Flash Dance: Digital Dashboards of the 1980s. "QUANTUM SHOT" #847 Link - article by Avi Abrams Not every car could be a star of the "Knight Rider" show, but almost every 1980s car model sported a flashy disco-lights digital dashboard What was the best thing about the 1980s? Some say it's the Disco fever and the sparkle of the disco balls (although these "glitter balls" were invented way back in the 1920s). Others say that the 1980s were great time to watch gloriously over-the-top action movies with Arnold Schwarzenegger and Sylvester Stallone, still others maintain that it is the wild and wooly clothing styles that define the 1980s decade... and yeah, Microsoft, of course.
In our humble opinion, one of the most coolest things that occurred in the 1980s was the rise of digital dashboards in cars, watches, hi-fi equipment (and just about everywhere), with their "early video game"-like riot of LCDs and LEDs and warm glow of CRT displays... (image via) (image via) Dashboard as a Video Game: Use your Joystick! (images via) (image via) Interactive Smart TV UX Demo powered by SMAX. The Invisible Science. The week in big data on Twitter, visualized. I decided to play around a little more with ScraperWiki this week to see what people were talking about when they talked about big data on Twitter. The idea was to kill two birds with one stone: (1) demonstrate once again what’s possible in the realm of data visualization and mining even for novices using free online tools, and (2) give a little taste of what got people excited in the past seven days.
There are scientific studies and then there are collections of numbers, words and charts that purport to say something. This is decidedly the latter, but I really just wanted to see what types of stuff I could do with the data. If it’s at all interesting or useful, let me know. Maybe it can become a weekly thing. Without further ado, here are some highlights of what I found, based on a sample of just more than 33,000 tweets mentioning “big data.” There were only a handful that were geotagged, but you can see how popular a topic big data is around the globe. Here’s the tweet. Hadoop Data science. Google launches Views, a community for contributing photo spheres to Google Maps. Google launched on Tuesday a new community website, called Views, which allows people to publicly contribute, share and geo-tag their photos spheres of places around the global to Google Maps.
To upload a photo sphere, sign into Views with your Google+ credentials and select the camera button on the top right. From there, simply import photo spheres from your Google+ photos. You can also upload photos to Views from the Gallery in Android devices. Just select "Share" and then Google Maps. Views also includes the Street View Gallery, letting users check out various panoramas from popular Street View collections like the Grand Canyon and Swiss Alps. Read: Google opens Google Maps Preview to all - no email invite required Anyone with Android 4.2 or higher, including most Nexus devices, can create a 360-degree photo sphere. Quip: A Beautiful, Contrarian Word Processor.
Word processors may be among the most essential pieces of software on the planet, but they’re also among the most mundane. The last one I can think of that felt like a landmark was Writely, the 2005 browser-based app that later became Google Docs. And even though a fair amount of writing is done on mobile devices these days, most of it is done with apps that basically attempt to mimic and extend desktop word processors — usually Microsoft Word, which still dominates the industry so utterly that it tends to define even its competition. And then there’s Quip. The brand-new product of a startup founded by Bret Taylor (ex-Facebook CTO and Google Maps co-creator) and Kevin Gibbs (another ex-Googler), Quip lacks some features you’d expect a word processor to have.
But the things it does do, it does in ways often strikingly different from garden-variety word processors. Even now, a heck of a lot of word-processing collaboration is done by e-mailing documents in Word format. FinovateSpring May 2013 – Narrative Science Launches Quill for Financial ServicesNarrative Science | Narrative Science. Redirect Notice. Pattern recognition. Pattern recognition algorithms generally aim to provide a reasonable answer for all possible inputs and to perform "most likely" matching of the inputs, taking into account their statistical variation.
This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns. A common example of a pattern-matching algorithm is regular expression matching, which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors. In contrast to pattern recognition, pattern matching is generally not considered a type of machine learning, although pattern-matching algorithms (especially with fairly general, carefully tailored patterns) can sometimes succeed in providing similar-quality output to the sort provided by pattern-recognition algorithms.
