簡介：中文中文4300字畢業(yè)設計（論文）譯文題目基于C語言的MIS程序庫設計學生姓名學號專業(yè)物聯網班級指導教師評閱教師完成日期2014年12月20日第2頁共10頁統、DBMS和大多數的系統軟件，都是用C語言設計的。通過C語言設計的應用軟件，有著大量的成功案例。這證明C語言對于開發(fā)像MIS這樣的應用系統，也是一種合適而且強大的程序語言。事實上，通過精心選擇常用功能，以及編程使他們形成一個庫，用C語言設計一個MIS的有效性也能得到顯著提高。本文提到的WEB編程庫是一個很好的例子，該庫的優(yōu)點如下。●網頁編程功能。設計一個基于MIS的網頁，網頁編程是一項基本的要求。因此這類功能將無疑使程序員設計起來更為方便。這部分是庫的主要組成部分，它包括設置頁面風格，顯示頁面標題，顯示頁頭，顯示頁尾等?！癜踩卿浌δ?。對于現今的MIS系統，登錄系統是必不可少的部分，而且系統的安全性必須得到保證。該功能組將提供一些有用的功能，例如CAPTCHA功能，登錄功能，COOKIE處理功能，郵件功能，密碼修改功能，和密碼獲取功能等，從而簡化了安全登錄系統的設計?！駥嵱霉δ?。能夠提供一些常用的工具，如計數器、迷你日歷、加密和編碼功能等。這將給程序員在開發(fā)中帶來一些幫助?！馛語言中的所有設計。通過使用C語言作為開發(fā)語言，在運行MIS的時候，只需要二進制對象代碼即可。這無疑增加了安全性、可靠性、可擴展性和運行效率。本文介紹了基于C語言的MIS程序庫，在設計和實施過程中的一些技術細節(jié)。包括網頁編程功能，安全登錄功能和實用功能，并提供了一個詳細的演示，來展現庫的使用和效果。IIII網頁創(chuàng)作功能網頁創(chuàng)作功能在WEB服務器和CGI程序之間的核心業(yè)務，是通過標準輸入和輸出對數據進行翻譯。通過CGI程序形成一個網頁，發(fā)送網頁內容到服務器的標準輸出是一個必要的工作。由于這個頁面實際上是一個HTML文檔，標準的格式化輸出功能PRINTF就可以完成這個任務。根據CGL說明5中，通過CGL形成的頁面，必須由兩部分組成，頁頭和主體，其中頁頭用于發(fā)送屬性信息，而主體則是通過服務器提供給客戶端實體。這兩個部分通過一個空行分開。

簡介：2009ISECSINTERNATIONALCOLLOQUIUMONCOMPUTING,COMMUNICATION,CONTROL,ANDMANAGEMENT9781424442461/09/2500?2009IEEECCCM2009DESIGNANDREALIZATIONOFANINTELLIGENTACCESSCONTROLSYSTEMBASEDONVOICERECOGNITIONBOCUICOLLEGEOFINFORMATIONHEBEIPOLYTECHNICUNIVERSITYTANGSHAN,CHINAEMAILMIKECUIHEUTEDUCNTONGZEXUECOLLEGEOFINFORMATIONSCIENCEANDENGINEERINGHEBEIUNIVERSITYOFSCIENCEANDTECHNOLOGYSHIJIAZHUANG,CHINAEMAILDIANZIXINXIYEAHNETABSTRACTTHEINTELLIGENTACCESSSYSTEMADOPTSTHETECHNOLOGYOFTHEVOICERECOGNITIONTHATBASEDONTHESPCE061ASINGLECHIPTHESYSTEMHARDWAREISMADEUPOFSPCE061ASINGLECHIP,THEPOWERANDGATINGCIRCUIT,THEEXTENDEDMEMORIZERSPR4096,THEVOICEINPUTANDOUTPUTCIRCUITTHEKEYTECHNOLOGIESARETHEAPPLICATIONOFTHESPCE061ASINGLECHIPONVOICERECOGNITIONANDTHEDESIGNOFTHEDOORCONTROLCIRCUITTHESYSTEMSOFTWAREISMADEUPOFTHEVOICETRAININGMODULE,THEVOICERECOGNITIONMODULE,THEVOICEDATAPROCESSINGMODULE,THEVOICEPLAYINGMODULEANDTHECODEOFINPUTANDOUTPUTMODULETHESYSTEMCOMPLETESTHEFUNCTIONSOFCOLLECTINGTHEVOICEDATA,DISTILLINGCHARACTER,SPECIALVOICERECOGNITIONANDVOICEPLAYINGINTERMSOFINITIALIZINGTHESYSTEMANDTHEIDENTIFICATIONTRAININGACCORDINGTOTHEVOICERECOGNITIONARITHMETICTHEORY,THEPRETREATMENTOFVOICESIGNAL,THECHARACTERDISTILLINGANDPATTERNMATCHINGISANALYZEDTHERESULTSOFTHEEXPERIMENTSINDICATETHATTHESYSTEMCAPABILITYISSTEADYANDTHEIDENTIFICATIONISEFFECTIVETHESYSTEMCANBEAPPLIEDINHOUSEORSMALLOFFICESAFETYPROTECTIONKEYWORDSACCESSCONTROLLINEARPREDICTIONVOICERECOGNITIONPATTERNMATCHCHARACTERDISTILIINTRODUCTIONTHEREAREMANYIDENTIFICATIONTECHNOLOGIESUSEDINCURRENTINTELLIGENTGUARDSYSTEMRELATIVETOOTHERTECHNIQUES,THEVOICERECOGNITIONTECHNOLOGYISGENERALLYREGARDEDASONEOFTHECONVENIENTANDSAFERECOGNITIONTECHNIQUESTHISTECHNIQUEISAKINDOFTECHNIQUETHATMAKESUSEOFTHECREATURECHARACTEROFAHUMANBODYTOCARRYONIDENTIFICATIONBECAUSEEVERYBODYSCREATURECHARACTERISUNIQUEANDSTABLEINACERTAINPERIOD,THEYAREDIFFERENTFROMOTHERSANDDIFFICULTTOBEFABRICATEDANDIMITATEDSOTHEVOICERECOGNITIONTECHNOLOGYCANBEMADEUSEOFIDENTIFICATION,WHICHISSAFE,ACCURATEANDDEPENDABLEIITHECLASSIFICATIONOFVOICERECOGNITIONBECAUSETHEPURPOSEANDFUNCTIONOFTHEVOICERECOGNITIONAREDIFFERENT,THERECOGNITIONISCLASSIFIEDASTALKERRECOGNITIONANDVOICERECOGNITIONANDTHETALKERRECOGNITIONCANBECLASSIFIEDASTWOTYPES,ONEISRELEVANTTOTEXTANDTHEOTHERISIRRELEVANTTOTEXTTHEVOICERECOGNITIONSYSTEMTHATISRELEVANTTOTEXTNEEDSUSERSTOPRONOUNCEACCORDINGTOTHESTATEDCONTENTS,ANDTHENEVERYBODYSSPEECHMODELISBUILTUPACCURATELYBECAUSEIDENTIFICATIONALSONEEDUSERSTOPRONOUNCEACCORDINGTOTHESTATEDCONTENTS,THEEFFECTISVERYGOODTHEVOICERECOGNITIONSYSTEMTHATISIRRELEVANTTOTEXTDOESNTRULEPRONUNCIATIONCONTENTSOFTHETALKERSITISDIFFICULTTOBUILDUPSPEECHMODELSBUTCUSTOMERSMAKEUSEOFTHESYSTEMCONVENIENTLY,ANDITISAPPLIEDWIDELYFROMTHEUSAGE,THESYSTEMCANBECLASSIFIEDASTALKERRECOGNITIONANDTALKERCONFIRMATIONTHEFORMERJUDGESAVOICETHATNEEDSTOBEIDENTIFIEDFROMSEVERALTALKERSTHELATTERJUDGESTHATANIDENTIFIEDVOICECOMESFROMACERTAINTALKERWHETHERORNOTITSOUTPUTONLYHASTWOKINDSOFRESULT,YESORNOTTHECENTRALPROCESSOROFTHISSYSTEMISTHESPCE061ASINGLECHIPTHETALKERCONFIRMATIONTHATISRELEVANTTOTEXTISREALIZEDONTHECHIP,ANDTHENHOMOLOGOUSORDERANDOPERATIONARECARRIEDOUTTHESYSTEMISMAINLYMADEUPOFTALKERIDENTIFICATIONMODULE,GATINGCIRCUITANDDOORLOCKETCINTRAINING,THEVOICEOFTALKERSGETSINTOTHEVOICESIGNALCOLLECTIONCIRCUITTHROUGHAMICROPHONE,ANDTHENTHECOLLECTEDVOICESIGNALSAREPROCESSEDBYTHEVOICEPROCESSINGCIRCUIT,THECHARACTERISTICPARAMETERSOFTALKERSAREDISTILLEDANDSAVEDATLASTTHEDATABASEOFCHARACTERISTICPARAMETERSOFTALKERSISFORMEDINIDENTIFYING,THEVOICETHATNEEDSTOBEIDENTIFIEDISMATCHEDWITHTHEINFORMATIONINTHEDATABASEOFCHARACTERISTICPARAMETERSOFTALKERSOUTPUTCIRCUITSCONTROLTHEGATINGELECTRICALMACHINE,ANDLASTLYTHEDOORLOCKISCONTROLLEDFIGURE1FRAMEOFTHISSYSTEM229MOSTALIKEREFERENCETEMPLATEISFOUNDOUT,THEVOICEISTHEIDENTIFICATIONRESULTAVOICESIGNALSPRETREATMENTTHENOISESSERIOUSLYDISTURBTHEPROCESSINGANDIDENTIFICATIONOFVOICESIGNALS,SOTHENOISESMUSTBEDISPOSEDFIRSTLYTHEINPUTANALOGVOICESIGNALSFROMMICROPHONESMUSTBESAMPLEDANDMEASUREDINORDERTOOBTAINDIGITALVOICESIGNALSBEFORECONVERTINGVOICESIGNALSINTODIGITALSIGNALS,ITISNECESSARYTOFILTERANDCOUNTERDISTURBINFILTERINGTHESIGNALPARTANDNOISESBEYOND1/2SAMPLEFREQUENCYAREFILTEREDTHECLEANVOICESIGNALSAREOBTAINEDLATER,ANDTHENLOWFREQUENCYDISTURBINGISFILTEREDTHROUGHFOREAGGRAVATIONTECHNOLOGY,ESPECIALLYTHEDISTURBINGOF50HZOR60HZTHEHIGHFREQUENCYVOICESIGNALSAREIMPROVEDANDTHEYCANREMOVEDCFLOATING,RESTRAINRANDOMNOISESANDIMPROVETHEFUNCTIONOFENERGYOFCLEANVOICEBCHARACTERISTICDISTILLINGTHESYSTEMADOPTSTHEEVALUATIONMETHODTHATUSESTHECONTRASTVALUEBETWEENDISPERSIONDEGREEOFDIFFERENTSPEAKERSANDSELFDISPERSIONDEGREEOFEACHSPEAKERASCHARACTERISTICPARAMETERSTHEBASICIDEAISTODISTILLGROUPCHARACTERISTICPARAMETERSFROMAVOICESEGMENTOFTHESAMESPEAKER,THATISTOSAYTOMAPTHESEGMENTONADOTOFTHEMULTISPACEDIFFERENTVOICESFROMTHESAMESPEAKERWILLPRODUCEDIFFERENTDOTSINTHECHARACTERISTICSPACETHEFUNCTIONOFMULTIVARIABLEPROBABILITYDENSITYCANDESCRIBETHEDISTRIBUTIONFORDIFFERENTSINGLEPRONUNCIATIONFROMTHESAMESPEAKER,THESEDOTSARERELATIVELYCONCENTRATEDBUTTHEPRONUNCIATIONDISTRIBUTIONFROMDIFFERENTSPEAKERSISAPARTFARTHER,THEGROUP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OACLASSBYDIFFERENTDEGREEOFMEMBERSHIPTHEVALUEOFMEMBERSHIPAFFECTSTHECONVERGENCERATEOFITERATIVEPROGRESSSOWEHEREGIVEAFORMULATHATCANENLARGETHEMAXIMUMDEGREEINTHEMEMBERSHIPANDFURTHERREDUCETHEOTHERMEMBERSHIPSETJSAMPLEBELONGSTOOCATEGORYBYTHELARGESTMEMBERSHIP,ANDTHUSTHEIMPROVEDEXPRESSIONFORTHEDEGREEOFMEMBERSHIP2OJOJOJUUU?????81IJIJIJUUU?????,1,2,,ICIO≠9BYTHEFORMULAABOVE,WECANFINDTHATIFTHEMAXIMUMDEGREEOFMEMBERSHIPVALUEISSMALL,THENTHECOEFFICIENTINFRONTOFITWILLBELARGERANDONTHECONTRARY,THETRUTHISALSOTRUESOTHEFORMULACANMEETTHEREQUIREMENTSTHATENLARGETHEMAXIMUMVALUEOFTHEMEMBERSHIPDEGREEANDREDUCEOTHERMEMBERSHIP4THEFASTHWFCMALGORITHM41THEORYINTRODUCTIONFUZZYCMEANSCLUSTERINGALGORITHMISALOCALSEARCHALGORITHM,ANDITISVERYSENSITIVETOTHEINITIALVALUETHEIMPROPERSELECTIONOFINITIALVALUEISLIKELYTOLEADTOCONVERGENCEOFLOCALMINIMUMPOINTINTHESOLUTIONSPACE,THEPARTICLESWARMOPTIMIZATIONPSOALGORITHMISNOTRESTRICTEDTOONEPOINT,BUTAGROUPOFPOINTSSIMULTANEOUSLYTHATCANAVOIDFALLINGINTOLOCALSOLUTIONSYAOANDXU,2007SOPSOISAKINDOFDYNAMICPOPULATIONBASEDEVOLUTIONARYCOMPUTINGTECHNOLOGY,SHOWINGSTRONGCONVERGENCE,EASYTOIMPLEMENTWITHNOMOREPARAMETERSETTINGSHIGASSHIANDLBA,2003EACHPARTICLEINPSOISASOLUTIONINTHESOLUTIONSPACEITADJUSTSITSFLIGHTBYITSELFANDTHECOMPANION’SFLYINGEXPERIENCETHEBESTPLACETHATEACHPARTICLEEXPERIENCEDDURINGTHEFLIGHTISTHEOPTIMALSOLUTIONOFTHEPARTICLEITSELF,WHICHISCALLEDINDIVIDUALEXTREMUMBESTP,REPLACEDBYTHEEXTREMEVALUEOFEACHCLASSBESTCINTHISPAPERTHEBESTPOSITIONEXPERIENCEDBYTHEENTIREGROUP,THATIS,THEOPTIMALSOLUTIONTHEENTIREGROUPGOTATPRESENT,ISCALLEDTHEGLOBALBESTBESTGPARTICLESWARMOPTIMIZATIONALGORITHMWILLUPDATEPARTICLES’SPEEDANDLOCATIONBYTHEFOLLOWINGEQS10AND11111BEST22BESTIIIIVVCRCXCRGXΩ???????101IIIXXVΗ11WHERE1C,2CARECONSTANTS,CALLEDTHELEARNINGFACTOR12,RRARERANDOMNUMBERSBETWEEN0AND1,WISINERTIAWEIGH,IVISTHEFLIGHTSPEEDINTHEIGENERATION,ANDIXREPRESENTSTHEPARTICLEPOSITIONINTHEIGENERATIONEBERHARTANDSHI2000DISCOVEREDTHROUGHTHERESEARCHTHATINEQ10,WHENΩISLARGE,THEALGORITHMWILLHAVESTRONGGLOBALSEARCHCAPABILITYANDWHENΩISSMALL,THEALGORITHMTENDSTOLOCALSEARCHITISOBTAINEDTHATWECANGETABETTERSEARCHRESULTTHROUGHTHEITERATIVEΩVALUEFROMTHEMAXIMUMTOTHEMINIMUM,WHICHFIRSTFOCUSESONTHEGLOBALSEARCHANDTHENENHANCESTHEABILITYOFTHELOCALSEARCHSO,PARTICLESWARMOPTIMIZATIONPSODESCRIBEDBYSINEFUNCTIONISINTRODUCEDTOHWFCMALGORITHMFORTHEUNDERWATERIMAGESEGMENTATION,INORDERTOOVERCOMETHESHORTCOMINGSTHATFUZZYCMEANSISOVERRELIANTONTHEINITIALVALUEANDISEASYTOFALLINTOLOCALMINIMUMEQ11ANDEQ12CANBEEXPRESSEDASFOLLOWS

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簡介：此文檔是畢業(yè)設計外文翻譯成品（含英文原文中文翻譯），無需調整復雜的格式下載之后直接可用，方便快捷本文價格不貴,也就幾十塊錢一輩子也就一次的事外文標題COMPARATIVESTUDYOFWEBSITEPAGESIZEASDESIGNISSUEINVARIOUSWEBSITES外文作者JATINDERMANHAS文獻出處IJINFORMATIONENGINEERINGANDELECTRONICBUSINESS,2018,6,3339如覺得年份太老，可改為近2年，畢竟很多畢業(yè)生都這樣做英文2826單詞，16932字符字符就是印刷符，中文4473漢字。（如果字數多了，可自行刪減，大多數學校都是要求選取外文的一部分內容進行翻譯的。）