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  • Google I/O 2011: Smart App Design

    Google I/O 2011: Smart App Design Travis Green, Max Lin, Robert Kaplow, Jóhannes Kristinsson, Ryan McGee Learn how to recommend the unexpected, automate the repetitive, and distill the essential using machine learning. This session will show you how you can easily add smarts to your apps with the Prediction API, and how to create apps that rapidly adapt to new data. From: GoogleDevelopers Views: 10078 47 ratings Time: 01:01:04 More in Science & Technology

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  • Initial direction of intersection between two moving vehicles?

    - by Larolaro
    I'm working with a bit of projectile prediction for my AI and I'm looking for some ideas, any input? If a blue vehicle is moving in a direction at a constant speed of X m/s and a stationary orange vehicle has a rocket that travels Y m/s, which initial direction would the orange vehicle have to fire the rocket for it to hit the blue vehicle at the earliest time in the future? Thanks for reading!

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  • Possible applications of algorithm devised for differentiating between structured vs random text

    - by rooznom
    I have written a program that can rapidly (within 5 sec on a 2GB RAM desktop, 2.33 Ghz CPU) differentiate between structured text (e.g english text) and random alphanumeric strings. It can also provide a probability score for the prediction. Are there any practical applications/uses of such a program. Note that the program is based on entropy models and does not have any dictionary comparisons in its workflow. Thanks in advance for your responses

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  • Les quatre tendances qui vont changer la Business Intelligence dans les trois ans à venir, selon Gartner

    Les 4 tendances qui changeront (peut-être) la BI Dans les trois ans à venir, selon Gartner Dans le cadre de ses Prédiction 2011, le cabinet Gartner a identifié quatre grandes évolutions qui devraient impacter le domaine de la Business Intelligence. Ces prévisions restent hypothétiques mais elle s'appuie tout de même sur des tendances lourdes observables. Les voici en résumé : 1 - En 2013, 33% des fonctions de BI seront consommées au travers d'appareils mobiles Le taux d'adoption et la grande disponibilité des appareils nomades, ajoutée aux efforts des éditeurs de BI (développement de nouveaux produits et marketing) devraient rapidement générer ...

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  • CodePlex Daily Summary for Thursday, June 06, 2013

