A Historical Geography of the British Colonies Vol V docx

... sighted by the first discoverer the Italian Cabot was spoken of under the Italian name of Prima Terra Vista. The name Baccalaos[24] tells of voyages of the Basques, as CapeBreton of visitors from ... writers. At the present day, on the maps of Newfoundland, an islet off the east coast, at the extreme north of the peninsula of Avalon, bears the name of Baccalieu. See Parkman, p.189 note as above, ... are geographically separate from each other. There is the eastern seaboard, the old Acadia; there is the basin of the St. Lawrence; there are the plains of the North-West and the regions of the Hudson...

... catalytic pockets in the asymmetric unit, and the glutamate-binding modes are identical to eachother (Fig. 2A) . The a- carboxyl and a- amino groups of the bound glutamate are at the bottom of the pocket, ... was amplified by PCR from the plasmid pCY167 (Suzuki H & Yamada C, Unpublished),using forward primer 5¢-CATATGGATGAGTACAAACAAGTAGATG-3¢ and reverse primer 5¢-GGATCCTCGAGCTCATTTACGTTTTAAATTAATGCCGAT-3¢ ... LaJolla, CA, USA) with forward primer 5¢-GAAACGATGCATTTGTCCTATGCCGACCGTGCGTC-3¢ and reverseprimer 5¢-GACGCACGGTCGGCATAGGACAAATGCATCGTTTC-3¢. The sequence of the second PCR product wasalso confirmed....

... is that the cyclical behavior of the ratings reflects the sensitivity of the various financial ratios on which they are based.16 Hickman voiced concern about the cyclical behavior of agency-ratings ... owners of financial assets, the institutions (both public and private) that guarantee the assets, and the asset managers that act as agents for the principals or owners. An asset manager, for example, ... publicly available sources of information pertinent to investment values are far greater than they were in the day when rating agencies first appeared, and since the markets themselves (partly because...

... contribution came to us by the aid of the Revival of Learning rather a process than an event, the dates of which are vague, but which may be said to have taken place in the sixteenth and seventeenth ... to adjectives, verbs, and other parts of language. The causes of this arenot far to seek. Spoken language can never be so accurate as written language; the mass of the English andDanes never ... rogue; varlet, vassal, wicket. The above words were brought over to Britain by the Normans;and they gradually took an acknowledged place among the words of our own language, and have held thatplace...

... than the nextAn Historical Account of the Rise and Progress of the Colonies of South Carolina and Georgia, vol 119An Historical Account of the Rise and Progress of the Colonies of South Carolina ... TeamAN HISTORICAL ACCOUNT OF THE RISE AND PROGRESS OF THE COLONIES OF SOUTHCAROLINA AND GEORGIA.In Two Volumes. VOL. I.By ALEXANDER HEWATTAn Historical Account of the Rise and Progress of ... colonists the methods either of improving the advantages, or guarding against the disadvantages of the climate, and therefore it is no wonder that they found themselves involved at this periodin a complication...

