HONEYBOT EXPERIMENT
Intro
I wanted to build a machine that would be the subject of the attacks from the web. These attacks could actually show people what is going on. I think that a huge first step for teaching about what goes on “in the dark” is to just show it to them. I wanted to find a way to do that.
First, I looked into a web manipulator, but almost immediately realized that it was too much of a risk on my computer and my personal network
I consulted some coworkers who have significantly more experience in this field than myself. Thomas Jack, a network analyst and enthusiast for data security and privacy; and Brendan Vincelli, a talented developer and enthusiast for open source and the open data movement. Almost immediately they were excited to be a part of this experiment.
Quickly they explained to me that a web browser going around acting naively is not actually a good example of how data privacy is breached or broken. A much better example would be to show how a server gets attacked.
Brendan showed me a tool called “Damn Vulnerable Web App”, which is a training tool for network security people to practice their hacking skills in a safe environment.
The webapp is itself vulnerable, and thus I decided it would be a good guineapig. I went to a hosting site called “Digital Ocean” similar to AWS or google servers, but more hands-off (to allow hacking to occur). A server on Digital Ocean is pretty cheap, at about 22 cents per hour, and is referred to as a droplet. I set up my droplet and began immediately to prepare for the extraction of data.
My plan: Collect all the syslogs, copy the syslogs to a google drive folder of a falsified account on google (for security purposes). Set Cron to run the copy script every 20 minutes (No idea how often I would get hacked, or how long until someone broke the machine). As a final measure, make snapshots of the machine to ensure that I can “roll back” to a previous version in the case that someone had a “Home Run” and my computer’s root access was taken from me.
With script in hand and a vulnerable server I was set to go. But as soon as I started I visited the server itself. This wasn’t a fake app or a fake website, like I had hoped it would be (like a hosted store where someone could try their hand at stealing data). This was a training terminal. Disappointed, I shut down the droplet and went back to the drawing board.
I locked down everything and went searching for a decent way to capture data about malicious online activity. After all my reading I was certain that there is something already made. I don’t need my machine to be destroyed, I just want to see what people try to do.
By a stroke of luck in my research, I came upon an open source repository made by T Mobile. I heard that developers from many European companies (especially infosec) had been encouraged to write code and contribute to the open source community. This must be one of those projects, I thought to myself. It did not have very much documentation, and it used other well-known open source tools (Including my favourite, Elasticsearch).
I downloaded and read through the files in the repository and set out to install it on my machine. I was hesitant at first – since it seemed that this would completely erase my work thus far on my virtual machine. Not only that, but it could also get me banned. Generally, these hosting sites don’t want malicious activity on their servers. I took the risk anyways.
The installation process was difficult, and once the machine was installed and prepared, it didn’t work. It seems that in order for this to work, I would need to allocate more resources.  Success! The machine was alive and well!
Three hours later It was down again. Hacked – defeated. The honeypot had been got. I was devastated, frantically trying to get access to my creation again. When I did get online I saw I had an uninvited visitor, and in a panic I immediately disconnected and erased the machine. I started the whole process again, but this time with a seriously tough password. It was generated out of a hashing program, and it is super long. From what I have learned about brute force algorithms, this would take at least a month to crack – more than enough time to blacklist an attacker.
With the machine up and running for 48 hours I was blown away by the numbers. My machine had been attacked ONE MILLION TIMES. I leaned back in my chair and took a deep breath. It was unbelievable. Most of it was from china, of course. As I peeled deeper into the data, however , I saw so many surprising sources. So many corporations and organizations were tied to these attacks.
Of course, those companies are likely uninvolved. A hacker might just use those DNS names to hide their own identity. It’s unlikely a botnet would actually have its owner’s information attached to the headers of the attack. No one is that dumb.
Background
How aware are you of data privacy as an issue? How does technological literacy relate to that awareness? People tend to trust their apps because of a social investment in the technology. In Germany, for instance, a study was done with 674 responding student participants mostly from the University of Salzburg was conducted (Fuchs, 177). This study featured a series of questions presented to both undergraduate and graduate students to assess their knowledge or understanding of data privacy. The results of the study showed that 16.5% of students had zero of potential four correct answers, implying no understanding of data privacy and surveillance; 65.3% had one, implying a very low level of understanding; 16.5% had two correct answers; and 1.8% had all three correct answers, showing a good understanding of data privacy and surveillance (Fuchs, 178).
In 2013, a European study called Eurobarometer was conducted with 16,244 EU citizens from several countries (Sobolewski, 211). In that group, 80% felt not in control over their own personal data. Of that 80%, 66% felt concerned about that fact (Sobolewski, 211). While that suggests an interest in their own data privacy, that same study showed that these participants were willing to hand over their personal data in exchange for very little compensation (Sobolewski, 212). Eurobarometer conducted an adjacent study which found that Europeans are not taking the simplest actions to protect themselves, such as changing their privacy settings on their social media platforms (Sobolewski, 212). This is referred to as the “Privacy Paradox” (Sobolewski, 212).
In the wake of massive data leaks from Facebook, Ashley Madison, Target, and Equifax, users are clearly concerned about their data privacy (Fairclough, 1). Users might not take action to protect themselves – but the users also might not know enough to be able to take action. Users clearly want more protection, more privacy, and more security. That being said, they might not even know how to ask for more privacy.
Council of Europe Data Privacy Convention (Greenleaf, 68). The groundwork set by these two large pieces of legislature would eventually grow into a cohesive data privacy plan that would inspire countries around the world to follow suit (Greenleaf, 70). The number of data privacy laws enforced in the EU grew from the 1980’s through to today. In 1970, there were 8 data privacy laws; in the 1980’s, 13 new laws were introduced; in the 2000’s, 21 new laws were introduced; and between 2010 and 2012, 12 new laws had been introduced (Greenleaf, 69).
Of those new laws, was the Information Privacy Act (IPA), which focused on Health Education and Welfare of European people (Greenleaf, 71). The IPA plainly stated, “Data collected for one purpose should not be used or made available for other purposes without consent" (Greenleaf, 71). The Data Protection Directive, which later produced the Data Protection Agency (DPA), added significantly stronger protections to Data Privacy (Greenleaf, 68). The DPA today is part of the EU’s international Data policy when discussing data. The rules that the DPA laid out for a country to be considered to have sufficient data privacy laws in place are as follows: Does that country have a national law that monitors public and private sectors; are there basic data privacy principles (according to OECD Guielines); and is there a statutory enforcement for these laws (Greenleaf, 69).
From a privacy and security standpoint, Convention 108 from the Council of Europe is the most significant addition to a legal corpus supporting users. Convention 108 is “the convention for the protection of individuals with regard to automatic processing of personal data” (Greenleaf, 81). In other words, protections against growing Machine Learning and Artificial Intelligence methods of data processing. In addition to machine learning, Convention 108 seeks to limit the countries where that data can go. It would behave a lot like border security for data in and out of the EU and supported countries. Not allowing specific traffic in or out of these countries on a base legal level means that the ability for producers of data insights and machine learning tools, which house our personal identifiable data, to defend against and prosecute breaches of privacy is enhanced significantly.
'Black Code' by Ronald Deibert goes much more in depth to various other kinds of espionage and sale of data, which is interesting as a reader, but not to my thesis. The book is a recount of deibert’s lab, ‘Citizen Labs’ which investigates activity on the web that is kept from our view. His lab receives lots of criticism from governments, scholars, and corporations – and yet it also is simply the lab trying to learn what they can about the web. What was so interesting about this book was not only the massive conspiracies the lab uncovered, but the degree to which governments don’t want Deibert to be investigating or exposing the activity on the web.
In terms of the display of the information that I gathered, I turn to the grandfathers of Data Visualization. Edward Tufte and Jaques Bertin are the two most prolific researchers in this field – laying out the forms and structures, basic principles, and best practices of the Visual Representation of data.
In Tufte’s book, ‘The Visual Display of Quantitative Information’, Tufte delivers an encyclopedic tome of visualization rules and definitions. These Definitions include the eight visual variables: Size, Colour, Value, Orientation, Shape , Position, Pattern, and Texture. He also sets up the rules of what makes an ‘efficient’ visualization.
In Bertin’s book, ‘Semiology of Graphics, Diagrams, Networks, Maps’, the focus for Bertin is on the levels of reading a visualization. Bertin provides the framework for visual stimuli, broken into three categories: Monosemic, Polysemic, and Pansemic. He follows up by explaining the three levels of reading or understanding a visualization: Elementary, Intermediate and Overall. These three levels are more like stages rather than actual levels, but they make testing for efficiency much easier.
I want to explore some of these tools for visualization in my thesis.
Setup
The setup for the HONEYBOT Experiment is made in three parts. The first part is the actual virtual machine. It has 6 gigs of ram, 120 gigs of storage, 4 VCPU’s and no added security. The original machine that I used was smaller, with fewer resources, but it crashed far too quickly. It seems that the T-Pot software takes a significant amount of processing power. Either that, or it was under extremely heavy load from the attackers.
The next part of the setup was the honeypot itself. It took me a while to find the right software to use. At first, I wanted to code my own honeypot, but quickly realized that it wouldn’t work very well. Then I pursued a different software, called DVWA or Damn Vulnerable WebApp. According to all I had read, it was the perfect solution! What ended up being the problem was that it is not a honeypot – it is instead a testing tool for programmers to try out their hacking capabilities. This was a training tool for Quality Assurance Engineers. I eventually stumbled upon T-Pot and was blown away by how much It had.
With my VM built, and my Honeypot software selected, it was a process of installing the honeypot, and making sure that I wouldn’t be unable to access my own machine. After several attempts, I was finally able to install Ubuntu, curl and install the package on my headless box, and BAM it was running!
It crashed several times because of outside influences, and my first few passwords were not strong enough – but I did eventually get it working with some stability.
Hypothesis
My hypothesis in this experiment is that my machine will be attacked about 100,000 times. I know there are lots of players on the web, and that the hacking community is huge. That being said, I am not advertising my machine and I don’t know if it could even handle more traffic.
From what I have read on the T-Pot site, the machine should be resilient enough to handle shutdowns, and temporary outages. That is good because I’m certain that DigitalOcean does regular backups that will probably disrupt my machine.
Also, from what I learned while reading black code, I also expect that most of these attacks will be coming from non-north American sources. My best guess, based on the ‘ghostnet’ scandal, as well as the recent news about Trump winning the election, is that the top countries will be either Russia or China. That is not a statement about those people, it is just a statement about the names of countries I have been hearing in the news associated with the recent data attacks.
I don’t have much to say about the types of attacks. Obviously the most common attack will be the cowrie attacks, or rather the ‘Simple Network Management Protocol’ or SNMP attacks. The reason why those will be the most common is that they are the least invasive. Someone can do an SNMP call on a machine from anywhere with little resistance. What that does is it returns the information about the machine – such as who is connected to it, where it is on the web, and what the machine is. It’s like a diagnostic report that can be pulled.
The other more invasive attacks will happen as well, but I hypothesize that the attacks will be 80% Non-Invasive and 20% Invasive attacks.
Results
Conclusion
I learned in this exercise that there are significantly more attackers on the web than I had expected. My hypothetical numbers were blown out by so much and in such a short time. Not only that, but the short lifespan of my honeypots was just a reminder that the security I set up for any future projects should really be tight.
I know that there are standards of practice like changing your ssh port and creating barriers to keep people out, but that still leaves hundreds of attacks that would have found another way in.
I wanted to explore this space so that I could show people what was happening in the web. What I found instead was that I was not even prepared for the numbers I found.
The single largest shock in reviewing the results was that the United States was by far the most common place for hackers to originate from. I also noticed that the service I used to host my own honeypot was the service that hosted a lot of these machines. I guess that means that hackers have begun to use these services to run their own projects?
I haven’t had a chance to peel through the data of what the hackers did once inside the machine, but I am certain it’s not good stuff. I come away from this experience with confidence that the average computer is not secure. I wanted to encourage others to think about privacy and to really consider whether their own app providers were secure, but now I am considering that for myself.
