英文翻译原文
英语文摘中英对照File
英语文摘中英对照File一、生活感悟英文原文：Life is like a camera. Just focus on what's important and capture the good times, develop from the negatives and if things don't work out, just take another shot.中文翻译：生活就像一台相机。
只需关注重要的事物，捕捉美好时光，从挫折中成长，如果事情不尽如人意，那就再试一次。
二、名人名言英文原文："The only way to do great work is to love what you do." – Steve Jobs中文翻译：“成就伟大事业的唯一途径，就是热爱你所做的事。
” ——史蒂夫·乔布斯三、趣味故事英文原文：Once upon a time, there was a fox who was very proud of his tail. One day, he got caught in a trap and had to sacrifice his tail to escape. Though he was free, he felt ashamed of his appearance. However, he soon realized that his life was more important than his tail.中文翻译：从前，有一只狐狸非常自豪自己的尾巴。
有一天，它不慎陷入了陷阱，为了逃脱，不得不牺牲自己的尾巴。
虽然它重获自由，但它为自己的外貌感到羞愧。
然而，它很快意识到，生命比尾巴更重要。
四、励志故事英文原文：Thomas Edison failed more than 10,000 times before he invented the light bulb. When asked about his failures, he replied, "I have not failed. I've just found 10,000 ways that won't work."中文翻译：托马斯·爱迪生在发明电灯泡之前失败了超过一万次。
英文原文及翻译
Vera Wang Honors Her Chinese Roots王薇薇以中国根为傲With nuptials(婚礼) season in full swing, Vera Wang’s wedding dress remains at the top of many a bride’s(婚礼) wish list. The designer, who recently took home the lifetime achievement award from the Council of Fashion Designers of America, has been innovating in bridal design for years—using color, knits and even throwing fabric into a washing machine.随着婚礼季的全面展开，王薇薇(Vera Wang)婚纱依然是许多新娘愿望清单上的首选。
王薇薇最近刚拿到美国时装设计师协会(Council of Fashion Designers of America)颁发的终生成就奖。
多年来她一直在婚纱设计领域进行创新──运用色彩和编织手法，甚至将面料扔进洗衣机里。
Ms. Wang said that her latest collection is about construction. “I had felt that I had really messed that vocabulary of perfection for brides for a while, where there’s six fabrics to a skirt, ” she said. “I wanted to go back to something that maybe was what I started with, but in a whole new way, and that would be architecture—not simplicity—but maybe minimalism.”王薇薇说，她的最新婚纱系列重点在于构建。
名篇名译（英译汉）
名篇名译0011.原文：It is an ill wind that blows nobodygood.译文：世事皆利弊并存。
赏析：原句结构比较特殊（"Itis…that…"），理解起来有点困难。
“对谁都没有好处的风才是坏风”，也就是说大多数情况下风对人都是有好处、有坏处，在引申一步就是成了上面的译句。
林佩耵在《中英对译技巧》一书中（第68页）还给了几个相同结构的英文句子。
翻译的前提是理解。
有人指出。
市面上见到的翻译作品，有好多都带有因理解不正确而产生的低级错误，“信”都谈不上还妄谈什么“达”和“雅”！初学翻译的朋友，在理解原文上当不遗余力。
2.原文：Their languag e was almostunrestr ainedby any motiveof prudenc e.译文：他们几乎爱讲什么就讲什么，全然不考虑什么谨慎不谨慎。
赏析：如果硬译，译文势必成了“他们的言论几乎不受任何深思熟虑的动机的约束”。
译者本其译，化其滞，将原句一拆为二，充分运用相关翻译技巧，译文忠实、通顺。
3.原文：Get a livelih ood,and then practis e virtue.译文：先谋生而后修身。
（钱钟书译）赏析：原句是祈使句，译句也传达出了训导的意味。
用“谋生”来译“Getalivelih ood"，用“修身”来译“practis e virtue",可谓精当。
巧的是，原句七个词，译句也是七个汉字。
4.原文：I enjoy the clean voluptu ousnes s of the warm breezeon my skin and the cool support of water.译文：我喜爱那洁净的暖风吹拂在我的皮肤上使我陶然欲醉，也喜爱那清亮的流水把我的身体托浮在水面。
中英文翻译英文原文
BPMN 2.0 Introduction to the Standard for Business Process Modeling By Thomas Allweyer2.1 A First BPMN ModelAs a starting point, a simple BPMN process model is considered. The model of posting a job in figure 1 can be directly understood by most people who previously have been concerned with any kind of process modeling. The way of modeling is similar to well known flow charts and activity diagrams.Figure 1: A simple BPMN modelA business department and the human resources department are involved in the process “Post a Job”. The process starts when an employee is required. The business department reports this job opening. Then the human resources department writes a job posting. The business department reviews this job posting.At this point, there are two possibilities: Either the job posting is okay, or it is not okay. If it is not okay, it is reworked by the human resources department. This is once more followed by the business department reviewing the job posting. Again, the result can be okay or not okay. Thus, it can happen that the job posting needs to be reviewed multiple times. If it is okay, it is published by the human resources department, and the end of the process is reached.In reality, the process for creating and publishing a job posting can be much more complex and extensive. The presented example is –like all examples in this book –a simplification in order to have small and easily understandable models which can be used for explaining the different BPMN elements.2.2 BPMN Constructs UsedBelow each element from the model in figure 1 is explained more closely. The entire process is contained in a pool. This is a general kind of container for a complete process. In the example above, the pool is labeled with the name of the contained process.Every process is situated within a pool. If the pool is not important for understanding the process, it is not required to draw it in the diagram. In a process diagram which does not show a pool, the entire process is contained in an invisible, implicit pool. Pools are especially interesting when several pools are used in order to model a collaboration, i.e. the interplay of several partners’processes. Each partner’s process is then shown in a separate pool. This will be described in chapter 5.The pool from figure 1 is partitioned into two lanes. A lane can be used for various purposes,e.g. for assigning organizational units, as in the example, or for representing different components within a technical system. In the example, the lanes show witch of the process’s activities are performed by the business department and which by the human resource department.Pools and