簡(jiǎn)介：中文中文7900字，字，4500單詞，單詞，25萬(wàn)英文字符萬(wàn)英文字符出處出處BJ?GVINSSONE,EHNP,HILLGRENPDESIGNTHINGSANDDESIGNTHINKINGCONTEMPORARYPARTICIPATORYDESIGNCHALLENGESJDESIGNISSUES,2012,283101116設(shè)計(jì)與設(shè)計(jì)思維設(shè)計(jì)與設(shè)計(jì)思維當(dāng)代參與式設(shè)計(jì)的挑戰(zhàn)當(dāng)代參與式設(shè)計(jì)的挑戰(zhàn)DESIGNTHINGSANDDESIGNTHINKINGCONTEMPORARYPARTICIPATORYDESIGNCHALLENGES學(xué)部（院）建筑與藝術(shù)學(xué)院專業(yè)藝術(shù)設(shè)計(jì)（環(huán)境藝術(shù)設(shè)計(jì)）學(xué)生姓名學(xué)號(hào)指導(dǎo)教師完成日期設(shè)計(jì)與設(shè)計(jì)思維當(dāng)代參與式設(shè)計(jì)的挑戰(zhàn)–2–設(shè)計(jì)過(guò)程設(shè)計(jì)過(guò)程從“事物”到“事物”到事物作為社會(huì)物質(zhì)組件事物作為社會(huì)物質(zhì)組件作為本文背景，我們需要重新梳理“事物”的詞源歷史，以及政治歷史和參與式設(shè)計(jì)的價(jià)值基礎(chǔ)。英文單詞“事物”的詞源，揭示了一個(gè)從社會(huì)和政治集會(huì)由來(lái)的意義發(fā)生在特定的時(shí)間和在某一個(gè)地方,一個(gè)對(duì)象的意義,一個(gè)實(shí)體的物質(zhì)。讓“事物”回到在古代北歐和日耳曼社會(huì)的最初意義，這個(gè)前基督教的單詞的意義是集會(huì)，儀式，和地方糾紛解決與政治決策。理解從事物的物質(zhì)對(duì)象回到事物作為社會(huì)物質(zhì)組成物這個(gè)過(guò)程的重要基礎(chǔ)是如果我們生活在擁有同一個(gè)觀點(diǎn)的地方，我們不需要聚在一起來(lái)解決爭(zhēng)端，因?yàn)闆]有爭(zhēng)端存在。相反如果沒有擁有同樣觀點(diǎn)，我們就需要一個(gè)協(xié)商沖突的地方了。而引起沖突的往往是多元化的視角、關(guān)注點(diǎn)、利益。本文中，我們的出發(fā)點(diǎn)是事物的共享這些社會(huì)物質(zhì)組成物有一個(gè)著名的定義，即布魯諾拉圖的人類非人類集合說(shuō)。我們認(rèn)為，這種關(guān)于“事物”的意義的轉(zhuǎn)變十分有趣，我們從一名設(shè)計(jì)者的角度去反思如何工作，生活以及在設(shè)計(jì)公共領(lǐng)域中發(fā)揮作用。所謂的設(shè)計(jì)公共領(lǐng)域指的是這樣一種空間，它致力于將沖突的對(duì)象和諧化，允許藝術(shù)家之間觀點(diǎn)的多樣性。圍繞著設(shè)計(jì)對(duì)象我們應(yīng)該怎樣合作、分配任務(wù)這些對(duì)象正在改變互動(dòng)表現(xiàn)的空間，而且作為社會(huì)物質(zhì)被繼續(xù)發(fā)掘，它解決爭(zhēng)議、打開新思路、創(chuàng)造新的行為，并且為意想不到的用途做好準(zhǔn)備。參與式設(shè)計(jì)是一個(gè)設(shè)計(jì)方式，它的起源地是北歐國(guó)家的民主化運(yùn)動(dòng)的工作場(chǎng)所。在上世紀(jì)70年代參與并共同決策成為關(guān)系到工作場(chǎng)所和引進(jìn)新技術(shù)的重要因素。在早期的參與式設(shè)計(jì)項(xiàng)目中，人們制造出了新的生產(chǎn)工具，也改變了生產(chǎn)計(jì)劃、控制管理和組織工作，并從用戶的角度來(lái)看待勞動(dòng)分工。參與式設(shè)計(jì)從簡(jiǎn)單的角度出發(fā)，與設(shè)計(jì)結(jié)果有關(guān)的人在設(shè)計(jì)過(guò)程中應(yīng)該具有有發(fā)言權(quán)。這種觀點(diǎn)反映了當(dāng)時(shí)持不同意見的結(jié)果是辯論而不是圍繞一個(gè)新興的設(shè)計(jì)對(duì)象達(dá)成共識(shí)。在這種情況下，參與式設(shè)計(jì)支持資源弱勢(shì)者（通常是當(dāng)?shù)氐墓?huì)）并為其制定了有效的項(xiàng)目策略，使其合法參與設(shè)計(jì)。一個(gè)無(wú)爭(zhēng)議的互補(bǔ)參與式設(shè)計(jì)可以確保在設(shè)計(jì)過(guò)程中，現(xiàn)有的技能可以成為一種資源。因此可以說(shuō)，兩種價(jià)值從戰(zhàn)略上引導(dǎo)參與式設(shè)計(jì)。第一個(gè)價(jià)值是民主的社會(huì)理念，它使適當(dāng)?shù)?、合法的用戶參與進(jìn)我們?cè)谶@里稱其為“分階段進(jìn)行”和“打基礎(chǔ)”的過(guò)程。另一個(gè)價(jià)值是參與者的隱性知識(shí)發(fā)揮作用。在設(shè)計(jì)過(guò)程中不僅需要他們正式和明確的能力，還需要隱性知識(shí)。那些隱藏的實(shí)用、多樣化的技能是制造對(duì)象或器物的基礎(chǔ)。因?yàn)閰⑴c式設(shè)計(jì)出現(xiàn)在上世紀(jì)70年代，所以它可能在理論與實(shí)踐上被看作是事物（或者說(shuō)“正在思考”海德格爾會(huì)這樣稱呼它）的一種“現(xiàn)代”例子。拉圖爾呼吁過(guò)

簡(jiǎn)介：AMAXIMUMPOWERPOINTCONTROLPHOTOVOLTAICSYSTEMMSALHI,ANDRELBACHTIRIABSTRACTAMAXIMUMPOWERPOINTTRACKINGCONTROLMPPTISUSEDFORAPHOTOVOLTAICPVSYSTEMINORDERTOMAXIMIZETHEOUTPUTPOWERIRRESPECTIVEOFTHETEMPERATUREANDIRRADIATIONCONDITIONSANDOFTHELOADELECTRICALCHARACTERISTICSINTHISPAPER,WECONSIDERAPHOTOVOLTAICPANELSUPPLYINGABATTERYFORMAXIMIZINGITSOUTPUTPOWER,WEHAVEUSEDABOOSTDC/DCCONVERTERCONTROLLEDBYAPIREGULATORTHESYNTHESISOFTHISREGULATORPARAMETERSHASBEENACHIEVEDBYUSINGBODEMETHODFORHAVINGATRANSFERFUNCTIONOFTHESYSTEM,WEHAVEUSEDASMALLSIGNALMODELINGTHEORETICALANDSIMULATEDRESULTSAREPRESENTEDEXPERIMENTALRESULTSARECONCLUSIVEKEYWORDSPHOTOVOLTAICSYSTEMS,MAXIMUMPOWERPOINTTRACKING,BOOSTDC/DCCONVERTER,PIREGULATORIINTRODUCTIONPHOTOVOLTAICGENERATORHASANONLINEARBEHAVIOURTHETYPICALPOWERVOLTAGEANDCURRENTVOLTAGECHARACTERISTICSOFPHOTOVOLTAICPANELARESHOWNINFIG1THEPRODUCTOFPVOUTPUTVOLTAGEANDCURRENTHASAMAXIMUMVALUEATAPOINTCALLEDMAXIMUMPOWERPOINT“MPP”FORTHEBESTUTILIZATION,THEPHOTOVOLTAICPANELMUSTOPERATEATITSMPPHOWEVER,THEPVSYSTEMOPERATINGPOINTSHIFTSOUTOFMPPDUETOSOLARIRRADIATION,CELLTEMPERATUREORLOADCHANGESWHENAMAXIMUMPOWERPOINTTRACKING“MPPT”REGULATORISINSERTEDBETWEENTHEPVSYSTEMANDTHELOAD,ITFORCESTHESYSTEMTOOPERATEATITSMPPUNDERALLCONDITIONS,RESULTINGINIMPROVEDEFFICIENCY1MANYMPPTREGULATORSUSEAMICROCONTROLLERORAPERSONALCOMPUTERFORIMPLEMENTINGSOPHISTICALALGORITHMS25,OREVENNEURALNETWORKS6THESESYSTEMSENSUREVERYHIGHPERFORMANCESHOWEVERTHEYAREVERYEXPENSIVEANDOFTENNEEDASEPARATED,STABLEPOWERSUPPLYFORITSOPERATIONTHEREFORETHEYAREONLYSUITABLEFORHIGHPOWERAPPLICATIONS7ANOTHERALGORITHMISBASEDONTHESEARCHINGOFOPERATINGPOINTWHICHVERIFIES0??VPSINCETHESIGNOF“VP??”GIVESTHEDIRECTIONOFMPPTSEARCHINGITISPOSSIBLETODETERMINETHEMAXIMUMPOWEROPERATINGBYCONTINUOUSMEASUREMENTOFPOWERANDVOLTAGEINRECENTYEARS,MANYMPPTAPPLICATIONSBASEDONTHISSEARCHINGALGORITHMHAVEBEENPRESENTED8IN9AND10,ANANALOGMPPTCONTROLSYSTEMISPROPOSED,WHEREABOOSTDC/DCCONVERTERISHANDEDFORHAVING“VOUTI??”EQUALSZEROFIG3,WHEREOUTIISTHEDC/DCCONVERTEROUTPUTCURRENTINTHISMETHOD,INORDERTOREDUCETHECOMPLEXITYOFTHEMANUSCRIPTRECEIVEDJANUARY13,2010MSALHIISMEMBEROF″LESSILABORATORY″INFACULTYOFSCIENCESDHARMEHRAZFSDM,FEZ,MOROCCORELBACHTIRIISAPROFESSORIN″HIGHSCHOOLOFTECHNOLOGY″,FEZ,MOROCCOSYSTEM,THEBATTERYISCONSIDEREDASACONSTANTVOLTAGEEANDTHECONVERTERISASSUMEDTOBEIDEALSO,THEOUTPUTPOWERBPOFDC/DCCONVERTEREQUALSTHEPVOUTPUTPOWERPASIMILARWORKISPROPOSEDIN11,THATTHEBATTERYISCONSIDEREDASACONSTANTVOLTAGEINSERIESWITHACONSTANTRESISTANCEBRTHISWORKISIMPROVEDIN12BYTAKINGINTOACCOUNTTHELOSSESINTHEDC/DCCONVERTER,PARTICULARLY,THESWITCHLOSSESINTHEMOSFETTRANSISTORINTHISPAPER,WERECONSIDERWORKSPROPOSEDIN912FOREXPERIMENTALIMPLEMENTATIONABLOCKDIAGRAMOFTHEPROPOSEDSYSTEMISSHOWNINFIG3AABOOSTDC/DCCONVERTERISUSEDTOINTERFACETHEPVOUTPUTTOTHEBATTERYINORDERTOTRACKTHEMAXIMUMPOWERPOINTOFTHEPVMODULEFORTHATTHEMPPTCONTROLLERMUSTKEEP“VP??”EQUALSZEROWHATISPOSSIBLEWITHACTIONONTHEDUTYCYCLE10≤≤ΑΑACCORDINGTOSOLARIRRADIATIONΛANDTEMPERATURETDUTYCYCLEISTHEONEOFASIGNALGENERATEDBYTHEPIREGULATORFORSYNTHESIZINGTHEPARAMETERSOFTHISREGULATOR,WEHAVEDEVELOPEDATRANSFERFUNCTIONFORTHESYSTEMUSINGASMALLSIGNALMODELTHEPIREGULATORCOEFFICIENTSPKANDIKAREOBTAINEDBYFREQUENCYSYNTHESISTHESYNOPTICSCHEMEOFTHEPROPOSEDMETHODISSHOWNINFIG3BWITHMEASUREMENTSOFTHEPVPANELVOLTAGEANDCURRENT,THEOUTPUTPOWERISCALCULATEDANDDERIVEDWITHRESPECTTOVOLTAGEINORDERTOOBTAINTHEDVDPWHOISCOMPAREDTOZEROTHERESULTINGDIFFERENCESIGNALERRORSIGNALISUSEDASANINPUTSIGNALTOTHEPIREGULATORWHICHDELIVERSACONTROLSIGNALGSVFORTHEBOOSTDC/DCIITHEORETICALSTUDYTHEPOWERELECTRONICCONVERTERISABOOSTCONVERTERINSERTEDBETWEENTHEPVGENERATORANDTHEBATTERYFIG2AITISCONTROLLEDBYASIGNALWITHADUTYCYCLE10≤≤ΑΑTHATGIVESTHERATIOBETWEENTHEINPUTANDTHEOUTPUTVOLTAGEWHENTHECONDUCTIONISCONTINUOUSTHETRANSISTORISONDURINGTΑANDOFFDURINGTHERESTOFTHEPERIODIE,T1Α?THEDIODESTATE,INCONTINUOUSCONDUCTIONMODEISCOMPLEMENTARYOFTHETRANSISTORONETHEINDUCTANCEISCHARGEDTHROUGHTHETRANSISTOR,ANDITISDISCHARGED,OUTPUTTHROUGHTHEDIODE,INTHEBATTERYIFTHECHOPPINGFREQUENCYISENOUGHHIGHERTHANTHESYSTEMCHARACTERISTICFREQUENCIES,WECANREPLACETHECONVERTERWITHANEQUIVALENTCONTINUOUSMODELWEWILLCONSIDERSOTHEMEANVALUES,OVERTHECHOPPINGPERIOD,OFTHEELECTRICQUANTITIESFIG2BA18THMEDITERRANEANCONFERENCEONCONTROLANDINBLOCKCONVERTERBATTERY,EQUATIONS811AREUSEDTHEPROPOSEDCONTROLLERCIRCUITTHATFORCESTHESYSTEMTOOPERATEATITSOPTIMALOPERATINGPOINTUNDERVARIABLETEMPERATUREANDIRRADIATIONCONDITIONSISSHOWNINFIG7FIG6BLOCKDIAGRAMFORSYSTEMSIMULATIONISOLRSHVIRSISOLRSHVIRS00004A/KSHORTCIRCUITCURRENTTEMPERATURECOEFFICIENTATISCKI55WMAXIMUMPOWERPMAX174VMAXIMUMPOWERVOLTAGEVMPP315AMAXIMUMPOWERCURRENTIMPP345ASHORTCIRCUITCURRENTISC217VOPENCIRCUITVOLTAGEVO25°CCELLTEMPERATURETVALUEQUANTITYSYMBOL00004A/KSHORTCIRCUITCURRENTTEMPERATURECOEFFICIENTATISCKI55WMAXIMUMPOWERPMAX174VMAXIMUMPOWERVOLTAGEVMPP315AMAXIMUMPOWERCURRENTIMPP345ASHORTCIRCUITCURRENTISC217VOPENCIRCUITVOLTAGEVO25°CCELLTEMPERATURETVALUEQUANTITYSYMBOLYS0PIG0SΕS?ΑSYS0PIG0SΕS?ΑSPVΑMPPTCONTROLSYSTEMIΑVPCONVERTERBATTERYTEMPERATURETVTIPVMODULEIRRADIATIONΛΛPVΑMPPTCONTROLSYSTEMIΑVPCONVERTERBATT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簡(jiǎn)介：3000英文單詞，17000英文字符，中文5100字出處INDI,TS,YALAGI,PS,NIRGUDE,MA2016USEOFJAVAEXCEPTIONSTACKTRACETOIMPROVEBUGFIXINGSKILLSOFINTERMEDIATEJAVALEARNERS2016INTERNATIONALCONFERENCEONLEARNINGANDTEACHINGINCOMPUTINGANDENGINEERINGLATICE使用JAVA異常堆棧跟蹤來(lái)改進(jìn)中級(jí)JAVA學(xué)習(xí)者的漏洞修復(fù)技巧作者TRUPTISINDI，PRATIBHASYALAGI,MANISHAANIRGUDE譯文摘要今天的行業(yè)需要關(guān)注開發(fā)過(guò)程中的軟件質(zhì)量，而不僅僅是軟件交付?？梢栽谲浖_發(fā)生命周期的不同階段測(cè)量，監(jiān)控和測(cè)試軟件質(zhì)量。軟件的重大失敗會(huì)影響金錢以及公司的聲譽(yù)。在這種情況下，在更短的時(shí)間內(nèi)修復(fù)漏洞是一個(gè)重要因素。今天對(duì)工科學(xué)生的挑戰(zhàn)是擁有程序編寫技能以及漏洞修復(fù)技能，并在規(guī)定的時(shí)間內(nèi)完成任務(wù)。在這里，我們介紹了如何改進(jìn)漏洞修復(fù)技巧的實(shí)驗(yàn)。我們?cè)谛畔⒓夹g(shù)學(xué)科三年級(jí)學(xué)生的JAVA編程課程中進(jìn)行了實(shí)驗(yàn)。這個(gè)實(shí)驗(yàn)是使用JAVA異常堆棧跟蹤來(lái)查找JAVA程序中的漏洞并在規(guī)定的時(shí)間內(nèi)修復(fù)它們。為了測(cè)試該實(shí)驗(yàn)的效果，進(jìn)行了預(yù)測(cè)試后實(shí)驗(yàn)研究以及感知調(diào)查。我們發(fā)現(xiàn)超過(guò)65％的學(xué)生在規(guī)定的時(shí)間內(nèi)成功修復(fù)了漏洞，大約20％的學(xué)生能夠修復(fù)漏洞，但不是在規(guī)定的時(shí)間內(nèi)。大約8085％的學(xué)生在課程內(nèi)處于分析和修復(fù)程序中漏洞的狀態(tài)。關(guān)鍵字JAVA編程，調(diào)試，JAVA異常堆棧跟蹤，異常處理，漏洞修復(fù)技巧1介紹計(jì)算機(jī)編程是工程課程的基礎(chǔ)課程。此類中添加的各種計(jì)算機(jī)編程語(yǔ)言是C編程語(yǔ)言，C，C＃，JAVA等。這些計(jì)算機(jī)編程語(yǔ)言是軟件開發(fā)過(guò)程所需的基本構(gòu)建塊。學(xué)生應(yīng)具備良好的計(jì)算機(jī)編程概念知識(shí)，包括程序編寫技巧，問(wèn)題解決方案設(shè)計(jì)技巧，程序分析技巧和程序調(diào)試技巧。如今，行業(yè)需要關(guān)注開發(fā)過(guò)程中的軟件質(zhì)量，而不僅僅是軟件交付。可以在軟件開發(fā)生命周期的不同階段測(cè)量，監(jiān)控和測(cè)試軟件質(zhì)量。在教授編程課程時(shí)，需要向?qū)W生詳細(xì)闡述所有這些事實(shí)。在今天的教學(xué)過(guò)程中，只有程序?qū)懽骷寄艿闹R(shí)是不夠的8。除了程序編寫技巧，漏洞修復(fù)技能還可以幫助學(xué)生編寫高質(zhì)量的程序。在許多實(shí)際系統(tǒng)中，例如服務(wù)器，基于安卓平臺(tái)的系統(tǒng)和設(shè)備以及嵌入式系統(tǒng)，由于其面向?qū)ο蟮奶匦裕€(wěn)定性，可移植性和安全性，JAVA是高要求的編程語(yǔ)言7。因此，IT行業(yè)需要JAVA程序員有優(yōu)秀的程序?qū)懽骷记珊吐┒葱迯?fù)技巧。在本文中，我們介紹了在信息技術(shù)學(xué)科三年級(jí)學(xué)生的JAVA編程課程中進(jìn)行的實(shí)驗(yàn)。本實(shí)驗(yàn)的主要目的是使用JAVA異常堆棧跟蹤來(lái)理解JAVA程序中的異常，并在規(guī)定的時(shí)間內(nèi)修復(fù)程序中的錯(cuò)誤。在所提出的實(shí)驗(yàn)中，進(jìn)行了預(yù)測(cè)試后實(shí)驗(yàn)研究以及感知調(diào)查。代碼非常悲慘，如果之后沒有刪除調(diào)試消息，則會(huì)引入運(yùn)行時(shí)開銷。在所提出的實(shí)驗(yàn)中遵循的方法不需要很長(zhǎng)時(shí)間并且不需要經(jīng)常進(jìn)行代碼修改，而是僅需要理解和分析異常堆棧跟蹤以修復(fù)程序中的漏洞/錯(cuò)誤。在這里，學(xué)生需要了解JAVA異常堆棧跟蹤在程序捕獲或拋出異常時(shí)的作用。異常堆棧跟蹤的知識(shí)將幫助學(xué)生找到導(dǎo)致錯(cuò)誤的正確代碼。因此JAVA異常堆棧跟蹤將比其他方法更快地幫助學(xué)生修復(fù)漏洞。實(shí)驗(yàn)的目標(biāo)是了解異常堆棧跟蹤并分析異常堆棧跟蹤，以提高對(duì)JAVA學(xué)習(xí)者的概念性理解并修復(fù)JAVA程序中的漏洞。本實(shí)驗(yàn)的主要目的是使用JAVA異常堆棧跟蹤來(lái)理解JAVA程序中的異常，并在規(guī)定的時(shí)間內(nèi)修復(fù)程序中的錯(cuò)誤。為了找到研究問(wèn)題的答案，與信息技術(shù)學(xué)科的三年級(jí)工科學(xué)生一起進(jìn)行了測(cè)試前測(cè)試實(shí)驗(yàn)研究以及感知調(diào)查。首先進(jìn)行了預(yù)編程測(cè)試。在這里，每個(gè)學(xué)生都有三個(gè)帶有漏洞的程序。提到持續(xù)時(shí)間來(lái)修復(fù)這些程序中的漏洞并成功執(zhí)行這些程序。每個(gè)學(xué)生的程序執(zhí)行狀態(tài)和持續(xù)時(shí)間記錄如圖2所示。然后，老師使用功率點(diǎn)演示和演示示例教授“JAVA異常堆棧跟蹤”概念。概念解釋后，在實(shí)驗(yàn)室進(jìn)行編程后測(cè)試。在這個(gè)測(cè)試中，三個(gè)程序給學(xué)生帶來(lái)了錯(cuò)誤。在此，還提到了學(xué)生成功執(zhí)行各自課程的指定時(shí)間。我們確保在測(cè)試前和測(cè)試后給出的程序的認(rèn)知水平相同。發(fā)布每個(gè)學(xué)生記下的程序執(zhí)行狀態(tài)和持續(xù)時(shí)間，如圖4所示。4方法研究問(wèn)題是“如何改善JAVA學(xué)習(xí)者的漏洞/錯(cuò)誤修復(fù)技巧”以下是為此實(shí)驗(yàn)設(shè)定的目標(biāo)成就（1）學(xué)生將能夠獲得JAVAEXCEPTIONSTACKTRACE的知識(shí)。（2）學(xué)生將能夠閱讀和理解JAVA異常堆棧跟蹤。（3）學(xué)生將在分析堆棧跟蹤后采取適當(dāng)?shù)拇胧﹣?lái)修復(fù)程序中的錯(cuò)誤。（4）學(xué)生在解決當(dāng)前錯(cuò)誤時(shí)不會(huì)產(chǎn)生新的錯(cuò)誤。（5）最后，學(xué)生將在規(guī)定的時(shí)間內(nèi)使用STACKTRACE修復(fù)JAVA程序中的錯(cuò)誤。41使用樣品在這個(gè)實(shí)驗(yàn)中，我們考慮了中級(jí)JAVA學(xué)習(xí)者。隨機(jī)選擇了40名來(lái)自信息技術(shù)工程系的三年級(jí)學(xué)生。42實(shí)驗(yàn)裝置該研究是為“JAVA編程”課程進(jìn)行的。在本課程中，每周有兩個(gè)講座和兩個(gè)小時(shí)的實(shí)驗(yàn)課。在本課程中，學(xué)生學(xué)習(xí)了基本的JAVA編程和對(duì)異常處理的理解。在學(xué)期結(jié)束時(shí)，在編程實(shí)驗(yàn)室進(jìn)行了第一次預(yù)測(cè)試，其中向每個(gè)學(xué)生提供了三個(gè)有錯(cuò)誤的程序。提到持續(xù)時(shí)間來(lái)修復(fù)錯(cuò)誤在那些程序中并成功執(zhí)行這些