Imagine how often google gets attacked – imagine how viciously and constant those attacks must me.
Bibliography
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Adams, John. "Credit Sesame Brings Credit Score/Debt Management Service to Mobile Devices." American Banker, 22 Dec. 2011. Academic OneFile, http://link.galegroup.com.ocadu.idm.oclc.org/apps/doc/A275440951/AONE?u=toro37158&sid=AONE&xid=1979e750. Accessed 20 Nov. 2018.
-
Alibaba. “Ant Financial Partner with Government to Build Jiangxi's Digital Economy." China Telecom, June 2018, p. 8. Academic OneFile, http://link.galegroup.com/apps/doc/A547533219/AONE?u=toro37158&sid=AONE&xid=58ff776d. Accessed 20 Nov. 2018.
-
Barone, Tom and Elliot W. Eisner. "What is and What is Not Arts Based Research?." Arts Based Research. Thousand Oaks: SAGE Publications, Inc., 2012.
-
Bertin, J. “Semiology of Graphics, Diagrams, Networks, Maps”. University of Wisconsin Press, 1983. Madison Wisconsin, USA
-
Chen, Chaochao, et al. "Distributed Collaborative Hashing and its Applications in Ant Financial.", 2018.
-
Choo, Kukhee. "Cool Governance: Japan's Ubiquitous Society, Surveillance, and Creative Industries." Culture, Theory and Critique, vol. 59, no. 2
-
Dayen, David. "Big Tech: The New PREDATORY CAPITALISM." The American Prospect, Winter 2018.
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Deibert, Ronald J. Black Code: Surveillance, Privacy, and the Dark Side of the Internet. Signal, 2013.
Ronald Deibert, the head of Citizen Labs in Toronto, has a long and prolific history of involvement with data privacy. He and his lab were recommended to me for research by one of my advisors, and what I have learned from them and about them has been incredible even after just a few weeks of reading.
Deibert’s book is a story of his lab’s journeys through the discovery and undoing of China’s ghostnet, as well as other journeys. On top of that, it is a critique and opinion piece from Deibert about data privacy overall. His book thus far has helped me position my thoughts in my own thesis. My direction of “What happens to you when you are compromised” as an introductory learning piece for everyday users is definitely inspired by what happened with the ghostnet story, as well as other stories that I read about in the news.
The basic thesis is simple. Hackers rarely hack people for their identity – they hack for access, for mechanical resource, or for widespread intelligence gathering. The difference between access and widespread intelligence gathering is the precision with which a hacker might act. For access, a hacker would target someone specifically so that they can get closer to their true target. This often happens on a personal device or on a personal network of devices or area networks. Widespread intelligence gathering, on the other hand, is for the purpose of monitoring the consensus of devices over a very large network of people. This is often less invasive and also often less damaging to its victims. These two methods, however, are not mutually exclusive and can be part of the same strategy.
Long story short – this article gave me focus.
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Fairclough, Bradyn. "Privacy piracy: the shortcomings of the United States' data privacy regime and how to fix it." The Journal of Corporation Law, Winter 2016, p. 461.
With all of these sources in mind, this article was enlightening and useful to ground many of my arguments and thoughts. The reason is many events that have taken place in the US and internationally in terms of data privacy are mentioned in this article. It also outlined a series of very concerning (and therefore good argument points) topics of US data privacy. I know this is a contentious topic and changes at any given moment, but as of 2019 these laws have not changed or been improved.
As I write, an inquiry is going on for Facebook’s massive data breach that has pulled in google, apple, and amazon. It is likely that this massive inquiry will end with regulatory laws for these companies and these actions, but I cannot write about what has not happened yet. This article makes clear that the US has no data privacy law. Not only that, but its own constitution favors the wrongdoer in most situations – citing the second amendment.
I think that lots of people don’t know this is the case for the US (and largely also Canada), but it definitely has an impact on whether a person would support GDPR or not. I think that if more people knew what was happening with their data, and how utterly unprotected they are, then they would act very differently.
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Finn, Jonathan. “Capturing the Criminal Image : From Mug Shot to Surveillance Society.” University Of Minnesota Press, 2009.
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Fuchs, Christian. "studiVZ: Social Networking in the Surveillance Society." Ethics and Information Technology, vol. 12, no. 2, 2010.
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Greenleaf, Graham. “The influence of European data privacy standards outside Europe: implications for globalization of Convention 108.” International Data Privacy Law, Volume 2, Issue 2, 1 May 2012.
This article served as an incredibly thorough explanation and overview of GDPR and Convention 108. It is also an excellent resource of “what’s going on internationally” as a review of data policies at a very high level from several different countries. Before my change in thesis direction, I was interested in the comparison between GDPR and the changes coming in the banking world of China with respect to private data (trust me there’s something there).
Something that became very clear in this article is what GDPR could become. Reading through the potential impacts and responses to Convention 108 in GDPR was an inspiring moment in my research. The basic summary of Convention 108 is similar to the security that countries have installed at their borders and their airports. A complex system that checks for security risks and international threats as people enter the country. By simply changing some of the words around of that description, you have the gist of Convention 108. For instance: A complex system that checks for security risks and threats as users enter the national web space.
There are other insights in this article, but Convention 108 is by far the most impactful and has the loudest resonance both for and against in respective communities.
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Han, Dong. "The Market Value of Who We Are: The Flow of Personal Data and Its Regulation in China." Media and Communication, 5.2 (2017
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Kanopy (Firm), and The Great Courses (Firm). “How Apple Raises Competitive Barriers.” The Great Courses, California, USA, 2015.
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Kurzgesagt – In a Nutshell. “Safe and Sorry – Terrorism & Mass Surveillance.” Youtube, Kurzgesagt, Apr 14, 2016, https://www.youtube.com/watch?v=V9_PjdU3Mpo.
I often turn to Kurzgesagt for background knowledge on a subject. They often focus on very high level concepts of something that’s going on – and they hit privacy and security right on the head. The overall thesis of this video is that there is a balance to be struck between protecting ourselves and restricting ourselves from the freedoms that we should be entitled to. My thesis does not necessarily deal with terrorism or the impact of overprotective legislation, but these topics definitely inform some of the background of my research.
Data privacy laws will be very similar to national privacy laws, except that these legislations have the portential to impact our day to day lives in our pockets and at homes. Not only that, but the privacy laws that could come into place (or the agreements between software companies and governments) could lead to us being compromised more ore being watched with greater ease.
In my opinion, being watched as a core concept doesn’t bother me. What does bother me is who is watching me and why are they watching. Those two questions can be the difference between better healthcare and a new international battlegrounds for insurgence and data gathering.
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LastWeekTonight. “Facebook: Last Week Tonight with John Oliver (HBO).” Youtube, LastWeekTonight, Sep 23, 2018, https://www.youtube.com/watch?v=OjPYmEZxACM.
It can often be hard to keep up with the news and to keep up with the ever-growing collection of events that are leading both Canada and the US into different paths with respect to data privacy. This video is a helpful re-cap of what has happened thus far with American policy making and data privacy. It also makes special note of machine learning and third party data analysis. These are practices that are very common for those in the world of data analytics – but those capabilities turned at people can be horrifying to think of.
The reason why those concepts are so frightening is explained in this video. Basically, if these companies were successful in guiding a population to vote a huge orange infant into the seat of President of the United States, then they surely have control over some decisions that voters are making. With access to that kind of influential media and access to machine learning, simply the interactions of people can model a government-leading data structure. Such a science fiction manifestation could be a very scary future to live in.
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Laybats, Claire, and John Davies. "GDPR." Business Information Review, vol. 35, no. 2, 2018.
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Lo and Behold, Reveries of the Connected World. Directed by Werner Herzog, Produced by Werner Herzog and Rupert Maconick, Magnolia Pictures, Publication date. January 23, 2016.
This film is not just an influential piece in my thesis – but an influential piece for me as an individual going through life. There are many different courses and environments that one can go to for a thorough understanding of cyberspace. This film is simply a history of cyberspace, how the to’s and fro’s came to be, and how the contentious issue of surveillance, privacy, and government practice in cyberspace came to be.
This film also covers the methods by which network communication occurs – and how those communications can be intercepted. The understanding that it provides was a foundation for me to better understand my interactions in cyberspace.
One of the issues that is presented when discussing data privacy is either a lack of literacy or an excess of literacy. There are either people telling you they don’t understand technology and thus prefer not to talk about it, and there are people who will tell you that your understanding of technology is wrong. This film helped me and others understand how to communicate with either and that there are some skills required to cross these rifts.
The overall gist of the film is a “how did technology get to this point? Where will it go next?”. It covers hacking and military operations; facebook and boston dynamics. It’s a very good and thorough look at technology today.
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Lynch, Clifford, ‘How do your data grow?’, Nature Publishing Group, Volume 455, September 2008.
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Mehmood, Abid, I. Natgunanathan, Y. Xiang, G. Hua and S. Guo, "Protection of Big Data Privacy," in IEEE Access, vol. 4, 2016.
-
Oecd.org. (2018). About the OECD - OECD. http://www.oecd.org/about/, Accessed 13 Nov. 2018.
- Ong, Rebecca, “Recognition of the right to privacy on the Internet in China”, International Data Privacy Law, Volume 1, Issue 3, 1 August 2011.
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Rowley, Paul. "Navigating Brexit and GDPR." ITNow, vol. 58, no. 4, 12/01/2016.
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Robinson, Sandra. "Databases and Doppelgängers: New Articulations of Power." Configurations, vol. 26 no. 4, 2018, pp. 411-440. Project MUSE.
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Rutherford, Paul. “The New Icons?: The Art of Television Advertising.” University of Toronto Press, 1994;1995;2000.
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Sobolewski, Maciej, et al. "GDPR: A Step Towards a User-Centric Internet?" Inter Economics, vol. 52, no. 4, 07/01/2017.
Leading up to this article, I had generated a serious amount of interest in users’ perspective of data privacy. I already had done loads of research about GDPR, ANT financial, and various other players on the international stage. The overall story was already becoming clear to me – which is naïve but that’s how it felt. This article, however, opened it up when it presented the stats about the users in Europe and their perspective on Data Privacy and GDPR.
The basic thesis of this article was; Is the EU, and potentially also the world, moving towards a user centric internet with freedoms and protections similar to those of national legislation by way of digital regulation? The arguments stem from adoption of GDPR and perception of GDPR. One of those arguments really sticks to the core of my thesis – do people support GDPR?
It is made clear through field research that people do not really know what’s going on with data privacy – but they do care about data privacy. What was also clear was that the exchange of goods or services for a person’s data was a very uneven scale. The average user is / was giving away their precious identifiable data in exchange for nearly insignificant conveniences on their mobile devices.
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The New York Times. “How Cambridge Analytica Exploited the Facebook Data of Millions | NYT.” Youtube, The New York Times, April 9, 2018, https://www.youtube.com/watch?v=mrnXv-g4yKU.
In an effort to keep up with the current times, I often turn to New York Times and Globe and Mail for resources. This video in particular covers the events that took place over an agreement between Cambridge Analytica and Facebook. This event, which is still shaking the world with respect to data privacy, is exactly what I want to combat. The entire documentation that New York Times provides – while 100% accurate – is indicitave of what people think is the real end point of data privacy being compromised. There is some discussion in the other academic work of the adversary and the researcher as two ethical poles of people who need data.
This article discusses neither of them in depth, and simply says “oops we spilled your data”. Cambridge analytica poses itself to be a researcher – benign and in the interest of overall social growth – while in reality we have no idea whom else might have wanted to purchase data from that company – by way of the university research lab.
I want to dissuade people from thinking a facebook data leak is the real risk. It is not. The real risk is what people might do to accomplish their nefarious goals – and what they might use you for in the process.
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Tufte, E. R.“The visual display of quantitative information”. Graphics Press. 2001. Cheshire, Conneticut
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Wimmer, Kurt. "The Long Arm of the European Privacy Regulator: Does the New EU GDPR Reach U.S. Media Companies?" Communications Lawyer, Summer 2017.
- Xu, Lei; C. Jiang, J. Wang, J. Yuan and Y. Ren, "Information Security in Big Data: Privacy and Data Mining," in IEEE Access, vol. 2, pp. 1149-1176, 2014.
END
copyright hugh ritchie 2019


