym] readers to understand this technology and its benefits. This study gives a real-life example of how to use mobile agents for distributed network management. It is the first in the literature that reports the analysis of network performance based on an operational prototype of mobile agent-based distributednetwork. We strongly believe the contribution of this study warrants its publication in the [journaltitle/acronym].4. Names, addresses, and email addresses of four expert referees.Prof. Dr. William GatesChair Professor of Information Technology321 Johnson HallPremier University Lancaster, NY 00012-6666, USAphone: +1-888-888-8888 - fax: +1-888-888-8886 e-mail:Expertise: published a related paper ("TCP/IP and OSI: Four Strategies for Interconnection") in CACM, 38(3), pp. 188-198.Relationship: I met Dr. Gate only once at a conference in 1999. I didn't know him personally. Assoc Prof. Dr. John AdamsDirector of Network Research CenterCollege of Business Australian University123, Harbor Drive Sydney,Australia 56789phone: +61-8-8888-8888 - fax: +61-8-8888-8886e-mail:Expertise: published a related paper ("Creating Mobile Agents") in IEEE TOSE, 18(8), pp. 88-98. Relationship: None. I have never met Dr. Adams.Assoc Prof. Dr. Chia-Ho ChenChair of MIS DepartmentCollege of ManagementOpen University888, Putong RoadKeelung, Taiwan 100phone: +886-2-8888-8888 - fax: +886-2-8888-8886e-mail:Expertise: published a related paper ("Network Management for E-Commerce") in IJ Electronic Business, 1(4), pp. 18-28.Relationship: Former professor, dissertation chairman.Mr. Frank YoungPartner, ABC Consulting888, Seashore HighwayWon Kok, KowloonHong Kongphone: +852-8888-8888 - fax: +852-8888-8886e-mail:Expertise: Mr. Young provides consulting services extensively to his clients regarding network management practices.Relationship: I have worked with Mr. Young in several consulting projects in the past three years.Finally, this paper is our original unpublished work and it has not been submitted to any other journal for reviews.Sincerely,Johnny SmithCase 1Dear Editor,We would like to submit the enclosed manuscript entitled "GDNF Acutely Modulates Neuronal Excitability and A-type Potassium Channels in Midbrain Dopaminergic Neurons", which we wish to be considered for publication in Nature Neuroscience.GDNF has long been thought to be a potent neurotrophic factor for the survival of midbrain dopaminergic neurons, which are degenerated in Parkinson’s disease. In this paper, we report an unexpected, acute effect of GDNF on A-type potassium channels, leading to a potentiation of neuronal excitability, in the dopaminergic neurons in culture as well as in adult brain slices. Further, we show that GDNF regulates the K+ channels through a mechanism that involves activation of MAP kinase. Thus, this study has revealed, for the first time, an acute modulation of ion channels by GDNF. Our findings challenge the classic view of GDNF as a long-term survival factor for midbrain dopaminergic neurons, and suggest that the normal function of GDNF is to regulate neuronal excitability, and consequently dopamine release. These results may also have implications in the treatment of Parkinson’s disease.Due to a direct competition and conflict of interest, we request that Drs. XXX of Harvard Univ., and YY of Yale Univ. not be considered as reviewers. With thanks for your consideration, I amSincerely yours,case2Dear Editor,We would like to submit the enclosed manuscript entitled "Ca2+-binding protein frequenin mediates GDNF-induced potentiation of Ca2+ channels and transmitter release", which we wish to be considered for publication in Neuron.We believe that two aspects of this manuscript will make it interesting to general readers of Neuron. First, we report that GDNF has a long-term regulatory effect on neurotransmitter release at the neuromuscular synapses. This provides the first physiological evidence for a role of this new family of neurotrophic factors in functional synaptic transmission. Second, we show that the GDNF effect is mediated by enhancing the expression of the Ca2+-binding protein frequenin. Further, GDNF and frequenin facilitate synaptic transmission by enhancing Ca2+ channel activity, leading to an enhancement of Ca2+ influx. Thus, this study has identified, for the first time, a molecular target that mediates the long-term, synaptic action of a neurotrophic factor. Our findings may also have general implications in the cell biology ofneurotransmitter release.