Questions_Answers_Webinar_SAMA5D4_internal_July_21

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Answer英语答案

Answer英语答案习题参考答案第1章填空题：1. 计算理论、计算机、信息处理2. 算法设计和程序设计3. 有限性、可执⾏性、机械性、确定性、终⽌性4. 有确定的算法5. ⼆进制6. 在给定相同的输⼊时，A和B有相同的输出、A和B计算等价7. 存储器8. 电⼦管和继电器9. 光计算机、⽣物计算机、量⼦计算机10. 巨型化、微型化、⽹络化、智能化11. ASCII码，712. 213. bmp, jpg14. ⽂字15. 时间和幅值16. ⽂件，数据库17. ⽩盒，⿊盒18. 是⼀种⽆处不在的计算模式简答题：1.简述计算机采⽤⼆进制的原因。

（1）⼆进制只有0和1两个基本符号（2）⼆进制的算术运算规则简单，且适合逻辑运算。

2. 图灵机模型主要由哪4个部分组成？⼀条⽆限长的纸带，⼀个读写头，⼀套控制规则，⼀个状态寄存器。

3．图灵机在形式上可以⽤哪七个元素描述？它们分别表⽰什么含义？(参考教材p7回答) 4．图灵机模型中的四个要素是什么？输⼊信息，输出信息、程序（规则）、内部状态。

5．简述图灵机的⼯作过程。

图灵机的⼯作过程可以简单的描述为：读写头从纸带上读出⼀个⽅格中的信息，然后根据它内部的状态对程序进⾏查表（规则表Table），得出⼀个输出动作，确定是向纸带上写信息还是使读写头向前或向后移动到下⼀个⽅格。

同时，程序还会说明下⼀时刻内部状态转移到哪⾥。

6. 简述问题求解的⼀般过程。

需求分析，系统（模型）设计，编码与调试，系统测试。

7 .简述基于计算机的信息处理的⼀般过程。

信息采集，信息的表⽰和压缩，信息存储和组织，信息传输，信息发布，信息检索。

8. 简述⾼性能计算机涉及的主要关键技术。

答：软硬件技术、通信技术、纳⽶技术第2章1．计算机系统主要由（硬件系统）和（软件系统）组成。

2．说明以下计算机中的部件是属于主机系统、软件系统、还是属于外部设备。

（1）CPU （主机系统）（2）内存条（主机系统）（3）⽹卡（主机系统）（4）键盘和⿏标（外设）（5）显⽰器（外设）（6）Windows操作系统（软件系统）3．控制芯⽚组是主板的的核⼼部件，它由（北桥芯⽚）部分和（南桥芯⽚）部分组成。

学术英语理工类课后题答案

Reading: Text 11.Match the words with their definitions.1g 2a 3e 4b 5c 6d 7j 8f 9h 10i2. Complete the following expressions or sentences by using the target words listed below with the help of the Chinese in brackets. Change the form if necessary.1 symbolic 2distributed 3site 4complex 5identify6fairly 7straightforward 8capability 9target 10attempt11process 12parameter 13interpretation 14technical15range 16exploit 17networking 18involve19 instance 20specification 21accompany 22predictable 23profile3. Read the sentences in the box. Pay attention to the parts in bold.Now complete the paragraph by translating the Chinese in brackets. You may refer to the expressions and the sentence patterns listed above.ranging from（从……到）arise from some misunderstandings（来自于对……误解）leaves a lot of problems unsolved（留下很多问题没有得到解决）opens a path for（打开了通道）requires a different frame of mind（需要有新的思想）4.Translate the following sentences from Text 1 into Chinese.1) 有些人声称黑客是那些超越知识疆界而不造成危害的好人（或即使造成危害，但并非故意而为），而“骇客”才是真正的坏人。

关于网上搜索答案我的看法英语作文

关于网上搜索答案我的看法英语作文In today's digital age, the internet has become an indispensable tool for finding information quickly and easily. With just a few clicks, we can access a wealth of knowledge on any topic we desire. This convenience has made online search engines like Google, Bing, and Yahoo popular choices for students and professionals alike when seeking answers to their questions.However, the practice of using the internet to search for answers raises the question of whether it is considered cheating or not. Some argue that relying on the internet for answers is unethical, as it promotes laziness and discourages critical thinking skills. They believe that individuals should take the time to research and understand the material themselves rather than simply regurgitating information they find online.On the other hand, proponents of online search engines believe that they are valuable tools that can enhance learning and productivity. They argue that in today's fast-paced world, having quick access to information is essential for success. Additionally, they believe that the internet can provide a wide range of perspectives and resources that may not be available through traditional sources.In my opinion, using the internet to search for answers is not inherently good or bad. It ultimately depends on how the information is used. If individuals are using the internet to supplement their learning and gain a deeper understanding of a topic, then it can be a valuable tool. However, if people are relying solely on the internet for answers without critically evaluating the information, then it can be detrimental to their learning and development.As a student, I have found online search engines to be incredibly helpful in my academic pursuits. They have allowed me to access a wide range of resources and perspectives that have enriched my learning experience. However, I also recognize the importance of critical thinking and analysis in evaluating the information I find online. It is essential to verify the credibility of sources and consider multiple viewpoints before drawing conclusions.In conclusion, while online search engines can be valuable tools for finding information quickly and easily, it is important to use them responsibly. It is crucial to supplement online research with critical thinking skills and independent analysis to ensure a well-rounded understanding of a topic. By striking a balance between using the internet as a resource and developing one'sown critical thinking skills, individuals can harness the full potential of online search engines while fostering intellectual growth and development.。

关于上网搜索答案这一现象英语作文

关于上网搜索答案这一现象英语作文Searching for answers on the internet has become a common practice in our daily lives. It's quick, convenient, and often gives us a wide range of perspectives.When I'm stuck on a problem, I'll just type in a few keywords and within seconds, I'm presented with a bunch of articles, videos, and forums discussing the topic. It'slike having a whole library of information at my fingertips.One thing I love about online searching is that it'snot just about finding the right answer. It's aboutexploring different opinions and perspectives. You can find people from all over the world sharing their experiencesand knowledge, which can be really eye-opening.But, of course, there's a downside too. Sometimes, it's hard to separate the reliable information from the noise. Fake news and misinformation are everywhere, so you really have to be careful when you're looking for answers online.Overall, though, I think the internet has made it easier for us to access knowledge and learn new things. We can find answers to almost any question, anytime, anywhere. It's a pretty amazing tool, if you use it wisely.。

网上搜答案之我见英语作文

网上搜答案之我见英语作文Searching for answers online, it's a double-edged sword, really. On one hand, the convenience is undeniable. Just a few taps on a keyboard and you have access to a vast oceanof knowledge. But on the other, it's like a maze wheretruth and fiction blend.I mean, sometimes I find answers so quickly, it'salmost magical. But then there are times when I'm not sureif I should trust the source. You know, like those blog posts that sound convincing but who knows if the author's really an expert?Plus, there's this temptation to just copy and paste.I've been there, done that, and regretted it later. Teachers can always spot when something's not your own words. So, yeah, I've learned to be more careful.The best part, though, is that it opens up a whole new world of learning. I've discovered so many interestingtopics and perspectives just by browsing through forums and discussions. It's like a never-ending adventure.But I also think it's important to remember that online isn't the only source of knowledge. There's still a placefor books, libraries, and real-life experts. After all, nothing beats having a conversation with someone who's passionate about a subject.So in conclusion, searching for answers online is great, but it should be done with caution. Don't be afraid to.。

大一英语ismart测试答案

大一英语ismart测试答案1、---Excuse me sir, where is Room 301?---Just a minute. I’ll have Bob ____you to your room. [单选题] *A. show(正确答案)B. showsC. to showD. showing2、We have made a _______ tour plan to Sydney. [单选题] *A. two dayB. two daysC. two-day(正确答案)D. two-days3、Where have you _______ these days? [单选题] *A. been(正确答案)B. beC. isD. are4、--Can I _______ your dictionary?--Sorry, I’m using it. [单选题] *A. borrow(正确答案)B. lendC. keepD. return5、Seldom _____ in such a rude way. [单选题] *A.we have been treatedB. we have treatedC. have we been treated(正确答案)D. have treated6、The street was named _____ George Washington who led the American war for independence. [单选题] *A. fromB. withC. asD. after(正确答案)7、5 He wants to answer the ________ because it is an interesting one. [单选题] *A．problemB．question(正确答案)C．doorD．plan8、—______ is it from your home to the bookstore?—About 15 kilometers.（）[单选题] *A. How far(正确答案)B. How muchC. How longD. How many9、Boys and girls, _______ up your hands if you want to take part in the summer camp(夏令营)．[单选题] *A. puttingB. to putC. put(正确答案)D. puts10、Jim is a(n) _______. He is very careful and likes to work with numbers. [单选题] *A. secretaryB. tour guideC. accountant(正确答案)D. English teacher11、Mary's watch is more expensive than _____. [单选题] *A. Susan's(正确答案)B. that of Susan'sC. that of SusanD. Susan12、I can’t hear you _______. Please speak a little louder. [单选题] *A. clearly(正确答案)B. lovelyC. widelyD. carelessly13、—When are you going to Hainan Island for a holiday? —______ the morning of 1st May.（）[单选题] *A. InB. AtC. On(正确答案)D. For14、He didn't allow _____ in his room. Actually he didn't allow his family _____ at all. [单选题] *A. to smoke; to smokeB. smoking; to smoke(正确答案)C. to smoke; smokingD. smoking; smoking15、97．Go ______ the square and you will find the theatre. [单选题] *A．aboveB．atC．across(正确答案)D．on16、Jim, it’s dark now. Please _______ the light in the room. [单选题] *A. turn on(正确答案)B. turn upC. turn offD. turn down17、16．We asked ______ engineer we met before to help repair the radio yesterday. [单选题] *A．aB．anC．the(正确答案)D．/18、He doesn’t smoke and hates women _______. [单选题] *A. smokesB. smokeC. smokedD. smoking(正确答案)19、Sam is going to have the party ______ Saturday evening. （）[单选题] *A. inB. on(正确答案)C. atD. to20、73．The moonlight goes ____ the window and makes the room bright. [单选题] * A．acrossB．through(正确答案)C．overD．in21、6．—How can we get to the school?—________ bus. [单选题] *A．ToB．OnC．By(正确答案)D．At22、27．My father is a professor and he works in__________ university. [单选题] * A．a (正确答案)B．anC．/D．the23、—______?—He can do kung fu.（）[单选题] *A. What does Eric likeB. Can Eric do kung fuC. What can Eric do(正确答案)D. Does Eric like kung fu24、He _______ maths. [单选题] *A. does well in(正确答案)B. good atC. is well inD. does well at25、We had a(an)_____with him about this problem last night. [单选题] *A.explanationB.impressionC.exhibitionD.discussion(正确答案)26、The hall in our school is _____ to hold 500 people. [单选题] *A. big enough(正确答案)B. enough bigC. very smallD. very big27、Kids will soon get tired of learning _____ more than they can. [单选题] *A. if they expect to learnB. if they are expected to learn(正确答案)C. if they learn to expectD. if they are learned to expect28、The man called his professor for help because he couldn’t solve the problem by _______. [单选题] *A. herselfB. himself(正确答案)C. yourselfD. themselves29、He _______ walks to school, because he lives near school. [单选题] *A. sometimes(正确答案)B. neverC. doesn’tD. don’t30、I will _______ at the school gate. [单选题] *A. pick you up(正确答案)B. pick up youC. pick you outD. pick out you。