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Source: pdf
Author: Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
Abstract: The Google search engine has enjoyed huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks. Here we propose a simple universal ranking algorithm for data lying in the Euclidean space, such as text or image data. The core idea of our method is to rank the data with respect to the intrinsic manifold structure collectively revealed by a great amount of data. Encouraging experimental results from synthetic, image, and text data illustrate the validity of our method. 1
[1] R. Albert, H. Jeong, and A. Barabsi. Diameter of the world wide web. Nature, 401:130–131, 1999.
[2] S. Brin and L. Page. The anatomy of a large scale hypertextual web search engine. In Proc. 7th International World Wide Web Conf., 1998.
[3] R. Duda, P. Hart, and D. Stork. Pattern Classiﬁcation. Wiley-Interscience, 2nd edition, 2000.
[4] G. H. Golub and C. F. Van Loan. Matrix Computations. Johns Hopkins University Press, Baltimore, 1989.
[5] J. Kleinberg. Authoritative sources in a hyperlinked environment. JACM, 46(5):604–632, 1999.
[6] S. T. Roweis and L. K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290:2323–2326, 2000.
[7] J. B. Tenenbaum, V. de Silva, and J. C. Langford. Global geometric framework for nonlinear dimensionality reduction. Science, 290:2319–2323, 2000. ¨
[8] D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Sch olkopf. Learning with local and global consistency. In 18th Annual Conf. on Neural Information Processing Systems, 2003.


