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  • Why use third-party vector libraries at all?

    - by Patrick Powns
    So I'm thinking of using the Eigen matrix library for a project I'm doing (2D space simulator). I just went ahead and profiled some code with Eigen::Vector2d, and with bare arrays. I noticed a 10x improvement in assigning values to elements in the array, and a 40x improvement in calculating the dot products. Here is my profiling if you want to check it out, basically it's ~4.065s against ~0.110s. Obviously bare arrays are much more efficient at dot products and assigning stuff. So why use the Eigen library (or any other library, Eigen just seemed the fastest)? Is it stability? Complicated maths that would be hard to code by yourself efficiently?

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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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  • eclipse show errors but compiles when external makefile

    - by Anthony
    I have some c++ code using CImg and Eigen libraries. At the c++ code I define a plugin like this #define cimg_plugin1 "my_plugin.h" #include "CImg.h" The plugin contains many method definitions that are used at the c++ code. I also have a makefile that when called from the command line (./make), allows me to compile everything, and generates an executable. I want to import this code into a new Eclipse project, and I do it so: NewProjectC++ projectmakefile projectempty project unmark "Use default location", and select the folder containing my code at the filesystem ProjectpropertiesC/C++ Buildunmark "Use default build command" and set it to use my makefile Also in project propertiesC/C++ GeneralPaths and SymbolsAdd paths to folders containing Eigen and CImg Rebuild index Clean project Restart eclipse When I build the project, eclipse tells me I have more than 1000 errors in "my_plugin.h", but it is capable to generate the executable. Even though, I would like to get rid of this errors, because they are annoying. Also, if I want to open the declaration of CImg methods used at the plugin, I can't. I know it has been asked before, but any of the solutions I found were satisfactory for me (most of them enumerated at the previous list). The sources I visited are the following, and I would be really happy if you find and tell me others I didn't see. Eclipse shows errors but project compile fine eclipse C project shows errors (Symbol could not be resolved) but it compiles Eclipse CDT shows some errors, but the project is successfully built http://www.eclipse.org/forums/index.php/t/247954/

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  • Inverse Kinematics with OpenGL/Eigen3 : unstable jacobian pseudoinverse

