Analytics 2011 Conference


The Analytics 2011 Conference Series combines the power of SAS’s M2010 Data Mining Conference and F2010 Business Forecasting Conference into one conference covering the latest trends and techniques in the field of analytics. Analytics 2011 Conference Series brings the brightest minds in the field of analytics together with hundreds of analytics practitioners. Join us as these leading conferences change names and locations. At Analytics 2011, you’ll learn through a series of case studies, technical presentations and hands-on training. If you are in the field of analytics, this is one conference you can’t afford to miss.

Conference Details

October 24-25, 2011
Grande Lakes Resort
Orlando, FL

Analytics 2011 topic areas include:

Google Snappy

Diagram of how a 32-bit integer is arranged in...
Image via Wikipedia

a cool sounding software- yet again by the guys from California, this one enables to zip and unzip Big Data much much faster


Snappy is a compression/decompression library. It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression. For instance, compared to the fastest mode of zlib, Snappy is an order of magnitude faster for most inputs, but the resulting compressed files are anywhere from 20% to 100% bigger. On a single core of a Core i7 processor in 64-bit mode, Snappy compresses at about 250 MB/sec or more and decompresses at about 500 MB/sec or more.

Snappy is widely used inside Google, in everything from BigTable and MapReduce to our internal RPC systems. (Snappy has previously been referred to as “Zippy” in some presentations and the likes.)

For more information, please see the README. Benchmarks against a few other compression libraries (zlib, LZO, LZF, FastLZ, and QuickLZ) are included in the source code distribution.

Snappy is a compression/decompression library. It does not aim for maximum
compression, or compatibility with any other compression library; instead,
it aims for very high speeds and reasonable compression. For instance,
compared to the fastest mode of zlib, Snappy is an order of magnitude faster
for most inputs, but the resulting compressed files are anywhere from 20% to
100% bigger. (For more information, see “Performance”, below.)
Snappy has the following properties:
* Fast: Compression speeds at 250 MB/sec and beyond, with no assembler code.
See “Performance” below.
* Stable: Over the last few years, Snappy has compressed and decompressed
petabytes of data in Google’s production environment. The Snappy bitstream
format is stable and will not change between versions.
* Robust: The Snappy decompressor is designed not to crash in the face of
corrupted or malicious input.
* Free and open source software: Snappy is licensed under the Apache license,
version 2.0. For more information, see the included COPYING file.
Snappy has previously been called “Zippy” in some Google presentations
and the like.
Snappy is intended to be fast. On a single core of a Core i7 processor
in 64-bit mode, it compresses at about 250 MB/sec or more and decompresses at
about 500 MB/sec or more. (These numbers are for the slowest inputs in our
benchmark suite; others are much faster.) In our tests, Snappy usually
is faster than algorithms in the same class (e.g. LZO, LZF, FastLZ, QuickLZ,
etc.) while achieving comparable compression ratios.
Typical compression ratios (based on the benchmark suite) are about 1.5-1.7x
for plain text, about 2-4x for HTML, and of course 1.0x for JPEGs, PNGs and
other already-compressed data. Similar numbers for zlib in its fastest mode
are 2.6-2.8x, 3-7x and 1.0x, respectively. More sophisticated algorithms are
capable of achieving yet higher compression rates, although usually at the
expense of speed. Of course, compression ratio will vary significantly with
the input.
Although Snappy should be fairly portable, it is primarily optimized
for 64-bit x86-compatible processors, and may run slower in other environments.
In particular:
– Snappy uses 64-bit operations in several places to process more data at
once than would otherwise be possible.
– Snappy assumes unaligned 32- and 64-bit loads and stores are cheap.
On some platforms, these must be emulated with single-byte loads
and stores, which is much slower.
– Snappy assumes little-endian throughout, and needs to byte-swap data in
several places if running on a big-endian platform.
Experience has shown that even heavily tuned code can be improved.
Performance optimizations, whether for 64-bit x86 or other platforms,
are of course most welcome; see “Contact”, below.
Note that Snappy, both the implementation and the interface,
is written in C++.
To use Snappy from your own program, include the file “snappy.h” from
your calling file, and link against the compiled library.
There are many ways to call Snappy, but the simplest possible is
snappy::Compress(input, &output);
and similarly
snappy::Uncompress(input, &output);
where “input” and “output” are both instances of std::string.