{% extends "beta.html" %} {% block beta %}
The next steps are as follows. We know they're complicated, but that's Apple's fault. We're annoyed too.
You will receive an email from Test Flight allowing you to download the Viewfinder app.
Still having problems? Here's a detailed step-by-step guide with screenshots
Again, congratulations and thanks for participating. We're very excited to make Viewfinder a reality and we sincerely appreciate your help.
The Viewfinder team
{% end %}


Advent of Code 2018 -
13p2
13p1
|
index
|
14p1
/>-<\ | | | /<+-\ | | | v \>+ | | ^ \<->/
Solve Puzzle


List of Changes
Our heuristic evaluators highlighted some key functionality elements that need to be improved. In particular, they noted there should be other organization options for journal entries, there needed to be an editing function, and the highlighting capability was unintuitive. In addition, the emotion graph display was confusing, the emotion choices were unrealistic, and the search function needed to be all-encompassing. Lastly, the evaluators were undecided whether users should be able to delete journal entries.To address these issues, we made the following changes:
- Added the omnisearch bar that examines titles, content, and tags to allow users to find notes easily that haven’t been tagged or highlighted.
- Created a page that makes it easy for users to view their entries by time--this could be a calendar or a quick scroll capability.
- Added an edit page that will look similar to a new entry page but with the information already entered. Delete was not implemented yet as we are still discussing how to implement this (whether it should be a permanent delete or an archive).
- Added a wider range of emotions for users to 'tag' entries with, rather than just a simple sliding scale. Note that this is not implemented in the assignment we are submitting, as we are looking into better ways of visualizing the emotions.
- Removed the emotion over time graph, as it was difficult to use and was restricting. Again, we plan to implement a better visualization mechanism for this, such as a pie chart or a bubble graph.
- With regards to highlights, we agree that highlighting on a mobile device as envisioned now is a bit cumbersome, so we have included that as a stretch goal, or an added capability that is not a core feature after brainstorming potential ways to overcome this usability barrier.


Julia set is almost a mirror image of the Mandelbrot. For the function: f(x)=x^2+c, keep c fixed and vary x. The Julia set for c is the set of x-values for which iterating f does not diverge.
**Place the cursor below the image and use the mouse wheel to zoom into the image**


SUCCESSFUL
Indicates the task was run successfully.
Wendy will delete the PendingTask instance and not run it again.


{% unless page.header.overlay_color or page.header.overlay_image %}
{{ page.title }}
{% endunless %}Robot User Detection
I worked for a while in Dadmatech as an intern. In Dadmatech, my main focus was collecting specific data from Twitter to balance the training data for Robot User Detection. Then, I modified the existing model and reached a better result.
Course Projects
- Computer Vision: Crack Detection
- Deep Learning: Covid-19 Prediction
- Software Engineering: Saffrun


Partisan is the design of an alternative runtime system for improved scalability and reduced latency in actor applications.
Partisan provides:
Partisan is provided as a user library in Erlang and achieves up to an order of magnitude increase in the number of nodes the system can scale to through runtime overlay selection, up to a 34.96x increase in throughput, and up to a 13.4x reduction in latency over Distributed Erlang.
Each of the microbenchmarks run multiple configurations of Partisan under both increasing latency and payload size, with a fixed number of 10,000 messages per experiment. At the start of each experiment for our microbenchmarks, N actors are spawned on each of two instances of the Erlang VM, based on the desired concurrency level. Each actor will send a single message to an actor on the other node and wait for acknowledgement before proceeding. Experiments were run using the full-mesh overlay, but the optimizations are implemented for all overlays. Latency is reported as the time to send a single message from the source to the destination.
We start by showing a baseline configuration of Distributed Erlang compared with Partisan with all optimization enabled. Our results show that leveraging additional connections and affinitizing communication increases performance regardless of concurrency. With 128 actors, 512KB payload, and 1ms RTT, Partisan with affinitized parallelism performs 1.9x better than Distributed Erlang.
What happens if we don’t have such favorable network conditions? What if our application is spread out between two AWS availability zones and suffers from RTTs closer to 20ms instead? We show the effects of running our earlier experiment this time with a 20ms RTT latency between actors located on different nodes. As we can see, as the latency increases, the system can take advantage of more communications channels to parallelize inter-actor communication on the network. With 128 actors, 512KB payload, and 20ms RTT, Partisan with affinitized parallelism performs 13.4x better than Distributed Erlang.
In the Erlang community, large message sizes are not uncommon. Consider Riak, the distributed key-value store which could contain user-stored and arbitrary-sized data. An Erlang message then could contain a user-provided piece of data megabytes in size. However, it’s well-known in the Erlang community that Distributed Erlang doesn’t handle large message sizes well. In fact, the Riak documentation suggests to avoid storing objects larger than 1-2MB due to the performance degradation that occurs due to Distributed Erlang. Cognizant of this, we turn our attention to question of how large payload size affects performance in Partisan. Can Partisan overcome some of the performance issues faced by Distributed Erlang in the face of large payloads?
We explore the effects of increasing payload size on Partisan as compared to Distributed Erlang. Keeping in line with the community-observed limits of Distributed Erlang, we vary the message size from 512kb (below the 1MB performance degradation threshold) to 8MB (far above the 1MB performance degradation threshold). With 128 actors, 8MB payload, and 1ms RTT, Partisan with affinitized parallelism performs 3.7x better than Distributed Erlang!
To look at read-world applicability, we ported the distributed systems framework, Riak Core, to Partisan and built two example applications: (i) a simple echo service – an application that’s designed to only be bound by the speed of the actor receiving messages and the network itself; and (ii) a memory-based key-value store that operates using read/write quorums – more representative of a workload where more data is being transmitted and more CPU work has to occur.
Riak Core is a distributed programming framework written in Erlang and based on the Amazon Dynamo system that influenced the design of the distributed database Riak, Apache Cassandra, and the distributed actor framework Akka. In Riak Core, a distributed hash table is used to partition a hash space across a cluster of nodes. These virtual nodes—the division of the hash space into N partitions—are claimed by a node in the cluster, and the resulting ownership is stored in a data structure known as the ring that is periodically gossiped to all nodes in the cluster. Requests for a given key are routed to a node in the cluster based on the current partitioning of virtual nodes to cluster nodes in the ring structure using consistent hashing, which minimizes the impact of reshuffling when nodes join and leave the cluster. Background processes are used for cluster maintenance; ownership handoff, (transferring virtual node ownership) metadata anti-entropy (an internal KVS for configuration metadata) and ring gossip (information about the cluster’s virtual node to node mapping).
Our first application is a simple echo service, implemented on a three node Riak Core cluster. For each request, we generate a binary object, uniformly select a partition to send the request to, and wait for a reply containing the original message before issuing the next request. Binary objects are generated for two payload sizes, 512KB and 8MB. Concurrency is increased during the test execution and parallelism is configured at 16. We test two latency configurations: 1ms (representative of single-AZ, single-region) and 20ms (representative of multi-AZ, single region.) We run a fixed duration of 120 seconds.
We first demonstrate that with 128 actors, 1ms RTT, and large payloads (8MB), Partisan is 3.10x faster than Distributed Erlang. With smaller payloads (512KB), Partisan is on par with Distributed Erlang (1.01x).
We also demonstrate that with 128 actors, 20ms RTT, and larger payloads (8MB), Partisan is 34.96x faster than Distributed Erlang (which achieves only 5 ops/second before reaching peak throughput). With smaller payloads (512KB), Partisan is 7.21x faster than Distributed Erlang.
Our second application is a memory-based key-value store, similar to the Riak database, implemented on a three node Riak Core cluster.
Each key is hashed and mapped to a virtual node using the ring structure that is gossiped in the cluster. The virtual node that the key is hashed to, along with that virtual nodes’s two clockwise neighbors on the ring, represent the three virtual nodes that contain the three replicas for the data item. Each request (either a get operation or put operation) to the keyvalue store uses a quorum request pattern, where requests are made to these three replicas, and the response is returned to the user when a majority (2 out of 3) replicas reply.
This pattern involves multiple nodes in the request path, and each partition simulates a 1ms storage delay in the request path. We reuse the aforementioned benchmarking strategy: test execution is fixed at 120 seconds.
For each request, we draw a key from a normal distribution across 10,000 keys and run the key through Riak Core’s consistent hashing algorithm for placement. The consistent hashing placement algorithm aims for uniform partitioning of keys across the cluster. We use a 10:1 read/write ratio for the experimental workload. Concurrency is varied in our experiments (x-axis) and parallelism is configured at 16. We test two latency configurations: 1ms, and 20ms.
We present the results of the 1ms RTT KVS experiment. Under workloads that are CPU-bound, where the network is not congested nor contended for, Distributed Erlang can outperform Partisan for small payloads, but underperforms Partisan for large payloads. Distributed Erlang can overperform Partisan in the case of small payloads because of (i) the impact of scheduling overhead for Partisan; and (ii) its placement in the Erlang VM, which minimizes the cost of a given message send. However, as the size of both payloads and latency increases, the benefits of Partisan becomes apparent. In this experiment, with 128 actors, 1ms RTT, and large payloads (8MB), Partisan is 1.4x faster than Distributed Erlang, while with smaller payloads (512KB), Partisan on par with Distributed Erlang (0.96x). However, these dynamics change markedly in less favorable network conditions.
We present the results of the 20ms RTT KVS experiment. Here, we see that Partisan optimizations allow for better performance in terms of latency and throughput, whereas Distributed Erlang loses performance as concurrency increases. In this experimet, with 128 actors, 20ms RTT and smaller payloads (512KB), Partisan is 1.8x faster than Distributed Erlang. As we increase the payload size, Distributed Erlang surprises us. Under larger payloads (8MB), Partisan far exceeds the performance of Distributed Erlang, achieving 95 ops/second; Distributed Erlang can only complete 1 operation during the entire 120s execution with 128 actors, and only 3 operations during the entire execution with 64 actors!
Lasp is a programming framework designed for large scale coordination-free programming. Applications in Lasp are written using shared state; this shared state is stored in an underlying key-value store and is replicated between all nodes. Applications modify their own replica and propagate the effects of their changes to their peers. Lasp ensures that applications converge to the same result on every node through the use of data structures known as Conflict-Free Replicated Data Types, combined with monotone programming. For our Lasp evaluation, the application is a simulated advertisement counter, modeled after the Rovio advertisement counter scenario for Angry Birds. In this application, each client keeps a replica of a grow-only distributed counterissuing increment operations when an advertisement is displayed. Once a certain number of impressions is reached, the advertisement is disabled. The increment interval was fixed at 10s, and the propagation interval for the counter was fixed at 5s. The total number of impressions was configured to ensure that the experiment would run for 30 minutes under all configurations. The evaluation is performed on both the client-server and peer-to-peer overlays for different cluster sizes, ranging from 32 all the way up to 1,024 node clusters.
For both overlays, the system propagates the full state of the counter to the node’s peers at each propagation interval. Note that since the Rovio advertisement counter scenario was designed for mobile applications, we do not run the fullmesh topology because it would be unrealistic. That is, in the context of mobile apps, clients would not connect to all other nodes, nor will they have knowledge of who all of the clients in the system are. Rather, either mobile apps will communicate with some number of nearby peers (peer-to-peer) or they will communicate through a server (client-server). Clientserver also serves as the standard model of deploying mobile applications today. Thus, we designed our experiments to reflect this—we examine client-server and peer-to-peer overlays for this application in our experiments.
We present the total data transmission required for the experiment to finish as we scale the size of the cluster from 32 to 1024 nodes. For smaller clusters of nodes, client-server is the more efficient overlay in terms of the amount of data that must be transmitted to finish the experiment. This improved efficiency comes at a cost, however, as the client-server configuration is unable to scale beyond 256 nodes. Beyond 256 nodes, the cilent-server experiments could not be completed; as the Erlang VM has unbounded queues, when the server cannot process incoming messages quickly enough, the VM allocates all available memory, leading to termination of the Erlang VM by the Linux OOM Killer. Peer-to-peer is more resilient in the face of a node failure allowing it to support larger clusters of nodes—up to 1024! However, peer-to-peer is less efficient due to this—the redundancy of communication links used by the overlay causes it to transmit more data in order to complete the experiments.
Perhaps the most interesting takeaway from the results of this real-world large-scale experiment is that the experiment was even possible at all with Erlang. As Distributed Erlang permits one to only use a full-mesh overlay, it’s possible that the previous results observed by Ericsson on the maximum size of Erlang clusters–only 200 nodes–are due to this full-mesh-only restriction. This experiment suggests that Partisan may enable the development of new applications with actors systems that have not been previously possible by enabling the application developer to dynamically change the pattern of communication between nodes, without altering application semantics. Perhaps the lack of mobile applications written using distributed actor systems is a symptom of the full-mesh-only restriction. Similarly, this observation may also hold true for the emerging class of “Internet of Things” applications.
Partisan’s design choices assume a lowest-common-denominator strategy: these optimizations should be beneficial for any of the major distributed actor systems: Distributed Erlang, Scala’s Akka, or Microsoft’s Orleans. However, if you’re using Erlang or Elixir, you can take advantage of Partisan immediately using our library-based reference implementation available on GitHub!