    - by SigTerm
    I'm trying to implement simple inverse kinematics test using OpenGL, Eigen3 and "jacobian pseudoinverse" method. The system works fine using "jacobian transpose" algorithm, however, as soon as I attempt to use "pseudoinverse", joints become unstable and start jerking around (eventually they freeze completely - unless I use "jacobian transpose" fallback computation). I've investigated the issue and turns out that in some cases jacobian.inverse()*jacobian has zero determinant and cannot be inverted. However, I've seen other demos on the internet (youtube) that claim to use same method and they do not seem to have this problem. So I'm uncertain where is the cause of the issue. Code is attached below: *.h: struct Ik{ float targetAngle; float ikLength; VectorXf angles; Vector3f root, target; Vector3f jointPos(int ikIndex); size_t size() const; Vector3f getEndPos(int index, const VectorXf& vec); void resize(size_t size); void update(float t); void render(); Ik(): targetAngle(0), ikLength(10){ } }; *.cpp: size_t Ik::size() const{ return angles.rows(); } Vector3f Ik::getEndPos(int index, const VectorXf& vec){ Vector3f pos(0, 0, 0); while(true){ Eigen::Affine3f t; float radAngle = pi*vec[index]/180.0f; t = Eigen::AngleAxisf(radAngle, Vector3f(-1, 0, 0)) * Eigen::Translation3f(Vector3f(0, 0, ikLength)); pos = t * pos; if (index == 0) break; index--; } return pos; } void Ik::resize(size_t size){ angles.resize(size); angles.setZero(); } void drawMarker(Vector3f p){ glBegin(GL_LINES); glVertex3f(p[0]-1, p[1], p[2]); glVertex3f(p[0]+1, p[1], p[2]); glVertex3f(p[0], p[1]-1, p[2]); glVertex3f(p[0], p[1]+1, p[2]); glVertex3f(p[0], p[1], p[2]-1); glVertex3f(p[0], p[1], p[2]+1); glEnd(); } void drawIkArm(float length){ glBegin(GL_LINES); float f = 0.25f; glVertex3f(0, 0, length); glVertex3f(-f, -f, 0); glVertex3f(0, 0, length); glVertex3f(f, -f, 0); glVertex3f(0, 0, length); glVertex3f(f, f, 0); glVertex3f(0, 0, length); glVertex3f(-f, f, 0); glEnd(); glBegin(GL_LINE_LOOP); glVertex3f(f, f, 0); glVertex3f(-f, f, 0); glVertex3f(-f, -f, 0); glVertex3f(f, -f, 0); glEnd(); } void Ik::update(float t){ targetAngle += t * pi*2.0f/10.0f; while (t > pi*2.0f) t -= pi*2.0f; target << 0, 8 + 3*sinf(targetAngle), cosf(targetAngle)*4.0f+5.0f; Vector3f tmpTarget = target; Vector3f targetDiff = tmpTarget - root; float l = targetDiff.norm(); float maxLen = ikLength*(float)angles.size() - 0.01f; if (l > maxLen){ targetDiff *= maxLen/l; l = targetDiff.norm(); tmpTarget = root + targetDiff; } Vector3f endPos = getEndPos(size()-1, angles); Vector3f diff = tmpTarget - endPos; float maxAngle = 360.0f/(float)angles.size(); for(int loop = 0; loop < 1; loop++){ MatrixXf jacobian(diff.rows(), angles.rows()); jacobian.setZero(); float step = 1.0f; for (int i = 0; i < angles.size(); i++){ Vector3f curRoot = root; if (i) curRoot = getEndPos(i-1, angles); Vector3f axis(1, 0, 0); Vector3f n = endPos - curRoot; float l = n.norm(); if (l) n /= l; n = n.cross(axis); if (l) n *= l*step*pi/180.0f; //std::cout << n << "\n"; for (int j = 0; j < 3; j++) jacobian(j, i) = n[j]; } std::cout << jacobian << std::endl; MatrixXf jjt = jacobian.transpose()*jacobian; //std::cout << jjt << std::endl; float d = jjt.determinant(); MatrixXf invJ; float scale = 0.1f; if (!d /*|| true*/){ invJ = jacobian.transpose(); scale = 5.0f; std::cout << "fallback to jacobian transpose!\n"; } else{ invJ = jjt.inverse()*jacobian.transpose(); std::cout << "jacobian pseudo-inverse!\n"; } //std::cout << invJ << std::endl; VectorXf add = invJ*diff*step*scale; //std::cout << add << std::endl; float maxSpeed = 15.0f; for (int i = 0; i < add.size(); i++){ float& cur = add[i]; cur = std::max(-maxSpeed, std::min(maxSpeed, cur)); } angles += add; for (int i = 0; i < angles.size(); i++){ float& cur = angles[i]; if (i) cur = std::max(-maxAngle, std::min(maxAngle, cur)); } } } void Ik::render(){ glPushMatrix(); glTranslatef(root[0], root[1], root[2]); for (int i = 0; i < angles.size(); i++){ glRotatef(angles[i], -1, 0, 0); drawIkArm(ikLength); glTranslatef(0, 0, ikLength); } glPopMatrix(); drawMarker(target); for (int i = 0; i < angles.size(); i++) drawMarker(getEndPos(i, angles)); } Any help will be appreciated.