... and“where.” The Do-specialistreplaces the predicateDO(from the verb“do”)with a morespecificverbchosenfromthoseacquiredfor a domain.Although“do”doesnotappearas the mainverbveryoftenin the databasequerytask, the translatorsdeduceitsimpliedpresenceinsomequeries—forinstanceinsuchcomparativequestionsas“WhatcountriescovermoreareathanPeruLdoes~?”. The comparativespecialistexamines the twoarguments of a comparisontodeterminewhether the comparisontobemadeisbetweentwoattributevalues(e.g.,Jack’sheightandsevenfeet)orbetweenanentityandsomevalue(e.g.,Jackandsevenfeet).In the lattercase,TEAMtriestoidentify the appropriateattribute of the entity(e.g.,Jack’sheight).2.3.4DatabaseSchema The translationfromlogicalformtoSODAqueryrequiresknowing the exactstructure of the targetdatabaseand the mannerinwhich the predicatesappearingin the logicalformareassociatedwith the relationsin the database.Thisinformationisprovidedby the databaseschema,whichincludes the followinginformation8:•Definition of sortsinterms of databaserelations(subject)orfields(andfieldvalueforsortsderivedfromfeaturefields). 8The schematranslatoralsousescertaininformationin the conceptualschema,includingtaxonomicinformationin the sorthierarchyanddelineationinformationassociatedwithnonsortpredicates.—18—-‘IrisenuIIORLDCBCITYCONTieldP1~nuCITY—COUNTRYBCITY—NRMEBCITY—POPCONT—ARERONT-HEMICONT—NRPIECONT—POPPEAK-COUNTRYERK-HEIGHTPEAK—MAPlEPEAK -VOL WURLOC-RRERIORLDC-CRPITRLWORLOC—COtITIIIEIITUORLDC—TIRMEWORLDC—POPordPlenuRER(n)CAPITAL(n)CITY(n)ONTINENT(n)COUNTRY(o)HEIGHT(n)EPII(n)HEMISPHERE(n)HIGH(edj)ARGE(adj)LOW(edj)N(n)RME(n)MORTIIEN(edj)PERK(n)OP(n)POPULATION(n)POPULOUS(sdj)(n)SHORT(edj)SMALL(adj)uestjonRnswerjn9Area4e~dPERK-HEIGHT1~partoranACTUALrs)ation.Typs of 11.14-SYMOOUC A~ 1)~TICFEATUREeluntyp.DATES~Ait~SCOUNTSAuthaunitsImpfcit?YESNOMarImplicitunit—FOOTI000ursty~ of thisunit-TIMEWEIONTSPEEDVOLUMEI3 ~A~ AMAWORTHTCt,WERATUREOTHERAbbr.vI.donforthisunit?—FTConv.r,lonformulafromMETERStoFEET-(IK0.3048)Conv.rilonfonoulafromFEETtoMETERS-K0.3040)‘ositly.edjactivu—HIGHTAb.Nagetivaodiscdvsa-SHORTLOWFigure4: The AcquisitionMenu•List of convenientidentifyingfieldsforeachsortcorrespondingto a filesubjectorfield.•Definition of predicatesinterms of actualdatabaserelationsandattributes;thisisdoneforpredicatesderivedfrombothactualandvirtualrelations(forrelationsubjectsandattributes).•List of eachrelation’skeyfields. The databaseschemarelatesall the predicatesin the conceptualschematotheirrepresentationin a particulardatabase.Foreachpredicate, the databaseschemagenerates a logicformuladefining the predicateinterms of databaserelations.Forexample, the predicateWORLDC-CAPITAL -OF hasasitsassociateddatabaseschema a formularepresenting the factthatitsfirstargumentistakenfrom the WORLDC-CAPITALfield of a tuple of the WORLDCrelation,andthatitssecondargumentcomesfrom the WORLDC-NAMEfield of the samerelation.If a predicatehasmultipledelineations—i.e.,ifitappliestodifferentsorts of arguments(e.g., a HEMISPHERE -OF predicatecouldapplytobothCOUNTRIESandCONTINENTS) the schemawillinclude a separatedefinitionforeachset of arguments.Insomecases(e.g.,predicatesresultingfrom the acquisition of someverbsandadjectives), the mappingassociatedwith a predicateindicatesthatitisequivalenttoanotherconceptualschema]predicatewithcertainargumentssettofixedvalues.2.4Acquisition The acquisitioncomponent of TEAMiscrucialtoitssuccessas a transportablesystem.RecallthatoneconstraintonTEAMisthat the DBEnotberequiredtohaveanyknowledge of TEAM’sinternalworkings,norabout the intricacies of the grammar,nor of computationallinguisticsingeneral.Yetdetailedinformation,oftennecessarilylinguisticinitsorientation,mustsomehowbeextractedfrom-~desirablethat the acquisitioncomponentbedesignedtoallow a DBEtochangeanswerstoquestionsand ... onSwissmountainpeaks. The kinds of queries a usermightpose—forexample“Whatis the highestSwisspeak?”