Learning to Extract Answers in Question Answering Experimental Studies

ABSTRACT.Question Answering(QA)systems are complex programs able to answer a question in natural language.Their source of information is a given corpus or,as assumed here,the Web.To achieve their goal,these systems perform various subtasks among which the last one, called answer extraction,is very similar to an Information Extraction task.The main objective of this study it to adapt machine learning techniques deﬁned for Information Extraction tasks to the slightly different task of answer extraction in QA systems.The speciﬁcities of QA sys-tems are identiﬁed and exploited in this adaptation.Three algorithms,assuming an increasing abstraction of natural language texts,are tested and compared.RÉSUMÉ.Les systèmes Question/Réponse sont des programmes complexes capables de répondre àune question en langage naturel,en utilisant comme source d’information soit un corpus donné,soit,comme c’est le cas ici,le Web.Pour cela,ces systèmes réalisent différentes sous-tâches parmi lesquelles la dernière,appelée extraction de la réponse,est très similaireàune tâche d’Extraction d’Information.L’objectif de cet article est d’adapter les techniques d’ap-prentissage automatique utilisées en Extraction d’Informationàl’extraction de la réponse.Les spéciﬁcités des systèmes Question/Réponse sont identiﬁées et utilisées dans cette adaptation. Trois algorithmes utilisant une abstraction croissante du texte sont testés et comparés. KEYWORDS:Question Answering,Machine Learning,Information ExtractionMOTS-CLÉS:Systèmes Question-Réponse,Extraction d’information,Apprentissage automatique1.This research was partially supported by:“CPER2000-2006,Contrat de Planétat-région Nord/Pas-de-Calais:axe TACT,projet TIC”;fonds européens FEDER“TIC-Fouille Intelli-gente de données-Traitement Intelligent des Connaissance”OBJ2-phasing out-2001/3-4.1 -n3.2.www.grappa.univ-lille3.fr2CORIA’05.1.IntroductionQuestion answering(QA)systems are complex systems that,given a question asked in natural language,canﬁnd an answer to this question,in a corpus or in the Web,and justify it by quoting their source(s).From the user’s point of view,they can be considered as an improvement over traditional search engines such as Google or AltaVista because they provide a more direct and precise access to the desired information.The counterpart is thatﬁnding the correct answer to a question requires much more analysis and processing than a typical search engine.Traditionally,a Question Answering system is divided into three steps:question analysis,passage retrieval and answer extraction.Our focus will be on the last task (answer extraction)which can be compared with an Information Extraction(IE)task. The purpose of IE is to automaticallyﬁll a database from a corpus of texts in natural language or semi-structured data from the Web.IE is an active research area in which many improvements have been made recently.Among them,we are particularly in-terested in machine learning techniques and techniques that deal with internet data sources[SOD99,KUS02,CAR04].Our objective is to improve the answer extraction task in QA systems on the Web by using insights provided by recent machine learning techniques developed for IE. Some speciﬁcities of QA systems can be useful here.As a matter of fact,in QA systems,theﬁrst steps of the process give hints that can help the answer extraction. Unlike in IE,we can take advantage of the outcomes of these steps.We focus our study on using common outcomes of the question analysis step:the class of the ques-tion and the keyword(s).To summarize,in this paper,we experimentally study how to use machine learning techniques developed for IE in answer extraction,taking into account QA systems speciﬁcities.We propose several ways to adapt existing IE algo-rithms,mainly differing by the document representation they adopt.We have built a dataset to evaluate and analyze several alternatives.This dataset if freely available on.Our ex-periments deal with various encodings and three machine learning algorithms.The ﬁrst algorithm,suggested by[RA V02],applies on raw text.It relies on a document representation that is a sequence of token values(a token is either a word or a punc-tuation symbol)and builds extraction patterns by searching for the largest common subsequences of tokens present around the answer.RAPIER,deﬁned by[CAL98], is the second tested algorithm.It exploits deeper information about the documents, including part of speech tags,and elaborates complex extraction rules using both to-ken values and POS tags.The third one is PAF developed in the Mostrare group [MAR04].PAF relies on supervised classiﬁcation and is veryﬂexible from the docu-ment representation point of view.In our experiments with PAF,token values are not used but only token types(POS tag,punctuation,case,...)and simple numerical fea-tures computable from the texts(lengths,etc.).These three algorithms are worth being compared because they make very different assumptions on how to represent a text inLearning to Extract Answers in QA3 natural language.The representations used correspond to three levels of abstraction. For each algorithm,we also study the inﬂuence of using the keyword information.The next section in an overview of QA systems.We present our experiments and our analysis in Section3.2.Overview of Question Answering SystemsAlthough theﬁrst works in this researchﬁeld go back to the1960s and1970s with the works of[GRE61],[WOO73]and[LEH78],Question Answering systems became popular in the late1990s.This emergence was encouraged by the TREC-8 conference in1999,where a QA track[VOO99]was initiated and where theﬁrst large-scale evaluation of such systems took place.This evaluation led to a consen-sus on the general architecture of a QA system.Now,every QA system performs three successive tasks:question analysis,information retrieval and answer extraction. Although we will mainly focus on the third one,we introduce each of them and the assumptions made at each step,to justify our own choices.We also brieﬂy review previous attempts to introduce machine learning techniques in QA systems.2.1.Question AnalysisFirst,an analysis of the question is performed,its goal being to extract the infor-mation needed to perform the next two steps from the question.In all systems,the result is at least a classiﬁcation of the question into a class.The set of possible classes is predeﬁned,and ranges from few basic sets only depending on theﬁrst word of the question(“where”,“when”,etc.)to veryﬁne sets of hierarchical classes.But this information alone is not precise enough to directly allow to answer the question.So,another goal of this task is usually to extract words giving crucial in-formation about the subject of the question.The notion of“focus”is often employed. We prefer to use the term keywords.A keyword is a word or a sequence of words. The number of keywords to be extracted from a question depends on its class.For example,in the question“When was W.A.Mozart born?”,the question class can be and the only keyword needed is“W.A.Mozart”.So,the classis of arity1,meaning that only one keyword must be given with the class to specify a unique answer.This very precise class could easily be replaced by a less precise one,for example,but with two keywords:“W.A.Mozart”and“born”.In the following,the assumption is made that the couple(question class,keywords) is a synthetic representation of the question and that this representation is necessary and sufﬁcient to correctly answer the question.Some systems keep more precise a track of the initial question,such as AskMSR[BRI02],including syntactic features. We do not pretend that a syntactic analysis is useless,for example to distinguish“Who killed Lee Harvey Oswald?”from“Who did Lee Harvey Oswald kill?”.But the difference between both sentences can be reﬂected in different class assignments.The4CORIA’05.ﬁrst question’s representation could be(,Lee Harvey Oswald)while the second one’s could be(,Lee Harvey Oswald).These couples(questionclass,keywords)are the essential QA-speciﬁc data that will be used to perform the next steps.rmation RetrievalThen,QA systems perform an IR task whose objective is to build a limited corpus of relevant documents,i.e.portions of texts in which the answer is very likely to befound.The purpose of this step is to reduce the search space of the next step.Selected passages must be long enough to contain the answer and some useful context.Butwhen using the Web as a corpus,which is the case here,it is impossible to apply NLP techniques on the corpus beforehand.Therefore,the selected passages should not be too long,to be able to perform various NLP techniques such as POS tagging without dramatically increasing processing time.2.3.Answer ExtractionFinally,the last task to be performed is the extraction of all candidate answers from the set of extracted passages.Due to the difﬁculty of the whole QA task,the candidate answers are then ranked to get the top5answers.This task is very similar to the one of Information Extraction,which consists inﬁlling a database(whose structure is known)from natural language texts.In answer extraction,the answer can be considered as the(unique)piece of data to be extracted,and the question class represents its type.Document representation plays a critical role in Information Extraction,hence alsoin answer extraction.Texts are usually considered as sequences of tokens,a token being either a word or a punctuation symbol.POS tags are often added to each token, and sometimes even syntactic structures are taken into account[LIG04].Externalresources like named entity recognizers or semantic information(such as Wordnet) can also be exploited[POI03].In our study,only POS tags and simple numerical descriptions computable from the texts(length,number of occurrences,etc.)will beused,in order to have a reasonable computation time.An important question to consider is the representation of the keyword itself insidethe passage.It is intuitively efﬁcient to abstract it,that is to forget its value and replace it by either a type or a description that indicates“a part of text that containsthe keyword”.For example,in the question“When was Mozart born?”,the question keyword is“Mozart”.Abstracting it by a tag“ ”in documents allows to generate extraction rules like“ was born in ”rather than“Mozart was born in ”.This seems much better because it is more generic,as it is correct for the other questions of the same class.One of our purposes is to test theefﬁciency of this abstraction.Learning to Extract Answers in QA5 The extraction itself is usually performed by hand-made patterns which describe the possible contexts in which the answer can occur.A set of patterns is associated with every question class.And,of course,the patterns themselves often include the abstracted keyword.But the extraction cannot always be described in terms of patterns.One of the techniques we use is based on decision trees.Similarly,some question answering sys-tems,such as Javelin[NYB03],choose among different approaches(SVM,statistical extraction,patterns,etc.)depending on the question class in order to maximize their system’s performances.Finally,to rank the candidate answers,a conﬁdence score is calculated.The score of a candidate answer can rely on its frequency,on its type(using a named entity tagger),as in[ABN00].This score can also rely on the proximity of the keyword(s), but this won’t be the case in the following.2.4.Machine Learning and QA systemsIt is only recently that several attempts to introduce machine learning techniques to help process some of the tasks of a QA system have appeared.The advantages of introducing such techniques are obvious.The building of hand-made patterns used in question analysis and answer extraction tasks is long and fastidious.Learning them automatically would certainly be easier.Furthermore,employing learning techniques is the best way to automatically adapt a QA system to some speciﬁcities,such as:the language used(hand-made patterns are language-speciﬁc)and the domain of special-ity(some patterns may also be speciﬁc to a domain)for specialized corpora.Most of previous works trying to combine machine learning and QA focused on theﬁrst steps,for example on learning to automatically classify a question,or learn-ing to locate and expand the keywords in the question in order to generate queries [USU04].To our knowledge,theﬁrst attempt to learn answer extraction patterns was the one of[RA V02],using alignment learning with sufﬁx trees.But,we have seen that the answer extraction task shares many features with the IE task.In this domain,several machine learning techniques have been proposed.Our purpose is to adapt some of them to answer extraction,and to analyze their efﬁciency in this context.3.ExperimentsThe main objective of this section is to use IE learning algorithms for answer ex-traction,and to evaluate the interest of using the keyword in those algorithms to make them more QA oriented.We will use three radically different IE learning algorithms. To evaluate the performances of the extraction rules learnt for each question class by these algorithms,we build a data set from documents provided by Google.We adapt6CORIA’05.the protocol proposed by[RA V02]by making clearer the evaluation protocol,intro-ducing QA cross-checking,in the spirit of standard machine learning cross validation.3.1.Building the corpusAs we did not develop a complete QA system,the question analysis step is not implemented but only simulated.The experiments we make are based on only two predeﬁned classes:and,both of arity1.The inputs of our programs are thus couples(question class,keyword),which are supposed to correctlyrepresent the initial questions.is supposedly an easy question class be-cause of its very speciﬁc aspect,whereas is considered more difﬁcult,since it includes localisation of towns,sites,lakes,etc.For each class,we choose100distinct keywords.Each keyword is associated witha list of all its valid answers,called Answers.For example,the question(,“Danube”)has several valid answers,such as"Hungary","Austria",etc.Input:the set S of keyword/Answers couples.1:Corpus=∅2:for each couple(keyword,Answers)in S do3:Documents=top100documents retrieved by Google containing both keyword and at least one