lanes are also called “swimlanes”. They resemble the partitioning of swimming pools into lanes. Every participant of a competition swims only in his own lane.The process itself begins with the start event “Employee required”. Processes usually have such a start event. Its symbol is a simple circle. In most cases it makes sense to use only one start event, not several ones.A rounded rectangle represents an activity. In an activity something gets done. This is expressed by the activities’names, such as “Report Job Opening”or “Review Job Posting”.The connecting arrows are used for modeling the sequence flow. They represent the sequence in which the different events, activities, and further elements are traversed. Often this is called control flow, but in BPMN there is a second type of flow, the message flow, which influences the control of a process as well, and is therefore some kind of control flow, too. For that reason, the term “sequence flow”is used. For distinguishing it from other kinds of flow, it is important to draw sequence flows with solid lines and filled arrowheads.The process “Post a Job”contains a split: The activity “Review job posting”is followed by a gateway. A blank diamond shape stands for an exclusive gateway. This means that out of several outgoing sequence flows, exactly one must be selected. Every time the right gateway in the job posting-process is reached, a decision must be taken. Either the sequence flow to the right is followed, leading to the activity “Publish Job Posting”, or the one to the left is selected, triggering the activity “Rework Job Posting”. It is not possible to follow both paths simultaneously.The logic of such a decision is also called “exclusive OR”, abbreviated “XOR”. The conditions on the outgoing paths determine which path is selected. If a modeling tool is used and the process has to be executed or simulated by a software program, then it is usually possible to formally define exact conditions. Such formal descriptions, which may be expressed in a programming language, can be stored in special attributes of the sequence flows.If, on the other hand, the purpose of a model is to explain a process to other people,then it is advisable to write informal, but understandable, statements directly into the diagram, next to the sequence flows. The meaning of “okay”and “not okay”after the activity called “Review Job Posting”is clear to humans –a program could not make use of it.Gateways are also used for merging alternative paths. In the sample process, the gateway on the left of the activity “Review Job Posting”merges the two incoming sequence flows. Again, this is an exclusive gateway. It expects that either the activity“Write Job Posting”or “Rework Job Posting”is carried out before the gateway is reached –but not both at the same time. It should be taken care to use a gateway either for splitting or for joining, but not for a combination of both. The last element in the example process is the end event. Like the start event it has a circle as symbol –but with a thick border.2.3 Sequence Flow LogicThe flow logic of the job posting process above is rather easy to understand. In more complex models it is sometimes not clear how the modeled structure exactly is to be interpreted. Therefore it is helpful if the meaning of the sequence flow’s elements is defined in an unambiguous way.The logic of a process diagram’s sequence flow can be explained by “tokens”. Just as in a board game tokens are moved over the board according to the game’s rules, one can imagine moving tokens through a process model according to BPMN’s rules.Every time the process is started, the start event creates a token (cf. figure 2). Since the job posting process is carried out more than once, many tokens can be created in the course of time. Thereby it can happen that the process for one job posting is not yet finished, when the process for posting another job starts. As it moves through the process, each token is independent from the other tokens’movements.Figure 2: A start event creates a tokenThe token that has been created by the start event moves through the sequence flow to the first activity. This activity receives a token, performs its task (in this case it reports a job opening), and then releases it to the outgoing sequence flow (cf. figure 3).Figure 3: An activity receives a token and forwards it after completionThe following activity forwards the token. It then arrives at the merging exclusive gateway. The task of this gateway is simple: It just takes a token that arrives via any incoming sequence flow and moves it to the outgoing sequence flow. This is shown in figure 4. In case A, a token arrives from the left, in case B from below. In both cases the token is routed to the outgoing sequence flow to the right.Figure 4: Routing of a token by a merging exclusive gatewayThe task of the splitting exclusive gateway is more interesting. It takes one arriving token and decides according to the conditions, to which sequence flow it should be moved. In case A in figure 5, the condition “okay”is true, i.e. the preceding review activity has produced a positive result. In this case, the token is moved to the right. Otherwise, if the condition “not okay”is true, the token is moved to the downwards sequence flow (case B).The modeler must define the conditions in such a way that