A study to determine the opinion of expert practitioners of the most important risks in the developmWord文件下载.docx

A study to determine the opinion of expert practitioners of the most important risks in the developmWord文件下载.docx

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

ADF95isatooltoautomaticallycalculatenumericalfirstderivativesforanymathematicalexpressionasafunctionofuserdefinedindependentvariables.Accuracyofderivativesisachievedwithinmachineprecision.ADF95maybeappliedtoanyFORTRAN77/90/95conformingcodeandrequiresminimalchangesbytheuser.ItprovidesanewderiveddatatypethatholdsthevalueandderivativesandappliesforwarddifferencingbyoverloadingallFORTRANoperatorsandintrinsicfunctions.Anefficientindexingtechniqueleadstoareducedmemoryusageandasubstantiallyincreasedperformancegainoverotheravailabletoolswithoperatoroverloading.Thisgainisespeciallypronouncedforsparsesystemswithlargenumberofindependentvariables.Awideclassofnumericalsimulations,e.g.,thoseemployingimplicitsolvers,canprofitfromADF95.

Programsummary

Titleofprogram:

ADF95

Catalogueidentifier:

ADVI

ProgramsummaryURL:

http:

//cpc.cs.qub.ac.uk/summaries/ADVI

Programobtainablefrom:

CPCProgramLibrary,Queen'

sUniversityofBelfast,N.Ireland

Computerforwhichtheprogramisdesigned:

allplatformswithaFORTRAN95compiler

Programminglanguageused:

FORTRAN95

No.oflinesindistributedprogram,includingtestdata,etc.:

3103

No.ofbytesindistributedprogram,includingtestdata,etc.:

9862

Distributionformat:

tar.gz

Natureofproblem:

Inmanyareasinthecomputationalsciencesfirstorderpartialderivativesforlargeandcomplexsetsofequationsareneededwithmachineprecisionaccuracy.Forexample,anyimplicitorsemi-implicitsolverrequiresthecomputationoftheJacobianmatrix,whichcontainsthefirstderivativeswithrespecttotheindependentvariables.ADF95isasoftwaremoduletofacilitatetheautomaticcomputationofthefirstpartialderivativesofanyarbitrarilycomplexmathematicalFORTRANexpression.Theprogramexploitsthesparsityinheritedbymanysetofequationstherebyenablingfastercomputationscomparedtoalternatedifferentiationtools

Solutionmethod:

AclassisconstructedwhichappliesthechainruleofdifferentiationtoanyFORTRANexpression,tocomputethefirstderivativesbyforwarddifferencing.Anefficientindexingtechniqueleadstoareducedmemoryusageandasubstantiallyincreasedperformancegainwhensparsitycanbeexploited.Fromauserspointofview,onlyminimalchangestohis/heroriginalcodeareneededinordertocomputethefirstderivativesofanyexpressioninthecode

Restrictions:

Processorandmemoryhardwaremayrestrictboththepossiblenumberofindependentvariablesandthecomputationtime

Unusualfeatures:

ADF95canoperateonusercodethatmakesuseofthearrayfeaturesintroducedinFORTRAN90.AconvenientextractionsubroutinefortheJacobianmatrixisalsoprovided

Runningtime:

Inmanyrealisticcases,theevaluationofthefirstorderderivativesofamathematicalexpressionisonlysixtimesslowercomparedtotheevaluationofanalyticallyderivedandhard-codedexpressions.Theactualfactordependsontheunderlyingsetofequationsforwhichderivativesaretobecalculated,thenumberofindependentvariables,thesparsityandontheFORTRAN95compiler

ArticleOutline

1.Introduction

2.FORTRAN90/95concepts

3.Usage

3.1.Afirstexample

3.2.Asecondexample

3.3.Fulldescription

3.4.Specialcases

3.5.Outputverification

4.Implementation

4.1.Userfunctions

4.2.SupportedFORTRAN90/95intrinsics

4.3.Implementationdetailsoftanh

4.4.Limitations

4.5.Undefinedderivatives

5.Tests

5.1.Verifyingthesolution

5.2.Performanceandcompilercomparison

6.Discussion

Acknowledgements

References

TheACGTMasterOntologyanditsapplications–Towardsanontology-drivencancerresearchandmanagementsystem 

JournalofBiomedicalInformatics,InPress,CorrectedProof,Availableonline1May2010

MathiasBrochhausen,AndrewD.Spear,CristianCocos,GabrieleWeiler,LuisMartí

n,AlbertoAnguita,HolgerStenzhorn,EvangeliaDaskalaki,FatimaSchera,UlfSchwarz,SteliosSfakianakis,StephanKiefer,MartinDö

rr,NorbertGraf,ManolisTsiknakis

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Objective:

