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Interview Rob J Hyndman Forecasting Expert #rstats

Here is an interview with Prof Rob J Hyndman who has created many time series forecasting methods and authored books as well as R packages on the same.

Ajay -Describe your journey from being a student of science to a Professor. What were some key turning points along that journey?
 
Rob- I started a science honours degree at the University of Melbourne in 1985. By the end of 1985 I found myself simultaneously working as a statistical consultant (having completed all of one year of statistics courses!). For the next three years I studied mathematics, statistics and computer science at university, and tried to learn whatever I needed to in order to help my growing group of clients. Often we would cover things in classes that I’d already taught myself through my consulting work. That really set the trend for the rest of my career. I’ve always been an academic on the one hand, and a statistical consultant on the other. The consulting work has led me to learn a lot of things that I would not otherwise have come across, and has also encouraged me to focus on research problems that are of direct relevance to the clients I work with.
I never set out to be an academic. In fact, I thought that I would get a job in the business world as soon as I finished my degree. But once I completed the degree, I was offered a position as a statistical consultant within the University of Melbourne, helping researchers in various disciplines and doing some commercial work. After a year, I was getting bored doing only consulting, and I thought it would be interesting to do a PhD. I was lucky enough to be offered a generous scholarship which meant I was paid more to study than to continue working.
Again, I thought that I would probably go and get a job in the business world after I finished my PhD. But I finished it early and my scholarship was going to be cut off once I submitted my thesis. So instead, I offered to teach classes for free at the university and delayed submitting my thesis until the scholarship period ran out. That turned out to be a smart move because the university saw that I was a good teacher, and offered me a lecturing position starting immediately I submitted my thesis. So I sort of fell into an academic career.
I’ve kept up the consulting work part-time because it is interesting, and it gives me a little extra money. But I’ve also stayed an academic because I love the freedom to be able to work on anything that takes my fancy.
Ajay- Describe your upcoming book on Forecasting.
 
Rob- My first textbook on forecasting (with Makridakis and Wheelwright) was written a few years after I finished my PhD. It has been very popular, but it costs a lot of money (about $140 on Amazon). I estimate that I get about $1 for every book sold. The rest goes to the publisher (Wiley) and all they do is print, market and distribute it. I even typeset the whole thing myself and they print directly from the files I provided. It is now about 15 years since the book was written and it badly needs updating. I had a choice of writing a new edition with Wiley or doing something completely new. I decided to do a new one, largely because I didn’t want a publisher to make a lot of money out of students using my hard work.
It seems to me that students try to avoid buying textbooks and will search around looking for suitable online material instead. Often the online material is of very low quality and contains many errors.
As I wasn’t making much money on my textbook, and the facilities now exist to make online publishing very easy, I decided to try a publishing experiment. So my new textbook will be online and completely free. So far it is about 2/3 completed and is available at http://otexts.com/fpp/. I am hoping that my co-author (George Athanasopoulos) and I will finish it off before the end of 2012.
The book is intended to provide a comprehensive introduction to forecasting methods. We don’t attempt to discuss the theory much, but provide enough information for people to use the methods in practice. It is tied to the forecast package in R, and we provide code to show how to use the various forecasting methods.
The idea of online textbooks makes a lot of sense. They are continuously updated so if we find a mistake we fix it immediately. Also, we can add new sections, or update parts of the book, as required rather than waiting for a new edition to come out. We can also add richer content including video, dynamic graphics, etc.
For readers that want a print edition, we will be aiming to produce a print version of the book every year (available via Amazon).
I like the idea so much I’m trying to set up a new publishing platform (otexts.com) to enable other authors to do the same sort of thing. It is taking longer than I would like to make that happen, but probably next year we should have something ready for other authors to use.
Ajay- How can we make textbooks cheaper for students as well as compensate authors fairly
 
Rob- Well free is definitely cheaper, and there are a few businesses trying to make free online textbooks a reality. Apart from my own efforts, http://www.flatworldknowledge.com/ is producing a lot of free textbooks. And textbookrevolution.org is another great resource.
With otexts.com, we will compensate authors in two ways. First, the print versions of a book will be sold (although at a vastly cheaper rate than other commercial publishers). The royalties on print sales will be split 50/50 with the authors. Second, we plan to have some features of each book available for subscription only (e.g., solutions to exercises, some multimedia content, etc.). Again, the subscription fees will be split 50/50 with the authors.
Ajay- Suppose a person who used to use forecasting software from another company decides to switch to R. How easy and lucid do you think the current documentation on R website for business analytics practitioners such as these – in the corporate world.
 