always exactly one of the conditions is true. The BPMN specification does not state how to define conditions and how to check whichconditions are true. Since the considered process is not executed by software, the rather simple statements used here are sufficient. Otherwise, it would be necessary to define the conditions according to the requirements and rules of the software tool.The token may travel several times through the loop for reworking the job posting. Finally it arrives at the end event. This simply removes any arriving token and thus finishes the entire process (figure 6).Figure 5: Routing of a token by a splitting exclusive gatewayThe sequence flow of every process diagram can be simulated in this way with the help of tokens. This allows for analyzing whether the flow logic of a process has been modeled correctly.It should be noted that a token does not represent such a thing as a data object or a document. In the case of the job posting process, it could be imagined to have a document “job posting”flowing through the process. This document could contain all required data, such as the result of the activity “Review Job Posting”. At the splitting gateway, the decision could then be based on this attribute value. However, the BPMN sequence flow is constrained to the pure order of execution. The tokens therefore do not carry any information, other than a unique identifier for distinguishing the tokens from each other. For data objects there are separate BPMN constructs which will be presented in chapter 10.2.4 Presentation OptionsUsually pools are drawn horizontally. The preferred direction of sequence flow is then from left to right. On the other hand, it is also possible to use vertical pools and to draw the sequence flow from top to bottom, as in the example in figure 7.It makes sense to decide for only one of these possibilities –horizontal or vertical. Nevertheless there are modeling tools which only support horizontal modelingFigure 6: An end event removes an arriving tokenFigure 7: Vertical swimlanes and nested lanesFigure 7 also shows an example of nested lanes. The lane labeled “Sales”is partitioned into the two lanes “Sales Force”and “Order Processing”. In principle it is possible to partition these lanes again, etc., although this only makes sense up to a certain level of depth.It is not prescribed where to place the names of pools and lanes. Typical are the variants selected for figure 1 and figure 7. Here the names are placed on the left of the pools or lanes, or at the top for the vertical style, respectively. The name of a pool is separated by a line. The names of the lanes, however, are placed directly within the lanes. A separation line is only used for a lane that is partitioned into further sub-lanes. Lanes can also be arranged as a matrix. The procurement process in figure 8 runs through a business department and the procurement department, both of which span a branch office and the headquarters. When a demand occurs in a branch’s business department, this department reports the demand. In the next step, the procurement is approved by the same department in the headquarters. The central part of the procurement department then closes a contract with a supplier, followed by the branch’s purchasing department carrying out the purchase locally.Although the BPMN specification explicitly describes the possibility of such a matrix presentation, it is hardly ever applied, so far.12.2 Message CorrelationThe contents of the message flows within one conversation are always related to each other. For example, all messages that are exchanged within one instance of the conversation “Process Order for Advertisement”relate to the same advertisement order. It is therefore possible to use the order ID for the correlation, i.e. the assignment of messages to a process instance. If a customer receives an advertisement for approval, he can determine the corresponding order –and thus the process instance –based on the order ID. All messages of a conversation have a common correlation.A simple conversation which is not broken down into other conversations is called communication. Therefore, the lines are called communication links (the specification draft at some places alsocalls them conversation links). A conversation has always communication links to two or more participants.If the end of a communication link is forked, multiple partners of the same type can be part of the communication, otherwise exactly one. “Process Order for Advertisement”has exactly one customer and one advertising agency as participants, but multiple designers. Therefore, the designer’s pool contains a multiple marker. However, having only the multiple marker in the pool is not sufficient. The conversation “Handle order for an illustration”, for example, has only one designer as participant. Therefore, the respective end of the communication link is not forked.12.3 Hierarchies of ConversationsBesides communications, it is also possible to use sub-conversations. Similar to sub-processes they are marked with a ‘+’-sign. The details of a sub-conversation can be described in another conversation diagram. The diagram of a sub-conversation can only contain those participants who are linked to the sub-conversation within the parent diagram.Figure 171 shows the detailed conversation diagram for the sub-conversation “Process Order for Advertisement”As can be seen from this diagram, it is also possible to draw message flows directly into the conversation diagram. Other than collaboration diagrams, conversation diagrams are not allowed to show processes in the pools or choreographies between the pools.Figure 171: Conversation diagram for sub-conversation “Process Order for Advertisement”The diagram contains those message flows that are related to the same order. To be more precise, they relate to the same inquiry. At the beginning, an order has not been placed yet, and not every inquiry turns into an order. Therefore, the common reference point is the inquiry.Besides the explicitly displayed message flows between customer and advertising agency, the diagram also contains the communication “Assignment of Graphics Design”. All message flows of this communication are also related to the same inquiry, but this information is not sufficient for the advertising agency in order to assign all incoming messages correctly. This is due to the fact that availability requests are sent to several designers. The advertising agency has to correctly assign each incoming availability notice to the correct availability request. Thus, additional information is required for correlating these messages, e.g. the IDs of the availability requests.Therefore it is possible to define a separate communication for the message flows between advertising agency and designer. The message exchanges of this communication can also be modeled in a collaboration diagram (figure 172) or in a choreography diagram (figure 173). Of course, it is also possible to show the message flows of the entire sub-conversation within a single diagram (figures 161 and 162 in the previous chapter).Figure 172: Collaboration diagram for communication “Assignment of Graphics Design”Like sub-processes, sub-conversations can also be expanded, i.e. the hexagon is enlarged, and the detailed conversation is shown in its interior. However, it is graphically not easy to include, for example, the contents of figure 171 into an expanded sub-conversation in figure 170. Unfortunately, the BPMN specification draft does not contain any examples for expandedsub-conversations either.。
中英文翻译
附录英文原文：Chinese Journal of ElectronicsVo1.15,No.3,July 2006A Speaker--Independent Continuous SpeechRecognition System Using Biomimetic Pattern RecognitionWANG Shoujue and QIN Hong(Laboratory of Artificial Neural Networks，Institute ol Semiconductors，Chinese Academy Sciences，Beijing 100083，China)Abstract—In speaker-independent speech recognition,the disadvantage of the most diffused technology(HMMs，or Hidden Markov models)is not only the need of many more training samples，but also long train time requirement. This Paper describes the use of Biomimetic pattern recognition(BPR)in recognizing some mandarin continuous speech in a speaker-independent Manner. A speech database was developed for the course of study．The vocabulary of the database consists of 15 Chinese dish’s names, the length of each name is 4 Chinese words．Neural networks(NNs)based on Multi-weight neuron(MWN) model are used to train and recognize the speech sounds．The number of MWN was investigated to achieve the optimal performance of the NNs-based BPR.This system, which is based on BPR and can carry out real time recognition reaches a recognition rate of 98.14％for the first option and 99.81％for the first two options to the Persons from different provinces of China speaking common Chinese speech．Experiments were also carried on to evaluate Continuous density hidden Markov models(CDHMM ),Dynamic time warping(DTW)and BPR for speech recognition．The Experiment results show that BPR outperforms CDHMM and DTW especially in the cases of samples of a finite size．Key words—Biomimetic pattern recognition, Speech recogniton,Hidden Markov models(HMMs),Dynamic time warping(DTW)．I．IntroductionThe main goal of Automatic speech recognition(ASR)is to produce a system which will recognize accurately normal human speech from any speaker．The recognition system may be classified as speaker-dependent or speaker-independent．The speaker dependence requires that the system be personally trained with the speech of the person that will be involved with its operation in order to achieve a high recognition rate．For applications on the public facilities，on the other hand，the system must be capable of recognizing the speech uttered by many different people，with different gender，age，accent,etc.,the speaker independence has many more applications，primarily in the general area of public facilities．The most diffused technology in speaker-independent speech recognition is Hidden Markov Models，the disadvantage of it is not only the need of many more training samples，but also long train time requirement．Since Biomimetic pattern recognition(BPR) was first proposed by Wang Shoujue，it has already been applied to object recognition, face identification and face recognition etc.,and achieved much better performance．With some adaptations，such modeling techniques could be easily used within speech recognition too．In this paper，a real-time mandarin speech recognition system based on BPR is proposed，which outperforms HMMs especially in the cases of samples of a finite size．