answer∈Answers4:for each document in Documents do5:for each answer in Answers do6:Let s be the smallest passage containing both keyword and answer7:Let s2be s with surrounding context(50characters)from document 8:tokenize(s2)9:Add s2to Corpus10:end for11:end for12:end forOutput:CorpusLearning to Extract Answers in QA7 a valid answer are selected,leaving some context(50characters)before and after this passage.For example,if the text is“the great composer Ludwig V on Beethoven was born in1770in Bonn,Germany.”,the selected passage is something like“great composer Ludwig V on Beethoven was born in1770in Bonn”(the context is in italics).The next step consists in tokenizing these passages to match our document rep-resentation.A document is considered as a sequence of tokens.As already stated,a token is either a word or a punctuation symbol.Spaces,tabulations,line feed,etc.are not considered as tokens but as token delimiters and hence are not taken into account.The opportunity to realize abstraction of the keyword as presented in Section2.3 leads us to build two versions of each corpus.Finally,document preparation as well as the way to use the keyword differ with the choice of the learning algorithm.3.2.Evaluation protocol:QA cross-checkingIn order to evaluate the performance of the rules learnt by each tested algorithm, with or without using the keyword,we deﬁne a new evaluation protocol,inspired by machine learning cross-validation,and independent of the learning algorithm.Because of the way we built the learning corpus,it is mandatory to build a new separate testing corpus.Indeed,if we separated the corpus built as described in the previous section into two distinct parts,a learning corpus and a testing corpus,a typ-ical cross validation technique could be applied.But this corpus is exclusively made of passages containing both the keyword and a valid answer.So,the results obtained would necessarily differ from the ones obtained in a real QA process,where the pas-sages extracted in the information retrieval step are selected without knowing the an-swer,and hence contain the keyword but not necessarily a valid answer.To avoid this cheat,a new testing corpus must be built.Building the testing corpus is quite similar to building the learning corpus.We only change two aspects of algorithm1.First,for each question,we send Google a query consisting of the keyword alone.Second,the keyword is used to retrieve small passages.In each document,the selected passages areﬁxed-sized windows around all the occurrences of the keyword.The window size is clearly a parameter to adjust. Roughly,larger is the window,better is the recall but worst is the precision.We have made experiments with several window sizes that conﬁrm this intuition.The results presented here are for a window size of200characters before and after the keyword.Finally,the complete evaluation protocol is given in algorithm2.We have two corpora,the learning corpus L and the testing corpus T,built from a set S of100 (keyword,Answers)couples c0to c99.In both corpora,each passage is associated to a couple.Hence,each corpus is divided into10parts:l0to l9for the learning corpus,and t0to t9for the testing corpus,each part i containing passages associated to10couples c10i to c10i+9.This way we build a partition of our corpora.Then10 iterations are performed.In each iteration k,extraction rules are learnt on L\l k,and8CORIA’05.Input:S={c j|j∈[0,99]},the set of keyword/Answers couples.L,the learning corpus.T,the testing corpus.1:Build the partition of L={l i|i∈[0,9]},where l i is the set of passages of L corresponding to the keyword/Answers couples c10i to c10i+92:Build the partition of T={t i|i∈[0,9]},where t i is the set of passages of T corresponding to the keyword/Answers couples c10i to c10i+93:for i from0to9do4:Rules=Learn(L\l i).5:for each c j represented in t i do6:Apply Rules on the passages of t i corresponding to c j.7:Rank the extracted candidate answers.8:RR j=Reciprocal Rank of the correct answer.9:end for10:end forOutput:MRR=Mean of the RR j2.The MRR is themean of these scores.To evaluate whether an extracted answer is correct,we perform an“exact match”evaluation,i.e.an extracted answer is considered correct if it is iden-tical to the correct answer.For example,if the expected answer is"Paris","paris"will be considered as correct,but"in Paris"will not.Moreover,for each question,only the best ranked correct answer counts.For example,if the expected correct answers are "Paris"or"France",and the system has extracted"Paris","Lille"and"France",the correct extracted answer"France"won’t count since"Paris"has also been extracted and ranked higher.3.2.1.StatisticsTable1shows statistics on our learning and testing corpora.Every passage of the learning corpus contains both the keyword and at least one correct answer,whereas every passage of the testing corpus contains the keyword and hopefully the answer,but it is not compulsory.In each iteration of our evaluation with questions, we learn on approximately1900annotated passages and test on appromimately2900 passages,while with questions,we learn on3000annotated passages and test on2000passages.Learning to Extract Answers in QA9 We can also notice that only93questions have at least one correspond-ing passage in the testing corpus containing the correct answer.Therefore,7questions will not be answered in the answer extraction step.3374207275546one passage with a correct answer100/100Algorithm3Alignment Learning Algorithm10CORIA’05.To take advantage of the keyword in this algorithm,we use the method introduced by[RA V02],which differs from the algorithm in Fig3on two points.First,the key-word is abstracted.It is replaced by the tag in the corpus and only frequent subsequences containing both the tags and are kept.The second difference concerns the pattern ranking.Instead of measuring the precision on the learning corpus,we measure it on the corresponding part of the testing corpus.This means the precision is measured on passages associated with the same questions as the learning corpus,but containing the keyword and not necessarily the answer(c.f.3.1).These two changes make the algorithm more adapted to a QA system.3.3.2.Extraction algorithmBoth with and without using the keyword,once the rules have been applied on the documents,we have a list of all the occurrences of the candidate answers along with their conﬁdence score,which is the precision of the pattern which extracted it.To rank these candidate answers,we compute a score for each candidate answer which is the sum of the conﬁdence scores of all the occurrences of this candidate answer,as shown in Fig4.For example,if the candidate answer“1756”has been extracted twice with the score0.5and0.3,the score of“1756”is0.8.Input:List of answers along with their conﬁdence score.1:for each(answer,confidence)do2:add confidence to score answer3:end for4:Sort the answers according to score answerOutput:Ordered list of the candidate answers.MRR#Answers0.45234/93used63/1000.513Table2.Results using Alignment Learning with Sufﬁx Trees.Column#Answers givesthe number of times at least one of the correct answers belongs to the top5answers are considered incorrect because they contain the exact birth date and not just thebirth year,for example"January20,1946"instead of"1946",against5with the rules learnt without using the keyword.Considering these answers correct brings the MRRto0.672with the keyword information and0.475without.Moreover,with questions and the rules learnt with the keyword infor-mation,we notice that,in most cases,when a correct answer has been extracted but isnot in the top5answers,which happens13times,all the answers ranked higher are just noise and none of them are dates,not even numbers.This particular case showsthe main weakness of these patterns.Indeed,they are based on raw text only and donot provide any information concerning the answer to be extracted.Adding informa-tion about the answer would help solve this problem.For example,withquestions,the POS tag could tell that the answer must be a number.Overall,looking at the patterns makes it easy to explain why those learnt using thekeyword perform better on both question classes.Indeed,both on and on questions,when the keyword is not used,the algorithm learns patterns that are very precise but overly speciﬁc.Most of the patterns contain the value of the key-word,for example“Adams( ”or“Hitchcock( ”with questions,and“Parthenon, ”or“Balaton, ”with ques-tions.Since the keyword is not abstracted,these patterns are too speciﬁc and cannot be used to answer different questions.When the keyword is abstracted,the patterns are more general and the previous patterns are replaced by“ ( ”for questions and“ , ”for questions.3.4.Experiments with RAPIER3.4.1.AlgorithmThe second approach consists in using the IE system RAPIER[CAL98]to learn answer extraction patterns and extract the answers.RAPIER’s patterns have a more abstract view of texts.Indeed,not only do they use the value of the token,but they also use its POS tag.These patterns are sequences of tokens on which there are two types of constraint,each constraint being a disjunction of possible values.Theﬁrst constraints are word constraints and concern the value of the token.For example,if the constraint is a list of the words a,b and c,then the token must be one of these threewords.The second constraints are called Part-Of-Speech constraints and indicate which POS tag the token must have.Having these two constraints allows the system to generalize his patterns and,for example,learn a pattern saying that a token must have the POS tag“NN”(noun)without explicitly giving its value.The reader is reported to[CAL98]for further explanation on how RAPIER works.Since RAPIER does not give a conﬁdence score for each candidate answers,we cannot rank the candidate answers as we did with alignment learning.But RAPIER’s patterns set is ordered,so we rank our candidate answers accordingly to the rank of the pattern that extracted them.For example,if“1756”is extracted by rule1and“1845”by rule3,the best candidate answer is“1756”.3.4.2.DataSet Pre-processingTo meet RAPIER requirements,we had to add POS tags to our passages.We used Brill’s POS tagger[BRI92]to do so.To take advantage of the keyword information, we also abstracted it by replacing all its occurrences by the tag .3.4.3.ResultsMRR#Answers0.49110/93used74/1000.085Table3.Results using RAPIER.Column#Answers gives the number of times at least one of the correct answers belongs to the top5answersTable3shows the results.Theﬁrst thing to notice is that RAPIER does not per-form well on questions.Indeed,whether the keyword information is used or not,the results are equally poor,meaning it is totally independent of the keyword. The problem in this case is that RAPIER never generalizes on the answer to extract, i.e.in all the patterns it learns,the word constraints on the tokens to be extracted are lists of the answers encountered during the learning process.Therefore,the patterns are far too speciﬁc to the questions in the learning corpus,and hence cannot be used to answer other questions.Here,RAPIER may need more examples to learn on in order to perform a proper generalization and learn more efﬁcient patterns.Oppositely,on questions,the system performs well and using the key-word improves the performances.For example,whether the keyword is used or not, RAPIER is able to learn a pattern saying that the answer is a number,preceded by a “(”and followed by a“-”,as in“Mozart(1756-1791”.But when using the keyword, RAPIER is also able to learn that the token preceding the“(”is precisely the keyword, whereas when the keyword is not abstracted,RAPIER is at best able to learn that this token is a proper noun.Unfortunately,this is the only generalized pattern produced by RAPIER in our experiments.All the other patterns are over speciﬁc for the samereason as with questions.Once again,a larger set of examples may have helped RAPIER to learn more general patterns.But providing larger sets of examples is difﬁcult for some question classes and may be expensive.3.5.Experiments with PAF3.5.1.AlgorithmThe third learning algorithm we used is PAF[MAR04].This algorithm’s ap-proach is very different from the previous two algorithms.Indeed,it does not learn patterns,but classiﬁers.The passages of our corpora being tokenized,a separator is deﬁned as the position between two successive tokens.Thus,to identify the correct answer,we need to identify its start separator and its end separator.Separators are represented as an attribute-valued vector.PAF learns to identify separators using su-pervised classiﬁcation.The classiﬁers learnt are readable decision trees produced by Quinlan’s C5.To rank the candidate answers given by PAF,a score for each candidate answer is computed the same way as was done with alignment learning.3.5.2.DataSet Pre-processingFor the classiﬁer to be able to effectively learn how to classify the separators,we had to choose a document representation,i.e.a list of attributes.In our experiments, we considered the following attributes for each token:–the Part-Of-Speech tag(Brill’s POS tagger[BRI92]was used);–an attribute saying whether the token is a word,a number or a punctuation sym-bol.This is a generalization over the Part-Of-Speech tag;–the case of the token:allCaps,lowercase,UpperInitial or LowerInitial;–the length of the token(i.e.its number of characters).Note that this document representation is an abstraction of the initial text,as it does not use the string value of the tokens.Hence,unlike RAPIER,PAF cannot learn lists of the answers encountered in the learning corpus.To use the keyword,we could not abstract it since the string values of the tokens are not considered.Therefore,we added an attribute that represents the distance between the keyword and the answer.For example in the passage“Mozart(1756-”the distance is1token.The order in which the keyword and the answer appear is also represented. In our example,the keyword is before the answer.3.5.3.ResultsTable4shows the results,which outperform the other ones.On the one hand,with questions,the system performs very well and the keyword attribute helps improve the results.At the root of the decision tree learnt without using the keyword attribute,one can read that the answer must be a number of length4,which is not。

