Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

August 22, 2016

First Amendment Secondary? [Full Text – Response to Stay]

Filed under: Censorship,Free Speech,Government — Patrick Durusau @ 8:49 pm

Backpage.com defies sex trafficking subpoena despite Senate contempt vote by David Kravets.

From the post:

The First Amendment has been good, really good to the online classified ads portal Backpage.com. In 2015, the US Constitution helped Backpage dodge a lawsuit from victims of sex trafficking. What’s more, a federal judge invoked the First Amendment and crucified an Illinois sheriff—who labeled Backpage a “sex trafficking industry profiteer”—because the sheriff coerced Visa and Mastercard to refrain from processing payments to the site. The judge said Cook County Sheriff Thomas Dart’s anti-Backpage lobbying amounted to “an informal extralegal prior restraint of speech” because Dart’s actions were threatening the site’s financial survival.

But the legal troubles didn’t end there for Backpage, which The New York Times had labeled “the leading site for trafficking of women and girls in the United States.”

Kravets does a great job of linking to the primary documents in this case and while quoting from the government’s response to the request for a stay, does not include a link for the government’s response.

For your research and reading convenience, RESPONSE IN OPPOSITION [1631269] filed by Senate Permanent Subcommittee on Investigations to motion to stay case. A total of 128 pages.

In that consolidated document, Schedule A of the subpoena runs from page 40 to page 50, although the government contends in its opposition that it tried to be more reasonable that it appears.

Even more disturbing than the Senate’s fishing expedition into the records of Backpage is the justification for disregarding the First Amendment:

The Subcommittee is investigating the serious problem of human trafficking on the Internet—much of which takes place on Backpage’s website—and has subpoenaed Mr. Ferrer for documents relating to Backpage’s screening for illegal trafficking. It is important for the Subcommittee’s investigation of Internet sex trafficking to understand what methods the leading online marketplace for sex advertisements employs to screen out illegal sex trafficking on its website. Mr. Ferrer has no First Amendment right to ignore a subpoena for documents about Backpage’s business practices related to that topic. He has refused to identify his First Amendment interests except in sweeping generalities and failed even to attempt to show that any such interests outweigh important governmental interests served by the Subcommittee’s investigation. Indeed, Mr. Ferrer cannot make any balancing argument because he refused to search for responsive documents or produce a privilege log describing them, claiming that the First Amendment gave him blanket immunity from having to carry out these basic duties of all subpoena respondents.

As serious a problem as human trafficking surely is, there are no exceptions to the First Amendment because a crime is a serious one. Just as there are no exceptions to the Fourth or Fifth Amendments because a crime is a serious one.

If you are interested in the “evidence” cited against Backpage, S. Hrg. 114–179 Human Trafficking Investigation (November 2015), runs some 260 pages, details the commission of illegal human trafficking by others, not Backpage.

Illegal sex traffic undoubtedly occurs in the personal ads of the New York Times (NYT) but the Senate hasn’t favored the NYT with such a subpoena.

Kravets reports Backpage is due to respond to the government by 4:00 p.m. Wednesday of this week. I will post a copy of that response as soon as it is available.

Regexer [JavaScript Regexes – Railroad Diagrams]

Filed under: Javascript,Regexes — Patrick Durusau @ 4:43 pm

Regexer

From the documentation page:

The images generated by Regexper are commonly referred to as “Railroad Diagrams”. These diagram are a straight-forward way to illustrate what can sometimes become very complicated processing in a regular expression, with nested looping and optional elements. The easiest way to read these diagrams to to start at the left and follow the lines to the right. If you encounter a branch, then there is the option of following one of multiple paths (and those paths can loop back to earlier parts of the diagram). In order for a string to successfully match the regular expression in a diagram, you must be able to fulfill each part of the diagram as you move from left to right and proceed through the entire diagram to the end.

As an example, this expression will match “Lions and tigers and bears. Oh my!” or the more grammatically correct “Lions, tigers, and bears. Oh my!” (with or without an Oxford comma). The diagram first matches the string “Lions”; you cannot proceed without that in your input. Then there is a choice between a comma or the string ” and”. No matter what choice you make, the input string must then contain ” tigers” followed by an optional comma (your path can either go through the comma or around it). Finally the string must end with ” and bears. Oh my!”.

js-regex-example-460

JavaScript-style regular expression input and railroad diagram output.

Can you think of a better visualization for teaching regexes? (Or analysis when they get hairy.)

What is a Stingray?

Filed under: Cybersecurity,Privacy — Patrick Durusau @ 4:16 pm

Pitched at an adult Sunday School level, which makes this perfect for informing the wider public about government surveillance issues.

Share this video far and wide!

For viewers who want more detail, direct them to: How IMSI Catchers Work by Jason Hernandez.

Every group has a persecution story so tie present day government surveillance to “…what if (historical) X had surveillance…” to drive your point home.

U.K. Parliament – U.S. Congress : Legislative Process Glossaries

Filed under: Glossary,Government,Law,Legal Informatics — Patrick Durusau @ 3:57 pm

I encountered the glossary for legislative activity for the U.S. Congress and remembered a post where I mentioned a similar resource for the U.K.

