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  • Partition Wise Joins II

    - by jean-pierre.dijcks
    One of the things that I did not talk about in the initial partition wise join post was the effect it has on resource allocation on the database server. When Oracle applies a different join method - e.g. not PWJ - what you will see in SQL Monitor (in Enterprise Manager) or in an Explain Plan is a set of producers and a set of consumers. The producers scan the tables in the the join. If there are two tables the producers first scan one table, then the other. The producers thus provide data to the consumers, and when the consumers have the data from both scans they do the join and give the data to the query coordinator. Now that behavior means that if you choose a degree of parallelism of 4 to run such query with, Oracle will allocate 8 parallel processes. Of these 8 processes 4 are producers and 4 are consumers. The consumers only actually do work once the producers are fully done with scanning both sides of the join. In the plan above you can see that the producers access table SALES [line 11] and then do a PX SEND [line 9]. That is the producer set of processes working. The consumers receive that data [line 8] and twiddle their thumbs while the producers go on and scan CUSTOMERS. The producers send that data to the consumer indicated by PX SEND [line 5]. After receiving that data [line 4] the consumers do the actual join [line 3] and give the data to the QC [line 2]. BTW, the myth that you see twice the number of processes due to the setting PARALLEL_THREADS_PER_CPU=2 is obviously not true. The above is why you will see 2 times the processes of the DOP. In a PWJ plan the consumers are not present. Instead of producing rows and giving those to different processes, a PWJ only uses a single set of processes. Each process reads its piece of the join across the two tables and performs the join. The plan here is notably different from the initial plan. First of all the hash join is done right on top of both table scans [line 8]. This query is a little more complex than the previous so there is a bit of noise above that bit of info, but for this post, lets ignore that (sort stuff). The important piece here is that the PWJ plan typically will be faster and from a PX process number / resources typically cheaper. You may want to look out for those plans and try to get those to appear a lot... CREDITS: credits for the plans and some of the info on the plans go to Maria, as she actually produced these plans and is the expert on plans in general... You can see her talk about explaining the explain plan and other optimizer stuff over here: ODTUG in Washington DC, June 27 - July 1 On the Optimizer blog At OpenWorld in San Francisco, September 19 - 23 Happy joining and hope to see you all at ODTUG and OOW...

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  • How To Peel Garlic In Quick & Easy Way

    - by Gopinath
    Garlic is very common ingredient used in cooking in many parts of the world. In India it’s an undeniable ingredient in almost all the food items that are made using masala. So every cook of Indian kitchen knows the pain of peeling garlic. It’s a messy and time consuming process to peel of all the dead skin layers to get the tasty cloves. Cooking web site Saveur shows us as easy way to peel an entire garlic in less than 10 seconds using just two bowls.  No knifes, no scissor or any other instruments. Check the embedded video   I’ve not yet tried this trick at home, but looks like very easy one. What do you say? via Lifehacker (thanks vijay). cc image credit: flickr/lightlady

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  • Cosmic Journeys – Supermassive Black Hole at the Center of the Galaxy

    - by Akemi Iwaya
    Even though the center of our galaxy is obscured by thick dust and blinding starlight, that has not stopped scientists from piecing together clues about what may lie there. Sit back and enjoy a ‘cosmic journey’ with this excellent half-hour video from YouTube channel SpaceRip discussing what scientists have learned about the supermassive black hole at the center of our galaxy, and their work on getting a ‘direct image’ of it. Cosmic Journeys: Supermassive Black Hole at the Center of the Galaxy [YouTube]     

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  • Unity Is The Swiss Army Knife of Game Console Mods

    - by Jason Fitzpatrick
    This expansive console modification blends over a dozen game systems into one unified console with a shared power source and controller. There are console mods and then there are builds like this. This impressive work in progress combines the hardware boards of multiple game systems into a single unified system that shares a single power source, video output, and controller. The attention to detail and outright gaming obsession and geekiness is definitely creeping to the top of the charts with this one. Hit up the link below to check out a detailed post about the build and see additional videos and photos. Bacteria’s Project Unity [via Hack A Day] HTG Explains: Why You Only Have to Wipe a Disk Once to Erase It HTG Explains: Learn How Websites Are Tracking You Online Here’s How to Download Windows 8 Release Preview Right Now