Rob- The documentation on the R website is not very good for newcomers, but there are a lot of other R resources now available. One of the best introductions is Matloff’s “The Art of R Programming”. Provided someone has done some programming before (e.g., VBA, python or java), learning R is a breeze. The people who have trouble are those who have only ever used menu interfaces such as Excel. Then they are not only learning R, but learning to think about computing in a different way from what they are used to, and that can be tricky. However, it is well worth it. Once you know how to code, you can do so much more.  I wish some basic programming was part of every business and statistics degree.
If you are working in a particular area, then it is often best to find a book that uses R in that discipline. For example, if you want to do forecasting, you can use my book (otexts.com/fpp/). Or if you are using R for data visualization, get hold of Hadley Wickham’s ggplot2 book.
Ajay- In a long and storied career- What is the best forecast you ever made ? and the worst?
 
 Rob- Actually, my best work is not so much in making forecasts as in developing new forecasting methodology. I’m very proud of my forecasting models for electricity demand which are now used for all long-term planning of electricity capacity in Australia (see  http://robjhyndman.com/papers/peak-electricity-demand/  for the details). Also, my methods for population forecasting (http://robjhyndman.com/papers/stochastic-population-forecasts/ ) are pretty good (in my opinion!). These methods are now used by some national governments (but not Australia!) for their official population forecasts.
Of course, I’ve made some bad forecasts, but usually when I’ve tried to do more than is reasonable given the available data. One of my earliest consulting jobs involved forecasting the sales for a large car manufacturer. They wanted forecasts for the next fifteen years using less than ten years of historical data. I should have refused as it is unreasonable to forecast that far ahead using so little data. But I was young and naive and wanted the work. So I did the forecasts, and they were clearly outside the company’s (reasonable) expectations, and they then refused to pay me. Lesson learned. It’s better to refuse work than do it poorly.

Probably the biggest impact I’ve had is in helping the Australian government forecast the national health budget. In 2001 and 2002, they had underestimated health expenditure by nearly $1 billion in each year which is a lot of money to have to find, even for a national government. I was invited to assist them in developing a new forecasting method, which I did. The new method has forecast errors of the order of plus or minus $50 million which is much more manageable. The method I developed for them was the basis of the ETS models discussed in my 2008 book on exponential smoothing (www.exponentialsmoothing.net)

. And now anyone can use the method with the ets() function in the forecast package for R.
About-
Rob J Hyndman is Pro­fessor of Stat­ist­ics in the Depart­ment of Eco­no­met­rics and Busi­ness Stat­ist­ics at Mon­ash Uni­ver­sity and Dir­ector of the Mon­ash Uni­ver­sity Busi­ness & Eco­nomic Fore­cast­ing Unit. He is also Editor-in-Chief of the Inter­na­tional Journal of Fore­cast­ing and a Dir­ector of the Inter­na­tional Insti­tute of Fore­casters. Rob is the author of over 100 research papers in stat­ist­ical sci­ence. In 2007, he received the Moran medal from the Aus­tralian Academy of Sci­ence for his con­tri­bu­tions to stat­ist­ical research, espe­cially in the area of stat­ist­ical fore­cast­ing. For 25 years, Rob has main­tained an act­ive con­sult­ing prac­tice, assist­ing hun­dreds of com­pan­ies and organ­iz­a­tions. His recent con­sult­ing work has involved fore­cast­ing elec­tri­city demand, tour­ism demand, the Aus­tralian gov­ern­ment health budget and case volume at a US call centre.

SAS and Hadoop

Awesomely informative post on sascom magazine (whose editor I have I interviewed before here at http://www.decisionstats.com/interview-alison-bolen-sas-com/ – )

Great piece by Michael Ames ,SAS Data Integration Product Manager.

http://www.sas.com/news/sascom/hadoop-tips.html

 

Also see SAS’s big data thingys here at

http://www.sas.com/software/high-performance-analytics/in-memory-analytics/index.html

Solutions and Capabilities Using SAS® In-Memory Analytics

  • High-Performance Analytics – Get near-real-time insights with appliance-ready analytics software designed to tackle big data and complex problems.
  • High-Performance Risk – Faster, better risk management decisions based on the most up-to-date views of your overall risk exposure.
  • High-Performance Liquidity Risk Management – Take quick, decisive actions to secure adequate funding, especially in times of volatility.
  • High-Performance Stress Testing – Make faster, more precise decisions to protect the health of the firm.
  • Visual Analytics – Explore big data using in-memory capabilities to better understand all of your data, discover new patterns and publish reports to the Web and iPad®.

(Ajay- I liked the Visual Analytics piece especially for Big Data )

Note-

 

Awesome website for #rstats Mining Twitter using R

Just came across this very awesome website.