| Interface | Description |
|---|---|
| var |
All functions in Style tool box are provided both in Style and
here.
They are excatly the same. However sometimes you may not able to extends Style , then try
implements var to get full support.But in this way, you are still not able to invoke methods directly from static methods. Anyway implements var still works in most cases.Also you may write code like this: |
| Class | Description |
|---|---|
| $ |
Constants that's usually used with Style tool box
Recommended context are provided, but they are not limited to those recommendations. |
| Async<R> |
Async supporter.
|
| AsyncGroup |
Joins results of a group of Async process.
|
| Core | |
| def<R> |
an object representing a function
|
| Entry<K2,V2> |
Entry which formats a map from key to value
|
| ForSupport<N extends java.lang.Number> |
Supporter for For-to-step expression
|
| ForSupport.ToSupport<N extends java.lang.Number> |
Supporter for For-to-step expression
|
| IfBlock<T,INIT> |
Supporter for if expression
|
| JSONLike<K,V> |
Provide a way of forming up a map in the way looks like JSON
|
| LoopInfo<R> |
Info about current Iterator.
It's a subclass of LoopInfo |
| ptr<T> |
A container of objects, usually used when accessing a non-final value from
inner classes.
|
| Style |
All functions in Style tool box are provided here.
Let your class extends Style to avoid retyping
Style. which makes your coding prettier |
| SwitchBlock<T,R> |
Supporter for switch expression
Note that it doesn't support break, because it doesn't go through other cases except the matched one. |
| Exception | Description |
|---|---|
| StyleRuntimeException |
A RuntimeException to simplify exception handling.
it is recommended to create this exception using Style.$(Throwable) |


Yourtube.com is an online directory of videos just for you. Learn how to build your own youtube. Youtube has become the premier video service in the world. What if you could learn the ropes to build yours? Video transcoding, transformations, LHS. Learn how to leverage Cloudinary end-to-end solution in building your youtube in no time! 🔥🔥🔥
Basically it's built on the Mean Stack & Angular-Bootstrap.


#assign n0_intro="active"> <#assign n1_queries="active"> <#assign sqlQuery="active">
Sometimes it is useful to not use entity beans or dto beans but instead execute sql queries
producing SqlRow
objects or reading directly from JDBC ResultSet.
In typical recent applications around 2%
of queries were SqlQuery type queries.
Note that with SqlQuery we can get Ebean to add limit/offset
clause appropriate
to the database platform and we can bind parameters using all the mapped types
(Enums, java.time, array types etc).
For more information goto docs / query / sqlquery
<#include "/_common/lang-buttons.html">String sql = "select id, name, when_active from customer where status = ?"; List<|SqlRow> rows = DB.sqlQuery(sql) .setParameter(1, "NEW") .setMaxRows(100) .findList(); for (SqlRow sqlRow : rows) { Long id = row.getLong("id") String name = row.getString("name") Timestamp whenActivated = row.getTimestamp("when_activated") }
val sql = """ select id, name, when_activated from customer where name like ? """.trimIndent() val rows = DB.sqlQuery(sql) .setParameter(1, "Rob%") .setMaxRows(100) .findList() for (row in rows) { val id = row.getLong("id") val name = row.getString("name") val whenActivated = row.getTimestamp("when_activated") }
Alternatively we can use a RowMapper to read from the JDBC ResultSet.
<#include "/_common/lang-buttons.html">String sql = "select id, name, status from customer order by name desc"; DB.sqlQuery(sql) .findEachRow((resultSet, rowNum) -> { // read directly from ResultSet long id = resultSet.getLong(1); String name = resultSet.getString(2); // do something interesting with the data });
val sql = "select id, name, status from customer order by name desc" DB.sqlQuery(sql) .findEachRow { resultSet, rowNum -> // read directly from ResultSet val id = resultSet.getLong(1) val name = resultSet.getString(2) // do something interesting with the data }