[0630][投稿写作]某杂志给出的标准Sample Cover Letter[the example used is the IJEB]Case 3Sample Cover Letter[the example used is the IJEB]Dear Editor of the [please type in journal title or acronym]:Enclosed is a paper, entitled "Mobile Agents for Network Management." Please accept it as a candidate for publication in the [journal title]. Below are our responses to your submission requirements.1. Title and the central theme of the article.Paper title: "Mobile Agents for Network Management." This study reviews the concepts of mobile agents and distributed network management system. It proposes a mobile agent-based implementation framework and creates a prototype system to demonstrate the superior performance of a mobile agent-based network over the conventional client-server architecture in a large network environment.2. Which subject/theme of the Journal the material fitsNew enabling technologies (if no matching subject/theme, enter 'Subject highly related to [subject of journal] but not listed by [please type in journal title or acronym])3. Why the material is important in its field and why the material should be published in [please type in journal title or acronym]The necessity of having an effective computer network is rapidly growing alongside the implementation of information technology. Finding an appropriate network management systemhas become increasingly important today's distributed environment. However, the conventional centralized architecture, which routinely requests the status information of local units by the central server, is not sufficient to manage the growing requests. Recently, a new framework that uses mobileagent technology to assist the distributed management has emerged. The mobile agent reduces network traffic, distributes management tasks, and improves operational performance. Given today's bandwidth demand over the Internet, it is important for the [journal title/acronym] readersto understand this technology and its benefits. This study gives a real-life example of how to use mobile agents for distributed network management. It is the first in the literature that reports the analysis of network performance based on an operational prototype of mobile agent-based distributednetwork. We strongly believe the contribution of this study warrants its publication in the [journal title/acronym].4. Names, addresses, and email addresses of four expert referees.Prof. Dr. William GatesChair Professor of Information Technology321 Johnson HallPremier University Lancaster, NY 00012-6666, USAphone: +1-888-888-8888 - fax: +1-888-888-8886 e-mail:Expertise: published a related paper ("TCP/IP and OSI: Four Strategies for Interconnection") in CACM, 38(3), pp. 188-198.Relationship: I met Dr. Gate only once at a conference in 1999. I didn't know him personally. Assoc Prof. Dr. John AdamsDirector of Network Research CenterCollege of Business Australian University123, Harbor Drive Sydney,Australia 56789phone: +61-8-8888-8888 - fax: +61-8-8888-8886e-mail:Expertise: published a related paper ("Creating Mobile Agents") in IEEE TOSE, 18(8), pp. 88-98.Relationship: None. I have never met Dr. Adams.Assoc Prof. Dr. Chia-Ho ChenChair of MIS DepartmentCollege of ManagementOpen University888, Putong RoadKeelung, T aiwan 100phone: +886-2-8888-8888 - fax: +886-2-8888-8886e-mail:Expertise: published a related paper ("Network Management for E-Commerce") in IJ Electronic Business, 1(4), pp. 18-28.Relationship: Former professor, dissertation chairman.Mr. Frank YoungPartner, ABC Consulting888, Seashore HighwayWon Kok, KowloonHong Kongphone: +852-8888-8888 - fax: +852-8888-8886e-mail:Expertise: Mr. Young provides consulting services extensively to his clients regarding network management practices.Relationship: I have worked with Mr. Young in several consulting projects in the past three years.Finally, this paper is our original unpublished work and it has not been submitted to any other journal for reviews.Sincerely,。