自然语言处理_Question-Answer Dataset(试题答案数据集)

Question-Answer Dataset(试题答案数据集)数据摘要：This page provides a link to a corpus of Wikipedia articles, manually-generated factoid questions from them, and manually-generated answers to these questions, for use in academic research. These data were collected by Noah Smith, Michael Heilman, Rebecca Hwa, Shay Cohen, Kevin Gimpel, and many students at Carnegie Mellon University and the University of Pittsburgh between 2008 and 2010.中文关键词：问题,答案,数据集,语料库,手工生成,英文关键词：questions,answers,Dataset,corpus,questions,manually-generated,数据格式：TEXT数据用途：Information Processing,Academic Research数据详细介绍：Question-Answer DatasetThis page provides a link to a corpus of Wikipedia articles, manually-generated factoid questions from them, and manually-generated answers to these questions, for use in academic research. These data were collected by Noah Smith, Michael Heilman, Rebecca Hwa, Shay Cohen, Kevin Gimpel, and many students at Carnegie Mellon University and the University of Pittsburgh between 2008 and 2010.DownloadManually-generated factoid question/answer pairs with difficulty ratings from Wikipedia articles. Dataset includes articles, questions, and answers.Version 1.1 released August 6, 2010README.v1.1; Question_Answer_Dataset_v1.1.tar.gzArchived ReleasesVersion 1.0 released February 18, 2010README.v1.0; Question_Answer_Dataset_v1.0.tar.gzFurther ReadingPlease cite this paper if you write any papers involving the use of the data above: Question Generation as a Competitive Undergraduate Course ProjectNoah A. Smith, Michael Heilman, and Rebecca HwaIn Proceedings of the NSF Workshop on the Question Generation Shared Task and Evaluation Challenge, Arlington, VA, September 2008.AcknowledgmentsThis research project was supported by NSF IIS-0713265 (to Smith), an NSF Graduate Research Fellowship (to Heilman), NSF IIS-0712810 and IIS-0745914 (to Hwa), and Institute of Education Sciences, U.S. Department of Education R305B040063 (to Carnegie Mellon).数据预览：点此下载完整数据集。

我对上网查答案的看法英语作文

我对上网查答案的看法英语作文Using the internet to find answers is a common practice nowadays. It's like having a vast library at your fingertips, anytime, anywhere. It's super convenient when you're stuck on a problem and need a quick solution.But sometimes, it's not all about getting the answer fast. Searching online can be a bit overwhelming, with so much information out there. You gotta be careful not to get lost in the sea of data.On the other hand, using the internet to research can be really educational. You can explore topics in depth and discover new things you never knew about. It's a great way to broaden your horizons.And hey, let's not forget the social aspect of it. You can join forums, discuss ideas with people from all over the world, and maybe even make some new friends along the way.Overall, using the internet to find answers is a double-edged sword. It's convenient and educational, but you gotta be smart about it. Don't just rely on the internet for everything; use it as a tool to enhance your learning experience.。