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  • Tools for modelling data and workflows using structured text files

    - by Alexey
    Consider a case when I want to try some idea of an application. But I want to avoid investing a lot of effort in coding UI/work flows/database schema etc before I see that it's going to be useful to me (as example of potential user). My idea is stay lightweight and put all the data in text files. So the components could be following: Domain objects are represented by text files or their fragments Domain objects are grouped by their type using directories Structure the files using some both human- and machine-friendly format, e.g. YAML Use some smart text editor (e.g. vim, emacs, rubymine) to edit and navigate those files Use color schemes and macros/custom commands of the text editor to effectively manipulate those files Use scripts (or a lightweight web framework like Sinatra) to try some business logic ideas on top of the data model The question is: Are there tools or toolkits that support or can be adopted to this approach? Also any ideas, links to articles/other knowledge sources are very welcome. And more specific question: What is the simplest way to index and update index of files with YAML files?

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  • Can Ubuntu create a semi-transparent subtitle player for accessibility?

    - by Tyler
    I've asked this in Reddit.com/r/Ubuntu in here. I've tried to get the Subtitle Player linked here to work and it have failed on Wine. So I'm curious if Ubuntu community would be willing to try and build a simple transparent subtitle player for better accessibility on Flash Player, Netflix, or even in movie theaters? Currently, I'm watching movies/videos with an Android Tablet that runs on a blank black video for 3 hours with a subtitle overlay on it so I can enjoy movie and so forth, but it requires a bit of effort and it definitely isn't for everyone. (People will have to look at the subtitle playing tablet and the movie back and forth at 60 degrees angle, while a transparent subtitle player would reduce it to 5 degrees angle to watch the movie.) Please and thank you.

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  • Integrating BizTalk Server and StreamInsight paper

    - by gsusx
    With all the holidays madness I didn't realized that my "Integrating BizTalk Server and StreamInsight" paper is now available on MSDN . This paper was originally an idea of the BizTalk product team and intends to present some fundamental scenarios that can be enabled by the combination of BizTalk Server and StreamInsight. Thanks to everybody who, directly or indirectly, provided feedback about this paper: Syed Rasheed, Mark Simms , Richard Seroter , Roman Schindlauer and Torsten Grabs from the StreamInsight...(read more)

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  • Convert DVD to MKV (et al) without transcoding/recompression

    - by Oli
    Like a lot of people, I have a lot of DVDs. But we also have a stupid amount of disk space and a media centre (Boxee) so the DVDs are getting less and less use. It would be nice to convert our DVDs into something more relevant to our needs. I've dabbled with DVD ripping before but whereas I'd usually transcode down to a smaller picture size with a better video compression algorithm, this takes a silly amount of time. I don't have a couple of hours available for each disk. (Sidebar: is there dedicated, Linux-friendly hardware to improve h264 encoding performance?) So I was wondering if there's anything that take the DVD filesystem, De-CSS it, and then stitch together any the VOBs that make up the main part of the film and package that up in a wrapping format like MKV. A bonus would be if it could grab the subtitles and stick them in too but that's not a requirement as Boxee can grab the subtitles online if it needs to.

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  • TableTop: Inside Last Night on Earth

    - by Jason Fitzpatrick
    In this edition of TableTop, Wil Wheaton, Felicia Day, and friends explore Last Night on Earth–a campy and cooperative game that pits teams of humans and zombies against each other in an infested small town. Each game is unique thanks to a modular game board and a hefty deck of scenarios for players to work their way through. You can read more about the game at BoardgameGeek or watch the above video above for a–highly animated–overview of the game. TableTop Episode 15: Last Night on Earth Can Dust Actually Damage My Computer? What To Do If You Get a Virus on Your Computer Why Enabling “Do Not Track” Doesn’t Stop You From Being Tracked

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  • Query Tuning Mastery at PASS Summit 2012: The Demos

    - by Adam Machanic
    For the second year in a row, I was asked to deliver a 500-level "Query Tuning Mastery" talk in room 6E of the Washington State Convention Center, for the PASS Summit. ( Here's some information about last year's talk, on workspace memory. ) And for the second year in a row, I had to deliver said talk at 10:15 in the morning, in a room used as overflow for the keynote, following a keynote speaker that didn't stop speaking on time. Frustrating! Last Thursday, after very, very quickly setting up and...(read more)