Rather than having to dig for both of them in the future:

U.K. Parliment – Glossary

U.S. Congress – Glossary

To be truly useful, applications displaying information from either source should automatically tag these terms for quick reference by readers.

Enjoy!

Marketing Vulnerabilities (The Shadow Brokers)

Filed under: Cybersecurity,Security — Patrick Durusau @ 3:41 pm

Auction File: Only Worth What Someone Is Willing To Pay (August 22)

Another update on the Shadow Brokers saga and following auction. For hackers who aren’t also MBA’s, some insight into auction markets for vulnerabilities.

From the post:

There are so many facets to the recent Shadow Brokers’ leak it can be a bit overwhelming. But the Shadow Brokers’ mess does highlight front and center the importance of the perceived value of exploits and vulnerabilities. It is impossible to ignore the value of the exploits when this whole situation is potentially about an auction of high-end vulnerabilities.

In each RBS blog update covering the leak, we have provided a quick update on the auction status, and the reality is that the auction itself isn’t going very well. The leaked data auction recently showed an increase to 1.74847373 BTC (about US$1017.47), jumping from 41 to 56 bids:

You may find all the marketing data gathered here useful but as far as this auction, I suspect this captures the reality of the situation:


If this auction really contains valuable 0-day exploits, then one would expect that this would be worth bidding on for sure. But the parameters of the auction are far from standard, and may be one of the many reasons that the auction isn’t proceeding quickly. Rather than a traditional auction where a losing bid means your bid is returned and you lose no money, any bid on this data is not refunded if you do not win. It is also important to note that many believe that this really isn’t about an auction at all, rather to make a statement.

There may be valuable 0-day exploits but it isn’t possible to value them sight unseen.

Noting that reassurances from someone who allegedly stole from the NSA, don’t fill me with a sense of confidence.

If there are 0-days the NSA concealed, that the Shadow Brokers reveal, that open up the banking industry like a gumball machine:

gumball-smash-460

do you know the name for the agent for service of process at the NSA?

😉

September 1, 2016 – Increase Tor’s Bandwidth

Filed under: Cybersecurity,Security,Tor — Patrick Durusau @ 12:26 pm

Reports of government surveillance and loss of privacy are so common it’s hard to sustain moral outrage over them.

Tor offers involvement to treat impotent moral outrage!

You can donate $$, bandwidth, or volunteer to help the Tor project!

Lose that moral outrage ED! Make a difference at the Tor project!

September 1, 2016 is important because of a call for a 24-hour boycott of Tor on that day.

The use of innocent Tor users as hostages speaks volumes about any boycott of Tor and its supporters.

August 21, 2016

EasyCrypt Reference Manual

Filed under: Cryptography,Cybersecurity — Patrick Durusau @ 4:56 pm

EasyCrypt Reference Manual (PDF)

For your reading convenience, I have emended the hyperlinks in the introduction to point to online versions of the citations and not to the paper’s bibliography.

From the introduction:

EasyCrypt [BDG+14, BGHZ11] is a framework for interactively finding, constructing, and machine-checking security proofs of cryptographic constructions and protocols using the codebased sequence of games approach [BR04, BR06, Sho04]. In EasyCrypt, cryptographic games and algorithms are modeled as modules, which consist of procedures written in a simple userextensible imperative language featuring while loops and random sampling operations. Adversaries are modeled by abstract modules—modules whose code is not known and can be quantified over. Modules may be parameterized by abstract modules.

EasyCrypt has four logics: a probabilistic, relational Hoare logic (pRHL), relating pairs of procedures; a probabilistic Hoare logic (pHL) allowing one to carry out proofs about the probability of a procedure’s execution resulting in a postcondition holding; an ordinary (possibilistic) Hoare logic (HL); and an ambient higher-order logic for proving general mathematical facts and connecting judgments in the other logics. Once lemmas are expressed, proofs are carried out using tactics, logical rules embodying general reasoning principles, and which transform the current lemma (or goal) into zero or more subgoals—sufficient conditions for the original lemma to hold. Simple ambient logic goals may be automatically proved using SMT solvers. Proofs may be structured as sequences of lemmas, and EasyCrypt’s theories may be used to group together related types, predicates, operators, modules, axioms and lemmas. Theory parameters that may be left abstract when proving its lemmas—types, operators and predicates—may be instantiated via a cloning process, allowing the development of generic proofs that can later be instantiated with concrete parameters.

Be aware the documentation carries this warning (1.6 About this Documentation):

This document is intended as a reference manual for the EasyCrypt tool, and not as a tutorial on how to build a cryptographic proof, or how to conduct interactive proofs. We provide some detailed examples in Chapter 7, but they may still seem obscure even with a good understanding of cryptographic theory. We recommend experimenting.

My first time seeing documentation advising “experimenting” to understand it. 😉

You?

Before you jump to Chapter 7, be aware that Chapters 4 Structuring Specifications and Proofs, Chapter 5 EasyCrypt Library, Chapter 6 Advanced Features and Usage, and Chapter 7 Examples, have yet to be written.

