驾驶证英文翻译件(共6篇)
1.驾驶证英文翻译件 篇一
国外驾照转国内驾照 专业境外驾驶证翻译流程
国外驾照转国内驾照办理流程:第一步,准备身份证明和复印件;第二步,准备境外驾驶证和翻译件;第三步,准备照片和照片回执;第四步,身体条件检查。
主要涉及机构:1.深圳市车辆管理所2.深圳市公证处(非必须)3.本市公安局4.工商局注册的翻译公司。需要将境外驾驶证翻译分为两种情况:1.持境外驾驶证的外籍驾驶人员如果在境内想取得合法驾照要将境外人员驾驶证翻译成中文、盖章认证。2.在境外获得驾驶证的中国驾驶员回国驾驶要在境内将驾驶证翻译、盖章认证。
附:持境外机动车驾驶证申领机动车驾驶证所需资料
1.《机动车驾驶证申请表》
2.《机动车驾驶人身体条件证明》
3.有效境外驾驶证原件及复印件(非中文表述的外文驾驶证,还需提供我市区级以上公证处或者工商局注册的翻译公司公证的中文翻译文本,其中外文姓名也需要翻译成中文姓名,并在翻译文本上同时显示)。注:任何国家或组织签发的国际驾驶证及实习驾驶证、临时驾驶证不予受理,部分准驾车型标注不明的境外驾驶证须出具官方说明文本。
4.申请人身份证明原件及复印件:
1)境外人员提供其入时所持的护照及其他旅行证件,在签证期间,进入我国境内居(停)期为三个月以上的有效签证或者居留许可证(居留许可签发地非广东深圳的,需在居留许可签发地的车辆管理所申请),以及提供本市公安局开具的反映其住址的居留证或《境外人员临时住宿登记表》的原件及复印件。
2).深圳户籍居民提供《居民身份证》
3).外地户籍居民提供《居民身份证》及我市公安机关核发的居住、暂住身份证明
4).护照原件及复印机
5).提供本人在深圳市任何一间可照驾驶证相片照相馆的照相回执(回执6个月内有效)
6).自备四张驾驶证专用照片(两张分别贴申请表用及体检表格,两张用于制作驾驶证)。复印件要求为A4规格,境外驾驶证需要复印正反两面。
2.驾驶证英文翻译件 篇二
Traditional methods have used numerical tech-niques for defining a suitable mathematical model.The values in these techniques are treated as crisp for explaining real world events.However,it has been discussed that much of human reasoning is based on imprecise,vague and subjective values.The environments in which people make decisions are most often complex and defining a valid mathematical model is usually very difficult[1].Zadeh’s (1965) fuzzy logic has given analysts a tool to represent the human behavior more precisely,especially where relatively few data exist,and where the expert knowledge about the system is vague and linguistic[2].Since then,a large number of literatures have been committed on fuzzy set theory and fuzzy logic as well as much development on a complete fuzzy algebra.Therefore,in recent years,fuzzy logic has become one of the most effective methods that deal with uncertainty rooted from complexity and imprecision.
1 Fuzzy apperception
It would not be surprising that if we ask themabout their perceived travel times along a particular route,they would probably find it easier to use verbal definitions than exact numbers.For instance,a driver may state that“it was around 15 minutes”,while another may“it was 10 minutes”.Although,a driver may say that it was“14 minutes”,he/she can still not tell with certainty about how much time it was exactly.They all use approximate values to reflect their subjective appraisals.These assertions are due to the fact that the operational representation of exact real numbers is ambiguous (erroneous representation of real numbers argument)[3].Further,for the same example,if they were asked to describe how they categorize travel times that they perceive,a driver may describe it as“high”,while another who verbally expresses his/her perceived travel time as the same as someone else may think it as“moderate”.‘These assertions are,on the other hand,due to the fact that the representation of descriptive sets is mostly (vague appraisal argument)[4].Because of the ability of humans,even vague assertions or claims are present,it can reason in appropriate ways.Additionally,humans posses common sense that give them the ability to reason,and as a consequence they make use of imprecise or vague assertions in a proper manner to solve complex problems in a reasonable time.Therefore,these subjective estimations are not actually the execution of a random variable that assented travel time in a traditional method,but actually his/her subjective assessments of the travel time due to imprecision embedded in his/her judgment.In traditional methods,these descriptive sets are described using sharp boundaries,while in fuzzy logic,gradual transitions are allowed.As a result,using crisp sets to describe the human perceptions may be misleading and limited for appropriate real life modeling.