    CodePlex Daily Summary for Thursday, June 06, 2013Popular ReleasesReliability Modeling and Prediction: Reliability Prediction v2.0.1: Including the reliability modeling schema and the reliability prediction tool. Including case studies (Reporting service and WebScan system). Check Readme.txt for a quick tutorial.Virtual Sport for Sport Team: Virtual Sport Website: This is the website to manage a sports team. Through this website you can manage the members of the team, from players to staff, schedules, and more. and for supporter, be able more easily get to know team through the this websiteChristoc's DotNetNuke Module Development Template: DotNetNuke 7 Project Templates V2.3 for VS2012: V2.3 - Release Date 6/5/2013 Items addressed in this 2.3 release Fixed bad namespace for BusinessController in one of the C# templates. Updated documentation in all templates. Setting up your DotNetNuke Module Development Environment Installing Christoc's DotNetNuke Module Development Templates Customizing the latest DotNetNuke Module Development Project TemplatesPulse: Pulse 0.6.7.0: A number of small bug fixes to stabilize the previous Beta. Sorry about the never ending "New Version" bug!ZXMAK2: Version 2.7.5.3: - debugger: add LPC indicator (last executed opcode pc) - add host joystick support (written by Eltaron) - change file extension for CMOS PENTEVO to "cmos" - add hardware value monitor (see Memory Map for PENTEVO/ATM/PROFI)QlikView Extension - Animated Scatter Chart: Animated Scatter Chart - v1.0: Version 1.0 including Source Code qar File Example QlikView application Tested With: Browser Firefox 20 (x64) Google Chrome 27 (x64) Internet Explorer 9 QlikView QlikView Desktop 11 - SR2 (x64) QlikView Desktop 11.2 - SR1 (x64) QlikView Ajax Client 11.2 - SR2 (based on x64)BarbaTunnel: BarbaTunnel 7.2: Warning: HTTP Tunnel is not compatible with version 6.x and prior, HTTP packet format has been changed. Check Version History for more information about this release.Harvester - Debug Viewer for Trace, NLog & Log4Net: v2.0.1 (.NET 4.0): Minor Updates Fixed incorrect process naming being displayed if process ID reassigned before cache invalidated. Fixed incorrect event type/source for TraceListener.TraceData methods. Updated NLog package references. Official Documentation Moved to GitHub http://cbaxter.github.com/Harvester Official Source Moved to GitHub https://github.com/cbaxter/HarvesterSuperWebSocket, a .NET WebSocket Server: SuperWebSocket 0.8: This release includes these changes below: Upgrade SuperSocket to 1.5.3 which is much more stable Added handshake request validating api (WebSocketServer.ValidateHandshake(TWebSocketSession session, string origin)) Fixed a bug that the m_Filters in the SubCommandBase can be null if the command's method LoadSubCommandFilters(IEnumerable<SubCommandFilterAttribute> globalFilters) is not invoked Fixed the compatibility issue on Origin getting in the different version protocols Marked ISub...BlackJumboDog: Ver5.9.0: 2013.06.04 Ver5.9.0 (1) ?????????????????????????????????($Remote.ini Tmp.ini) (2) ThreadBaseTest?? (3) ????POP3??????SMTP???????????????? (4) Web???????、?????????URL??????????????? (5) Ftp???????、LIST?????????????? (6) ?????????????????????Media Companion: Media Companion MC3.569b: New* Movies - Autoscrape/Batch Rescrape extra fanart and or extra thumbs. * Movies - Alternative editor can add manually actors. * TV - Batch Rescraper, AutoScrape extrafanart, if option enabled. Fixed* Movies - Slow performance switching to movie tab by adding option 'Disable "Not Matching Rename Pattern"' to Movie Preferences - General. * Movies - Fixed only actors with images were scraped and added to nfo * Movies - Fixed filter reset if selected tab was above Home Movies. * Updated Medi...Nearforums - ASP.NET MVC forum engine: Nearforums v9.0: Version 9.0 of Nearforums with great new features for users and developers: SQL Azure support Admin UI for Forum Categories Avoid html validation for certain roles Improve profile picture moderation and support Warn, suspend, and ban users Web administration of site settings Extensions support Visit the Roadmap for more details. Webdeploy package sha1 checksum: 9.0.0.0: e687ee0438cd2b1df1d3e95ecb9d66e7c538293b Microsoft Ajax Minifier: Microsoft Ajax Minifier 4.93: Added -esc:BOOL switch (CodeSettings.AlwaysEscapeNonAscii property) to always force non-ASCII character (ch > 0x7f) to be escaped as the JavaScript \uXXXX sequence. This switch should be used if creating a Symbol Map and outputting the result to the a text encoding other than UTF-8 or UTF-16 (ASCII, for instance). Fixed a bug where a complex comma operation is the operand of a return