Part I Listening Comprehension (25%) Section A (8x1=8)Directions: In this section, you will hear EIGHT short conversations. At the end of each conversation, a question will be asked about what was said. Both the conversation and the question will be spoken only once. After each question there will be a pause. During the pause, you must read the four choices marked A), B), C) and D), and decide which is the best answer Then mark the corresponding letter on the Answer Sheet with a single line through the centre.A) Jim. B) Anna. C) The woman. D) Bill.A) In the kitchen. B) In a restaurant. C) In a school. D)In a supermarket. A) playing basketball. B) playing soccer. C) swimming in the pool D) doing homework A) He's good at organizing parties. B) He's big and strong. like an athlete.C) He's fond of sports. D) He's rather funny.A) She has to be charming and good to chat with. B) She has to be sociable and easy to get along withC) She has to be pretty and quiet. D) She's got to have brains and beauty.6.A) Because he went to buy some medicine for his niece.B) Because he went to run with his niece.C) Because his sister visited him.D) Because he was running a fever.7.A) He thinks he has no other choice.B) He is not clear about the time.C) He realizes he is driving too fast.D) He is going to slow down.8.A) Both speakers were bored with movie.B) The man didn't think he would like the movie at first but later did.C)The man didn't like the movie but the woman did.D)The woman didn't like the movie but the man did.Section B (7x1=7)Directions: In this section, you will hear TWO long conversations. At the end of each conversation, you will hear some questions. Both the conversation and the questions will be spoken only once. After you hear a question, you must choose the best answer from the four choices marked A), B), C) and D). Then mark the corresponding letter on the Answer Sheet with a single line through the centre.Questions 9 to 11 are based on the conversation you have just heard.9A) Watching a film of the 1930s'.B) Searching for reference material.C) Writing a course book.D) Looking for a job in a movie studio.10A) It's a bit outdated.B) It's controversial.C) It's too broad to cope with.D) It's of little practical value.11.A) In the Reader's Guide to Periodical Literature.B) At the Reference Desk.C) In The New York Times.D)At the end of the online catalogue.Questions 12 to 15 are based on the conversation you have just heard.12.A) At eight o'clockB) At nine o'clockC)At ten o'clockD) At eleven o'clock13.A) He visits friendsB) He takes a napC) He goes to a movieD) does some exercises.14.A)He has lunch.B) He makes pancakes for himself.C) He visits friends.D) He watches sports on TV.15.A) He watches TV.B) He visits friends.C) He goes out for dinner.D) He goes to night clubs.Section C (10x1= 10)Directions: You will hear two passages. Each will be read TWICE Listen carefully and fill in the blanks with the information you get. from the recording. (注意:本部分请直接把答案写在主观答题纸上。