“ArethereanypeaksinSwitzerlandhigherthanMt.Whitney?”“Whereis the Jungfrau?”—areequallyappropriateforall the aforementionedencodingsand the inputsto the NLI(anEnglishquery)remainunchanged. The output(commandsto a databasesystem),however,willbequitedifferent.One of the mainfunctions of the NLIistomake the necessarytransformations,thusinsulating the userfrom the particularities of the databasestructure.Toprovidethisinsulationandtobridge the gapbetween the user’sviewand the system’sstructuresrequires a combination of domain-specificandgeneralinformation.Inparticular, the systemmusthave a model of the subjectmatter of the applicationdomain.Includedinthismodelwillbeinformationabout the objectsin the domain,theirpropertiesandrelationships,and the wordsandphrasesusedtorefertoeach.Finally, the systemmustknow the connectionbetweenentitiesinthatmodeland the informationin the database. A majorchallengeinconstructingtransportablesystemsistoprovide a meansforeasyacquisition of domain-specificinformation.TEAMisone of severalrecentattemptstobuildtransportablesystems(some of whicharedescribedelsewhereinthisissue.)Differentapproachestotransportablesystemsreflectdiverseconceptions of the kinds of skillsandknowledgethatmightberequired of thosewhowillbedoing the adaptations(inparticular,whethertheymusthaveexpertiseinnatural-languageprocessing),andwhatparts of the systemmightchange(inparticular,whether the databasecanberestructuredtofit the requirements of the NLI). A majorhypothesisunderlyingTEAMmaybestatedasfollows:ifanNLIisconstructedin a sufficientlywell-principledmanner, the informationneededtoadaptitto a newdatabase(anditscorrespondingdomain)canbeacquiredfromuserswhohavegeneralexpertiseaboutcomputersystemsand the givendatabase,butwhodonothaveanyspecialknowledgeaboutnatural-languageprocessingorthisNLI.Intestingthishypothesis,wealsoassumed(forboththeoreticalandpracticalreasons)that the databasecouldnotberestructured.Theoretically,itis the mostconservativechoicewecouldhavemade;itimposedgeneralsolutionsuponcertainissues of systemdesign,becausewecouldnotrestructure the datatoalleviateproblems of natural-languageprocessing.Suchrestructuringcanoftenbringabout a closermatchbetween the wayinformationisstoredand the wayitisreferredtoinNLexpressions.Forinstance,in the previousexample, a databasestructurethatincludes the SWISS?featurefieldismoredifficulttohandlein a generalmannerthanonethatuses the COUNTRYfieldencoding.From a practicalstandpoint, the choicereflectedourdesiretoprovidetechniquesadequatetohandleexistingdatabases,some of whicharequitelargeandcomplex,hencefairlydifficulttorestructure.1.2UsingTEAM The TEAMsystemisdesignedtoiñteract‘withtwokinds of users: a databaseèzpert(DBE)andanenduser. The DBEengagesinanacquisitiondialoguewithTEAMtoprovide the informationneededtoadapt the systemto a newdatabase,and,whendesired,toexpanditscapabilitiesinansweringquestionsabout a database(e.g.,byaddingnewverbsorsynonymsforexistingwords).Once a DBEhasprovidedTEAMwith the informationitneedsabout a