The Latest GUI for R- BioR

Once more a spanking new shiny software –

Bio7 is a integrated development environment for ecological modelling based on the Rich-Client-Platformconcept of the Java IDE Eclipse. The Bio7 platform contains several perspectives which arrange several views for a special purpose useful for the development and analysis of ecological models. One special perspective bundles a feature rich GUI (Graphical User Interface) for the statistical software R.
For the bidirectional communication between Java and R the Rserve application is used (as a backend to evaluate R code and transfer data from and to Java).
The Bio7 R perspective (see figure below) is divided into a R-Shell view on the left side (conceptual the R side) and a Table view on the right side (conceptual the Java side).
Data can be imported to a spreadsheet, edited and then transferred to the R workspace. Vice versa data from R can be transferred to a sheet of the Table view and then exported e.g. to an Excel or OpenOffice file.



Built upon Eclipse 3.6.1.

Now works with the latest Java version! (Windows version bundled with the latest JRE release).

Removed the Soil perspective (now soils can be modeled with ImageJ (float precision). Active images can be displayed in the 3D discrete view (new example available).

Removed the database perspective and the plant layer. You can now built any discrete models without any plant layer.

Removed several controls in the Control view. Added the “Custom Controls” view. In addition ported the Swing component of the Time panel to Swt.

Deleted the avi to swf converter in the ImageJ menu.

Now patterns can be saved with opened Java editor source. If this file is reopened and dragged on Bio7 the pattern is loaded, the source is compiled and the setup method (if available) is executed. In this way model files can be used for presentations ->drag, setup and run. The save actions are located in the Speadsheet view toolbar.

More options available to disable panel painting and recording of values (if not needed for speed!).

New Setup button in the toolbar of Bio7 to trigger a compiled setup method if available.

Removed the load and save pattern buttons from the toolbar of Bio7. Discrete patterns can now be stored with the available action in the spreadsheet view menu.

New P2 Update Manager available in Bio7.

Updated the Janino Compiler.

New HTML perspective added with a view which embeds the TinyMC editor.

New options to disable painting operations for the discrete panels.

New option to explicitly enable scripts at startup (for a faster startup).

Quadgrid (Hexgrid)

Only states are now available which can be created in the “Spreadsheet” view menu easily. Patterns can be stored and restored as usual but are now stored in an *.exml file.

New method to transfer the quadgrid pattern as a matrix to R.

New method to transfer the population data of all quadgrid states to R.


Update to the latest version (with additional fixes).

Fixed a bug to rename the image.

Thumbnail browser can now open images recursevely(limited to 1000 pics), the magnifiyng glass can be disabled, too.

Plugins can be installed dynamically with a drag and drop operation on the ImageJ view or toolbar (as known from ImageJ).

Installed plugins now extend the plugin menu as submenus or subsubmenus (not finished yet!).

Plugins can now be created with the Java editor. New Bio7 Wizard available to create a plugin template.

Compiled Java files can be added to a *.jar file with a new available action in the Navigator view (if you rightclick on the files in the Navigator). In this way ImageJ plugins can be packaged in a *.jar.


Fixed a repaint bug in the debug mode of a flow (now draws correctly the active shape in the flow).

Resize with Strg+Scrollwheel works again.

Comments with more than one line works again.

New Test action to verify connections in a flow.

Debug mode now shows all executed Shapes.

Integrated more default tests (for the verification of a regular flow).

A mouse-click now deletes colored shapes in a flow (e.g. in debug mode).

Points panel:

Integrated (dynamic) Voronoi, Delauney visualization (with area and clip to rectangle action).

Points coordinates can now be set in double precision.

Transfer of point coordinates to R now in double precision.

Bio7 Table:

New import and export of Excel 2007 OOXML.

Row headers can now be resized with the mouse device.


Updated R (2.12.1) and Rserve (0.6.3) to the latest version.