商务英语试题及答案一、选择题（每题2分，共20分）1. What is the most common method of payment in international trade?A. CashB. Letter of CreditC. ChequeD. Electronic transfer2. The term "FOB" in shipping refers to:A. Free on BoardB. Full of BoatC. For the BoardD. Freight on Board3. Which of the following is NOT a characteristic of a good business proposal?A. It is concise.B. It is persuasive.C. It is vague and lacks details.D. It is well-structured.4. In a business negotiation, what does "BATNA" stand for?A. Best Alternative to a Negotiated AgreementB. Bad Agreement To Negotiate AgreementC. Better Agreement To Negotiate AgreementD. Bad Alternative To Negotiate Agreement5. The acronym "B2B" stands for:A. Business to BusinessB. Business to ConsumerC. Business to GovernmentD. Business to Industry6. What is the purpose of a SWOT analysis in business?A. To identify strengths, weaknesses, opportunities, and threats.B. To evaluate the financial performance of a company.C. To determine the market share of a product.D. To analyze the competition in the industry.7. The term "due diligence" in business refers to:A. The process of verifying all facts and figures related to a business deal.B. The process of conducting a financial audit.C. The process of negotiating the terms of a contract.D. The process of closing a business deal.8. Which of the following is a common risk associated with international trade?A. Currency fluctuationB. High demand for the productC. Stable political environmentD. Low transportation costs9. The "4Ps" of marketing are:A. Product, Price, Promotion, PlaceB. Planning, Positioning, Promotion, PerformanceC. Product, Positioning, Price, PerformanceD. Planning, Price, Positioning, Place10. What is the role of a "middleman" in business transactions?A. To act as a mediator in negotiations.B. To provide financial services.C. To facilitate the exchange of goods between buyer and seller.D. To manufacture the goods.二、填空题（每题1分，共10分）11. The process of identifying potential customers and persuading them to buy a product or service is known as_______.12. In business, a _______ is a document that outlines the terms and conditions of a sale.13. A _______ is a type of insurance that covers the risk of loss or damage to goods during transportation.14. When a company offers a lower price to a customer in exchange for a larger order, this is known as a _______.15. The acronym "ROI" stands for _______.16. A _______ is a document that provides evidence of the ownership of goods or property.17. The term "blue ocean strategy" refers to creating a_______ in the market by developing new products or services that have no direct competition.18. A _______ is a financial statement that shows the income, expenses, and profit or loss of a business over a specific period.19. The _______ is the process of setting the price of a product or service based on its perceived value to thecustomer.20. In business, a _______ is a document that summarizes the financial transactions of a company during a specific period.三、简答题（每题5分，共20分）21. What are the key elements of a business plan?22. Explain the concept of "first-mover advantage" in business.23. Describe the importance of corporate socialresponsibility (CSR) in today's business environment.24. What is the difference between a franchise and a joint venture?四、案例分析题（每题15分，共30分）25. Analyze the following scenario: A small business owner is considering expanding into a new international market. What factors should they consider before making this decision? 26. Discuss the potential benefits and challenges of using social media for business promotion.五、论述题（共20分）27. Discuss the role of technology in modern business and how it has transformed the way companies operate.答案：一、选择题1. B2. A3. C4. A5. A6. A7. A8. A9. A 10. C二、填空题11. Marketing 12. Contract 13. Marine insurance 14. Discount 15. Return on Investment 16。

