Meta-Heuristics for the Design of a Demand-Responsive Transit Line

The Majestic and Unique OstrichThe ostrich is a fascinating and unique bird that stands out in the animal kingdom due to its impressive size,speed,and distinctive features. Native to Africa,the ostrich is the largest and heaviest living bird,and it has adapted remarkably well to its environment.This essay will explore the characteristics,behavior,habitat,ecological importance,and interactions of ostriches with humans.Characteristics of OstrichesOstriches possess several distinctive features that make them easily recognizable:Physical Appearance:Ostriches are large,flightless birds with long necks, powerful legs,and a small head.Adult males can reach heights of up to9 feet(2.7meters)and weigh between220to350pounds(100to160 kilograms).Females are slightly smaller.Their plumage is predominantly black and white in males and brownish-gray in females,providing camouflage in their natural habitat.Legs and Feet:Ostriches have strong,muscular legs that are adapted for running.They have two toes on each foot,with the larger toe bearing a sharp claw that can be used for defense.Their legs are capable of delivering powerful kicks,which can deter predators.Eyes and Vision:Ostriches have large eyes,which are the largest of any land animal,measuring up to2inches(5centimeters)in diameter.Their keen eyesight allows them to spot predators from a distance,giving them ample time to flee.Feathers and Wings:Although ostriches cannot fly,they have large wings that they use for balance while running and for display during courtship rituals.Their feathers are soft and fluffy,providing insulation and protection from the harsh sun.Behavior and AdaptationsOstriches exhibit a range of behaviors and adaptations that help them survive in their environments:Running Speed:Ostriches are the fastest running birds,capable of reaching speeds of up to45miles per hour(72kilometers per hour). Their long legs and powerful muscles enable them to cover great distances quickly,helping them escape predators and travel between feeding areas.Diet:Ostriches are omnivores,feeding on a variety of plant materials, including seeds,leaves,and fruits,as well as insects and small vertebrates.They have a unique digestive system that includes a large, muscular stomach called a gizzard,which grinds up food with the help of swallowed stones.Reproduction:During the breeding season,male ostriches perform elaborate courtship displays to attract females.These displays include dancing,feather fluffing,and vocalizations.Once a pair has mated,the female lays her eggs in a communal nest,which is a shallow depression in the ground.Multiple females may lay their eggs in the same nest,with the dominant female's eggs placed in the center.Both males and females take turns incubating the eggs.Social Structure:Ostriches are social animals that often live in groups called flocks.These flocks can range in size from a few individuals to several dozen.Living in groups provides protection from predators,as there are more eyes to keep watch and more individuals to deter threats.Habitat and DistributionOstriches are highly adaptable and can be found in a variety of habitats across Africa:Savannas and Grasslands:Ostriches are commonly found in open savannas and grasslands,where they have access to abundant food sources and can easily spot predators.These environments provide the space needed for their large size and running capabilities.Deserts and Semi-Arid Regions:Ostriches are also well-adapted to arid and semi-arid regions,such as the Sahara Desert.They can tolerate high temperatures and have physiological adaptations that allow them to conserve water and survive in harsh conditions.Woodlands and Shrublands:In some areas,ostriches inhabit woodlands and shrublands,where they find shelter and food among the trees and bushes.These environments offer protection from the sun and predators.Ecological ImportanceOstriches play several important roles in their ecosystems:Seed Dispersal:As they forage on a variety of plant materials,ostriches help disperse seeds through their droppings.This contributes to the regeneration and spread of plant species,promoting biodiversity and ecosystem health.Prey Species:Although adult ostriches have few natural predators due to their size and speed,their eggs and chicks are vulnerable to predation by animals such as jackals,hyenas,and birds of prey.This predation pressure helps regulate ostrich populations and maintain ecological balance.Grazing and Vegetation Management:By feeding on grasses and other vegetation,ostriches help manage plant growth and prevent overgrowth.This grazing activity can benefit other herbivores and contribute to the overall health of the ecosystem.Interactions with HumansOstriches have a range of interactions with humans,both positive and negative:Farming and Domestication:Ostriches have been farmed and domesticated for their feathers,meat,and leather.Ostrich farming is a significant industry in some parts of the world,providing economic benefits and sustainable livelihoods.Ostrich meat is lean and high in protein,while their feathers are used in fashion and decoration.Tourism and Wildlife Viewing:Ostriches are a popular attraction for tourists and wildlife enthusiasts.Safaris and wildlife reserves often include opportunities to observe ostriches in their natural habitat, contributing to eco-tourism and conservation awareness.Cultural Significance:Ostriches hold cultural significance in many African societies,symbolizing speed,strength,and beauty.They appear in folklore,art,and traditional ceremonies,reflecting their importance in local cultures.Conservation Challenges:While ostrich populations are generally stable, they face threats from habitat loss,hunting,and human-wildlife conflict. Conservation efforts focus on protecting their habitats,regulating hunting,and promoting sustainable farming practices.ConclusionOstriches are remarkable creatures that play important roles in their ecosystems and have a variety of interactions with humans.Their unique characteristics,behaviors,and adaptations make them fascinatingsubjects of study and appreciation.Understanding and appreciating ostriches can lead to greater awareness of the importance of biodiversity and the need to protect and conserve our natural environments.By fostering a deeper connection to the natural world and recognizing the ecological significance of even the most unique creatures,we can work towards a more sustainable and harmonious relationship with the environment.Protecting ostriches and their habitats is essential for maintaining the health and balance of ecosystems and ensuring the continued survival of these majestic and unique birds.。