COMPARATIVESTUDYOFWEBSITEPAGESIZEASDESIGNISSUEINVARIOUSWEBSITESABSTRACTWEBSITESAREVERYIMPORTANTMEANSOFCOMMUNICATIONINTHISCURRENTERAOFINFORMATIONTECHNOLOGYDIFFERENTINSTITUTIONS/ORGANIZATIONSPUTLOTSOFEFFORTSTOPORTRAYCOMPLETEINFORMATIONONBEAUTIFULLYDESIGNEDWEBSITESORGANIZATIONSTHESEDAYSCONCERNEDMOREINPROVIDINGUSERSWITHALLFACILITIESONLINETHROUGHWEBSITES,WHICHACTASANINTERFACETHROUGHWHICHAUSERCANGETHISWORKDONEWITHOUTPHYSICALLYVISITINGTHEORGANIZATIONWITHTHISTHERESPONSIBILITYOFTHEDESIGNERANDTHECONCERNEDINSTITUTIONS/ORGANIZATIONSINCREASESMANIFOLDSOTHATTHEWEBSITESBEHAVIORSHOULDREMAININTERACTIVEANDQUICKENOUGHFORTHEUSERTOAVAILALLFACILITIESTHROUGHWEBSITESCOMFORTABLYSPEEDANDSIZEOFAWEBSITEAREDIRECTLYRELATEDWITHEACHOTHERSIZEISVERYIMPORTANTWHENTARGETINGUSERSTHATDON’THAVEOPTIMALINTERNETCONNECTIONSAUTHORINTHISPAPERDEVELOPEDANONLINETOOLUSINGNETFRAMEWORKUSINGCTOSTUDYWEBPAGESIZEASDESIGNISSUEINVARIOUSCATEGORIESOFTHEWEBSITESLIKEGOVERNMENT,COMMERCIAL,EDUCATIONAL,SOCIALNETWORKINGANDJOBPORTALSTHEAUTOMATEDTOOLDEVELOPEDBYAUTHORFUNCTIONONTHEBASISOFTHEDIFFERENTSTANDARDSPRESCRIBEDINW3CANDPRESCRIBEDINANALYSISPERFORMEDIN2THETOOLACTLIKEAPARSERANDRENDERSTHECOMPLETECODEOFTHEWEBSITEANDTHENPRODUCESRESULTBYEXAMININGTHEMEMORYREQUIREMENTSOFTHECOMPONENTFILESTHATCONTRIBUTETOTHETOTALSIZEOFTHEWEBSITETHERESULTSPRODUCEDSHOWSTHATOUTOFTHEFIVEDIFFERENTCATEGORIESOFWEBSITES,ITCANBECONCLUDEDTHATNONEOFTHEWEBSITECATEGORIESDETERMINESTHETOTALSIZEBYFIRSTEXTRACTINGTHEFILESOFDIFFERENTEXTENSIONSBYPARSINGTHEHTMLFILERECEIVEDFROMSERVERANDTHENCALCULATINGTHEIRINDIVIDUALSIZESBYREQUEST/RESPONSEMETHODSTHEPARSERWILLTAKEURLOFTHEWEBSITEASINPUTANDTHENSENDITTOTHESERVERANDFROMTHESERVERHTMLCODEOFTHEWEBSITEISSUPPLIEDTOTHEINTERFACEFORMAKINGCOMPARISONWITHTHEEXISTINGSTANDARDSTHEALGORITHMOFTHEAUTOMATEDTOOLDEVELOPEDISGIVENBELOWALGORITHM4FORDETERMININGTOTALSIZEINTERMSOFMEMORYREQUIREMENTSOFAWEBSITEINPUTURLOFTHEWEBSITEOUTPUTTOTALSIZEOFWEBSITEINKBSMETHODSTEPSARENUMBEREDFORBETTERUNDERSTANDABILITYBEGINSTEPIGENERATEAREQUESTFOROBTAININGHTMLFILEOFTHEWEBSITEBYPASSINGURLTOTHESERVERSTEPIIPARSETHEHTMLFILEFORVARIOUSCOMPONENTFILESONONEBYONEBASISSTEPIIIFOREACHTYPEEGIMAGE,CSSETCOFCOMPONENTFILE

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MAILAGENCYWITHTHEFOURFACTORSOFCOURSE,THISFUNCTIONSHOULDONLYBEUSEDBYTHEADMINOFTHEMISCONFIGMAILAGENCYPASSWORDIMYMAILAGENCYPASSWORDMYMAILSMTP,126COMMYMAILAGENCY126,COMSUBMITI?FIGURE5FONTIOFCONFIGURINGMAILAGENCYFUNCTIONWEBMAILAGENCYOACCEPTSTHEFOURFACTORSBYTHEPAGEFORMSHOWNINFIG5,ANDTHENSTORETHEMINTHESERVERINORDERTOPROTECTTHEINFORMATIONFROMBEINGSTOLEN,THEINFORMATIONISENCRYPTEDFIRSTWITHRC4ALGORITHM,ANDTHEN,ENCODEDWITHBASE64ALGORITHMTOCONVENIENTFORSTORINGWHENEVERAMESSAGEISNEEDEDTOBEMAILED,THEMAILAGENCYINFORMATIONISREADIN,ANDTHEN,ENCODEDANDDECRYPTEDINTOORIGINALSBMODIFYINGPASSWORDTHEPURPOSEOFTHEFUNCTIONISPROVIDINGAPAGEFORMFORUSERSTOMODIFYTHEPASSWORDOBVIOUSLYTHEREARETHREEINPUTFORMCONTROLARENEEDED,INWHICHONEFORORIGINALANDTHEOTHERTWOFORTHENEWPASSWORDANDTHEREPEATEDONERESPECTIVELYTHEFORMPAGEOFITISNOTADIFFICULTTASKBUTTHEPROCESSOFTHEPASSWORDISANIMPORTANTISSUESOMESYSTEMSSTORETHEPASSWORDASPLAINTEXT,ANDCOMPAREITWITHTHEINPUTDATAFROMTHEUSERALTHOUGHTHISISTHESIMPLESTWAYTOVERIFYTHEPASSWORDBUTALSOADANGERONESINCETHEPLAINTEXTOFTHEPASSWORDISSTOREDWHICHCANBESEENBYMALICIOUSADMINISTRATORSAGOODWAYTORESOLVETHEPROBLEMISTOSTORETHEPASSWORDINANENCRYPTEDFORMANDCOMPAREITWITHTHEENCRYPTEDFORMOFPASSWORDTHEREAREVARIOUSENCRYPTIONMETHODSANDONEOFCOMMONLYUSEDISBYMD5,THECORRESPONDINGSYSTEMFUNCTIONOFWHICHISCRYPTO735CCONFIGURINGMAILBOXCONFIGURINGMAILBOXISALSOACOMMONLYUSEDFUNCTION,FOREXAMPLE,WHENMODIFYINGUSERSPASSWORD,GETTINGBACKPASSWORD,ANNOUNCINGMESSAGESBYADMIN,ETCFUNCTIONWEBMAILBOXOISDESIGNEDTOACCOMPLISHCONFIGURATIONITACCEPTSTHEMAILBOXOFTHEUSERBYUSINGTHEPAGEFORMANDSTORETHEMAILBOXIFTHEPASSWORDPROVIDEDBYUSERISCORRECTDPASSWORDGETTINGBACKFUNCTIONTHEREARETWOFACTORSFORPASSWORDGETTINGBACK,USEMAMEANDTHEUSERSMAILBOXTHEFORMPAGEFORITISSIMPLYJUSTCONSISTINGOFANINPUTFORMCONTROLTOENTERTHEUSEMAMETHEMAILBOXOFTHEUSERMUSTBEPRESETBYUSERFIG6SHOWSTHEPAGEFORMGENERATEDBYTHEFUNCTIONTRYANEWCODEGETBACKPASSWORDUSERNAME11VERIFICATIONLCODERL1LOGINFIGURC6FORMOFGETTINGBACKPASSWORDITISOBVIOUSLYSIMILARTOTHEFORMOFLOGINEXCEPTTHATTHEREISNOPASSWORDREQUIREDTHEREFORE,INFACT,ITISACCOMPLISHEDBYTHESAMEFUNCTIONASFORLOGIN,WEB_USERLOGINOWITHTHEUSEMAME,THECORRESPONDINGMAILBOXOFTHEUSERCANBEOBTAINEDANDANEWPASSWORDISRANDOMLYGENERATEDTHENEWPASSWORDISSENTTOTHEUSERSMAILBOXASTHEPLAINTEXT,ANDATSAMETIME,ISENCRYPTEDANDTHENSTOREDTHEPURPOSEOFTHECAPTCHAINTHEFORMISAVOIDINGMALICIOUSUSERSTODOTHEFUNCTIONAUTOMATICALLYWHICHMAYGENERATEFLOODOFEMAILSIVUTILITYFUNCTIONSSOMEOTHERCOMMONLYUSEDUTILITYFUNCTIONSAREALSONEEDEDINTHEDESIGNINGOFWEBBASEDMIS,FOREXAMPLE,ACCESSCOUNTER,MINICALENDAR,RC4ENCRYPTION,ANDBASE64ENCODINGANDDECODING,ETCAACCESSCOUNTERTHEREARETWOTYPESOFACCESSCOUNTER,CHARACTERBASEDANDIMAGEBASEDTHELATTERISSELECTEDFORTHECOUNTERFUNCTIONINTHELIBRARYINORDERTOSIMPLIFYTHESTRUCTUREOFTHECGIFILE,THEDOTMATRIXOFTHEDIGITSISUSEDTOFORMTHECOUNTERIMAGEANDTHEDOTMATRIXINFORMATIONISCODEDDIRECTLYINTOTHESOURCECODETHEBITMAP7ISSELECTEDASTHECOUNTERIMAGEFORMATTHEREALEFFECTOFTHEACCESSCOUNTERIMPLEMENTFORTHELIBRARYISSHOWNASINTHEFIG2MENTIONEDABOVEITISWORTHYNOTEDTHATANACCESSCOUNTERSHOULDNOTBEREFRESHABLE,THATIS,ONLYWHENANEWSESSIONOCCURSCANTHECOUNTERINCREASETHISCANBEIMPLEMENTEDBYUSINGACOOKIEBMINICALENDARTHEREAREWIDEVARIETIESOFDIFFERENTFORMSOFMINICALENDARANDASIMPLEIMPLEMENTATIONISUSEDHERETHEEFFECTOFTHE