2 Route choice model
2.1 Fuzzy categorization
A decision maker compares several actions withrespect to some key attributes whose values are defined subjectively on a quantitative or qualitative plane.Subjectivity refers to cognitive mapping process that is not exact replicas of reality but merely models of the reality[5].Therefore,the aim of the first model is to define a way that reflects decision makers’subjective view of the system over which they appraise the alternatives.To this end,Weber’s psycho-physical law of1834,which states that the just noticeable difference,in stimulus intensity must be proportional to the actual stimulus intensity itself,is utilized.Psycho-physics typically refers to behavioral and cognitive study of brain/mind functions.Weber’s law introduces a qualitative psycho-physical sensor scale and states that qualitative measures of perception and stimuli are connected to each other proportionally,in other words;change in sensation is noticed when the stimulus is increased by a constant percentage of the stimulus itself[6].If the alternatives are compared over a range of Smin~Smax,which is the universe of discourse for a particular criterion,then the initial noticeable difference is mathematically expressed as follows.
Where As0 is the initial step or first notice,(1+ε) is the progression factor and n is an integer number showing the number of subintervals being considered.Since the law states that 4s in intensity is proportional to the actual stimulus intensity itself,the relation between intensities over a specific range constitutes a sequence with geometric progression from the most desired value,target value,Smax,in this case,to the least desired value,Smin,in this case.This relation is expressed as:
The solution space corresponds to the definitions of attractiveness from the comparisons.A categorization scheme is prepared similar to the one prepared for the input space to reflect the decision maker’s subjective weight assignments that represents his/her preference values or ratio judgments for the alternatives in pairwise matrices.Likewise the case for the input domain,as seen in figure 3.1,the output domain is labeled as Absolute Importance (AI),Demonstrated Importance(DI),Strong Importance (SI),Weak Importance(WI) and Equal Importance (EI) Saaty’s.It should be emphasized that these are not actual responses,but serve as a conceptual basis for pairwise comparisons.
This labeling scheme represents the response tothe increase in stimulus.Therefore,there exist an equal number of fuzzy categorizations that corresponds to decrease in stimulus to represent the reciprocal of the above preferences.Although,these reciprocal sets can be named in a more meaningful way,in this research they are labeled as Reciprocal of Absolute Importance’(RAI),'Reciprocal of Demonstrated Importance(RDI),'Reciprocal of Strong Importance (RSI),and'Reciprocal of Weak Importance’(RWI).The purpose of showing alphabetical terms,a,b,c,d,e in figure 3rather than Saaty’s original scale (1/9-9) as the output domain is due to the defuzzification method used.
2.2 Fuzzy rules
In this step,we prepared a set of‘if-then’rules to reflect the cognitive comparisons made between each alternative.Table 2 indicates the rules prepared for this method.The rules in the table are given in the form of“IF x is Ai and y is Bi THEN z is Ci‘,where x;y,and z are linguistic definitions of input and output variables,respectively,whereas Ai,Bi and Ci are the fuzzy sets defined for the x;y,and z in the universe of discourse X;Y,and Z,respectively.The table can be read from left to right and from top to bottom.For instance,if alternative A is compared over alternative B,then the first row of the table corresponds to this,which is read as“if alternative A is MMD and alternative B is MMD,then preference of A over B is EI”.The pre x“R”in some elements of the column e only refers to the reciprocally condition in the scale,i.e.“if alternative A is MD and alternative B is MMD,then preference of A over B is RWI”.The output of the rule system corresponds to aij’s in the pairwise matrix of the AHP and therefore should be regarded as the estimate for the weight of the alternative i;wi,to alternative j;wj.Utilizing‘Min’operator for‘and’ensures the model to be consistent with the reciprocal axiom.