计算机领域国际会议分类排名现在的会议非常多，在投文章前，大家可以先看看会议的权威性、前几届的录用率，这样首先对自己的文章能不能中有个大概的心理底线。

权威与否可以和同行的同学沟通、或者看录用文章的水平、或者自己平时阅读文献的时候的慢慢累及。

原来有人做过一个国际会议的排名，如下.sg/home/assourav/crank.htm其中的很多会议我们都非常熟悉的。

但是这个排名是大概2000的时候做的，后来没有更新，所以像ISWC 这个会议在其中就看不到。

但是很多悠久的会议上面都有的，如www,SIGIR,VLDB,EMLC,ICTAI这些等等。

这些东西可以作为一个参考。

现在很多学校的同学毕业都要有检索的要求了。

因此很多不在SCI，EI检索范围内的会议投了可能对毕业无用，所以投之前最好查查会议是不是被SCI，EI检索的。

当然这也不绝对，如Web领域最权威的WWW的全文就只是ISTP检索，而不是SCI，EI检索的（可能是ACM出版的原因吧？）。

罗嗦了这么多！祝愿大家能在好的会议上发PAPER，能被SCI，EI检索。

---------------附，会议排名（from .sg/home/assourav/crank.htm）Computer Science Conference RankingsSome conferences accept multiple categories of papers. The rankings below are for the mos t prestigious category of paper at a given conference. All other categories should be treat ed as "unranked".AREA: DatabasesRank 1:SIGMOD: ACM SIGMOD Conf on Management of DataPODS: ACM SIGMOD Conf on Principles of DB SystemsVLDB: Very Large Data BasesICDE: Intl Conf on Data EngineeringICDT: Intl Conf on Database TheoryRank 2:SSD: Intl Symp on Large Spatial DatabasesDEXA: Database and Expert System ApplicationsFODO: Intl Conf on Foundation on Data OrganizationEDBT: Extending DB TechnologyDOOD: Deductive and Object-Oriented DatabasesDASFAA: Database Systems for Advanced ApplicationsCIKM: Intl. Conf on Information and Knowledge ManagementSSDBM: Intl Conf on Scientific and Statistical DB MgmtCoopIS - Conference on Cooperative Information SystemsER - Intl Conf on Conceptual Modeling (ER)Rank 3:COMAD: Intl Conf on Management of DataBNCOD: British National Conference on DatabasesADC: Australasian Database ConferenceADBIS: Symposium on Advances in DB and Information SystemsDaWaK - Data Warehousing and Knowledge DiscoveryRIDE WorkshopIFIP-DS: IFIP-DS ConferenceIFIP-DBSEC - IFIP Workshop on Database SecurityNGDB: Intl Symp on Next Generation DB Systems and AppsADTI: Intl Symp on Advanced DB Technologies and Integration FEWFDB: Far East Workshop on Future DB SystemsMDM - Int. Conf. on Mobile Data Access/Management (MDA/MDM)ICDM - IEEE International Conference on Data MiningVDB - Visual Database SystemsIDEAS - International Database Engineering and Application Symposium Others:ARTDB - Active and Real-Time Database SystemsCODAS: Intl Symp on Cooperative DB Systems for Adv AppsDBPL - Workshop on Database Programming LanguagesEFIS/EFDBS - Engineering Federated Information (Database) Systems KRDB - Knowledge Representation Meets DatabasesNDB - National Database Conference (China)NLDB - Applications of Natural Language to Data BasesFQAS - Flexible Query-Answering SystemsIDC(W) - International Database Conference (HK CS)RTDB - Workshop on Real-Time DatabasesSBBD: Brazilian Symposium on DatabasesWebDB - International Workshop on the Web and DatabasesWAIM: Interational Conference on Web Age Information ManagementDASWIS - Data Semantics in Web Information SystemsDMDW - Design and Management of Data WarehousesDOLAP - International Workshop on Data Warehousing and OLAPDMKD - Workshop on Research Issues in Data Mining and Knowledge DiscoveryKDEX - Knowledge and Data Engineering Exchange WorkshopNRDM - Workshop on Network-Related Data ManagementMobiDE - Workshop on Data Engineering for Wireless and Mobile AccessMDDS - Mobility in Databases and Distributed SystemsMEWS - Mining for Enhanced Web SearchTAKMA - Theory and Applications of Knowledge MAnagementWIDM: International Workshop on Web Information and Data ManagementW2GIS - International Workshop on Web and Wireless Geographical Information Systems CDB - Constraint Databases and ApplicationsDTVE - Workshop on Database Technology for Virtual EnterprisesIWDOM - International Workshop on Distributed Object ManagementOODBS - Workshop on Object-Oriented Database SystemsPDIS: Parallel and Distributed Information SystemsAREA: Artificial Intelligence and Related SubjectsRank 1:AAAI: American Association for AI National ConferenceCVPR: IEEE Conf on Comp Vision and Pattern RecognitionIJCAI: Intl Joint Conf on AIICCV: Intl Conf on Computer VisionICML: Intl Conf on Machine LearningKDD: Knowledge Discovery and Data MiningKR: Intl Conf on Principles of KR & ReasoningNIPS: Neural Information Processing SystemsUAI: Conference on Uncertainty in AIAAMAS: Intl Conf on Autonomous Agents and Multi-Agent Systems (past: ICAA)ACL: Annual Meeting of the ACL (Association of Computational Linguistics)Rank 2:NAACL: North American Chapter of the ACLAID: Intl Conf on AI in DesignAI-ED: World Conference on AI in EducationCAIP: Inttl Conf on Comp. Analysis of Images and PatternsCSSAC: Cognitive Science Society Annual ConferenceECCV: European Conference on Computer VisionEAI: European Conf on AIEML: European Conf on Machine LearningGECCO: Genetic and Evolutionary Computation Conference (used to be GP)IAAI: Innovative Applications in AIICIP: Intl Conf on Image ProcessingICNN/IJCNN: Intl (Joint) Conference on Neural NetworksICPR: Intl Conf on Pattern RecognitionICDAR: International Conference on Document Analysis and RecognitionICTAI: IEEE conference on Tools with AIAMAI: Artificial Intelligence and MathsDAS: International Workshop on Document Analysis SystemsWACV: IEEE Workshop on Apps of Computer VisionCOLING: International Conference on Computational LiguisticsEMNLP: Empirical Methods in Natural Language ProcessingEACL: Annual Meeting of European Association Computational LingusticsCoNLL: Conference on Natural Language LearningDocEng: ACM Symposium on Document EngineeringIEEE/WIC International Joint Conf on Web Intelligence and Intelligent Agent Technology Rank 3:PRICAI: Pacific Rim Intl Conf on AIAAI: Australian National Conf on AIACCV: Asian Conference on Computer VisionAI*IA: Congress of the Italian Assoc for AIANNIE: Artificial Neural Networks in EngineeringANZIIS: Australian/NZ Conf on Intelligent Inf. SystemsCAIA: Conf on AI for ApplicationsCAAI: Canadian Artificial Intelligence ConferenceASADM: Chicago ASA Data Mining Conf: A Hard Look at DMEPIA: Portuguese Conference on Artificial IntelligenceFCKAML: French Conf on Know. Acquisition & Machine LearningICANN: International Conf on Artificial Neural NetworksICCB: International Conference on Case-Based ReasoningICGA: International Conference on Genetic AlgorithmsICONIP: Intl Conf on Neural Information ProcessingIEA/AIE: Intl Conf on Ind. & Eng. Apps of AI & Expert SysICMS: International Conference on Multiagent SystemsICPS: International conference on Planning SystemsIWANN: Intl Work-Conf on Art & Natural Neural NetworksPACES: Pacific Asian Conference on Expert SystemsSCAI: Scandinavian Conference on Artifical IntelligenceSPICIS: Singapore Intl Conf on Intelligent SystemPAKDD: Pacific-Asia Conf on Know. Discovery & Data MiningSMC: IEEE Intl Conf on Systems, Man and CyberneticsPAKDDM: Practical App of Knowledge Discovery & Data MiningWCNN: The World Congress on Neural NetworksWCES: World Congress on Expert SystemsASC: Intl Conf on AI and Soft ComputingPACLIC: Pacific Asia Conference on Language, Information and ComputationICCC: International Conference on Chinese ComputingICADL: International Conference on Asian Digital LibrariesRANLP: Recent Advances in Natural Language ProcessingNLPRS: Natural Language Pacific Rim SymposiumMeta-Heuristics International ConferenceRank 3:ICRA: IEEE Intl Conf on Robotics and AutomationNNSP: Neural Networks for Signal ProcessingICASSP: IEEE Intl Conf on Acoustics, Speech and SPGCCCE: Global Chinese Conference on Computers in EducationICAI: Intl Conf on Artificial IntelligenceAEN: IASTED Intl Conf on AI, Exp Sys & Neural NetworksWMSCI: World Multiconfs on Sys, Cybernetics & InformaticsLREC: Language Resources and Evaluation ConferenceAIMSA: Artificial Intelligence: Methodology, Systems, ApplicationsAISC: Artificial Intelligence and Symbolic ComputationCIA: Cooperative Information AgentsInternational Conference on Computational Intelligence for Modelling, Control and Automation Pattern MatchingECAL: European Conference on Artificial LifeEKAW: Knowledge Acquisition, Modeling and ManagementEMMCVPR: Energy Minimization Methods in Computer Vision and Pattern RecognitionEuroGP: European Conference on Genetic ProgrammingFoIKS: Foundations of Information and Knowledge SystemsIAWTIC: International Conference on Intelligent Agents, Web Technologies and Internet Commer ceICAIL: International Conference on Artificial Intelligence and LawSMIS: International Syposium on Methodologies for Intelligent SystemsIS&N: Intelligence and Services in NetworksJELIA: Logics in Artificial IntelligenceKI: German Conference on Artificial IntelligenceKRDB: Knowledge Representation Meets DatabasesMAAMAW: Modelling Autonomous Agents in a Multi-Agent WorldNC: ICSC Symposium on Neural ComputationPKDD: Principles of Data Mining and Knowledge DiscoverySBIA: Brazilian Symposium on Artificial IntelligenceScale-Space: Scale-Space Theories in Computer VisionXPS: Knowledge-Based