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  • Error installing scipy on Mountain Lion with Xcode 4.5.1

    - by Xster
    Environment: Mountain Lion 10.8.2, Xcode 4.5.1 command line tools, Python 2.7.3, virtualenv 1.8.2 and numpy 1.6.2 When installing scipy with pip install -e "git+https://github.com/scipy/scipy#egg=scipy-dev" on a fresh virtualenv. llvm-gcc: scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:51:23: error: immintrin.h: No such file or directory In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vceilf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:53: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vfloorf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:54: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: ‘_MM_FROUND_TRUNC’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: (Each undeclared identifier is reported only once /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: for each function it appears in.) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vnintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: ‘_MM_FROUND_NINT’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: incompatible types in return In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:51:23: error: immintrin.h: No such file or directory In file included from /System/Library/Frameworks/vecLib.framework/Headers/vecLib.h:43, from /System/Library/Frameworks/Accelerate.framework/Headers/Accelerate.h:20, from scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c:2: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vceilf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:53: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vfloorf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:54: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: ‘_MM_FROUND_TRUNC’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: (Each undeclared identifier is reported only once /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: for each function it appears in.) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:55: error: incompatible types in return /System/Library/Frameworks/vecLib.framework/Headers/vfp.h: In function ‘vnintf’: /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: ‘_MM_FROUND_NINT’ undeclared (first use in this function) /System/Library/Frameworks/vecLib.framework/Headers/vfp.h:56: error: incompatible types in return error: Command "/usr/bin/llvm-gcc -fno-strict-aliasing -Os -w -pipe -march=core2 -msse4 -fwrapv -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -Iscipy/sparse/linalg/eigen/arpack/ARPACK/SRC -I/Users/xiao/.virtualenv/lib/python2.7/site-packages/numpy/core/include -c scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.c -o build/temp.macosx-10.4-x86_64-2.7/scipy/sparse/linalg/eigen/arpack/ARPACK/FWRAPPERS/veclib_cabi_c.o" failed with exit status 1 Is it supposed to be looking for headers from my system frameworks? Is the development version of scipy no longer good for the latest version of Mountain Lion/Xcode?

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  • Is EmguCV`s EigenObjectRecognizer uses EigenFace?

    - by Meko
    Hi. I want to learn that is EmguCVs EigenObjectRecognizers has Recognize() method.But I could not found any information that is using which algorithm.I used it in my thesis and I need to know which technique is using that method.I know it uses Eigen Vector and Eigen Values but I am not sure how it uses it. Is any one know could point me ? Thanks.

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  • No proper kmeans clustering of images in matlab

    - by user3237134
    I am having 1200 face images in my training set.There are 2989 test face images. I am using eigen faces (PCA) for feature extraction. I am using kmeans clustering. Source code I tried: IDX = kmeans(z,5); clustercount=accumarray(IDX, ones(size(IDX))); disp(clustercount); Problem: Images are not clustered properly. Same faces should be clustered. But different faces are being clustered. Questions: Should I have to use still more face images for training? How accuracy of clustering can be achieved? What is the solution?

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  • Is NAN suitable for communicating that an invalid parameter was involved in a calculation?

    - by Arman
    I am currently working on a numerical processing system that will be deployed in a performance-critical environment. It takes inputs in the form of numerical arrays (these use the eigen library, but for the purpose of this question that's perhaps immaterial), and performs some range of numerical computations (matrix products, concatenations, etc.) to produce outputs. All arrays are allocated statically and their sizes are known at compile time. However, some of the inputs may be invalid. In these exceptional cases, we still want the code to be computed and we still want outputs not "polluted" by invalid values to be used. To give an example, let's take the following trivial example (this is pseudo-code): Matrix a = {1, 2, NAN, 4}; // this is the "input" matrix Scalar b = 2; Matrix output = b * a; // this results in {2, 4, NAN, 8} The idea here is that 2, 4 and 8 are usable values, but the NAN should signal to the receipient of the data that that entry was involved in an operation that involved an invalid value, and should be discarded (this will be detected via a std::isfinite(value) check before the value is used). Is this a sound way of communicating and propagating unusable values, given that performance is critical and heap allocation is not an option (and neither are other resource-consuming constructs such as boost::optional or pointers)? Are there better ways of doing this? At this point I'm quite happy with the current setup but I was hoping to get some fresh ideas or productive criticism of the current implementation.

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  • What is the reason for section 1 of LGPL and what is the implication for section 9.

