简介:ThehistoryofClassicalscholarshipcansometimesproviderevealinginsightsintomoregeneralintellectualtrends.Dilletan(?)ism,whichwasnotthenanoffence,wasinfashioninBritaininthenineteenthcentury,andyoungmenofaristocraticbackgroundswhoaspiredtopubliccareersregularlycompletedtheirsometimeslengthyeducationbyexperiencingatfirsthandtheremnantsofthecivilizationswhoseassumedvaluesprovidedtheirownclasswithitsmodelsandpatternsofexcellence,Incompleting
简介:TopologicalrelationshipsbetweentwospatialfeaturesrepresentimportantknowledgeinGeographicalInformationSystems(GIS).Inthelastfewyears,manymodelsthatrepresenttopologicalrelationshipshavebeenproposed.Butthesemodelscannotrepresentthetopologicalrelationshipsbetweenheterogeneousgeometrycollectionfeatures,whicharecomposedofdifferentdimensionalgeometries.Inthispaper,theformaldefinitionofregularheterogeneousgeometrycollectionandregularizationrulesaregiven.Basedonthespatialmodel,twomethodsforrepresentingtopologicalrelationshipsbetweenthesecomplexfeaturesareproposed.ThefirstmethodisDimensionallyExtendedNine-IntersectionModelBasedonComponents(DE-9IMBC)thatextendsDimensionallyExtendedNine-IntersectionModel(DE-9IM)andtakesintoaccountthetopologicalrelationshipsbetweencomponentsofthesecomplexfeatures.TheadvantageofDE-9IMBCisthatalargenumberofdifferenttopologicalrelationshipscanbechecked.ThesecondmethodextendsthedefinitionsoftopologicalrelationshipsinOpenGeodataInteroperabilitySpecification(OpenGIS),andredefinesthesevennamedtopologicalrelationships:{Disjoint,Touches,Within,Crosses,Overlaps,ContainsandEqual},torepresentthetopologicalrelationshipsbetweenheterogeneousgeometrycollectionfeatures.Itisproventhatthesevenextendedtopologicalrelationshipsarecompleteandmutuallyexclusive,andtheyaresuitableforbeingembeddedinspatialquerylanguages.
简介:摘要:在实施房屋建设项目时,多种风险和不确定因素层出不穷,如果管理不佳,可能导致项目推迟、超越预算,引发一系列负面影响。本文以识别和应对房建项目中的风险为中心,进行深入探讨。全方位识别房建项目的各项风险,包括设计、施工、合同、环境等各个环节的风险,并适当设置风险识别指标体系。通过结合定性和定量的分析手段,对众多风险因素进行影响度评估,为风险应对提供数值参考。根据风险识别和影响评估的结果,提供了一整套风险应对措施,涉及到优化设计、规范施工、强化合同管理以及环境保护等方面,意在减少风险对房屋建设项目带来的潜在损失。通过案例分析验证了风险管理策略的实际效果。研究结果对于指导房建项目的风险管理具有重要参考价值。
简介:AbstractPurpose:Various organizations and institutions are involved in road traffic injury (RTI) and crash registration such as police, forensic medicine organization, hospitals and emergency medical services. But there is a substantial uncertainty in interpreting the data, duplicated data collection and missing data in relation to RTI in most systems. This study aims to identify data sources for RTI surveillance in Iran and to explore traffic safety data source domains, data elements and detailed information by each data source.Methods:This is a qualitative study which was conducted in 2017 in Iran. Data were collected employing semi-structured interviews with informants in road safety organizations in relation to traffic safety including Police, Ministry of Health and Medical Education as well as Forensic Medicine Organization and other authorities-in-charge. For completing the preliminary extraction information, the minimum data set was used and compared in each system.Results:Eight different organizations relevant to road traffic safety were identified. The main domain of data provided by each one consists of Emergency Medical System form, Police KAM114 form, Ministry of Transport and Road Administration, Red Crescent Organization/Disaster Management Information System, Ministry of Health and Medical Education, Forensic Medicine Organization, Insurance Company and Ministry of Justice. Each system has its own database, based upon its scope and mainly at crash and post-crash status and little on pre-crash circumstance.Conclusion:All current registry systems are not surveillance systems for RTI prevention. Huge data have been collected in various registry systems in Iran, but most of the collected variables are duplicated in each system. On the other hand, some variables like alcohol and substance abuse, child seat belt, helmet use in relation to RTI prevention are missed in all systems. Accordingly, it is a critical need to integrate and establish a comprehensive surveillance system, with focus on the goal of each system and collection of minimum data in each organization, which currently is underway.