databaseanddomain,any—11—IIORLOCPERKNA~~CNT~NTCAPITAl.AJ ~A POPAfghani,tanAsIaKabul260,00017,450,000AlbaniaEuropeTlrana11,1002,620,000AlgeriaAfricaAlgIers919,95116,510,000CONTNA~HEMAJWAPOPt&AlkWdAfricaS11,600,00041,200,000Antarctica--S5,000,000500AsiaN16,990,0002,366,000,000NA~COUNTRYHEN~HT VOL AconcaguaArgentina23,080NAnnapurnaNepal26,504NChimborazoEcuador20,702 V NA~cOtIdIRYPOPBrusselsBelgIum1,050,787BuenosAiresArgentina6,925,000CanberraAustralIa210,600Figure1:SampleDatabasenumber of enduserscanuse the systemtoquery the database. The TEAMsystemthushastwomajormodes:acquisitionandquestion-answering. The acquisitiondialoguewith the DBEisorientedaround the databasestructure.itis a menu-driveninteractionthroughwhich the DBEprovidesinformationabout the filesandfieldsin the database,3 the conceptualcontenttheyencodeandhowtheyencodeit,and the wordsandphrasesusedtorefertotheseconcepts.Hence the DBEmustknowabout the particulardatabasestructureand the subjectdomainitsinformationcovers,buthe ... doesnotneedtoknowhowTEAMworksoranyspeciallanguage-processingterminology. The question-answeringsystemconsists of twomajorcomponents:(1) the DIALOGICsystemGrosS2]formappingnatural-languageexpressionsontoformallogicalrepresentations of theirmeanings;(2) a schematranslatorthattransformstheserepresentationsintostatements of a databasequerylanguage.DIALOGICand the schematranslatorrequirebothdomain-specificanddomain-independentinformation. The requisitedomain-independentinformationispart of the coreTEAMsystem; the domain-specificinformationisobtainedby the acquisitioncomponent.1.3 A SampleDatabaseWewilluse the databaseshownschematicallyinFigureitohelpillustratevariousaspects of TEAM.Thisdatabasecomprisesfourfiles(or,relations) of geographicdata. The firstfile,WORLDC,hasfivefields—NAME,CONTINENT,CAPITAL,AREAandPOP;respectively,theyspecify the continent,capital,area,andpopulationforeachcountryin the world.Variousmountainsin the worldarerepresentedin the secondfile,namedPEAK,alongwiththeircountry,height,andanindicationastowhethertheyarevolcanic. The thirdfile,namedCONT,shows the hemisphere,area,andpopulation of the continents. The fourthfile,BCITY,contains the countryandpopulation of some of the largercities of the world.Becauseseveralfilesmayhavefieldswith the samenames,TEAMprefixesfilenamestofieldnamestoformuniqueidentifiers(e.g.,WORLDC-NAME,PEAK-NAME,CONT-POP,BCITY-POP);wewilldolikewiseinourdiscussion.TEAMdistinguishesamongthreedifferentkinds of fields:feature,arithmetic,andsymbolic.Featurefieldscontaintrue/falsevaluesindicatingwhetherornotsomeattributeis a property of the filesubject.PEAK -VOL andCONT-HEMIarefeaturefields.Arithmeticfieldscontainnumericvaluesonwhichcomputations(e.g.,averaging)canbeperformedWORLDC-AREAandPEAK-HEIGHTareexamples of arithmeticfields.Letusnote,however,that a fieldcontainingsocialsecuritynumbers8TEAMcurrentlyassumes a relationaldatabasewith a numl~er of files.Nodifficultlanguage-processingproblemswouldresultfromconversiontoothermodels.BCITY—12—wouldbetreatedmorenaturallyas a symbolicfieldthanasanarithmeticfield,becauseitisunlikelythatanyarithmeticcomputationswouldbedoneonsuchnumbers.Symbolicfieldstypicallycontainvaluesthatcorrespondtonounsoradjectivesdenoting the subtypes of the domaindenotedby the field.WORLDC-NAMEandPEAK-COUNTRYareexamples.Moreinformationcanbegleanedfrom a databasethansimplywhat the individualfilescontain.Forinstance, the continentonwhich a peakislocatedcanbederivedfrom the countryinwhichitislocatedandthe...