簡介：USEOFVOICERECOGNITIONFORCONTROLOFAROBOTICWELDINGWORKCELLJKEVINWATSON,DOUGLASMTODD,ANDCLYDESJONES,111ABSTRACTTHISPAPERDESCRIBESWORKUNDERWAYTOEVALUATETHEEFFECTIVENESSOFVOICERECOGNITIONSYSTEMSASANELEMENTINTHECONTROLOFAROBOTICWELDINGWORKCELLFACTORSBEINGCONSIDEREDFORCONTROLINCLUDEPROGRAMEDITORACCESSSECURITYPREOPERATIONCHECKLISTREQUIREMENTS,WELDINGPROCESSVARIABLECONTROLANDROBOTMANIPULATORMOTIONOVERRIDESINTHELATTERTWOCATEGORIES,MANUALVOCALCONTROLISBEINGCOMPAREDAGAINSTMANUALTACTILECONTROLANDFULLYAUTOMATICCONTROLINTERMSOFSPEEDOFRESPONSE,ACCURACY,STABILITY,RELIABILITYANDSAFETYINTRODUCTIONVOICERECOGNITIONTECHNOLOGYISNOWRECOGNIZEDASAPOTENTIALMEANSFOREASINGTHEWORKLOADOFOPERATORSOFCOMPLEXSYSTEMS11NUMEROUSAPPLICATIONSHAVEALREADYBEENIMPLEMENTED,AREINVARIOUSSTAGESOFDEVELOPMENT,ORAREUNDERCONSIDERATION25THESEINCLUDEDATAENTRYCONTROLOFAIRCRAFTSYSTEMS,ANDVOICEIDENTIFICATIONANDVERIFICATIONFORSECURITYPURPOSESVOICECONTROLHASALSOBEENPROPOSEDFORUSEABOARDTHESPACESTATION68ONEPRIMEAREAFORAPPLICATIONWOULDBECONTROLOFSOMEFUNCTIONSOFROBOTSUSEDFORINTRAANDEXTRAVEHICULARINSPECTIONASSEMBLY,REPAIR,SATELLITERETRIEVAL,ANDSATELLITEMAINTENANCEWHENACREWMEMBERISSERVINGINASUPERVISORYCAPACITYORTHESYSTEMISOPERATINGINATELEOPERATIONMODEVOICECONTROLOFSENSORSANDPROCESSVARIABLESWOULDFREETHECREWMEMBER’SHANDSFOROTHERTASKS,SUCHASDIRECTCONTROLOROVEMDEOFTHEMANIPULATORMOTIONSIMILARLYTHEWORKLOADASSOCIATEDWITHCONTROLOFMANYONBOARDEXPERIMENTSCOULDBEEASEDTHROUGHTHEUSEOFTHISTECHNOLOGYTHISPAPERDESCRIBESTHEAPPLICATIONOFVOICERECOGNITIONFORCONTROLOFAROBOTICPRESENTEDATTHE1986IEEEINTERNATIONALCONFERENCEONSYSTEMSMAN,ANDCYBERNETICS,HELDINATLANTA,GEORGIAOCTOBER14171986JKEVINWATSONANDDOUGLASMTODDAREWITHTHEROCKETDYNEDIVISIONOFROCKWELLINTERNATIONALSUITE302227DRAKEAVENUE,SWHUNTSVILLEAL35805CLYDESJONES,UI,ISWITHNASAMARSHALLSPACEFLIGHTCENTER,AL3581216WELDINGWORKCELLTHISISACOMPLEXSYSTEMINVOLVINGINPUTSFROMMULTIPLESENSORSANDCONTROLOFAWIDEVARIETYOFROBOTMANIPULATORMOTIONSANDPROCESSVARIABLESWHILEMANYFUNCTIONSAREAUTOMATEDAHUMANOPERATORSERVESINASUPERVISORYCAPACITYREADYTOOVEMDEFUNCTIONSWJHENNECESSARYINTHEPRESENTINVESTIGATIONACOMMERCIALLYAVAILABLEVOICERECOGNITIONSYSTEMISBEINGINTEGRATEDWITHAROBOTICWELDINGWORKCELLATNASAMARSHALLSPACEFLIGHTCENTER,WHICHISUSEDASATESTBEDFOREVALUATIONANDDEVELOPMENTOFADVANCEDTECHNOLOGIESFORUSEINFABRICATIONOFTHESPACESHUTTLEMAINENGINEINTHESYSTEMUNDERDEVELOPMENT,SOMEFUNCTIONSDONOTYETHAVEAUTOMATICCLOSEDLOOPCONTROLTHUSREQUIRINGCONTINUOUSMONITORINGANDREALTIMEADJUSTMENTBYTHEHUMANOPERATORPRESENTLY,THESEOVEMDESAREINPUTTOTHESYSTEMTHROUGHTACTILECOMMANDSEPUSHINGBUTTONSTURNINGKNOBSFORPOTENTIOMETERS,ORADJUSTINGMECHANICALDEVICESSINCETHEOPERATORMONITORSTHEPROCESSPRIMARILYVISUALLY,HEMUSTEITHERLOOKAWAYFROMTHEPROCESSTOFINDTHEPROPERBUTTONORKNOBORRELYON“MUSCULARMEMORY”MUCHASATOUCHTYPISTDOESINTHEFIRSTCASE,THETIMEOFRESPONSETOADEVIANTCONDITIONMAYBEEXCESSIVEINTHESECONDCASETHEREISANINCREASEDPROBABILITYOFASECONDARYEMRBEINGINTRODUCEDBYTHEOPERATORAVOICERECOGNITIONSYSTEMCOULDREDUCETHERESPONSETIMEREQUIREDFROMTHEOPERATORTHEPROBABILITYOFPUSHINGTHEWRONGBUTTONSHOULDSIMILARLYBEREDUCEDALSO,OPERATORFATIGUESHOULDBEMINIMIZEDSINCETHEOPERATORCANCONTINUOUSLYMONITORTHEPROCESSDURINGOVEMDEINPUT,THEEFFECTOFTHECHANGECANBEOBSERVEDMOREQUICKLYTHUSIFTHEDESIREDVALUEISEXCEEDEDANDREVERSECORRECTIONISREQUIRED,ITSHOULDBEACCOMPLISHEDMOREQUICKLY,ALLOWINGLESSOVERSHOOTTHISREDUCTIONINOSCILLATIONABOUTTHEDESIREDVALUEMAKESTHESYSTEMMORESTABLEANOTHERFACTORTHATCANBEIMPROVEDISOPERATORSAFETYINASAFETYCRITICALSITUATION,THEROBOT’SOPERATIONCANBEHALTEDIMMEDIATELYBYUSEOFTHE“EMERGENCYSTOP,’’ORESTOPMODE,WHICHISINITIATED,CONVENTIONALLYBYDEPRESSINGALARGEBUTTONIFANOPERATORINADVERTENTLYFINDSHIMSELFINAHAZC2721708870600001601001987IEEEARDOUSSITUATION,ITMAYBENECESSARYFORHIMTOINITIATETHEESTOPSEQUENCESHOULDTHEOPERATORNOTBEWITHINREACHOFTHEBUTTON,HOWEVER,HEMAYBEUNABLETOTAKETHENECESSARYACTION,AND,ASARESULTCOULDSUFFERSERIOUSINJURYHAVINGTHECAPABILITYOFSTOPPINGTHEROBOTBYISSUINGAVOICECOMMANDCOULDSIGNIFICANTLYIMPROVETHEOPERATOR’SSAFETYBYENABLINGHIMTOSTOPTHEROBOTEVENWHENNOTWITHINREACHOFTHEESTOPBUTTONMANUALCORRECTIONSAREOCCASIONALLYREQUIREDTOADJUSTTHELOCATIONATWHICHTHEWELDFILLERWIREENTERSTHEWELDPOOLPROPERENTRYLOCATIONISABSOLUTELYCRITICALTOSOUNDWELDQUALITYADJUSTMENTSAREMADEEITHERBYMANUALLYADJUSTINGMECHANISMSTHATHOLDTHEWIREFEEDGUIDETUBEORBYISSUINGTACTILECOMMANDSTOASERVOMECHANISMUSEOFAVOICERECOGNITIONSYSTEMCOULDELIMINATETHENEEDFORTHEOPERATORTOPLACEHISHANDWITHINTHEWORKINGENVELOPEOFTHEROBOTENDEFFECTORORIFSERVOMECHANISMSAREEMPLOYED,COULDIMPROVESPEEDOFRESPONSEANDSTABILITYANOTHERASPECTOFROBOTOPERATIONINANINDUSTRIALENVIRONMENTTHATISVERYIMPORTANTISTHESECURITYOFAPROGRAMEDITINGCAPABILITYOFTHESYSTEMUNDERNOCIRCUMSTANCESSHOULDANYUNAUTHORIZEDPERSONBEABLETOENTERTHISPROGRAMMINGMODEANDALTERTHEROBOT’SPROGRAMAVOICERECOGNITIONSYSTEMCANPROVIDETHENECESSARYSECURITYBYALLOWINGACCESSONLYFORINDIVIDUALSWHOAREAUTHORIZEDANDWHOSEVOICESCANBEIDENTIFIEDBYTHESYSTEMBACKGROUNDROBOTICWELDINGISUNDERDEVELOPMENTBYNASAANDROCKETDYNEFORTHEAUTOMATIONOFWELDSONTHESPACESHUTTLEMAINENGINETHATAREPRESENTLYMADEMANUALL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SSM

簡介：2950英文單詞，英文單詞，16萬英文字符，中文萬英文字符，中文4900字文獻出處文獻出處ERRATTAHIR,HANNANIAE,OUAHMANEHAUTOMATICSPEECHRECOGNITIONERRORSDETECTIONANDCORRECTIONAREVIEWJPROCEDIACOMPUTERSCIENCE,2018,1283237AUTOMATICSPEECHRECOGNITIONERRORSDETECTIONANDCORRECTIONAREVIEWRAHHALERRATTAHI,ASMAAELHANNANI,HASSANOUAHMANEABSTRACTEVENTHOUGHAUTOMATICSPEECHRECOGNITIONASRHASMATUREDTOTHEPOINTOFCOMMERCIALAPPLICATIONS,HIGHERRORRATEINSOMESPEECHRECOGNITIONDOMAINSREMAINASONEOFTHEMAINIMPEDIMENTFACTORSTOTHEWIDEADOPTIONOFSPEECHTECHNOLOGY,ANDESPECIALLYFORCONTINUOUSLARGEVOCABULARYSPEECHRECOGNITIONAPPLICATIONSTHEPERSISTENTPRESENCEOFASRERRORSHAVEINTENSIFIEDTHENEEDTOFINDALTERNATIVETECHNIQUESTOAUTOMATICALLYDETECTANDCORRECTSUCHERRORSTHECORRECTIONOFTHETRANSCRIPTIONERRORSISVERYCRUCIALNOTONLYTOIMPROVETHESPEECHRECOGNITIONACCURACY,BUTALSOTOAVOIDTHEPROPAGATIONOFTHEERRORSTOTHESUBSEQUENTLANGUAGEPROCESSINGMODULESSUCHASMACHINETRANSLATIONINTHISPAPER,BASICPRINCIPLESOFASREVALUATIONAREFIRSTSUMMARIZED,ANDTHENTHESTATEOFTHECURRENTASRERRORSDETECTIONANDCORRECTIONRESEARCHISREVIEWEDWEFOCUSONEMERGINGTECHNIQUESUSINGWORDERRORRATEMETRICKEYWORDSAUTOMATICSPEECHRECOGNITIONASRERRORDETECTIONASRERRORCORRECTIONASREVALUATION1INTRODUCTIONAUTOMATICSPEECHRECOGNITIONASRSYSTEMSAIMSATCONVERTINGASPEECHSIGNALINTOASEQUENCEOFWORDSEITHERFORTEXTBASEDCOMMUNICATIONPURPOSESORFORDEVICECONTROLLINGTHEPURPOSEOFEVALUATINGASRSYSTEMSISTOSIMULATEHUMANJUDGEMENTOFTHEPERFORMANCEOFTHESYSTEMSINORDERTOMEASURETHEIRUSEFULNESSANDASSESSTHEREMAININGDIFFICULTIESANDESPECIALLYWHENCOMPARINGSYSTEMSTHESTANDARDMETRICOFASREVALUATIONISTHEWORDERRORRATE,WHICHISDEFINEDASTHEPROPORTIONOFWORDERRORSTOWORDSPROCESSEDASRHASMATUREDTOTHEPOINTOFCOMMERCIALAPPLICATIONSBYPROVIDINGTRANSCRIPTIONWITHANACCEPTABLELEVELOFPERFORMANCEWHICHALLOWSINTEGRATIONINTOMANYAPPLICATIONSINGENERAL,ASRSYSTEMSAREEFFECTIVEWHENTHECONDITIONSAREWELLCONTROLLEDNEVERTHELESS,THEYARETOODEPENDENTONTHETASKBEINGPERFORMEDANDTHERESULTSAREFARFROMIDEAL,ANDESPECIALLYFORLARGEVOCABULARYCONTINUOUSSPEECHRECOGNITIONLVCSRAPPLICATIONSTHISLATERSTILLONEOFTHEMOSTCHALLENGINGTASKSINTHEFIELD,DUETOANUMBEROFFACTORS,INCLUDINGPOORARTICULATION,VARIABLESPEAKINGRATEANDHIGHDEGREEOFACOUSTICVARIABILITYCAUSEDBYNOISE,SIDESPEECH,ACCENTS,SLOPPYPRONUNCIATION,HESITATION,REPETITION,INTERRUPTIONSANDCHANNELMISMATCH,AND/ORDISTORTIONSTODEALWITHALLTHESEPROBLEMS,THEREHASBEENAPLETHORAOFALGORITHMSANDTECHNOLOGIESPROPOSEDBYTHESCIENTIFICCOMMUNITIESFORALLSTEPSOFLVCSROVERTHELASTDECADEPREPROCESSING,FEATUREEXTRACTION,ACOUSTICMODELING,LANGUAGEMODELING,DECODINGANDRESULTPOSTPROCESSINGNEVERTHELESSLVCSRSYSTEMSARENOTYETROBUSTWITHERRORRATESOFUPTO50UNDERCERTAINCONDITIONS21,8THEPERSISTENTPRESENCEOFASRERRORSMOTIVATESTHEATTEMPTTOFINDALTERNATIVETECHNIQUESTOASSISTUSERSINCORRECTINGTHETRANSCRIPTIONERRORSORTOTOTALLYAUTOMATETHECORRECTIONPROCESSEVALUATIONPROCEDUREINOTHERWORDS,THEREFERENCEANDRECOGNISEDWORDSGETMATCHEDINORDERTODECIDEWHICHWORDHAVEBEENDELETEDORINSERTED,ANDWHICHREFERENCERECOGNISEDSTRINGPAIRSHAVEBEENALIGNEDTOEACHOTHER,WHICHMAYRESULTINAHITORASUBSTITUTIONTHISISNORMALLYDONEBYUSINGTHEVITERBIEDITDISTANCE17TOEFFICIENTLYSELECTTHEREFERENCEANDTHERECOGNISEDWORDSEQUENCEALIGNMENTFORWHICHTHEWEIGHTEDERRORSCOREISMINIMIZEDTHEEDITDISTANCEUSUALLYALIGNSANIDENTICALWEIGHTS1FORTHELEVENSTHEINDISTANCETOALLTHREE,INSERTION,SUBSTITUTIONANDDELETIONYET,UNIFIEDWEIGHTSMAYPRESENTADOUBTTOCHOOSETHEBESTPATHALIGNMENTINTHECASEWHENWEHAVEDIFFERENTONESWHICHHAVETHESAMESCORETOAVOIDTHISPROBLEMMORRISETAL12SUGGESTUSINGDIFFERENTWEIGHTS,SUCHTHATSUBSTITUTIONWILLBEFAVOUREDTHANINSERTIONANDDELETIONINGENERAL,IT’SRECOMMENDEDTOPUTWIWD,ANDWSWIWSWHEREWI,WSANDWDARERESPECTIVELYTHEWEIGHTOFINSERTION,SUBSTITUTION,ANDDELETION23ASREVALUATIONMETRICSACCORDINGTOMCCOWANETAL11ANIDEALASREVALUATIONMETRICSHOULDBEIDIRECTMEASUREASRCOMPONENTINDEPENDENTLYONTHEASRAPPLICATION,IIOBJECTIVETHEMEASURESHOULDBECALCULATEDINANAUTOMATEDMANNER,IIIINTERPRETABLETHEABSOLUTEVALUEOFTHEMEASUREMUSTGIVEANIDEAABOUTTHEPERFORMANCE,ANDIVMODULARTHEEVALUATIONMEASURESHOULDBEGENERALTOALLOWTHOROUGHAPPLICATIONDEPENDENTANALYSISWORDERRORRATEWERISTHEMOSTPOPULARMETRICFORASREVALUATION,ITMEASURESTHEPERCENTAGEOFINCORRECTWORDSSUBSTITUTIONSS,INSERTIONSI,DELETIONSDREGARDINGTHETOTALNUMBEROFWORDSPROCESSEDITISDEFINEDASWER11WHEREITOTALNUMBEROFINSERTIONS,DTOTALNUMBEROFDELETIONS,STOTALNUMBEROFSUBSTITUTIONS,HTOTALNUMBEROFHITS,ANDN1TOTALNUMBEROFINPUTWORDSDESPITEOFBEINGTHEMOSTCOMMONLYUSED,WERHASMANYSHORTCOMINGS10FIRSTOFALL,WERISNOTATRUEPERCENTAGEBECAUSEITHASNOUPPERBOUND,SOITDOESN’TTELLYOUHOWGOODASYSTEMIS,BUTONLYTHATONEISBETTERTHANANOTHERMOREOVER,WERISNOTD/ISYMMETRIC,SOINNOISYCONDITIONSWERCOULDEXCEED100,FORTHEFACTTHATITGIVESFARMOREWEIGHTTOINSERTIONSTHANTODELETIONSTHEWERSTILLEFFECTIVEFORSPEECHRECOGNITIONWHEREERRORSCANBECORRECTEDBYTYPING,SUCHAS,DICTATIONHOWEVER,FORALMOSTANYOTHERTYPEOFSPEECHRECOGNITIONSYSTEMS,WHERETHEGOALISMORETHANTRANSCRIPTION,ITISNECESSARYTOLOOKFORANALTERNATIVE,ORADDITIONAL,EVALUATIONFRAMEWORKMANYRESEARCHERSHAVEPROPOSEDALTERNATIVEMEASURESTOSOLVETHEEVIDENTLIMITATIONSOFWERIN12ANDREWETALINTRODUCEDTWOINFORMATIONTHEORETICMEASURESOFWORDINFORMATIONCOMMUNICATEDTHEFIRSTONE,NAMEDRELATIVEINFORMATIONLOSTRIL,ISBASEDONMUTUALINFORMATIONI,ORMI7,WHICHMEASURESTHESTATISTICALDEPENDENCEBETWEENTHEINPUTWORDSXANDOUTPUTWORDSY,ANDISCALCULATEDUSINGTHESHANNONENTROPYHASFOLLOWRIL2|WITHHY-3∑1

簡介：SCIENCEDIRECTAVAILABLEONLINEATWWWSCIENCEDIRECTCOMPROCEDIACOMPUTERSCIENCE128201832–3718770509?2018THEAUTHORSPUBLISHEDBYELSEVIERLTDTHISISANOPENACCESSARTICLEUNDERTHECCBYNCNDLICENSEHTTPS//CREATIVECOMMONSORG/LICENSES/BYNCND/40/SELECTIONANDPEERREVIEWUNDERRESPONSIBILITYOFTHESCIENTIFICCOMMITTEEOFTHEINTERNATIONALCONFERENCEONNATURALLANGUAGEANDSPEECHPROCESSING101016/JPROCS201803005?2018THEAUTHORSPUBLISHEDBYELSEVIERLTDTHISISANOPENACCESSARTICLEUNDERTHECCBYNCNDLICENSEHTTPS//CREATIVECOMMONSORG/LICENSES/BYNCND/40/SELECTIONANDPEERREVIEWUNDERRESPONSIBILITYOFTHESCIENTIFICCOMMITTEEOFTHEINTERNATIONALCONFERENCEONNATURALLANGUAGEANDSPEECHPROCESSINGKEYWORDSAUTOMATICSPEECHRECOGNITIONASRERRORDETECTIONASRERRORCORRECTIONASREVALUATION1INTRODUCTIONAUTOMATICSPEECHRECOGNITIONASRSYSTEMSAIMSATCONVERTINGASPEECHSIGNALINTOASEQUENCEOFWORDSEITHERFORTEXTBASEDCOMMUNICATIONPURPOSESORFORDEVICECONTROLLINGTHEPURPOSEOFEVALUATINGASRSYSTEMSISTOSIMULATEHUMANJUDGEMENTOFTHEPERFORMANCEOFTHESYSTEMSINORDERTOMEASURETHEIRUSEFULNESSANDASSESSTHEREMAININGDIFFICULTIESANDESPECIALLYWHENCOMPARINGSYSTEMSTHESTANDARDMETRICOFASREVALUATIONISTHEWORDERRORRATE,WHICHISDEFINEDASTHEPROPORTIONOFWORDERRORSTOWORDSPROCESSEDASRHASMATUREDTOTHEPOINTOFCOMMERCIALAPPLICATIONSBYPROVIDINGTRANSCRIPTIONWITHANACCEPTABLELEVELOFPERFORMANCEWHICHALLOWSINTEGRATIONINTOMANYAPPLICATIONSINGENERAL,ASRSYSTEMSAREEFFECTIVEWHENTHECONDITIONSAREWELLCONTROLLEDNEVERTHELESS,THEYARETOODEPENDENTONTHETASKBEINGPERFORMEDANDTHERESULTSAREFARFROMIDEAL,ANDESPECIALLYFORLARGEVOCABULARYCONTINUOUSSPEECHRECOGNITIONLVCSRAPPLICATIONSTHISLATERSTILLONEOFTHEMOSTCHALLENGINGTASKSINTHEFIELD,DUETOANUMBEROFFACTORS,INCLUDINGPOORARTICULATION,VARIABLE?CORRESPONDINGAUTHORTEL212523344822FAX212523394915EMAILADDRESSERRATTAHIRUCDACMAABSTRACTEVENTHOUGHAUTOMATICSPEECHRECOGNITIONASRHASMATUREDTOTHEPOINTOFCOMMERCIALAPPLICATIONS,HIGHERRORRATEINSOMESPEECHRECOGNITIONDOMAINSREMAINASONEOFTHEMAINIMPEDIMENTFACTORSTOTHEWIDEADOPTIONOFSPEECHTECHNOLOGY,ANDESPECIALLYFORCONTINUOUSLARGEVOCABULARYSPEECHRECOGNITIONAPPLICATIONSTHEPERSISTENTPRESENCEOFASRERRORSHAVEINTENSIFIEDTHENEEDTOFINDALTERNATIVETECHNIQUESTOAUTOMATICALLYDETECTANDCORRECTSUCHERRORSTHECORRECTIONOFTHETRANSCRIPTIONERRORSISVERYCRUCIALNOTONLYTOIMPROVETHESPEECHRECOGNITIONACCURACY,BUTALSOTOAVOIDTHEPROPAGATIONOFTHEERRORSTOTHESUBSEQUENTLANGUAGEPROCESSINGMODULESSUCHASMACHINETRANSLATIONINTHISPAPER,BASICPRINCIPLESOFASREVALUATIONAREFIRSTSUMMARIZED,ANDTHENTHESTATEOFTHECURRENTASRERRORSDETECTIONANDCORRECTIONRESEARCHISREVIEWEDWEFOCUSONEMERGINGTECHNIQUESUSINGWORDERRORRATEMETRICINTERNATIONALCONFERENCEONNATURALLANGUAGEANDSPEECHPROCESSING,ICNLSP2015AUTOMATICSPEECHRECOGNITIONERRORSDETECTIONANDCORRECTIONAREVIEWRAHHALERRATTAHIA,?,ASMAAELHANNANIA,HASSANOUAHMANEAALABORATORYOFINFORMATIONTECHNOLOGIES,NATIONALSCHOOLOFAPPLIEDSCIENCES,UNIVERSITYOFCHOUAIBDOUKKALI,ELJADIDAMOROCCO34RAHHALERRATTAHIETAL/PROCEDIACOMPUTERSCIENCE128201832–37AKEYPRACTICALISSUEWITHASREVALUATIONMETRICSCALCULATIONISFINDINGTHEWORDALIGNMENTBETWEENTHEREFERENCEANDTHEAUTOMATICTRANSCRIPTION,WHICHCONSTITUTETHEFIRSTSTEPINTHEEVALUATIONPROCEDUREINOTHERWORDS,THEREFERENCEANDRECOGNISEDWORDSGETMATCHEDINORDERTODECIDEWHICHWORDHAVEBEENDELETEDORINSERTED,ANDWHICHREFERENCERECOGNISEDSTRINGPAIRSHAVEBEENALIGNEDTOEACHOTHER,WHICHMAYRESULTINAHITORASUBSTITUTIONTHISISNORMALLYDONEBYUSINGTHEVITERBIEDITDISTANCE