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  • Mario Warfare: Live Action Adventures in the Mushroom Kingdom

    - by Jason Fitzpatrick
    What if the tale of the Mario Bros. and their exploits was told in the form of an action flick? Mario Warfare explores the gritty side of the battle for the Mushroom Kingdom. In the above video we’re treated to a trailer-style peek at a work-in progress film. While there is no set release date, we have our fingers crossed that it’s completed sooner rather than later–a film this awesome demands to be seen. [via Geekosystem] How to Get Pro Features in Windows Home Versions with Third Party Tools HTG Explains: Is ReadyBoost Worth Using? HTG Explains: What The Windows Event Viewer Is and How You Can Use It

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  • Convert DVD to MKV (et al) without transcoding/recompression

    - by Oli
    Like a lot of people, I have a lot of DVDs. But we also have a stupid amount of disk space and a media centre (Boxee) so the DVDs are getting less and less use. It would be nice to convert our DVDs into something more relevant to our needs. I've dabbled with DVD ripping before but whereas I'd usually transcode down to a smaller picture size with a better video compression algorithm, this takes a silly amount of time. I don't have a couple of hours available for each disk. (Sidebar: is there dedicated, Linux-friendly hardware to improve h264 encoding performance?) So I was wondering if there's anything that take the DVD filesystem, De-CSS it, and then stitch together any the VOBs that make up the main part of the film and package that up in a wrapping format like MKV. A bonus would be if it could grab the subtitles and stick them in too but that's not a requirement as Boxee can grab the subtitles online if it needs to.

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  • Portal Ported to a Graphing Calculator

    - by Jason Fitzpatrick
    It’s not exactly a 3D-rendered GPU-burner, but this calculator-based version of Portal still features the same portal-jumping tricks that delighted players in the original game. Built using Axe Parser, an advanced programming language for graphing calculators, Portal: Prelude is part an experiment in pushing the limits of Axe Parser and part long standing tradition of porting popular video games to graphing calculators. You can read more about Axe Parser and the many games and program projects under development using it here. [via Geeks Are Sexy] How to Fix a Stuck Pixel on an LCD Monitor How to Factory Reset Your Android Phone or Tablet When It Won’t Boot Our Geek Trivia App for Windows 8 is Now Available Everywhere

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  • SQL University: Parallelism Week - Introduction

    - by Adam Machanic
    Welcome to Parallelism Week at SQL University . My name is Adam Machanic, and I'm your professor. Imagine having 8 brains, or 16, or 32. Imagine being able to break up complex thoughts and distribute them across your many brains, so that you could solve problems faster. Now quit imagining that, because you're human and you're stuck with only one brain, and you only get access to the entire thing if you're lucky enough to have avoided abusing too many recreational drugs. For your database server,...(read more)

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  • Does Bad Weather Affect Cloud Computing? [Humor]

    - by Jason Fitzpatrick
    Indian government official Vishwa Bandhu Gupta deserves a Master Class Troll Lifetime Achievement Award for his performance in this five minute video and complete bamboozling of a poor reporter. Before we ridicule the reporter for buying Gupta’s spiel, keep in mind that 51% of Americans think cloud computing actually has something to do with clouds. Cloud Computing Is Great, But What If It Rains? [via Digital Inspiration] HTG Explains: Why Do Hard Drives Show the Wrong Capacity in Windows? Java is Insecure and Awful, It’s Time to Disable It, and Here’s How What Are the Windows A: and B: Drives Used For?

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  • Stereo images rectification and disparity: which algorithms?