c开头的英文单词大全C开头的英文单词大全。

Cabbage a leafy green or purple biennial plant, grown as an annual vegetable cropfor its dense-leaved heads.Cable a thick rope of wire or hemp used for construction, mooring ships, and towing vehicles.Cactus a succulent plant with thick, fleshy stems and often spines, native to arid regions of the Americas.Cafeteria a dining establishment in which customers serve themselves from a variety of dishes laid out on a counter or table.Cake a sweet baked food made from a mixture of flour, sugar, and other ingredients, usually with a sweetening agent, and often with fruit, nuts, or chocolate.Calculator a small electronic device used for performing mathematical calculations, typically with a visual display and buttons for inputting numbers and operations.Calendar a system for dividing the year into months, weeks, and days, used for organizing time and scheduling events.Camera a device for recording visual images in the form of photographs or video, typically using a lens to focus light onto a light-sensitive surface.Camp a place with temporary accommodation, typically consisting of tents or other structures, used for shelter or recreation.Candle a cylinder or block of wax or tallow with a central wick that is burned to produce light or heat.Candy a sweet food made with sugar or syrup combined with fruit, chocolate, or nuts.Cannon a large, heavy piece of artillery, typically mounted on wheels, used in warfare for firing projectiles.Canvas a strong, durable fabric used for making sails, tents, and other items requiring sturdiness.Cap a type of headwear with a brim and a crown, typically worn for protection from the sun or as part of a uniform.Capital the most important city or town of a country or region, usually the seat of government and administrative center.Car a road vehicle with an engine and four wheels, typically designed for carrying a small number of passengers.Card a piece of thick, stiff paper or plastic with a design or message, used for sending greetings or as an official document.Carpet a floor covering made from thick woven fabric, typically with an upper layer of pile attached to a backing.Carrot a long, orange root vegetable, often used in cooking and salads.Cartoon a simplified or exaggerated drawing or painting, typically used in humor or for children's entertainment.Cash money in the form of coins or banknotes, as opposed to checks, credit, or other forms of payment.Castle a large building or group of buildings fortified against attack with thick walls, battlements, and often a moat.Cat a small domesticated carnivorous mammal with soft fur, a short snout, and retractile claws.Cauliflower a variety of cabbage with a large, rounded head of white flowers, often eaten as a vegetable.Cave a large underground chamber, typically with a passage leading to the surface, formed by the natural forces of erosion or volcanic activity.Cell the smallest structural and functional unit of an organism, typically microscopic and enclosed by a membrane.Cello a large, four-stringed musical instrument of the violin family, played with a bow.Cement a powdery substance made by calcining lime and clay, mixed with water to form a paste, used in construction and for binding materials together.Cemetery a place used for burying the dead, typically with gravestones or other markers to identify individual graves.Cereal a grass that is cultivated for its edible grains, such as wheat, rice, or maize.Chair a separate seat for one person, typically with a back and four legs for support.Chalk a soft, white, porous sedimentary rock, often used for writing or drawing on blackboards or other surfaces.Champion a person who has defeated all opponents in a competition or series of competitions, and is thus the winner.Chandelier a decorative hanging light with branches for several light bulbs or candles.Change the act or process of making or becoming different.Channel a length of water wider than a strait, joining two larger areas of water, especially two seas.Character the mental and moral qualities distinctive to an individual.Cheese a food made from the pressed curds of milk, often seasoned and aged.Chef a professional cook, typically the chief cook in a restaurant or hotel.Chess a board game for two players, each beginning with 16 pieces of six kinds that are moved according to individual rules.Chicken a domestic fowl kept for its eggs or meat, especially a young one.Child a young human being below the age of puberty or below the legal age of majority.Chimney a vertical structure, typically of brick or stone, that carries smoke or steam away from a fire, boiler, or stove.China a fine white or translucent vitrified ceramic material.Chocolate a food in the form of a paste or solid block made from roasted and ground cacao seeds, typically sweetened and flavored.Church a building used for public Christian worship.Cinema a theater where movies are shown for public entertainment.Circle a round plane figure whose boundary consists of points equidistant from a fixed center.City a large town.Clay a stiff, sticky fine-grained earth, typically yellow, red, or bluish-gray in color and often forming an impermeable layer in the soil.Clock a mechanical or electrical device for measuring time, indicating hours, minutes, and sometimes seconds, typically by hands on a round dial or by displayed figures.Cloud a visible mass of condensed water vapor floating in the atmosphere, typically high above the ground.Coal a combustible black or dark brown rock consisting mainly of carbonized plant matter, found mainly in underground deposits and widely used as fuel.Coast the part of the land near the sea; the edge of the land.Cocktail an alcoholic drink consisting of a spirit or spirits mixed with other ingredients, such as fruit juice or cream.Coffee a hot drink made from the roasted and ground seeds (coffee beans) of a tropical shrub.Coin a flat, typically round piece of metal with an official stamp, used as money.Cold of or at a low or relatively low temperature, especially when compared with the human body.College an educational institution or establishment, in particular.Color the property possessed by an object of producing different sensations on the eye as a result of the way it reflects or emits light.Comb a strip of plastic, metal, or wood with a row of narrow teeth, used for untangling or arranging the hair.Comedy professional entertainment consisting of jokes and satirical sketches, intended to make an audience laugh.Comet a celestial object consisting of a nucleus of ice and dust and, when near the sun, a “tail” of gas and dust particles pointing away from the sun.。