Did you know there were six kinds of wordclouds in R.

(giggles like a little boy)

https://sites.google.com/site/miningtwitter/questions/talking-about

 

Simple Wordcloud

Comparison Wordcloud
Tweets about some given topic

Tweets of some given user (ex 1)
Tweets of some given user (ex 2)
Modified tag-cloud

This guy – the force is strong in him

Gaston Sanchez 
Data Analysis + Visualization + Statistics + R FUN

http://www.gastonsanchez.com/about

 Contact Info
 gaston.stat@gmail.com
> home
 
linkedIn
pinterest
resume.pdf
About Currently, I’m a postdoc in Rasmus Nielsen’s Lab in the Center for Theoretical Evolutionary Genomics at the University of California, Berkeley. I’m also collaborating with the Biology Scholars Program (BSP) at UC Berkeley, and I am affiliated to the Program on Reproductive Health and the Environment (PRHE) at UC San Francisco. In my (scarce) free time outside the academic world, I often work on collaborative projects for marketing analytics, statistical consulting, and statistical advising in general.

How to learn Hacking Part 2

Now that you have read the basics here at http://www.decisionstats.com/how-to-learn-to-be-a-hacker-easily/ (please do read this before reading the below)

 

Here is a list of tutorials that you should study (in order of ease)

1) LEARN BASICS – enough to get you a job maybe if that’s all you wanted.

http://www.offensive-security.com/metasploit-unleashed/Main_Page

2) READ SOME MORE-

Lena’s Reverse Engineering Tutorial-”Use Google.com  for finding the Tutorial

Lena’s Reverse Engineering tutorial. It includes 36 parts of individual cracking techniques and will teach you the basics of protection bypassing

01. Olly + assembler + patching a basic reverseme
02. Keyfiling the reverseme + assembler
03. Basic nag removal + header problems
04. Basic + aesthetic patching
05. Comparing on changes in cond jumps, animate over/in, breakpoints
06. “The plain stupid patching method”, searching for textstrings
07. Intermediate level patching, Kanal in PEiD
08. Debugging with W32Dasm, RVA, VA and offset, using LordPE as a hexeditor
09. Explaining the Visual Basic concept, introduction to SmartCheck and configuration
10. Continued reversing techniques in VB, use of decompilers and a basic anti-anti-trick
11. Intermediate patching using Olly’s “pane window”
12. Guiding a program by multiple patching.
13. The use of API’s in software, avoiding doublechecking tricks
14. More difficult schemes and an introduction to inline patching
15. How to study behaviour in the code, continued inlining using a pointer
16. Reversing using resources
17. Insights and practice in basic (self)keygenning
18. Diversion code, encryption/decryption, selfmodifying code and polymorphism
19. Debugger detected and anti-anti-techniques
20. Packers and protectors : an introduction
21. Imports rebuilding
22. API Redirection
23. Stolen bytes
24. Patching at runtime using loaders from lena151 original
25. Continued patching at runtime & unpacking armadillo standard protection
26. Machine specific loaders, unpacking & debugging armadillo
27. tElock + advanced patching
28. Bypassing & killing server checks
29. Killing & inlining a more difficult server check
30. SFX, Run Trace & more advanced string searching
31. Delphi in Olly & DeDe
32. Author tricks, HIEW & approaches in inline patching
33. The FPU, integrity checks & loader versus patcher
34. Reversing techniques in packed software & a S&R loader for ASProtect
35. Inlining inside polymorphic code
36. Keygenning

If you want more free training – hang around this website

http://www.owasp.org/index.php/Cheat_Sheets

OWASP Cheat Sheet Series

Draft OWASP Cheat Sheets

3) SPEND SOME MONEY on TRAINING

http://www.corelan-training.com/index.php/training/corelan-live/

Course overview

Module 1 – The x86 environment

  • System Architecture
  • Windows Memory Management
  • Registers
  • Introduction to Assembly
  • The stack

Module 2 – The exploit developer environment

  • Setting up the exploit developer lab
  • Using debuggers and debugger plugins to gather primitives

Module 3 – Saved Return Pointer Overwrite

  • Functions
  • Saved return pointer overwrites
  • Stack cookies

Module 4 – Abusing Structured Exception Handlers

  • Abusing exception handler overwrites
  • Bypassing Safeseh

Module 5 – Pointer smashing

  • Function pointers
  • Data/object pointers
  • vtable/virtual functions

Module 6 – Off-by-one and integer overflows

  • Off-by-one
  • Integer overflows

Module 7 – Limited buffers

  • Limited buffers, shellcode splitting

Module 8 – Reliability++ & reusability++

  • Finding and avoiding bad characters
  • Creative ways to deal with character set limitations