statement, and it was looking at the wrong variable for possible optimization of = to just .Document.Editor: 2013.22: What's new for Document.Editor 2013.22: Improved Bullet List support Improved Number List support Minor Bug Fix's, improvements and speed upsPHPExcel: PHPExcel 1.7.9: See Change Log for details of the new features and bugfixes included in this release, and methods that are now deprecated.Droid Explorer: Droid Explorer 0.8.8.10 Beta: Fixed issue with some people having a folder called "android-4.2.2" in their build-tools path. - 16223 Magick.NET: Magick.NET 6.8.5.402: Magick.NET compiled against ImageMagick 6.8.5.4. These zip files are also available as a NuGet package: https://nuget.org/profiles/dlemstra/patterns & practices: Data Access Guidance: Data Access Guidance Drop3 2013.05.31: Drop 3DotNet.Highcharts: DotNet.Highcharts 2.0 with Examples: DotNet.Highcharts 2.0 Tested and adapted to the latest version of Highcharts 3.0.1 Added new chart types: Arearange, Areasplinerange, Columnrange, Gauge, Boxplot, Waterfall, Funnel and Bubble Added new type PercentageOrPixel which represents value of number or number with percentage. Used for sizes, width, height, length, etc. Removed inheritances in YAxis option classes. Closed issues: 682: Missing property - XAxisPlotLinesLabel.Text 688: backgroundColor and plotBackgroundColor are...DirectX Tool Kit: May 2013: May 30, 2013 Added more GeometricPrimitives: Cone, Tetrahedron, Octahedron, Dodecahedron, Icosahedron Updated to support loading new metadata from DDS files (if present) Fixed bug with loading of WIC 32bpp RGBE format images Fixed bug when skipping mipmaps in a 1D or 2D array texture DDS fileNew Projectsabang: ????????Alex Develop Kit: ????????C#?????????。AnaLog - Analyse Logique: Software for logical equations analyse. App Excess: App Platform for Windows.Associativy Frontend Engines Administration: Frontend Engines Administration module for the Associativy (http://associativy.com) Orchard graph platform.ATDD Applied (Example): Sample code for Nordic Testing Days 2013 workshop - Acceptance Test Driven Development Applied: An Intro to ATDD using Jasmine and SpecFlowAzCAD: AzCAD is a free CAD program.BVVD Project: SOURCE CODECrzy Engine: C# and XNA ORPG Game Development engine.Custom Pong: Custom PongEDID Puller: Simple C# application showing how to get the EDIDs of the connected monitors to a PC, in particular the manufacturer and model of the display device.GooMUI: A desktop player for the Google Play Music service that runs on Windows.Had: HadIIS Express GUI: The GUI for IISExpress (version 7.5 and 8.0) jean0605jabbrchangbranch: ddjQueryBuddy Port to .Net 4.0+: Upgrading the project to current dot net will make using this app easier for some folks!Kinopoly: Dieses Projekt ist eine Arbeit der Berufschule Bern, GIBB. Das Ziel ist es das berühmte Spiel Monopoly im Film Theme als eine Clientapplikation zu realisieren.Magic Engine - 2D and 3D engine developed by school students: Magic Engine - 2D and 3D engine developed by school studentsMetrics calculation: Calculates metrics with the use of Driven Metrics.Metro WPF: Metro WPF provides a set of controls and styles for you to build your metro style WPF applications.mysitie: this is unknown error site Native API Test Command-Line Utility: A command-line utility that allows the user to call native API function interactively and experiment with how they function.prakark06052013Hg01: *bold* _italics_ +underline+ ! Heading 1 !! Heading 2 * Bullet List ** Bullet List 2 # Number List ## Number List 2 [another wiki page] [url:http://www.example.prakark06052013Tfs01: *bold* _italics_ +underline+ ! Heading 1 !! Heading 2 * Bullet List ** Bullet List 2 # Number List ## Number List 2 [another wiki page] [url:http://www.example.prakarkGit06052013Git01: *bold* _italics_ +underline+ ! Heading 1 !! Heading 2 * Bullet List ** Bullet List 2 # Number List ## Number List 2 [url:http://www.example.com] {"Do QlikView Extension - Animated Scatter Chart: Animated scatter chart for QlikView, inspired by D3js.orgREADPDB(Program Database Reader): This tool uses the Microsoft Debug Interface Access Software Development Kit (DIA SDK) to parser PDB file SelfProject: Just For TestSlWfDesign: 11212SSZZ: SSZZ is a tool for Data Analysistest project codeplex: This is a testtesttom06052013git01: dfdstesttom06052013hg01: *bold* _italics_ +underline+ ! Heading 1 !! Heading 2 * Bullet List ** Bullet List 2 # Number List ## Number List 2 [another wiki page] [url:http://www.example.testtom06052013tfs01: gfdgfdthree: It's a personal project.Validation Rules Framework for C++: C++ framework for rule creation, validation and management.