You have time to work through the first three chapters and to experiment with EasyCrypt before being called upon to evaluate Chapter 7.

Enjoy!

The Ethics of Data Analytics

Filed under: Data Analysis,Data Science,Ethics,Graphics,Statistics,Visualization — Patrick Durusau @ 4:00 pm

The Ethics of Data Analytics by Kaiser Fung.

Twenty-one slides on ethics by Kaiser Fung, author of: Junk Charts (data visualization blog), and Big Data, Plainly Spoken (comments on media use of statistics).

Fung challenges you to reach your own ethical decisions and acknowledges there are a number of guides to such decision making.

Unfortunately, Fung does not include professional responsibility requirements, such as the now out-dated Canon 7 of the ABA Model Code Of Professional Responsibility:

A Lawyer Should Represent a Client Zealously Within the Bounds of the Law

That canon has a much storied history, which is capably summarized in Whatever Happened To ‘Zealous Advocacy’? by Paul C. Sanders.

In what became known as Queen Caroline’s Case, the House of Lords sought to dissolve the marriage of King George the IV

George IV 1821 color

to Queen Caroline

CarolineOfBrunswick1795

on the grounds of her adultery. Effectively removing her as queen of England.

Queen Caroline was represented by Lord Brougham, who had evidence of a secret prior marriage by King George the IV to Catholic (which was illegal), Mrs Fitzherbert.

Portrait of Mrs Maria Fitzherbert, wife of George IV

Brougham’s speech is worth your reading in full but the portion most often cited for zealous defense reads as follows:


I once before took leave to remind your lordships — which was unnecessary, but there are many whom it may be needful to remind — that an advocate, by the sacred duty of his connection with his client, knows, in the discharge of that office, but one person in the world, that client and none other. To save that client by all expedient means — to protect that client at all hazards and costs to all others, and among others to himself — is the highest and most unquestioned of his duties; and he must not regard the alarm, the suffering, the torment, the destruction, which he may bring upon any other; nay, separating even the duties of a patriot from those of an advocate, he must go on reckless of the consequences, if his fate it should unhappily be, to involve his country in confusion for his client.

The name Mrs. Fitzherbert never slips Lord Brougham’s lips but the House of Lords has been warned that may not remain to be the case, should it choose to proceed. The House of Lords did grant the divorce but didn’t enforce it. Saving fact one supposes. Queen Caroline died less than a month after the coronation of George IV.

For data analysis, cybersecurity, or any of the other topics I touch on in this blog, I take the last line of Lord Brougham’s speech:

To save that client by all expedient means — to protect that client at all hazards and costs to all others, and among others to himself — is the highest and most unquestioned of his duties; and he must not regard the alarm, the suffering, the torment, the destruction, which he may bring upon any other; nay, separating even the duties of a patriot from those of an advocate, he must go on reckless of the consequences, if his fate it should unhappily be, to involve his country in confusion for his client.

as the height of professionalism.

Post-engagement of course.

If ethics are your concern, have that discussion with your prospective client before you are hired.

Otherwise, clients have goals and the task of a professional is how to achieve them. Nothing more.

August 20, 2016

US Army committed $6.5 trillion in accounting fraud in one year (w/correction)

Filed under: Auditing,Government,Transparency — Patrick Durusau @ 8:54 pm

US Army committed $6.5 trillion in accounting fraud in one year by Cory Doctorow.

From the post:

In June, the Defense Department’s Inspector General released a report on the US Army’s accounting, revealing that the Army had invented $6.5 trillion in “improper adjustments” ($2.8T in one quarter!) to make its books appear balanced though it could not account for where the funds had gone.

If you are interested in transparent and trackable information systems, that’s a headline that captures your attention!

Except that when you run it back to the original story, U.S. Army fudged its accounts by trillions of dollars, auditor finds by Scot J. Paltrow, which reads in part:

The United States Army’s finances are so jumbled it had to make trillions of dollars of improper accounting adjustments to create an illusion that its books are balanced.

The Defense Department’s Inspector General, in a June report, said the Army made $2.8 trillion in wrongful adjustments to accounting entries in one quarter alone in 2015, and $6.5 trillion for the year. Yet the Army lacked receipts and invoices to support those numbers or simply made them up.

You won’t find a reference to the “June report,” as cited by Paltrow. No link, no title, no nothing.

In fact, there is no such June report.

If you look carefully enough at the Inspector General site for the DoD you will find:

07-26-2016
Financial Management
Army General Fund Adjustments Not Adequately Documented or Supported (Project No. D2015-D000FL-0243.000)
DODIG-2016-113

The webpage for that July report, reads in part:

Finding

The Office of the Assistant Secretary of the Army (Financial Management & Comptroller) (OASA[FM&C]) and the Defense Finance and Accounting Service Indianapolis (DFAS Indianapolis) did not adequately support $2.8 trillion in third quarter journal voucher (JV) adjustments and $6.5 trillion in yearend JV adjustments1 made to AGF data during FY 2015 financial statement compilation.2 The unsupported JV adjustments occurred because OASA(FM&C) and DFAS Indianapolis did not prioritize correcting the system deficiencies that caused errors resulting in JV adjustments, and did not provide sufficient guidance for supporting system‑generated adjustments.