SystemsI2CS: Innovative Internet Computing SystemsTARK: Theoretical Aspects of Rationality and Knowledge MeetingMKM: International Workshop on Mathematical Knowledge ManagementACIVS: International Conference on Advanced Concepts For Intelligent Vision Systems ATAL: Agent Theories, Architectures, and LanguagesLACL: International Conference on Logical Aspects of Computational LinguisticsAREA: Hardware and ArchitectureRank 1:ASPLOS: Architectural Support for Prog Lang and OSISCA: ACM/IEEE Symp on Computer ArchitectureICCAD: Intl Conf on Computer-Aided DesignDAC: Design Automation ConfMICRO: Intl Symp on MicroarchitectureHPCA: IEEE Symp on High-Perf Comp ArchitectureRank 2:FCCM: IEEE Symposium on Field Programmable Custom Computing MachinesSUPER: ACM/IEEE Supercomputing ConferenceICS: Intl Conf on SupercomputingISSCC: IEEE Intl Solid-State Circuits ConfHCS: Hot Chips SympVLSI: IEEE Symp VLSI CircuitsCODES+ISSS: Intl Conf on Hardware/Software Codesign & System SynthesisDATE: IEEE/ACM Design, Automation & Test in Europe ConferenceFPL: Field-Programmable Logic and ApplicationsCASES: International Conference on Compilers, Architecture, and Synthesis for Embedded Syste msRank 3:ICA3PP: Algs and Archs for Parall ProcEuroMICRO: New Frontiers of Information TechnologyACS: Australian Supercomputing ConfISC: Information Security ConferenceUnranked:Advanced Research in VLSIInternational Symposium on System SynthesisInternational Symposium on Computer DesignInternational Symposium on Circuits and SystemsAsia Pacific Design Automation ConferenceInternational Symposium on Physical DesignInternational Conference on VLSI DesignCANPC: Communication, Architecture, and Applications for Network-Based Parallel Computing CHARME: Conference on Correct Hardware Design and Verification MethodsCHES: Cryptographic Hardware and Embedded SystemsNDSS: Network and Distributed System Security SymposiumNOSA: Nordic Symposium on Software ArchitectureACAC: Australasian Computer Architecture ConferenceCSCC: WSES/IEEE world multiconference on Circuits, Systems, Communications & Computers ICN: IEEE International Conference on Networking Topology in Computer Science ConferenceAREA: Applications and MediaRank 1:I3DG: ACM-SIGRAPH Interactive 3D GraphicsSIGGRAPH: ACM SIGGRAPH ConferenceACM-MM: ACM Multimedia ConferenceDCC: Data Compression ConfSIGMETRICS: ACM Conf on Meas. & Modelling of Comp SysSIGIR: ACM SIGIR Conf on Information RetrievalPECCS: IFIP Intl Conf on Perf Eval of Comp \& Comm Sys WWW: World-Wide Web ConferenceRank 2:IEEE VisualizationEUROGRAPH: European Graphics ConferenceCGI: Computer Graphics InternationalCANIM: Computer AnimationPG: Pacific GraphicsICME: Intl Conf on MMedia & ExpoNOSSDAV: Network and OS Support for Digital A/VPADS: ACM/IEEE/SCS Workshop on Parallel \& Dist Simulation WSC: Winter Simulation ConferenceASS: IEEE Annual Simulation SymposiumMASCOTS: Symp Model Analysis \& Sim of Comp \& Telecom Sys PT: Perf Tools - Intl Conf on Model Tech \& Tools for CPE NetStore: Network Storage SymposiumMMCN: ACM/SPIE Multimedia Computing and NetworkingJCDL: Joint Conference on Digital LibrariesRank 3:ACM-HPC: ACM Hypertext ConfMMM: Multimedia ModellingDSS: Distributed Simulation SymposiumSCSC: Summer Computer Simulation ConferenceWCSS: World Congress on Systems SimulationESS: European Simulation SymposiumESM: European Simulation MulticonferenceHPCN: High-Performance Computing and NetworkingGeometry Modeling and ProcessingWISEDS-RT: Distributed Simulation and Real-time Applications IEEE Intl Wshop on Dist Int Simul and Real-Time Applications ECIR: European Colloquium on Information RetrievalEd-MediaIMSA: Intl Conf on Internet and MMedia SysUn-ranked:DVAT: IS\&T/SPIE Conf on Dig Video Compression Alg \& TechMME: IEEE Intl Conf. on Multimedia in EducationICMSO: Intl Conf on Modelling, Simulation and OptimisationICMS: IASTED Intl Conf on Modelling and SimulationCOTIM: Conference on Telecommunications and Information MarketsDOA: International Symposium on Distributed Objects and ApplicationsECMAST: European Conference on Multimedia Applications, Services and TechniquesGIS: Workshop on Advances in Geographic Information SystemsIDA: Intelligent Data AnalysisIDMS: Interactive Distributed Multimedia Systems and Telecommunication ServicesIUI: Intelligent User InterfacesMIS: Workshop on Multimedia Information SystemsWECWIS: Workshop on Advanced Issues of E-Commerce and Web/based Information Systems WIDM: Web Information and Data ManagementWOWMOM: Workshop on Wireless Mobile MultimediaWSCG: International Conference in Central Europe on Computer Graphics and Visualization LDTA: Workshop on Language Descriptions, Tools and ApplicationsIPDPSWPIM: International Workshop on Parallel and Distributed Computing Issues in Wireless N etworks and Mobile ComputingIWST: International Workshop on Scheduling and TelecommunicationsAPDCM: Workshop on Advances in Parallel and Distributed Computational ModelsCIMA: International ICSC Congress on Computational Intelligence: Methods and Applications FLA: Fuzzy Logic and Applications MeetingICACSD: International Conference on Application of Concurrency to System DesignICATPN: International conference on application and theory of Petri netsAICCSA: ACS International Conference on Computer Systems and ApplicationsCAGD: International Symposium of Computer Aided Geometric DesignSpanish Symposium on Pattern Recognition and Image AnalysisInternational Workshop on Cluster Infrastructure for Web Server and E-Commerce Applications WSES ISA: Information Science And Applications ConferenceCHT: International Symposium on Advances in Computational Heat TransferIMACS: International Conference on Applications of Computer AlgebraVIPromCom: International Symposium on Video Processing and Multimedia Communications PDMPR: International Workshop on Parallel and Distributed Multimedia Processing & Retrieval International Symposium On Computational And Applied PdesPDCAT: International Conference on Parallel and Distributed Computing, Applications, and Tec hniquesBiennial Computational Techniques and Applications ConferenceSymposium on Advanced Computing in Financial MarketsWCCE: World Conference on Computers in EducationITCOM: SPIE's International Symposium on The Convergence of Information Technologies and Com municationsConference on Commercial Applications for High-Performance ComputingMSA: Metacomputing Systems and Applications WorkshopWPMC : International Symposium on Wireless Personal Multimedia Communications WSC: Online World Conference on Soft Computing in Industrial Applications HERCMA: Hellenic European Research on Computer Mathematics and its Applications PARA: Workshop on Applied Parallel ComputingInternational Computer Science Conference: Active Media TechnologyIW-MMDBMS - Int. Workshop on Multi-Media Data Base Management SystemsAREA: System TechnologyRank 1:SIGCOMM: ACM Conf on Comm Architectures, Protocols & AppsINFOCOM: Annual Joint Conf IEEE Comp & Comm SocSPAA: Symp on Parallel Algms and ArchitecturePODC: ACM Symp on Principles of Distributed ComputingPPoPP: Principles and Practice of Parallel ProgrammingRTSS: Real Time Systems SympSOSP: ACM SIGOPS Symp on OS PrinciplesSOSDI: Usenix Symp on OS Design and ImplementationCCS: ACM Conf on Comp and Communications SecurityIEEE Symposium on Security and PrivacyMOBICOM: ACM Intl Conf on Mobile Computing and NetworkingUSENIX Conf on Internet Tech and SysICNP: Intl Conf on Network ProtocolsPACT: Intl Conf on Parallel Arch and Compil TechRTAS: IEEE Real-Time and Embedded Technology and Applications Symposium ICDCS: IEEE Intl Conf on Distributed Comp SystemsRank 2:CC: Compiler ConstructionIPDPS: Intl Parallel and Dist Processing SympIC3N: Intl Conf on Comp Comm and NetworksICPP: Intl Conf on Parallel ProcessingSRDS: Symp on Reliable Distributed SystemsMPPOI: Massively Par Proc Using Opt InterconnsASAP: Intl Conf on Apps for Specific Array ProcessorsEuro-Par: European Conf. on Parallel ComputingFast Software EncryptionUsenix Security SymposiumEuropean Symposium on Research in Computer SecurityWCW: Web Caching WorkshopLCN: IEEE Annual Conference on Local Computer NetworksIPCCC: IEEE Intl Phoenix Conf on Comp & CommunicationsCCC: Cluster Computing ConferenceICC: Intl Conf on CommWCNC: IEEE Wireless Communications and Networking ConferenceCSFW: IEEE Computer Security Foundations WorkshopRank 3:MPCS: Intl. Conf. on Massively Parallel Computing SystemsGLOBECOM: Global CommICCC: Intl Conf on Comp CommunicationNOMS: IEEE Network Operations and Management SympCONPAR: Intl Conf on Vector and Parallel ProcessingVAPP: Vector and Parallel ProcessingICPADS: Intl Conf. on Parallel and Distributed SystemsPublic Key CryptosystemsAnnual Workshop on Selected Areas in CryptographyAustralasia Conference on Information Security and PrivacyInt. Conf on Inofrm and