... the definitions of the complexobjecttypes.Wewillpresent,inparticular, the techniquesusedin the ESPRITprojectMULTOS.Inthisproject, a dataserverhasbeenimplementedinwhichdataobjectsareconstitutedbymultimediadocumentswithcomplexinternalstructures.1.IntroductionManyapplications,suchasofficeinformationsystems(OIS),particularlyfilingandretrieval of multimediadocumentsIEEE84],computer-aideddesignandmanufacturing(CAD/CAM),andartificialintelligence(Al)ingeneralandknowledge-basedexpertsystemsinparticular,needtodealwith a largenumber of dataobjectshavingcomplexstructures.Insuchapplicationareas, the datamanagementsystemhastocopewith the largevolumes of dataandtomanage the complexity of the structures of thesedataobjectsBANE87J.Animportantcharacteristic of many of thesenewapplicationsisthatthereis a muchlowerratio of instancespertypethanintraditionaldatabaseapplications.Consequently, a largenumber of objectsimplies a largenumber of objecttypes. The resultisoften a verylargeschema,onwhichitbecomesdifficultfor the userstospecifyqueries. The datamanagementsystemmustbeabletoprocessqueriescontainingbothconditionson the schema(i.e.partialconditionsontypestructures of the complexdataobjectstobeselected)andon the dataobjects(i.e.conditionson the values of the basiccomponentscontainedin the complexdataobjects).Inthispaperwewillfocuson a particularphaseinqueryprocessingon a database of complexobjects.Inthisphase the queryisanalyzed,completed,andtransformedbasedon the informationcontainedin the definitions of the complexobjecttypes.WecallthisphaseType-LevelQueryProcessing.Withthisphase, the systemrealizes a two-foldfunctionality:• The systemdoesnotforce the usertospecifyexactly the structures(i.e. the types) of the complexdataobjectstoselect.On the contrary,itallows the usertospecifyonlypartialstructures of thesecomplexobjects,somakingqueriesoncontentismuchmoreflexible.Infact, the usercanspecify the type of only a fewcomponents of the complexobjects(andgivingconditionson the values),withoutspecifying the completetype of the complexobjects.• The systemexploits the complexstructures of the dataobjects,describedaccordingto a high-levelmodel,forquerytransformationswhichsimplify the rest of the queryprocessing.DuringType-Levelprocessing,sometransformationsallowpruning of the query,sothat the resultingquerycontainsfewerpredicatestoevaluate.Inotherwords,for a givenquery, the Type-Levelprocessorcheckswhetherthereareconjunctsordisjunctsin the querythatarealwaystrueforinstances of the objecttypesreferencedin the query.Incertaincases,duringthisphase,itmayalsobededucedthat the queryisemptywithouthavingtoaccess the data.In ... )clusteredonTID.Clusteringisbasedon a hashedortreestructuredorganization. A selectionindexonattribute A of relationRis a baserelationF (A, TID)clusteredon A. LetR1andR2betworelations,notnecessarilydistinct,andletTID1andTID2beidentifiers of tuples of R1and A2 ,respectively. A joinindexonrelationsR1and A2 is a relation of couples(TID1,TID2),whereeachcoupleindicatestwotuplesmatching a joinpredicate.Intuitively, a joinindexisanabstraction of the join of tworelations. A joinindexcanbeimplementedbytwobaserelationsF(TID1,TID2),oneclusteredonTID1and the otheronTID2.Joinindicesareuniquelydesignedtooptimizejoins. The joinpredicateassociatedwith a joinindexmaybequitegeneralandincludeseveralattributes of bothrelations.Furthermore,morethanonejoinindexcanbedefinedbetweenanytworelations. The identification of variousjoinindicesbetweentworelationsisbasedon the associatedjoinpredicate.Thus, the join of