17TOEFFICIENTLYSELECTTHEREFERENCEANDTHERECOGNISEDWORDSEQUENCEALIGNMENTFORWHICHTHEWEIGHTEDERRORSCOREISMINIMIZEDTHEEDITDISTANCEUSUALLYALIGNSANIDENTICALWEIGHTS1FORTHELEVENSTHEINDISTANCETOALLTHREE,INSERTION,SUBSTITUTIONANDDELETIONYET,UNIFIEDWEIGHTSMAYPRESENTADOUBTTOCHOOSETHEBESTPATHALIGNMENTINTHECASEWHENWEHAVEDIFFERENTONESWHICHHAVETHESAMESCORETOAVOIDTHISPROBLEMMORRISETAL12SUGGESTUSINGDIFFERENTWEIGHTS,SUCHTHATSUBSTITUTIONWILLBEFAVOUREDTHANINSERTIONANDDELETIONINGENERAL,IT’SRECOMMENDEDTOPUTWIWD,ANDWSWIWSWHEREWI,WSANDWDARERESPECTIVELYTHEWEIGHTOFINSERTION,SUBSTITUTION,ANDDELETION23ASREVALUATIONMETRICSACCORDINGTOMCCOWANETAL11ANIDEALASREVALUATIONMETRICSHOULDBEIDIRECTMEASUREASRCOMPONENTINDEPENDENTLYONTHEASRAPPLICATION,IIOBJECTIVETHEMEASURESHOULDBECALCULATEDINANAUTOMATEDMANNER,IIIINTERPRETABLETHEABSOLUTEVALUEOFTHEMEASUREMUSTGIVEANIDEAABOUTTHEPERFORMANCE,ANDIVMODULARTHEEVALUATIONMEASURESHOULDBEGENERALTOALLOWTHOROUGHAPPLICATIONDEPENDENTANALYSISWORDERRORRATEWERISTHEMOSTPOPULARMETRICFORASREVALUATION,ITMEASURESTHEPERCENTAGEOFINCORRECTWORDSSUBSTITUTIONSS,INSERTIONSI,DELETIONSDREGARDINGTHETOTALNUMBEROFWORDSPROCESSEDITISDEFINEDASWERSDIN1SDIHSD1WHEREITOTALNUMBEROFINSERTIONS,DTOTALNUMBEROFDELETIONS,STOTALNUMBEROFSUBSTITUTIONS,HTOTALNUMBEROFHITS,ANDN1TOTALNUMBEROFINPUTWORDSDESPITEOFBEINGTHEMOSTCOMMONLYUSED,WERHASMANYSHORTCOMINGS10FIRSTOFALL,WERISNOTATRUEPERCENTAGEBECAUSEITHASNOUPPERBOUND,SOITDOESN’TTELLYOUHOWGOODASYSTEMIS,BUTONLYTHATONEISBETTERTHANANOTHERMOREOVER,WERISNOTD/ISYMMETRIC,SOINNOISYCONDITIONSWERCOULDEXCEED100,FORTHEFACTTHATITGIVESFARMOREWEIGHTTOINSERTIONSTHANTODELETIONSTHEWERSTILLEFFECTIVEFORSPEECHRECOGNITIONWHEREERRORSCANBECORRECTEDBYTYPING,SUCHAS,DICTATIONHOWEVER,FORALMOSTANYOTHERTYPEOFSPEECH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簡介：中文中文2740字文獻出處文獻出處KLEMPKARANEWMETHODFORTHECTYPEPASSIVEFILTERDESIGNJPRZEGLADELEKTROTECHNICZNY,2012,887A277281本科畢業(yè)設計外文翻譯外文譯文題目（中文）C型無源濾波器的一種新型設計方法學院信息學院專業(yè)電氣工程及其自動化學號學生姓名學生姓名指導教師指導教師日期摘要論文介紹了新型C型諧波電力濾波器設計過程。其目的在于在一個工業(yè)供電系統中減少全部的諧波失真。C型濾波器的新型設計方法是被建議的，也是被工業(yè)發(fā)電所需要的。在設計階段，對于新的計算程序的基礎是假設諧波電流的要求分配在供電網絡與被用于調諧的濾波器之間，這個方法考慮了網絡的等效阻抗。關鍵詞無源濾波器；補償；電力系統諧波；C型濾波器1引言安裝在工廠的大功率非線性負載數量不斷增加的原因是無源諧波濾波器仍然是在連接點處減小電壓畸變的最普通的方式，許多不同結構和不同運行特性的無源LC濾波系統已經被開發(fā)出來了，然而，單調諧單分支濾波器仍然是工業(yè)應用的主導解決方式，而且它缺失是理解更先進濾波結構（如C型濾波器）的基礎。另一個方法是有源濾波器或者是混合濾波器（結合了有源濾波器與無源濾波器）。這種設計和控制能成為一個使用人工智能方法的任務，如神經網絡或者遺傳算法。目前大多數使用的濾波補償裝置結構的主要劣勢是高頻時的濾波能力差。C型濾波器使被包含在寬帶濾波器的范疇之中。寬帶濾波器有其他優(yōu)點，當寬帶濾波器與電力電子整流器合作時，寬帶濾波器使持續(xù)的，寬帶濾波器能比單支濾波器更有效率地抑制換向缺口，即它們有更寬的寬帶。寬帶濾波器也能更高效地消除間入簡諧分量（在鄰著特征諧波的邊頻帶上，其由靜態(tài)頻率轉換器產生）。C型濾波器與單支濾波器相比，也能夠減少有功功率的損失，因為電容電感串聯支路被調諧到基波諧振頻率，基波諧波電流沒通過電阻，避免了大功率的損耗。確立C型濾波器參數的方法在后面介紹。復雜的無源濾波器更頻繁地用人工智能的方法被設計。如遺傳算法，也能在解決其他問題上更有效。2C型濾波器參數的確定對于C性濾波器參數確定，論文介紹了一種新的方法。大功率系統的濾波器設計是一個復雜的任務，除了確定參數使之滿足設計要求，還需檢查由于與電力系統中其他有源元件相互作用而產生的可能的共振點。C型濾波器參數可通過下面的關系確定，此論文介紹了一種新的，更簡單的方法去確定參數，在設計階段，這方法包括假設（在被調諧到諧波的）濾波器和供電網之間的諧波電流的需求分配。這個方法需要考慮網絡等效阻抗。

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簡介：PRZEGL?DELEKTROTECHNICZNYELECTRICALREVIEW,ISSN00332097,R88NR7A/2012277RYSZARDKLEMPKAAKADEMIAGóRNICZOHUTNICZA,WYDZIA?ELEKTROTECHNIKI,AUTOMATYKI,INFORMATYKIIELEKTRONIKIANEWMETHODFORTHECTYPEPASSIVEFILTERDESIGNABSTRACTTHEPAPERPRESENTSTHENEWCTYPEHIGHHARMONICPOWERFILTERDESIGNPROCESSWHOSEAIMISTHEREDUCTIONOFTOTALHARMONICDISTORTIONINANINDUSTRIALPOWERSUPPLYSYSTEMANEWMETHODFORCTYPEFILTERDESIGNISPROPOSEDANDANEXAMPLEOFTHEMETHODAPPLICATIONTOANINDUSTRIALPLANTISPROVIDEDTHEBASISFORTHENEWALGORITHMISASSUMING,ATTHEDESIGNPHASE,THEREQUIREDDISTRIBUTIONOFTHEHARMONICCURRENTBETWEENTHEFILTERTOBETUNEDTOTHATHARMONICANDTHESUPPLYNETWORKTHISMETHODTAKESINTOCONSIDERATIONTHENETWORKEQUIVALENTIMPEDANCESTRESZCZENIENINIEJSZYARTYKU?PRZEDSTAWIAPROJEKTOWANIEENERGETYCZNEGOFILTRUTYPUCWY?SZYCHHARMONICZNYCH,KTóREGOZADANIEMJESTZMNIEJSZENIEWSPó?CZYNNIKAZAWARTO?CIHARMONICZNYCHWPRZEMYS?OWYMSYSTEMIEZASILANIAZAPROPONOWANONOW?METOD?PROJEKTOWANIACFILTRUORAZPRZEDSTAWIONOPRZYK?ADZASTOSOWANIATEJMETODYPROJEKTOWANIAWPRAKTYCEDLAZAK?ADUPRZEMYS?OWEGONOWAMETODAPROJEKTOWANIAFILTRUTYPUCKEYWORDSPASSIVEFILTER,COMPENSATION,POWERSYSTEMHARMONICS,CTYPEFILTERS?OWAKLUCZOWEFILTRYPASYWNE,KOMPENSACJAMOCYBIERNEJ,HARMONICZNE,FILTRTYPUCINTRODUCTIONANEVERINCREASINGNUMBEROFLARGEPOWERNONLINEARLOADS,INSTALLEDININDUSTRYISTHEREASONTHATPASSIVEHARMONICFILTERSARESTILLTHEMOSTCOMMONWAYTOREDUCEVOLTAGEDISTORTIONATTHEIRPOINTSOFCONNECTIONMANYPASSIVELCFILTERSYSTEMS,OFVARIOUSSTRUCTURESANDDIFFERENTOPERATINGCHARACTERISTICSHAVEBEENDEVELOPED1–4NEVERTHELESS,THESINGLETUNEDSINGLEBRANCHFILTERSTILLISTHEDOMINANTSOLUTIONFORINDUSTRIALAPPLICATIONS,ANDITCERTAINLYISTHEBASISFORUNDERSTANDINGMOREADVANCEDFILTERINGSTRUCTURES,SUCHASTHECTYPEFILTERANALTERNATIVESOLUTIONCANBEACTIVEFILTERSORHYBRIDFILTERSTHATCOMBINETHESESTRUCTURES5–7BOTHTHEDESIGNANDCONTROLOFSUCHSYSTEMSCANBEATASKEMPLOYINGARTIFICIALINTELLIGENCEMETHODS,EGNEURALNETWORKSORGENETICALGORITHMS8–10THEPRINCIPALDISADVANTAGEOFTHEMAJORITYOFCURRENTLYUSEDFILTERCOMPENSATINGDEVICESTRUCTURESISPOORFILTERINGOFHIGHFREQUENCIESINORDERTOELIMINATETHESEDISADVANTAGESAREUSUALLYUSEDBROADBANDDAMPEDFILTERSOFTHEFIRST,SECONDORTHIRDORDERTHECTYPEFILTERISINCLUDEDINTHECATEGORYOFBROADBANDFILTERSBROADBANDFILTERSHAVEADDITIONALADVANTAGE,SUBSTANTIALFORTHEIRCOOPERATIONWITHPOWERELECTRONICCONVERTERSTHEYDAMPCOMMUTATIONNOTCHESMOREEFFECTIVELYTHANSINGLEBRANCHFILTERSTHEYHAVEAMUCHBROADERBANDWIDTHTHEYALSOMOREEFFECTIVELYELIMINATEINTERHARMONICCOMPONENTSINSIDEBANDSADJACENTTOCHARACTERISTICHARMONICSGENERATEDBYSTATICFREQUENCYCONVERTERSTHATFILTER,ASCOMPAREDTOSINGLEBRANCHFILTERS,ALSOENSURESREDUCTIONOFACTIVEPOWERLOSSESBECAUSETHE22CLBRANCHFIG1ISTUNEDTOTHEFUNDAMENTALHARMONICFREQUENCYTHEFUNDAMENTALHARMONICCURRENTISNOTPASSINGTHROUGHTHERESISTORRT,AVOIDINGTHEREFORELARGEPOWERLOSSESTHEMETHODFORDETERMININGCTYPEFILTERPARAMETERSISDESCRIBEDIN11COMPLEXPASSIVEFILTERSAREMOREANDMOREOFTENDESIGNEDUSINGARTIFICIALINTELLIGENCEMETHODS,LIKEGENETICALGORITHMS12–13THATCANALSOBEEFFECTIVEINSOLVINGOTHERPROBLEMS14–20DETERMINATIONOFTHECTYPEFILTERPARAMETERSTHEPAPERDESCRIBESANEWMETHODFORDETERMININGTHECTYPEFILTERPARAMETERSDESIGNINGOFFILTERSFORLARGEPOWERSYSTEMSISACOMPLEXTASKASIDEOFDETERMININGTHEFILTERPARAMETERSTOMEETTHEDESIGNREQUIREMENTS,THEFILTERSHALLBECHECKEDFORPOSSIBLERESONANCEOCCURRENCESDUETOINTERACTIONWITHOTHERPASSIVECOMPONENTSINTHEPOWERSYSTEM21–22THEFILTERPARAMETERSCANBEDETERMINEDFROMRELATIONSGIVENIN11THISPAPERPROPOSESANEW,ANDSIMPLER,METHODFORDETERMININGTHEFILTERPARAMETERSTHEMETHODCONSISTSINASSUMING,ATTHEDESIGNPHASE,THEDESIREDDISTRIBUTIONOFTHEHARMONICCURRENTBETWEENTHEFILTERTUNEDTOTHATHARMONICANDTHESUPPLYNETWORKTHISMETHODREQUIRESTAKINGINTOCONSIDERATIONTHENETWORKEQUIVALENTIMPEDANCETHECTYPEFILTERDIAGRAMISSHOWNINFIG1FIG1THECTYPEFILTERCIRCUITTHEFILTERIMPEDANCEISGIVENBY112222111CJCJLJRRCJLJZTTF??????????????????THEL2ANDC2COMPONENTSARETUNEDTOTHEFUNDAMENTALFREQUENCY222121CL??HENCE3????12122212121CJJCRJRZTTF????????????THECTYPEFILTERISTUNEDTOTHERESONANCEANGULARFREQUENCY1??RRN?4??1121221212?????RRNCCCCCCL?HENCERTL2C2C1UIFISILOADLOADPRZEGL?DELEKTROTECHNICZNYELECTRICALREVIEW,ISSN00332097,R88NR7A/2012279FIG3FREQUENCYIMPEDANCECHARACTERISTICSOFATHEPOWERNETWORKEQUIVALENTIMPEDANCEZS,THERESULTANTIMPEDANCEOFTWO3RDHARMONICFILTERSZ2X3H,THECTYPEFILTERIMPEDANCEZCFILTER,THERESULTANTIMPEDANCEOFTWO3RDHARMONICFILTERSANDTHECTYPEFILTERZFBTHEIMPEDANCESEENFROMTHELOADTERMINALSWITHOUTFILTERSZS,THENETWORKEQUIVALENTIMPEDANCEANDTWO3RDHARMONICFILTERSIMPEDANCECONNECTEDINPARALLELZS||Z2X3H,ANDPARALLELCONNECTIONOFTHENETWORKEQUIVALENTIMPEDANCE,TWO3RDHARMONICFILTERSANDTHECTYPEFILTERIMPEDANCESZS||Z2X3H||ZCFILTERFIGURE4ASHOWSTHECTYPEFILTERFREQUENCYCHARACTERISTICSFORDIFFERENTQUALITYFACTORS,FIGURE4BILLUSTRATESTHERELATIONBETWEENTHERESISTANCERTANDTHECOEFFICIENTKTHATINDICATESTHEDISTRIBUTIONOFTHECURRENTHARMONICTOWHICHTHEFILTERISTUNEDTABLE3THEPERCENTAGEDISTRIBUTIONOFTHEHARMONICCURRENTBETWEENTHEFILTERTUNEDTOTHATHARMONICANDTHESUPPLYNETWORKTHECORRESPONDINGRTVALUESANDTHEDESIGNEDFILTERQUALITYFACTORIFISKRT?385615160172444556125221500500100276865194810933005714290753506663330505557502500338408331670251111910900102778DATAINTABLE3SHOWSTHEPERCENTAGEDISTRIBUTIONOFTHEHARMONICCURRENTBETWEENTHEFILTERTUNEDTOTHATHARMONICANDTHESUPPLYNETWORKTHEVALUESOFTHEFACTORKCORRESPONDINGTOTHERTVALUESAREALSOPROVIDEDINTHETABLEFIG4ATHECTYPEFILTERFREQUENCYCHARACTERISTICSFORVARIOUSQUALITYFACTORS,BTHERESISTANCERTVSTHECOEFFICIENTKIMPLEMENTATIONANDMEASUREMENTSINORDERTOVERIFYTHEEFFECTIVENESSOFTHEPROPOSEDMETHODHASBEENDESIGNEDACTYPEFILTERFORANELECTRICARCFURNACEPOWERSUPPLYSYSTEMFIG,2THEDESIGNEDCTYPEFILTERWASINSTALLEDINTHEARCFURNACESUPPLYSYSTEMTHECAPACITANCEC1ISCOMPOSEDOF60CAPACITORS20PERPHASEWITHCAPACITANCE1415?FEACH,WHICHGIVESTOTALCAPACITANCEC17075?FTHECAPACITANCEC2ISCOMPOSEDOF24CAPACITORS8PERPHASEWITHCAPACITANCES246?FEACH,WHICHGIVESTOTALCAPACITANCEC21968?FTHEREACTORL2PARAMETERSSHOULDBERECALCULATEDBECAUSEOFALTERATIONOFTHECAPACITANCEC2DUETOTHEINSTALLATIONMODIFICATIONSL25148MHTHERESISTORRESISTANCEISRT300??10THEDIAGRAMOFTHEACTUALSINGLEPHASEFILTERCIRCUITISDEPICTEDINFIG5FIG5DIAGRAMOFTHEACTUALCTYPEFILTERCIRCUIT115225335405101520253035404550NZCFILTRZ2X3HZSZF|ZCFILTR||Z2X3H||ZS||ZF|A1152253354012345678910NZSZS||Z2X3HZS||Z2X3H||ZCFILTER|ZS||Z2X3H||ZCFILTR||ZS||Z2X3H||ZS|BRFXZRNNA0123456024681012R??QF220QF210QF215QF210QF215QF220RTK0020406081121416050010001500200025003000K1R27686K033R840B8X246?F20X1415?F300?5148MH

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