    - by alessandro.francesconi
    I'm trying to figure out what are currently the two most efficent algorithms that permit, starting from a L/R pair of stereo images created using a traditional camera (so affected by some epipolar lines misalignment), to produce a pair of adjusted images plus their depth information by looking at their disparity. Actually I've found lots of papers about these two methods, like: "Computing Rectifying Homographies for Stereo Vision" (Zhang - seems one of the best for rectification only) "Three-step image recti?cation" (Monasse) "Rectification and Disparity" (slideshow by Navab) "A fast area-based stereo matching algorithm" (Di Stefano - seems a bit inaccurate) "Computing Visual Correspondence with Occlusions via Graph Cuts" (Kolmogorov - this one produces a very good disparity map, with also occlusion informations, but is it efficient?) "Dense Disparity Map Estimation Respecting Image Discontinuities" (Alvarez - toooo long for a first review) Anyone could please give me some advices for orienting into this wide topic? What kind of algorithm/method should I treat first, considering that I'll work on a very simple input: a pair of left and right images and nothing else, no more information (some papers are based on additional, pre-taken, calibration infos)? Speaking about working implementations, the only interesting results I've seen so far belongs to this piece of software, but only for automatic rectification, not disparity: http://stereo.jpn.org/eng/stphmkr/index.html I tried the "auto-adjustment" feature and seems really effective. Too bad there is no source code...

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  • How advanced are author-recognition methods?

    - by Nick Rtz
    From a written text by an author if a computer program analyses the text, how much can a computer program tell today about the author of some (long enough to be statistically significant) texts? Can the computer program even tell with "certainty" whether a man or a woman wrote this text based solely on the contents of the text and not an investigation such as ip numbers etc? I'm interested to know if there are algorithms in use for instance to automatically know whether an author was male or female or similar characteristics of an author that a computer program can decide based on analyses of the written text by an author. It could be useful to know before you read a message what a computer analyses says about the author, do you agree? If I for instance get a longer message from my wife that she has had an accident in Nigeria and the computer program says that with 99 % probability the message was written by a male author in his sixties of non-caucasian origin or likewise, or by somebody who is not my wife, then the computer program could help me investigate why a certain message differs in characteristics. There can also be other uses for instance just detecting outliers in a geographically or demographically bounded larger data set. Scam detection is the obvious use I'm thinking of but there could also be other uses. Are there already such programs that analyse a written text to tell something about the author based on word choice, use of pronouns, unusual language usage, or likewise?

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  • The Lost Episode of Cosmos: The Meat Planet

    - by Jason Fitzpatrick
    In the 1980s Carl Sagan captivated TV viewers with his exploration of the universe; we present to you, a lost episode, The Meat Planet. Creators of the parody video, Darren Cullen and Mark Tolson, engaged in some expert splicing and dicing of past Cosmos episodes to create their masterpiece: the lost episode focused on the fabled Meat Planet. Watch the episode above or hit up the link below for more information about the project. Meat Planet [via Boing Boing] How Hackers Can Disguise Malicious Programs With Fake File Extensions Can Dust Actually Damage My Computer? What To Do If You Get a Virus on Your Computer

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  • How to store generated eigen faces for future face recognition?