The system is a small vocabulary speaker independent continuous speech recognition one. The whole system is implemented on the PC under windows98／2000／XPenvironment with CASSANN-II neurocomputer.It supports standard 16-bit sound card ．II ．Introduction of Biomimetic Pattern Recognition and Multi —Weights Neuron Networks1． Biomimetic pattern recognitionTraditional Pattern Recognition aims at getting the optimal classification of different classes of sample in the feature space ．However, the BPR intends to find the optimal coverage of the samples of the same type. It is from the Principle of Homology —Continuity ，that is to say ，if there are two samples of the same class, the difference between them must be gradually changed ． So a gradual change sequence must be exists between the two samples. In BPR theory ．the construction of the sample subspace of each type of samples depends only on the type itself ．More detailedly ，the construction of the subspace of a certain type of samples depends on analyzing the relations between the trained types of samples and utilizing the methods of “cov erage of objects with complicated geometrical forms in the multidimensional space”.2．Multi-weights neuron and multi-weights neuron networksA Multi-weights neuron can be described as follows ：12m Y=f[(,,,)]W W W X θΦ-…，,Where ：12m ,,W W W …， are m-weights vectors ；X is the inputvector ；Φis the neuron’s computation function ；θis the threshold ；f is the activation function ．According to dimension theory, in the feature spacen R ，n X R ∈，the function12m (,,,)W W W X Φ…，=θconstruct a (n-1)-dimensional hypersurface in n-dimensional space which isdetermined by the weights12m ,,W W W …，.It divides the n-dimensional space into two parts ．If12m (,,,)W W W X θΦ=…， is a closed hypersurface, it constructs a finite subspace ．According to the principle of BPR,determination the subspace of a certain type of samples basing on the type of samples itself ．If we can find out a set of multi-weights neurons(Multi-weights neuron networks) that covering all the training samples ，the subspace of the neural networks represents the sample subspace. When an unknown sample is in the subspace, it can be determined to be the same type of the training samples ．Moreover ，if a new type of samples added, it is not necessary to retrain anyone of the trained types of samples ．The training of a certain type of samples has nothing to do with the other ones ．III ．System DescriptionThe Speech recognition system is divided into two main blocks. The first one is the signal pre-processing and speech feature extraction block ．The other one is the Multi-weights neuron networks, which performs the task of BPR ．1．Speech feature extractionMel based Campestral Coefficients(MFCC) is used as speech features ．It is calculated as follows ：A ／D conversion ；Endpoint detection using short time energy and Zero crossing rate(ZCR)；Preemphasis and hamming windowing ；Fast Fourier transform ；DCT transform ．The number of features extracted for each frame is 16，and 32 frames are chosen for every utterance ．A 512-dimensiona1-Me1-Cepstral feature vector(1632⨯ numerical values) represented the pronunciation of every word ． 2． Multi-weights neuron networks architectureAs a new general purpose theoretical model of pattern Recognition, here BPR is realized by multi-weights neuron Networks. In training of a certain class of samples ，an multi-weights neuron subNetwork should beestablished ．The subNetwork consists of one input layer ．one multi-weights neuron hidden layer and one output layer. Such a subNetwork can be considered as a mapping 512:F R R →.12m ()min(,,Y )F X Y Y =…，，Where Y i is the output of a Multi-weights neuron. There are m hiddenMulti-weights neurons ．i= 1,2, …,m,512X R ∈is the input vector ．IV ．Training for MWN Networks1． Basics of MWN networks trainingTraining one multi-weights neuron subNetwork requires calculating the multi-weights neuron layer weights ．The multi-weights neuron and the training algorithm used was that of Ref.[4]．In this algorithm ，if the number of training samples of each class is N,we can use2N -neurons ．In this paper ，N=30．12[(,,,)]ii i i Y f s s s x ++=，is a function with multi-vector input ，one scalar quantity output ．2． Optimization methodAccording to the comments in IV.1,if there are many training samples, the neuron number will be very large thus reduce the recognition speed ．In the case of learning several classes of samples, knowledge of the class membership of training samples is available. We use this information in a supervised training algorithm to reduce the network scales ．When training class A ，we looked the left training samples of the other 14 classes as class B ． So there are 30 training samples in set1230:{,,}A A a a a =…，and 420 training samples inset 12420:{,,}B B b b =…，b ．Firstly select 3 samples from A, and we have a neuron ：1123Y =f[(,,,)]k k k a a a x .Let 01_123,=f[(,,,)]A i k k k i A A Y a a a a =，where i= 1,2, (30)1_123Y =f[(,,,)]B j k k k j a a a b ，where j= 1,2,…420；1_min(Y )B j V =,we specify a value r ,0<r<1.If1_*A i Y r V <,removed i a from set A, thus we get a new set (1)A .We continue until the number ofsamples in set ()k Ais(){}k A φ=,then the training is ended, and the subNetwork of class A has a hiddenlayer of1r - neurons.V ．Experiment ResultsA speech database consisting of 15 Chinese dish’s names was developed for the course of study. The length of each name is 4 Chinese words, that is to say, each sample of speech is a continuous string of 4 words, such as “yu xiang rou si”，“gong bao ji ding”，etc ．