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  • Cutting Subscriber Churn with Media Intelligence

    - by Oracle M&E
    There's lots of talk in media and entertainment companies about using "big data".  But it's often hard to see through the hype and understand how big data brings benefits in the real world.  How about being able to predict with 92% accuracy which subscribers intend to cancel their subscription - and put in place a renewal strategy to dramatically reduce that churn?  That's what Belgian media company De Persgroep has achieved with Oracle's Media Intelligence solution.  "One of the areas in which we're able to achieve beautiful results using big data is the churn prediction," De Persgroep's CIO Luc Verbist explains in a new Oracle video.  "Based on all the data that we collect on websites and all your behavior, payment behavior and so on, we're able to make a prediction model, which, with an accuracy of 92 percent, is able to predict that you probably won't renew your newspaper, anymore. So our approach to renewal is completely different to the people in that segment than towards the other people. And this has brought us a lot of value and a lot of customers who didn't stop their newspaper where else they would have done so." De Persgroep is using Oracle's Big Data Appliance, along with software from Oracle partner NGDATA to build up a detailed "DNA profile" of each individual customer, based on every interaction, in real time.  This means that any change in behavior - a drop in content consumption, a late subscription payment, a negative social media comment - is captured.  Applying advanced data modeling techniques automatically converts those raw interactions into data with real business meaning - like that customer's risk of churning. The very same data profile - comprising hundreds if individual dimensions - can simultaneously drive targeted marketing campaigns - informing audience about new content that's most relevant and encouraging them to subscribe.  It can power content recommendations and personalization right in the content sites and apps. And it can link directly into digital advertising networks via platforms like Oracle's BlueKai data management platform (DMP), to drive increased advertising CPMs. Using Oracle's Media Intelligence solution enables this across De Persgroep's business - comprising eight newspapers and 25 magazines published in Belgium and The Netherlands, and digital properties including websites with 6m daily unique visitors, along with TV and radio stations. "The company strategy is in fact a customer-centric strategy, so we want to get a 360-view about our customers, about our prospects. And the big data project helped us to achieve that goal," says Verbist. Using Oracle's Big Data Appliance to underpin the solution created huge savings.   "The selection of the Big Data Appliance was quite easy.  It was very quick to install, very easy to install, as well. And it was far cheaper than building our own Hadoop cluster. So it was in fact a non-brainer," Verbist explains. Applying Media Intelligence approach has yielded incredible results for De Persgroep, including: Improved products - with a new understanding of how readers are consuming print and digital content across the day Improved customer segmentation - driving a 6X improvement in customer prospecting and acquisition when contacting a specific segment Having the project up and running in three months And that has led to competitive benefits for De Persgroep, as Luc Verbist explains: "one of the results we saw since we started using big data is that we're able to increase the gap between we as the market leader, and the second [by] more than 20 percent."

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  • Folding at home: how to check the actual bonus credited?

    - by netvope
    In the past I've completed many SMP Core A2 units, but I haven't been folding since A3 was out. Now I'm running SMP Core A3 on Linux. HFM.NET shows that I should be getting a certain amount of bonus credit, but somebody pointed out that it is only a prediction. How can I check the amount of actual bonus credited to my account for each completed unit?

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  • Google chrome disable url suggestions from history

    - by Tural Aliyev
    I was searching for a solution which will help me to disable URL auto suggestion (from history) while I type url on adressbar. But I haven't found anything about this solution. I tryied to uncheck Use a prediction service to help complete searches and URLs typed in the address barin privacy settings, but it doesn't help. Is there any way to disable history or disable url suggestions from history?

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  • How to backup BOINC

    - by Stephen Judge
    I have BOINC Manager installed from the PPA, version 6.10.17, and I am about to upgrade my Ununtu install with a clean install. I would like to know how I can backup my work done on BOINC so I don't loose what I have already done and have to start from scratch again. For example I am running the Climate Prediction project and it runs for a year or so, I'm at 30% work done so I want to backup that 30% work done. Also as an addition to this, can someone advise me the best way to upgrade BOINC when new versions are released on their website but are not available on the PPA yet. I know you can install BOINC anywhere, but I want to install it to the same place the PPA install does so all my settings and work done is recognised. Thanks in advance.

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  • Physics engine that can handle multiple attractors?

    - by brice
    I'm putting together a game that will be played mostly with three dimensional gravity. By that I mean multiple planets/stars/moons behaving realistically, and path plotting and path prediction in the gravity field. I have looked at a variety of physics engines, such as Bullet, tokamak or Newton, but none of them seem to be suitable, as I'd essentially have to re-write the gravity engine in their framework. Do you know of a physics engine that is capable of dealing with multiple bodies all attracted to one another? I don't need scenegraph management, or rendering, just core physics. (collision detection would be a bonus, as would rigid body dynamics). My background is in physics, so I would be able to write an engine that uses Verlet integration or RK4 (or even Euler integration, if I had to) but I'd much rather adapt an off the shelf solution. [edit]: There are some great resources for physics simulation of n-body problems online, and on stackoverflow

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  • Use a template to get alternate behaviour?