Comm. SecurityFinancial CryptographyWorkshop on Information HidingSmart Card Research and Advanced Application ConferenceICON: Intl Conf on NetworksNCC: Nat Conf CommIN: IEEE Intell Network WorkshopSoftcomm: Conf on Software in Tcomms and Comp NetworksINET: Internet Society ConfWorkshop on Security and Privacy in E-commerceUn-ranked:PARCO: Parallel ComputingSE: Intl Conf on Systems Engineering (**)PDSECA: workshop on Parallel and Distributed Scientific and Engineering Computing with Appli cationsCACS: Computer Audit, Control and Security ConferenceSREIS: Symposium on Requirements Engineering for Information SecuritySAFECOMP: International Conference on Computer Safety, Reliability and SecurityIREJVM: Workshop on Intermediate Representation Engineering for the Java Virtual Machine EC: ACM Conference on Electronic CommerceEWSPT: European Workshop on Software Process TechnologyHotOS: Workshop on Hot Topics in Operating SystemsHPTS: High Performance Transaction SystemsHybrid SystemsICEIS: International Conference on Enterprise Information SystemsIOPADS: I/O in Parallel and Distributed SystemsIRREGULAR: Workshop on Parallel Algorithms for Irregularly Structured ProblemsKiVS: Kommunikation in Verteilten SystemenLCR: Languages, Compilers, and Run-Time Systems for Scalable ComputersMCS: Multiple Classifier SystemsMSS: Symposium on Mass Storage SystemsNGITS: Next Generation Information Technologies and SystemsOOIS: Object Oriented Information SystemsSCM: System Configuration ManagementSecurity Protocols WorkshopSIGOPS European WorkshopSPDP: Symposium on Parallel and Distributed ProcessingTreDS: Trends in Distributed SystemsUSENIX Technical ConferenceVISUAL: Visual Information and Information SystemsFoDS: Foundations of Distributed Systems: Design and Verification of Protocols conference RV: Post-CAV Workshop on Runtime VerificationICAIS: International ICSC-NAISO Congress on Autonomous Intelligent SystemsITiCSE: Conference on Integrating Technology into Computer Science EducationCSCS: CyberSystems and Computer Science ConferenceAUIC: Australasian User Interface ConferenceITI: Meeting of Researchers in Computer Science, Information Systems Research & Statistics European Conference on Parallel ProcessingRODLICS: Wses International Conference on Robotics, Distance Learning & Intelligent Communic ation SystemsInternational Conference On Multimedia, Internet & Video TechnologiesPaCT: Parallel Computing Technologies workshopPPAM: International Conference on Parallel Processing and Applied MathematicsInternational Conference On Information Networks, Systems And TechnologiesAmiRE: Conference on Autonomous Minirobots for Research and EdutainmentDSN: The International Conference on Dependable Systems and NetworksIHW: Information Hiding WorkshopGTVMT: International Workshop on Graph Transformation and Visual Modeling Techniques AREA: Programming Languages and Software EngineeringRank 1:POPL: ACM-SIGACT Symp on Principles of Prog LangsPLDI: ACM-SIGPLAN Symp on Prog Lang Design & ImplOOPSLA: OO Prog Systems, Langs and ApplicationsICFP: Intl Conf on Function ProgrammingJICSLP/ICLP/ILPS: (Joint) Intl Conf/Symp on Logic ProgICSE: Intl Conf on Software EngineeringFSE: ACM Conf on the Foundations of Software Engineering (inc: ESEC-FSE) FM/FME: Formal Methods, World Congress/EuropeCAV: Computer Aided VerificationRank 2:CP: Intl Conf on Principles & Practice of Constraint ProgTACAS: Tools and Algos for the Const and An of SystemsESOP: European Conf on ProgrammingICCL: IEEE Intl Conf on Computer LanguagesPEPM: Symp on Partial Evalutation and Prog ManipulationSAS: Static Analysis SymposiumRTA: Rewriting Techniques and ApplicationsIWSSD: Intl Workshop on S/W Spec & DesignCAiSE: Intl Conf on Advanced Info System EngineeringSSR: ACM SIGSOFT Working Conf on Software ReusabilitySEKE: Intl Conf on S/E and Knowledge EngineeringICSR: IEEE Intl Conf on Software ReuseASE: Automated Software Engineering ConferencePADL: Practical Aspects of Declarative LanguagesISRE: Requirements EngineeringICECCS: IEEE Intl Conf on Eng. of Complex Computer SystemsIEEE Intl Conf on Formal Engineering MethodsIntl Conf on Integrated Formal MethodsFOSSACS: Foundations of Software Science and Comp StructAPLAS: Asian Symposium on Programming Languages and SystemsMPC: Mathematics of Program ConstructionECOOP: European Conference on Object-Oriented ProgrammingICSM: Intl. Conf on Software MaintenanceHASKELL - Haskell WorkshopRank 3:FASE: Fund Appr to Soft EngAPSEC: Asia-Pacific S/E ConfPAP/PACT: Practical Aspects of PROLOG/Constraint TechALP: Intl Conf on Algebraic and Logic ProgrammingPLILP: Prog, Lang Implentation & Logic ProgrammingLOPSTR: Intl Workshop on Logic Prog Synthesis & TransfICCC: Intl Conf on Compiler ConstructionCOMPSAC: Intl. Computer S/W and Applications ConfTAPSOFT: Intl Joint Conf on Theory & Pract of S/W DevWCRE: SIGSOFT Working Conf on Reverse EngineeringAQSDT: Symp on Assessment of Quality S/W Dev ToolsIFIP Intl Conf on Open Distributed ProcessingIntl Conf of Z UsersIFIP Joint Int'l Conference on Formal Description Techniques and Protocol Specification, Tes ting, And VerificationPSI (Ershov conference)UML: International Conference on the Unified Modeling LanguageUn-ranked:Australian Software Engineering ConferenceIEEE Int. W'shop on Object-oriented Real-time Dependable Sys. (WORDS)IEEE International Symposium on High Assurance Systems EngineeringThe Northern Formal Methods WorkshopsFormal Methods PacificInt. Workshop on Formal Methods for Industrial Critical SystemsJFPLC - International French Speaking Conference on Logic and Constraint ProgrammingL&L - Workshop on Logic and LearningSFP - Scottish Functional Programming WorkshopLCCS - International Workshop on Logic and Complexity in Computer ScienceVLFM - Visual Languages and Formal MethodsNASA LaRC Formal Methods WorkshopPASTE: Workshop on Program Analysis For Software Tools and EngineeringTLCA: Typed Lambda Calculus and ApplicationsFATES - A Satellite workshop on Formal Approaches to Testing of SoftwareWorkshop On Java For High-Performance ComputingDSLSE - Domain-Specific Languages for Software EngineeringFTJP - Workshop on Formal Techniques for Java ProgramsWFLP - International Workshop on Functional and (Constraint) Logic ProgrammingFOOL - International Workshop on Foundations of Object-Oriented LanguagesSREIS - Symposium on Requirements Engineering for Information SecurityHLPP - International workshop on High-level parallel programming and applicationsINAP - International Conference on Applications of PrologMPOOL - Workshop on Multiparadigm Programming with OO LanguagesPADO - Symposium on Programs as Data ObjectsTOOLS: Int'l Conf Technology of Object-Oriented Languages and SystemsAustralasian Conference on Parallel And Real-Time SystemsPASTE: Workshop on Program Analysis For Software Tools and EngineeringAvoCS: Workshop on Automated Verification of Critical SystemsSPIN: Workshop on Model Checking of SoftwareFemSys: Workshop on Formal Design of Safety Critical Embedded SystemsAda-EuropePPDP: Principles and Practice of Declarative ProgrammingAPL ConferenceASM: Workshops on Abstract State MachinesCOORDINATION: Coordination Models and LanguagesDocEng: ACM Symposium on Document EngineeringDSV-IS: Design, Specification, and Verification of Interactive SystemsFMCAD: Formal Methods in Computer-Aided DesignFMLDO: Workshop on Foundations of Models and Languages for Data and ObjectsIFL: Implementation of Functional LanguagesILP: International Workshop on Inductive Logic ProgrammingISSTA: International Symposium on Software Testing and AnalysisITC: International Test ConferenceIWFM: Irish Workshop in Formal MethodsJava GrandeLP: Logic Programming: Japanese ConferenceLPAR: Logic Programming and Automated ReasoningLPE: Workshop on Logic Programming EnvironmentsLPNMR: Logic Programming and Non-monotonic ReasoningPJW: Workshop on Persistence and JavaRCLP: Russian Conference on Logic ProgrammingSTEP: Software Technology and Engineering PracticeTestCom: IFIP International Conference on Testing of Communicating SystemsVL: Visual LanguagesFMPPTA: Workshop on Formal Methods for Parallel Programming Theory and Applications WRS: International Workshop on Reduction Strategies in Rewriting and Programming FATES: A Satellite workshop on Formal Approaches to Testing of Software FORMALWARE: Meeting on Formalware Engineering: Formal Methods for Engineering Software DRE: conference Data Reverse EngineeringSTAREAST: Software Testing Analysis & Review ConferenceConference on Applied Mathematics and Scientific ComputingInternational Testing Computer Software ConferenceLinux Showcase & ConferenceFLOPS: International Symposum on Functional and Logic ProgrammingGCSE: International Conference on Generative and Component-Based Software Engineering JOSES: Java Optimization Strategies for Embedded Systems。