Blitzboks keen to use that one opportunity - Sage
Cape Town - The World Rugby Sevens Series - as competitive as it is right now - is all about grabbing that one opportunity and the Springbok Sevens team would love nothing more than doing just that.
Register your interest for the British & Irish Lions tickets in South Africa 2021
That is according to Blitzbok forward Dylan Sage, who will be back at the Cape Town Stadium for the first time in three years when the Cape Town Sevens kicks off on Friday (December 13), playing in his 26th tournament for South Africa.
Sage made his Blitzbok debut in 2015, played again in 2016, but missed out in 2017 due to injury and 2018 because of Super Rugby commitments.
The Cape Town Sevens is very close to the heart of the Blitzboks and it is a privilege and honour to play in front of their home crowd, because they have that one opportunity at it, says Sage.
"Cape Town is that one chance we get to play at home, and we need to use that opportunity," said Sage.
"It is a great event, always a sell-put and the organisers always make sure that there are lots of things keeping the crowds entertained."
The Blitzbok forward will not lack any motivation come Friday.
"The bodies are sore after Dubai and the long flight home but being welcomed at the airport like we were with a band playing and fans waiting, and then having a good night's rest at home is more than enough to perk you up again," he said.
"We have closed the door on Dubai and will start the week fresh. New challenges await in Cape Town. We have a tough pool and the teams will be coming for us, so will have to be ready for that."
South Africa face USA, Fiji and Japan in Pool A.
Fellow forward, Ryan Oosthuizen, concurred with Sage: "It is great to be back at home. The people at the airport were clearly excited to share the win in Dubai with us and we appreciate that.
"We really enjoy the support from the people back home and playing in Cape Town is a great, because we can return the compliment," said Oosthuizen, who added the Blitzboks will start afresh when they re-assemble on Monday.
"You need to be able to switch off and on again in the World Series. The Dubai event is gone, we did well and are happy about our performance, but now everyone starts at scratch again," he said.
Meanwhile, Springbok Sevens coach Neil Powell has added Hacjivah Dayimani to the Blitzboks squad for the tournament. He replaces Christie Grobbelaar who travelled to Dubai as 13th player. Powell will name his final 12-man tournament squad on Thursday.
Pools for the Cape Town Sevens:
Pool A
South Africa, USA, Fiji, Japan
Pool B
New Zealand, Argentina, Canada, Wales
Pool C
England, France, Spain, Scotland
Pool D
Samoa, Australia, Ireland, Kenya
- SA Rugby


pio check
Perform a static analysis check on a PlatformIO project.
More information: home page
- Perform a basic analysis check on the current project:
pio check
- Perform a basic analysis check on a specific project:
pio check --project-dir project_dir
- Perform an analysis check for a specific environment:
pio check --environment environment
- Perform an analysis check and only report a specified defect severity type:
pio check --severity low|medium|high
- Perform an analysis check and show detailed information when processing environments:
pio check --verbose


[all packages]
[package ]
[class hierarchy]
[index]
public class Graph0Curry1
(source file: Graph0Curry1.java)
java.lang.Object
|
+----Drawable
|
+----Graph0
|
+----Graph0Curry1
The pure class interface.
public class Graph0Curry1
extends Graph0
-
Create a function node (a node containing a subgraph) where
the subgraph has a control line.
- Author:
- Alan Jeffrey
- Version: v1.0 1998/06/11
- Graph0Curry1(Constraints, Graph1, Interface, Interface, Interface)
-
Create a new function node.
- draw(Drawer)
-
Graph0Curry1
public Graph0Curry1(Constraints C,
Graph1 G,
Interface source,
Interface target,
Interface args);
-
Create a new function node.
- Parameters:
- C - the constraint set.
- G - the subgraph (whose source should be source.tensor (args)).
- source - the source of the graph
- target - the target of the graph
- args - the interface for the bound variables of the subgraph.
draw
public void draw(Drawer d);
[all packages]
[package ]
[class hierarchy]
[index]
Graph0Curry1.html


The Board Manager handles the state of everything on the board, and communicates with the player objects.
More...
|
| void | CreateBoard (GameManager gm, int seed) |
| | Creates a board based on the board width and height The board is centered on the screen, and the bottom square left is (0,0) More...
|
| |
| TileState | GetTileState (Vector3 tilePos) |
| | Takes in a World space Vector3 and gets the state of the tile at that position. More...
|
| |
| void | MineTile (Vector3 tilePos, Robot robot) |
| | Removes a tile for a robot. Adds points if the tile is a gem. More...
|
| |
| void | PlaceTile (Vector3 tilePos) |
| | Places a tile for a robot. More...
|
| |
| void | CheckForCollectable (Robot robot) |
| | Checks if the robot is on a tile that gives points. More...
|
| |
| IEnumerator | RunTurn (string p1Moves, string p2Moves) |
| | Takes in two command strings and runs them on the board. More...
|
| |
|
| Tilemap | backgroundTilemap |
| | References for tilemaps that handle the objects on the screen. More...
|
| |
| Tilemap | objectTilemap |
| |
| TileBase | bgTile |
| | References for tiles to fill the tilemap. More...
|
| |
| TileBase | placedRock |
| |
| List< TileBase > | rockTiles |
| | Can contain any number of tiles that will randomly fill the board. More...
|
| |
| List< TileBase > | gemTiles |
| | Filled with 3 tiles in editor: small, medium, large, in that order. More...
|
| |
| TileBase | powerupTile |
| | Reference for the powerup tile icon. Types of powerups are randomized. More...
|
| |
| Color | borderColor = new Color(0.5f, 0.5f, 0.5f, 1.0f) |
| |
| Camera | cam |
| | Reference for camera so it can properly be scaled to fit the board. More...
|
| |
| Robot | player1 |
| | Reference for each of the players; needs to probably be switched to their base class later, but is temporarily a gameobject for testing. More...
|
| |
| Robot | player2 |
| |
The Board Manager handles the state of everything on the board, and communicates with the player objects.
This facilitates the ordering of all of the motion of a turn, and controls some of the game logic.


Winter’s Heart
Maps:
Far Madding
Prologue: Snow
Leaving the Prophet
Taken
Customs
Offers
Flags
The Scent of Madness
The Streets of Caemlyn
Sea Folk and Kin
A Cup of Tea
A Plan Succeeds
Ideas of Importance
A Lily in Winter
Wonderful News
What a Veil Hides
In Need of a Bellfounder
An Unexpected Encounter
Pink Ribbons
An Offer
Three Women
Questions of Treason
A Matter of Property
Out of Thin Air
To Lose the Sun
Among the Counsels
Bonds
Expectation
To Surprise Queens and Kings
News in a Cloth Sack
Another Plan
Cold, Fat Raindrops
What the Aelfinn Said
A Portion of Wisdom
Blue Carp Street
The Hummingbird’s Secret
With the Choedan Kal
Glossary
Book 9 of The Wheel of Time
Robert Jordan
Index of Books
|
Next—Book Ten:
Crossroads of Twilight


Home
Organizers
Program Committee
Invited Speakers
Schedule
Contact
ICDM- 2020
Contact Us
For any inquires, please email them to
<EMAIL_ADDRESS>and
<EMAIL_ADDRESS>Publication
The Proceedings of ICDM 2020 will be published in IEEE XPlore.
Important Dates
Workshop paper submissions:
Aug 24, 2020
Workshop paper notification:
Sept 17, 2020
Camera-Ready deadline
Sept 24, 2020
Conference dates
Nov 17-20, 2020


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In gradient descent we compute the cost function and its gradient for all data points we have.
In large-scale applications such as the ILSVRC challenge, the training data can have on order of millions of examples. Hence, it seems wasteful to compute the full cost function over the entire training set in order to perform only a single parameter update. A very common approach to addressing this challenge is to compute the gradient over batches of the training data. For example, a typical batch could contain some thousand examples from an entire training set of several millions. This batch is then used to perform a parameter update.