ArcGIS WebApps 与其他系统的集成方法说明书

Questions and AnswersWebinar 1: Improving Inspections and Maintenance1.Can we integrate Workforce for ArcGIS assignments with other systems? if so, how? Isthere any help documents or support resources?a.This can be done with scripting and we recommend using the ArcGIS API forPython. You can read more about this process here.b.This Github repository contains sample scripts.2.Is an integration to Microsoft Teams on your roadmap?a.While there is no direct integration available with Microsoft Teams, you canembed web apps made in ArcGIS Online or Enterprise within Teams. To dothis, add a new tab to a channel and set it as a website. Use the URL from yourweb app to link the app into Teams. The app will still need to be sharedappropriately and those accessing it may still need to be a named user. Pleaseknow that ArcGIS does integrate with Microsoft: Excel, PowerPoint, SharePoint,and Power BI. Take a look into ArcGIS Maps for Office, ArcGIS Maps forSharePoint, and ArcGIS Maps for Power BI.3.Can anyone within the utility have access to the dashboard? Does the dashboard requirean Esri license?a.Dashboards can be shared in the same way that you share other items/appswith ArcGIS Online/Enterprise. Simply create your dashboard and then share itwith groups, the organization, or publicly. For someone within an organizationto view dashboards, they would need at least a “viewer” license. To create one,you need at least a “creator” license. If a dashboard is publicly facing, then nolicense to view it is necessary.4.Can this system (Collector for ArcGIS, etc.) talk with a non-Esri system? We use MapInfo(OSPInsight) and QGIS, both enterprise databases.a.ArcGIS products and apps are designed to work within the Esri platform. If youwould like to integrate with other platforms, the data would most likely need tobe Extracted, Transformed, and Loaded (ETL) out of Esri and into your otherGIS systems. You can also check with those other systems to see if they haveany means of integrating with the ArcGIS platform.5.When are webhooks coming to Collector for ArcGIS?a.Webhooks are currently only supported for Survey123, QuickCapture, andEnterprise Portal.b.To gain visibility, submitting this request to ArcGIS Ideas would be a great nextstep.6.How are you using the image of the gas meter setup in Survey123 to select the differentparts of the meter? Is this possible in the web version of Survey123?a.This process is done using a Scalable Vector Graphic (.svg), a type of imagefile, and a select_one or select_multiple questions with appearance set toimage-map. The SVG file typically has to be custom made to fit your needs.You can follow the steps in this blog to get started. Currently, this functionalityis only possible with surveys made using Survey123 Connect that are used withthe Survey123 mobile app. The image-map appearance is not supported inthe Survey123 web app.7.How can we get access to ArcGIS Insights? Is it included with our ArcGIS Online license?a.ArcGIS Insights is a premium app for ArcGIS Online/Enterprise and can also beinstalled locally on your desktop as well. If you are interested in ArcGISInsights, you can read more about it here and see its Frequently AskedQuestions here. Please contact your Esri Account Manager to learn more.8.How do you configure Survey 123 to automatically set the inspection in Workforce? Isee too much back and forth for the field worker to manage.a.You can configure the integration between Survey123 and Workforce withinthe Workforce project’s configuration. Specifically, go to the “Advanced” taband look under “App Integration.” You can integrate with Collector for ArcGIS,Explorer for ArcGIS, Navigator for ArcGIS, and Survey123 for ArcGIS. To learnmore about this process, follow this link and look under “Tip: Integrate otherEsri apps.”9.When capturing an issue in the field using a mobile app, how accurate is the GPSlocation? Any tips or tools that can improve the accuracy of the marked location?a.The accuracy of the data collected is based on the GPS of your mobile device.At best it’s usually accurate to few meters, but this accuracy can also vary basedon local or atmospheric conditions (clouds, buildings, trees, phone case, etc.).The easiest way to overcome the positional error would be through using anexternal, Bluetooth GPS unit. Esri has many partners that make these GPS unitsthat work with mobile devices and Collector, QuickCapture, and Survey123.b.The price can vary based on the manufacturer and the level of accuracyrequired. Eos, Trimble, Bad Elf, and Juniper units are quite common in thefield.10.How do you add the photo attachment in the e-mail webhook? I’ve built a few webhooks but never see the images attached in the e-mail. Thanks!a.To provide some background, the webhook demonstrated was set up usingIntegromat. This blog covers how you can configure the webhook to pull animage taken in the field to add it to an email as an attachment. This works forboth Survey123 and QuickCapture. Photo attachments are not currentlypossible with webhooks made using Microsoft Power Automate (formerlyMicrosoft Flow).11.Is there an Esri Blog article about this?a.Resources available based on functionality shown in the demonstration:i.Integrate Workforce with an Enterprise Asset Management Systemii.Integrate Workforce and Survey123iii.Work with selectable images in Survey123iv.Integrate Survey123 and QuickCapturev.Webhooks and QuickCapturevi.Getting started with Dashboardsvii.ArcGIS Insights Gallery12.Is there a way to collect data offline and later upload data offline to a database?a.Collector for ArcGIS, Survey123 for ArcGIS, and ArcGIS QuickCapture are allcapable of working offline. To use Collector offline, you can follow the stepsoutlined here (be sure to follow the steps for the appropriate mobile device).For Survey123, simply download the survey to your device before you leave anarea with good cellular reception. For QuickCapture, the process is similar toSurvey123; download the project before heading into the field. In all cases, thedata collected will be stored on the mobile device and can be synced toArcGIS Online or Enterprise once you return to an area with good cellularconnectivity.13.Is ArcGIS Insights only available in ArcGIS Enterprise? What version?a.ArcGIS Insights is available for ArcGIS Online, ArcGIS Enterprise, and can beinstalled locally on your desktop as well. The version of ArcGIS Insights thatyou can run in ArcGIS Enterprise depends on your version of ArcGISEnterprise. The table at the top of this page can help you determine whichversion of ArcGIS Insights is compatible with each version of ArcGIS Enterprise.Please note that ArcGIS insights is a premium app. If you are interested inaccessing this application, please reach out to your Esri Account Manager. Webinar 2: Optimizing Capital Work1.I realize the demos are informative using ArcGIS but how would the Utility Networkbenefit a utility? Or is there an integration?a.Understanding the Utility Network: A Guide for Water Utilities(https:///en-us/landing-page/industry/water/2019/understanding-utility-network)b.Water Distribution Utility Network Foundation(https:///water/help/water-distribution-utility-network-foundation/get-started/create-water-utility-network.htm)c.Webinar: Introduction to the Utility Network(https:///watch?v=CWEhSUszTRw&t=1880s)2.How can we do this operation using Survey123?a.Get Started with Survey123 for ArcGIS (https:///en/projects/get-started-with-survey123/)3.How can we enable attachments in Survey123?ers could go the layer setting in ArcGIS Online/Portal (Item Details) >Overview and enable attachments via the toggle.b.Image only at this point.4.Is snapping still limited to vertices? I would like to have ability to snap to edge.a.You can snap to existing point features or vertices of lines and polygons whenusing the map to create new features or when updating the location of existingones.b.Vertices only at this point5.I have an issue with bad resolution of satellite images. Do you know how to overcome itand enable the use these tools?a.Customize Basemapi.Design and Publish Basemaps (https:///en/projects/design-and-publish-basemaps/)ii.Customize basemaps in Portal for ArcGIS(https:///en/portal/latest/administer/windows/customize-basemaps.htm)b.There are also partners that provide High Resolution Aerial Imagery productsto customers such as Nearmap & EagleView (formerly Pictometry)6.Does the data from Collector for ArcGIS have the same input fields as the dashboard?a.Yes, they are all pointing at the same feature service.b.They are fully configurable on the data fields you would like to display as well.7.If we are using a separate design tool, what is our best format/interface to send a designto Esri for inclusion in a constructability review application?a.We could leverage a data conversion process to bring over and publish thedesign to an ArcGIS Online or Portal for ArcGIS Environment for fieldoperations.b.Supported Data Types and Format (https:///en/pro-app/help/projects/supported-data-types-and-items.htm)8.Is the May 14th webinar available for watching if we weren’t registered for it?a.Yes. Webinar recordings and presentations can be found here:/InspectConstructInnovate9.Are the annotation polygons an SDE feature class?a.Yes, it could be.Webinar 3: Transforming Fieldwork with Advanced Technologies1.Can the QR Code image be added to mapping? Possibly a popup window that workerscan scan to enter inspection data?a.The QR code in this demo opens a Survey123 survey using URL parameters. It ispossible to include a location question in the survey and then have a point addedto the inspection data automatically when the QR code is scanned.b.Check out this link that contains information on how to configure a Survey123 linkto prepopulate fields(https:///groups/survey123/blog/2019/02/06/survey123-tricks-of-the-trade-web-form-url-parameters).2.How much of this functionality is enabled in ArcGIS Runtime?3.How did they pinpoint the points? Was it with the drone’s coordinates?a.4.Michael - can you use the AI processes to ID and locate trees?a.You sure can! There are some built in processes that can identify items in a fewdifferent ways. For example: if you want to know an area has trees, you can dothat. If you want to identify how many trees, you can do that. If you want to knowwhat kind of tree it is, you can do that too. If you wanted to include this data withina vegetation management process or to know what assets may be at risk ofdamage from a fallen tree, this would be perfect.5.Would you have a workflow for the image classification process used in Pro and for thiswebinar?a.6.How does the QR Code know where to push the data to? How do we configure this inSurvey 123? Do we make our own QR Codes for this to work?a.The data is pushed to wherever the survey was created (ArcGIS Online or Portal).b.Check out this link that contains information on how to configure a Survey123 linkto prepopulate fields(https:///groups/survey123/blog/2019/02/06/survey123-tricks-of-the-trade-web-form-url-parameters).c. To create the QR code we used a free online QR Code generator that was thenexported as an image.7.What about the use of RFiD instead of Barcoding?a.If you have an RFiD reader that connects to your mobile device, then you coulduse RFiD technology. It would require a URL to be transmitted from the RFiD tag.b.Check out this link for more information on how to configure a Survey123 URL toprepopulate fields (This link contains information on how to configure a Survey123link to prepopulate fields(https:///groups/survey123/blog/2019/02/06/survey123-tricks-of-the-trade-web-form-url-parameters).8.Can I use ESRI's imagery for analysis?a.If you are asking about basemaps, not necessarily. The analysis needs to look atthe layers and imagery that has been added to the map on top of the basemap.9.How well does voice recognition work with various English dialects across the US andwith industry specific jargon?a.Voice recognition is dependent on the device you are using.10.On damaged assets like a broken power line crossarm from your experience what gsdlevel images would be required?a.It would be a case by case basis on the level of damage you are looking to identify.I would suggest.11.Which drones models are supported with the flight planning software?a.Most drones can use the flight planning software and new drones are currentlybeing added. Most drones that we have done tests with are DJI.。