    - by Serge
    Is this a bad practice? const int sId(int const id); // true/false it doesn't matter template<bool i> const int sId(int const id) { return this->id = id; } const int MCard::sId(int const id){ MCard card = *this; this->id = id; this->onChange.fire(EventArgs<MCard&, MCard&>(*this, card)); return this->id; } myCard.sId(9); myCard.sId<true>(8); As you can see, my goal is to be able to have an alternative behaviour for sId. I know I could use a second parameter to the function and use a if, but this feels more fun (imo) and might prevent branch prediction (I'm no expert in that field). So, is it a valid practice, and/or is there a better approach?

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  • What is involved for a simple UDP game?

    - by acidzombie24
    I once tried to write a simple game with UDP in a week as a throwaway test. It went horribly. I threw it away early. The main problem i had was restoring the game state of all players/enemies/objects to an old state and fast forward the game to the point of time the player is playing (ie half a second before a jump. A little early or late can make the player miss the jump) Maybe this method is not the easiest way? i suspect it to be but i designed it wrong from the beginning and realized at the end of 2nd day. (so i didnt learn too much or wasted that much time) For myself and others, What is involved for a simple UDP game and how do i write one? Or how do i solve the prediction problem restoring to state properly. I'll mark this as CW bc i know there will be lots of helpful answers.

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  • Short Season, Long Models - Dealing with Seasonality

    - by Michel Adar
    Accounting for seasonality presents a challenge for the accurate prediction of events. Examples of seasonality include: ·         Boxed cosmetics sets are more popular during Christmas. They sell at other times of the year, but they rise higher than other products during the holiday season. ·         Interest in a promotion rises around the time advertising on TV airs ·         Interest in the Sports section of a newspaper rises when there is a big football match There are several ways of dealing with seasonality in predictions. Time Windows If the length of the model time windows is short enough relative to the seasonality effect, then the models will see only seasonal data, and therefore will be accurate in their predictions. For example, a model with a weekly time window may be quick enough to adapt during the holiday season. In order for time windows to be useful in dealing with seasonality it is necessary that: The time window is significantly shorter than the season changes There is enough volume of data in the short time windows to produce an accurate model An additional issue to consider is that sometimes the season may have an abrupt end, for example the day after Christmas. Input Data If available, it is possible to include the seasonality effect in the input data for the model. For example the customer record may include a list of all the promotions advertised in the area of residence. A model with these inputs will have to learn the effect of the input. It is possible to learn it specific to the promotion – and by the way learn about inter-promotion cross feeding – by leaving the list of ads as it is; or it is possible to learn the general effect by having a flag that indicates if the promotion is being advertised. For inputs to properly represent the effect in the model it is necessary that: The model sees enough events with the input present. For example, by virtue of the model lifetime (or time window) being long enough to see several “seasons” or by having enough volume for the model to learn seasonality quickly. Proportional Frequency If we create a model that ignores seasonality it is possible to use that model to predict how the specific person likelihood differs from average. If we have a divergence from average then we can transfer that divergence proportionally to the observed frequency at the time of the prediction. Definitions: Ft = trailing average frequency of the event at time “t”. The average is done over a suitable period of to achieve a statistical significant estimate. F = average frequency as seen by the model. L = likelihood predicted by the model for a specific person Lt = predicted likelihood proportionally scaled for time “t”. If the model is good at predicting deviation from average, and this holds over the interesting range of seasons, then we can estimate Lt as: Lt = L * (Ft / F) Considering that: L = (L – F) + F Substituting we get: Lt = [(L – F) + F] * (Ft / F) Which simplifies to: (i)                  Lt = (L – F) * (Ft / F)  +  Ft This latest expression can be understood as “The adjusted likelihood at time t is the average likelihood at time t plus the effect from the model, which is calculated as the difference from average time the proportion of frequencies”. The formula above assumes a linear translation of the proportion. It is possible to generalize the formula using a factor which we will call “a” as follows: (ii)                Lt = (L – F) * (Ft / F) * a  +  Ft It is also possible to use a formula that does not scale the difference, like: (iii)               Lt = (L – F) * a  +  Ft While these formulas seem reasonable, they should be taken as hypothesis to be proven with empirical data. A theoretical analysis provides the following insights: The Cumulative Gains Chart (lift) should stay the same, as at any given time the order of the likelihood for different customers is preserved If F is equal to Ft then the formula reverts to “L” If (Ft = 0) then Lt in (i) and (ii) is 0 It is possible for Lt to be above 1. If it is desired to avoid going over 1, for relatively high base frequencies it is possible to use a relative interpretation of the multiplicative factor. For example, if we say that Y is twice as likely as X, then we can interpret this sentence as: If X is 3%, then Y is 6% If X is 11%, then Y is 22% If X is 70%, then Y is 85% - in this case we interpret “twice as likely” as “half as likely to not happen” Applying this reasoning to (i) for example we would get: If (L < F) or (Ft < (1 / ((L/F) + 1)) Then  Lt = L * (Ft / F) Else Lt = 1 – (F / L) + (Ft * F / L)  

