还在苦恼三段距离保护的S函数编写吗……代码内容包括实现距离保护中的相间短路、两相接地短路和三相短路……以及三段式保护。
具体参数需要自己去设置，如果运行时间过长，把运行模式改为离散模式。

4款社工库源码带有部分数据

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