Statistical Analysis of DNS Latencies.pdf
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Short lightning talk on measuring and comparing DNS latency.
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Know Your Data: The stats behind your alerts
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Abstract: Quick, what's the difference between the mean, the mode and the median? Which mean do you mean? Do you need a Gaussian or a normal distribution And does your choice impact the alerts and observations you get from your observability tools?
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Instagram: https://www.instagram.com/allthingsopen/
Facebook: https://www.facebook.com/AllThingsOpen
Mastodon: https://mastodon.social/@allthingsopen
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2023 conference: https://2023.allthingsopen.org/
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Recommended
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Presented at All Things Open 2023
Presented by Dave McAllister - nginx
Title: Know Your Data: The stats behind your alerts
Abstract: Quick, what's the difference between the mean, the mode and the median? Which mean do you mean? Do you need a Gaussian or a normal distribution And does your choice impact the alerts and observations you get from your observability tools?
Come get refreshed on the impact some basic choices in statistical behavior can have on what gets triggered. Learn why a median might be the choice for historical anomaly or sudden change. Jump into Gaussian distributions, data alignment challenges and the trouble with sampling. Walk out with a deeper understanding of your metrics and what they might be telling you.
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On the web: https://www.allthingsopen.org/
Twitter: https://twitter.com/AllThingsOpen
LinkedIn: https://www.linkedin.com/company/all-things-open/
Instagram: https://www.instagram.com/allthingsopen/
Facebook: https://www.facebook.com/AllThingsOpen
Mastodon: https://mastodon.social/@allthingsopen
Threads: https://www.threads.net/@allthingsopen
2023 conference: https://2023.allthingsopen.org/
OSMC 2023 | Know your data: The stats behind your alerts by Dave McAllister
Quick, what’s the difference between the mean, the mode and the median? Do you need a Gaussian or a normal distribution And does your choice impact the alerts and observations you get from your observability tools?
Come get refreshed on the impact some basic choices in statistical behavior can have on what gets triggered. Learn why a median might be the choice for historical anomaly or sudden change. Jump into Gaussian distributions, data alignment challenges, and the trouble with sampling. Walk out with a deeper understanding of your metrics and what they might tell you.
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Once you have started learning about predictive algorithms, and the basic knowledge discovery in databases process, what is the next level of detail to learn for a consulting project?
* Give examples of the many model training parameters
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* Use a model metric that combines both accuracy and generalization to rank models
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* One way to describe an arbitrarily complex predictive system is by using sensitivity analysis
Everybody Lies
Hardware fails, applications fail, our code... well, it fails too (at least mine). To prevent software failure we test. Hardware failures are inevitable, so we write code that tolerates them, then we test. From tests we gather metrics and act upon them by improving parts that perform inadequately. Measuring right things at right places in an application is as much about good engineering practices and maintaining SLAs as it is about end user experience and may differentiate successful product from a failure.
In order to act on performance metrics such as max latency and consistent response times we need to know their accurate value. The problem with such metrics is that when using popular tools we get results that are not only inaccurate but also too optimistic.
During my presentation I will simulate services that require monitoring and show how gathered metrics differ from real numbers. All this while using what currently seems to be most popular metric pipeline - Graphite together with metrics.dropwizard.io library - and get completely false results. We will learn to tune it and get much better accuracy. We will use JMeter to measure latency and observe how falsely reassuring the results are. Finally I will show how HdrHistogram helps in gathering reliable metrics. We will also run tests measuring performance of different metric classes.
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Bridging the Gap: Machine Learning for Ubiquitous Computing -- Evaluation
Tutorial @Ubicomp 2015: Bridging the Gap -- Machine Learning for Ubiquitous Computing (evaluation session).
A tutorial on promises and pitfalls of Machine Learning for Ubicomp (and Human Computer Interaction). From Practitioners for Practitioners.