    - by Roland Schulz
    Why was section 1 added to LGPLv3? My understanding of section 3&4 is, one can convey the combined work under any license and with no requirements from GPLv3 (besides those explicitly stated as requirements in LGPLv3 3&4). Given that, why is section 1 necessary. Wouldn't that sections 3&4 by themselves already imply anyhow what section 1 explicitly states? I assume that I'm missing something and section 1 isn't redundant. Assuming that, does this have implications for other sections in GPLv3? E.g. does conveying a covered work under sections 3&4 fall under the patent clause of section 10 of GPLv3? Why does section 1 not also state an exception for section 10? Put another way. Is the Eigen FAQ correct by stating: LGPL requires [for header only libraries] pretty much the same as the 2-clause BSD license. It it true that for conveying object files including material from LGPLv3 headers no GPLv3 patent clauses apply?

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  • Finding most Important Node(s) in a Directed Graph

    - by Srikar Appal
    I have a large (˜ 20 million nodes) directed Graph with in-edges & out-edges. I want to figure out which parts of of the graph deserve the most attention. Often most of the graph is boring, or at least it is already well understood. The way I am defining "attention" is by the concept of "connectedness" i.e. How can i find the most connected node(s) in the graph? In what follows, One can assume that nodes by themselves have no score, the edges have no weight & they are either connected or not. This website suggest some pretty complicated procedures like n-dimensional space, Eigen Vectors, graph centrality concepts, pageRank etc. Is this problem that complex? Can I not do a simple Breadth-First Traversal of the entire graph where at each node I figure out a way to find the number of in-edges. The node with most in-edges is the most important node in the graph. Am I missing something here?

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  • Datenbank in a Box

    - by A&C Redaktion
    Die Oracle Database Appliance: ein zuverlässiges, einfach zu bedienendes und erschwingliches Datenbank-System. Endlich kommt ein Datenbanksystem auf den Markt, das auf die Bedürfnisse kleinerer Unternehmen zugeschnitten ist: Oracle Database Appliance (ODA). Nicht jeder, der große Datenmengen zu verwalten hat, kann schließlich gleich zu Exadata und Co. greifen. Die kompakte „Datenbank in a Box“ kombiniert Software, Server und Speicherkapazität und bietet diverse Vernetzungsmöglichkeiten. Sie beinhaltet zwei geclusterte SunFire-Server, die unter Oracle Linux laufen, vorinstalliert ist eine Oracle Database 11g Release 2. Einer der großen ODA-Vorteile: Die Datenbank wächst mit den Bedürfnissen des Unternehmens: Die Leistungsfähigkeit des Clusters lässt sich anpassen, indem per "Pay-as-you-grow" Software-Lizensierung sukzessive zwei bis 24 Cores freigeschaltet werden können. Sie bietet außerdem hohe Verfügbarkeit für Eigen- und Standard-OLTP sowie universelle Datenbanken, auch in großer Anzahl. Für den Schutz vor Server- und Speichersystemausfällen sorgen Oracle Real Application Clusters, beziehungsweise Oracle Automatic Storage Management. Proaktive Systemüberwachung, Software-Bereitstellung auf einen Klick, integrierte Patches über den gesamten Stack und ein automatischer Call-Home bei Hardware-Ausfällen sparen Kosten und Ressourcen bei der Instandhaltung. Über das Oracle PartnerNetzwerk steht Kunden eine große Anzahl an branchenübergreifenden und -spezifischen Anwendungen zur Verfügung, die von der besseren Verfügbarkeit der Oracle Database Appliance profitieren. Auch die Fachpresse setzt sich mit der neuen Oracle Database Appliance auseinander: Ausführlich berichten unter anderem die Computerwoche und heise online. Das Admin-Magazin bietet eine kurze aber treffende Übersicht. Eine ebenfalls anschauliche, etwas ausführlichere Darstellung bietet die Webseite von DOAG e.V. Im Webcast zur Oracle Database Appliance geht Judson Althoff unter anderem auf deren Bedeutung für das Partner-Business ein:

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  • Tool to diagonalize large matrices

    - by Xodarap
    I want to compute a diffusion kernel, which involves taking exp(b*A) where A is a large matrix. In order to play with values of b, I'd like to diagonalize A (so that exp(A) runs quickly). My matrix is about 25k x 25k, but is very sparse - only about 60k values are non-zero. Matlab's "eigs" function runs of out memory, as does octave's "eig" and R's "eigen." Is there a tool to find the decomposition of large, sparse matrices? Dunno if this is relevant, but A is an adjacency matrix, so it's symmetric, and it is full rank.