Overview[edit] Probabilistic classifiers[edit] They output a confidence value associated with their choice. . To output labels . . . Where. Design computing. Design Computing refers to an area of Design Studies that deals with furthering the understanding and the practice of design activities through the application and development of novel concepts and techniques in computing. In recent years a number of research and education areas have been grouped under the umbrella term "Design Computing", namely: The main research groups working in this area span from Faculties of Architecture, Engineering and Computer Science. Australia has been a pioneer in this area. For the last four decades the Key Centre of Design Computing and Cognition (KCDC), currently known as the Design Lab, at the University of Sydney has been active in establishing this area of research and teaching. The University of Sydney offers a Bachelor of Design Computing ([1]). In the US this research area is also known as "Design and Computation", namely at the Massachusetts Institute of Technology (MIT).
Other relevant research groups include: Algorithms and Perception for Interactive Free-Viewpoint Image-Based Navigation. Watson. Federated search. Federated search is an information retrieval technology that allows the simultaneous search of multiple searchable resources. A user makes a single query request which is distributed to the search engines participating in the federation. The federated search then aggregates the results that are received from the search engines for presentation to the user.
Purpose[edit] Federated search came about to meet the need of searching multiple disparate content sources with one query. This allows a user to search multiple databases at once in real time, arrange the results from the various databases into a useful form and then present the results to the user. Process[edit] Federated search portals, either commercial or open access, generally search public access bibliographic databases, public access Web-based library catalogues (OPACs), Web-based search engines like Google and/or open-access, government-operated or corporate data collections.
Implementation[edit] Challenges[edit] See also[edit] Collaboration tool. A collaboration tool is something that helps people collaborate. The term is often used to mean collaborative software, but collaboration tools were being used before computers existed. A piece of paper, for example, can be used as collaboration tool. Everything that helps to solve a predefined task together in a group more easily is an effective collaborative tool. Collaboration means, in this context, working together to fulfill a shared, collective, bounded goal.
Conference phone calls may be replaced by asynchronous conferencing, video conferences, IRC or Instant Messaging now. Peer Reviews of documentation are easier to establish through wikis than by iterative versions on paper. See also[edit] Sources[edit] Eugene Eric Kim (2005). Data feed. Data feed formats[edit] Emerging semantic data feed[edit] The Web is evolving into a web of data or Semantic Web. Data will be encoded by Semantic Web languages like RDF or OWL according to many experts' visions. So, it is not difficult to envision data feeds will be also in the form of RDF or OWL. A big advantage of providing semantic data feeds, i.e. feeding data in Semantic Web standards, is that the data can then be readily consumed and reused by other computers. Examples of semantic data feed are available on the Ufeed online service. Ufeed allows users to create feeds in RDF format for various types of data, which include product information, news, events, job openings and studies.
CSV datafeed and affiliate marketing[edit] CSV datafeeds are mostly being used within the affiliate marketing. See also[edit] Semantic publishing References[edit] External links[edit] Pulse of Maersk Line. Data fusion. Data fusion is the process of integration of multiple data and knowledge representing the same real-world object into a consistent, accurate, and useful representation. fusion of the data from 2 sources (dimension #1 & #2) can yield a classifier superior to any classifiers based on dimension #1 or dimension #2 alone Data fusion processes are often categorized as low, intermediate or high, depending on the processing stage at which fusion takes place.[1] Low level data fusion combines several sources of raw data to produce new raw data. The expectation is that fused data is more informative and synthetic than the original inputs.
For example, sensor fusion is also known as (multi-sensor) data fusion and is a subset of information fusion. Geospatial applications[edit] In the geospatial (GIS) domain, data fusion is often synonymous with data integration. A simplified example of this process is shown below where data set "α" is fused with data set β to form the fused data set δ. See also[edit] Link analysis. Knowledge discovery[edit] Data gathering and processing requires access to data and has several inherent issues, including information overload and data errors. Once data is collected, it will need to be transformed into a format that can be effectively used by both human and computer analyzers.