| CONSIGNEE | : | {buyer_name} | |
| ADDRESS | : | {buyer_address} | |
| PROVINCE | : | {buyer_state} | {buyer_area} |
| CITY | : | {buyer_city} | |
| TEL NO | : | {buyer_contact_number} |
| SHIPPER | : | {seller_name} |
| ADDRESS | : | {seller_address} |
| CITY | : | {seller_city} |
| TEL NO | : | {seller_contact_number} |
| ORIGIN | : | {origin} |
| QUANTITY | : | {quantity} |
| COLLECTIBLE AMT. | : | COD {cod_fee} |
| CLIENT | : | {client} |
| REFERENCE NO. | : | {reference_no} |


catch
sections and suggests splitting them into separate catch
blocks.
Example:
try {
int i = getIndex();
} catch (NullPointerException|IndexOutOfBoundsException e) {
e.printStackTrace();
}
After the quick-fix is applied:
try {
int i = getIndex();
} catch (NullPointerException e) {
e.printStackTrace();
} catch (IndexOutOfBoundsException e) {
e.printStackTrace();
}
Multi-catch
appeared in Java 7.
This inspection can help to downgrade for backward compatibility with earlier Java versions.


| Background:clearError (id) |
Clear error display (progress scope) |
| Background:considerIdleProcessing (call) |
Background process for processing next photo or video in the catalog. |
| Background:continue () |
Continue background task. |
| Background:displayError (errm, id, immediate, call) |
Display background error as progress scope. |
| Background:displayErrorX (options, fmt, ...) |
Display error, named options first, so remainder can be used for formatting & params. |
| Background:finale (call) |
Background call finale. |
| Background:init (call) |
Background init function. |
| Background:initDone (call) |
call/called when background initialization is complete (after init hold-off time expires). |
| Background:isPausing () |
Rarely used, but helps long-running background tasks to abort if user is trying to pause for foreground purposes. |
| Background:main (call) |
Background initializer and optional main loop. |
| Background:new (t) |
Constructor for new instance. |
| Background:newClass (t) |
Constructor for extending class. |
| Background:pause (tmo) |
Pause background task. |
| Background:process (call) |
Background process function. |
| Background:quit () |
Signal background task to quit. |
| Background:start () |
Start's background initialization, followed by periodic background processing - if desired. |
| Background:stop (tmo) |
Stop background task. |
| Background:waitForIdle (tmo) |
Wait for background task to finish. |
| Background:waitForInit (tmo, ival) |
Wait for asynchronous initialization to complete. |
- Background:clearError (id)
-
Clear error display (progress scope)
Parameters:
- Background:considerIdleProcessing (call)
-
Background process for processing next photo or video in the catalog.
Parameters:
Usage:
Called when nothing else to do in background process.
- Background:continue ()
-
Continue background task.
Usage:
No-op if not paused.
- Background:displayError (errm, id, immediate, call)
-
Display background error as progress scope.
Parameters:
-
errm
: - unparsed error message
-
id
:
-
immediate
:
-
call
: - call object containing background context.
Usage:
base class uses "genericBackgroundErrorId" for generic background error id. Derived classes may define additional error IDs for special purposes...
- Background:displayErrorX (options, fmt, ...)
-
Display error, named options first, so remainder can be used for formatting & params.
Parameters:
- Background:finale (call)
-
Background call finale.
Parameters:
Usage:
If overriding, you MUST set state to idle, or just call this from extended class method.
- Background:init (call)
-
Background init function.
Parameters:
-
call
: object - usually not needed, but its got the name, and context... just in case.
Usage:
override to do special initialization, if desired.
Try not to throw errors in init, but instead set initStatus to true or false depending on whether successful or not.
no need to call this method from extended class, yet.
if init is lengthy, check for shutdown sometimes and abort(return) if set - initStatus a dont care in that case.
- Background:initDone (call)
-
call/called when background initialization is complete (after init hold-off time expires).
Parameters:
- Background:isPausing ()
-
Rarely used, but helps long-running background tasks to abort if user is trying to pause for foreground purposes.
- Background:main (call)
-
Background initializer and optional main loop.
Parameters:
- Background:new (t)
-
Constructor for new instance.
Parameters:
-
t
: initialization table, including:
interval (number, default: 1 second) process frequency base-rate. Recommend .2 as normal minimum, .1 if process is quick and fast response is necessary.
minInitTime (number, default: 10 seconds), but recommend setting to 15 or 20 - so user has time to inspect startups in progress corner, or set to zero to suppress init progress indicator altogether.
- Background:newClass (t)
-
Constructor for extending class.
Parameters:
- Background:pause (tmo)
-
Pause background task.
Parameters:
Usage:
you must continue in finale method of call or service, lest background task dies forever.
- Background:process (call)
-
Background process function.
Parameters:
-
call
: object - usually not needed, but its got the name, and context... just in case.
- Background:quit ()
-
Signal background task to quit.
Usage:
Need not be called from task - does not wait for confirmation.
- Background:start ()
-
Start's background initialization, followed by periodic background processing - if desired.
Usage:
Generally called from init module if background auto-start is enabled. also called from plugin manager for start/stop on demand.
- Background:stop (tmo)
-
Stop background task.
Parameters:
-
tmo
: (number, required) - seconds to wait for stop confirmation.
Usage:
Return value:
confirmed (boolean) true iff stoppage confirmed.
- Background:waitForIdle (tmo)
-
Wait for background task to finish.
Parameters:
Usage:
Dont call unless you know its on its way out, e.g. shutdown for reload.
- Background:waitForInit (tmo, ival)
-
Wait for asynchronous initialization to complete.
Parameters:
-
tmo
: - initial timeout in seconds - default is half second.
-
ival
: - recheck interval if not finished initializing upon initial timeout - return immediately and do not prompt user if nil or zero. Ignored if tmo is zero.
Usage:
Untested @2011-01-08 ###2
Return values:
- status - true iff init completed successfully.
- explanation - if status false, is error message. if status true, indicates some waiting was required.


|
Click
|
A set of Tasks scheduled on the same CPU. More...
Public Member Functions | |
| int | thread_id () const |
| Returns this thread's ID. More... | |
| Master * | master () const |
| Returns this thread's associated Master. More... | |
| TimerSet & | timer_set () |
| const TimerSet & | timer_set () const |
| SelectSet & | select_set () |
| const SelectSet & | select_set () const |
| bool | active () const |
| Returns whether any tasks are scheduled. More... | |
| Task * | task_begin () const |
| Returns the beginning of the scheduled task list. More... | |
| Task * | task_next (Task *task) const |
| Returns the task following task in the scheduled task list. More... | |
| Task * | task_end () const |
| Returns the end of the scheduled task list. More... | |
| void | scheduled_tasks (Router *router, Vector< Task *> &x) |
| void | lock_tasks () |
| void | unlock_tasks () |
| void | schedule_block_tasks () |
| void | block_tasks (bool scheduled) |
| void | unblock_tasks () |
| bool | stop_flag () const |
| void | mark_driver_entry () |
| void | driver () |
| void | kill_router (Router *router) |
| bool | greedy () const |
| void | set_greedy (bool g) |
| void | wake () |
| void | run_signals () |
| void | set_thread_state (int state) |
| void | set_thread_state_for_blocking (int delay_type) |
Public Attributes | |
| unsigned | _tasks_per_iter |
| unsigned | _iters_per_os |
A set of Tasks scheduled on the same CPU.
|
inline |
Returns this thread's ID.
The result is >= 0 for true threads, and < 0 for threads that never run any of their associated Tasks.
|
inline |
Returns this thread's associated Master.
|
inline |
Returns whether any tasks are scheduled.
Returns false iff no tasks are scheduled and no events are pending. Since not all events actually matter (for example, a Task might have been scheduled and then subsequently unscheduled), active() may temporarily return true even when no real events are outstanding.
|
inline |
Returns the beginning of the scheduled task list.
Each RouterThread maintains a list of all currently-scheduled tasks. Elements may traverse this list with the task_begin(), task_next(), and task_end() functions, using iterator-like code such as:
The thread's task lock must be held during the traversal, as shown above.
The return value may not be a real task. Test it against task_end() before use.
Returns the task following task in the scheduled task list.
| task | the current task |
The return value may not be a real task. Test it against task_end() before use. However, the task argument must be a real task; do not attempt to call task_next(task_end()).
|
inline |
Returns the end of the scheduled task list.
The return value is not a real task.


"Rounding" the colors of an image to map to a profile
You can 'round' an image to a given palette. This has the effect of limiting the amount of colors in an image, which allows for much faster searching. [TODO: Like what?]
This example will map a given image to a simple gray-scale palette


|
mlpack
1.0.12
|
mlpack provides a couple of convenience macros and functions to get the version of mlpack. More information (and straightforward code) can be found in src/mlpack/core/util/version.hpp.
The following three macros provide major, minor, and patch versions of mlpack (i.e. for mlpack-x.y.z, 'x' is the major version, 'y' is the minor version, and 'z' is the patch version):
In addition, the function mlpack::util::GetVersion()
returns the mlpack version as a string (for instance, "mlpack 1.0.12").
Each mlpack executable supports the –version
(or -V
) option, which will print the version of mlpack used. If the version is not an official release but instead from svn trunk, the version will be "mlpack trunk" (and may have a revision number appended to "trunk").