小学上册英语第一单元期末试卷(有答案)英语试题一、综合题(本题有100小题，每小题1分，共100分.每小题不选、错误，均不给分)1.What is the name of the phenomenon where the moon blocks the sun?A. Solar eclipseB. Lunar eclipseC. SupermoonD. Blood moon答案: A2.The ancient Greeks participated in ________ to showcase their athletic skills.3.She is _______ (searching) for her keys.4.The flowers are _____ in the garden. (blooming)5.小蜥蜴) basks on the warm rocks. The ___6.The ______ (蝴蝶) is flying from flower to flower. Its wings are very ______ (美丽的).7.The cat sleeps on a _____.8.What do you call the act of telling a lie?A. DeceitB. TruthC. HonestyD. Integrity答案:A9.The stars are shining ________.10.The ______ helps us learn about public policy.11.My friend is a ______. She loves to paint.12. A ____ is a gentle creature that enjoys eating fruits and vegetables.13.habitat fragmentation) threatens many species. The ____14.I enjoy going to the ___. (beach)15.I want to _______ (了解) more about space.16.What do we call the process of a gas changing into a liquid?A. EvaporationB. CondensationC. FreezingD. Melting答案:B.Condensation17.Certain types of flowers bloom only in ______ weather. (某些类型的花仅在寒冷的天气中开放。

小学上册英语第2单元寒假试卷英语试题一、综合题(本题有100小题，每小题1分，共100分.每小题不选、错误，均不给分)1.We will go _______ (旅行) next month.2.What do we call a person who studies the earth?A. GeologistB. BiologistC. ChemistD. PhysicistA3.His favorite sport is ________.4.We have a ______ (精彩的) cultural festival every year.5.Ions are charged ______.6.The _______ (The Marshall Plan) helped Europe recover after World War II.7.My _____ (表哥) loves to play soccer with his friends every weekend. 我表哥每个周末都喜欢和朋友们踢足球。