Manual or computer-generated visualizations tools may be mapped from the data, including network charts. Several algorithms exist to help with analysis of data – Dijkstra’s algorithm, breadth-first search, and depth-first search. Link analysis is used for 3 primary purposes:[4] Find matches in data for known patterns of interest;Find anomalies where known patterns are violated;Discover new patterns of interest (social network analysis, data mining). History[edit] Association Matrix In addition to the association matrix, the activities matrix can be used to produce actionable information, which has practical value and use to law-enforcement.
Applications[edit] Issues with link analysis[edit] J.J. WORKSHOP: Linking and Contextualizing Publications and Datasets, Sept. 26, Malta. Valletta, Malta A one-day workshop on "Linking and Contextualizing Publications and Datasets" will be held in Valletta, Malta, on September 26, 2013. The workshop is sponsored by OpenAIREplus (www.openaire.eu) and EuroCRIS (www.eurocris.org) and is being offered In conjunction with TPDL 2013 (www.tpdl2013.info).
Web site: Workshop Objectives The goal of this workshop is to provide researchers and practitioners in the fields of Digital Libraries, e-Science, and e-Research, with a forum where they can constructively explore foundational, organizational and systemic challenges in contexts having publishing, interlinking, preservation, discovery, access, and reuse of publications and datasets as focal points. It expects to contribute to the actual picture of the state of the art approaches and solutions that researchers and practitioners active in these fields have investigated and realized. Invited speaker Workshop topics Important Dates. Intel Face Tracking technology hands-on. Your business isn't a game of chance. Fill out the form to get your custom demo. Cognos. Only better. Esri Maps for IBM Cognos plugs directly into your existing Cognos environment.
The result? Cognos taken to the next level. Stop ignoring your data. Find out where your best customers are and see where you can find more of them. Engineered for your enterprise. Take advantage of your existing BI architecture, including the security, capabilities, and scalability you've worked hard to define. Geography in action. See how a major beverage distributor uses Esri Maps for IBM Cognos to display unit sales by ZIP code along with all underlying business information. World Leading Intelligence Analysis - Analyst's Notebook 8.5. Google launches Views, a community for contributing photo spheres to Google Maps.
Gardner's Multiple Intelligences. Howard Gardner of Harvard has identified seven distinct intelligences. This theory has emerged from recent cognitive research and "documents the extent to which students possess different kinds of minds and therefore learn, remember, perform, and understand in different ways," according to Gardner (1991). According to this theory, "we are all able to know the world through language, logical-mathematical analysis, spatial representation, musical thinking, the use of the body to solve problems or to make things, an understanding of other individuals, and an understanding of ourselves. Where individuals differ is in the strength of these intelligences - the so-called profile of intelligences -and in the ways in which such intelligences are invoked and combined to carry out different tasks, solve diverse problems, and progress in various domains. " Www.uninova.pt/cam/paper1.pdf.
Forecasting Future Events With Predictive Analytics. Signals intelligence. The last German message intercepted by the British during World War II, signaling Germany's unconditional surrender As a means of collecting intelligence, signals intelligence is a subset of intelligence collection management, which, in turn, is a subset of intelligence cycle management. History[edit] Intercepting written but encrypted communications, and extracting information, probably did not lag long after the development of writing. A simple encryption system, for example, is the Caesar cipher. Electronic interception appeared as early as 1900, during the Boer Wars.
The Boers had captured some British radios, and, since the British were the only people transmitting at the time, no special interpretation of the signals was necessary.[1] More technical definitions of SIGINT and its branches[edit] In the United States and other nations involved with NATO, signals intelligence is defined as:[2] Intelligence derived from communications, electronic, and foreign instrumentation signals.
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