Module 9 – Fun with Unicode

  • Exploiting Unicode based overflows
  • Writing venetian alignment code
  • Creating and Using venetian shellcode

Module 10 – Heap Spraying Fundamentals

  • Heap Management and behaviour
  • Heap Spraying for Internet Explorer 6 and 7

Module 11 – Egg Hunters

  • Using and tweaking Egg hunters
  • Custom egghunters
  • Using Omelet egghunters
  • Egghunters in a WoW64 environment

Module 12 – Shellcoding

  • Building custom shellcode from scratch
  • Understanding existing shellcode
  • Writing portable shellcode
  • Bypassing Antivirus

Module 13 – Metasploit Exploit Modules

  • Writing exploits for the Metasploit Framework
  • Porting exploits to the Metasploit Framework

Module 14 – ASLR

  • Bypassing ASLR

Module 15 – W^X

  • Bypassing NX/DEP
  • Return Oriented Programming / Code Reuse (ROP) )

Module 16 – Advanced Heap Spraying

  • Heap Feng Shui & heaplib
  • Precise heap spraying in modern browsers (IE8 & IE9, Firefox 13)

Module 17 – Use After Free

  • Exploiting Use-After-Free conditions

Module 18 – Windows 8

  • Windows 8 Memory Protections and Bypass
TRAINING SCHEDULES AT

ALSO GET CERTIFIED http://www.offensive-security.com/information-security-training/penetration-testing-with-backtrack/ ($950 cost)

the syllabus is here at

http://www.offensive-security.com/documentation/penetration-testing-with-backtrack.pdf

4) HANG AROUND OTHER HACKERS

At http://attrition.org/attrition/

or The Noir  Hat Conferences-

http://blackhat.com/html/bh-us-12/training/bh-us-12-training_complete.html

or read this website

http://software-security.sans.org/developer-how-to/

5) GET A DEGREE

Yes it is possible

 

See http://web.jhu.edu/jhuisi/

The Johns Hopkins University Information Security Institute (JHUISI) is the University’s focal point for research and education in information security, assurance and privacy.

Scholarship Information

 

The Information Security Institute is now accepting applications for the Department of Defense’s Information Assurance Scholarship Program (IASP).  This scholarship includes full tuition, a living stipend, books and health insurance. In return each student recipient must work for a DoD agency at a competitive salary for six months for every semester funded. The scholarship is open to American citizens only.

http://web.jhu.edu/jhuisi/mssi/index.html

MASTER OF SCIENCE IN SECURITY INFORMATICS PROGRAM

The flagship educational experience offered by Johns Hopkins University in the area of information security and assurance is represented by the Master of Science in Security Informatics degree.  Over thirty courses are available in support of this unique and innovative graduate program.

———————————————————–

Disclaimer- I havent done any of these things- This is just a curated list from Quora  so I am open to feedback.

You use this at your own risk of conscience ,local legal jurisdictions and your own legal liability.

 

 

 

 

 

 

Ads Alliance on Internet

Just saw

the Digital Advertising Alliance’s (DAA) Self-Regulatory Program for Online Behavioral Advertising.

Multi-Site Data Collection Principles Broaden Self Regulation Beyond Online Behavioral Advertising
WASHINGTON, D.C., NOVEMBER 7, 2011

The new Principles consist of the following specific requirements:

  1. Transparency and consumer control for purposes other than OBA – The Multi-Site Data Principles call for organizations that collect Multi-Site Data for purposes other than OBA to provide transparency and control regarding Internet surfing across unrelated Websites.
  2. Collection / use of data for eligibility determination – The Multi-Site Data Principles prohibit the collection, use or transfer of Internet surfing data across Websites for determination of a consumer’s eligibility for employment, credit standing, healthcare treatment and insurance.
  3. Collection / use of children’s data – The Multi-Site Data Principles state that organizations must comply with the Children’s Online Privacy Protection Act (COPPA).
  4. Meaningful accountability – The Multi-Site Data Principles are subject to enforcement through strong accountability mechanisms.

http://www.aboutads.info/principles

The DAA Self-Regulatory Principles

 

The cross-industry Self-Regulatory Principles for Multi-Site Data augment the Self-Regulatory   Principles for Online Behavioral Advertising  (OBA)  by covering the prospective  collection of Web site   data beyond that collected for OBA purposes.  The existing OBA  Principles and definitions  remain in   full force and effect and are not limited by the new  principles.