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  • T9 patented while QWERTY is not?

    - by Marco W.
    I've seen that there are lots of custom keyboards for Android, but all are QWERTY keyboards. I couldn't find any keyboard with T9 layout. Is this because T9 is patented and the QWERTY layout is not? So if I made a T9 keyboard, I would have to pay patent fees? So what does the patent protect when you look at T9? Only the layout? Or the prediction engine? The problem is, this way of predicting words is the only one that makes sense for this layout ...

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  • Google livre quelques secrets sur la recherche vocale, la précision du système extrêmement liée à la quantité de données

    Google dévoile quelques secrets sur la recherche vocale la précision du système extrêmement liée à la quantité de données Google Research, la division de recherche de Google a publié un document qui décrit un peu comment sa technologie de recherche vocale fonctionne. Les mécanismes qui sont développés au sein de ses applications de reconnaissance vocale reposent essentiellement sur les données. En effet, les chercheurs ont constaté que la présence des quantités de données énormes entraine moins d'erreurs lors de la prédiction du mot suivant en fonction des mots qui le précèdent. Selon l'article publié par Google, son implémentation de la recherche vocale utilise pr...

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  • Les premiers smartphones dual-core présentés au CES hier, à quoi servira une telle puissance ?

    Les premiers smartphones dual-core présentés au CES hier, à quoi servira une telle puissance ? Mise à jour du 06.01.2011 par Katleen Début décembre 2010, Nvidia affirmait que "les processeurs dual-core seront le standard en 2011" pour les smartphones et pour les tablettes. Cette prédiction semble être sur le chemin de la réalisation, comme l'ont démontré certains acteurs du secteur hier au CES. En effet, les premiers modèles de téléphones mobiles multi-coeurs y ont été présentés. Motorola a dévoilé son Atrix 4G qu'il vante comme «le smartphone le plus puissant du monde». Dans ses entrailles, on trouve un processeur dual-core Tegra 2 cadencé à 2 Ghz et 1 Go de RAM. De quoi réaliser de ...

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  • unix tool to remove duplicate lines from a file

    - by Nathan Fellman
    I have a tool that generates tests and predicts the output. The idea is that if I have a failure I can compare the prediction to the actual output and see where they diverged. The problem is the actual output contains some lines twice, which confuses diff. I want to remove the duplicates, so that I can compare them easily. Basically, something like sort -u but without the sorting. Is there any unix commandline tool that can do this?

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  • What list of words can be used in commit messages after fixing a bug?

    - by mkafkas
    I am currently working on a senior project on software engineering and implementing a defect prediction mechanism in software projects which use version control system. Therefore, i want to ask the community about their commit message procedures. Which words in the commit messages may infer "bug fixed" meaning? So that, i can understand that the modified files in that revision was in a buggy state?

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  • Making sense of S.M.A.R.T