In addition, DFAS Indianapolis did not document or support why the Defense Departmental Reporting System‑Budgetary (DDRS-B), a budgetary reporting system, removed at least 16,513 of 1.3 million records during third quarter FY 2015. This occurred because DFAS Indianapolis did not have detailed documentation describing the DDRS-B import process or have accurate or complete system reports.

As a result, the data used to prepare the FY 2015 AGF third quarter and yearend financial statements were unreliable and lacked an adequate audit trail. Furthermore, DoD and Army managers could not rely on the data in their accounting systems when making management and resource decisions. Until the Army and DFAS Indianapolis correct these control deficiencies, there is considerable risk that AGF financial statements will be materially misstated and the Army will not achieve audit readiness by the congressionally mandated deadline of September 30, 2017.

Everybody makes mistakes. I’m sure I make several everyday without hardly trying.

However, if you link to original sources, readers stand some chance of discovering and correcting those errors.

If you cite a resource, link to the resource.

PS: Before you use the word “fraud” with regard to military accounting systems, realize financial accounting is not a primary or even secondary concern of a military force. There are possible solutions to military accounting issues but congressional tantrums, a/k/a mandates, aren’t among them.

NASA just made all its research available online for free (Really?)

Filed under: NASA,Open Access,Space Data — Patrick Durusau @ 3:46 pm

NASA just made all its research available online for free by Tim Walker.

Caution: The green colored links in the original post are pop-up ads and not links to content.

From the post:

Care to learn more about 400-foot tsunamis on Mars? Now you can, after Nasa announced it is making all its publicly funded research available online for free. The space agency has set up a new public web portal called Pubspace, where the public can find Nasa-funded research articles on everything from the chances of life on one of Saturn’s moons to the effects of space station living on the hair follicles of astronauts.

In 2013, the White House Office of Science and Technology Policy directed Nasa and other agencies to increase access to their research, which in the past was often available (if it was available online at all) only via a paywall. Now, it is Nasa policy that any research articles funded by the agency have to be posted on Pubspace within a year of publication.

There are some exceptions, such as research that relates to national security. Nonetheless, there are currently a little over 850 articles available on the website with many more to come.

Created in 1958, all of NASA’s research “available online for free,” amounts to approximately 850 documents?

Even starting in 2013, 850 documents seems a bit light.

Truth of the matter is that NASA has created yet another information silo of NASA data.

Here are just a few of the other NASA silos that come to mind right off hand:

Johnson Space Center Document Index System

NASA Aeronautics and Space Database

NASA Documents Online

NASA GALAXIE

NASA Technical Report Server

I don’t know if any of those include data repositories from NASA missions or not. Plus any other information silos NASA has constructed over the years.

I applaud NASA making sponsored research public but building yet another silo to do so seem wrong-headed.

Conversion and replacement of any of these silos is obviously out of the question.

Under taking to map all of them together, for some undefined ROI, seems equally unlikely.

Suggestions on how to approach such a large, extant silo problem?

@rstudio Easter egg: Alt-Shift-K (shows all keyboard shortcuts)

Filed under: R — Patrick Durusau @ 3:19 pm

Carl Schemertmann asks:

rstudio-easter-egg-460

Forty-two people have retweeted Carl’s tweet without answering Carl’s question.

If you have an answer, please reply to Carl. Otherwise, remember:

Alt-Shift-K

shows all keyboard shortcuts in RStudio.

Enjoy!

Everybody Discusses The Weather In R (+ Trigger Warning)

Filed under: Climate Data,Climate Informatics,R,Weather Data — Patrick Durusau @ 3:01 pm

Well, maybe not everybody but if you are interested in weather statistics, there’s a trio of posts at R-Bloggers made for you.

Trigger Warning: If you are a climate change denier, you won’t like the results presented by the posts cited below. Facts dead ahead.

Tracking Precipitation by Day-of-Year

From the post:

Plotting cumulative day-of-year precipitation can helpful in assessing how the current year’s rainfall compares with long term averages. This plot shows the cumulative rainfall by day-of-year for Philadelphia International Airports rain gauge.

Checking Historical Precipitation Data Quality

From the post:

I am interested in evaluating potential changes in precipitation patterns caused by climate change. I have been working with daily precipitation data for the Philadelphia International Airport, site id KPHL, for the period 1950 to present time using R.

I originally used the Pennsylvania State Climatologist web site to download a CSV file of daily precipitation data from 1950 to the present. After some fits and starts analyzing this data set, I discovered that data for January was missing for the period 1950 – 1969. This data gap seriously limited the usable time record.

John Yagecic, (Adventures In Data) told me about the weatherData package which provides easy to use functions to retrieve Weather Underground data. I have found several precipitation data quality issues that may be of interest to other investigators.