OK, so this is basically advertising, but it might be interesting to some of you.
http://ruggedcircuits.com/html/ancp01.html
Archived Forum |
|
How to destroy an ArduinoSubmitted by Robert Wall on Mon, 10/12/2012 - 11:42OK, so this is basically advertising, but it might be interesting to some of you. http://ruggedcircuits.com/html/ancp01.html
» |
Re: How to destroy an Arduino
Applying overvoltage to analogue inputs is the most likely way that I can see for damaging our Arduinos, particularly for the current sensor. Although most of us only need to measure currents up to around 13A, household consumption can far exceed this level. At such times, the CT's output signal is likely to be well in excess of 5.5V, so we're totally reliant on protection diodes, both internal and external.
Re: How to destroy an Arduino
so we're
totallyreliant on protection diodes, both internal and external aided, in the case of the emonTx, by the impedance of the bias chain which should just about limit the current to a safe value.But a series resistor right next to the input pin, after any external clamping diodes, would pretty much ensure safe operation under normal conditions. The full analysis needs to take the source impedance of the damaging voltage into account, together with all the surrounding circuitry.
Re: How to destroy an Arduino
Why does the series resistor need to be after the protection diodes rather than before them? My gut feeling is that this arrangement leaves the protection diodes more vulnerable to being damaged.
Is it likely that the Arduino's input circuitry would be damaged while the protection diodes are still intact?
Re: How to destroy an Arduino
The underlying assumption is that you have rated the external protection diodes to withstand the possible fault current. Because those diodes should limit the input to (Vs + 0.65) V or - 0.65 V (and assuming there's enough load so that the supply rail voltage does not lift in the case of a positive over-voltage), then the resistor only has to drop a few hundred (or even less) millivolts and hold the current down to a few milliamps to assure the internal protection diodes are not damaged. If there's a risk of a substantially higher voltage at the input (e.g. mains !), or enough current to lift the supply rail, then a second resistor before the external protection diodes, which might need to become fast zener diodes to common, would be necessary to limit the current. (But for a c.t. output with limited current capability, that's unlikely to be necessary).
Without the resistor after the external diodes, as the voltage dropped across the internal and external diodes is likely to be similar, there's no knowing how the current will share. Hence the resistor to ensure the external diodes, which can be suitably rated, take most of the current.
It is impossible to lay down rules of thumb to suit every situation. The input circuit has to be properly designed.


Installation is done via the NuGet package manager:
PM> Install-Package $popularPackageName.[Android|iOS|Mac].DefinitelyBound
For example, to install the popular MBProgressHUD into your Xamarin iOS project:
PM> Install-Package MBProgressHUD.iOS.DefinitelyBound


| Interface | Description |
|---|---|
| QueryVisitor |
Contains "visit" start/end methods called by query traversal algorithms as
various structural nodes are encountered.
|
| Class | Description |
|---|---|
| DefaultQueryVisitor |
Default no-op query visitor implementation.
|
| VisitorContext |
Encapsulates logic and data specific to a single traversal.
|
| Enum | Description |
|---|---|
| Traversal |
PlasmaSDO™ and PlasmaQuery™ are trademarks of TerraMeta Software, Inc. Copyright © 2011 - All Rights Reserved.


The following FAQ's are in related to database preparation.
Problem1 : how can I analysis bacteria related datas? Solution :
Before this, you need to add the bacteria database into the DATABASE_HOME directory. And bacteria database's process method is similar to the viruses database which detailed described in paper.
Problem1 : how can I add another host reference to map aginst and remove the host genetic information from the query dataset? Solution :
You need to add the host genome ID in USCS by "ANALYSIS-database".


Utility functions, which are used in different VSCP framework modules.
More...
Utility functions, which are used in different VSCP framework modules.
| #define VSCP_UTIL_ARRAY_NUM |
( |
|
__array | ) |
(sizeof(__array) / sizeof((__array)[0])) |
Get number of elements in a array.
| #define VSCP_UTIL_COMPILE_TIME_ASSERT |
( |
|
__expr | ) |
typedef char COMP_TIME_ASSERT[(__expr) ? 1 : -1] |
Use this macro for a compile time assertion.
| #define VSCP_UTIL_UNUSED |
( |
|
__var | ) |
do{ (void)(__var); }while(0) |
Mark unused variables with this macro.
| void vscp_util_cyclicBufferInit |
( |
vscp_util_CyclicBuffer *const |
cbuffer, |
|
|
void *const |
storage, |
|
|
uint8_t |
size, |
|
|
uint8_t |
elemSize |
|
) |
| |
This function initializes a cyclic buffer.
- Parameters
-
| [in,out] | cbuffer | Cyclic buffer context |
| [in] | storage | Storage of all elements in the cyclic buffer |
| [in] | size | Storage size in byte |
| [in] | elemSize | Size of a single element in byte |
| uint8_t vscp_util_cyclicBufferRead |
( |
vscp_util_CyclicBuffer *const |
cbuffer, |
|
|
void *const |
elem, |
|
|
uint8_t |
maxNum |
|
) |
| |
This function reads one or more elements from a cyclic buffer.
- Parameters
-
| [in,out] | cbuffer | Cyclic buffer context |
| [in] | elem | Element buffer (one ore more elements) |
| [in] | maxNum | Max. number of elements to read |
- Returns
- Number of read elements
| uint8_t vscp_util_cyclicBufferWrite |
( |
vscp_util_CyclicBuffer *const |
cbuffer, |
|
|
void const *const |
elem, |
|
|
uint8_t |
maxNum |
|
) |
| |
This function writes one or more elements to a cyclic buffer.
- Parameters
-
| [in,out] | cbuffer | Cyclic buffer context |
| [in] | elem | Element buffer (one ore more elements) |
| [in] | maxNum | Max. number of elements to write |
- Returns
- Number of written elements
| uint8_t vscp_util_getZoneIndex |
( |
uint16_t |
vscpClass, |
|
|
uint8_t |
vscpType |
|
) |
| |
Get the index in the message data of the zone.
Note, sub zone index = zone index + 1
This function is only necessary, because some VSCP events has the zone/sub-zone at a different location in their data payload.
- Parameters
-
| [in] | vscpClass | VSCP class |
| [in] | vscpType | VSCP type |
- Returns
- Zone index in the message data


Trump's Impeachment Ire Turns on Pompeo Amid Diplomats' Starring Roles
The impeachment inquiry has created the first rift between President Donald Trump and the Cabinet member who has been his closest ally, Secretary of State Mike Pompeo, four current and former senior administration officials told NBC News.
Trump has fumed for weeks that Pompeo is responsible for hiring State Department officials whose congressional testimony threatens to bring down his presidency, the officials said. The president confronted Pompeo about the officials — and what he believed was a lackluster effort by the secretary of state to block their testimony — during lunch at the White House on Oct. 29, those familiar with the matter said.
Inside the White House, the view was that Trump “just felt like, ‘rein your people in,’” a senior administration official said. Trump particularly blames Pompeo for tapping Ambassador Bill Taylor in June to be the top U.S. diplomat in Ukraine, the current and former senior administration officials said.
A crack in the seemingly unbreakable bond between Trump and Pompeo is striking because Pompeo, a former Kansas congressman, is viewed as the “Trump whisperer” who has survived — and thrived — working for a president who has routinely tired of and discarded senior members of his team.


{% blocktrans %}
Make sure you check your spelling. It is not possible to change your issue later.
We do not allow change because people might have voted. If content changes, votes
are invalidated. You can archive and hide it by not publishing your issue.
{% endblocktrans %}
{% else %}
{% trans "You cannot propose yet or anymore, you need more points" %}
{% endif %}
{% endif %}
{% votes_by_user user on issues as vote_dct %}
{% vote_counts_for_objects issues as counts_dct %}
{% trans "proposed by you" %}
{% for issue in issues %}
{% dict_entry_for_item issue from vote_dct as vote %}
{% dict_entry_for_item issue from counts_dct as score %}
{% if vote.vote %}
{% for key , direction in possible_votes.items %}{% ifequal key vote.vote %}{% trans direction %}{% endifequal %}{% endfor %}
{% endif %}
{% for k, count in score.items %}
{% if count %}
{% for key , direction in possible_votes.items %}{% ifequal key k %}