The cross-industry Self-Regulatory Principles for Online Behavioral Advertising was developed by   leading industry associations to apply  consumer-friendly standards to online  behavioral advertising  across the Internet. Online behavioral advertising increasingly supports the convenient access to  content, services, and applications over the Internet that consumers have come to expect at no cost   to them.

The Education Principle calls for organizations to participate in efforts to educate individuals and businesses about online behavioral advertising and the Principles.

The Transparency Principle calls for clearer and easily accessible disclosures to consumers about data collection and use practices associated with online behavioral advertising. It will result in new, enhanced notice on the page where data is collected through links embedded in or around advertisements, or on the Web page itself.

The Consumer Control Principle provides consumers with an expanded ability to choose whether data is collected and used for online behavioral advertising purposes. This choice will be available through a link from the notice provided on the Web page where data is collected.

The Consumer Control Principle requires “service providers”, a term that includes Internet access service providers and providers of desktop applications software such as Web browser “tool bars” to obtain the consent of users before engaging in online behavioral advertising, and take steps to de-identify the data used for such purposes.

The Data Security Principle calls for organizations to provide appropriate security for, and limited retention of data, collected and used for online behavioral advertising purposes.

The Material Changes Principle calls for obtaining consumer consent before a Material Change is made to an entity’s Online Behavioral Advertising data collection and use policies unless that change will result in less collection or use of data.

The Sensitive Data Principle recognizes that data collected from children and used for online behavioral advertising merits heightened protection, and requires parental consent for behavioral advertising to consumers known to be under 13 on child-directed Web sites. This Principle also provides heightened protections to certain health and financial data when attributable to a specific individual.

The Accountability Principle calls for development of programs to further advance these Principles, including programs to monitor and report instances of uncorrected non-compliance with these Principles to appropriate government agencies. The CBBB and DMA have been asked and agreed to work cooperatively to establish accountability mechanisms under the Principles.

 

Ajay- So why the self regulations?

Answer- Shoddy Maths in behaviorally targeted ads is leading to a very high glut in targeted ads, more than can be reasonably expected to click based on consumer spending. On the internet- unlike on television- cost is less of a barrrier to OVER ADVERTISING.

 

Business Metrics

Business Metrics (a partial extract from my upcoming book “R for Business Analytics”

Business Metrics are important variables that are collected on a periodic basis to assess the health and sustainability of a business. They should have the following properties-

1) What is a Business Metric-The absence of collection of regular update of the business metric could cause business disruption by incorrect and incomplete decision making.

2) Cost of Business Metrics- The costs of collection, storage and updating of the business metric is less than the opportunity costs of wrong decision making cause by lack of information of that business metric.

3) Continuity in your Business Metrics- The business metrics are continuous in comparing across time periods and business units- if necessary the assumptions for smoothing the comparisons should be listed in the business metric presentation itself.

4) Simplify your Business Metrics- Business metrics can be derived as well from other business metrics. If necessary and to avoid clutter only the most important business metrics should be presented, or the metrics with the biggest deviation from past trends should be mentioned.

5) Normalize your Business Metrics- Scale of the business metric units should be comparable to other business metrics as well as significant to emphasize the difference in numbers.

6) Standardize your Business Metrics- Dimension of business metrics should be increased to enhance comparison and contrasts without enhancing complexity. This means adding an extra dimension for analysis rather than a 2 by 2 comparison, to add time /geography/ employee/business owner as a dimension .

HANA Oncolyzer

An interesting use case of technology for better health is HANA Oncolyzer at http://epic.hpi.uni-potsdam.de/Home/HanaOncolyzer

“Build on the newest in-memory technology the HANA Oncolyzer is able to analyze even huge amounts of medical data in shortest time”, says Dr. Alexander Zeier, Deputy Chair of EPIC. Research institutes and university hospital support from HANA Oncolyzer by building the basis for a flexible exchange of information about efficiency of medicines and treatments.

In near future, the tumor’s DNA of all cancer patients needs to be analyzed to support specific patient therapies. These analyses result in medical data in amount of multiple terabytes. “These data need to be analyzed regarding mutations and anomalies in real-time”, says Matthias Steinbrecher at SAP’s Innovation Center in Potsdam. As one of the aims the research prototype HANA Oncolyzer was developed at our chair in cooperation with SAP’s Innovation Center in Potsdam. “The ‘heart’ of our development builds the in-memory technology that supports the parallel analysis of million of data within seconds in main memory”, saysMatthieu Schapranow, Ph.D. cand. at the HPI.

and

research activities result in 500.000 or more data points per patient.

and

With the help of a dedicated iPad application medical doctors can access all data mobile at any location anytime.

 

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