Access and Analyze 170 Monthly Climate Time Series Using Simple R Scripts

From the post:

Open Mind, a climate trend data analysis blog, has a great Climate Data Service that provides updated consolidated csv file with 170 monthly climate time series. This is a great resource for those interested in studying climate change. Quick, reliable access to 170 up-to-date climate time series will save interested analysts hundreds – thousands of data wrangling hours of work.

This post presents a simple R script to show how a user can select one of the 170 data series and generate a time series plot like this:

All of these posts originated at RClimate, a new blog that focuses on R and climate data.

Drop by to say hello to D Kelly O’Day, PE (professional engineer) Retired.

Relevant searches at R-Bloggers (as of today):

Climate – 218 results

Flood – 61 results

Rainfall – 55 results

Weather – 291 results

Caution: These results contain duplicates.

Enjoy!

Frinkaic (Simpsons)

Filed under: Humor,Search Engines — Patrick Durusau @ 2:36 pm

Frinkaic

From the webpage:

Frinkiac has nearly 3 million Simpsons screencaps so get to searching for crying out glayvin!

With a link to Morbotron as well.

Once you recover, consider reading: Introducing Frinkiac, The Simpsons Search Engine Built by Rackers by Abe Selig.

Where you aren’t trying to boil the ocean with search, the results can be pretty damned amazing.

235,000 Voices Cried Out And Were Suddenly Silenced

Filed under: Censorship,Free Speech,Government — Patrick Durusau @ 1:19 pm

Yahoo! News carried this report of censorship: Twitter axes 235,000 more accounts in terror crackdown.

From the post:

Twitter on Thursday announced that it has cut off 235,000 more accounts for violating its policies regarding promotion of terrorism at the global one-to-many messaging service.

The latest account suspensions raised to 360,000 the total number of accounts sidelined since the middle of 2015 and was helping “drive meaningful results” in curbing the activity, according to the San Francisco-based company.

Twitter has been under pressure to balance protecting free speech at the service with not providing a stage for terrorist groups to spread violent messages and enlist people to their causes.

The latest account suspensions came since February, when Twitter announced that it had neutralized 125,000 accounts for violating rules against violent threats and promotion of terrorism.

“Since that announcement, the world has witnessed a further wave of deadly, abhorrent terror attacks across the globe,” Twitter said in a blog post.

When you read Twitter’s blog post, An update on our efforts to combat violent extremism, out of 235,000 accounts, how many are directly tied to a terrorist attack?

Would you guess:


235,000?

150,000?

100,000?

50,000?

25,000?

10,000?

5,000?

Twitter reports 0 accounts as being tied to terrorist attacks.

Odd considering that Twitter says:

Since that announcement, the world has witnessed a further wave of deadly, abhorrent terror attacks across the globe

“…wave of deadly, abhorrent terror attacks…” What wave?

From March of 2016 until July 31, the List of terrorist incidents, 2016 lists some 864 attacks.

A far cry from the almost 1/4 million silenced accounts.

Of course, “terrorism” depends on your definition, the Global Terrorism Database lists over 6,000 terrorist attacks for the time period March 2015 until July 31, 2015.

Even using 2015’s 6,000 attack figure, that’s a long way from 235,000 Twitter accounts.

If you think “…wave of deadly, abhorrent terror attacks…” is just marketing talk on the part of Twitter, the evidence is on your side.

Anyone who thinks they may be in danger of being silenced by Twitter should obtain regular archives of their tweets. Don’t allow your history to be stolen by Twitter.

I do have a question for anyone working on this issue:

Are there efforts to create a non-Twitter servers that make fair use of the Twitter API, so that archives of tweets and/or even new accounts, could continue silenced accounts? Say a Dark Web Not-Twitter Server?

I ask because Twitter continues to demonstrate that “free speech” is subject to its whim and caprice.

A robust and compatible alternative to Twitter, especially if archives can be loaded, would enable free speech for many diverse groups.

August 19, 2016

Top Ten #ddj:… [18 August 2016]

Filed under: Journalism,News,Reporting — Patrick Durusau @ 8:34 pm

Top Ten #ddj: The Week’s Most Popular Data Journalism Links

A weekly feature of the Global Investigative Journalism Network and particularly good this week:

  • Animated Data Visualisation: Trends in Household Debts Reveals a Constant Increase in Student Loans
  • Discover Why and How The New York Times is Changing the Way They Present Interactive Content
  • Analysis of Trump’s Tweets: Trump Writes Angrier Tweets on Android While His Staff Tweets More Positively On His Behalf Using an iPhone
  • Analysis of Trump’s Tweets: Sharp Decline in Trump’s Own Tweets from 77 to 24 percent Suggests Tighter Campaign Control
  • Open Data-Driven Articles Using Olympic Data: Edit the Source Code and Create Your Own Visualisations
  • Interactive Map of Recreational Areas in Ravensburg, Germany
  • Onodo: Network Visualisation and Analysis Tool for Non-Tech Users
  • Opinion: Not Every Venn Diagram Has Something Worth Reporting
  • Data on Teenage Pregnancies and HIV rates in Kenya
  • Mapbox: How to Customise and Embed Maps on Websites

See the original post for links and very annoying “share” options. (Annoying to me, others may find them indispensable.)