New help action in the R-Shell view.

New action to display help for R specific commands in the embedded Bio7 browser (which opens automatically).

New Key actions to copy the selected variable names to the expression dialog (c=cocatenate (+), a=add (,)).

New action to transfer character or numeric vectors horizontally or vertically in an opened spread (Table view) at selection coordinates.

Empty spaces in the filepath are now allowed under Windows if Rserve is started with a system shell or the RGUI (for the tempfile select a location in the Preferences dialog which is writeable) is started.This works also for the RGUI action.

Improved the search for the “Install packages” action (option “Case Sensitive” added).


New API methods available!


Many fixes since the last version!



Important information:

A certain firewall software can corrupt the Bio7 *.zip file (as well as other files).
Please ensure that you have downloaded a functioning Bio7 1.5 version. In addition it is also reported that a certain antivirus software detects the bundled R software (on Windows) as malware. Often the R specific “open.exe” is detected as malware. Please use a different scanner to make sure that the software is not infected if you have any doubts. For more details see:


Viva Libre Office

WordPerfect 5.1 for DOS.
Image via Wikipedia

The Document Foundation is happy to announce the release candidate of
LibreOffice 3.3.1. This release candidate is the first in a series of
frequent bugfix releases on top of our LibreOffice 3.3 product. Please
be aware that LibreOffice 3.3.1 RC1 is not yet ready for production
use, you should continue to use LibreOffice for that.

Following is the list of changes against LibreOffice 3.3:

Key changes at a glance:

* Numerous translation updates
* new mimetype icons for LibreOffice – explained here:
* quite a few crasher fixes

Detailed change log:

* translation updates
* Removed old/unmaintained icon themes
* Fix for Don’t
use a reference or the default formula string will be changed
* Install bash completion for oo* wrappers when enabled
* Build fix: get the stlport compat workaround working for gcc 4.6.0
* Build fix: no ddraw.h or ddraw.lib in the June 2010 DirectX SDK,
removed usage
* Windows installer: padded nologobanner.bmp, new size is 102×58
* removed gd – Gaelic, ky – Kirghiz, pap – Papiamento, ti – Tigrinya,
ms – Malay, ps – Pashto, ur – Urdu. UI localization does not exist
in these languages. So it makes no sense to ship packages.
* Build fix: pass thru PYTHON, found by configure. Will be used by
* Upgraded libwpd (WordPerfect filter) to 0.9.1
* Fixed BrOffice Windows start menu branding
* Removed language code ‘kid’. kid is not Koshin, but key id pseudo
language which is good for debugging UI but should no be included
in the product
* Added ca_XV and ast language/local name and description
* Fixed incorrect page number in page preview mode
( When the
window is large enough to show several ‘Page X’ strings,
the page number was not properly incremented.
* Fixed incorrect import of cell attributes from Excel
documents. When a cell with non-default formatting attribute starts
with non-first row in a column, the filter would incorrectly apply
the same format to all the cells above it if they didn’t have any
* Ubuntu: fix for lp#696527 – enable human icon theme in LibreOffice
* Fix for crash on
changing position of drawing object in header.
* Changed to LibreOffice in nsplugin
* Added Occitan dictionary
* Added Ukrainian dictionaries
* Fix window focus for langpack installation on Mac –
* Added/modified NLPsolver translations from Pootle
* Fix for
* Fix for RTF export crasher
* Use LibreOffice as product name for EPS Creator header
* Parse svg ‘color’ property (fixes
* Use double instead of float in writerfilter import
* Build fix: use PYTHON as passed through by
* Fix for remove
debug line
* Fix for – fixes
ole object import for writer (docx)
* Fix for
rename OOo -> LibO on Getting Support Page
* Fix ooxml import: handle css::table::BorderLine in addition to
css::table::BorderLine2 That means that table cell properties are
correctly set on import again.
* Fix for
wikihelp: Improve the check for existence of the localized help.
* Fix for – fixes
several crashes around config UNO API
* Fix for
* Fix for
Implementation names weren’t matching with xcu.
* Fix: don’t pushback and process a corrupt extension
* Fix: wikihelp – do not check for existence of the localized
help. In case we do not have the help installed, it is up to the
online service to decide the fallback in case a language version is
not available.
* Fix README: change su urpmi to sudo urpmi for Mandriva section
* Fix README formatting – – using CRLF
instead of LF on WIN platform
* Fix README: word wrap at column 75 for better readability
* Build fix: KDE3 library search order
instead of STDLIBS.
* Start using technical.dic instead of oracle.dic
* Build fix: add explicit QRegion* for clipRegion to fix compile of
kde backend
* Cleanup: removed obsolete m_bSingleAltPress
* Remove the menu when Left Alt Key was pressed for GTK
* Fix for use
year of era in long format for zh_TW by default
* Fix wrong collation for Catalan language
* Fix for wrong
line break with “(”
* Fix for – crash
when iterating over the database types.
* Default currency for Estonia should be Euro – fixes
* Avoid a pointless GetHelpText() call in the toolbox. Fixes GetHelpText()
can be quite heavy, see
* Paint toolbar handle positioned properly
* Build fix: move cxxabi.h after stl headers to workaround gcc 4.6.0
and stlport
* Fix for
manipulate also the C runtime’s environment
* Fix for CTL/Other Default Font #i25247#, #i25561#, #i48064#,
* RTF export crasher
* Fixed an infinite loop in RTF exporter
* UI: translations need more space on word count dialog, made space
for it.
* Fix for improve
formfield checkbox binary export (and import)

