Assign Names to Objects Based on Names of Files in a Directory using R for a large number of input csv files
Personally I think a browser with inbuilt backdoors to Tor Relays and data transfer by Bit Torrrents could be worthy a project too.
Quit the bullshit, Google- you are as evil as The Russian Communist Empire
I was just reading up on my weekly to-read list and came across this interesting method. It is called Play Color Cipher-
Each Character ( Capital, Small letters, Numbers (0-9), Symbols on the keyboard ) in the plain text is substituted with a color block from the available 18 Decillions of colors in the world  and at the receiving end the cipher text block (in color) is decrypted in to plain text block. It overcomes the problems like “Meet in the middle attack, Birthday attack and Brute force attacks ”.
It also reduces the size of the plain text when it is encrypted in to cipher text by 4 times, with out any loss of content. Cipher text occupies very less buffer space; hence transmitting through channel is very fast. With this the transportation cost through channel comes down.
Visual Cryptography is indeed an interesting topic-
Visual cryptography, an emerging cryptography technology, uses the characteristics of human vision to decrypt encrypted
images. It needs neither cryptography knowledge nor complex computation. For security concerns, it also ensures that hackers
cannot perceive any clues about a secret image from individual cover images. Since Naor and Shamir proposed the basic
model of visual cryptography, researchers have published many related studies.
Visual cryptography (VC) schemes hide the secret image into two or more images which are called
shares. The secret image can be recovered simply by stacking the shares together without any complex
computation involved. The shares are very safe because separately they reveal nothing about the secret image.
Visual Cryptography provides one of the secure ways to transfer images on the Internet. The advantage
of visual cryptography is that it exploits human eyes to decrypt secret images .
ESPECIALLY SEE |THIS AND THIS
Even more fun—– visual cryptography using a series of bar codes – leaving the man in middle guessing how many sub images are there and which if at all is the real message
Color Visual Cryptography Scheme Using Meaningful Shares
Visual cryptography for color images
- Visual Crypto – One-time Image Create two secure images from one by Robert Hansen
- Visual Crypto Java Applet at the University of Regensburg
- Visual Cryptography Kit Software to create image layers
- On-line Visual Crypto Applet by Leemon Baird
- Extended Visual Cryptography (pdf) by Mizuho Nakajima and Yasushi Yamaguchi
- Visual Cryptography Paper by Moni Noar and Adi Shamir
- Visual Crypto Talk (pdf) by Frederik Vercauteren ESAT Leuven
- t the University of Salerno web page on visual cryptogrpahy.
- Visual Crypto Page by Doug Stinson
Constructions and Bounds for Visual Cryptography
Lecture Notes in Computer Science 1099 (1996), 416-428 (23rd International Colloquium on Automata, Languages and Programming).
- Visual Cryptography for General Access Structures
Information and Computation 129 (1996), 86-106 (this paper is an expanded and revised version of the conference paper).
- On the Contrast in Visual Cryptography Schemes
Journal of Cryptology 12 (1999), 261-289.
- Extended Schemes for Visual Cryptography
Theoretical Computer Science 250 (2001), 143-161.
- Threshold Visual Cryptography Schemes With Specified Whiteness Levels of Reconstructed Pixels
Designs, Codes and Cryptography 25 (2002), 15-61.
- Contrast Optimal Threshold Visual Cryptography Schemes
SIAM J. on Discrete Math. 16 (2003), 224-261.
- “Visual Cryptography: Seeing is Believing” availablehere,
- example- face http://cacr.uwaterloo.ca/~dstinson/VCS-happyface.html
- flag http://cacr.uwaterloo.ca/~dstinson/VCS-flag.html
- pi http://cacr.uwaterloo.ca/~dstinson/VCS-pi.html
- Simple implementation of the visual cryptography scheme based on Moni Naor and Adi Shamir, Visual Cryptography, EUROCRYPT 1994, pp1–12. This technique allows visual information like pictures to be encrypted so that decryption can be done visually.The code outputs two files. Try printing them on two separate transparencies and putting them one on top of the other to see the hidden message. http://algorito.com/algorithm/visual-cryptography
- Moni Naor and Adi Shamir, Visual Cryptography , Eurocrypt 94. Postscript , gzipped Postscript
- Moni Naor and Adi Shamir, Visual Cryptography II , Cambridge Workshop on Protocols, 1996. Postscript, gzipped Postscript
- Moni Naor and Benny Pinkas, Visual Authentication , Crypto 97. Postscript, gzipped Postscript
Ajay- I think a combination of sharing and color ciphers would prove more helpful to secure Internet Communication than existing algorithms. It also levels the playing field from computationally rich players to creative coders.