Mark your calendars to check for new top ten lists and/or follow @gijn.

Typography for User Interfaces

Filed under: Design,Typography — Patrick Durusau @ 7:45 pm

Typography for User Interfaces by Viljami Salminen.

From the post:

Back in 2004, when I had just started my career, sIFR was the hottest thing out there. It was developed by Shaun Inman and it embedded custom fonts in a small Flash movie, which could be utilized with a little bit of JavaScript and CSS. At the time, it was basically the only way to use custom fonts in browsers like Firefox or Safari. The fact that this technique relied on Flash soon made it obsolete, with the release of the iPhone (without flash) in 2007.

Our interfaces are written, text being the interface, and typography being our main discipline.

In 2008, browsers started eventually supporting the new CSS3 @font-face rule. It had already been a part of the CSS spec in 1998, but later got pulled out of it. I remember the excitement when I managed to convince one of our clients to utilize the new @font-face and rely on progressive enhancement to deliver an enhanced experience for browsers which already supported this feature.

Since my early days in the industry, I’ve grown to love type and all the little nuances that go into setting it. In this article, I want to share some of the fundamentals that I’ve learned, and hopefully help you get better at setting type for user interfaces.

A nice stroll through the history of typography for user interfaces.

With ten (10) tips on choosing a typeface for a UI.

Enjoy and produce better UIs!

29 common beginner Python errors on one page [Something Similar For XQuery?]

Filed under: Programming,Python — Patrick Durusau @ 3:55 pm

29 common beginner Python errors on one page

From the webpage:

A few times a year, I have the job of teaching a bunch of people who have never written code before how to program from scratch. The nature of programming being what it is, the same error crop up every time in a very predictable pattern. I usually encourage my students to go through a step-by-step troubleshooting process when trying to fix misbehaving code, in which we go through these common errors one by one and see if they could be causing the problem. Today, I decided to finally write this troubleshooting process down and turn it into a flowchart in non-threatening colours.

Behold, the “my code isn’t working” step-by-step troubleshooting guide! Follow the arrows to find the likely cause of your problem – if the first thing you reach doesn’t work, then back up and try again.

Click the image for full-size, and click here for a printable PDF. Colour scheme from Luna Rosa.

Useful for Python beginner’s and should be inspirational for other languages.

Thoughts on something similar for XQuery Errors? Suggestions for collecting the “most common” XQuery errors?

What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning?

Filed under: Artificial Intelligence,Deep Learning,Machine Learning — Patrick Durusau @ 3:37 pm

What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning? by Michael Copeland.

From the post:

Artificial intelligence is the future. Artificial intelligence is science fiction. Artificial intelligence is already part of our everyday lives. All those statements are true, it just depends on what flavor of AI you are referring to.

For example, when Google DeepMind’s AlphaGo program defeated South Korean Master Lee Se-dol in the board game Go earlier this year, the terms AI, machine learning, and deep learning were used in the media to describe how DeepMind won. And all three are part of the reason why AlphaGo trounced Lee Se-Dol. But they are not the same things.

The easiest way to think of their relationship is to visualize them as concentric circles with AI — the idea that came first — the largest, then machine learning — which blossomed later, and finally deep learning — which is driving today’s AI explosion — fitting inside both.

If you are confused by the mix of artificial intelligence, machine learning, and deep learning, floating around, Copeland will set you straight.

It’s a fun read and one you can recommend to non-technical friends.

Report of the Bulk Powers Review

Filed under: Government,Privacy — Patrick Durusau @ 2:55 pm

Report of the Bulk Powers Review (PDF) by David Anderson Q.C. Independent Reviewer of Terrorism Legislation. (Web version)

From its webpage:

This report includes the findings of the independent review of the operational case for bulk powers, which will inform scrutiny of the Investigatory Powers Bill.

If you find yourself dissatisfied with the sound bite and excerpt commentaries on this report, you may find the two hundred and three (203) full version more to your likely. At least in terms of completeness.

I have glanced at the conclusions but will refrain from commenting until reading the report in full. It is possible that Anderson will persuade me to change my initial impressions, although I concede that is highly unlikely.

TLDR pages [Explanation and Example Practice]

Filed under: Documentation,Linux OS — Patrick Durusau @ 2:16 pm

TLDR pages

From the webpage:

The TLDR pages are a community effort to simplify the beloved man pages with practical examples.

Try the live demo below, have a look at the pdf version, or follow the installing instructions.

Be sure to read the Contributing guidelines.

I checked and ngrep isn’t there. 🙁

Well, ngrep only has thirty (30) options and switches before you reach <match expression> and <bpf filter>, so how much demand could there be for examples?

😉

Great opportunity to practice your skills at explanation and creating examples.

Contributing to StackOverflow: How Not to be Intimidated

Filed under: Data Science,Programming — Patrick Durusau @ 12:43 pm

Contributing to StackOverflow: How Not to be Intimidated by Ksenia Coulter.