    - by James
    First of all, I think everyone knows that hard drives fail a lot more than the manufacturers would like to admit. Google did a study that indicates that certain raw data attributes that the S.M.A.R.T status of hard drives reports can have a strong correlation with the future failure of the drive. We find, for example, that after their first scan error, drives are 39 times more likely to fail within 60 days than drives with no such errors. First errors in re- allocations, offline reallocations, and probational counts are also strongly correlated to higher failure probabil- ities. Despite those strong correlations, we find that failure prediction models based on SMART parameters alone are likely to be severely limited in their prediction accuracy, given that a large fraction of our failed drives have shown no SMART error signals whatsoever. Seagate seems like it is trying to obscure this information about their drives by claiming that only their software can accurately determine the accurate status of their drive and by the way their software will not tell you the raw data values for the S.M.A.R.T attributes. Western digital has made no such claim to my knowledge but their status reporting tool does not appear to report raw data values either. I've been using HDtune and smartctl from smartmontools in order to gather the raw data values for each attribute. I've found that indeed... I am comparing apples to oranges when it comes to certain attributes. I've found for example that most Seagate drives will report that they have many millions of read errors while western digital 99% of the time shows 0 for read errors. I've also found that Seagate will report many millions of seek errors while Western Digital always seems to report 0. Now for my question. How do I normalize this data? Is Seagate producing millions of errors while Western digital is producing none? Wikipedia's article on S.M.A.R.T status says that manufacturers have different ways of reporting this data. Here is my hypothesis: I think I found a way to normalize (is that the right term?) the data. Seagate drives have an additional attribute that Western Digital drives do not have (Hardware ECC Recovered). When you subtract the Read error count from the ECC Recovered count, you'll probably end up with 0. This seems to be equivalent to Western Digitals reported "Read Error" count. This means that Western Digital only reports read errors that it cannot correct while Seagate counts up all read errors and tells you how many of those it was able to fix. I had a Seagate drive where the ECC Recovered count was less than the Read error count and I noticed that many of my files were becoming corrupt. This is how I came up with my hypothesis. The millions of seek errors that Seagate produces are still a mystery to me. Please confirm or correct my hypothesis if you have additional information. Here is the smart status of my western digital drive just so you can see what I'm talking about: james@ubuntu:~$ sudo smartctl -a /dev/sda smartctl version 5.38 [x86_64-unknown-linux-gnu] Copyright (C) 2002-8 Bruce Allen Home page is http://smartmontools.sourceforge.net/ === START OF INFORMATION SECTION === Device Model: WDC WD1001FALS-00E3A0 Serial Number: WD-WCATR0258512 Firmware Version: 05.01D05 User Capacity: 1,000,204,886,016 bytes Device is: Not in smartctl database [for details use: -P showall] ATA Version is: 8 ATA Standard is: Exact ATA specification draft version not indicated Local Time is: Thu Jun 10 19:52:28 2010 PDT SMART support is: Available - device has SMART capability. SMART support is: Enabled === START OF READ SMART DATA SECTION === SMART overall-health self-assessment test result: PASSED SMART Attributes Data Structure revision number: 16 Vendor Specific SMART Attributes with Thresholds: ID# ATTRIBUTE_NAME FLAG VALUE WORST THRESH TYPE UPDATED WHEN_FAILED RAW_VALUE 1 Raw_Read_Error_Rate 0x002f 200 200 051 Pre-fail Always - 0 3 Spin_Up_Time 0x0027 179 175 021 Pre-fail Always - 4033 4 Start_Stop_Count 0x0032 100 100 000 Old_age Always - 270 5 Reallocated_Sector_Ct 0x0033 200 200 140 Pre-fail Always - 0 7 Seek_Error_Rate 0x002e 200 200 000 Old_age Always - 0 9 Power_On_Hours 0x0032 098 098 000 Old_age Always - 1468 10 Spin_Retry_Count 0x0032 100 100 000 Old_age Always - 0 11 Calibration_Retry_Count 0x0032 100 100 000 Old_age Always - 0 12 Power_Cycle_Count 0x0032 100 100 000 Old_age Always - 262 192 Power-Off_Retract_Count 0x0032 200 200 000 Old_age Always - 46 193 Load_Cycle_Count 0x0032 200 200 000 Old_age Always - 223 194 Temperature_Celsius 0x0022 105 102 000 Old_age Always - 42 196 Reallocated_Event_Count 0x0032 200 200 000 Old_age Always - 0 197 Current_Pending_Sector 0x0032 200 200 000 Old_age Always - 0 198 Offline_Uncorrectable 0x0030 200 200 000 Old_age Offline - 0 199 UDMA_CRC_Error_Count 0x0032 200 200 000 Old_age Always - 0 200 Multi_Zone_Error_Rate 0x0008 200 200 000 Old_age Offline - 0

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  • Nagios notifications definitions