relations A1 andR2on the predicate(R1 .A =R2 .A andR1.B=R2.B)canbecapturedaseither a singlejoinindex,on the multi—attributejoinpredicate,ortwojoinindices,oneon(R1 .A =R2 .A) and the otheron(R1.BR2.B). The choicebetween the alternativesis a databasedesigndecisionbasedonjoinfrequencies,updateoverhead,etc.Letusconsider the followingrelationaldatabaseschema(keyattributesarebold):11CUSTOMER(cname,city,age,job)ORDER(cname,pname,qty,date)PART(pname,weight,price,spname) A (partial)physicalschemaforthisdatabase,basedon the storagemodeldescribedabove,is(clusteredattributesarebold)C_PC(CID,cname,city,age,job)City_IND(city,CID)Age_IND(age,CID)0_PC(OlD,cname,pname,qty,date)CnamelND(cname,OlD)CIDJI(CID,OlD)OID_Jl(OlD,CID)C_PCand0_PCareprimarycopies of CUSTOMERandORDERrelations.City_INDandAge_INDareselectionindicesonCUSTOMER.CnamelNDis a selectionindexonORDER.CIDJIandOlDJIarejoinindicesbetweenCUSTOMERandORDERfor the joinpredicate(CUSTOMER.Cname=ORDER.Cname).3.Optimization of Non—RecursiveQueries- The objective of queryoptimizationistoselectanaccessplanforaninputquerythatoptimizes a givencostfunction.Thiscostfunctiontypicallyreferstomachineresourcessuchasdiskaccesses,CPUtime,andpossiblycommunicationtime(for a distributeddatabasesystem). The queryoptimizerisincharge of decisionsregarding the ordering of databaseoperations,and the choice of the accesspathsto the data, the algorithmsforperformingdatabaseoperations,and the intermediaterelationstobematerialized.Thesedecisionsareundertakenbasedon the physicaldatabaseschemaandrelatedstatistics. A set of decisionsthatleadtoanexecutionplancanbecapturedby a processingtreeKrishnamurthy86]. A processingtree(PT)is a treeinwhich a leafis a baserelationand a non—leafnodeisanintermediaterelationmaterializedbyapplyinganinternaldatabaseoperation.Internaldatabaseoperationsimplementefficientlyrelationalalgebraoperationsusingspecificaccesspathsandalgorithms.Examples of internaldatabaseoperationsareexact—matchselect,sort—mergejoin,n—arypipelinedjoin,semi—join,etc. The application of algebraictransformationrulesJarke84]permitsgeneration of manycandidatePT’sfor a singlequery. The optimizationproblemcanbeformulatedasfinding the PT of minimalcostamongallequivalentPT’s.TraditionalqueryoptimizationalgorithmsSelinger79]performanexhaustivesearch of the solutionspace,definedas the set of allequivalentPT’s,for a givenquery. The estimation of the cost of a PTisobtainedbycomputing the sum of the costs of the individualinternaldatabaseoperationsin the PT. The cost of aninternaloperationisitself a monotonicfunction of the operandcardinalities.If the operandrelationsareintermediaterelationsthentheircardinalitiesmustalsobeestimated.Therefore,foreachoperationin the PT,twonumbersmustbepredicted:(1) the individualcost of the operationand(2) the cardinality of itsresultbasedon the selectivity of the conditionsSelinger79,Piatetsky84]. The possiblePT’sforexecutinganSPJqueryareessentiallygeneratedbypermutation of the joinordering.Withnrelations,therearen!possiblepermutations. The complexity of exhaustivesearchisthereforeprohibitivewhennislarge(e.g.,n>10). The use of dynamicprogrammingandheuristics,asinSelinger79],reducesthiscomplexityto2~,whichisstillsignificant.Tohandle the case of complexqueriesinvolving a largenumber of relations, the optimizationalgorithmmustbemoreefficient. The complexity of the optimizationalgorithmcanbefurtherreducedbyimposingrestrictionson the class of 12PT’sIbaraki84),limiting the generality of the costfunctionKrishnamurthy86),orusing a