专利名称：Automated method and system for theevaluation of disease and registrationaccuracy in the subtraction of temporallysequential medical images发明人：Heber MacMahon,Samuel G. Armato申请号：US10721827申请日：20031126公开号：US20050111718A1公开日：20050526专利内容由知识产权出版社提供专利附图：摘要：An apparatus, method and computer program product for performingcomputer aided diagnosis on temporal subtraction images of objects. A mode of a gray-level histogram is identified, and a gray-level threshold is established at a predefined fraction of this modal value. All pixels with gray levels below this threshold that lie within the lung regions of the temporal subtraction image remain “on,” while all other pixels are set to zero. Area and circularity requirements are imposed to eliminate false-positive regions. Areas of pathologic change identified in this manner may be presented as outlines in the subtraction image or as highlighted regions in the original radiographic image so that, in effect, temporal subtraction becomes a “background” process for computer-aided diagnosis. The present invention is also directed to method, apparatus, and computer program product for performing temporal subtraction on energy subtraction images, with or without subsequent computer aided diagnosis, of objects.申请人：Heber MacMahon,Samuel G. Armato地址：Chicago IL US,Downers Grove IL US国籍：US,US更多信息请下载全文后查看。

Metaphysics形而上学I. IntroductionMetaphysics, branch of philosophy concerned with the nature of ultimate reality. Metaphysics is customarily divided into ontology, which deals with the question of how many fundamentally distinct sorts of entities compose the universe, and metaphysics proper, which is concerned with describing the most general traits of reality. These general traits together define reality and would presumably characterize any universe whatever. Because these traits are not peculiar to this universe, but are common to all possible universes, metaphysics may be conducted at the highest level of abstraction. Ontology, by contrast, because it investigates the ultimate divisions within this universe, is more closely related to the physical world of human experience.The term metaphysics is believed to have originated in Rome about 70 bc, with the Greek Peripatetic philosopher Andronicus of Rhodes (flourished 1st century bc) in his edition of the works of Aristotle. In the arrangement of Aristotle's works by Andronicus, the treatise originally called First Philosophy, or Theology, followed the treatise Physics. Hence, the First Philosophy came to be known as meta (ta) physica, or “following (the) Physics,” later shortened to Metaphysics. The word took on the connotation, in popular usage, of matters transcending material reality. In the philosophic sense, however, particularly as opposed to the use of the word by occultists, metaphysics applies to all reality and is distinguished from other formsof inquiry by its generality.The subjects treated in Aristotle's Metaphysics (substance, causality, the nature of being, and the existence of God) fixed the content of metaphysical speculation for centuries. Among the medieval Scholastic philosophers, metaphysics was known as the “transphysical science” on the assumption that, by means of it, the scholar philosophically could make the transition from the physical world to a world beyond sense perception. The 13th-century Scholastic philosopher and theologian St. Thomas Aquinas declared that the cognition of God, through a causal study of finite sensible beings, was the aim of metaphysics. With the rise of scientific study in the 16th century the reconciliation of science and faith in God became an increasingly important problem.II Metaphysics Before Kant康德(德国哲学家, 1724-1805, 古典唯心主义的创始人)Before the time of the German philosopher Immanuel Kant metaphysics was characterized by a tendency to construct theories on the basis of a priori knowledge, that is, knowledge derived from reason alone, in contradistinction to a posteriori knowledge, which is gained by reference to the facts of experience. From a priori knowledge were deduced general propositions that were held to be true of all things. The method of inquiry based on a priori principles is known as rationalistic. This method may be subdivided into monism, which holds that the universe is made up of a single fundamental substance; dualism, the belief in two such substances; and pluralism,which proposes the existence of many fundamental substances.The monists, agreeing that only one basic substance exists, differ in their descriptions of its principal characteristics. Thus, in idealistic monism the substance is believed to be purely mental; in materialistic monism it is held to be purely physical, and in neutral monism it is considered neither exclusively mental nor solely physical. The idealistic position was held by the Irish philosopher George Berkeley, the materialistic by the English philosopher Thomas Hobbes, and the neutral by the Dutch philosopher Baruch Spinoza. The latter expounded a pantheistic view of reality in which the universe is identical with God and everything contains God's substance. See Idealism; Materialism; Pantheism.The most famous exponent of dualism was the French philosopher René Descartes, who maintained that body and mind are radically different entities and that they are the only fundamental substances in the universe. Dualism, however, does not show how these basic entities are connected.In the work of the German philosopher Gottfried Wilhelm Leibniz, the universe is held to consist of an infinite number of distinct substances, or monads. This view is pluralistic in the sense that it proposes the existence of many separate entities, and it is monistic in its assertion that each monad reflects within itself the entire universe.Other philosophers have held that knowledge of reality is not derived from a priori principles, but is obtained only from experience. This type of metaphysics is called empiricism. Still another school ofphilosophy has maintained that, although an ultimate reality does exist, it is altogether inaccessible to human knowledge, which is necessarily subjective because it is confined to states of mind. Knowledge is therefore not a representation of external reality, but merely a reflection of human perceptions. This view is known as skepticism or agnosticism in respect to the soul and the reality of God.III The Metaphysics of KantSeveral major viewpoints were combined in the work of Kant, who developed a distinctive critical philosophy called transcendentalism. His philosophy is agnostic in that it denies the possibility of a strict knowledge of ultimate reality; it is empirical in that it affirms that all knowledge arises from experience and is true of objects of actual and possible experience; and it is rationalistic in that it maintains the a priori character of the structural principles of this empirical knowledge.These principles are held to be necessary and universal in their application to experience, for in Kant's view the mind furnishes the archetypal forms and categories (space, time, causality, substance, and relation) to its sensations, and these categories are logically anterior to experience, although manifested only in experience. Their logical anteriority to experience makes these categories or structural principles transcendental; they transcend all experience, both actual and possible. Although these principles determine all experience, they do not in any way affect the nature of things in themselves. The knowledge of which these principles are the necessary conditions must not be considered, therefore, as constituting a revelation ofthings as they are in themselves. This knowledge concerns things only insofar as they appear to human perception or as they can be apprehended by the senses. The argument by which Kant sought to fix the limits of human knowledge within the framework of experience and to demonstrate the inability of the human mind to penetrate beyond experience strictly by knowledge to the realm of ultimate reality constitutes the critical feature of his philosophy, giving the key word to the titles of his three leading treatises, Critique of Pure Reason, Critique of Practical Reason, and Critique of Judgment. In the system propounded in these works, Kant sought also to reconcile science and religion in a world of two levels, comprising noumena, objects conceived by reason although not perceived by the senses, and phenomena, things as they appear to the senses and are accessible to material study. He maintained that, because God, freedom, and human immortality are noumenal realities, these concepts are understood through moral faith rather than through scientific knowledge. With the continuous development of science, the expansion of metaphysics to include scientific knowledge and methods became one of the major objectives of metaphysicians.IV Metaphysics Since KantSome of Kant's most distinguished followers, notably Johann Gottlieb Fichte, Friedrich Schelling, Georg Wilhelm Friedrich Hegel, and Friedrich Schleiermacher, negated Kant's criticism in their elaborations of his transcendental metaphysics by denying the Kantian conception of the thing-in-itself. They thus developed anabsolute idealism in opposition to Kant's critical transcendentalism.Since the formation of the hypothesis of absolute idealism, the development of metaphysics has resulted in as many types of metaphysical theory as existed in pre-Kantian philosophy, despite Kant's contention that he had fixed definitely the limits of philosophical speculation. Notable among these later metaphysical theories are radical empiricism, or pragmatism, a native American form of metaphysics expounded by Charles Sanders Peirce, developed by William James, and adapted as instrumentalism by John Dewey; voluntarism, the foremost exponents of which are the German philosopher Arthur Schopenhauer and the American philosopher Josiah Royce; phenomenalism, as it is exemplified in the writings of the French philosopher Auguste Comte and the British philosopher Herbert Spencer; emergent evolution, or creative evolution, originated by the French philosopher Henri Bergson; and the philosophy of the organism, elaborated by the British mathematician and philosopher Alfred North Whitehead. The salient doctrines of pragmatism are that the chief function of thought is to guide action, that the meaning of concepts is to be sought in their practical applications, and that truth should be tested by the practical effects of belief; according to instrumentalism, ideas are instruments of action, and their truth is determined by their role in human experience. In the theory of voluntarism the will is postulated as the supreme manifestation of reality. The exponents of phenomenalism, who are sometimes called positivists, contend that everything can be analyzed in terms of actualor possible occurrences, or phenomena, and that anything that cannot be analyzed in this manner cannot be understood. In emergent or creative evolution, the evolutionary process is characterized as spontaneous and unpredictable rather than mechanistically determined. The philosophy of the organism combines an evolutionary stress on constant process with a metaphysical theory of God, the eternal objects, and creativity.V Contemporary DevelopmentsIn the 20th century the validity of metaphysical thinking has been disputed by the logical positivists (see Analytic and Linguistic Philosophy; Positivism) and by the so-called dialectical materialism of the Marxists. The basic principle maintained by the logical positivists is the verifiability theory of meaning. According to this theory a sentence has factual meaning only if it meets the test of observation. Logical positivists argue that metaphysical expressions such as “Nothing exists except material particles” and “Everything is part of one all-encompassing spirit” cannot be tested empirically. Therefore, according to the verifiability theory of meaning, these expressions have no factual cognitive meaning, although they can have an emotive meaning relevant to human hopes and feelings.The dialectical materialists assert that the mind is conditioned by and reflects material reality. Therefore, speculations that conceive of constructs of the mind as having any other than material reality are themselves unreal and can result only in delusion. To these assertions metaphysicians reply by denying the adequacy of the verifiabilitytheory of meaning and of material perception as the standard of reality.Both logical positivism and dialectical materialism, they argue, conceal metaphysical assumptions, for example, that everything is observable or at least connected with something observable and that the mind has no distinctive life of its own. In the philosophical movement known as existentialism, thinkers have contended that the questions of the nature of being and of the individual's relationship to it are extremely important and meaningful in terms of human life. The investigation of these questions is therefore considered valid whether or not its results can be verified objectively.Since the 1950s the problems of systematic analytical metaphysics have been studied in Britain by Stuart Newton Hampshire and Peter Frederick Strawson, the former concerned, in the manner of Spinoza, with the relationship between thought and action, and the latter, in the manner of Kant, with describing the major categories of experience as they are embedded in language. In the U.S. metaphysics has been pursued much in the spirit of positivism by Wilfred Stalker Sellars and Willard Van Orman Quine. Sellars has sought to express metaphysical questions in linguistic terms, and Quine has attempted to determine whether the structure of language commits the philosopher to asserting the existence of any entities whatever and, if so, what kind. In these new formulations the issues of metaphysics and ontology remain vital.。