Again a BIG Thank You!

Again whats Libre Office

What does LibreOffice give you?

Writer is the word processor inside LibreOffice. Use it for everything, from dashing off a quick letter to producing an entire book with tables of contents, embedded illustrations, bibliographies and diagrams. The while-you-type auto-completion, auto-formatting and automatic spelling checking make difficult tasks easy (but are easy to disable if you prefer). Writer is powerful enough to tackle desktop publishing tasks such as creating multi-column newsletters and brochures. The only limit is your imagination.

Calc tames your numbers and helps with difficult decisions when you’re weighing the alternatives. Analyze your data with Calc and then use it to present your final output. Charts and analysis tools help bring transparency to your conclusions. A fully-integrated help system makes easier work of entering complex formulas. Add data from external databases such as SQL or Oracle, then sort and filter them to produce statistical analyses. Use the graphing functions to display large number of 2D and 3D graphics from 13 categories, including line, area, bar, pie, X-Y, and net – with the dozens of variations available, you’re sure to find one that suits your project.

Impress is the fastest and easiest way to create effective multimedia presentations. Stunning animation and sensational special effects help you convince your audience. Create presentations that look even more professional than the standard presentations you commonly see at work. Get your collegues’ and bosses’ attention by creating something a little bit different.

Draw lets you build diagrams and sketches from scratch. A picture is worth a thousand words, so why not try something simple with box and line diagrams? Or else go further and easily build dynamic 3D illustrations and special effects. It’s as simple or as powerful as you want it to be.

Base is the database front-end of the LibreOffice suite. With Base, you can seamlessly integrate your existing database structures into the other components of LibreOffice, or create an interface to use and administer your data as a stand-alone application. You can use imported and linked tables and queries from MySQL, PostgreSQL or Microsoft Access and many other data sources, or design your own with Base, to build powerful front-ends with sophisticated forms, reports and views. Support is built-in or easily addable for a very wide range of database products, notably the standardly-provided HSQL, MySQL, Adabas D, Microsoft Access and PostgreSQL.

Math is a simple equation editor that lets you lay-out and display your mathematical, chemical, electrical or scientific equations quickly in standard written notation. Even the most-complex calculations can be understandable when displayed correctly. E=mc2.

LibreOffice also comes configured with a PDF file creator, meaning you can distribute documents that you’re sure can be opened and read by users of almost any computing device or operating system.

Download LibreOffice now and try it out today.


Interview Jamie Nunnelly NISS

An interview with Jamie Nunnelly, Communications Director of National Institute of Statistical Sciences

Ajay– What does NISS do? And What does SAMSI do?