Presenter: Nils Hammerla <n.hammerla@gmail.com>
video recording of talks as they wer held at Ubicomp:
https://youtu.be/LgnnlqOIXJc?list=PLh96aGaacSgXw0MyktFqmgijLHN-aQvdq
Learning to Search Henry Kautz
The document discusses research on learning to improve the efficiency of machine learning algorithms through speedup learning. It provides three key points:
1) Early work on explanation-based learning for speedup had limited success, but techniques like memoization and clause learning led to major improvements in SAT solvers.
2) More recent approaches use machine learning to build predictive models of problem instances and solver behavior, in order to inform strategies like automatic noise setting and randomized restart policies.
3) Case studies demonstrate these learning-based approaches can outperform traditional techniques and fixed policies by customizing resource allocation and reformulation based on problem structure and solver progress.
Learning to Search Henry Kautz
The document discusses research on learning to improve the efficiency of machine learning algorithms through speedup learning. It provides three key points:
1) Early work on explanation-based learning for speedup had limited success, but techniques like memoization and clause learning led to major improvements in SAT solvers.
2) More recent approaches use predictive models trained on dynamic features to learn optimal policies for controlling search algorithms, like setting noise levels or restart policies.
3) Open problems remain in developing optimal predictive policies with partial information and approximations, to continue improving search and reasoning performance.
(BDT207) Real-Time Analytics In Service Of Self-Healing Ecosystems
Netflix strives to provide an amazing experience to each member. To accomplish this, Netflix needs to maintain very high availability across our systems. However, at a certain scale, humans can no longer scale their ability to monitor the status of all systems, making it critical for Netflix to build tools and platforms that can automatically monitor their production environments and make intelligent real-time operational decisions to remedy the problems they identify. In this session, we discuss how Netflix uses data mining and machine learning techniques to automate decisions in real-time with the goal of supporting operational availability, reliability, and consistency. We review how we got to the current states, the lessons we learned, and the future of real-time analytics at Netflix. While Netflix's scale is larger than most other companies, we believe the approaches and technologies we discuss are highly relevant to other production environments, and audience members should come away with actionable ideas that are implementable in, and benefit, most other environments.
Decision Forests and discriminant analysis
This document summarizes a tutorial on randomised decision forests and tree-structured algorithms. It discusses how tree-based algorithms like boosting and random forests can be used for tasks like object detection, tracking and segmentation. It also describes techniques for speeding up computation, such as converting boosted classifiers to decision trees and using multiple classifier systems. The tutorial is structured in two parts, covering tree-structured algorithms and randomised forests.
Real World Performance - OLTP
This document discusses various topics related to optimizing OLTP performance in Oracle databases, including:
1) Database performance principles such as acceptable CPU utilization levels and how user response times are affected by utilization levels above 60-65%.
2) Different connection architectures including dedicated servers, shared servers, and database resident connection pooling and their tradeoffs in terms of connection speed and code path length.
3) The importance of writing efficient SQL statements and maintaining proper schema statistics to enable the database to choose efficient execution plans.
4) Best practices for SQL optimization such as validating join conditions, indexes, partition pruning strategies, and parallelization levels are emphasized.
Parallel DNA Sequence Alignment
The document describes several parallel approaches for speeding up sequence alignment. It discusses splitting a DNA string into chunks that are distributed to worker nodes. Various techniques are proposed for handling matches that span multiple chunks, including using bigger chunks, on-demand requests for additional data, and having workers find partial matches along chunk edges to be combined by the master. The approaches are analyzed in terms of advantages and disadvantages, and a test plan is outlined to evaluate performance under varying parameters like number of workers and query length.
System and User Aspects of Web Search Latency
This document discusses factors that influence web search latency from both the user and system perspectives. It summarizes that users expect fast response times from search engines, while search engines aim to balance speed, quality, and costs. The document then outlines components that contribute to latency, experiments measuring user sensitivity to latency, and the impact of latency on user search experience. Specifically, it finds users notice delays over 1000ms and that faster search sites lead to higher user engagement.