启启的回答

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文档下载后可定制修改，请根据实际需要进行调整和使用，谢谢!并且，本店铺为大家提供各种类型的经典范文，如托班教案、小班教案、中班教案、大班教案、幼儿游戏、教育资料、幼儿管理、计划总结、家园教育、其他范文等等，想了解不同范文格式和写法，敬请关注!Download tips: This document is carefully compiled by this editor.I hope that after you download it, it can help you solve practical problems. The document can be customized and modified after downloading, please adjust and use it according to actual needs, thank you!In addition, this store provides various types of classic sample essays, such as nursery school lesson plans, small class lesson plans, middle class lesson plans, large class lesson plans, children's games, educational materials, child management, plan summary, home education, other sample essays, etc. Learn about the different formats and writing styles of sample essays, so stay tuned!启启的回答今天，我和孩子们在一起聊关于“身体转动”的话题，孩子们对这个话题并不陌生，所以，课堂气氛很是活跃，每个人都在积极的发表着自己的看法。

网络面试问题和答案Networking - Interview Questions and Answers

Networking - Interview Questions and Answers1. Define Network?A network is a set of devices connected by physical media links. A network is recursively is a connection of two or more nodes by a physical link or two or more networks connected by one or more nodes.2. What is a Link?At the lowest level, a network can consist of two or more computers directly connected by some physical medium such as coaxial cable or optical fiber. Such a physical medium is called as Link.3. What is a node?A network can consist of two or more computers directly connected by some physical medium such as coaxial cable or optical fiber. Such a physical medium is called as Links and the computer it connects is called as Nodes.4. What is a gateway or Router?A node that is connected to two or more networks is commonly called as router or Gateway. It generally forwards message from one network to another.5. What is point-point link?If the physical links are limited to a pair of nodes it is said to be point-point link.6. What is Multiple Access?If the physical links are shared by more than two nodes, it is said to be Multiple Access.7. What are the advantages of Distributed Processing?a. Security/Encapsulationb. Distributed databasec. Faster Problem solvingd. Security through redundancye. Collaborative Processing8. What are the criteria necessary for an effective and efficient network?a. PerformanceIt can be measured in many ways, including transmit time and response time. b. ReliabilityIt is measured by frequency of failure, the time it takes a link to recover from a failure, and the network's robustness.c. SecuritySecurity issues includes protecting data from unauthorized access and virues.9. Name the factors that affect the performance of the network?a. Number of Usersb. Type of transmission mediumc. Hardwared. Software10. Name the factors that affect the reliability of the network?a. Frequency of failureb. Recovery time of a network after a failure11. Name the factors that affect the security of the network?a. Unauthorized Accessb. Viruses12. What is Protocol?A protocol is a set of rules that govern all aspects of information communication.13. What are the key elements of protocols?The key elements of protocols area. SyntaxIt refers to the structure or format of the data, that is the order in which they are presented.b. SemanticsIt refers to the meaning of each section of bits.c. TimingTiming refers to two characteristics: When data should be sent and how fast they can be sent.14. What are the key design issues of a computer Network?a. Connectivityb. Cost-effective Resource Sharingc. Support for common Servicesd. Performance15. Define Bandwidth and Latency?Network performance is measured in Bandwidth (throughput) and Latency (Delay). Bandwidth of a network is given by the number of bits that can be transmitted over the network in a certain period of time. Latency corresponds to how long it t5akes a message to travel from one end off a network to the other. It is strictly measured in terms of time.16. Define Routing?The process of determining systematically hoe to forward messages toward the destination nodes based on its address is called routing.17. What is a peer-peer process?The processes on each machine that communicate at a given layer are called peer-peer process.18. When a switch is said to be congested?It is possible that a switch receives packets faster than the shared link can accommodate and stores in its memory, for an extended period of time, then the switch will eventually run out of buffer space, and some packets will have to be dropped and in this state is said to congested state.19. What is semantic gap?Defining a useful channel involves both understanding the applications requirements and recognizing the limitations of the underlying technology. The gap between what applications expects and what the underlying technology can provide is called semantic gap.20. What is Round Trip Time?The duration of time it takes to send a message from one end of a network to the other and back, is called RTT.21. Define the terms Unicasting, Multiccasting and Broadcasting?If the message is sent from a source to a single destination node, it is called Unicasting.If the message is sent to some subset of other nodes, it is called Multicasting.If the message is sent to all the m nodes in the network it is called Broadcasting.22. What is Multiplexing?Multiplexing is the set of techniques that allows the simultaneous transmission of multiple signals across a single data link.23. Name the categories of Multiplexing?a. Frequency Division Multiplexing (FDM)b. Time Division Multiplexing (TDM)i. Synchronous TDMii. ASynchronous TDM Or Statistical TDM.c. Wave Division Multiplexing (WDM)24. What is FDM?FDM is an analog technique that can be applied when the bandwidth of a link is greater than the combined bandwidths of the signals to be transmitted.25. What is WDM?WDM is conceptually the same as FDM, except that the multiplexing and demultiplexing involve light signals transmitted through fiber optics channel.26. What is TDM?TDM is a digital process that can be applied when the data rate capacity of the transmission medium is greater than the data rate required by the sending and receiving devices.27. What is Synchronous TDM?In STDM, the multiplexer allocates exactly the same time slot to each device at all times, whether or not a device has anything to transmit.28. List the layers of OSIa. Physical Layerb. Data Link Layerc. Network Layerd. Transport Layere. Session Layerf. Presentation Layerg. Application Layer29. Which layers are network support layers?a. Physical Layerb. Data link Layer andc. Network Layers30. Which layers are user support layers?a. Session Layerb. Presentation Layer andc. Application Layer31. Which layer links the network support layers and user support layers?The Transport layer links the network support layers and user support layers.32. What are the concerns of the Physical Layer?Physical layer coordinates the functions required to transmit a bit stream over a physical medium.a. Physical characteristics of interfaces and mediab. Representation of bitsc. Data rated. Synchronization of bitse. Line configurationf. Physical topologyg. Transmission mode33. What are the responsibilities of Data Link Layer?The Data Link Layer transforms the physical layer, a raw transmission facility, to a reliable link and is responsible for node-node delivery.a. Framingb. Physical Addressingc. Flow Controld. Error Controle. Access Control34. What are the responsibilities of Network Layer?The Network Layer is responsible for the source-to-destination delivery of packet possibly across multiple networks (links).a. Logical Addressingb. Routing35. What are the responsibilities of Transport Layer?The Transport Layer is responsible for source-to-destination delivery of the entire message.a. Service-point Addressingb. Segmentation and reassemblyc. Connection Controld. Flow Controle. Error Control36. What are the responsibilities of Session Layer?The Session layer is the network dialog Controller. It establishes, maintains and synchronizes the interaction between the communicating systems.a. Dialog controlb. Synchronization37. What are the responsibilities of Presentation Layer?The Presentation layer is concerned with the syntax and semantics of the information exchanged between two systems.a. Translationb. Encryptionc. Compression38. What are the responsibilities of Application Layer?The Application Layer enables the user, whether human or software, to access the network. It provides user interfaces and support for services such as e-mail, shared database management and other types of distributed information services.a. Network virtual Terminalb. File transfer, access and Management (FTAM)c. Mail servicesd. Directory Services39. What are the two classes of hardware building blocks?Nodes and Links.40. What are the different link types used to build a computer network?a. Cablesb. Leased Linesc. Last-Mile Linksd. Wireless Links41. What are the categories of Transmission media?a. Guided Mediai. Twisted - Pair cable1. Shielded TP2.Unshielded TPii.Coaxial Cableiii.Fiber-optic cableb. Unguided Mediai. Terrestrial microwaveii. Satellite Communication42. What are the types of errors?a. Single-Bit errorIn a single-bit error, only one bit in the data unit has changedb. Burst ErrorA Burst error means that two or more bits in the data have changed.43. What is Error Detection? What are its methods?Data can be corrupted during transmission. For reliable communication errors must be deducted and Corrected. Error Detection uses the concept of redundancy, which means adding extra