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  • Where is the bottleneck in this code?

    - by Mikhail
    I have the following tight loop that makes up the serial bottle neck of my code. Ideally I would parallelize the function that calls this but that is not possible. //n is about 60 for (int k = 0;k < n;k++) { double fone = z[k*n+i+1]; double fzer = z[k*n+i]; z[k*n+i+1]= s*fzer+c*fone; z[k*n+i] = c*fzer-s*fone; } Are there any optimizations that can be made such as vectorization or some evil inline that can help this code? I am looking into finding eigen solutions of tridiagonal matrices. http://www.cimat.mx/~posada/OptDoglegGraph/DocLogisticDogleg/projects/adjustedrecipes/tqli.cpp.html

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  • Package system broken - E: Sub-process /usr/bin/dpkg returned an error code (1)

    - by delha
    After installing some packages and libraries I have an error on Package Manager, I can't run any update because it says: "The package system is broken If you are using third party repositories then disable them, since they are a common source of problems. Now run the following command in a terminal: apt-get install -f " I've tried to do what it says and it returns me: jara@jara-Aspire-5738:~$ sudo apt-get install -f Reading package lists... Done Building dependency tree Reading state information... Done Correcting dependencies... Done The following packages were automatically installed and are no longer required: libcaca-dev libopencv2.3-bin nite-dev python-bluez ps-engine libslang2-dev python-sphinx ros-electric-geometry-tutorials ros-electric-geometry-visualization python-matplotlib libzzip-dev ros-electric-orocos-kinematics-dynamics ros-electric-physics-ode libbluetooth-dev libaudiofile-dev libassimp2 libnetpbm10-dev ros-electric-laser-pipeline python-epydoc ros-electric-geometry-experimental libasound2-dev evtest python-matplotlib-data libyaml-dev ros-electric-bullet ros-electric-executive-smach ros-electric-documentation libgl2ps0 libncurses5-dev ros-electric-robot-model texlive-fonts-recommended python-lxml libwxgtk2.8-dev daemontools libxxf86vm-dev libqhull-dev libavahi-client-dev ros-electric-geometry libgl2ps-dev libcurl4-openssl-dev assimp-dev libusb-1.0-0-dev libopencv2.3 ros-electric-diagnostics-monitors libsdl1.2-dev libjs-underscore libsdl-image1.2 tipa libusb-dev libtinfo-dev python-tz python-sip libfltk1.1 libesd0 libfreeimage-dev ros-electric-visualization x11proto-xf86vidmode-dev python-docutils libvtk5.6 ros-electric-assimp x11proto-scrnsaver-dev libnetcdf-dev libidn11-dev libeigen3-dev joystick libhdf5-serial-1.8.4 ros-electric-joystick-drivers texlive-fonts-recommended-doc esound-common libesd0-dev tcl8.5-dev ros-electric-multimaster-experimental ros-electric-rx libaudio-dev ros-electric-ros-tutorials libwxbase2.8-dev ros-electric-visualization-common python-sip-dev ros-electric-visualization-tutorials libfltk1.1-dev libpulse-dev libnetpbm10 python-markupsafe openni-dev tk8.5-dev wx2.8-headers freeglut3-dev libavahi-common-dev python-roman python-jinja2 ros-electric-robot-model-visualization libxss-dev libqhull5 libaa1-dev ros-electric-eigen freeglut3 ros-electric-executive-smach-visualization ros-electric-common-tutorials ros-electric-robot-model-tutorials libnetcdf6 libjs-sphinxdoc python-pyparsing libaudiofile0 Use 'apt-get autoremove' to remove them. The following extra packages will be installed: libcv-dev The following NEW packages will be installed libcv-dev 0 upgraded, 1 newly installed, 0 to remove and 4 not upgraded. 2 not fully installed or removed. Need to get 0 B/3,114 kB of archives. After this operation, 11.1 MB of additional disk space will be used. Do you want to continue [Y/n]? y (Reading database ... 261801 files and directories currently installed.) Unpacking libcv-dev (from .../libcv-dev_2.1.0-7build1_amd64.deb) ... dpkg: error processing /var/cache/apt/archives/libcv-dev_2.1.0-7build1_amd64.deb (-- unpack): trying to overwrite '/usr/bin/opencv_haartraining', which is also in package libopencv2.3-bin 2.3.1+svn6514+branch23-12~oneiric dpkg-deb: error: subprocess paste was killed by signal (Broken pipe) Errors were encountered while processing: /var/cache/apt/archives/libcv-dev_2.1.0-7build1_amd64.deb E: Sub-process /usr/bin/dpkg returned an error code (1) I've tried everything people recommend on internet like: sudo apt-get clean sudo apt-get autoremove sudo apt-get update sudo apt-get upgrade sudo apt-get -f install Also I've tried to install the synaptic manager but it doesn't let me install anything.. As you can see nothing works so I'm desperate! I'm using ubuntu 11.10, 64 bits Thanks!!