Jamie– The National Institute of Statistical Sciences (NISS) was established in 1990 by the national statistics societies and the Research Triangle universities and organizations, with the mission to identify, catalyze and foster high-impact, cross-disciplinary and cross-sector research involving the statistical sciences.

NISS is dedicated to strengthening and serving the national statistics community, most notably by catalyzing community members’ participation in applied research driven by challenges facing government and industry. NISS also provides career development opportunities for statisticians and scientists, especially those in the formative stages of their careers.

The Institute identifies emerging issues to which members of the statistics community can make key contributions, and then catalyzes the right combinations of researchers from multiple disciplines and sectors to tackle each problem. More than 300 researchers from over 100 institutions have worked on our projects.

The Statistical and Applied Mathematical Sciences Institute (SAMSI) is a partnership of Duke University,  North Carolina State University, The University of North Carolina at Chapel Hill, and NISS in collaboration with the William Kenan Jr. Institute for Engineering, Technology and Science and is part of the Mathematical Sciences Institutes of the NSF.

SAMSI focuses on 1-2 programs of research interest in the statistical and/or applied mathematical area and visitors from around the world are involved with the programs and come from a variety of disciplines in addition to mathematics and statistics.

Many come to SAMSI to attend workshops, and also participate in working groups throughout the academic year. Many of the working groups communicate via WebEx so people can be involved with the research remotely. SAMSI also has a robust education and outreach program to help undergraduate and graduate students learn about cutting edge research in applied mathematics and statistics.

Ajay– What successes have you had in 2010- and what do you need to succeed in 2011. Whats planned for 2011 anyway

Jamie– NISS has had a very successful collaboration with the National Agricultural Statistical Service (NASS) over the past two years that was just renewed for the next two years. NISS & NASS had three teams consisting of a faculty researcher in statistics, a NASS researcher, a NISS mentor, a postdoctoral fellow and a graduate student working on statistical modeling and other areas of research for NASS.

NISS is also working on a syndromic surveillance project with Clemson University, Duke University, The University of Georgia, The University of South Carolina. The group is currently working with some hospitals to test out a model they have been developing to help predict disease outbreak.

SAMSI had a very successful year with two programs ending this past summer, which were the Stochastic Dynamics program and the Space-time Analysis for Environmental Mapping, Epidemiology and Climate Change. Several papers were written and published and many presentations have been made at various conferences around the world regarding the work that was conducted as SAMSI last year.

Next year’s program is so big that the institute has decided to devote all it’s time and energy around it, which is uncertainty quantification. The opening workshop, in addition to the main methodological theme, will be broken down into three areas of interest under this broad umbrella of research: climate change, engineering and renewable energy, and geosciences.

Ajay– Describe your career in science and communication.

Jamie– I have been in communications since 1985, working for large Fortune 500 companies such as General Motors and Tropicana Products. I moved to the Research Triangle region of North Carolina after graduate school and got into economic development and science communications first working for the Research Triangle Regional Partnership in 1994.

From 1996-2005 I was the communications director for the Research Triangle Park, working for the Research Triangle Foundation of NC. I published a quarterly magazine called The Park Guide for awhile, then came to work for NISS and SAMSI in 2008.

I really enjoy working with the mathematicians and statisticians. I always joke that I am the least educated person working here and that is not far from the truth! I am honored to help get the message out about all of the important research that is conducted here each day that is helping to improve the lives of so many people out there.

Ajay– Research Triangle or Silicon Valley– Which is better for tech people and why? Your opinion

Jamie– Both the Silicon Valley and Research Triangle are great regions for tech people to locate, but of course, I have to be biased and choose Research Triangle!

Really any place in the world that you find many universities working together with businesses and government, you have an area that will grow and thrive, because the collaborations help all of us generate new ideas, many of which blossom into new businesses, or new endeavors of research.

The quality of life in places such as the Research Triangle is great because you have people from around the world moving to a place, each bringing his/her culture, food, and uniqueness to this place, and enriching everyone else as a result.