Beyond Averages - Web Performance Meetup
When raw data becomes overwhelming, we turn to abstraction to understand our world. In examining the performance of our systems, the data is always overwhelming. Solutions like summary statistics have come to our rescue, and they are good—up to a point. In order to truly understand our systems, we need to know when and how to sidestep those abstractions,to get deep, detailed performance insight. At this meetup, I’ll explore techniques for visualizing the underlying structure of performance data and how this empowers drilling down to populations and individual samples in the data set.
Towards Detecting Performance Anti-patterns Using Classification Techniques
This is the talk I gave on behalf of my Ph.D. student at the Machine Learning and Information Retrieval (MALIR) for Software Evolution (MALIR-SE) workshop at ASE 2013.
Splunk Enterprise for Information Security Hands-On Breakout Session
The document provides information about detecting various types of cyber attacks using Splunk, including web attacks, lateral movement, and DNS exfiltration. It includes examples of search queries and apps that can be used in Splunk to detect SQL injection, pass-the-hash attacks, and DNS tunneling used for data exfiltration. The document demonstrates how machine data from different sources can be analyzed in Splunk to gain visibility into attack behaviors and detect security incidents.
Similar to Statistical Analysis of DNS Latencies.pdf (20)
Finding Bugs Faster with Assertion Based Verification (ABV)
Finding Bugs Faster with Assertion Based Verification (ABV)
Performance Issue? Machine Learning to the rescue!
Performance Issue? Machine Learning to the rescue!
Sean Kandel - Data profiling: Assessing the overall content and quality of a ...
Sean Kandel - Data profiling: Assessing the overall content and quality of a ...
Bridging the Gap: Machine Learning for Ubiquitous Computing -- Evaluation
Bridging the Gap: Machine Learning for Ubiquitous Computing -- Evaluation
(BDT207) Real-Time Analytics In Service Of Self-Healing Ecosystems
(BDT207) Real-Time Analytics In Service Of Self-Healing Ecosystems
Towards Detecting Performance Anti-patterns Using Classification Techniques
Towards Detecting Performance Anti-patterns Using Classification Techniques
Splunk Enterprise for Information Security Hands-On Breakout Session
Splunk Enterprise for Information Security Hands-On Breakout Session
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【主营项目】
一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
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三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
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1、在校期间，因各种原因未能顺利毕业，拿不到官方毕业证+微信95270640
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3、不清楚流程以及材料该如何准备悉尼大学悉尼大学毕业证offer；
4、回国时间很长，忘记办理；
5、回国马上就要找工作，办给用人单位看；
6、企事业单位必须要求办理的；