簡(jiǎn)介：字?jǐn)?shù)英文字?jǐn)?shù)英文28872887單詞，單詞，1640016400字符；中文字符；中文54305430漢字漢字出處出處STUARTSTUARTRUSSELL,DANIELRUSSELL,DANIELDEWEY,MAXDEWEY,MAXTEGMARKRESEARCHTEGMARKRESEARCHPRIORITIESPRIORITIESFORFORROBUSTROBUSTANDANDBENEFICIALBENEFICIALARTIFICIALARTIFICIALINTELLIGENCEJASSOCIATIONINTELLIGENCEJASSOCIATIONFORFORTHETHEADVANCEMENTADVANCEMENTOFOFARTIFICIALARTIFICIALINTELLIGENCE2015,364105114INTELLIGENCE2015,364105114外文文獻(xiàn)外文文獻(xiàn)RESEARCHPRIORITIESFORROBUSTANDBENEFICIALARTIFICIALINTELLIGENCEABSTRACTSUCCESSINTHEQUESTFORARTIFICIALINTELLIGENCEHASTHEPOTENTIALTOBRINGUNPRECEDENTEDBENEFITSTOHUMANITY,ANDITISTHEREFOREWORTHWHILETOINVESTIGATEHOWTOMAXIMIZETHESEBENEFITSWHILEAVOIDINGPOTENTIALPITFALLSTHISARTICLEGIVESNUMEROUSEXAMPLESWHICHSHOULDBYNOMEANSBECONSTRUEDASANEXHAUSTIVELISTOFSUCHWORTHWHILERESEARCHAIMEDATENSURINGTHATAIREMAINSROBUSTANDBENEFICIALKEYWORDSARTIFICIALINTELLIGENCE,SUPERINTELLIGENCE,ROBUST,BENEFICIAL,SAFETY,SOCIETYARTIFICIALINTELLIGENCEAIRESEARCHHASEXPLOREDAVARIETYOFPROBLEMSANDAPPROACHESSINCEITSINCEPTION,BUTFORTHELAST20YEARSORSOHASBEENFOCUSEDONTHEPROBLEMSSURROUNDINGTHECONSTRUCTIONOFINTELLIGENTAGENTS–SYSTEMSTHATPERCEIVEANDACTINSOMEENVIRONMENTINTHISCONTEXT,THECRITERIONFORINTELLIGENCEISRELATEDTOSTATISTICALANDECONOMICNOTIONSOFRATIONALITY–COLLOQUIALLY,THEABILITYTOMAKEGOODDECISIONS,PLANS,ORINFERENCESTHEADOPTIONOFPROBABILISTICREPRESENTATIONSANDSTATISTICALLEARNINGMETHODSHASLEDTOALARGEDEGREEOFINTEGRATIONANDCROSSFERTILIZATIONBETWEENAI,MACHINELEARNING,STATISTICS,CONTROLTHEORY,NEUROSCIENCE,ANDOTHERFIELDSTHEESTABLISHMENTOFSHAREDTHEORETICALFRAMEWORKS,COMBINEDWITHBYNOMEANSBEINTERPRETEDASANEXHAUSTIVELISTLABORMARKETFORECASTINGWHENANDINWHATORDERSHOULDWEEXPECTVARIOUSJOBSTOBECOMEAUTOMATEDFREYANDOSBORNE2013HOWWILLTHISAFFECTTHEWAGESOFLESSSKILLEDWORKERS,THECREATIVEPROFESSIONS,ANDDIFFERENTKINDSOFINFORMATIONWORKERSSOMEHAVEHAVEARGUEDTHATAIISLIKELYTOGREATLYINCREASETHEOVERALLWEALTHOFHUMANITYASAWHOLEBRYNJOLFSSONANDMCAFEE2014HOWEVER,INCREASEDAUTOMATIONMAYPUSHINCOMEDISTRIBUTIONFURTHERTOWARDSAPOWERLAWBRYNJOLFSSON,MCAFEE,ANDSPENCE2014,ANDTHERESULTINGDISPARITYMAYFALLDISPROPORTIONATELYALONGLINESOFRACE,CLASS,ANDGENDERRESEARCHANTICIPATINGTHEECONOMICANDSOCIETALIMPACTOFSUCHDISPARITYCOULDBEUSEFULOTHERMARKETDISRUPTIONSSIGNIFICANTPARTSOFTHEECONOMY,INCLUDINGFINANCE,INSURANCE,ACTUARIAL,ANDMANYCONSUMERMARKETS,COULDBESUSCEPTIBLETODISRUPTIONTHROUGHTHEUSEOFAITECHNIQUESTOLEARN,MODEL,ANDPREDICTHUMANANDMARKETBEHAVIORSTHESEMARKETSMIGHTBEIDENTIFIEDBYACOMBINATIONOFHIGHCOMPLEXITYANDHIGHREWARDSFORNAVIGATINGTHATCOMPLEXITYMANYIKAETAL2013POLICYFORMANAGINGADVERSEEFFECTSWHATPOLICIESCOULDHELPINCREASINGLYAUTOMATEDSOCIETIESFLOURISHFOREXAMPLE,BRYNJOLFSSONANDMCAFEEBRYNJOLFSSONANDMCAFEE2014EXPLOREVARIOUSPOLICIESFORINCENTIVIZINGDEVELOPMENTOFLABORINTENSIVESECTORSANDFORUSINGAIGENERATEDWEALTHTOSUPPORTUNDEREMPLOYEDPOPULATIONSWHATARETHEPROSANDCONSOFINTERVENTIONSSUCHASEDUCATIONALREFORM,APPRENTICESHIPPROGRAMS,LABORDEMANDINGINFRASTRUCTUREPROJECTS,ANDCHANGESTOMINIMUMWAGELAW,TAXSTRUCTURE,ANDTHESOCIALSAFETYNETGLAESER2014HISTORYPROVIDESMANYEXAMPLESOFSUBPOPULATIONSNOTNEEDINGTOWORKFORECONOMICSECURITY,RANGINGFROMARISTOCRATSINANTIQUITYTOMANYPRESENTDAYCITIZENSOFQATARWHATSOCIETALSTRUCTURESANDOTHERFACTORSDETERMINEWHETHERSUCHPOPULATIONSFLOURISHUNEMPLOYMENTISNOTTHESAMEASLEISURE,ANDTHEREAREDEEPLINKSBETWEENUNEMPLOYMENTANDUNHAPPINESS,SELFDOUBT,ANDISOLATIONHETSCHKO,KNABE,ANDSCHO¨B2014CLARKANDOSWALD1994UNDERSTANDINGWHATPOLICIESANDNORMSCAN

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簡(jiǎn)介：1SENSITIVITYANALYSISOFTHECCHE1DCHANNELNETWORKMODELWEIMINGWU1,DALMOAVIEIRA2,ABDULKHAN3ANDSAMSYWANG41,2,3AND4,NATIONALCENTERFORCOMPUTATIONALHYDROSCIENCEANDENGINEERING,SCHOOLOFENGINEERING,THEUNIVERSITYOFMISSISSIPPI,MS38677PH6629155673/6629157788FAX6629157796EMAILWUWMNCCHEOLEMISSEDUABSTRACTTHECCHE1DMODELWASDESIGNEDTOSIMULATELONGTERMFLOWANDSEDIMENTTRANSPORTINCHANNELNETWORKSTOSUPPORTTHEDECPROJECTITUSESEITHERTHEDYNAMICWAVEORTHEDIFFUSIVEWAVEMODELTOCOMPUTEUNSTEADYFLOWSINCHANNELNETWORKSWITHCOMPOUNDCROSSSECTIONS,TAKINGINTOACCOUNTTHEEFFECTSOFINSTREAMHYDRAULICSTRUCTURES,SUCHASCULVERTS,WEIRS,DROPSTRUCTURES,ANDBRIDGECROSSINGSITSIMULATESNONUNIFORMSEDIMENTTRANSPORTUSINGANONEQUILIBRIUMAPPROACH,ANDCALCULATESBANKTOEEROSIONANDMASSFAILUREDUETOCHANNELINCISIONTHECCHE1DMODELDECOUPLESTHEFLOWANDSEDIMENTTRANSPORTCALCULATIONSBUTCOUPLESTHECALCULATIONSOFNONUNIFORMSEDIMENTTRANSPORT,BEDCHANGESANDBEDMATERIALSORTINGINORDERTOENHANCETHENUMERICALSTABILITYOFTHEMODELINTHISPAPER,THESENSITIVITYOFCCHE1DTOPARAMETERSSUCHASTHENONEQUILIBRIUMADAPTATIONLENGTHOFSEDIMENTTRANSPORTANDTHEMIXINGLAYERTHICKNESSISEVALUATEDINCASESOFCHANNELAGGRADATIONANDDEGRADATIONINLABORATORYFLUMESASWELLASINANATURALCHANNELNETWORKINTHECASEOFCHANNELDEGRADATION,THESIMULATEDSCOURPROCESSISNOTSENSITIVETOVARIATIONINVALUESOFTHENONEQUILIBRIUMADAPTATIONLENGTH,BUTTHEDETERMINATIONOFTHEMIXINGLAYERTHICKNESSISIMPORTANTTOTHECOMPUTATIONSOFTHEEQUILIBRIUMSCOURDEPTHANDOFTHEBEDMATERIALSIZEDISTRIBUTIONATTHEARMORINGLAYERTHESIMULATEDBEDPROFILESINTHECASEOFCHANNELAGGRADATIONANDTHECALCULATEDSEDIMENTYIELDINTHECASEOFNATURALCHANNELNETWORKAREINSENSITIVETOTHEPRESCRIPTIONOFBOTHTHENONEQUILIBRIUMADAPTATIONLENGTHANDTHEMIXINGLAYERTHICKNESSTHECCHE1DMODELCANPROVIDERELIABLERESULTSEVENWHENTHESETWOPARAMETERSAREGIVENAWIDERANGEOFVALUESINTRODUCTIONTHECCHE1DMODELWASDESIGNEDTOSIMULATELONGTERMFLOWANDSEDIMENTTRANSPORTINCHANNELNETWORKSTOSUPPORTTHEDEMONSTRATIONEROSIONCONTROLDECPROJECT,WHICHISANINTERAGENCYCOOPERATIVEEFFORTAMONGTHEUSARMYCORPSOFENGINEERSCOE,THENATURALRESOURCESCONSERVATIONSERVICENRCSANDTHEAGRICULTURALRESEARCHSERVICEARSOFTHEUSDEPARTMENTOFAGRICULTURETHECCHE1DVERSION20WASBASEDONTHEUNSTEADYFLOWMODELDWAVNETDIFFUSIONWAVEMODELFORCHANNELNETWORKS,LANGENDEON,1996ANDTHESEDIMENTTRANSPORTMODELBEAMSBEDANDBANKEROSIONANALYSISMODELFORSTREAMS,LIETAL,1996ITWASSIGNIFICANTLYIMPROVEDBYIMPLEMENTINGTHEDYNAMICWAVEMODELANDTHENONEQUILIBRIUMSEDIMENTTRANSPORTMODELWU,VIEIRAANDWANG2000THECCHE1DWASINTEGRATEDWITHTHELANDSCAPEANALYSISTOOLTOPAZGARBRECHTANDMARTZ,1995ANDWITHTHEWATERSHEDMODELSAGNPSBOSCHETAL,1998ANDSWATARNOLDETAL,1993,THROUGHANARCVIEWGISBASEDGRAPHICALUSERINTERFACEVIEIRAANDWU,2000THECCHE1DHASBEENSUCCESSFULLYTESTEDINVARIOUSEXPERIMENTALANDFIELDCASESBECAUSESEVERALPARAMETERSINCCHE1DMUSTBEPRESCRIBEDEMPIRICALLY,ITISVERYIMPORTANTTOKNOWTHERESPONSEOFTHEMODELCOPYRIGHTASCE2004WORLDWATERCONGRESS2001COPYRIGHTASCE2004WORLDWATERCONGRESS2001BRIDGINGTHEGAPDOWNLOADEDFROMASCELIBRARYORGBYUNIVERSITYOFLIVERPOOLON04/19/15COPYRIGHTASCEFORPERSONALUSEONLYALLRIGHTSRESERVED3WHEREAMISTHECROSSSECTIONALAREAOFTHEMIXINGLAYERTAB??/ISTHETOTALBEDDEFORMATIONRATE,DEFINEDAS∑????NKBKBTATA1NISTHETOTALNUMBEROFSIZECLASSESBKPISPBKOFTHEMIXINGLAYERWHEN0//≤?????TATABM,ANDBKPISTHEPERCENTAGEOFTHEKTHSIZECLASSOFBEDMATERIALINSUBSURFACELAYERUNDERMIXINGLAYERWHEN0//?????TATABMEQ1ISDISCRETIZEDUSINGTHEPREISSMANNIMPLICITSCHEME,WITHITSSOURCETERMBEINGDISCRETIZEDBYTHESAMEFORMULATIONASTHATFORTHERIGHTHANDTERMOFEQ3INORDERTOSATISFYTHESEDIMENTCONTINUITYEQ4ISDISCRETIZEDBYADIFFERENCESCHEMETHATSATISFIESMASSCONSERVATIONACOUPLEDMETHODFORTHECALCULATIONSOFSEDIMENTTRANSPORT,BEDCHANGEANDBEDMATERIALSORTINGISESTABLISHEDBYIMPLICITLYTREATINGTHEPBKINEQ2AS1NBKPANDSIMULTANEOUSLYSOLVINGTHESETOFALGEBRAICEQUATIONSCORRESPONDINGTOEQS14BYUSINGTHEDIRECTMETHODPROPOSEDBYWUANDLI1992THISCOUPLEDMETHODISMORESTABLEANDCANMOREEASILYELIMINATETHEOCCURRENCEOFTHECOMPUTEDNEGATIVEBEDMATERIALGRADATION,WHENCOMPAREDTOTHEDECOUPLEDMETHOD,INWHICHTHEPBKINEQ2ISTREATEDEXPLICITLYHOWEVER,THEAFOREMENTIONEDCOUPLINGPROCEDUREFORSEDIMENTTRANSPORT,BEDCHANGEANDBEDMATERIALSORTINGCOMPUTATIONSISSTILLDECOUPLEDFROMTHEFLOWCALCULATIONMODELPARAMETERSTOBEANALYZEDTHEPARAMETERSINNUMERICALMODELSOFFLOWANDSEDIMENTTRANSPORTINRIVERSCANBECLASSIFIEDINTOTWOGROUPSNUMERICALPARAMETERSANDPHYSICALPARAMETERSTHENUMERICALPARAMETERSRESULTFROMTHEDISCRETIZATIONANDSOLUTIONPROCEDURES,WHILETHEPHYSICALPARAMETERSREPRESENTTHEPHYSICALPROPERTIESOFFLOWANDSEDIMENT,ORTHEQUANTITIESDERIVEDFROMTHEMODELINGOFFLOWANDSEDIMENTTRANSPORTINTHECCHE1DCHANNELNETWORKMODEL,THENUMERICALPARAMETERSINCLUDECOMPUTATIONTIMESTEPANDGRIDLENGTH,ANDTHEPHYSICALPARAMETERSARETHEMANNING’SROUGHNESSCOEFFICIENT,NONEQUILIBRIUMADAPTATIONLENGTHOFSEDIMENTTRANSPORT,MIXINGLAYERTHICKNESS,BEDMATERIALPOROSITY,ETCUSUALLY,THENUMERICALPARAMETERSCANBEMOREEASILYHANDLEDTHANTHEPHYSICALPARAMETERSSOMEOFTHESEPHYSICALPARAMETERS,SUCHASTHEMANNING’SROUGHNESSCOEFFICIENTANDBEDMATERIALPOROSITY,HAVEBEENSTUDIEDBYMANYINVESTIGATORSANDMAYBEDETERMINEDBYMEASUREMENTHOWEVER,THENONEQUILIBRIUMADAPTATIONLENGTHANDTHEMIXINGLAYERTHICKNESSARELESSUNDERSTOODANDMUSTBEPRESCRIBEDEMPIRICALLYTHEREFORE,THEMAINCONCERNINTHISPAPERISTOANALYZETHEINFLUENCEOFTHESETWOPHYSICALPARAMETERSONTHESIMULATIONRESULTSTHENONEQUILIBRIUMADAPTATIONLENGTHLSCHARACTERIZESTHEDISTANCEFORSEDIMENTTOADJUSTFROMANONEQUILIBRIUMSTATETOANEQUILIBRIUMSTATEWU,RODIANDWENKA2000ANDWUANDVIEIRA2000REVIEWEDINDETAILTHOSEEMPIRICALANDSEMIEMPIRICALMETHODSFORDETERMININGLSPUBLISHEDINTHELITERATURE,SUCHASBELLANDSUTHERLAND’S1981,ARMANINIANDDISILVIO’S1988,ETCITWASFOUNDTHATTHOSEMETHODSPROVIDESIGNIFICANTLYDIFFERENTESTIMATIONSOFLSINCCHE1D,THEADAPTATIONLENGTHFORWASHLOADTRANSPORTISSETASINFINITELYLARGEBECAUSETHENETEXCHANGEBETWEENWASHLOADANDCHANNELBEDISUSUALLYNEGLIGIBLETHEADAPTATIONLENGTHFORSUSPENDEDLOADTRANSPORTISCALCULATEDWITHLSUH/ΑΩS,INWHICHUISTHESECTIONAVERAGEDVELOCITY,HISTHEFLOWDEPTH,ΩSISTHESETTLINGVELOCITYOFSEDIMENTPARTICLES,ANDΑISTHEADAPTATIONCOEFICIENTWHICHCANBECALCULATEDWITHARMANINIANDDISILVIO’S1988METHOD,ORSPECIFIEDASACONSTANTVALUEBYTHEUSERTHEADAPTATIONLENGTHFORBEDLOADTRANSPORTISSUGGESTEDTOSETASTHELENGTHOFTHEDOMINANTBEDFORMS,SUCHAS73H,THELENGTHOFSANDDUNESCOPYRIGHTASCE2004WORLDWATERCONGRESS2001COPYRIGHTASCE2004WORLDWATERCONGRESS2001BRIDGINGTHEGAPDOWNLOADEDFROMASCELIBRARYORGBYUNIVERSITYOFLIVERPOOLON04/19/15COPYRIGHTASCEFORPERSONALUSEONLYALLRIGHTSRESERVED

簡(jiǎn)介：ANELECTRICPOWERSAVINGHYDRAULICFATIGUETESTINGMACHINEMECHANICALHYDRAULICPULSATORMACHINEWITHTHREECONTROLLOOPSHASBEENCONSTRUCTEDSTABILITYOFCONTROLIS05PERCENTOFTHERANGECONSUMPTIONOFELECTRICPOWERISABOUTONETHIRDOFELECTROHYDRAULICMACHINEBYAOHTAANDESASAKIABSTRACTANHYDRAULICFATIGUETESTINGMACHINECOMBININGAMECHANICALHYDRAULICPULSATORANDACLOSEDLOOPCONTROLSYSTEMHASBEENCONSTRUCTEDASATRIALTHEDYNAMICCAPACITIESFORLOADANDSTROKERANGESARE1MNSUPERPOSEDBYAMEANLOADRANGINGFROM0TO1MNAND5RAM,RESPECTIVELY,OVERAFREQUENCYRANGEFROM33TO10HZTHECONSUMPTIONOFELECTRICPOWERANDTOOTINGWATERFORTHISMACHINEISABOUTONETHIRDOFTHESERVOCONTROLLEDELECTROHYDRAULICMACHINETHESTABILITYOFTHISCONTROLSYSTEMIS05PERCENTOFTHERANGESOMEEXPERIMENTALRESULTSAREPRESENTEDTODEMONSTRATETHEEXCELLENTSTABILITYOFLOADDURINGFATIGUETESTINGINTRODUCTIONHYDRAULICANDRESONANTTYPEFATIGUETESTINGMACHINESAREUSEDFORHIGHLOADFATIGUETESTSL,2THERESONANTTYPEMACHINECANBERUNWITHASMALLAMOUNTOFELECTRICPOWERHOWEVERITCANNOTBERUNINAHIGHDAMPINGCONDITIONOFSPECIMENS,ORLONGSTROKEANDHIGHLOADFATIGUETESTTHEHYDRAULICTYPEMACHINESCANBERUNINTHESECONDITIONSTHUS,THEHYDRAULICFATIGUETESTINGMACHINESAREUSEDFORHIGHLOADANDLONGSTROKEFATIGUETESTSTHISTYPEOFMACHINEISUSUALLYDIVIDEDINTOTWOCATEGORIESONEISTHESERVOCONTROLLEDELECTROHYDRAULICMACHINE2ANDTHEOTHERISTHEMECHANICALHYDRAULICPULSATOR13THESERVOCONTROLLEDELECTROHYDRAULICFATIGUETESTINGMACHINE2HASACLOSEDLOOPCONT“0SYSTEM,ANDTHISCONTINUOUSLYCORRECTSTHEDIFFERER/CEOFTHELOADORELONGATIONSIGNALFROMTHECOMMANDSIGNALTHEREFORE,THESERVOCONTROLLEDELECTROHYDRAULICMACHINECANBEOPERATEDINANARBITRARYWAVEFORMOFTHELOADORELONGATIONUNDERLIMITEDFREQUENCYCONDITIONSTHATIS,ITCANPRODUCENOTONLYASINUSOIDALWAVEFORMBUTALSOARANDOMWAVEFORMINACCORDANCEWITHACOMMANDSIGNALGENERATORTHEMACHINEOFTHISTYPE,HOWEVER,NEEDSLARGEAMOUNTSOFELECTRICPOWERANDWATERFORCOOLINGOFOIL,SOITISEXPENSIVEBOTHINAOHTAANDESASAKIARERESEARCHERANDCHIEFOFFATIGUE2NDLABORATORY,RESPECTIVELY,SECONDFATIGELABORATORY,FATIGUETESTINGDIVISION,NATIONALRESEARCHINSTITUTEFORMETALS,2312,NAKAMEGURO,MEGUROKU,TOKYO153,JAPANORIGINALMANUSCRIPTSUBMITTEDAUGUST15,1974REVISEDVERSIONECALVEDUNE24,1976CONSTRUCTIONANDINOPERATIONINCASEALABORATORYDOESNOTHAVEASUFFICIENTLYLARGEELECTRICSUPPLYSYSTEM,THISKINDOFMACHINECANNOTBEEQUIPPEDONTHEOTHERHAND,THEMECHANICALHYDRAULICPULSATORMACHINE3NEEDSLESSELECTRICPOWERANDLESSWATERFORCOOLINGTHANTHESERVOCONTROLLEDELECTROHYDRAULICMACHINEDOESHOWEVER,THISMACHINEHASANOPENLOOPCONTROLSYSTEMTHATIS,ONCETHEAMPLITUDEVALUEOFLOADHASBEENSETATTHEBEGINNINGOFTHETEST,THISVALUEISNOTCONTROLLEDAUTOMATICALLYMOREOVER,THEMEANVALUEOFLOADISKEPTONLYWITHIN5PERCENTOFLOADRANGEBYANACTIONOFTWOOILPRESSURESWITCHESWHICHARECONNECTEDTHROUGHTHEMECHANICALPULSATORUNITBYMEANSOFAROTARYVALVECONNECTEDTOTHEWORKINGCYLINDERSTHISONOFFCONTROLSYSTEMCANNOTMAINTAINTHESETVALUEATTHEBEGINNINGOFTHETESTBECAUSEOFTHECHANGEINTHECOMPLIANCEOFTHESPECIMENANDTHECHANGEINTHETEMPERATUREOFTHEOILTHEREFORE,ANOPERATORHASTOCORRECTMANUALLYTHELOADTHATCHANGESEVERYMINUTEWITHTHEADVANCEOFFATIGUETESTINGFURTHER,THISMACHINECOULDONLYBEUSEDFORCONSTANTLOADFATIGUETESTSOFSINUSOIDALWAVETHUS,INORDERTOOBTAINALOWCONSUMPTIONOFELECTRICPOWERASWELLASGOODSTABILITYINCONTROL,ANHYDRAULICFATIGUETESTINGMACHINEEQUIPPEDWITHAMECHANICALHYDRAULICPULSATORANDACLOSEDLOOPCONTROLSYSTEMWASCONSTRUCTEDASATRIALTHISPAPERREPORTSTHEPRINCIPLEOFTHESYSTEMANDTHEEXCELLENTPERFORMANCEOFTHISMACHINECONTROLSYSTEMASMENTIONEDABOVE,THISMACHINEWASCONSTRUCTEDBASEDONTHELOADGENERATINGMECHANISMOFTHEMECHANICALHYDRAULICPULSATOR13THISMECHANISMGENERATESTHEALTERNATINGLOADANDTHEMEANLOADINDEPENDENTLYNAMELY,ITCONSISTSOFTWOPARTSAMECHANICALHYDRAULICPULSATORWHICHHASASMALLERCROSSSECTIONANDALONGERSTROKETHANTHEACTUATORANDGENERATESALTERNATINGOILPRESSUREBYTHERECIPROCATIONOFAPLUNGER,ANDASMALLOILPUMPTHATSUPPLIESAEXPERIMENTALMECHANICSI37INVOLUMEWITHTHEELONGATIONORTHESHRINKAGEOFASPECIMEN,BECOMESNEGLIGIBLYSMALLANDTHEPRESSUREISREGARDEDTOBECONSTANTFORASHORTPERIODOFTIMEFORTHECOMPENSATIONOFADECREASEINPRESSUREOFTHISCYLINDERWHICHFOLLOWSFROMALEAKAGEOFOILWITHALAPSEOFTIME,ASERVOVALVEISACTUATEDBYTHECOMMANDOFASIGNALFROMASERVOAMPLIFIER,WHICHISEQUIVALENTTOTHEDIFFERENCEOFTHEOUTPUTSIGNALOFAPRESSURETRANSDUCERINSERTEDINTHEUPPERCYLINDERFROMTHEVALUEPCSETATTHEBEGINNINGOFTESTINTHECONSTANTPRESSURESETTINGUNITTHEALTERNATINGCOMPONENTOFPRESSURE,PASINT,INTHELOWERCYLINDERISEXCITEDBYAMECHANICALHYDRAULICPULSATORTHISISCOMPOSEDOFAPULSATORCYLINDERONAROCKINGARMWHICHROCKSWITHAROTATIONOFACRANKSHAFTTHEPULSATORRAMBOBSUPANDDOWNWITHTHEMOVEMENTOFTHEROCKINGARM,MAKESTHEVOLUMEOFCYLINDERALTER,ANDEXCITESTHEALTERNATIONOFOILPRESSURETHEALTERNATINGOILPRESSUREEXCITEDINTHISMANNERREACHESTHELOWERCYLINDERTHROUGHTHEPIPELINEANDAPPLIESTHEALTERNATINGLOADTOTHESPECIMENTHEAMPLITUDEOFTHISALTERNATINGOILPRESSURE,PA,ISDETERMINEDBYTHEPOSITIONOFTHEPLUNGERONTHEROCKINGARMTHECLOSERTHEPOSITIONTAKESTOTHEFULCRUMOFTHEROCKINGARM,THESMALLERTHEAMPLITUDEBECOMESTHUS,WHENPAHASTOVARY,THEPULSATORCYLINDERISMOVEDONTHEROCKINGARMBYTHERUNOFASERVOMOTORTHEVALUEOFAMPLITUDEDETECTEDTHROUGHPEAKDETECTINGCIRCUITSISCOMPAREDWITHTHEVALUEWHICHHASBEENPREVIOUSLYSETINANAMPLITUDEVALUESETTINGUNITATTHEBEGINNINGOFTESTTHENTHELOADAMPLITUDEISKEPTCONSTANTBYTHEACTIONOFTHESERVOMOTORRUNBYTHEAMPLIFIEDSIGNALOFTHEDIFFERENCEINTHISCOMPARISONASFORTHEMEANLOADCONTROL,THEOUTPUTSIGNALOFTHEMEANVALUE,PRO,ISCOMPAREDWITHTHEVALUETHATHASBEENPREVIOUSLYSETINAMEANVALUESETTINGUNITTHESERVOVALVESUPPLIESTHEOILPRESSURE,PT,INTHELOWERCYLINDERWHICHCORRESPONDSTOTHEDIFFERENCESIGNALINTHISCOMPARISONONLYOFTHEMEANVALUEFLOWRATESOFTHESERVOVALVESTHATAREUSEDFORTHECONTROLOFMEANLOAD,PRO,ANDOFCONSTANTPRESSURE,PC,AREVERYSMALLASCOMPAREDWITHTHATOFTHESERVOVALVEWHICHISUSEDFORTHEUSUALSERVOCONTROLLEDELECTROHYDRAULICMACHINEANDCONTINUOUSLYCORRECTSTHEDIFFERENCEOFTHELOADORELONGATIONSIGNALFROMTHECOMMANDSIGNALOFASINUSOIDALWAVEFORMORARANDOMWAVEFORMASMENTIONEDABOVE,THISMACHINEHASTHREECONTROLLOOPSFORCONSTANTPRESSURE,AMPLITUDEVALUEANDMEANVALUEEACHCONTROLCIRCUITHASAPROPERINTEGRATINGCIRCUITTOAVOIDTHEINTERFERENCEBETWEENEACHOTHERSOFAR,THECONTROLSYSTEMWASEXPLAINEDASFORTHELOADCONTROLANELONGATIONCONTROLCANBECONDUCTEDBYINTERCHANGINGALOADCELLWITHANEXTENSOMETERWHENAPROGRAMTESTISREQUIRED,THEAMPLITUDEANDMEANVALUESETTINGUNITSCOULDBEREPLACEDBYSUITABLEPROGRAMMEDSIGNALGENERATORSPEAKDETECTINGCIRCUITTHEPEAKDETECTINGCIRCUITISSHOWNINFIG3ANINPUTSIGNALBRANCHESOFFINTWOONEISUSEDFORTHEDETECTIONOFTHEUPPERPEAK,ANDTHEOTHER,THELOWERPEAKTHEUPPERPEAKVALUEISDETECTEDASFOLLOWSDIODED1ALLOWSCURRENTTOFLOWONLYINONEDIRECTIONTOCHARGEAHOLDINGCAPACITORC1D2PROVIDESFEEDBACKFORA1AFTERAPEAKISDETECTEDANDC1HOLDSTHEUPPERPEAKVALUEOFTHESIGNAL4INTHISSITUATION,WHENTHEUPPERPEAKOFTHESIGNALBECOMESSMALL,THEDCVOLTAGEDOESNOTFOLLOWITSO,TORESETTHISVALUE,ANFETSWITCHSWLISCLOSEDBYASYNCHRONIZEDPULSEET1FROMTHEMECHANICALHYDRAULICPULSATORTHENEUPLVALUEISRESETTOYRNAXATEACHCYCLEBEFORECUP1ISRESET,THISVOLTAGEHASBEENTRANSMITTEDTOTHEHOLDINGCAPACITORC2BYASYNCHRONIZEDPULSEER2THUS,THEUPPERPEAKVALUERESPONSESWITHADEAYOFAQUARTERCYCLENOW,THELOWERPEAKVALUEISDETECTEDINTHESAMEMANNERASINTHEUPPERPEAKDETECTORBYREERL_,ER2ENI,OKIOKER2OKFJ_EPIOKELPLLELPJLOOKLOOK50K130K50KOK2EAMPEUPPEMEANEUPETP2FIG3PEAKDETECTINGCIRCUITEXPERIMENTALMECHANICSI39