It was organized into two sets ：training set and test set. The speech signal is sampled at 16kHz and 16-bit resolution ．Table 1．Experimental result atof different values450 utterances constitute the training set used to train the multi-weights neuron networks. The 450 ones belong to 10 speakers(5 males and 5 females) who are from different Chinese provinces. Each of the speakers uttered each of the word 3 times. The test set had a total of 539 utterances which involved another 4 speakers who uttered the 15 words arbitrarily ．The tests made to evaluate the recognition system were carried out on differentr from 0.5 to 0.95 with astep increment of 0.05.The experiment results at r of different values are shown in Table 1．Obviously ，the networks was able to achieve full recognition of training set at any r ．From the experiments ，it was found that0.5r achieved hardly the same recognition rate as the Basic algorithm. In the mean time, theMWNs used in the networks are much less than of the Basic algorithm. Table 2．Experiment results of BPR basic algorithmExperiments were also carried on to evaluate Continuous density hidden Markov models (CDHMM),Dynamic time warping(DTW) and Biomimetic pattern recognition(BPR) for speech recognition, emphasizing the performance of each method across decreasing amounts of training samples as wellas requirement of train time. The CDHMM system was implemented with 5 states per word.Viterbi-algorithm and Baum-Welch re-estimation are used for training and recognition ．The reference templates for DTW system are the training samples themselves. Both the CDHMM and DTW technique are implemented using the programs in Ref.[11]．We give in Table 2 the experiment results comparison of BPR Basic algorithm ，Dynamic time warping (DTW)and Hidden Markov models (HMMs) method ．The HMMs system was based on Continuous density hidden Markov models(CDHMMs),and was implemented with 5 states per name.VI．Conclusions and AcknowledgmentsIn this paper, A mandarin continuous speech recognition system based on BPR is established.Besides,a training samples selection method is also used to reduce the networks scales. As a new general purpose theoretical model of pattern Recognition，BPR could be used in speech recognition too, and the experiment results show that it achieved a higher performance than HMM s and DTW.References[1]WangShou-jue,“Blomimetic (Topological) pattern recognit ion-A new model of pattern recognition theoryand its application”，Acta Electronics Sinica,(inChinese)，Vo1.30,No.10,PP.1417-1420,2002．[2]WangShoujue，ChenXu，“Blomimetic (Topological) pattern recognition-A new model of patternrecognition theory and its app lication”, Neural Networks,2003.Proceedings of the International Joint Conference on Neural Networks,Vol.3,PP.2258-2262,July 20-24,2003．[3]WangShoujue,ZhaoXingtao,“Biomimetic pattern recognition theory and its applications”，Chinese Journalof Electronics，V0l.13，No.3，pp.373-377,2004．[4]Xu Jian．LiWeijun et a1,“Architecture research and hardware implementation on simplified neuralcomputing system for face identification”，Neuarf Networks，2003．Proceedings of the Intern atonal Joint Conference on Neural Networks，Vol.2,PP.948-952,July 20-24 2003．[5]Wang Zhihai,Mo Huayi et al,“A method of biomimetic pattern recognition for face recognition”,Neural Networks,2003.Proceedings of the International Joint Conference on Neural Networks,Vol.3，pp.2216-2221,20-24 July 2003．[6]WangShoujue,WangLiyan et a1,“A General Purpose Neuron Processor with Digital-Analog Processing”，Chinese Journal of Electornics,Vol.3,No.4,pp.73-75,1994．[7]Wang Shoujue,LiZhaozhou et a1,“Discussion on the basic mathematical models of neurons in gen eralpurpose neuro-computer”，Acta Electronics Sinica(in Chinese),Vo1.29,No.5,pp.577-580,2001．[8]WangShoujue,Wang Bainan,“Analysis and theory of high-dimension space geometry of artificial neuralnetworks”,Acta Electronics Sinica (in Chinese)，Vo1.30，No.1,pp.1-4,2001．[9]WangShoujue,Xujian et a1,“Multi-camera human-face personal identiifcation system based on thebiomimetic pattern recognition”，Acta Electronics Sinica (in Chinese)，Vo1.31,No.1,pp.1-3,2003．[10]Ryszard Engelking,Dimension Theory,PWN-Polish Scientiifc Publishers—Warszawa,1978．[11]QiangHe,YingHe,Matlab Porgramming,Tsinghua University Press，2002．中文翻译：电子学报2006年7月15卷第3期基于仿生模式识别的非特定人连续语音识别系统王守觉秦虹（中国，北京100083，中科院半导体研究所人工神经网络实验室）摘要：在非特定人语音识别中，隐马尔科夫模型（HMMs）是使用最多的技术，但是它的不足之处在于：不仅需要更多的训练样本，而且训练的时间也很长。
人教版高中英语课文原文与翻译参考
⼈教版⾼中英语课⽂原⽂与翻译参考⼈教版⾼中英语课⽂原⽂与翻译参考 ⾼中英⽂课⽂⼀《⼈教版⾼中英语课⽂原⽂和翻译》 ANNE’S BEST FRIEND Do you want a friend whom you could tell everything to, like your deepest feelings and thoughts? Or are you afraid that your friend would laugh at you, or would not understand what you are going through? Anne Frank wanted the first kind, so she made her diary her best friend. 安妮最好的朋友 你想不想有⼀位⽆话不谈能推⼼置腹的朋友？或者你会不会担⼼你的朋友会嘲笑你，会不理解你⽬前的困境呢？安妮?弗兰克想要的是第⼀种类型的朋友，所以她把的⽇记视为⾃⼰最好的朋友。
Anne lived in Amsterdam in the Netherlands during World War II. Her family was Jewish so the had to hide or they would be caught by the German Nazis. She and her family hide away for two years before they were discovered. During that time the only true friend was her diary. She said, “I don’t want to set down a series of facts in a diary as most people do, but I want this diary itself to be my friend, and I shall call my friend Kitty.” Now read how she felt after being in the hiding place since July 1942. 在第⼆次世界⼤战期间，安妮住在荷兰的阿姆斯特丹。