bits for detecting errors at the destination. The common Error Detection methods area. Vertical Redundancy Check (VRC)b. Longitudinal Redundancy Check (VRC)c. Cyclic Redundancy Check (VRC)d. Checksum44. What is Redundancy?The concept of including extra information in the transmission solely for the purpose of comparison. This technique is called redundancy.45. What is VRC?It is the most common and least expensive mechanism for Error Detection. In VRC, a parity bit is added to every data unit so that the total number of 1s becomes even for even parity. It can detect all single-bit errors. It can detect burst errors only if the total number of errors in each data unit is odd.46. What is LRC?In LRC, a block of bits is divided into rows and a redundant row of bits is added to the whole block. It can detect burst errors. If two bits in one data unit are damaged and bits in exactly the same positions in another data unit are also damaged, the LRC checker will not detect an error. In LRC a redundant data unit follows n data units.47. What is CRC?CRC, is the most powerful of the redundancy checking techniques, is based on binary division.48. What is Checksum?Checksum is used by the higher layer protocols (TCP/IP) for error detection49. List the steps involved in creating the checksum.a. Divide the data into sectionsb. Add the sections together using 1's complement arithmeticc. Take the complement of the final sum, this is the checksum.50. What are the Data link protocols?Data link protocols are sets of specifications used to implement the data link layer. The categories of Data Link protocols are 1. Asynchronous Protocols2. Synchronous Protocolsa. Character Oriented Protocolsb. Bit Oriented protocols51. Compare Error Detection and Error Correction:The correction of errors is more difficult than the detection. In error detection, checks only any error has occurred. In error correction, the exact number of bits that are corrupted and location in the message are known. The number of the errors and the size of the message are important factors.52. What is Forward Error Correction?Forward error correction is the process in which the receiver tries to guess the message by using redundant bits. 53. Define Retransmission?Retransmission is a technique in which the receiver detects the occurrence of an error and asks the sender to resend the message. Resending is repeated until a message arrives that the receiver believes is error-freed.54. What are Data Words?In block coding, we divide our message into blocks, each of k bits, called datawords. The block coding process is one-to-one. The same dataword is always encoded as the same codeword.55. What are Code Words?"r" redundant bits are added to each block to make the length n = k + r. The resulting n-bit blocks are called codewords. 2n - 2k codewords that are not used. These codewords are invalid or illegal.56. What is a Linear Block Code?A linear block code is a code in which the exclusive OR (addition modulo-2) of two valid codewords creates another valid codeword.57. What are Cyclic Codes?Cyclic codes are special linear block codes with one extra property. In a cyclic code, if a codeword is cyclically shifted (rotated), the result is another codeword.58. Define Encoder?A device or program that uses predefined algorithms to encode, or compress audio or video data for storage or transmission use. A circuit that is used to convert between digital video and analog video.59. Define Decoder?A device or program that translates encoded data into its original format (e.g. it decodes the data). The term is often used in reference to MPEG-2 video and sound data, which must be decoded before it is output.60. What is Framing?Framing in the data link layer separates a message from one source to a destination, or from other messages to other destinations, by adding a sender address and a destination address. The destination address defines where the packet has to go and the sender address helps the recipient acknowledge the receipt.61. What is Fixed Size Framing?In fixed-size framing, there is no need for defining the boundaries of the frames. The size itself can be used as a delimiter.62. Define Character Stuffing?In byte stuffing (or character stuffing), a special byte is added to the data section of the frame when there is a character with the same pattern as the flag. The data section is stuffed with an extra byte. This byte is usually called the escape character (ESC), which has a predefined bit pattern. Whenever the receiver encounters the ESC character, it removes it from the data section and treats the next character as data, not a delimiting flag.63. What is Bit Stuffing?Bit stuffing is the process of adding one extra 0 whenever five consecutive Is follow a 0 in the data, so that the receiver does not mistake the pattern 0111110 for a flag.64. What is Flow Control?Flow control refers to a set of procedures used to restrict the amount of data that the sender can send before waiting for acknowledgment.65. What is Error Control ?Error control is both error detection and error correction. It allows the receiver to inform the sender of any frames lost or damaged in transmission and coordinates the retransmission of those frames by the sender. In the data link layer, the term error control refers primarily to methods of error detection and retransmission.66. What Automatic Repeat Request (ARQ)?Error control is both error detection and error correction. It allows the receiver to inform the sender of any frames lost or damaged in transmission and coordinates the retransmission of those frames by the sender. In the data link layer, the term error control refers primarily to methods of error detection and retransmission. Error control in the data link layer is often implemented simply: Any time an error is detected in an exchange, specified frames are retransmitted. This process is called automatic repeat request (ARQ).67. What is Stop-and-Wait Protocol?In Stop and wait protocol, sender sends one frame, waits until it receives confirmation from the receiver (okay to go ahead), and then sends the next frame.68. What is Stop-and-Wait Automatic Repeat Request?Error correction in Stop-and-Wait ARQ is done by keeping a copy of the sent frame and retransmitting of the frame when the timer expires.69. What is usage of Sequence Number in Relaible Transmission?The protocol specifies that frames need to be numbered. This is done by using sequence numbers. A field is added to the data frame to hold the sequence number of that frame. Since we want to minimize the frame size, the smallest range that provides unambiguous communication. The sequence numbers can wrap around.70. What is Pipelining ?In networking and in other areas, a task is often begun before the previous task has ended. This is known as pipelining.71. What is Sliding Window?The sliding window is an abstract concept that defines the range of sequence numbers that is the concern of the sender and receiver. In other words, he sender and receiver need to deal with only part of the possible sequence numbers.72. What is Piggy Backing?A technique called piggybacking is used to improve the efficiency of the bidirectional protocols. When a frame is carrying data from A to B, it can also carry control information about arrived (or lost) frames from B; when a frame is carrying data fromB to A, it can also carry control information about the arrived (or lost) frames from A.73. What are the two types of transmission technology available?(i) Broadcast and (ii) point-to-point74. What is subnet?A generic term for section of a large networks usually separated by a bridge or router.75. Difference between the communication and transmission.Transmission is a physical movement of information and concern issues like bit polarity, synchronisation, clock etc. Communication means the meaning full exchange of information between two communication media.76. What are the possible ways of data exchange?(i) Simplex (ii) Half-duplex (iii) Full-duplex.77. What is SAP?Series of interface points that allow other computers to communicate with the other layers of network protocol stack.78. What do you meant by "triple X" in Networks?The function of PAD (Packet Assembler Disassembler) is described in a document known as X.3. The standard protocol has been defined between the terminal and the PAD, called X.28; another standard protocol exists between hte PAD and the network, called X.29. Together, these three recommendations are often called "triple X".79. What is frame relay, in which layer it comes?Frame relay is a packet switching technology. It will operate in the data link layer.80. What is terminal emulation, in which layer it comes?Telnet is also called as terminal emulation. It belongs to application layer.81. What is Beaconing?The process that allows a network to self-repair networks problems. The stations on the network notify the other stations on the ring when they are not receiving the transmissions. Beaconing is used in Token ring and FDDI networks.82. What is redirector?Redirector is software that intercepts file or prints I/O requests and translates them into network requests. This comes under presentation layer.83. What is NETBIOS and NETBEUI?NETBIOS is a programming interface that allows I/O requests to be sent to and received from a remote computer and it hides the networking hardware from applications.NETBEUI is NetBIOS extended user interface. A transport protocol designed by microsoft and IBM for the use on small subnets.84. What is RAID?A method for providing fault tolerance by using multiple hard disk drives.。