Thispaperintroducestheobjectives,methodsandresultsofontologydevelopmentintheEUco-fundedprojectAdvancingClinico-genomicTrialsonCancer–OpenGridServicesforImprovingMedicalKnowledgeDiscovery（ACGT）.Whiletheavailabledatainthelifescienceshasrecentlygrownbothinamountandquality,thefullexploitationofitisbeinghinderedbytheuseofdifferentunderlyingtechnologies,codingsystems,categoryschemesandreportingmethodsonthepartofdifferentresearchgroups.ThegoaloftheACGTprojectistocontributetotheresolutionoftheseproblemsbydevelopinganontology-driven,semanticgridservicesinfrastructurethatwillenableefficientexecutionofdiscovery-drivenscientificworkflowsinthecontextofmulti-centric,post-genomicclinicaltrials.ThefocusofthepresentpaperistheACGTMasterOntology（MO）.Methods:

ACGTprojectresearchersundertookasystematicreviewofexistingdomainandupper-levelontologies,aswellasofexistingontologydesignsoftware,implementationmethods,andend-userinterfaces.Thisincludedthecarefulstudyofbestpractices,designprinciplesandevaluationmethodsforontologydesign,maintenance,implementation,andversioning,aswellasforuseonthepartofdomainexpertsandclinicians.Results:

Todate,theresultsoftheACGTprojectinclude（i）thedevelopmentofamasterontology（theACGT-MO）basedonclearlydefinedprinciplesofontologydevelopmentandevaluation;

（ii）thedevelopmentofatechnicalinfrastructure（theACGTPlatform）thatimplementstheACGT-MOutilizingindependenttools,componentsandresourcesthathavebeendevelopedbasedonopenarchitecturalstandards,andwhichincludesanapplicationupdatingandevolvingtheontologyefficientlyinresponsetoend-userneeds;

and（iii）thedevelopmentofanOntology-basedTrialManagementApplication（ObTiMA）thatintegratestheACGT-MOintothedesignprocessofclinicaltrialsinordertoguaranteeautomaticsemanticintegrationwithouttheneedtoperformaseparatemappingprocess.

2.TheACGTMasterOntology

2.1.Technicaldetails

2.2.Scope

2.3.Aim

2.4.TheACGT-MOandsemanticintegrationintheACGTinfrastructure

3.PrinciplesguidingthedevelopmentoftheACGT-MO

3.1.Theadoptionofaradicallyrestrictivedefinitionoftheterm“ontology”,incompliancewiththeprinciplesofrealism

3.2.Enforcingastrictsubsumptionhierarchy,basedonaformallyspecifiedis_arelation,asopposedtoaloose“subclass”hierarchy

3.3.Avoiding（non-trivial）multipleinheritanceinthehierarchyofuniversals

3.4.AvoidingUnknownXandrelatedclasses

3.5.UsinganUpperOntology,namelyBasicFormalOntology

3.6.UsingOBORelationOntology（RO）asasourceof,andinsightfornewrelations/properties

4.MaintenanceoftheACGT-MO

4.1.TheACGTSubmissionSystem

4.2.TheSubmissionProcess

5.EvaluationoftheACGT-MO

5.1.Criteriaofontologyevaluation

5.1.1.Logicalsoundness

5.1.2.Domaincoverage

5.1.3.Taskorientation

5.1.4.Re-useofexistingontologies

5.2.TheroleoftheOBOFoundryintheevaluationoftheACGT-MO

5.3.TheuseoftheACGT-MOoutsidetheACGTproject

6.ExploitationoftheMOintheACGTproject

6.1.SemanticdataintegrationinACGT

6.1.1.Ontologiesindatabaseintegrationsystems–background

6.1.2.SemanticMediation

6.1.3.Queryprocessing

6.1.4.Themappingprocess

6.2.ObTiMA–anOntology-basedTrialManagementApplicationforACGT

6.2.1.Ontology-basedtrialsetup

6.2.2.Ontology-baseddataintegrationforcross-trialanalysis

6.2.3.OntologyevolutioninObTiMA

6.2.4.Advantagesofontologyintegration

7.Discussion

7.1.SemanticMediationinACGT

7.2.ComparisonoftheACGTstrategywiththecaBIGapproach

7.2.1.OverviewofthecaBIGdataintegrationplatform

7.2.2.caBIGvsACGT–theproblemofmetadata

8.Conclusion

9.Summarytable

9.1.Whatwasalreadyknownonthetopic

9.2.Whatthestudyaddedtoourknowledge

First-principlescomputationofmaterialproperties:

theABINITsoftwareproject 

ComputationalMaterialsScience,Volume25,Issue3,November2002,Pages478-492

X.Gonze,J.-M.Beuken,R.Caracas,F.Detraux,M.Fuchs,G.-M.Rignanese,L.Sindic,M.Verstraete,G.Zerah,F.Jollet,M.Torrent,A.Roy,M.Mikami,Ph.Ghosez,J.-Y.Raty,D.C.Allan

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Thedensityfunctionaltheory（DFT）computationofelectronicstructure,totalenergyandotherpropertiesofmaterials,isafieldinconstantprogress.Inordertostayattheforefrontofknowledge,aDFTsoftwareprojectcanbenefitenormouslyfromwidesp