HETEROGENEOUS COMPUTINGShoukat Ali, Tracy D. Braun, Howard Jay Siegel, and Anthony A. MaciejewskiSchool of Electrical and Computer Engineering, Purdue UniversityHeterogeneous computing is a set of techniques enabling the use of diverse computational capabilities for the execution of a meta-task [2, 4, 7]. A meta-task is an arbitrary collection of independent (non-communicating) tasks with a variety of computational needs, which are to be executed during a given interval of time (e.g., a day). Some tasks may be decomposable into one or more communicating subtasks (subtasks may, in turn, have diverse computational needs). There are many types of heterogeneous computing systems [2]. This article focuses on mixed-machine systems, where a heterogeneous suite of independent machines is interconnected by high-speed links to function as a meta-computer (see Meta-Computer) or as part of a computational grid(see Computational Grid) [3]. The user of a heterogeneous suite has the illusion of working on a single virtual machine.Research in the field of heterogeneous computing is motivated by the fact that high performance machines vary in capability and, hence, suitability for different types of tasks and subtasks. Examples of such machine architectures include large distributed shared memory machines (e.g., an SGI 2800), distributed memory multiprocessors (e.g., an IBM SP2), and small shared memory machines (e.g., a Sun Enterprise 3000 Server). Furthermore, two implementations of a given machine type may vary in CPU speed, cache memory size and structure, I/O bandwidth, etc. With the recent advances in high-speed digital communications, it has become possible to use collections of different machines in concert to execute large meta-tasks whose tasks and subtasks have diverse computational needs.The goal of heterogeneous computing is to assign these tasks and subtasks to machines and schedule their execution to optimize some performance measure. This measure may be as simple as the execution time of the meta-task. The measure may be more complex and be a mathematical function of various factors such as the weighted priorities of tasks, deadlines for task execution, security requirements, and quality of service (QoS) needs (see QoS). The process of assigning (matching) tasks/subtasks to machines and scheduling their execution is called mapping.A hypothetical example task with four subtasks that are best suited for different machine architectures is shown in Figure 1. The example task executes for 100 time units on a typical workstation. The task consists of four subtasks: the first (S1) is best suited to execute on a large cluster of PCs (e.g., a Beowulf Cluster), the second (S2) is best suited to execute on a distributed memory multiprocessor, the third (S3) is best suited to execute on a distributed shared memory machine, and the fourth (S4) is best suited to execute on a small shared memory machine.Executing the whole task on a large cluster may improve the execution time of the first subtask from 25 to 0.3 time units, and those of the other subtasks to varying extents. The overall execution time improvement may only be about a factor of five because other subtasks are not well suited for execution on a cluster (e.g., due to the need for inter-processor communication). However, using four different machines that match the computational requirements for each of the individual subtasks can result in an overall execution time that is better than the execution time on the workstation by a factor of over 50. For communicating subtasks, inter-machine data transfers need to be performed when multiple machines are used. Hence, data transfer overhead has to be considered as part of the overall execution time on the heterogeneous computing suite whereas there is no such overhead when the entire task is executed on a single workstation.This is a simplified example. Actual tasks may consist of a large number of subtasks with a much more complex inter-subtask communications structure. Also, the sharing of the machines by all the tasks in the meta-task must be considered when mapping.MappingFinding a mapping for tasks that optimizes some performance measure is, in general, an NP-complete problem. For example, consider mapping 30 tasks onto five machines. This means that there are 530 possible mappings. Even if it took only one nanosecond to evaluate each mapping, an exhaustive search to find the best mapping would require 530 nanoseconds > 1000 years! Therefore, it is necessary to have heuristics to find near-optimal mappings without using an exhaustive search. Factors that impact mapping decisions include: (1) match of the task computational requirements to the machine capabilities, (2) overhead for the inter-machine communication of code and data (initial and generated), (3) expected machine load and network congestion, and (4) inter-subtask precedence constraints.There are many different types of heuristics for mapping tasks to the machines in a heterogeneous computing suite. In static mapping heuristics [1], the mapping decisions are made off-line before the execution of the meta-task. A staticmapping heuristic is employed if (1) the tasks that comprise the meta-task are known a priori , (2) predictions about the available heterogeneous computing resources are likely to be accurate, and (3) the estimated expected execution time of each task on each machine in the suite is known reasonably accurately. Static mapping heuristics can be used for planning the “next day’s work” on a heterogeneous computing system.Figure 1. Hypothetical example (based on [4]) of the advantage of using a heterogeneous computing suite of machines. The number underneath each bar indicates execution time. For the suite, each subtask execution time includes the overhead to receive data. Not drawn to scale.In dynamic mapping heuristics [6], the mapping decisions are made on-line during the execution of the meta-task. Dynamic approaches to mapping are needed if any of the following are unpredictable: (1) arrival times of the tasks, (2) machines available in the heterogeneous computing system (some machines in the suite may go off-line and new machines may come on-line), and (3) expected execution times of the tasks on the machines. While a static mapper considers the entire meta-task to be executed (e.g., the next day) when making decisions, a dynamic mapper has only information about tasks that have already arrived for execution. Furthermore, because a dynamic mapper operates on-line, it must make decisions much faster than an off-line static mapper. Consequently, dynamic mapping heuristics often use feedback from the heterogeneous computing system (while tasks are executing) to improve any “bad” mapping decisions.A semi-static mapping heuristic [8] can be used for an iterative task whose subtask execution times will change from iteration to iteration based on the input data. A semi-static methodology observes, from one iteration to another, the effects of the changing characteristics of the task's input data, called dynamic parameters, on the task's execution time. The off-line phase uses a static mapping algorithm to generate high quality mappings for a sampling of values for the dynamic parameters a priori. During the on-line phase, the actual dynamic parameters are observed and a new mapping for the subtasks may be selected from the precomputed off-line mappings. Automatic Heterogeneous ComputingOne of the long-term goals of heterogeneous computing research is to develop software environments that will automatically map and execute tasks expressed in a machine-independent high-level language. Such an environment will facilitate the use of heterogeneous computing suite by increasing portability, because the programmer need not be concerned with the composition of the heterogeneous computing suite, and increasing the possibility of deriving better mappings than the user can derive with ad hoc methods. Thus, it will improve the performance of and encourage the use of heterogeneous computing. While no such environment exists today, many researchers are working to develop one. A conceptual model for such an environment using a dedicated heterogeneous computing suite of machines is described in Figure 2, and consists of four stages.Stage 1 uses information about the type of tasks in the meta-task and machines in the heterogeneous computing suite to generate a set of parameters relevant to both the computational characteristics of tasks and the architectural features of machines. The system then derives categories for computational requirements and categories for machine capabilities from this set of parameters.Stage 2 consists of two components: task profiling and analytical benchmarking. Task profiling (see Task Profiling) decomposes each task of the meta-task into subtasks, where each subtask is computationally homogeneous. The computational requirements of each subtask are quantified by profiling the code and data. Analytical benchmarkingexecution on a cluster(see Analytical Benchmarking) quantifies how effectively each available machine in the suite performs on each type of computational requirement.The information available from stage 2 is used by stage 3 to derive the estimated execution time of each subtask on each machine in the heterogeneous computing suite, along with the associated inter-machine communication overheads. These statically derived results are then incorporated with initial values for machine ready times, inter-machine network delays, and status parameters (e.g., machine/network faults) to perform the mapping of subtasks to machines based on a given performance metric. The result is an assignment of subtasks to machines and an execution schedule. The process as described corresponds to a static mapping.The subtasks are executed in stage 4. If dynamic mapping is employed, the subtask completion times and loading/status of the machines/network are monitored (shown in dashed lines in Figure 2). The monitoring process is necessary because the actual computation times and data transfer times may be input-data dependent and deviate considerably from the static estimates. This information may be used to re-invoke the mapping of stage 3 to improve the machine assignment and execution schedule.Figure 2. Model for integrating the software support needed for automating the use of heterogeneous computing systems (based on [7]). Ovals indicate information and rectangles indicate action.1 2 3 4Environments and ApplicationsExamples of heterogeneous computing environments are: (1) the Purdue University Network Computing Hubs, a wide area network computing system which can be used to run a selection of software tools via a World Wide Web browser [5]; (2) NetSolve, a client-server system with geographically distributed servers that can be accessed from a variety of interfaces, including MATLAB, shell scripts, C, and FORTRAN [3]; and (3) the Globus meta-computing infrastructure toolkit, a set of low-level mechanisms that can be built upon to develop higher level heterogeneous computing services [3].Example applications that have demonstrated the usefulness of heterogeneous computing include: (1) a three-dimensional simulation of mixing and turbulent convection at the Minnesota Supercomputer Center [7]; (2) the shipboard anti-air warfare program (HiPer-D) used at the Naval Surface Warfare Center for threat detection, target engagement, and missile guidance; and (3) a simulation of colliding galaxies performed by solving large n-body dynamics problems and large gas dynamics problems at the National Center for Supercomputing Applications [7]. Open Problems in Heterogeneous ComputingHeterogeneous computing is a relatively new research area for the computer field. Interest in such systems continues to grow both in the research community and in the user community. The realization of the automatic heterogeneous computing environment envisioned in Figure 2 requires further research in many areas. Machine-independent languages with user-specified directives are needed to (1) allow compilation of a given task into efficient code for any machine in the suite, (2) aid in decomposing tasks into subtasks, and (3) facilitate determination of subtask computational requirements. Moreover, methods must be refined for measuring the loading and status of the machines in the heterogeneous computing suite and the network, and for estimating the subtask completion times. Also, the uncertainty present in the estimated parameter values, such as subtask completion times, should be taken into consideration in determining the mappings. Other research areas are (1) developing communication protocols for reliable, low overhead data transmission over heterogeneous networks with given QoS requirements, (2) devising debugging tools that can be used transparently across the suite of machines, and (3) formulating algorithms for task migration between heterogeneous machines, using task migration for fault tolerance or load re-balancing. Acknowledgment: This work was supported by the DARPA/ITO Quorum Program through the Office of Naval Research under Grant No. N00014-00-1-0599.References[1] T. D. Braun, H. J. Siegel, N. Beck, L. L. Boloni, M. Maheswaran, A. I. Reuther, J. P. Robertson, M. D. Theys, B. Yao, D. Hensgen, and R. F. Freund, A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems, Journal of Parallel and Distributed Computing, 61(6), 810-837, 2001.[2] M. M. Eshaghian (ed.), Heterogeneous Computing, Artech House, Norwood, MA, 1996.[3] I. Foster and C. Kesselman (eds.), The Grid: Blueprint for a New Computing Infrastructure, Morgan Kaufmann, San Francisco, CA, 1999.[4] R. F. Freund and H. J. Siegel (guest eds.), Special Issue on Heterogeneous Processing, IEEE Computer, 26(6), 1993.[5] N. H. Kapadia and J. A. B. Fortes, PUNCH: An Architecture for Web-Enabled Wide-Area Network-Computing, Cluster Computing: The Journal of Networks, Software Tools and Applications, Special Issue on High Performance Distributed Computing, 2(2), 153-164, 1999.[6] M. Maheswaran, S. Ali, H. J. Siegel, D. Hensgen, and R. F. Freund, Dynamic Mapping of a Class of Independent Tasks onto Heterogeneous Computing Systems, Journal of Parallel and Distributed Computing, Special Issue on Software Support for Distributed Computing, 59(2), 107-131, 1999.[7] M. Maheswaran, T. D. Braun, and H. J. Siegel, “Heterogeneous Distributed Computing,” in Encyclopedia of Electrical and Electronics Engineering, Vol. 8, J. G. Webster, ed., John Wiley, New York, NY, 1999, pp. 679-690. [8] M. D. Theys, T. D. Braun, Y.-K. Kwok, H. J. Siegel, and A. A. Maciejewski, “Mapping of Tasks onto Distributed Heterogeneous Computing Systems Using a Genetic Algorithm Approach,” in Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences, A. Y. Zomaya, ed., John Wiley & Sons, New York, NY, 2001, pp. 135-178.Cross Reference:Analytical Benchmarking see Heterogeneous Computing.Computational Grid see Heterogeneous Computing.Meta-Computer see Heterogeneous Computing.Meta-Task see Heterogeneous Computing.Task Profiling see Heterogeneous Computing.Dictionary Terms:Analytical BenchmarkingAnalytical benchmarking of a given computing machine provides a measure of performance of the machine on each of the different code types that may be present in a given source program. The performance of a particular code type on a specific kind of resource is a multi-variable function. Some of the variables of such a function may be: the quality of service requirements of the application program (e.g., data precision), the size of the data set to be processed, the algorithm to be applied, programmer and compiler efforts to optimize the program, and the operating system and architecture of the machine that will execute the specific code type. (See Heterogeneous Computing.) Computational GridA developing area of research and technology seeking to connect regional and national computational resources in a transparent fashion, thus transforming any computer connected to the grid into part of a new class of supercomputer. The implied analogy is with an electric power grid. If access to advanced computational capabilities and accessories became as ubiquitous and dependable as an electric power grid, the impact on society would be dramatic. (See Heterogeneous Computing.)Meta-ComputerA system framework that utilizes the resources of many different computers connected via a network to cooperate on solving a problem. In general, this allows the problem to be solved much more quickly than would be possible using a single computer. Meta-computers usually consist of heterogeneous, distributed elements, and operate in a coarse-grained fashion. A meta-computer would be a more localized component of a larger computational grid. (See Heterogeneous Computing.)QoSQoS (Quality of Service) is an aggregate function of many different system characteristics used to represent the overall performance of a system. The components in the function, and the computation of the function itself, vary widely (i.e., QoS means many different things to many different people). Sample components of a QoS measure could include task deadlines, data precision, image color range, video jitter, network bandwidth, bit error rate, and end-to-end latency. (See Heterogeneous Computing.)Task ProfilingTask profiling of a given source program specifies types of computations that are present in the source program by decomposing it into code blocks based on computational requirements of the blocks. The set of computation types defined depends on the architectural features of the machines available for executing the source program or its subprograms, and on both the application task code and the types and sizes of data sets it is to process. (See Heterogeneous Computing.)。