牛津英语必修一课文原文及中文翻译
M1U1S C H O O L l i f e i n t h e U KGoing to a British high school for one year was a very enjoyable and exciting experience for me. I was very happy with the school hours in Britain because school starts around 9 a later than usual as schools in China begin before 8 a.m.On the first day, all of the new students attended an assembly in the school hall. I sat next to a girl whose name is Diane. We soon became best friends. During the assembly, the headmaster told us about the rules of the school. He also told us that the best way to earn respect was to devote oneself to study and achieve high grades. This sounded like my school in China.I had many teachers in the past year. Mr. Heywood , my class teacher, was very helpful. My favorite teacher was Miss Burke—I loved the lessons that she gave in English Literature. In our class there were 28 students. This is about the average size for British schools. We had to move to different classrooms for different classes. We also had different students in some classes, so it was a struggle for me to remember all the faces and names.I found the homework was not as heavy as what I used to get in my old school, but it was a bit challenging for me at firs t because all the homework was in English. I felt lucky as all my teachers gave me much encouragement and I enjoyed all my subjects: English, History, English Literature, Computer Science, Maths, Science, PE, Art, Cooking and French.My English improved a lot as I used English every day and spent an hour each day reading English books in the library.I usually went to the Computer Club during the lunch break, so I could send e-mails to my family and friends back home for free. I also had an extra French class on Tuesday evenings. Cooking was really fun as I learned how to buy, prepare and cook food. At the end of term we held a class party and we all had to cook something. I was glad that all my classmates were fond of the cake that I made.Students at that school have to study Maths, English and Science, but can stop studying some subjects if they don’t like them, for example, History and French. They can choose other subjects like Art and Computer Science or Languages such as Spanish and German. In the Art class that I took, I made a small sculpture. Though it didn’t look very beautiful when it was finished, I still liked it very much.I missed Chinese food a lot at lunch. British food is very different. British people like eating dessert at the end of their main meal. After lunch, we usually played on the school field. Sometimes I played football with the boys. Sometimes I just relaxed under a tree or sat on the grass.I was very lucky to experience this different way of life. I look back on my time in the UK with satisfaction, and I really hope to go back and study in Manchester again.在英国的学校生活在英国上了一年的中学对我来说是一段非常令人愉快和兴奋的经历。
朱自清荷塘月色英文版
朱自清《荷塘月色》英文版著名作家朱自清的散文《荷塘月色》想必大家已经在语文课上学过。
现在大家来看看它的英文翻译吧，看译文读起来的感觉如何。
原文：这几天心里颇不宁静。
今晚在院子里坐着乘凉，忽然想起日日走过的荷塘，在这满月的光里，总该另有一番样子吧。
月亮渐渐地升高了，墙外马路上孩子们的欢笑，已经听不见了；妻在屋里拍着闰儿，迷迷糊糊地哼着眠歌。
我悄悄地披了大衫，带上门出去。
沿着荷塘，是一条曲折的小煤屑路。
这是一条幽僻的路；白天也少人走，夜晚更加寂寞。
荷塘四面，长着许多树，蓊蓊郁郁的。
路的一旁，是些杨柳，和一些不知道名字的树。
没有月光的晚上，这路上阴森森的，有些怕人。
今晚却很好，虽然月光也还是淡淡的。
路上只我一个人，背着手踱着。
这一片天地好像是我的；我也像超出了平常的自己，到了另一世界里。
我爱热闹，也爱冷静；爱群居，也爱独处。
像今晚上，一个人在这苍茫的月下，什么都可以想，什么都可以不想，便觉是个自由的人。
白天里一定要做的事，一定要说的话，现在都可不理。
这是独处的妙处，我且受用这无边的荷香月色好了。
曲曲折折的荷塘上面，弥望的是田田的叶子。
叶子出水很高，像亭亭的舞女的裙。
层层的叶子中间，零星地点缀着些白花，有袅娜地开着的，有羞涩地打着朵儿的；正如一粒粒的明珠，又如碧天里的星星，又如刚出浴的美人。
微风过处，送来缕缕清香，仿佛远处高楼上渺茫的歌声似的。
这时候叶子与花也有一丝的颤动，像闪电般，霎时传过荷塘的那边去了。
叶子本是肩并肩密密地挨着，这便宛然有了一道凝碧的波痕。
叶子底下是脉脉的流水，遮住了，不能见一些颜色；而叶子却更见风致了。
月光如流水一般，静静地泻在这一片叶子和花上。
薄薄的青雾浮起在荷塘里。
叶子和花仿佛在牛乳中洗过一样；又像笼着轻纱的梦。
虽然是满月，天上却有一层淡淡的云，所以不能朗照；但我以为这恰是到了好处——酣眠固不可少，小睡也别有风味的。
月光是隔了树照过来的，高处丛生的灌木，落下参差的斑驳的黑影，峭楞楞如鬼一般；弯弯的杨柳的稀疏的倩影，却又像是画在荷叶上。
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南京师范大学泰州学院英文翻译原文年级： 2011级学号：12110330 姓名：申佳佳系部：信息工程学院专业：通信工程题目：基于C51的数字测速仪设计与仿真指导教师：焦蓬蓬2015 年 4 月 5 日Linux - Operating system of cybertimesThough for a lot of people , regard Linux as the main operating system to make u p huge work station group, finish special effects of " Titanic " make , already can be re garded as and show talent fully. But for Linux, this only numerous news one of. Rece ntly, the manufacturers concerned have announced that support the news of Linux to i ncrease day by day, users' enthusiasm to Linux runs high unprecedentedly too. Then, Linux only have operating system not free more than on earth on 7 year this piece wh at glamour, get the favors of such numerous important software and hardware manufa cturers as the masses of users and Orac le , Informix , HP , Sybase , Corel , Intel , Net scape , Dell ,etc. , OK?1.The background of Linux and characteristicLinux is a kind of " free (Free ) software ": What is called free, mean users can o btain the procedure and source code freely , and can use them freely , including revise or copy etc.. It is a result of cybertimes, numerous technical staff finish its research a nd development together through Inte rnet, countless user is it test and except fault , c an add user expansion function that oneself make conveniently to participate in. As the most outstanding one in free software, Linux has characteristic of the