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Google I/O'17: Channel 2
Technical sessions and deep dives into Google's latest developer products and platforms.
Views: 11885 Android Developers
Technical Guidelines Development Committee (TGDC) Meeting — Day 1
EAC and NIST are pleased to announce the upcoming meeting of the TGDC on September 11-12, 2017, at the U.S. Election Assistance Commission in Silver Spring, Maryland. The meeting will be the next step in moving forward with the development of the Voluntary Voting System Guidelines (VVSG) version 2.0. Presentations and discussions at the meeting will include the following topics: (1) Update from the National Institute of Standards and Technology (NIST); (2) Review of Voluntary Voting System Guidelines (VVSG 2.0), Adoption Process and Transitioning Standards; (3) Security & Accessibility Meeting Update; (4) Overview and Discussion of Principles & Guidelines; (5) Overview & Update on Requirements and Test Assertions; (6) Cyber Security Presentation; and (7) Critical Infrastructure/MS-ISAC Presentation. Committee members will discuss next steps in the adoption process for VVSG 2.0. The full meeting agenda will be posted in advance at http://vote.nist.gov/. All sessions of this meeting will be open to the public. Members of the public may submit relevant written statements to the TGDC with respect to the meeting no later than 5:00 pm EDT on Tuesday, September 5, 2017. Statements may be sent via email at [email protected], via standard mail addressed to the U.S. Election Assistance Commission, 1335 East West Highway, Suite 4300, Silver Spring, MD 20910, or by fax at 301-734-3108. All comments will also be posted on http://vote.nist.gov/. The TGDC was established in accordance with the requirements of Section 221 of the Help America Vote Act of 2002 (P.L. 107-252, codified at 42 U.S.C 15361) to act in the public interest to assist the Executive Director of the U.S. Election Assistance Commission (EAC) in the development of voluntary voting system guidelines. Details regarding the TGDC's activities are available at http://vote.nist.gov/.
GSA Reverse Industry Training: Session 2: PACS Compliance and Pro Tips
In collaboration with FICAM, GSA’s Reverse Industry Training on September 17th, 2018, the session will highlight some of the main barriers in doing business with the government. The four main topics included in this session are: Consolidation of Government Approved Product Lists (Roy Hayes, Systems Engineering, Inc.), How to ensure you’ll have qualified integrators for your PACS projects (Stafford Mahfouz, Software House), Creating an “On-site checklist” for both vendors and the ordering agency (Rob Zivney, IDTP), and New construction considerations (Tony Damalas, Signet). www.gsa.gov
Full Event: An Evening With Vint Cerf 2018
On April 5, 2018, the NSTMF hosted an evening with Vint Cerf, co-father and architect of the internet, for an intimate evening of conversation and discovery at the Georgetown University School of Continuing Studies. Brian Fung of The Washington Post interviews Dr. Cerf about creating an interplanetary internet, the need for better security protocols, the drawbacks of blockchain, bit rot, and much more. Learn more about Vint Cerf: https://goo.gl/GQdFBs Learn more about the NSTMF: https://goo.gl/f9KDCn
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TGDC Meeting 091117 Part 1
EAC and NIST TGDC meeting on September 11-12, 2017, at the U.S. Election Assistance Commission in Silver Spring, Maryland. The meeting was an important next step in moving forward with the development of the Voluntary Voting System Guidelines (VVSG) version 2.0.
Algorithm design | Wikipedia audio article
This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Algorithm 00:01:56 1 Etymology 00:04:20 2 Informal definition 00:06:45 3 Formalization 00:07:30 3.1 Expressing algorithms 00:10:38 4 Design 00:12:53 5 Implementation 00:14:02 6 Computer algorithms 00:14:31 7 Examples 00:21:58 7.1 Algorithm example 00:22:07 7.2 Euclid's algorithm 00:23:13 7.2.1 Computer language for Euclid's algorithm 00:25:01 7.2.2 An inelegant program for Euclid's algorithm 00:25:41 7.2.3 An elegant program for Euclid's algorithm 00:25:45 7.3 Testing the Euclid algorithms 00:28:41 7.4 Measuring and improving the Euclid algorithms 00:29:58 8 Algorithmic analysis 00:30:48 8.1 Formal versus empirical 00:32:11 8.2 Execution efficiency 00:34:14 9 Classification 00:34:36 9.1 By implementation 00:35:48 9.2 By design paradigm 00:37:22 9.3 Optimization problems 00:38:08 9.4 By field of study 00:38:23 9.5 By complexity 00:42:21 10 Continuous algorithms 00:45:49 11 Legal issues 00:50:05 12 History: Development of the notion of "algorithm" 00:51:04 12.1 Ancient Near East 00:52:24 12.2 Discrete and distinguishable symbols 00:53:01 12.3 Manipulation of symbols as "place holders" for numbers: algebra 00:54:04 12.4 Mechanical contrivances with discrete states 00:54:16 12.5 Mathematics during the 19th century up to the mid-20th century 00:54:50 12.6 Emil Post (1936) and Alan Turing (1936–37, 1939) 00:55:30 12.7 J.B. Rosser (1939) and S.C. Kleene (1943) 00:56:21 12.8 History after 1950 01:01:15 13 See also 01:04:35 14 Notes 01:10:23 15 Bibliography 01:12:57 16 Further reading 01:13:29 17 External links 01:13:39 Notes 01:13:48 Bibliography 01:13:57 Further reading 01:14:06 External links Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.9976038862100259 Voice name: en-US-Wavenet-C "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= In mathematics and computer science, an algorithm ( (listen)) is a set of instructions, typically to solve a class of problems or perform a computation. Algorithms are unambiguous specifications for performing calculation, data processing, automated reasoning, and other tasks. As an effective method, an algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function. Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states, eventually producing "output" and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate random input.The concept of algorithm has existed for centuries. Greek mathematicians used algorithms in the sieve of Eratosthenes for finding prime numbers, and the Euclidean algorithm for finding the greatest common divisor of two numbers.The word algorithm itself is derived from the 9th century mathematician Muḥammad ibn Mūsā al-Khwārizmī, Latinized Algoritmi. A partial formalization of what would become the modern concept of algorithm began with attempts to solve the Entscheidungsproblem (decision problem) posed by David Hilbert in 1928. Later formalizations were framed as attempts to define "effective calculability" or "effective method". Those formalizations included the Gödel–Herbrand–Kleene recursive functions of 1930, 1934 and 1935, Alonzo Church's lambda calculus of 1936, Emil Post's Formulation 1 of 1936, and Alan Turing's Turing machines of 1936–37 and 1939.
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