We used the center of area (COA) defuzzificationmethod for our model.If Saaty’s ratio scale (1/9-9)is directly used as the solution variable for the rule base,the outcome will be counterintuitive;the values on diagonals of matrices will not be equal to one.This is due to the additive nature of COA method,where the reciprocal property cannot be re ected properly when the solution variables act as multiplicative.We used a linear 1-9 scale that serve as a conceptual solution variable to overcome this problem as seen in the column f of table 2.The values in the column g indicate their corresponding values in the Saaty’s scale.Once the defuzzified results,aij’s,are obtained,their equalities in Saaty’s scale,aij’s,can be found from the following transformation functions that comply with the axioms:
2.3 Finding criteria weights
Once the elements of pairwise matrices areobtained by means of fuzzy logic and approximate reasoning,the resulting priorities can be captured by applying the eigenvalue method of the AHP.A pairwise matrix for an expert i with respect to criterion k can be indicated as:
Each pairwise matrix in the form of m×m,whose elements are aij’s,is a square positive reciprocal matrix:
Therefore,the ratios either under or above theprincipal diagonal of the matrix are enough to complete the matrix by taking the reciprocals of the givenelements.Each aij could be regarded as an estimate ofthe weight of the alternative i;wi,to alternative j;wj:
Then
In such a matrix,only one column is enough tocomplete all the ratios and the number of alternatives,m,represents the largest principal right eigenvalue,λ1of the matrix while the other eigenvalues of the matrix are all equal to zero.Naturally,the experts may have some inconsistencies in judgment and in general use of the.AHP,this can be allowed to a tolerable level.In this case,the principal right eigenvalue is greater than m.Thus,eq.(6) can be rewritten as:
3 Example
One of the subjects defines his/her perceptions oftravel times on three routes,A;B and C in his/her choice set as triangular fuzzy numbers,then the universe of discourse can be categorized as shown in fig.4.
Table 3 shows the truth values obtained from thepredicates of fuzzy rules showing the match between each fuzzy travel time and the fuzzy-categorized universe of discourse.After applying‘max-product,inference,the rules’conclusions for each pairwise comparison can be found and corresponding defuzziffied results can be obtained as shown in Table 4 where the equivalent values for Saaty’s scale is obtained from eqs.(13) and (14).Hence,the resultant pairwise matrix becomes
Consequently,the right eigenvector of its largesteigenvalue can be found as[0.77,0.59,0.23].Once it is normalized,the preference values can be captured as[0.48,0.37,0.14].Therefore,of the preferences that the subject allocates among the alternatives route A accounts for48%,while route B and route C account for 37%and 14%,respectively.
4 Conclusions
In this paper,we proposed a method that can beused to handle fuzzy perceptions rationally in route choice decision-making behavior.We followed a psychometric approach based on Weber’s psychophysical law of 1 834 to represent typical aspects of the human decision-making process for route choice in transportation systems.Saaty’s AHP was utilized as a plausible method to deduct a complex multi-alternative comparison case to a simple binary comparison case,as well as a satisfactory technique for human cognitive evaluation process.First,decision makers’input spaces were subdivided into subjectively equal spaces using Weber’s psycho-physical law of 1834 with a progression factor of two.Then,a set of“if-then”rule base was prepared to reflect human cognitive computation for capturing the pairwise preferences among the alternatives.Regardless of the number of alternatives in hand,due to the nature of the‘ifthen’rules,they were always compared as binary.Finally,we employed the AHP pairwise matrices and eigenvalue method to find each individual’s preference values allocated among the alternatives in their choice set.To justify this new method,a real world sample that is based on stated values was used where subjects provided their perceptions as triangular fuzzy numbers for three factors,travel time,congestion and safety.By use of the least sum of the squared error method,we evaluated the model’s estimation capability by comparing calculated preferences with stated preference values for the alternatives.Although,the analysis is carried out for only triangular fuzzy numbers,this method can easily be extended to any type of fuzzy numbers.We found that this new procedure can replicate the drivers’behavior on route choice as intuitively significant.Therefore,it deserves special attention.When all the factors are combined into a cost function that can be defined as a fuzzy number,this method can also be used on a large scale to estimate traffic assignment.