following:(1)Totally follow POSLX standard, expand the network operating system of sup porting all AT&T and BSD Unix characteristic. Because of inheritting Unix outstandi ng design philosophy , and there are clean , stalwart , high-efficient and steady kernels , their all key codes are finished by Li nus Torvalds and other outstanding programmer s, without any Unix code of AT&T or Berkeley, so Linu x is not Unix, but Linux and Unix are totally compatible. (2)Real many tasks, multi-user's system, the built-in n etwork supports, can be with such seamless links as NetWare , Windows NT , OS/2 , Unix ,etc.. Network in various kinds of Unix it tests to be fastest in comparing and ass ess efficiency. Support such many kinds of files systems as FAT16 , FAT32 , NTFS , E x t2FS , ISO9600 ,etc. at the same time .(3) Can operate it in many kinds of hardwares platform , including such processo rs as Alpha , SunSparc , PowerPC , MIPS ,etc., to various kinds of new-type periphera l hardwares, can from distribute on global numerous programmer there getting suppor t rapidly too.(4) To that the hardware requires lower, can obtain very good performance on mo re low-grade machine , what deserves particular mention is Linux outstanding stability , permitted " year " count often its running times.2.Main application of Linux At present,Now, the application of Linux mainly includes:(1) Internet/Intranet: This is one that Linux was used most at present, it can offer andinclude Web server , all such Inter net services as Ftp server , Gopher server , SM TP/POP3 mail server , Proxy/Cache server , DNS server ,etc.. Linux kernel supports I Palias , PPP and IPtunneling, these functions can be used for setting up fictitious host computer , fictitious service , VPN (fictitious special-purpose network ) ,etc.. Operatin g Apache Web server on Linux mainly, the occupation rate of market in 1998 is 49%, far exceeds the sum of such several big companies as Microsoft , Netscape ,etc..(2) Because Linux has outstanding networking ability , it can be usedin calculati ngdistributedly large-scaly, for instance cartoon making , scientific caculation , database and file server ,etc..(3) As realization that is can under low platform fullness of Unix that operate , ap ply at all levels teaching and research work of universities and colleges extensively, if Mexico government announce middle and primary schools in the whole country dispo se Linux and offer Internet service for student already.(4) Tabletop and handling official business appliedly. Application number of peo ple of in this respect at present not so good as Windows of Microsoft far also, reason i ts lie in Lin ux quantity , desk-top of application software not so good as Windows ap plication far not merely, because the characteristic of the freedom software makes it n ot almost have advertisement that support (though the function of Star Office is not second to MS Office at the same time, but there are actually few people knowing).3.Can Linux become a kind of major operating system?In the face of the pressure of coming from users that is strengthened day by day, more and more commercial companies transplant its application to Linux platform, co mparatively important i ncident was as follows, in 1998.(1)Compaq and HP determine to put forward user of requirement truss up Linux at their servers , IBM and Dell promise to offer customized Linux system to user too.(2)Lotus announce, Notes the next edition include one special-purpose edition in Linux.(3)Corel Company transplants its famous WordPerfect to on Linux, and free issue. Corel also plans to move the other figure pattern process products to Linux platfor m completely.(4)Main database producer: Sybase , Informix , Oracle , CA , IBM have already been transplanted one's own database products to on Linux, or has finished Beta editio n, among them Oracle and Informix also offer technical support to their products.4.The gratifying one is, some farsighted domestic corporations have begun to try hard to change this kind of current situation already. Stone Co. not long ago is it inves t a huge sum of money to claim , regard Linux as platform develop a Internet/Intranet solution, regard this as the core and launch Stone's system integration business , plan t o set up nationwide Linux technical support organization at the same time , take the le ad to promote the freedom software application and development in China. In additio n domestic computer Company , person who win of China , devoted to Linux relevant software and hardware application of system popularize too. Is it to intensification th at Linux know , will have more and more enterprises accede to the ranks that Linux w ill be used with domestic every enterprise to believe, more software will be planted in Linux platform. Meanwhile, the domestic university should regard Linux as the origin al version and upgrade already existing Unix content of courses , start with analysing t he source code and revising the kernel and train a large number of senior Linux talent s, improve our country's own operating system. Having only really grasped the operati ng system, the software industry of our country could be got rid of and aped sedulously at present, the passive state led by the nose by others, create conditions for revitalizi ng the software industry of our country fundamentally.。