    - by Colin
    I am trying to monitor a web server in such a way that I want to search for a particular string on a page via http. The command is defined in command.cfg as follows # 'check_http-mysite command definition' define command { command_name check_http-mysite command_line /usr/lib/nagios/plugins/check_http -H mysite.example.com -s "Some text" } # 'notify-host-by-sms' command definition define command { command_name notify-host-by-sms command_line /usr/bin/send_sms $CONTACTPAGER$ "Nagios - $NOTIFICATIONTYPE$ :Host$HOSTALIAS$ is $HOSTSTATE$ ($OUTPUT$)" } # 'notify-service-by-sms' command definition define command { command_name notify-service-by-sms command_line /usr/bin/send_sms $CONTACTPAGER$ "Nagios - $NOTIFICATIONTYPE$: $HOSTALIAS$/$SERVICEDESC$ is $SERVICESTATE$ ($OUTPUT$)" } Now if nagios doesn't find "Some text" on the home page mysite.example.com, nagios should notify a contact via sms through the Clickatell http API which I have a script for that that I have tested and found that it works fine. Whenever I change the command definition to search for a string which is not on the page, and restart nagios, I can see on the web interface that the string was not found. What I don't understand is why isn't the notification sent though I have defined the host, hostgroup, contact, contactgroup and service and so forth. What I'm I missing, these are my definitions, In my web access through the cgi I can see that I have notifications have been defined and enabled though I don't get both email and sms notifications during hard status changes. host.cfg define host { use generic-host host_name HAL alias IBM-1 address xxx.xxx.xxx.xxx check_command check_http-mysite } *hostgroups_nagios2.cfg* # my website define hostgroup{ hostgroup_name my-servers alias All My Servers members HAL } *contacts_nagios2.cfg* define contact { contact_name colin alias Colin Y service_notification_period 24x7 host_notification_period 24x7 service_notification_options w,u,c,r,f,s host_notification_options d,u,r,f,s service_notification_commands notify-service-by-email,notify-service-by-sms host_notification_commands notify-host-by-email,notify-host-by-sms email [email protected] pager +254xxxxxxxxx } define contactgroup{ contactgroup_name site_admin alias Site Administrator members colin } *services_nagios2.cfg* # check for particular string in page via http define service { hostgroup_name my-servers service_description STRING CHECK check_command check_http-mysite use generic-service notification_interval 0 ; set > 0 if you want to be renotified contacts colin contact_groups site_admin } Could someone please tell me where I'm going wrong. Here are the generic-host and generic-service definitions *generic-service_nagios2.cfg* # generic service template definition define service{ name generic-service ; The 'name' of this service template active_checks_enabled 1 ; Active service checks are enabled passive_checks_enabled 1 ; Passive service checks are enabled/accepted parallelize_check 1 ; Active service checks should be parallelized (disabling this can lead to major performance problems) obsess_over_service 1 ; We should obsess over this service (if necessary) check_freshness 0 ; Default is to NOT check service 'freshness' notifications_enabled 1 ; Service notifications are enabled event_handler_enabled 1 ; Service event handler is enabled flap_detection_enabled 1 ; Flap detection is enabled failure_prediction_enabled 1 ; Failure prediction is enabled process_perf_data 1 ; Process performance data retain_status_information 1 ; Retain status information across program restarts retain_nonstatus_information 1 ; Retain non-status information across program restarts notification_interval 0 ; Only send notifications on status change by default. is_volatile 0 check_period 24x7 normal_check_interval 5 retry_check_interval 1 max_check_attempts 4 notification_period 24x7 notification_options w,u,c,r contact_groups site_admin register 0 ; DONT REGISTER THIS DEFINITION - ITS NOT A REAL SERVICE, JUST A TEMPLATE! } *generic-host_nagios2.cfg* define host{ name generic-host ; The name of this host template notifications_enabled 1 ; Host notifications are enabled event_handler_enabled 1 ; Host event handler is enabled flap_detection_enabled 1 ; Flap detection is enabled failure_prediction_enabled 1 ; Failure prediction is enabled process_perf_data 1 ; Process performance data retain_status_information 1 ; Retain status information across program restarts retain_nonstatus_information 1 ; Retain non-status information across program restarts max_check_attempts 10 notification_interval 0 notification_period 24x7 notification_options d,u,r contact_groups site_admin register 1 ; DONT REGISTER THIS DEFINITION - ITS NOT A REAL HOST, JUST A TEMPLATE! }

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