参考文献
[1] Teodorovic D,Kikuchi S.Fuzzy sets in traffic and transportation systems.Fuzzy Sets and Systems,2000;116(1):1-5
[2] Lotan T,Koutsopoulos H N.Models route choice behavior in the presence of information using concepts from fuzzy set theory and approximate reasoning.Transportation,1993;20:129-155
[3] Hoogendoorn S.Hoogendoon-lanser S.Perspectives of fuzzy logic in traffic engineering.Transportation Research Board 78th Annual Meeting,1999
[4] Ridwan M.Fuzzy preference based traffic assignment problem. Transportation Research Part C,2004;12:209-233
[5] Miller G.The Magical number seven plus or minus two:some limits on our capacity for processing information.Psychological Review, 1956;63:81-97
3.驾驶员英文自我评价 篇三
1. Life: cheerful, humorous, with good coordination and communication skills, and team spirit.
2. Work: clear thinking, strong sense of responsibility, able to view the overall situation. Good professionalism, be able to bear hardships and work under pressure. And has the extremely high judgment and the matter decisive ability. Be good at summing up work experience and make overall personal summary for each project.
3. Personal expertise: veteran, retired to Panyu Agricultural College as an instructor, work hard, conscientious, conscientious, conscientious. I am a driver in the army. I have been in and out of many provinces and cities with the army. I am a good driver. I have rich driving experience, mature and steady, and can make a quick decision.
4.在职证明翻译件 篇四
Dear Sir/Madam
We would like to confirm that the above named person is an employee of XXX Ltd(公司名);Mr XXX started his employment on the XXth May 200X and works XX hours, X days a week as an XXX(你的职位)within our company.I hope this information is sufficient, however if you require any further assistance please do not hesitate to contact me again.Yours faithfully
签名
XXX
Central Support Administrator
5.一件感人的事中英文作文 篇五
A Touching Event
Yesterday afternoon I went to the Yuexiu Park。 It happened that I saw a touching event。 At that time, some people were boating on the lake。 Among them was perhaps a happy family。 They were taking photos when suddenly the girl fell off the boat into the water。 She was struggling and her parents cried out, “Help!Help !” It was obvious that they could not swim at all。 From nearby a young man immediately rushed to the lake。 Without taking off his clothes, he jumped into the water and quickly swam towards the girl l who was already tired out。 At last he carried her to the lake side。 She was saved!