8.The chemical formula for sulfur dioxide is ______.9.I have a special ________ that reminds me of my childhood.10.The ________ is a gentle giant in the jungle.11.The Earth rotates on its ______ once every hours.12.I can ______ (jump) very high.13.Which tool do you use to measure length?A. ScaleB. RulerC. ClockD. ThermometerB14.The __________ (人权) must be respected worldwide.15.The balloon is ___ (floating).16.I have a pet that is very ____.17.The _____ (火烈鸟) stands on one leg while resting.18.What is the color of an emerald?A. RedB. BlueC. GreenD. YellowC19. A substance that donates electrons is called a ______ agent.20.What do we call a person who acts in movies or plays?A. DirectorB. ProducerC. ActorD. ScreenwriterC21.What do you call a person who collects stamps?A. PhilatelistB. NumismatistC. CollectorD. CuratorA22.Did you ever see a _______ (小蜻蜓) hovering by the water?23.The _____ (stevia) plant is a natural sweetener.24.What is the name of the famous novel by Mark Twain?A. Moby DickB. The Great GatsbyC. Huckleberry FinnD. To Kill a Mockingbird25.The __________ can reveal patterns in sediment deposition and erosion.26.The Earth's atmosphere is vital for protecting life from ______.27.What is the term for a young panda?A. CubB. KitC. PupD. HatchlingA28.I have a toy _______ that can talk and walk.29. A ____ is a playful animal that enjoys chasing after its friends.30. A _______ is a solution that cannot dissolve any more solute.31.What do you call a baby boar?A. CalfB. KitC. PigletD. Cub32.The chemical formula for ammonium sulfide is ______.33.My friend is a big __________ of dance. (爱好者)34.It’s important to be ______ (尊重) towards others and listen to their opinions. Everyone has something valuable to share.35.Who is known for writing plays and stories?A. PainterB. AuthorC. ScientistD. Musician36.My __________ (玩具名) always makes me feel __________ (形容词).37.She has long _______ (hair).38.I want to _______ (学习) a new language.39._____ (cultivation) is important for sustainable farming.40.My brother is a ______. He enjoys cooking.41.The chemical formula for iron(II) chloride is ______.42.The trees in the _______ provide a cool shade on sunny days.43.My friend is a ______. He loves to collect stamps.44.I like to watch the ______ in the sky.45.The ________ is the line that runs from the North Pole to the South Pole.46.What is the largest land animal?A. RhinoB. ElephantC. GiraffeD. Hippo47.The __________ is a large desert in Australia. (吉利亚沙漠)48. A _______ (小乌龟) hides in its shell when scared.49.What do we call the place where we learn?A. OfficeB. SchoolC. StoreD. LibraryB50. A ________ can swim in the ocean.51.The capital of Kazakhstan is __________.52.I want to ___ a new game. (try)53.The _____ (果实) is sweet and juicy.54.The Andromeda galaxy is the nearest ______ to the Milky Way.55.Which animal is known for its speed?A. TortoiseB. CheetahC. ElephantD. SlothB Cheetah56.I enjoy __________ with my friends. (聊天)57.My dog enjoys rolling in the _______ (草).58.My brother wants to be a __________ (宇航员) when he grows up.59.I like to use my toy ________ (玩具名称) for creative projects.60.Which country is famous for its pyramids?A. MexicoB. EgyptC. ChinaD. India61.The _____ (butterfly/bird) is colorful.62.My dad is a wonderful __________ (父亲) who always listens.63.The Pleiades is a famous star ______.64.Which fruit is red and round?A. BananaB. AppleC. GrapeD. Orange65.The ancient Incas built _____ in the Andes Mountains.66.What is the freezing point of water?A. 0°CB. 32°CC. 100°CD. 50°CA67.What color are emeralds?A. BlueB. RedC. GreenD. YellowC68.The _______ (小驴) brays loudly in the pasture.69.What is the capital of France?A. LondonB. BerlinC. ParisD. RomeC70.The __________ (历史的主题) resonate across cultures.71.The ____ is often seen resting in the sun on warm days.72.The chemical formula for calcium chloride is ______.73.In geography, __________ refers to the height above sea level. (海拔)74.The body of a fish is covered in __________.75.The children are _____ (playing/sleeping) in the yard.76.The conductor, ______ (指挥), leads the choir.77.What do we call the process of water turning into vapor?A. EvaporationB. CondensationC. PrecipitationD. FiltrationA78.The Ptolemaic model of the universe placed Earth at the ______.79.They are friends at ___. (school)80. A sunflower is a type of _______ that grows tall.81.I like to _____ (draw/color).82.My cat loves to curl up on my ______ (腿).83.What is the name of the famous Italian artist known for painting the Sistine Chapel?A. Leonardo da VinciB. MichelangeloC. RaphaelD. BotticelliB84.Earth's atmosphere protects us from harmful ______.85.The ________ grows quickly.86.The ocean is very ________.87.The ancient Egyptians wrote using _______.88.The filmmaker creates _____ (电影) that tell stories.89.Plants can help improve _______.90.What do we call the first woman to fly solo across the Atlantic Ocean?A. Amelia EarhartB. Bessie ColemanC. Harriet QuimbyD. Jacqueline CochranA91.What is the name of the famous painting of a girl holding a pearl earring?A. The Girl with a Pearl EarringB. The Mona LisaC. The Birth of VenusD. The Starry Night92.The _______ (The Vietnam War) resulted in significant loss of life and impact on US foreign policy.93.What is the name of the animal known for its ability to change colors?A. ChameleonB. GeckoC. IguanaD. Lizard94.I like to draw pictures for my ____.95.The __________ of a bird helps it to keep warm.96.The bird is ___ in the sky. (soaring)97.The __________ was a major event in US history that abolished slavery.98.The ice cream is ___ (melting/freezing).99.What is the name of the famous artist who painted the Mona Lisa?A. PicassoB. Van GoghC. Da VinciD. RenoirC100.She likes to _____ (dance/sing) in the evening.。