    - by user3237134
    My code works in the following manner: 1.First, it obtains several images from the training set 2.After loading these images, we find the normalized faces,mean face and perform several calculation. 3.Next, we ask for the name of an image we want to recognize 4.We then project the input image into the eigenspace, and based on the difference from the eigenfaces we make a decision. 5.Depending on eigen weight vector for each input image we make clusters using kmeans command. Source code i tried: clear all close all clc % number of images on your training set. M=1200; %Chosen std and mean. %It can be any number that it is close to the std and mean of most of the images. um=60; ustd=32; %read and show images(bmp); S=[]; %img matrix for i=1:M str=strcat(int2str(i),'.jpg'); %concatenates two strings that form the name of the image eval('img=imread(str);'); [irow icol d]=size(img); % get the number of rows (N1) and columns (N2) temp=reshape(permute(img,[2,1,3]),[irow*icol,d]); %creates a (N1*N2)x1 matrix S=[S temp]; %X is a N1*N2xM matrix after finishing the sequence %this is our S end %Here we change the mean and std of all images. We normalize all images. %This is done to reduce the error due to lighting conditions. for i=1:size(S,2) temp=double(S(:,i)); m=mean(temp); st=std(temp); S(:,i)=(temp-m)*ustd/st+um; end %show normalized images for i=1:M str=strcat(int2str(i),'.jpg'); img=reshape(S(:,i),icol,irow); img=img'; end %mean image; m=mean(S,2); %obtains the mean of each row instead of each column tmimg=uint8(m); %converts to unsigned 8-bit integer. Values range from 0 to 255 img=reshape(tmimg,icol,irow); %takes the N1*N2x1 vector and creates a N2xN1 matrix img=img'; %creates a N1xN2 matrix by transposing the image. % Change image for manipulation dbx=[]; % A matrix for i=1:M temp=double(S(:,i)); dbx=[dbx temp]; end %Covariance matrix C=A'A, L=AA' A=dbx'; L=A*A'; % vv are the eigenvector for L % dd are the eigenvalue for both L=dbx'*dbx and C=dbx*dbx'; [vv dd]=eig(L); % Sort and eliminate those whose eigenvalue is zero v=[]; d=[]; for i=1:size(vv,2) if(dd(i,i)>1e-4) v=[v vv(:,i)]; d=[d dd(i,i)]; end end %sort, will return an ascending sequence [B index]=sort(d); ind=zeros(size(index)); dtemp=zeros(size(index)); vtemp=zeros(size(v)); len=length(index); for i=1:len dtemp(i)=B(len+1-i); ind(i)=len+1-index(i); vtemp(:,ind(i))=v(:,i); end d=dtemp; v=vtemp; %Normalization of eigenvectors for i=1:size(v,2) %access each column kk=v(:,i); temp=sqrt(sum(kk.^2)); v(:,i)=v(:,i)./temp; end %Eigenvectors of C matrix u=[]; for i=1:size(v,2) temp=sqrt(d(i)); u=[u (dbx*v(:,i))./temp]; end %Normalization of eigenvectors for i=1:size(u,2) kk=u(:,i); temp=sqrt(sum(kk.^2)); u(:,i)=u(:,i)./temp; end % show eigenfaces; for i=1:size(u,2) img=reshape(u(:,i),icol,irow); img=img'; img=histeq(img,255); end % Find the weight of each face in the training set. omega = []; for h=1:size(dbx,2) WW=[]; for i=1:size(u,2) t = u(:,i)'; WeightOfImage = dot(t,dbx(:,h)'); WW = [WW; WeightOfImage]; end omega = [omega WW]; end % Acquire new image % Note: the input image must have a bmp or jpg extension. % It should have the same size as the ones in your training set. % It should be placed on your desktop ed_min=[]; srcFiles = dir('G:\newdatabase\*.jpg'); % the folder in which ur images exists for b = 1 : length(srcFiles) filename = strcat('G:\newdatabase\',srcFiles(b).name); Imgdata = imread(filename); InputImage=Imgdata; InImage=reshape(permute((double(InputImage)),[2,1,3]),[irow*icol,1]); temp=InImage; me=mean(temp); st=std(temp); temp=(temp-me)*ustd/st+um; NormImage = temp; Difference = temp-m; p = []; aa=size(u,2); for i = 1:aa pare = dot(NormImage,u(:,i)); p = [p; pare]; end InImWeight = []; for i=1:size(u,2) t = u(:,i)'; WeightOfInputImage = dot(t,Difference'); InImWeight = [InImWeight; WeightOfInputImage]; end noe=numel(InImWeight); % Find Euclidean distance e=[]; for i=1:size(omega,2) q = omega(:,i); DiffWeight = InImWeight-q; mag = norm(DiffWeight); e = [e mag]; end ed_min=[ed_min MinimumValue]; theta=6.0e+03; %disp(e) z(b,:)=InImWeight; end IDX = kmeans(z,5); clustercount=accumarray(IDX, ones(size(IDX))); disp(clustercount); QUESTIONS: 1.It is working fine for M=50(i.e Training set contains 50 images) but not for M=1200(i.e Training set contains 1200 images).It is not showing any error.There is no output.I waited for 10 min still there is no output. I think it is going infinite loop.What is the problem?Where i was wrong? 2.Instead of running the training set everytime how eigen faces generated are stored so that stored eigen faces are used for future face recoginition for a new input image.So it reduces wastage of time.