M e t a分析的思想及步骤Meta分析的前身源于Fisher1920年“合并P值”的思想,1955年由Beecher首次提出初步的概念,1976年心理学家Glass进一步按照其思想发展为“合并统计量”,称之为Meta分析;1979年英国临床流行病学家ArchieCochrane提出系统评价systematicreview,SR的概念,并发表了激素治疗早产孕妇降低新生儿死亡率随机对照试验的系统评价,对循证医学的发展起了举足轻重的作用;Meta分析国内翻译为“荟萃分析”,定义是“Thestatisticalanalysisoflargecollectionofanalysisresultsfromindividual studiesforthepurposeofintegratingthefindings.”亦即“对具备特定条件的、同课题的诸多研究结果进行综合的一类统计方法;”Meta从字源来说据考证有“Metalogic：abranchofanalyticphilosophythatdealswiththecriticalexaminationofthebasic conceptsoflogic”；“Metamathematics：thephilosophyofmathematics,especially,thelogicalsyntaxofmathematics.”其中最简洁并且一语中的的是Metascience:：atheoryorscienceofscience,atheoryconcernedwiththeinvestigationanalysisor descriptionoftheoryitself.”意为一种科学中的科学或理论,一种对原理本身进行调查、分析和描述的原理;Meta分析有广义和狭义两种概念：前者指的是一个科学的临床研究活动,指全面收集所有相关研究并逐个进行严格评价和分析,再用定量合成的方法对资料进行统计学处理得出综合结论的整个过程；后者仅仅是一种单纯的定量合成的统计学方法;目前国内外文献中以广义的概念应用更为普遍,系统评价常和Meta分析交叉使用,当系统评价采用了定量合成的方法对资料进行统计学处理时即称为Meta-分;因此,系统评价可以采用Meta-分析quantitativesystematicreview 定量系统评价,也可以不采用Meta-分析non-quantitativesystematicreview,定性系统评价;参照Cochrane协作网系统评价工作手册CochraneReviewers’Handbook制定的统一标准; Meta分析的基本步骤如下：1明确简洁地提出需要解决的问题;2制定检索策略,全面广泛地收集随机对照试验;3确定纳入和排除标准,剔除不符合要求的文献;4资料选择和提取;5各试验的质量评估和特征描述;6统计学处理;a．异质性检验齐性检验;b．统计合并效应量加权合并,计算效应尺度及95％的置信区间并进行统计推断; c．图示单个试验的结果和合并后的结果;d．敏感性分析;e．通过“失安全数”的计算或采用“倒漏斗图”了解潜在的发表偏倚;7结果解释、作出结论及评价;8维护和更新资料;临床医生只需要知道Meta分析的基本思想,具体的统计学方法让统计学家研究,让统计学软件帮我们完成;ReviewManagerRevMan是Cochrane协作网提供给评价者准备和维护更新Cochrane系统评价而设计的软件,也可以说是专门为临床医生度身订做,用于完成Meta分析的软件,它不仅可以协助我们完成Meta分析的计算过程,还可以帮助我们了解Meta分析的架构并学习系统评价的分析方法,最后把完成的系统评价制作成易于通过电子转换的文件以标准统一的格式发送到Cochrane系统评价资料库TheCochraneDatabaseofSystematicReviews,CDSR,便于电子出版和日后更新;充分利用RevMan软件对初次从事系统评价的人员获得方法学上的指导有很大的裨益;系统评价有多种类型,如病因研究、诊断性试验的评价、预后及流行病学研究等;Cochrane系统评价目前主要限于随机对照试验;非随机对照试验的系统评价方法学还处于不太完善的阶段,需要进行更多的相关研究;诊断试验的Meta分析方法与一般的随机对照试验Meta分析不同,需要同时考虑敏感性与特异性,采用综合接受者工作特征summaryreceiveroperatingcharacteristiccurve,SROC的分析,但RevMan4.2未提供Meta分析的完整步骤,根据个人的体会,结合战友的经验总结而成,meta的精髓就是对文献的二次加工和定量合成,所以这个总结也算是对战友经验的meta分析吧;一、选题和立题一形成需要解决的临床问题：系统评价可以解决下列临床问题:1.病因学和危险因素研究;2.治疗手段的有效性研究;3.诊断方法评价;4.预后估计;5.病人费用和效益分析等;进行系统评价的最初阶段就应对要解决的问题进行精确描述,包括人群类型疾病确切分型、分期、治疗手段或暴露因素的种类、预期结果等,合理选择进行评价的指标;二指标的选择直接影响文献检索的准确性和敏感性,关系到制定检索策略;三制定纳入排除标准;二、文献检索一检索策略的制定这是关键,要求查全和查准;推荐Mesh联合freeword检索;二文献检索,获取摘要和全文国内的有维普全文VIP,CNKI,万方数据库,外文的有medline,SD,OVID等;三文献管理强烈推荐使用endnote,procite,noteexpress等文献管理软件进行检索和管理文献;查找文献全文的途径：在这里,讲一下找文献的过程,以请后来的战友们参考不包括网上有电子全文的：1.查找免费全文：1在pubmedcenter中看有无免费全文;有的时候虽然没有显示freefulltext,但是点击进去看全文链接也有提供免费全文的;我就碰到几次;2在google中搜一下;少数情况下,NCBI没有提供全文的,google有可能会找到,使用“学术搜索”;本人虽然没能在google中找到一篇所需的文献,但发现了一篇非常重要的综述,里面包含了所有我需要的文献当然不是数据,但起码提供了一个信息,所需要的文献也就这么多了,因为老外的综述也只包含了这么多的内容;这样,到底找多少文献,找什么文献,心里就更有底了;3免费医学全文杂志网站;;提供很过超过收费期的免费全文;2.图书馆查馆藏目录：包括到本校的,当然方便,使用pubmed的linkout看文献收录的数据库,就知道本校的是否有全文;其它国内高校象复旦、北大、清华等医学院的全文数据库都很全,基本上都有权限;上海的就有华东地区联目、查国内各医学院校的图书馆联目;这里给出几个：1中国高等院校医药图书馆协会的地址：,进入左侧的“现刊联目”,可以看到有“现刊联目查询”和“过刊联目查询”,当然,查询结果不可全信,里面有许多错误;本人最难找的两篇文章全部给出了错误的信息后来电话联系证实的;2再给出两个比较好的图书馆索要文献的email地址有偿服务,但可以先提供文献,后汇钱,当然做为我们,一定要讲信誉吆;一是解放军医学图书馆信息部：,电话：；3二是复旦大学医科图书馆原上医：i,联系人,周月琴,王蔚之,郑荣,电话,,需下载文献传递申请表;其他的图书馆要么要求先交开户费,比如协和500元,要么嫌麻烦,虽然网上讲过可提供有偿服务,在这里我就不一一列出了;3.请DXY战友帮忙,在馆藏文献互助站中发帖,注意格式正确,最好提供linkout的多个数据库的全文链接,此时为帮助的人着想,就是帮助自己;自己也同时帮助别人查文献,一来互相帮助,我为人人,人人为我;二则通过帮助别人可以积分,同时学会如何发帖和下载全文,我就感觉通过帮助别人收获很大,自己积分越高,获助的速度和机会也就相应增加;现在不少免费的网络空间我常用爱存,比发邮件简便很多;所以如果你求助以后,要及时去“我的论坛”中查看帖子,有的很快就把下载链接发过来了,不要一味只看邮箱;4.实在不行,给作者发email;这里给出一个查作者email的方法,先在NCBI中查出原文献作者的所有文章,注意不要只限于第一作者,display,abstract,并尽可能显示多的篇数,100,200,500;然后在网页内查找“”,一般在前的字母会与人名有些地方相似;再根据地址来确定是否是同一作者;5.查找杂志的网址,给主编发信求取全文;这里我就不讲查找的方法了,DXY中有许多帖子;我的一篇全文就是这样得到的;6.向国外大学里的朋友求助;国外大学的图书馆一般会通过馆际互借来查找非馆藏文献,且获得率非常高;我的三篇文献是通过这一途径得到的;如果还是找不到,那就……我也没辙了,还有朋友如有其他的方法,不妨来这里交流;难度不小吧,比起做实验来如何三、对文献的质量评价和数据收集一研究的质量评价对某一试验研究的质量评价主要是评价试验结果是否有效,结果是什么该结果是否适用于当地人群;下面一系列问题可以帮助研究者进行系统的质量评价:①该研究的试验设计是否明确,包括研究人群、治疗手段和结果判定方法;②试验对象是否随机分组;③病人的随访率是否理想及每组病人是否经过统计分析;④受试对象、研究人员及其它研究参与者是否在研究过程中实行“盲法”;⑤各组病人的年龄、性别、职业等是否相似;⑥除进行研究的治疗手段不同外,其它的治疗是否一致;⑦治疗作用大小;⑧治疗效果的评价是否准确;⑨试验结果是否适用于当地的人群,种族差异是否影响试验结果;⑩是否描述了所有重要的治疗结果;治疗取得的效益是否超过了治疗的危险性和费用;系统评价者应根据上述标准进行判断,不满足标准的文献应剔除或区别对待数据合并方法不同,以保证系统评价的有效性;二、数据收集研究者应设计一个适合本研究的数据收集表格;许多电子表格制作软件如Excel、Access,和数据库系统软件如FoxPro等,可以用于表格的制作;表格中应包括分组情况、每组样本数和研究效应的测量指标;根据研究目的不同,测量指标可以是率差、比数odds、相对危险度relativerisk,包括RR和OR;各研究间作用测量指标不一致,需转化为统一指标;常用的统一指标是作用大小EffectSize,ES,ES是两比较组间作用差值除以对照组或合并组的标准差;ES无单位是其优点;三、数据分析系统评价过程中,对上述数据进行定量统计合并的流行病学方法称为Meta分析Metaanalysis;Meta意思是morecomprehensive,即更加全面综合;通过Meta分析可以达到以下目的:1.提高统计检验效能;2.评价结果一致性,解决单个研究间的矛盾;3.改进对作用效应的估计;4.解决以往单个研究未明确的新问题;统计分析的指标一、异质性检验1.检验原理：meta分析的原理首先是假定各个不同研究都是来自非同一个总体H0:各个不同样本来自不同总体,存在异质性,备择假设H1,如果p>0.1,拒绝H0,接受H1,,即来自同一总体这样就要求不同研究间的统计量应该接近总体参数真实值,所以各个不同文献研究结果是比较接近,就是要符合同质性,这时候将所有文献的效应值合并可以采用固定效应模型的有些算法,如倒方差法,mantelhaenszel法,peto法等.2.分类：异质性检验,包括三个方面：临床异质性,统计学异质性和方法学异质性,作meta分析首先应当保证临床同质性,比如研究的设计类型、实验目的、干预措施等相同,否则就要进入亚组分析,或者取消合并,在满足临床同质性的前提下非常重要,不能一味追求统计学同质性,首先考虑专业和临床同质性,我们进一步观测统计学同质性;临床异质性较大时不能行meta分析,随机效应模型也不行.只能行描述性系统综述systemicreviews,SR或分成亚组消除临床异质性.解决临床异质后再考虑统计学异质性的问题.如果各个文献研究间结果不存在异质性p>0.1,选用固定效应模型fixedmodel,这时其实选用随即效应模型的结果与固定效应模型相同；如果不符合同质性要求,即异质性检验有显着性意义p<0.1,这时候固定效应模型的算法来合并效应值就是有偏倚,合并效应值会偏离真实值.所以,异质性存在时候要求采用随机模型,主要是矫正合并效应值的算法,使得结果更加接近无偏估计,即结果更为准确.此外,这里要说明的是,采用的模型不同,和合并效应值的方法不同,都会导致异质性检验P值存在变动,这个可以从算法原理上证明,不过P值变动不会很大,一般在小数点后第三位的改变.异质性检验的Q值在固定模型中采用倒方差法和Mantel-haenszel法中也会不同;随机效应模型是不需要假定各个研究来自同一个总体为前提,本来就是对总体参数的近似无偏估计,这个与固定模型不一样必须要同质为基础,所以随机模型来作异质性检验简直是“画蛇添足”,无奈之举因此,随机模型异质性检验是否有统计学意义都是可以用,而固定模型必须要求无异质性;可以证明和实践,如果无异质性存在的时候,随机模型退化为固定,即固定模型的结果于随机模型的合并效应值是相等的具体见下图：目前,国内外对meta分析存在异质性,尤其是异质性检验P值很小的时候具体范围我不清楚,是0.05～0.1吗请版主补充,学术界有着不同的争论,很多人认为这个时候做meta分析是没有意义,相当于合并了一些来自不同总体的统计结果,也有人认为,这些异质性的存在可能是由于文献发表的时间,研究的分组,研究对象的特征等因素引起,只要采用亚组分析或meta回归分析可以将异质性进行控制或解释,还是可以进行meta分析,至少运用随机效应模型可以相对无偏的估计总体.这里要强调的是,异质性检验P值较小时候,最好能对异质性来源进行分析和说明;合理进行解释,同时进行亚组分析,相当于分层分析,消除混杂因素造成的偏倚bias;3.衡量异质性的指标一个有用的定量衡量异质性的指标是I2,I2=Q–df/Qx100%,此处的Q是卡方检验的统计值,df是其自由度Higgins2003,Higgins2002;这个I2值代表了由于异质性而不是抽样误差机会导致的效应占总效应估计值的百分率;I2值大于50％时,可以认为有明显的异质性;参考二、敏感性分析：1.敏感性分析的含义：改变纳入标准特别是尚有争议的研究、排除低质量的研究、采用不同统计方法/模型分析同一资料等,观察合并指标如OR,RR的变化,如果排除某篇文献对合并RR有明显影响,即认为该文献对合并RR敏感,反之则不敏感,如果文献之间来自同一总体,即不存在异质性,那么文献的敏感性就低,因而敏感性是衡量文献质量纳入和排除文献的证据和异质性的重要指标;敏感性分析主要针对研究特征或类型如方法学质量,通过排除某些低质量的研究、或非盲法研究探讨对总效应的影响;王吉耀第二版P76中“排除某些低质量的研究,再评价,然后前后对比,探讨剔除的试验与该类研究特征或类型对总效应的影响”;王家良第一版八年制P66、154敏感性分析是从文献的质量上来归类,亚组分析主要从文献里分组病例特征分类;敏感性分析是排除低质量研究后的meta分析,或者纳入排除研究后的meta分析;亚组分析是根据纳入研究的病人特点适当的进行分层,过多的分层和过少的分层都是不好的;例如在排除某个低质量研究后,重新估计合并效应量,并与未排除前的Meta分析结果进行比较,探讨该研究对合并效应量影响程度及结果稳健性;若排除后结果未发生大的变化,说明敏感性低,结果较为稳健可信；相反,若排除后得到差别较大甚至截然相反结论,说明敏感性较高,结果的稳健性较低,在解释结果和下结论的时候应非常慎重,提示存在与干预措施效果相关的、重要的、潜在的偏倚因素,需进一步明确争议的来源;2.衡量方法和措施其实常用的就是选择不同的统计模型或进行亚组分析,并探讨可能的偏倚来源,慎重下结论;亚组分析通常是指针对研究对象的某一特征如性别、年龄或疾病的亚型等进行的分析,以探讨这些因素对总效应的影响及影响程度;而敏感性分析主要针对研究特征或类型如方法学质量,通过排除某些低质量的研究、或非盲法的研究以探讨对总效应的影响;建议可以看参考王吉耀主编,科学出版社出版的循证医学与临床实践;敏感性分析只有纳入可能低质量文献时才作,请先保证纳入文献的质量纳入文献的质量评价方法,如果是RCT,可选用JADAD评分;如果病因学研究,我认为使用敏感性分析是评价文献质量前提是符合纳入标准的较为可行的方法;敏感性分析是分析异质性的一种间接方法;有些系统评价在进行异质性检验时发现没有异质性,这时还需不需要作敏感性分析我的看法是需要,因为我觉得异质性也是可以互相抵消的,有时候作出来没有异质性,但经过敏感性分析之后,结果就会有变化;三对入选文献进行偏倚估计发表偏倚publicationbias评估包括作漏斗图,和对漏斗图的对称性作检验;可以用stata软件进行egger检验;人是活的,软件是死的,临床是相对的,统计学是绝对的;四、总结：一结果的解释Meta-分析结果除要考虑是否有统计学意义外,还应结合专业知识判断结果有无临床意义;若结果仅有统计学意义,但合并效应量小于最小的有临床意义的差值时,结果不可取；若合并效应量有临床意义,但无统计学意义时,不能定论,需进一步收集资料;不能推荐没有Meta-分析证据支持的建议;在无肯定性结论时,应注意区别两种情况,是证据不充分而不能定论,还是有证据表明确实无效;二结果的推论Meta-分析的结果的外部真实性如何在推广应用时,应结合该Meta-分析的文献纳入/排除标准,考虑其样本的代表性如何,特别应注意研究对象特征及生物学或文化变异、研究场所、干预措施及研究对象的依从性、有无辅助治疗等方面是否与自己的具体条件一致;理想的Meta-分析应纳入当前所有相关的、高质量的同质研究,无发表性偏倚,并采用合适的模型和正确统计方法;三系统评价的完善与应用系统评价完成后,还需要在实际工作中不断完善,包括:①接受临床实践的检验和临床医师的评价;②接受成本效益评价;③关注新出现的临床研究,要及时对系统评价进行重新评价;临床医师只有掌握了系统评价的方法,才能为本专业的各种临床问题提供证据,循证医学才能够顺利发展;。