簡(jiǎn)介：WHERERISTHEREFLECTANCEOFTHESAMPLE,?ISTHEDISTANCEONTHESURFACEBETWEENTWOPOINTS,?ISTHEANGULARFREQUENCY,KISTHEWAVENUMBER,FISTHEFOCALLENGTHOFTHEINCIDENTRADIATION,AND?ISTHERMSHEIGHTOFTHESURFACEA2DANALYSISOFTHEOPTICSHASBEENCARRIEDOUTBYOGILVY35WHITEHOUSECONCLUDED34FORUNDULATIONSWITHLENGTHSCALEGREATERTHANTHEWAVELENGTHOFTHEINCIDENTRADIATIONTHATTHESURFACEAPPEAREDGLOSSYIFTHEPROBABILITYDENSITYOFTHESLOPESONTHESURFACEWASSTRICTLYCONFINEDTOANARROWANGLEBIOCOMPATIBILITYFINALLY,BIOLOGICALINTERACTIONSWITHASURFACEHAVEALSOBEENFOUNDTODEPENDONITSTOPOGRAPHYAGOODREVIEWOFTHETOPOLOGICALCONTROLOFCELLADHESIONANDACTIVITYONASURFACEHASBEENMADEBYCURTISANDWILKINSON36,ANDAMOREGENERALREVIEWOFTHEROLEOFPOLYMERBIOMATERIALSMAYALSOBEFOUND37SUCHCONSIDERATIONSARERELEVANTFORANUMBEROFINVIVOANDINVITROAPPLICATIONS,SUCHASBIOLOGICALSENSORS,HIPREPLACEMENTS38,ANDMORECOMPLEXTISSUEIMPLANTSSUCHASREPLACEMENTBONE,WHERETHEGROWTHOFCELLSWITHINTHEARTIFICIALSTRUCTUREISTOBEENCOURAGEDFOREXAMPLE,THESIZEANDMORPHOLOGYOFCRYSTALSATTHESURFACEOFOCTACALCIUMPHOSPHATE–COATEDCOLLAGENHAVEBEENSHOWNTOAFFECTTHEINTERACTIONOFCELLSWITHTHESURFACE,ASILLUSTRATEDINFIG4THELARGERSCALETOPOGRAPHYWASFOUNDTOLEADTOLESSFAVORABLESPHEROIDALCELLSTHATFORMEDFEWERINTERCELLULARCONNECTIONS39INSOMECASES,THETOPOGRAPHYOFASURFACEMAYBECAREFULLYCONTROLLEDTOPROMOTECELLADHESION40,41CONCLUSIONTHETOPOGRAPHYOFASURFACEISADIRECTRESULTOFTHENATUREOFTHEMATERIALTHATDEFINESITTHEANALYSISOFTHETOPOGRAPHYOFASAMPLE,MADEPOSSIBLEONTHENANOSCALEBYTHEDEVELOPMENTOFAFMTECHNIQUES,NEEDSTOBECAREFULLYCONSIDEREDINORDERTORELATETHECOMPLEXITYOFA2DSURFACETOTHEMATERIAL’SPROPERTIESTHERESULTWILLBETHEBETTERCONTROLOFANUMBEROFPROPERTIES,SUCHASOPTICALFINISH,ANDOFTHEINTERACTIONOFASURFACEWITHASECONDARYMATERIAL,WHETHERTHATBEANADHESIVE,ASECONDARYCOMPONENTOFACOMPOSITE,ORABIOLOGICALSPECIESREFERENCESANDNOTES1JDAFFINITOETAL,THINSOLIDFILMS291,6319962JADEARO,KDWESTON,SKBURATTO,ULEMMER,CHEMPHYSLETT277,53219973YNABETANI,MYAMASAKI,AMIURA,NTAMAI,THINSOLIDFILMS393,32920014MSFERRAZZAETAL,PHYSREVLETT78,369319975ESCHA¨FFER,TTHURNALBRECHT,TPRUSSELL,USTEINER,EUROPHYSLETT53,21820016DGBUCKNALL,GADBRIGGS,MRSSYMPSERNANOPATTERNINGULTRALARGESCALEINTEGRATIONBIOTECHNOL705,1512002,LMERHARI,KEGONSALVES,EADOBISZ,MANGELOPULSS,DHERR,EDS7SWALHEIM,ESCHA¨FFER,JMLYNEK,USTEINER,SCIENCE283,52019998JHEIER,ESIVANIAH,EJKRAMER,MACROMOLECULES32,900719999TTHURNALBRECHT,JDEROUCHEY,TPRUSSELL,MACROMOLECULES33,3250200010AKARIMETAL,MACROMOLECULES31,857199811XPJIANG,HPZHENG,SGOURDIN,PTHAMMOND,LANGMUIR18,2607200212GGOLDBECKWOODETAL,MACROMOLECULES35,5283200213VNBLIZNYUK,KKIROV,HEASSENDER,GADBRIGGS,POLYMPREPRINTS41,1489200014FDINELLI,HEASSENDER,KKIROV,OVKOLOSOV,POLYMER41,4285200015CRAUWENDAAL,POLYMEREXTRUSIONHANSER,MUNICH,198516SJLIU,PLASTRUBBERCOMPOSITES30,170200117BMONASSEETAL,PLASTELASTOMERESMAG53,29200118YOYANAGI,INTPOLYMSCITECHNOL24,T38199719AGUINIER,XRAYDIFFRACTIONINCRYSTALS,IMPERFECTCRYSTALS,ANDAMORPHOUSBODIESWHFREEMAN,SANFRANCISCO,196320VNBLIZNYUK,VMBURLAKOV,HEASSENDER,GADBRIGGS,YTSUKAHARA,MACROMOLSYMP167,89200121WMTONG,RSWILLIAMS,ANNUREVPHYSCHEM45,401199422PMEAKIN,FRACTALS,SCALINGANDGROWTHFARFROMEQUILIBRIUMCAMBRIDGEUNIVPRESS,CAMBRIDGE,199823CMCHAN,TMKO,HHIRAOKA,SURFSCIREP24,3199624EMLISTON,LMARTINU,MRWERTHEIMER,JADHESIONSCITECHNOL7,1091199325QCSUN,DDZHANG,LCWADSWORTH,TAPPIJ81,177199826VBLIZNYUKETAL,MACROMOLECULES32,361199927NZETTSU,TUBUKATA,TSEKI,KICHIMURA,ADVMATER13,1693200128RSHUNTER,RWHAROLD,THEMEASUREMENTOFAPPEARANCEWILEY,NEWYORK,ED2,198729HDAVIES,PROCINSTELECTRENG101,209195430FMWILLMOUTH,INOPTICALPROPERTIESOFPOLYMERS,GHMEETEN,EDELSEVIER,AMSTERDAM,198631DPORTER,GROUPINTERACTIONMODELLINGOFPOLYMERPROPERTIESMARCELDEKKER,NEWYORK,199532PBECKMANN,ASPIZZICHINO,THESCATTERINGOFELECTROMAGNETICWAVESFROMROUGHSURFACESPERGAMON,NEWYORK,198733KPORFYRAKIS,NMARSTON,HEASSENDER,INPREPARATION34DJWHITEHOUSE,PROCINSTMECHENGBJENGMANUF207,31199335JAOGILVY,THEORYOFWAVESCATTERINGFROMRANDOMROUGHSURFACESADAMHILGER,BRISTOL,UK,199136ACURTIS,CWILKINSON,BIOMATERIALS18,1573199737LGGRIFFITH,ACTAMATER48,263200038TMMCGLOUGHLIN,AGKAVANAGH,PROCINSTMECHENGPARTH–JENGMED214,349200039ACLAWSONETAL,MRSSYMPSERBIOMEDMATERDRUGDELIVERY,IMPLANTSTISSUEENG550,2351999,TNEENAN,MMARCOLONGO,RFVALENTINI,EDS40CSRANUCCI,PVMOGHE,JBIOMEDMATERRES54,149200141PBANERJEE,DJIRVINE,AMMAYES,LGGRIFFITH,JBIOMEDMATERRES50,331200042THEAUTHORSACKNOWLEDGECONTRIBUTIONSTOTHISWORKFROMABRIGGS,DBUCKNALL,VBURLAKOV,JCZERNUSKA,ANDSWILKINSONFROMOXFORDUNIVERSITYNMARSTONANDIROBINSONFROMLUCITEINTERNATIONALANDYTSUKAHARAFROMTHETOPPANPRINTINGCOMPANYVIEWPOINT20THTO21STCENTURYTECHNOLOGICALCHALLENGESINSOFTCOATINGSROBERTRMATHESONJRCOATINGSAREAMONGTHEMOSTANCIENTTECHNOLOGIESOFHUMANKINDRELATIVELYSOFTCOATINGSCOMPRISINGORGANICMATERIALSSUCHASBLOOD,EGGS,ANDEXTRACTSFROMPLANTSWEREINUSEMORETHAN20,000YEARSAGO,ANDCOATINGACTIVITYHASBEENCONTINUOUSLYPRACTICEDSINCETHENWITHGRADUALLYIMPROVINGMATERIALSANDAPPLICATIONTECHNIQUESTHEFUNDAMENTALPURPOSESOFPROTECTINGAND/ORDECORATINGSUBSTRATESHAVEREMAINEDUBIQUITOUSACROSSALLTHECENTURIESANDCULTURESOFCIVILIZATIONTHISARTICLEATTEMPTSTOEXTRAPOLATETHELONGTALEOFCHANGEINSOFTCOATINGTECHNOLOGYFROMITSCURRENTSTATEBYIDENTIFYINGSOMEKEYPROBLEMSTHATATTRACTRESEARCHANDDEVELOPMENTEFFORTSASOUR21STCENTURYBEGINSHUMANSHAVEBEENDECORATINGANDPROTECTINGVARIOUSSURFACESFORMANYTHOUSANDSOFYEARSONEVERYUSEFULWAYOFACCOMPLISHINGEITHERORBOTHOFTHOSETASKSISTOAPPLYATHINLAYEROFSOMENEWMATERIALWITHAPPROPRIATECHARACTERISTICSOFAPPEARANCE,DURABILITY,ADHESION,ANDAPPLICATIONREQUIREMENTSDIRECTLYONTOTHESURFACEOFINTERESTTHATNEWMATERIALISACOATINGUNDERSTANDABLY,THEEARLYHISTORYOFCOATINGSISASTORYOFVERYSPECIALIZED,OFTENUNIQUEMATERIALCOMBINATIONS,ASTRIALANDERRORACHIEVEDGOALSWITHONLYTHEMATERIALSATHANDINNATURETHISHERITAGEOFCUSTOMIZATIONISSTILLDETECTABLEINTHEMODERNCOATINGSWORLD,WHICHDEMANDSATREMENDOUSAMOUNTFROMTHEMATERIALSOFTENSYNTHETICBUTSOMESTILLCONTAININGORMADEOFNATURALPRODUCTSTOBETHINLYAPPLIEDONASURFACETHEYNEEDTOBEEASILYANDUNIFORMLYAPPLIEDSETUPWITHINAREASONABLEAMOUNTOFTIMEANDPROCESSCONSTRAINTSHAVEAMINIMALENVIRONMENTALIMPACTINTHEIRSYNTHESIS,COMBINADUPONTPERFORMANCECOATINGS,950STEPHENSONHIGHWAY,TROY,MI48083,USAEMAILROBERTRMATHESONUSADUPONTCOM9AUGUST2002VOL297SCIENCEWWWSCIENCEMAGORG976MATERIALSSCIENCESOFTSURFACESONMARCH23,2010WWWSCIENCEMAGORGDOWNLOADEDFROMTOTAKEGREATCAREINSYNTHESIZINGTHEVARNISHINGREDIENTSSOTHATNOESPECIALLYTROUBLESOMEREACTIONSCANEVEROCCURSOMESIDEREACTIONSAREUNDERSTANDABLYMOREDELETERIOUSTHANOTHERS,ANDTHEGOALISTOLEAVENOOPPORTUNITYFORTHEMOSTTROUBLESOME,NOMATTERWHATCONDITIONSMIGHTAPPEARTHISLEADSTOTHEUSEOFCONTROLLEDPOLYMERIZATIONTECHNIQUESEXEMPLIFIEDBUTCERTAINLYNOTLIMITEDTOGROUPTRANSFERPOLYMERIZATION7FORACRYLICMATERIALS,RIGOROUSEXCLUSIONOFNONFUNCTIONALUNABLETOPARTICIPATEINCURINGMATRIXMATERIALS,ANDOPTIMIZINGMOLARMASSDISTRIBUTIONSTOAVOIDUNTIMELYIMMISCIBILITYDURINGCUREANDSIMILARSTRATEGIESTHESPECIFICFIELDOFAUTOMOTIVECOATINGHASBEENINTHEFOREFRONTOFTHISACTIVITYBECAUSEOFTHEEXTREMELYHIGHPERFORMANCESTANDARDSANDPOWERFULECONOMICINCENTIVESFOUNDINMASSPRODUCINGAUTOMOBILESSOMEOFTHENEWSYNTHETICANDANALYTICALTECHNIQUESBEINGINTRODUCEDFORCONTROLLINGANDMONITORINGAUTOMOTIVEENAMELSHAVEBEENDESCRIBED8DECORATIVECOATINGSINPARTICULARNEEDTOINCORPORATEPIGMENTS,DYES,REFLECTIVEMETAL,ANDMICAFLAKESFORMANYAPPLICATIONSONECOMMONTECHNIQUEFOREFFECTIVELYDISTRIBUTINGSUCHPARTICLESISTOCOVERTHEIRSURFACESWITHDISPERSANTSTHATAIDINTHEIRDISPERSIONINTHEBULKOFTHECOATINGANDPREVENTREAGGLOMERATIONUNDERTHEVARIETYOFCIRCUMSTANCESTHATMIGHTARISELATEREXQUISITECONTROLOFTHEMOLECULARSTRUCTUREISNEEDEDINORDERTOACHIEVEGOODDISTRIBUTIONOFTHEPARTICLES,MINIMALMOBILITYONCEAPPLIEDTOASURFACE,THEABILITYTORESISTFORCESTHATDRIVEREAGGLOMERATION,ANDCOMPATIBILITYWITHTHEBULKCOATINGANDYETNOTINDUCEPROBLEMSWITHADHESION,APPLICATION,ORLONGTERMPERFORMANCEBECAUSEPIGMENTSAREVERYFREQUENTLYTHEMOSTEXPENSIVEINGREDIENTSINADECORATIVECOATING,ITISIMPORTANTTOUSETHEMEFFICIENTLYADDITIONALLY,ASSOLVENTCONCENTRATIONANDVARIETYAREDECREASEDBECAUSEOFTHEENVIRONMENTALPRESSURESPREVIOUSLYCITED,OPPORTUNITIESFORMANAGINGDISPERSIONPROBLEMSBYMODIFYINGTHECOATINGMEDIUMTHECOATINGVEHICLEDECREASESMALLWONDERTHATTHECHEMISTRYUSEDTOMAKEMODERNDISPERSANTSPROVIDESANEXCEPTIONALLYCLEARPICTUREOFTHESTATEOFTHEARTINMOLECULARCONTROLINCOATINGSTECHNIQUESFORMAKINGBLOCKCOPOLYMERSEACHBLOCKDESIGNEDFORAFFINITYTOEITHERASURFACEORTHESOLVENTENVIRONMENTHAVEBEENDEVELOPEDANDCOMMERCIALIZEDANDARESTILLBEINGIMPROVEDTHEPATENTARTISEXTENSIVEANDGROWING,BUTTHATFROMCHOSOTTEFILBERT9ISAREPRESENTATIVEEXAMPLEFUNCTIONALCOATINGSAFOURTHMODERNFRONTIERINTHEWORLDOFSOFTCOATINGSCANBEDESCRIPTIVELYCALLED“POSTCUREREACTIVITY”FORVARNISHES,ORPERHAPS“INUSEREACTIVITY”FORLACQUERSSUCHREACTIONSHAVEBEENRECOGNIZEDFORALONGTIMEINEXAMPLESSUCHASTHELONGTERMOXIDATIONOFALKYDVARNISHESANDMANYLACQUERSBASEDONNATURALPRODUCTSHISTORICALLY,THESEHAVEBEENVIEWEDASTROUBLESOMEINSTABILITIESHOWEVER,ITHASBEENLEARNEDTHATSOMEINSTANCESOFPOSTCURECHEMISTRYHAVEADVANTAGES,WITHONEEXAMPLEBEINGTHESLOWCONDENSATIONANDINTERCHANGEOFSILOXANEBONDSINORGANOSILANEENAMELS10THESECANACTTORELAXSTRESSESTHATOTHERWISEGROWUNCOMPENSATEDINLIGHTANDOXIDATIONSTRESSEDEXTERIORCOATINGSHETEROGENEOUSCOATINGSTHATREACTTOCRACKSORFRACTURESBYRELEASINGPOSTCUREREPAIRINGREDIENTSHAVEBEENPOSTULATED11EVENMORESOPHISTICATEDUSESINCONTROLLEDRELEASEOROTHERTRANSPORTCONTROLPROBLEMSCANBESKETCHEDTODAYITSHOULDBENOTEDTHATAGREATMANYINSTANCESEXISTINWHICHCOATINGSAREUSEDTOMANIPULATEGENERALLYTORETARD,DELAY,ORPREVENTTHETRANSPORTANDEXCHANGEOFMATERIALSATMOSPHERICOXYGENCONTACTINGFOOD,CARBONDIOXIDEEXITINGCARBONATEDBEVERAGES,THERELEASEOFPHARMACEUTICALSINTOTHEBODY,ELECTRICALCHARGELEAKINGINTOADEVICECOMPONENT,HEATEXITINGANISOTHERMALENVIRONMENT,ORWATERANDIONICMATERIALSCONTACTINGCORROSIONSUSCEPTIBLEMETALSAREEXAMPLESWHERETHETRANSPORTCHARACTERISTICSOFCOATINGSAREIMPORTANTINDETERMININGPERFORMANCETHELONGTERMCAPABILITYOFACOATINGTOIMPROVEORATTHELEASTREACTTOCOMPENSATEFORADECLININGTRANSPORTCHARACTERISTICMAYBEJUSTASUSEFULASTHESAMEABILITYTOOFFSETDECLININGMECHANICALCHARACTERISTICSINDUSTRIALSCALECHALLENGESAFINALCLASSOFPROBLEMSDRIVINGINNOVATIONINMODERNCOATINGSCANBEFOUNDINTHECOSTSANDLIMITATIONSOFTHEHEATINGSTEPINENAMELPROCESSINGNOTSURPRISINGLY,THESEPROBLEMSINCLUDETHECAPITALANDENERGYCOSTSASSOCIATEDWITHHEAT

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ORPTIONRATETHEREAFTERHASBEENASSIGNEDTOLIGANDEXCHANGETHEPSEUDOSECONDORDERRATEMODELHASBEENWIDELYAPPLIEDTOADSORPTIONOFPOLLUTANTSFROMAQUEOUSSOLUTIONS24THEADVANTAGEOFUSINGTHISMODELISTHATTHEMODELCALCULATESTHERATECONSTANTANDTHEEQUILIBRIUMCAPACITYSOTHATTHEREISNONEEDFIG2ADSORPTIONOFNOMONTOTHEUNMODIFIEDANDHDTMAMODIFIEDIOCSATPH45±02ANDPH90±01INITIALCONCENTRATIONOF10MG/LNOM,01NNANO3IONICSTRENGTH,25GIOCS/LFIG3ADSORPTIONISOTHERMSOFNOMAATPH50±01,70±01AND100±01,WITHANIONICSTRENGTHOF001NANDBWITHANIONICSTRENGTHOF001AND01N,ATPH75±01ONTOTHEUNMODIFIEDANDHDTMAMODIFIEDIOCS,WITHANEQUILIBRATIONTIMEOF24HTOOBTAINTHELATTERFROMISOTHERMEXPERIMENTS25THEPSEUDOSECONDORDERRATEMODELISEXPRESSEDAS24DQTDTKQE?QT21ORTQT1KQ2E1QET2WHEREQEANDQTARETHEAMOUNTMG/GOFTHEADSORBATEADSORBEDATEQUILIBRIUMANDTIMET,RESPECTIVELY,ANDKISTHEADSORPTIONRATECONSTANTG/MG/MINFIG2SHOWSTHATTHEEXPERIMENTALDATAAGREEDWELLWITHSUCHMODELTABLES1PRESENTSTHEKINETICPARAMETERSOFNOMADSORPTIONDERIVEDFORBOTHTHEUNMODIFIEDANDMODIFIEDIOCSTHERATECONSTANTSOFNOMADSORPTIONONTHEMODIFIEDIOCSWEREHIGHERTHANTHOSEONTHEUNMODIFIEDIOCSATBOTHACIDICANDBASICPH,SUGGESTINGASTRONGERDRIVINGFORCEFORNOMADSORPTIONONTHEHDTMAMODIFIEDIOCS322ADSORPTIONISOTHERMSNOMADSORPTIONISOTHERMSWEREDEVELOPEDATPH50±01,70±01AND100±01THEPH10WASABOVETHEPZCOFTHEMODIFIEDIOCSTHEIONICSTRENGTHSTESTEDWERE001OR01NNANO3THEEXPERIMENTALDATAPLOTTEDWITHCURVESPREDICTEDFROMALANGMUIRMODELARESHOWNINFIG3AANDBTHELANGMUIRADSORPTIONMODELISEXPRESSEDASQEQMBCE1BCE3WHERECEISTHEEQUILIBRIUMCONCENTRATIONINMG/L,QEISTHEAMOUNTADSORBEDATEQUILIBRIUMINMG/G,QMISTHEMAXIMUMAMOUNTOFADSORBATETHATCANBEADSORBEDUPTOMONOLAYERCOVERAGE,ANDBISTHELANGMUIRCONSTANT,WHICHISRELATEDTOTHEBINDINGSTRENGTHASSHOWN,THEEXPERIMENTALDATAFITTEDWITHTHELANGMUIRMODELWELL,INDICATINGTHATTHETWOIOCSSURFACESWERERELATIVELYHOMOGENEOUS