课后题答案

第一章1.简述WEB的特点。

答：①Web是图形化和易于导航的②Web与平台无关。

无论平台是什么，都可以通过Internet访问Web。

③Web是分布式。

图形、声音、视频等大量信息可以放在不同的站点，但在逻辑上是一体化的。

④Web是动态的。

信息的提供者经常对网站上的信息进行更新。

2.简述静态网页和动态网页的执行过程，说明两者的异同。

答：静态网页：指那些不能够接收用户输入信息的Web网页，其内容是静态的，唯一的响应就是接受鼠标单击超链接后显示所链接的网页。

其执行过程如下：①用户在客户端将HTML文件的网址输入到浏览器的地址栏，请求一个HTML网页。

②Web浏览器向Web服务器发送HTML文件请求，称为Request（请求）。

③Web服务器找到该HTML文件，将其传送给用户浏览器，称为Response（响应）。

④用户的Web浏览器解释HTML文件，结果在Web浏览器中显示。

动态网页：是采用ASP、、JSP或PHP等语言动态生成的网页，只有在接到用户访问请求后才生成网页并传输到用户的浏览器。

其执行过程如下：①用户在客户端将一个网址输入到浏览器的地址栏，请求一个Web网页。

②Web浏览器向Web服务器发送Web网页请求，称为Request（请求）。

③Web服务器找到该文件对其进行解释并生成标准的HTML文件。

④Web浏览器将HTML文件传送给用户浏览器，称为Response（响应）。

用户的Web浏览器解释HTML文件，结果在Web浏览器中显示。

③异同点：第2章编程模型2.简述典型的网页结构答: 页面的内部结构是非常模块化的，包括页面指令、代码和页面布局3个独立的部分。

●页面指令。

页面指令建立该页面的运行环境，规定引擎的运行库如何处理该页面，控制页面的行为。

●页面布局。

页面布局表示页面的可视元素，包括标记、服务器控件和静态文本。

●源代码部分。

源代码部分包括页面和控件事件处理程序等，先编译后执行。

其中页面指令和页面布局统称为HTML部分。

我对网上搜索答案的看法英语作文

我对网上搜索答案的看法英语作文Finding Answers on the InternetThe internet is a huge place with so much information! Whenever I have a question about anything, my first thought is to go online and search for the answer. With just a few taps on the keyboard, I can find explanations, facts, pictures, and videos about whatever is on my mind. It's really amazing how much knowledge is available at my fingertips.When I'm doing research for a school project, I try to stick to websites that seem credible and educational. Sites from universities, museums, government agencies, and major organizations tend to have well-researched and fact-checked information. User-generated content like Wikipedia can be a good starting point, but I know I can't just accept it as 100% accurate. I have to verify important details from other trusted sources.My favorite way to get reliable information is by using akid-friendly search engine or an online encyclopedia made specifically for students my age. These are much safer than a general web search because they filter out inappropriate content and present material in a way that is easy for me to understand.The articles are written clearly, avoid big complex words, and often have illustrations, video clips, and interactive features to make the topics more engaging and memorable.Sometimes I still need help from adults to comprehend what I'm reading online or to determine if a source can be trusted. That's okay – I'm still learning! When I get stuck, I ask my parents or teacher for guidance. They can explain things in a way that makes sense to me and steer me towards sources they know are dependable.Using the internet for research has definite advantages over traditional books and encyclopedias. The information is constantly updated, so I know I'm getting the latest facts and data. I can easily access viewpoints and perspectives from all around the world, not just what's published locally. And I can quickly find answers to very specific questions that might not be covered in a book.On the other hand, there's just so much information out there that it can be overwhelming and difficult to filter through it all. I sometimes get distracted going down rabbit holes by clicking related link after related link until I've completely lost track of what I was originally searching for. It's easy to feelscatter-brained when everything is right there ready to be explored.There's also the concern about online privacy and safety, especially for kids my age. I have to be really cautious about sharing any personal information, downloading things, or clicking on questionable links or pop-ups. My parents have a lot of rules and restrictions in place to try to keep me protected. While I may find those limits frustrating sometimes, I know they are just looking out for me because there are definitely dangers lurking out there on the wild internet.Overall, I'm grateful to have such a powerful tool for learning and satisfying my curiosity about the world around me. The internet provides an inexhaustible supply of knowledge at my fingertips. As long as I think critically about the sources,fact-check important information, and follow online safety guidelines, it's an incredibly valuable educational resource that will only become more useful as I get older. With time and experience, I'm getting better at efficiently finding trustworthy answers to all my questions on the internet. It's empowering to be able to research virtually anything I want to learn!。

我在网上寻找答案的意见英语作文

我在网上寻找答案的意见英语作文Finding answers online has become a common practice for many people in this digital age. Whether it's searching for information on a topic, looking for solutions to a problem, or seeking guidance on a certain issue, the internet has become a go-to source for quick and convenient answers. However, the process of searching for answers online is not without its pitfalls, and it is important to approach it with caution and a critical mindset.One of the biggest advantages of seeking answers online is the sheer amount of information that is available at our fingertips. With just a few clicks, we can access a wealth of knowledge on virtually any topic imaginable. This is incredibly helpful when we are in need of quick information or when we want to learn more about a specific subject. Additionally, the internet allows us to connect with experts and professionals in various fields, making it easier to get accurate and up-to-date information.Another benefit of searching for answers online is the speed and convenience it offers. Gone are the days of poring through books or making phone calls to find the information we need. With search engines like Google, we can quickly find answers toour questions within seconds. This convenience is especially valuable in today's fast-paced world where time is of the essence.However, despite the many advantages of finding answers online, there are also several drawbacks to be aware of. One of the biggest concerns is the reliability and credibility of the information that is available on the internet. Not all sources are trustworthy, and it can be difficult to discern fact from fiction in the vast sea of online content. This is why it is important to verify the accuracy of the information and cross-reference it with other sources before accepting it as true.Another issue to consider when searching for answers online is the risk of encountering misinformation or biased opinions. The internet is full of conflicting viewpoints and unsubstantiated claims, making it easy to be misled by false information. It is crucial to approach online sources with a critical eye and to be mindful of the credibility of the information being presented.Despite these challenges, there are steps we can take to ensure that we are getting reliable answers online. One approach is to stick to reputable sources and websites that are known for providing accurate information. Websites of academic institutions, government agencies, and established organizationsare generally more trustworthy than personal blogs or social media posts.Additionally, it is important to fact-check the information we find online and to seek out multiple sources to corroborate the information. By comparing information from different sources, we can get a more well-rounded view of a topic and reduce the risk of being misled by false information.In conclusion, searching for answers online can be a valuable tool for obtaining information quickly and conveniently. However, it is important to approach online sources with a critical mindset and to verify the credibility of the information being presented. By being discerning in our search for answers online, we can make the most of the wealth of knowledge available on the internet while avoiding the pitfalls of misinformation and bias.。

网上搜索作业答案辩论赛英语作文

网上搜索作业答案辩论赛英语作文Title: Debate on the Ethical Implications of Searching for Homework Answers OnlineIntroduction:In today's digital age, students have easy access to a wealth of information on the internet. This includes the ability to search for homework answers online. While this may seem like a convenient way to complete assignments quickly, it brings up ethical concerns regarding cheating and academic dishonesty. In this debate, we will explore the pros and cons of searching for homework answers online and discuss whether it is ethically acceptable.Pros of Searching for Homework Answers Online:One argument in favor of searching for homework answers online is that it can help students learn. By researching the answers to their questions, students may gain a better understanding of the material and improve theirproblem-solving skills. Additionally, students may be able to access resources that they would not have otherwise been exposed to, expanding their knowledge beyond what is covered in the classroom.Another benefit of searching for homework answers online is that it can save time. Students have busy schedules and may not always have the time to complete assignments on their own. By finding answers online, students can efficiently complete their homework and focus on other tasks.Cons of Searching for Homework Answers Online:On the other hand, searching for homework answers online raises concerns about academic integrity. When students rely on online sources for answers, they are not demonstrating their own understanding of the material. This can lead to a lack of academic growth and hinder students' development of critical thinking skills.Moreover, searching for homework answers online can result in plagiarism. If students copy answers from online sources without citing them properly, they are committing academic dishonesty. This can have serious consequences, such as failing grades or even expulsion from school.Debate:Proponents of searching for homework answers online argue that it is a valuable tool for students to supplement their learning. They believe that as long as students use onlineresources responsibly and cite their sources, it can be a beneficial practice.On the other side of the debate, opponents argue that searching for homework answers online promotes laziness and hinders students' academic growth. They believe that students should be encouraged to think critically and work through problems on their own, rather than relying on external sources for answers.Conclusion:In conclusion, the debate over searching for homework answers online is a complex issue with valid arguments on both sides. While online resources can be helpful for students, it is important for them to use these tools responsibly and ethically. Ultimately, students should strive to develop their own understanding of the material and demonstrate their knowledge through their own work. By approaching homework assignments with integrity and academic honesty, students can truly benefit from their educational experiences.。

网上搜索答案之我见英文作文

网上搜索答案之我见英文作文Searching for answers online, it's a double-edged sword. Sometimes, it's like having a magic wand that can instantly solve your problems. A quick Google search and there you have it step-by-step guides, videos, and even expert opinions. But then, there's the other side of it. You find so much information, it's like being in a maze and not knowing which way to go.On the positive side, the convenience of online searching is unbeatable. Imagine being stuck on a math problem and being able to find the solution within seconds. Or needing to know how to fix a leaky faucet and finding a tutorial right at your fingertips. It's just so efficient! Plus, you can access information from anywhere in the world, expanding your knowledge horizons.But then, there's the issue of credibility. With so much information out there, how do you know what's true and what's not? Fake news and misleading articles are a realthreat. You have to be careful and do your research, checking sources and cross-referencing information. It's a skill that takes time to master.Another thing is that sometimes, you can get overwhelmed by the amount of information. It's like beingin a library with millions of books and not knowing which one to pick. You might end up scrolling through endless web pages, feeling more.。

关于上网搜答案的英语作文初中

关于上网搜答案的英语作文初中The Internet has become an indispensable tool for accessing information in modern society. With just a few clicks, we can find answers to almost any question we have. However, relying too heavily on the internet to search for answers may have its drawbacks, especially for middle school students.Firstly, searching for answers online may result in a lack of critical thinking and problem-solving skills. When students constantly turn to the internet for answers, they may become dependent on it and neglect the importance of thinking for themselves. Developing critical thinking skills is essential for academic success and personal growth. Without these skills, students may struggle to analyze information, evaluate different perspectives, and come up with creative solutions to problems.Secondly, the information found online may not always be accurate or reliable. The internet is filled with misinformation, biased opinions, and outdated sources. Students who rely solely on online sources for answers may unknowingly reproduce incorrect information in their work. This not only harms their academic performance but also perpetuates the spread of false information.Moreover, relying on the internet for answers can discourage students from developing good research skills. Research skills are crucial for conducting thorough investigations, evaluating sources, and synthesizing information. When students simply copy and paste answers from the internet, they miss out on the opportunity to hone these important skills.In addition, excessive internet use for finding answers may lead to procrastination and a lack of engagement with the learning material. Instead of actively participating in class discussions, conducting experiments, or doing independent research, students may opt to take the easy way out by looking up answers online. This passive approach to learning can hinder students' academic progress and overall development.Despite these potential drawbacks, the internet can still be a valuable tool for supplementing students' learning. It can provide access to a wealth of resources, such as educational websites, online tutorials, and digital libraries. Students can use the internet to explore new topics, deepen their understanding of complex concepts, and enhance their learning experience.To strike a balance between using the internet for answers and developing essential skills, it is important for middle school students to approach online research with caution. They shouldlearn to critically evaluate information, cross-reference sources, and verify the credibility of the information they find online. Teachers and parents can also play a role in guiding students on how to effectively use the internet for educational purposes.In conclusion, while the internet can be a valuable tool for accessing information, middle school students should be mindful of the potential drawbacks of relying too heavily on it for answers. By developing critical thinking skills, honing research skills, and using the internet in a responsible manner, students can enhance their learning experience and become independent learners.。