面向美国乔治城大学毕业留学生提供以下服务:
【★悉尼大学悉尼大学毕业证offer毕业证、成绩单等全套材料，从防伪到印刷，从水印到钢印烫金，与学校100%相同】
【★真实使馆认证（留学人员回国证明），使馆存档可通过大使馆查询确认】
【★真实教育部认证，教育部存档，教育部留服网站可查】
【★真实留信认证，留信网入库存档，可查悉尼大学悉尼大学毕业证offer】
我们从事工作十余年的有着丰富经验的业务顾问，熟悉海外各国大学的学制及教育体系，并且以挂科生解决毕业材料不全问题为基础，为客户量身定制1对1方案，未能毕业的回国留学生成功搭建回国顺利发展所需的桥梁。我们一直努力以高品质的教育为起点，以诚信、专业、高效、创新作为一切的行动宗旨，始终把“诚信为主、质量为本、客户第一”作为我们全部工作的出发点和归宿点。同时为海内外留学生提供大学毕业证购买、补办成绩单及各类分数修改等服务；归国认证方面，提供《留信网入库》申请、《国外学历学位认证》申请以及真实学籍办理等服务，帮助众多莘莘学子实现了一个又一个梦想。
专业服务，请勿犹豫联系我
如果您真实毕业回国，对于学历认证无从下手，请联系我，我们免费帮您递交
诚招代理：本公司诚聘当地代理人员，如果你有业余时间，或者你有同学朋友需要，有兴趣就请联系我
你赢我赢，共创双赢
你做代理，可以帮助悉尼大学同学朋友
你做代理，可以拯救悉尼大学失足青年
你做代理，可以挽救悉尼大学一个个人才
你做代理，你将是别人人生悉尼大学的转折点
你做代理，可以改变自己，改变他人，给他人和自己一个机会过暑假的小学生快乐的日子总是过得飞快山娃尚未完全认清那几位小朋友时他们却一个接一个地回家了山娃这时才恍然发现二个月的暑假已转到了尽头他的城市生活也将划上一个不很圆满的句号了值得庆幸的是山娃早记下了他们的学校和联系方式说也奇怪在山娃离城的头一天父亲居然请假陪山娃耍了一天那一天父亲陪着山娃辗转长隆水上乐园疯了一整天水上漂流高空冲浪看大马戏大凡里面有的父亲都带着他去疯一把山娃算了算这一次足足花了老爸元很
办理新西兰奥克兰大学毕业证学位证书范本原版一模一样
原版一模一样【微信：741003700 】【新西兰奥克兰大学毕业证学位证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
可查真实(Monash毕业证)西澳大学毕业证成绩单退学买
办理假西澳大学毕业证【微信176555708】购买,办理Monash成绩单,Monash毕业证制作【微信176555708】【西澳大学毕业证】，Monash毕业证购买，Monash学位证，西澳大学学位证【Monash成绩单制作】【Monash毕业证文凭 Monash本科 澳洲学历认证原版制作【diploma certificate degree transcript 】【留信网认证，本科，硕士，海归，博士，排名，成绩单】代办国外（海外）澳洲、韩国、加拿大、新西兰等各大学毕业证。 ?我们对海外大学及学院的毕业证成绩单所使用的材料，尺寸大小，防伪结构（包括：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。 文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）都有原版本文凭对照。#一整套西澳大学文凭证件办理#—包含西澳大学西澳大学毕业证成绩单学历认证|使馆认证|归国人员证明|教育部认证|留信网认证永远存档教育部学历学位认证查询办理国外文凭国外学历学位认证#我们提供全套办理服务。
一整套留学文凭证件服务：
一：西澳大学西澳大学毕业证成绩单毕业证 #成绩单等全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站永久可查
四：留信认证留学生信息网站永久可查
国外毕业证学位证成绩单办理方法：
1客户提供办理西澳大学西澳大学毕业证成绩单信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
教育部文凭学历认证认证的用途：
如果您计划在国内发展那么办理国内教育部认证是必不可少的。事业性用人单位如银行国企公务员在您应聘时都会需要您提供这个认证。其他私营 #外企企业无需提供！办理教育部认证所需资料众多且烦琐所有材料您都必须提供原件我们凭借丰富的经验帮您快速整合材料让您少走弯路。
实体公司专业为您服务如有需要请联系我: 微信176555708
Gen Z and the marketplaces - let's translate their needs
The product workshop focused on exploring the requirements of Generation Z in relation to marketplace dynamics. We delved into their specific needs, examined the specifics in their shopping preferences, and analyzed their preferred methods for accessing information and making purchases within a marketplace. Through the study of real-life cases , we tried to gain valuable insights into enhancing the marketplace experience for Generation Z.
The workshop was held on the DMA Conference in Vienna June 2024.
成绩单ps(UST毕业证)圣托马斯大学毕业证成绩单快速办理
一比一原版制作UST毕业证【微信176555708】圣托马斯大学毕业证书原版↑制作圣托马斯大学学历认证文凭办理圣托马斯大学留信网认证,留学回国办理毕业证成绩单文凭学历认证【微信176555708】专业为海外学子办理毕业证成绩单、文凭制作，学历仿制，回国人员证明、做文凭，研究生、本科、硕士学历认证、留信认证、结业证、学位证书样本、美国教育部认证百分百真实存档可查】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
◆◆◆◆◆ — — — — — — — — 【留学教育】留学归国服务中心 — — — — — -◆◆◆◆◆
【主营项目】
一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
学历顾问：微信：176555708
Should Repositories Participate in the Fediverse?