簡(jiǎn)介：AROBUSTVISIONBASEDMOVINGTARGETDETECTIONANDTRACKINGSYSTEMALIREZABEHRAD,ALISHAHROKNI,SEYEDAHMADMOTAMEDIELECTRICALENGINEERINGDEPARTMENTAMIRKABIRUNIVERSITYOFTECHNOLOGY424HAFEZAVE15914TEHRAN,IRANEMAILB7723958AKUACIR,ASHAHROKNIYAHOOCOM,MOTAMEDIAKUACIRKUROSHMADANIINTELLIGENCEININSTRUMENTATIONANDSYSTEMSLABI2SSENARTINSTITUTEOFTECHNOLOGYUNIVERSITYPARISXIIAVENUEPIERREPOINT,F77127LIEUSAINT–FRANCEEMAILMADANIUNIVPARIS12FRABSTRACTINTHISPAPERWEPRESENTANEWALGORITHMFORREALTIMEDETECTIONANDTRACKINGOFMOVINGTARGETSINTERRESTRIALSCENESUSINGAMOBILECAMERAOURALGORITHMCONSISTSOFTWOMODESDETECTIONANDTRACKINGINTHEDETECTIONMODE,BACKGROUNDMOTIONISESTIMATEDANDCOMPENSATEDUSINGANAFFINETRANSFORMATIONTHERESULTANTMOTIONRECTIFIEDIMAGEISUSEDFORDETECTIONOFTHETARGETLOCATIONUSINGSPLITANDMERGEALGORITHMWEALSOCHECKEDOTHERFEATURESFORPRECISEDETECTIONOFTHETARGETLOCATIONWHENTHETARGETISIDENTIFIED,ALGORITHMSWITCHESTOTHETRACKINGMODEMODIFIEDMORAVECOPERATORISAPPLIEDTOTHETARGETTOIDENTIFYFEATUREPOINTSTHEFEATUREPOINTSAREMATCHEDWITHPOINTSINTHEREGIONOFINTERESTINTHECURRENTFRAMETHECORRESPONDINGPOINTSAREFURTHERREFINEDUSINGDISPARITYVECTORSTHETRACKINGSYSTEMISCAPABLEOFTARGETSHAPERECOVERYANDTHEREFOREITCANSUCCESSFULLYTRACKTARGETSWITHVARYINGDISTANCEFROMCAMERAORWHILETHECAMERAISZOOMINGLOCALANDREGIONALCOMPUTATIONSHAVEMADETHEALGORITHMSUITABLEFORREALTIMEAPPLICATIONSTHEREFINEDPOINTSDEFINETHENEWPOSITIONOFTHETARGETINTHECURRENTFRAMEEXPERIMENTALRESULTSHAVESHOWNTHATTHEALGORITHMISRELIABLEANDCANSUCCESSFULLYDETECTANDTRACKTARGETSINMOSTCASESKEYWORDSREALTIMEMOVINGTARGETTRACKINGANDDETECTION,FEATUREMATCHING,AFFINETRANSFORMATION,VEHICLETRACKING,MOBILECAMERAIMAGE1INTRODUCTIONVISUALDETECTIONANDTRACKINGISONEOFTHEMOSTCHALLENGINGISSUESINCOMPUTERVISIONAPPLICATIONOFTHEVISUALDETECTIONANDTRACKINGARENUMEROUSANDTHEYSPANAWIDERANGEOFAPPLICATIONSINCLUDINGSURVEILLANCESYSTEM,VEHICLETRACKINGANDAEROSPACEAPPLICATION,TONAMEAFEWDETECTIONANDTRACKINGOFABSTRACTTARGETSEGVEHICLESINGENERALISAVERYCOMPLEXPROBLEMANDDEMANDSSOPHISTICATEDSOLUTIONSUSINGCONVENTIONALPATTERNRECOGNITIONANDMO1SELECTNRANDOMFEATUREPOINTFROMPREVIOUSFRAME,ANDUSETHESTANDARDNORMALIZEDCROSSCORRELATIONMETHODTOLOCATETHECORRESPONDINGPOINTSINTHECURRENTFRAMENORMALIZEDCORRELATIONEQUATIONISGIVENBY2/122,221,1221,1,,,,??????????????∑∑∑∈∈∈FYXFFYXFFYXFFYXFRSYXSYXSYX2HERE21ANDFFARETHEAVERAGEINTENSITIESOFTHEPIXELSINTHETWOREGIONSBEINGCOMPARED,ANDTHESUMMATIONSARECARRIEDOUTOVERALLPIXELSWITHINSMALLWINDOWSCENTEREDONTHEFEATUREPOINTSTHEVALUERINTHEABOVEEQUATIONMEASURESTHESIMILARITYBETWEENTWOREGIONSANDISBETWEEN1AND1SINCEITISASSUMEDTHATMOVINGOBJECTSARELESSTHAN50OFTHEWHOLEIMAGE,THEREFOREMOSTOFTHENPOINTSWILLBELONGTOTHESTATIONARYBACKGROUND2SELECTMRANDOMSETSOFTHREEFEATUREPOINTSXI,YI,XI,YIFORI1,2,3,FROMTHENFEATUREPOINTSOBTAINEDINSTEP1XI,YIARECOORDINATESOFTHEFEATUREPOINTSINTHEPREVIOUSFRAME,ANDXI,YIARETHEIRCORRESPONDSINCURRENTFRAME3FOREACHSETCALCULATETHEAFFINETRANSFORMATIONPARAMETERS4TRANSFORMNFEATUREPOINTSINSTEP1USINGMAFFINETRANSFORMATIONS,OBTAINEDINSTEP3ANDCALCULATETHEMMEDIANSOFSQUAREDDIFFERENCESBETWEENCORRESPONDINGPOINTSANDTRANSFORMEDPOINTSTHENSELECTTHEAFFINEPARAMETERSFORWHICHTHEMEDIANOFSQUAREDDIFFERENCEISTHEMINIMUMACCORDINGTOTHEABOVEPROCEDURE,THEPROBABILITYPTHATATLEASTONEDATASETINTHEBACKGROUNDANDTHEIRCORRECTCORRESPONDINGPOINTSAREOBTAINEDISDERIVEDFROMTHEFOLLOWINGEQUATION7MQMQP111,,3ΕΕ???3WHEREΕ05ISTHERATIOOFTHEMOVINGOBJECTREGIONSTOWHOLEIMAGEANDQISTHEPROBABILITYTHATCORRESPONDINGPOINTSARECORRECTLYFINDIN7ITHASBEENSHOWNTHATTHEABOVEMETHODWILLGIVEANACCURATEANDRELIABLEMODEL22MOVINGTARGETDETECTIONUSINGBACKGROUNDMOTIONCOMPENSATEDFRAMESWHENAFFINEPARAMETERSAREESTIMATED,THEYCANBEUSEDFORCANCELLATIONOFTHEAPPARENTBACKGROUNDMOTION,BYTRANSFORMATIONOFPREVIOUSFRAMENOWDIFFERENCEOFTHECURRENTFRAMEANDTRANSFORMEDPREVIOUSFRAMEREVEALSTRUEMOVINGTARGETSTHENWEAPPLYATHRESHOLDTOPRODUCEABINARYIMAGETHERESULTSOFTHETRANSFORMATIONANDSEGMENTATIONARESHOWNISFIGURE1AAND1BSOMEPARTSARESEGMENTEDASMOVINGTARGETSDUETONOISECONNECTEDCOMPONENTPROPERTYCANBEAPPLIEDTOREDUCEERRORSDUETONOISEWEUSESPLITANDMERGEALGORITHMTOFINDTARGETBOUNDINGBOXESIFNOTARGETISFOUND,THENITMEANSEITHERTHEREISNOMOVINGTARGETINTHESCENEOR,THERELATIVEMOTIONOFTHETARGETISTOOSMALLTOBEDETECTEDINTHELATTERCASE,ITISPOSSIBLETODETECTTHETARGETBYADJUSTINGTHEFRAMERATEOFTHECAMERATHEALGORITHMACCOMPLISHESTHISAUTOMATICALLYBYANALYZINGTHEPROCEEDINGFRAMESUNTILATARGETISDETECTEDOURSPECIALINTERESTISDETECTIONANDTRACKINGOFTHEMOVINGVEHICLESSOWEUSEDASPECTRATIOANDHORIZONTALANDVERTICALLINEASCONSTRAINTSTOVERIFYVEHICLESOUREXPERIMENTSSHOWTHATCOMPARISONOFTHELENGTHOFHORIZONTALANDVERTICALLINESINTHETARGETAREAWITHTHEPERIMETEROFTHETARGETWILLGIVEAGOODCLUEABOUTTHENATUREOFTHETARGET3TARGETTRACKINGAFTERATARGETISVERIFIED,THEALGORITHMSWITCHESINTOTHETRACKINGMODEMODIFIEDMORAVECOPERATORISAPPLIEDTOTHETARGETTOIDENTIFYFEATUREPOINTSTHESEFEATUREPOINTSAREMATCHEDWITHPOINTSINTHEREGIONOFINTERESTINTHECURRENTFRAMEDISPARITYVECTORSARECOMPUTEDFORTHEMATCHEDPAIRSOFPOINTSWEUSEDDISPARITYVECTORSTOREFINETHEMATCHEDPOINTSTHEREFINEDPOINTSDEFINETHENEWPOSITIONOFTHETARGETIN

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IPMENTMANUFACTUREROEM,COLLECTIONWITHRETAILERSANDCOLLECTIONWITHTHIRDPARTYLOGISTICSPROVIDERSBARKERANDZABINSKY2008,2011INTHEIRCONCEPTUALFRAMEWORKFORDECISIONMAKINGIN

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