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  • XNA - Error while rendering a texture to a 2D render target via SpriteBatch

    - by Jared B
    I've got this simple code that uses SpriteBatch to draw a texture onto a RenderTarget2D: private void drawScene(GameTime g) { GraphicsDevice.Clear(skyColor); GraphicsDevice.SetRenderTarget(targetScene); drawSunAndMoon(); effect.Fog = true; GraphicsDevice.SetVertexBuffer(line); effect.MainEffect.CurrentTechnique.Passes[0].Apply(); GraphicsDevice.DrawPrimitives(PrimitiveType.TriangleStrip, 0, 2); GraphicsDevice.SetRenderTarget(null); SceneTexture = targetScene; } private void drawPostProcessing(GameTime g) { effect.SceneTexture = SceneTexture; GraphicsDevice.SetRenderTarget(targetBloom); spriteBatch.Begin(SpriteSortMode.Immediate, BlendState.Opaque, null, null, null); { if (Bloom) effect.BlurEffect.CurrentTechnique.Passes[0].Apply(); spriteBatch.Draw( targetScene, new Rectangle(0, 0, Window.ClientBounds.Width, Window.ClientBounds.Height), Color.White); } spriteBatch.End(); BloomTexture = targetBloom; GraphicsDevice.SetRenderTarget(null); } Both methods are called from my Draw(GameTime gameTime) function. First drawScene is called, then drawPostProcessing is called. The thing is, when I run this code I get an error on the spriteBatch.Draw call: The render target must not be set on the device when it is used as a texture. I already found the solution, which is to draw the actual render target (targetScene) to the texture so it doesn't create a reference to the loaded render target. However, to my knowledge, the only way of doing this is to write: GraphicsDevice.SetRenderTarget(outputTarget) SpriteBatch.Draw(inputTarget, ...) GraphicsDevice.SetRenderTarget(null) Which encounters the same exact problem I'm having right now. So, the question I'm asking is: how would I render inputTarget to outputTarget without reference issues?

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  • Vectorization of matlab code for faster execution

    - by user3237134
    My code works in the following manner: 1.First, it obtains several images from the training set 2.After loading these images, we find the normalized faces,mean face and perform several calculation. 3.Next, we ask for the name of an image we want to recognize 4.We then project the input image into the eigenspace, and based on the difference from the eigenfaces we make a decision. 5.Depending on eigen weight vector for each input image we make clusters using kmeans command. Source code i tried: clear all close all clc % number of images on your training set. M=1200; %Chosen std and mean. %It can be any number that it is close to the std and mean of most of the images. um=60; ustd=32; %read and show images(bmp); S=[]; %img matrix for i=1:M str=strcat(int2str(i),'.jpg'); %concatenates two strings that form the name of the image eval('img=imread(str);'); [irow icol d]=size(img); % get the number of rows (N1) and columns (N2) temp=reshape(permute(img,[2,1,3]),[irow*icol,d]); %creates a (N1*N2)x1 matrix S=[S temp]; %X is a N1*N2xM matrix after finishing the sequence %this is our S end %Here we change the mean and std of all images. We normalize all images. %This is done to reduce the error due to lighting conditions. for