Presentation for OR2024 making the case that repositories could play a part in the "fediverse" of distributed social applications
Search Result Showing My Post is Now Buried
Search results burying my post that used to rank before Google's March 2024 algorithm update.
Ready to Unlock the Power of Blockchain!
Imagine a world where data flows freely, yet remains secure. A world where trust is built into the fabric of every transaction. This is the promise of blockchain, a revolutionary technology poised to reshape our digital landscape.
Toptal Tech is at the forefront of this innovation, connecting you with the brightest minds in blockchain development. Together, we can unlock the potential of this transformative technology, building a future of transparency, security, and endless possibilities.
不能毕业如何获得(USYD毕业证)悉尼大学毕业证成绩单一比一原版制作
挂科购买☀【悉尼大学毕业证购买】【微信176555708】【USYD毕业证模板办理】加拿大文凭、本科、硕士、研究生学历都可以做,二、业务范围：
★、全套服务：毕业证、成绩单、化学专业毕业证书伪造【悉尼大学大学毕业证】微信176555708【USYD学位证书购买】◆◆◆◆◆ — — — 归国服务中心 — — -◆◆◆◆◆
【主营项目】
一.毕业证、成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
国外毕业证、学位证、成绩单办理流程：
1、客户提供办理信息：姓名、生日、专业、学位、毕业时间等（如信息不确定可以咨询顾问：【微信176555708】我们有专业老师帮你查询）；
2、开始安排制作毕业证、成绩单电子图；
3、毕业证、成绩单电子版做好以后发送给您确认；
4、毕业证、成绩单电子版您确认信息无误之后安排制作成品；
5、成品做好拍照或者视频给您确认；
6、快递给客户（国内顺丰，国外DHL、UPS等快读邮寄）。
专业服务，请勿犹豫联系我！本公司是留学创业和海归创业者们的桥梁。一次办理，终生受用，一步到位，高效服务。详情请在线咨询办理,欢迎有诚意办理的客户咨询!洽谈。
◆招聘代理：本公司诚聘英国、加拿大、澳洲、新西兰、加拿大、法国、德国、新加坡各地代理人员，如果你有业余时间，有兴趣就请联系我们咨询【微信176555708】
没文凭怎么找工作。让您回国发展信心十足！
★、真实教育部学历学位认证；（一对一专业服务，可全程监控跟踪进度）
★、真实使馆认证，可以通过大使馆查询确认；（即教育部留服认证，不成功不收费）
★、毕业证、成绩单等材料，从防伪到印刷、水印到钢印烫金，高精仿度都是跟学校原版100%相同的；（敬请放心使用）
★、可以提供钢印、水印、烫金、激光防伪、凹凸版、最新版的毕业证、百分之百让您绝对满意、
★、印刷，DHL快递毕业证、成绩单7个工作日，真实大使馆教育部认证1个月。为了达到高水准高效率。
重新申请毕业证书(RMIT毕业证)皇家墨尔本理工大学毕业证成绩单精仿办理
不能毕业办理【RMIT毕业证【微信176555708】皇家墨尔本理工大学文凭学历】【微信176555708】【皇家墨尔本理工大学文凭学历证书】【皇家墨尔本理工大学毕业证书与成绩单样本图片】毕业证书补办 Fake Degree做学费单【毕业证明信-推荐信】成绩单，录取通知书，Offer，在读证明，雅思托福成绩单，真实大使馆教育部认证，回国人员证明，留信网认证。网上存档永久可查！全套服务：皇家墨尔本理工大学皇家墨尔本理工大学本科学位证成绩单真实回国人员证明 #真实教育部认证。让您回国发展信心十足#铸就十年品质！信誉！实体公司！可以视频看办公环境样板如需办理真实可查可以先到公司面谈勿轻信小中介黑作坊！
可以提供皇家墨尔本理工大学钢印 #水印 #烫金 #激光防伪 #凹凸版 #最新版的毕业证 #百分之百让您绝对满意
印刷DHL快递毕业证 #成绩单7个工作日真实大使馆教育部认证1个月。为了达到高水准高效率
请您先以qq或微信的方式对我们的服务进行了解后如果有皇家墨尔本理工大学皇家墨尔本理工大学本科学位证成绩单帮助再进行电话咨询。
国外毕业证学位证成绩单如何办理：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作皇家墨尔本理工大学毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
制作毕业证书(ANU毕业证)莫纳什大学毕业证成绩单官方原版办理
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Gen Z and the marketplaces - let's translate their needs
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Statistical Analysis of DNS Latencies.pdf
- 1. Ondřej Surý <ondrej@isc.org> Internet Systems Consortium 2024-05-21
