思科最新路由器IOSv镜像，可用于GNS3。
注意，此文件是使用qcow2转换而来，md5值与cisco-iosv这个appliance不符。

实现了服务端与客户端的连接，可以互相进行通信，资源是实验报告，里面含有源代码

小米笔记本一代6200uhd520完成mojave：config.plist.zip1、修复电源驱动，可以睡眠、休眠2、修复hdmi热插拔，休眠后识别3、不需要第三方工具，声卡、耳机插口自动识别4、修复关机5、修复cpu变频

过期域名抢注查询工具软件一款非常不错的查询工具.测试无毒.支持目前很多主流域名后缀.是米农必备的工具.....................................................................................................................................................

最新自动发卡源码全开源自动发货对接免签约即时到帐接口带3套模板。
对接吗支付，易支付等多种支付接口，安装简单带教程，演示网址：http://www.sck56.cn/forum.php?mod=forumdisplay&fid=51

用于excel计算MD5码可以计算32位、16位的方便批量制作MD5

ProbabilisticFoundationsofStatisticalNetworkAnalysispresentsafreshandinsightfulperspectiveonthefundamentaltenetsandmajorchallengesofmodernnetworkanalysis.Itslucidexpositionprovidesnecessarybackgroundforunderstandingtheessentialideasbehindexchangeableanddynamicnetworkmodels,networksampling,andnetworkstatisticssuchassparsityandpowerlaw,allofwhichplayacentralroleincontemporarydatascienceandmachinelearningapplications.Thebookrewardsreaderswithaclearandintuitiveunderstandingofthesubtleinterplaybetweenbasicprinciplesofstatisticalinference,empiricalpropertiesofnetworkdata,andtechnicalconceptsfromprobabilitytheory.Itsmathematicallyrigorous,yetnon-technical,expositionmakesthebookaccessibletoprofessionaldatascientists,statisticians,andcomputerscientistsaswellaspractitionersandresearchersinsubstantivefields.Newcomersandnon-quantitativeresearcherswillfinditsconceptualapproachinvaluablefordevelopingintuitionabouttechnicalideasfromstatisticsandprobability,whileexpertsandgraduatestudentswillfindthebookahandyreferenceforawiderangeofnewtopics,includingedgeexchangeability,relativeexchangeability,graphonandgraphexmodels,andgraph-valuedLevyprocessandrewiringmodelsfordynamicnetworks.Theauthor’sincisivecommentarysupplementsthesecoreconcepts,challengingthereadertopushbeyondthecurrentlimitationsofthisemergingdiscipline.Withanapproachableexpositionandmorethan50openresearchproblemsandexerciseswithsolutions,thisbookisidealforadvancedundergraduateandgraduatestudentsinterestedinmodernnetworkanalysis,datascience,machinelearning,andstatistics.HarryCraneisAssociateProfessorandCo-DirectoroftheGraduatePrograminStatisticsandBiostatisticsandanAssociateMemberoftheGraduateFacultyinPhilosophyatRutgersUniversity.ProfessorCrane’sresea