Unit 5Section ASoftware Design （软件设计）Design is defined in [IEEE610.12-90] as both “the process of defining the architecture,components, interfaces, and other characteristics of a system or component ” and “the result of that process.” Viewed as a process, software design is the software engineering life cycle activity in which software requirements are analyzed in order to produce a description of the software ’s internal structure that will serve as the basis for itsconstruction. More precisely, a software design (the result) must describe the software architecture -- that is how software is decomposed and organized into components -- and the interfaces between those components. It must also describe the components at a level of detail that enable their construction. Software design plays an important role indeveloping software: it allows software engineers to produce various models that form a kind of blueprint of the solution to be implemented. We can analyze and evaluate these models to determine whether or not they will allow us to fulfill the variousrequirements. We can also examine and evaluate various alternative solutions and trade-offs . Finally, we can use the resulting models to plan thesubsequent development activities, in addition to using them as input and the starting point of construction and testing.In a standard listing of software life cycleprocessed such as IEEE/EIA 12207 Software Life Cycle Processes [IEEE 12207.0-96], software design consists of two activities that fit between software requirements analysis and software construction:Software architectural design (sometimes called top level design): describing software ’s top-level structure and organization and identifying the various components.Software detailed design: describing eachcomponent sufficiently to allow for its construction.General StrategiesSoftware often-cited examples of general strategies useful in the design process aredivide-and-conquer and stepwise refinement,top-down vs. bottom-up strategies, data abstraction and information hiding, use of heuristics, use of patterns and pattern languages, use of an iterative and incremental approach.Function-Oriented (Structured) DesignThis is one of the classical methods of software design, where decomposition centers on identifying the major software functions and then elaborating and refining them in a top-down manner. Structured design is generally used after structured analysis, thus producing, among other things, data flow diagrams and associated process descriptions. Researchers have proposed various strategies (for example, transformation analysis, transaction analysis) and heuristics (for example, fan-in/fan-out, scope of effect vs. scope of control) to transform a DFD into a software architecture generally represented as a structure chart.Object-Oriented DesignNumerous software design methods based on objects have been proposed. The field has evolved from the early object-based design of the mid-1980s (noun=object; verb=method; adjective=attribute) through OO design, where inheritance and polymorphism play a key role, to the field of component-based design, where meta-information can be defined and accessed (through reflection, for example). Although OO design’s roots stem fromthe concept of data abstraction, responsibility-driven design has also been proposed as an alternative approach to OO design.Data-Structure-Centered DesignData-structure-centered design (for example, Jackson, Warnier-Orr) starts from the data structures a program manipulates rather than from the function it performs. The software engineer first describes the input and output data structures (using Jackson’s structure diagrams, for instance) andthen develops the program ’s control structure based on these data structure diagrams. Various heuristics have been proposed to deal with special cases -- for example, when there is a mismatch between the input and output structures.Component-Based Design (CBD)A software component is an independent unit, having well-defined interfaces and dependencies that can be composed and deployed independently, Component-based design addresses issues related to providing, developing, and integrating such components in order to improve reuse .Other MethodsOther interesting but less mainstreamapproaches also exist: formal and rigorous methodand transformational methods.。