probabilistichill—climbingalgorithmloannidis87].Assumingthat the solutionspaceissearchedbyanefficientalgorithm,wenowillustrate the possiblePT’sthatcanbeproducedbasedon the storagemodelwithjoinindices. The addition of joinindicesin the storagemodelenlarges the solutionspaceforoptimization.Joinindicesshouldbeconsideredby the queryoptimizerasanyotherjoinmethod,andusedonlywhentheyleadto the optimalPT.InValduriez87],wegive a precisespecification of the joinalgorithmusingjoinindex,denotedbyJOINJI,anditscost.ThisalgorithmtakesasinputtwobaserelationsR1(TID1, A1 ,B1, ... the designertochoosefrom a variety of accessmethodsandimplementations of accessmethods,dataplacementstrategiesandimplementations of dataplacementstrategiestobedefinedfor a file.Thisset of accessmethodsandplacementstrategiesisextensible.Wearecurrentlytesting the system. The filingsystemwillbeusedforlow-levelsupport of the archivalcomponent of the server. The queryprocessingstrategiesthatwillperformbestin the performancestudiesoutlinedinthispaperwillbeincorporatedin the system.ReferencesChristodoulakis84]5.Christodoulakis:“Implications of AssumptionsinDatabasePerformanceEvaluation”,ACMTODS,June1984.Christodoulakis87aJS.Christodoulakis:“Analysis of RetrievalPerformanceforRecordsandObjectsUsingOpticalDiskTechnology”,ACMTODS,June1987.Christodoulakis87b]S.Christodoulakis:“AnalysisandFundamentalPerformanceTradeoffsforCLVOpticalDisks”,TechnicalReport,Department of ComputerScience,University of Waterloo,1987.ChristodoulakisandVelissaropoulos87]S.ChristodoulakisandT.Velissaropoulos:“Issuesin the Design of a DistributedTestbedforMINOS”,TransactionsonManagementInformationSystems”,1987.ChristodoulakisandNg87]5.ChristodoulakisandR.Ng:“QueryProcessingin a MultimediaRetrievalEnvironment”,inpreparation,1987.Christodoulakisetal.87]S.Christodoulakis,E.Ledoux,R.Ng:“AnOpticalDiskBasedObjectFilingSystem”,TechnicalReport,Department of ComputerScience,University of Waterloo,1987.ChristodoulakisandFaloutsos84]S.ChristodoulakisandC.Faloutsos:“PerformanceAnalysis of a MessageFileServer”,IEEETransactionsonSoftwareEngineering,March1984.FaloutsosandChristodoulakis87]C.FaloutsosandS.Christodoulakis:“Analysis of RetrievalPerformance of SignatureAccessMethods”,ACMTOOlS,1987.Haskin8l]L .A. Haskin:“SpecialPurposeProcessorsforTextRetrieval”,DatabaseEngineering4,1,Sept1981,16-29.21QueryProcessingBasedonComplexObjectTypesElisaBertino,FaustoRabittiIstitutodiElaborazionedellaInformazioneConsiglioNazionaledelleRicercheViaS.Maria46,Pisa(Italy)ABSTRACTInapplscatwnareaswhere the datamanagementsystemhastodealwith a largenumber of complexdataobjectswith a widevariety of types, the systemmustbeabletoprocessqueriescontainingbothconditionson the schema of the dataobjectsandon the values of the dataobjects.Inthispaperwewillfocuson a particularphaseinqueryprocessingon a database of complexobjectscalledType-LevelQueryProcessing.Inthisphase, the queryisanalyzed,completed,andtransformedon the basis of the...

... strategy or competitive strategy refers to the plan of actions thatmanagement adopt to use a company’s resource and its distintive ability to gain a competitiveadvantage over its rivals in a ... Analysis Alternative strategies Strategy evaluation Recommended strategy RecommendationDEVELOPING A COMPETITIVE STRATEGY: A CASE STUDY OF THE THANGLONG GARMENT COMPANY IN HANOI, VIETNAMbyDang Anh ... important of industrystructure as determinant of company profit rates. They argue that innovation and companydifferences play a vital role in competitive position of a company and then its profit rate....