ProbabilisticFoundationsofStatisticalNetworkAnalysispresentsafreshandinsightfulperspectiveonthefundamentaltenetsandmajorchallengesofmodernnetworkanalysis.Itslucidexpositionprovidesnecessarybackgroundforunderstandingtheessentialideasbehindexchangeableanddynamicnetworkmodels,networksampling,andnetworkstatisticssuchassparsityandpowerlaw,allofwhichplayacentralroleincontemporarydatascienceandmachinelearningapplications.Thebookrewardsreaderswithaclearandintuitiveunderstandingofthesubtleinterplaybetweenbasicprinciplesofstatisticalinference,empiricalpropertiesofnetworkdata,andtechnicalconceptsfromprobabilitytheory.Itsmathematicallyrigorous,yetnon-technical,expositionmakesthebookaccessibletoprofessionaldatascientists,statisticians,andcomputerscientistsaswellaspractitionersandresearchersinsubstantivefields.Newcomersandnon-quantitativeresearcherswillfinditsconceptualapproachinvaluablefordevelopingintuitionabouttechnicalideasfromstatisticsandprobability,whileexpertsandgraduatestudentswillfindthebookahandyreferenceforawiderangeofnewtopics,includingedgeexchangeability,relativeexchangeability,graphonandgraphexmodels,andgraph-valuedLevyprocessandrewiringmodelsfordynamicnetworks.Theauthor’sincisivecommentarysupplementsthesecoreconcepts,challengingthereadertopushbeyondthecurrentlimitationsofthisemergingdiscipline.Withanapproachableexpositionandmorethan50openresearchproblemsandexerciseswithsolutions,thisbookisidealforadvancedundergraduateandgraduatestudentsinterestedinmodernnetworkanalysis,datascience,machinelearning,andstatistics.HarryCraneisAssociateProfessorandCo-DirectoroftheGraduatePrograminStatisticsandBiostatisticsandanAssociateMemberoftheGraduateFacultyinPhilosophyatRutgersUniversity.ProfessorCrane’sresea

ProbabilisticFoundationsofStatisticalNetworkAnalysispresentsafreshandinsightfulperspectiveonthefundamentaltenetsandmajorchallengesofmodernnetworkanalysis.Itslucidexpositionprovidesnecessarybackgroundforunderstandingtheessentialideasbehindexchangeableanddynamicnetworkmodels,networksampling,andnetworkstatisticssuchassparsityandpowerlaw,allofwhichplayacentralroleincontemporarydatascienceandmachinelearningapplications.Thebookrewardsreaderswithaclearandintuitiveunderstandingofthesubtleinterplaybetweenbasicprinciplesofstatisticalinference,empiricalpropertiesofnetworkdata,andtechnicalconceptsfromprobabilitytheory.Itsmathematicallyrigorous,yetnon-technical,expositionmakesthebookaccessibletoprofessionaldatascientists,statisticians,andcomputerscientistsaswellaspractitionersandresearchersinsubstantivefields.Newcomersandnon-quantitativeresearcherswillfinditsconceptualapproachinvaluablefordevelopingintuitionabouttechnicalideasfromstatisticsandprobability,whileexpertsandgraduatestudentswillfindthebookahandyreferenceforawiderangeofnewtopics,includingedgeexchangeability,relativeexchangeability,graphonandgraphexmodels,andgraph-valuedLevyprocessandrewiringmodelsfordynamicnetworks.Theauthor’sincisivecommentarysupplementsthesecoreconcepts,challengingthereadertopushbeyondthecurrentlimitationsofthisemergingdiscipline.Withanapproachableexpositionandmorethan50openresearchproblemsandexerciseswithsolutions,thisbookisidealforadvancedundergraduateandgraduatestudentsinterestedinmodernnetworkanalysis,datascience,machinelearning,andstatistics.HarryCraneisAssociateProfessorandCo-DirectoroftheGraduatePrograminStatisticsandBiostatisticsandanAssociateMemberoftheGraduateFacultyinPhilosophyatRutgersUniversity.ProfessorCrane’sresea

“消防”即是消除隐患，预防灾患（即预防和解决人们在生活、工作、学习过程中遇到的人为与自然、偶然灾害的总称），当然狭义的意思在人们认识初期是：（扑灭）火灾的意思。
Firecontrol;Firefighting;Fireprotection灭火与防火。
亦指灭火、防火人员。
郭孝成《浙江光复记》：“卫队及巡警消防，见势已烈，均袖缀白布，以表输诚。
”如：必须抓好消防工作。
例如：消防车、消防技术。
中国已有两千多年的消防历史，“消防”一词是二十世纪从日本引进的，是一个外来语。
但“消防”的根在中国。
日本的文字是从中国的汉字演变而来，汉字早在西晋太康五年（284年）就开始传入日本。
“消防”一词不仅字形与汉字完全相同，字义也无差别。
现代意义的消防可以更深层的理解为消除危险和防止灾难。