i=1:size(S,2) temp=double(S(:,i)); m=mean(temp); st=std(temp); S(:,i)=(temp-m)*ustd/st+um; end %show normalized images for i=1:M str=strcat(int2str(i),'.jpg'); img=reshape(S(:,i),icol,irow); img=img'; end %mean image; m=mean(S,2); %obtains the mean of each row instead of each column tmimg=uint8(m); %converts to unsigned 8-bit integer. Values range from 0 to 255 img=reshape(tmimg,icol,irow); %takes the N1*N2x1 vector and creates a N2xN1 matrix img=img'; %creates a N1xN2 matrix by transposing the image. % Change image for manipulation dbx=[]; % A matrix for i=1:M temp=double(S(:,i)); dbx=[dbx temp]; end %Covariance matrix C=A'A, L=AA' A=dbx'; L=A*A'; % vv are the eigenvector for L % dd are the eigenvalue for both L=dbx'*dbx and C=dbx*dbx'; [vv dd]=eig(L); % Sort and eliminate those whose eigenvalue is zero v=[]; d=[]; for i=1:size(vv,2) if(dd(i,i)>1e-4) v=[v vv(:,i)]; d=[d dd(i,i)]; end end %sort, will return an ascending sequence [B index]=sort(d); ind=zeros(size(index)); dtemp=zeros(size(index)); vtemp=zeros(size(v)); len=length(index); for i=1:len dtemp(i)=B(len+1-i); ind(i)=len+1-index(i); vtemp(:,ind(i))=v(:,i); end d=dtemp; v=vtemp; %Normalization of eigenvectors for i=1:size(v,2) %access each column kk=v(:,i); temp=sqrt(sum(kk.^2)); v(:,i)=v(:,i)./temp; end %Eigenvectors of C matrix u=[]; for i=1:size(v,2) temp=sqrt(d(i)); u=[u (dbx*v(:,i))./temp]; end %Normalization of eigenvectors for i=1:size(u,2) kk=u(:,i); temp=sqrt(sum(kk.^2)); u(:,i)=u(:,i)./temp; end % show eigenfaces; for i=1:size(u,2) img=reshape(u(:,i),icol,irow); img=img'; img=histeq(img,255); end % Find the weight of each face in the training set. omega = []; for h=1:size(dbx,2) WW=[]; for i=1:size(u,2) t = u(:,i)'; WeightOfImage = dot(t,dbx(:,h)'); WW = [WW; WeightOfImage]; end omega = [omega WW]; end % Acquire new image % Note: the input image must have a bmp or jpg extension. % It should have the same size as the ones in your training set. % It should be placed on your desktop ed_min=[]; srcFiles = dir('G:\newdatabase\*.jpg'); % the folder in which ur images exists for b = 1 : length(srcFiles) filename = strcat('G:\newdatabase\',srcFiles(b).name); Imgdata = imread(filename); InputImage=Imgdata; InImage=reshape(permute((double(InputImage)),[2,1,3]),[irow*icol,1]); temp=InImage; me=mean(temp); st=std(temp); temp=(temp-me)*ustd/st+um; NormImage = temp; Difference = temp-m; p = []; aa=size(u,2); for i = 1:aa pare = dot(NormImage,u(:,i)); p = [p; pare]; end InImWeight = []; for i=1:size(u,2) t = u(:,i)'; WeightOfInputImage = dot(t,Difference'); InImWeight = [InImWeight; WeightOfInputImage]; end noe=numel(InImWeight); % Find Euclidean distance e=[]; for i=1:size(omega,2) q = omega(:,i); DiffWeight = InImWeight-q; mag = norm(DiffWeight); e = [e mag]; end ed_min=[ed_min MinimumValue]; theta=6.0e+03; %disp(e) z(b,:)=InImWeight; end IDX = kmeans(z,5); clustercount=accumarray(IDX, ones(size(IDX))); disp(clustercount); Running time for 50 images:Elapsed time is 103.947573 seconds. QUESTIONS: 1.It is working fine for M=50(i.e Training set contains 50 images) but not for M=1200(i.e Training set contains 1200 images).It is not showing any error.There is no output.I waited for 10 min still there is no output. I think it is going infinite loop.What is the problem?Where i was wrong?