Chapter 6 Strategic Information System: Information Technology’s Application for Enterprise Strategy.波特的价值链模型（Porter’s Value-Chain Model）企业的产品利润系基企业一连串的加值活动（Value-Add Activities）所产生，而企业的加值活动分为主要活动（Primary Activities）与支持活动（SupportActivities）。

主要活动系为与产品与服务有直接关联的活动，而支持活动则包含支持主要活动，但与产品与服务无直接关联的所有措施（包含管理与支持的活动）。

主要活动分为「进货后勤（Inbound Logistic）」、「生产制造（Operation）」、「出货后勤（Outbound Logistic）」、「营销销售（Sale and Marketing）」、「售后服务（Service）」五大项，主掌产品与服务的生产过程。

支持活动则涵盖了整个主要活动的范畴，如采购管理（Procurement）、科技开发（Technology Development）、人力资源管理（Human Resource Management）、财务会计管理（FinancialManagement）、企业的基础设施（Enterprise Infrastructure）等。

策略推力模型（Strategic Thrust Model）五个策略攻击的领域：✧差异化（Differentiation）－企业选择一种或数种对顾客有价值的需求，以自身优势的能力，单独满足这些需求，让其他对手在顾客认知上产生差异。

✧成本（Cost）－提供相当利益给顾客，但价格较低，竞争优势以降低成本为主要手段。

✧创新（Innovation）－开发新产品、服务或创新作业流程。

✧成长（Growth）－利用营业额、规模、市场、产品范围的扩大与提升来创造及维持其优势。

河南省高中英语必修三Unit5TheValueofMoney知识汇总笔记单选题1、We cannot always_________ the traditions handed down to us from the past. A．establishB．observeC．donateD．forgive答案：B考查动词词义辨析。

句意：我们不能总是遵守过去传下来的传统。

A. establish建立；B. observe遵守；C. donate捐赠；D. forgive原谅。

根据“the traditions handed down to us from the past”可知，此处表示“遵守”，故选B。

2、Her career of a supermodel started________—an agent saw her in a cafe and persuaded her to become a model. A．by accidentB．once in a whileC．in the endD．more or less答案：A考查固定搭配。

句意：她的超级模特生涯是偶然开始的——一位经纪人在咖啡馆看到她，并说服她成为一名模特。

A.by accident偶然；B.once in a while偶尔；C.in the end最后；D.more or less或多或少。

结合破折号后句意可知她的超级模特生涯是偶然开始的，用by accident符合题意。

故选A。

3、Hearing the call for help, Tom did not ________ for a second to save the drowning child. A．interruptB．hesitateC．glanceD．reply答案：B考查动词词义辨析。

句意：听到呼救声，汤姆毫不犹豫地去救那个溺水的孩子。

A. interrupt打断，插嘴；B. hesitate犹豫；C. glance瞥一眼；D. reply回答。

《跨境电商英语》期末试卷《跨境电商英语》期末试卷__________系_____级专业班姓名学号____________第I卷(1-4页)包括写作与阅读两部分，答题时间为45分钟。

卷I和答题纸在开考时分发。

Part I Writing(10’*2=20’)Directions:For this part, you are allowed20minutes to write two shortpassages.You should include inyour passages all the giveninformation.You should write atleast60words but not more than100words for each passage.Writeyour passages on Answer Sheet.Section AWrite an-email to Li Hua,a friend of yours,answering his questions about how to write the description of a product. The necessary information below should be included.1.⼀个优秀的产品描述有助于买家了解产品并形成下单意向。

2.由于买家都为境外客户，需要使⽤英⽂填写⼀切产品信息。

3.必须将买家⽐较关注的产品的特⾊、功能、服务、包装及运输信息等展⽰出来。

4.还应当包括产品的包装及配件信息、付款⽅式、物流⽅式、售后服务及承诺。

Section BWrite an email to one of your customer,reminding her of a quick payment.The necessary information below should be included.1.你所挑选的商品是本店最畅销的。