From the post:

StackOverflow is an essential resource for programmers. Whether you run into a bizarre and scary error message or you’re blanking on something you should know, StackOverflow comes to the rescue. Its popularity with coders spurred many jokes and memes. (Programming to be Officially Renamed “Googling Stackoverflow,” a satirical headline reads).

(image omitted)

While all of us are users of StackOverflow, contributing to this knowledge base can be very intimidating, especially to beginners or to non-traditional coders who many already feel like they don’t belong. The fact that an invisible barrier exists is a bummer because being an active contributor not only can help with your job search and raise your profile, but also make you a better programmer. Explaining technical concepts in an accessible way is difficult. It is also well-established that teaching something solidifies your knowledge of the subject. Answering StackOverflow questions is great practice.

All of the benefits of being an active member of StackOverflow were apparent to me for a while, but I registered an account only this week. Let me walk you t[h]rough thoughts that hindered me. (Chances are, you’ve had them too!)

I plead guilty to using StackOverFlow but not contributing back to it.

Another “intimidation” to avoid is thinking you must have the complete and killer answer to any question.

That can and does happen, but don’t wait for a question where you can supply such an answer.

Jump in! (Advice to myself as well as any readers.)

Re-Use, Re-Use! Using Weka within Lisp

Filed under: Lisp,Machine Learning,Weka — Patrick Durusau @ 12:24 pm

Suggesting code re-use, as described by Paul Homer in The Myth of Code Reuse, provokes this reaction from most programmers (substitute re-use for refund):

😉

Atabey Kaygun demonstrates he isn’t one of those programmers in Using Weka within Lisp:

From the post:

As much as I like implementing machine learning algorithms from scratch within various languages I like using, in doing serious research one should not take the risk of writing error-prone code. Most likely somebody already spent many thousand hours writing, debugging and optimizing code you can use with some effort. Re-use people, re-use!

In any case, today I am going to describe how one can use weka libraries within ABCL implementation of common lisp. Specifically, I am going to use the k-means implementation of weka.

As usual, well written and useful guide to using Weka and Lisp.

The issues of code re-use aren’t confined to programmers.

Any stats you can suggest on re-use of database or XML schemas?

Readable Regexes In Python?

Filed under: Python,Regex — Patrick Durusau @ 10:45 am

Doug Mahugh retweeted Raymond Hettinger tweeting:

#python tip: Complicated regexes can be organized into readable, commented chucks.
https://docs.python.org/3/library/re.html#re.X

Twitter hasn’t gotten around to censoring Python related tweets for accuracy so I did check the reference:

re.X
re.VERBOSE

This flag allows you to write regular expressions that look nicer and are more readable by allowing you to visually separate logical sections of the pattern and add comments. Whitespace within the pattern is ignored, except when in a character class or when preceded by an unescaped backslash. When a line contains a # that is not in a character class and is not preceded by an unescaped backslash, all characters from the leftmost such # through the end of the line are ignored.

This means that the two following regular expression objects that match a decimal number are functionally equal:

Which is the better question?

Why would anyone want to produce a readable regex in Python?

or,

Why would anyone NOT produce a readable regex given the opportunity?

Enjoy!

PS: It occurs to me that with a search expression you could address such strings as subjects in a topic map. A more robust form of documentation than # syntax.

Is UC-San Diego Running A Military Commission?

Filed under: Government,Law — Patrick Durusau @ 10:22 am

Will UC-San Diego keep hiding witnesses that could prove accused students innocent? by Greg Piper.

From the post:

The University of California-San Diego routinely hides the identity of witnesses that could help students accused of wrongdoing exonerate themselves, departing from its own rules on who is “relevant” to an investigation.

This policy, which has been applied against accused students for at least the past five years, was not publicly known until 11 months ago. A state appeals court fleshed out its existence in a due-process lawsuit against the school by a student who was found responsible for cheating and expelled.

That court struck down UCSD’s ruling against Jonathan Dorfman, saying it had no legal reason to withhold the identity of “Student X” – whose test answers Dorfman allegedly copied – from him.

Arguing before the court, the UC System’s own lawyer admitted that the school had never bothered to ask Student X where he was sitting in class that day in 2011 – potentially preempting its case against Dorfman.

UC-San Diego has copied the government’s use of “secret” evidence in U.S. military commissions.

Here UC-San Diego decided who or what was “relevant” to its inquiry, saying:

When a female judge suggests that UCSD decided “this was enough and we’re not going to give the information to the defense to try to poke holes in it,” Goldstein responds with apparent earnestness: “That is the procedure here.”

If U.S. prosecutors were so honest, they would echo:

we’re not going to give the information to the defense to try to poke holes in it,

That works, only if you have a presumption of guilt. So far as I know, lip service is still payed to the presumption of innocence.

If prosecutors want a presumption of guilt, they should argue for it openly, and not conceal that as well.

August 18, 2016

Using Search Terms and Facets on Congress.gov (Video) (Evaluation Help?)

Filed under: Library — Patrick Durusau @ 7:39 pm

Using Search Terms and Facets on Congress.gov (Video)

I would love to tell you about the contents of this video!