From the famous KARL REXER ANNUAL DATA MINING SURVEY
- SURVEY & PARTICIPANTS: 68-item survey conducted online in 2013. Participants: 1,259 analytic professionals from 75 countries. This is the 6th Data Miner Survey.
- FOCUS ON CRM: In the past few years, there has been an increase among data miners in the already substantial area of customer-focused analytics. Respondents are looking for a better understanding of customers and seeking to improve the customer experience. This can be seen in their goals, analyses, big data endeavors, and in the focus of their text mining.
- BIG DATA: Many in the field are talking about the phenomena of Big Data. There are clearly some areas in which the volume and sources of data have grown. However it is unclear how much Big Data has impacted the typical data miner. While data miners believe that the size of their datasets have increased over the past year, data from previous surveys indicate that the size of datasets have been fairly consistent over time.
- THE ASCENDANCE OF R: The proportion of data miners using R is rapidly growing, and since 2010, R has been the most-used data mining tool. While R is frequently used along with other tools, an increasing number of data miners also select R as their primary tool.
- CHALLENGES IN THE USE OF ANALYTICS: Data miners continue to report challenges at each level of the analytic process. Companies often are not using analytics to their fullest and have continuing issues in the areas of deployment and performance measurement.
- ENGAGEMENT & JOB SATISFACTION: The Data Miners in our survey are highly engaged with the analytic community: consuming and producing content, entering competitions and searching for education and growth within their jobs. All of these activities lead to high job satisfaction, which has been increasing over time.
- ANALYTIC SOFTWARE: Data miners are a diverse group who are looking for different things from their data mining tools. Ease-of-use and cost are two distinguishing dimensions. Software packages vary in their strengths and features. STATISTICA, KNIME, SAS JMP and IBM SPSS Modeler all receive high satisfaction ratings.
- OTHER FINDINGS include the labels analytic professionals use to describe themselves (Data Scientist is #1), the algorithms being used (regression, decision trees, and cluster analysis continue to be the triad of core algorithms), and computing environments (cloud computing is increasing).
I submitted a poster to User2013 that was accepted on Teaching R in India- but I could not attend since I was in Canada visiting family at that time
These were some of the experiences I wanted to talk about- but I think I will elaborate on them later
I founded the New Delhi R Users group almost a year ago. It now has 183 members, and we recently held our first Noida Chapter meeting ( Delhi is a huge area, with Noida and Gurgaon as two adjoining suburban hubs). The response was terrific many people attended.
The sessions were divided in two- for beginners and advanced users
This was the agenda
We invite you on the R learning session at Apsidata Solutions on 7th Dec 2013 from 2:30PM-5:00PM.
Our purpose is to cover up the basics of R and its current market and business scope.
We have divided the session in 2 parts-
(PART – I) Introduction and basics graphs of R (by Su from 2:30PM – 3:30PM)
· Basic Introduction
· Introduction of Statistical Analysis
· Installation of R
· What is Package and how to install and use it.
· Importing Data in R
· Hands-on inbuilt functions
Half an hour break for discussion and queries (from 3:30PM -4:00PM)
(PART – II) – What’s new in R and its market (by Ajay Ohri from 4:00PM – 5:00PM)
· Rattle-Data mining
· R-Studio Sever
These were the slides
Overall, we trying hard to develop the R ecosystem in a Microsoft ruled country 🙂
Credit- Wikipedia and Google Plus Maths Community
The road to Carnegie Hall
Illusion- Each of the dots are actually moving in straight line -Also used for Christmas Lights
Sine and Cosine
Tesseracts (not from Asgard)
Pythagoras Theorem- Greek Math
Simple Way to Teach Pi
Monte Carlo to Estimate Pi
- Facebook Page Insights- Cool Viz- Blue Line Graphs
- WordPress prefers bar plots and spatial analysis (if only minimal)
- Google Activity Dashboard prefers Tufte (?) . No it just shows fonts, and even a (gasp) pie chart.
- Scribd prefers —yes tables and line graphs rule
- Slideshare Stats are a pro feature (!) . Free features are a table– sigh
- LinkedIn – was a pioneer but now
- Linkedin Groups viz
- Quora Stats – hmm
- My Anti Virus still likes doughnuts
- OFFICIAL Twitter Analytics
- Google Analytics – a synonym for data vizualization on the web has Napolean March Chart ambitions but fails to simplify beyond the simple and fails totally at the complex .
- That’s a pie chart, bitches!
- There is no data that can be displayed in a pie chart, that cannot be displayed BETTER in some other type of chart.” John Tukey