- 3. DNS Performance Metrics (quick intro) Measuring DNS Latency • Performance under normal conditions ‣ • The data is right-skewed ‣ The usual descriptive statistics are useless (average, mean, …) ‣ Most of the queries are answered very quickly ‣ In fact, 95% of the queries are answered under 2 milliseconds ‣ The tails makes it interesting Ondřej Surý <ondrej@isc.org> 2024-05-21 1 / 8
- 4. Logarithmic Percentile Histogram Measuring DNS Latency Ondřej Surý <ondrej@isc.org> 2024-05-21 2 / 8
- 5. Logarithmic Percentile Histogram Measuring DNS Latency • Both axes are logarithmic ‣ x-axis: slowest percentile ‣ y-axis: average latency • It makes the tail more visible • Variant of Complementary Cumulative Distribution Function • Very robust, can be used for monitoring (1% slowest percentile) • Introduced by the good folks at PowerDNS See more: https://blog.powerdns.com/2017/11/02/dns-performance- metrics-the-logarithmic-percentile-histogram Ondřej Surý <ondrej@isc.org> 2024-05-21 3 / 8
- 7. DNS Performance for Developers Compare DNS Latencies • Comparing two branches of BIND 9 ‣ Did we improve the code? ‣ Did we made things worse? ‣ Currently, we compare the graphs by looking at them; ‣ And then running more tests; ‣ And then some wishful thinking… • Sending thanks to Python’s numpy and scipy developers! Ondřej Surý <ondrej@isc.org> 2024-05-21 4 / 8
- 8. Pick the right statistics Compare DNS Latencies • The distribution is not normal • Non-parametrical test then? ‣ Kolmogorov-Smirnov test didn’t really work • Normalize the data? ‣ Box Cox Transformation didn’t really work • Maybe look only at the tail then? Ondřej Surý <ondrej@isc.org> 2024-05-21 5 / 8
- 9. Looking at the tail Compare DNS Latencies • Pick the 95% (99%) percentile complement ‣ Either return the lowest bucket needed for 5% of responses ‣ Or count the answers in (1.9-2.0 second buckets) • Have at least 3 runs for each group • Yay! The data are normal and the group variances are equal ‣ Shapiro-Wilk test – first group (𝑊 = 0.905, 𝑝 = 0.436) – second group (𝑊 = 0.970, 𝑝 = 0.874) ‣ Brown-Forsyth test (𝐹 = 0.070, 𝑝 = 0.798) Ondřej Surý <ondrej@isc.org> 2024-05-21 6 / 8
- 10. Parametrical test (ANOVA) Compare DNS Latencies • We can test more than two branches • One-way ANOVA reports difference between branches ‣ 𝐹 = 9244.090, 𝑝 < .001 • Two-sample T-Test (for confirmation) ‣ 𝑇 = −96.146, 𝑝 < .001 Ondřej Surý <ondrej@isc.org> 2024-05-21 7 / 8
- 11. More ideas?
- 12. Other tests? More ideas? • Is this even correct? Or am I crazy? (I’m not a statistician) • Can we just compare two data sets (1x baseline with 1x branch)? • Can we use the full (right-skewed) population? • Are there any other non-parametrical tests I can try/use? • Are there any other suitable statistical methods? • Is this useful for other Internet measurements? Ondřej Surý <ondrej@isc.org> 2024-05-21 8 / 8
- 13. Thank you!