However, not having Flash is the only effect way to defeat Flash vulnerabilities.

Adobe advises 1.3 billion people are vulnerable to Flash security issues but I am not one of them.

If you care to review this resources and submit comments, I would appreciate it.

National Food Days

Filed under: Food,Graphics,Visualization — Patrick Durusau @ 2:12 pm

All the National Food Days by Nathan Yau.

Nathan has created an interactive calendar of all the U.S. national food days.

Here is a non-working replica to entice you to see his interactive version:

national-food-days-460

What’s with July having a national food day every day?

Lobby for your favorite food and month!

Rich Hickey and Brian Beckman – Inside Clojure (video)

Filed under: Clojure,Lisp — Patrick Durusau @ 1:43 pm

From the description:

Clojure is a dynamic programming language created by Rich Hickey that targets both the Java Virtual Machine and the CLR. It is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language – it compiles directly to JVM bytecode, yet remains completely dynamic. Every feature supported by Clojure is supported at runtime. Clojure provides easy access to the Java frameworks, with optional type hints and type inference, to ensure that calls to Java can avoid reflection.

Clojure is a dialect of Lisp, and shares with Lisp the code-as-data philosophy and a powerful macro system. Clojure is predominantly a functional programming language, and features a rich set of immutable, persistent data structures. When mutable state is needed, Clojure offers a software transactional memory system and reactive Agent system that ensure clean, correct, multithreaded designs.

Astrophysicist and Software Architect Brian Beckman interviews Rich Hickey to dig into the details of this very interesting language. If you don’t know much about Clojure and the general problems it aims to solve, well, watch and listen carefully to this great conversation with plenty of whiteboarding and outstanding questions. Expert to Expert simply rocks! Thank you for spending time with us, Rich! Clojure is great!

From 2013 but what a nice find for a Thursday afternoon!

Do you know the origin of “conj” in Clojure? 😉

Enjoy!

Why “We” Get Hacked

Filed under: Cybersecurity,Security — Patrick Durusau @ 10:52 am

Whether these are “authentic” tweets or not, I cannot say. However, I thought the rather pinched definition of “we” needed to be pointed out.

snowden-nsa-hack-460

Say rather:

#NSA left catastrophic flaws in all networks for 3+ years to aid offense, rather than fixing them

If any of us are insecure, then all of us are insecure.

When it comes to cybersecurity, check your nationalism at the door, or we will all be insecure.

August 17, 2016

Grokking Deep Learning

Filed under: Deep Learning,Military,Numpy,Python — Patrick Durusau @ 8:58 pm

Grokking Deep Learning by Andrew W. Trask.

From the description:

Artificial Intelligence is the most exciting technology of the century, and Deep Learning is, quite literally, the “brain” behind the world’s smartest Artificial Intelligence systems out there. Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champion Go player, achieving superhuman performance on video games, driving cars, translating languages, and sometimes even helping law enforcement fight crime. Deep Learning is a revolution that is changing every industry across the globe.

Grokking Deep Learning is the perfect place to begin your deep learning journey. Rather than just learn the “black box” API of some library or framework, you will actually understand how to build these algorithms completely from scratch. You will understand how Deep Learning is able to learn at levels greater than humans. You will be able to understand the “brain” behind state-of-the-art Artificial Intelligence. Furthermore, unlike other courses that assume advanced knowledge of Calculus and leverage complex mathematical notation, if you’re a Python hacker who passed high-school algebra, you’re ready to go. And at the end, you’ll even build an A.I. that will learn to defeat you in a classic Atari game.

In the Manning Early Access Program (MEAP) with three (3) chapters presently available.

A much more plausible undertaking than DARPA’s quest for “Explainable AI” or “XAI.” (DARPA WANTS ARTIFICIAL INTELLIGENCE TO EXPLAIN ITSELF) DARPA reasons that:


Potential applications for defense are endless—autonomous aerial and undersea war-fighting or surveillance, among others—but humans won’t make full use of AI until they trust it won’t fail, according to the Defense Advanced Research Projects Agency. A new DARPA effort aims to nurture communication between machines and humans by investing in AI that can explain itself as it works.

If non-failure is the criteria for trust, U.S. troops should refuse to leave their barracks in view of the repeated failures of military strategy since the end of WWII.

DARPA should choose a less stringent criteria for trusting an AI. However, failing less often than the Joint Chiefs of Staff may be too low a bar to set.

R Markdown

Filed under: R,R Markdown — Patrick Durusau @ 8:41 pm

R Markdown

From the webpage:

R Markdown provides an authoring framework for data science. You can use a single R Markdown file to both

  • save and execute code
  • generate high quality reports that can be shared with an audience

R Markdown documents are fully reproducible and support dozens of static and dynamic output formats. This 1-minute video provides a quick tour of what’s possible with R Markdown:

I started to omit this posting, reasoning that with LaTeX and XML, what other languages for composing documents are really necessary?

😉

I don’t suppose it will hurt to have a third language option for your authoring needs.

Enjoy!

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