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  • How to properly render a Frame Buffer to the BackBuffer in Stage3D / AGAL

    - by bigp
    After doing a render pass with RenderToTarget (RTT), how do you properly render that texture buffer to the screen while maintaining original scale / proportions so it doesn't stretch or lose quality? Can an AGAL VertexShader & FragmentShader be written so it's adaptable to any Texture size and Viewport dimensions? I find I'm getting some "blocky" effects in some of my first attempts at "ping-ponging" between two Texture buffers (to create trailing effects). Perhaps I'm not using the UVs correctly between the rendering-to-target and/or the backbuffer? Is there a simpler way just to "splash" the texture on the backbuffer, or is a Quad absolutely necessary (4 vertices, 2 triangles)? If it needs the Quad, should the Texture buffer be fully drawn (0.0 to 1.0 for vertical and horizontal UVs), or only a percentage of it should, like the example below? Texture Buffer U: 0.0 to viewport.width/texturebuffer.width; Texture Buffer V: 0.0 to viewport.height/texturebuffer.height; Thanks!

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  • Sentence Tree v/s Words List

    - by Rohit Jose
    I was recently tasked with building a Name Entity Recognizer as part of a project. The objective was to parse a given sentence and come up with all the possible combinations of the entities. One approach that was suggested was to keep a lookup table for all the know connector words like articles and conjunctions, remove them from the words list after splitting the sentence on the basis of the spaces. This would leave out the Name Entities in the sentence. A lookup is then done for these identified entities on another lookup table that associates them to the entity type, for example if the sentence was: Remember the Titans was a movie directed by Boaz Yakin, the possible outputs would be: {Remember the Titans,Movie} was {a movie,Movie} directed by {Boaz Yakin,director} {Remember the Titans,Movie} was a movie directed by Boaz Yakin {Remember the Titans,Movie} was {a movie,Movie} directed by Boaz Yakin {Remember the Titans,Movie} was a movie directed by {Boaz Yakin,director} Remember the Titans was {a movie,Movie} directed by Boaz Yakin Remember the Titans was {a movie,Movie} directed by {Boaz Yakin,director} Remember the Titans was a movie directed by {Boaz Yakin,director} Remember the {the titans,Movie,Sports Team} was {a movie,Movie} directed by {Boaz Yakin,director} Remember the {the titans,Movie,Sports Team} was a movie directed by Boaz Yakin Remember the {the titans,Movie,Sports Team} was {a movie,Movie} directed by Boaz Yakin Remember the {the titans,Movie,Sports Team} was a movie directed by {Boaz Yakin,director} The entity lookup table here would contain the following data: Remember the Titans=Movie a movie=Movie Boaz Yakin=director the Titans=Movie the Titans=Sports Team Another alternative logic that was put forward was to build a crude sentence tree that would contain the connector words in the lookup table as parent nodes and do a lookup in the entity table for the leaf node that might contain the entities. The tree that was built for the sentence above would be: The question I am faced with is the benefits of the two approaches, should I be going for the tree approach to represent the sentence parsing, since it provides a more semantic structure? Is there a better approach I should be going for solving it?

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  • Serial plans: Threshold / Parallel_degree_limit = 1

    - by jean-pierre.dijcks
    As a very short follow up on the previous post. So here is some more on getting a serial plan and why that happens Another reason - compared to the auto DOP is not on as we looked at in the earlier post - and often more prevalent to get a serial plan is if the plan simply does not take long enough to consider a parallel path. The resulting plan and note looks like this (note that this is a serial plan!): explain plan for select count(1) from sales; SELECT PLAN_TABLE_OUTPUT FROM TABLE(DBMS_XPLAN.DISPLAY()); PLAN_TABLE_OUTPUT -------------------------------------------------------------------------------- Plan hash value: 672559287 -------------------------------------------------------------------------------------- | Id  | Operation            | Name  | Rows  | Cost (%CPU)| Time     | Pstart| Pstop | -------------------------------------------------------------------------------------- PLAN_TABLE_OUTPUT -------------------------------------------------------------------------------- |   0 | SELECT STATEMENT     |       |     1 |     5   (0)| 00:00:01 |       |     | |   1 |  SORT AGGREGATE      |       |     1 |            |          |       |     | |   2 |   PARTITION RANGE ALL|       |   960 |     5   (0)| 00:00:01 |     1 |  16 | |   3 |    TABLE ACCESS FULL | SALES |   960 |     5   (0)| 00:00:01 |     1 |  16 | Note -----    - automatic DOP: Computed Degree of Parallelism is 1 because of parallel threshold 14 rows selected. The parallel threshold is referring to parallel_min_time_threshold and since I did not change the default (10s) the plan is not being considered for a parallel degree computation and is therefore staying with the serial execution. Now we go into the land of crazy: Assume I do want this DOP=1 to happen, I could set the parameter in the init.ora, but to highlight it in this case I changed it on the session: alter session set parallel_degree_limit = 1; The result I get is: ERROR: ORA-02097: parameter cannot be modified because specified value is invalid ORA-00096: invalid value 1 for parameter parallel_degree_limit, must be from among CPU IO AUTO INTEGER>=2 Which of course makes perfect sense...

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  • The Great Ball Contraption: A Massive Automated LEGO Construction

    - by Jason Fitzpatrick
    This massive LEGO construction combines 17 distinct modules into a lengthy factory-like conveyance system for five hundred LEGO balls. The variety and creativity of the methods employed is, dare we say, dazzling. Slotted robotic arms? Screw lifts? Handshake object transfers? Catapults that shoot baskets? The sheer number of creative and novel solutions LEGO builder Akiyuky employs to move the balls through his machine left us mesmerized for the whole seven minute video. Akiyuky’s LEGO Blog (Google Translate Interpreted)[via Make] How To Create a Customized Windows 7 Installation Disc With Integrated Updates How to Get Pro Features in Windows Home Versions with Third Party Tools HTG Explains: Is ReadyBoost Worth Using?

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