Two advantages the Research Triangle has over Silicon Valley are that the Research Triangle has a bigger diversity of industries, so when the telecommunications industry busted back in 2001-02, the region took a hit, but the biotechnology industry was still growing, so unemployment rose, but not to the extent that other areas might have experienced.

The latest recession has hit us all very hard, so even this strategy has not made us immune to having high unemployment, but the Research Triangle region has been pegged by experts to be one of the first regions to emerge out of the Great Recession.

The other advantage I think we have is that our cost of living is still much more reasonable than Silicon Valley. It’s still possible to get a nice sized home, some land and not break the bank!

Ajay– How do you manage an active online social media presence, your job and your family. How important is balance in professional life and when young professional should realize this?

Jamie– Balance is everything, isn’t it? When I leave the office, I turn off my iPhone and disconnect from Twitter/Facebook etc.

I know that is not recommended by some folks, but I am a one person communications department and I love my family and friends and feel its important to devote time to them as well as to my career.

I think it is very important for young people to establish this early in their careers because if they don’t they will fall victim to working way too many hours and really, who loves you at the end of the day?

Your company may appreciate all you do for them, but if you leave, or you get sick and cannot work for them, you will be replaced

. Lee Iacocca, former CEO of Chrystler, said, “No matter what you’ve done for yourself or for humanity, if you can’t look back on having given love and attention to your own family, what have you really accomplished?” I think that is what is really most important in life.


Jamie Nunnelly has been in communications for 25 years. She is currently on the board of directors for Chatham County Economic Development Corporation and Leadership Triangle & is a member of the International Association of Business Communicators and the Public Relations Society of America. She earned a bachelor’s degree in interpersonal and public communications at Bowling Green State University and a master’s degree in mass communications at the University of South Florida.

You can contact Jamie at or on twitter at

Summer School on Uncertainty Quantification

Scheme for sensitivity analysis
Image via Wikipedia

SAMSI/Sandia Summer School on Uncertainty Quantification – June 20-24, 2011

The utilization of computer models for complex real-world processes requires addressing Uncertainty Quantification (UQ). Corresponding issues range from inaccuracies in the models to uncertainty in the parameters or intrinsic stochastic features.

This Summer school will expose students in the mathematical and statistical sciences to common challenges in developing, evaluating and using complex computer models of processes. It is essential that the next generation of researchers be trained on these fundamental issues too often absent of traditional curricula.

Participants will receive not only an overview of the fast developing field of UQ but also specific skills related to data assimilation, sensitivity analysis and the statistical analysis of rare events.

Theoretical concepts and methods will be illustrated on concrete examples and applications from both nuclear engineering and climate modeling.

The main lecturers are:
Dan Cacuci (N.C. State University): data assimilation and applications to nuclear engineering

Dan Cooley (Colorado State University): statistical analysis of rare events
This short course will introduce the current statistical practice for analyzing extreme events. Statistical practice relies on fitting distributions suggested by asymptotic theory to a subset of data considered to be extreme. Both block maximum and threshold exceedance approaches will be presented for both the univariate and multivariate cases.

Doug Nychka (NCAR): data assimilation and applications in climate modeling
Climate prediction and modeling do not incorporate geophysical data in the sequential manner as weather forecasting and comparison to data is typically based on accumulated statistics, such as averages. This arises because a climate model matches the state of the Earth’s atmosphere and ocean “on the average” and so one would not expect the detailed weather fluctuations to be similar between a model and the real system. An emerging area for climate model validation and improvement is the use of data assimilation to scrutinize the physical processes in a model using observations on shorter time scales. The idea is to find a match between the state of the climate model and observed data that is particular to the observed weather. In this way one can check whether short time physical processes such as cloud formation or dynamics of the atmosphere are consistent with what is observed.

Dongbin Xiu (Purdue University): sensitivity analysis and polynomial chaos for differential equations
This lecture will focus on numerical algorithms for stochastic simulations, with an emphasis on the methods based on generalized polynomial chaos methodology. Both the mathematical framework and the technical details will be examined, along with performance comparisons and implementation issues for practical complex systems.

The main lectures will be supplemented by discussion sessions and by presentations from UQ practitioners from both the Sandia and Los Alamos National Laboratories.