How happy the parents were! Before they thought of thanking the Young man, he had disappeared!
一件感人的事
昨天下午我去越秀公园玩,碰巧看到一件感人的`事情。当时,有一些人雀湖上划船,也许其中有一个幸福的家庭。他们正在拍照,忽然小女孩从船上落入水中,她在水中挣扎,她的父母大声呼救;显然他们不会游。附近一位年轻人立即朝湖边冲去,他衣服没脱就跳入水中,迅速朝小女孩游去。就在小女孩筋疲力尽之时,他终于把她拖到湖边。她得救了!
6.驾驶证英文翻译件 篇六
CGMP违规
浙江中贝九洲进出口有限公司(FEI号3010365339)
1.未能实施有效的质量管理体系,未能将所有从原料药生产商处收到的质量和法规信息转达给客户。
你们的贸易公司,以下简称为中贝,从外部供应商处采购了原料药,未经质量部门审核即重新贴标。原始供应商提供的原始检验报告书中的信息被誊写到以浙江九洲药业有限公司为抬头的新检验报告书上,在新的报告书上没有体现原始生产商和原始分析化验室的信息。另外,包装桶上被加贴了标示为浙江九洲药业有限公司的新标签。该操作已从根本上掩盖了这些原料药的供应链信息。
中贝并没有重新贴标的质量体系。还有,我们注意到至少有一例中,一批发往美国的加巴喷丁的复验期(原生产商的COA中给定为2013年11月)被改成了有效期,而且新COA上的有效期比原复验期推迟了11个月(2014年10月)。
在你们的回复中,你公司声明按中国法律,中贝是一个独立的法人实体。但是,FDA认为该实体是在你们控制之下。在检查期间,你们员工声明中贝是浙江九洲药业有限公司的集团内,所提供的组织机构图显示中贝管理层向你(CEO)汇报。中贝人员的工作在同一个办公区域内。还有,从中贝发运的原料药随货有一封信函,声明浙江中贝和浙江九洲药业有限公司同属一个集团。即使没有这些紧密的关系,无论如何也是你们管理层允许了中贝集团继续在你公司的质量体系以外进行不合规运作。
在对本警告信的回复中,需要提供你们建议在中贝拟实施的质量体系详细信息,要描述运作流程,提交例子证明如何维护现有分销原料药的可追溯性,如何保证提交给客户的资料中包括准确的生产商和分析化验室信息。另外,要提交你们对上述批次加巴喷丁的有效期的给定理由。如果你们的资料不能支持上述操作或其它类似的延期,要描述对有问题批次准备采取的措施。
浙江九洲药业有限公司(FEI号 3003744377)2 质量部门在原料药批次销售前未能审核批生产记录 我们的检查官发现你公司将未完成批记录审核的批次发运了。尽管你公司有程序要求在产品旅行销售前应审核批记录,还是发现有好几次你们质量部门在产品放行前即批准发货。你公司的几个员工很清楚这种情况,但都没有采取措施去防止其发生。
在检查期间,你公司的员工进行了内部审核,发现质量部门还在放行前销售了另外三个批次。不管怎样,鉴于你们如此差的文件记录现状(详细描述见以下3#缺陷),我们还是担心你们的内部审核可能并未能发现所有未经审核批记录即发运的产品。我们提醒你们,质量部门对批记录的批准应不仅仅是作为一个纸面上的文章,也应该包括对该批次生产期间所有发生的偏差和非预期结果进行彻底的审核。
质量部门对批记录的审核在CGMP里是一个非常清楚的要求。相关管理人员应保证质量部门履行其职责。在对本警告信的回复中,请提交一份完整的实施清单,描述所有防止这些情况重复发生的措施,描述在将来能保证你们内审程序可以发现和纠正类似事件改进情况。3.未能在生产操作发生时及时记录
检查官在查看某设备的使用、清洁和维保日志时,发现检查之前那天的记录没有写。你们操作人员说那行留为空白是为了给上一班次补上他们做的清洁操作。在检查期间,我们检查官发现你们的生产记录中也有类似的数据缺失或数据填写滞后的现象。这种操作不符合CGMP要求。操作人员被告知公司没有体系用来报告这种记录中的滞后情况,这种记录失误是不需要进行偏差调查的,也不需要通知质量部门。
在检查期间,你们质量部门的一名员工还给检查官出示了一份批记录,其中有他的签名,他说他已经对该批记录进行了审核。该员工后来承认,他伪造了该CGMP记录,并说事实上他并没有进行审核,完全不顾其实他已经在该批记录上作为QA审核员签字并已放行了该批产品。上述这种数据做假和记录保存缺陷使得我们非常怀疑你们公司记录的有效性。在回复本警告信时,要提交一份对人员的数据做假行为的全面调查。另外,要提交你们公司如何记录所实施的操作时管理数据输入的时间的流程,并说明你们如何保证这些遵守这些程序。特别要提交你们公司避免数据作假和/或人员做假的情况发生所要采取的纠正措施。4.未能对设备进行充分的维保,使其处于适合其既定的原料药生产用途的状态
我们的检查官在这次检查中注意到纯化水系统有一个地方有泄漏,值得注意的是前一次检查中也是这套纯化水系统被发现有类似的问题。你们对上次检查的回复中所描述的预防措施其实并未足以让你们的员工发现和修补纯化水系统的泄漏,因此,我们很质疑现有的措施是否有效。在对本警告信的回复中,请说明为什么原来的措施没起作用,已采取了什么新的措施,为什么新的措施会起作用。
这次检查中还发现其它生产设备也处于需要修理的状态,因此在将来的检查中,我们会更详细地审核你们修订过的预防性维保计划。
在对本警告信的回复中,要提交一份综合的整改行动计划,说明你公司保证数据完整性的方式。我们强烈推荐你们聘请一位对数据完整性问题具有较好经验的第三方审计员,让他帮助你们评估你们的整体GMP符合性。
在本次检查中,你们质量部门的员工说该部门的工作量对于现在的人员数量来说太大了。我们发现的这些重大问题显示你们质量部门无法完全履行其职责。例如,在检查期间,你们的运营主管告诉我们检查官说你们的质量部门还没有时间对那个月生产的所有产品进行审核。你有责任保证给质量部门提供充分适当的资源,使他们能完成自己的工作。
错误标识违规
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