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  • Eigenvector computation using OpenCV

    - by Andriyev
    Hi I have this matrix A, representing similarities of pixel intensities of an image. For example: Consider a 10 x 10 image. Matrix A in this case would be of dimension 100 x 100, and element A(i,j) would have a value in the range 0 to 1, representing the similarity of pixel i to j in terms of intensity. I am using OpenCV for image processing and the development environment is C on Linux. Objective is to compute the Eigenvectors of matrix A and I have used the following approach: static CvMat mat, *eigenVec, *eigenVal; static double A[100][100]={}, Ain1D[10000]={}; int cnt=0; //Converting matrix A into a one dimensional array //Reason: That is how cvMat requires it for(i = 0;i < affnDim;i++){ for(j = 0;j < affnDim;j++){ Ain1D[cnt++] = A[i][j]; } } mat = cvMat(100, 100, CV_32FC1, Ain1D); cvEigenVV(&mat, eigenVec, eigenVal, 1e-300); for(i=0;i < 100;i++){ val1 = cvmGet(eigenVal,i,0); //Fetching Eigen Value for(j=0;j < 100;j++){ matX[i][j] = cvmGet(eigenVec,i,j); //Fetching each component of Eigenvector i } } Problem: After execution I get nearly all components of all the Eigenvectors to be zero. I tried different images and also tried populating A with random values between 0 and 1, but the same result. Few of the top eigenvalues returned look like the following: 9805401476911479666115491135488.000000 -9805401476911479666115491135488.000000 -89222871725331592641813413888.000000 89222862280598626902522986496.000000 5255391142666987110400.000000 I am now thinking on the lines of using cvSVD() which performs singular value decomposition of real floating-point matrix and might yield me the eigenvectors. But before that I thought of asking it here. Is there anything absurd in my current approach? Am I using the right API i.e. cvEigenVV() for the right input matrix (my matrix A is a floating point matrix)? cheers

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  • strange redefined symbols

    - by Chris H
    I included this header into one of my own: http://codepad.org/lgJ6KM6b When I compiled I started getting errors like this: CMakeFiles/bin.dir/SoundProjection.cc.o: In function `Gnuplot::reset_plot()': /usr/lib/gcc/x86_64-pc-linux-gnu/4.3.4/include/g++-v4/new:105: multiple definition of `Gnuplot::reset_plot()' CMakeFiles/bin.dir/main.cc.o:project/gnuplot-cpp/gnuplot_i.hpp:962: first defined here CMakeFiles/bin.dir/SoundProjection.cc.o: In function `Gnuplot::set_smooth(std::basic_string, std::allocator const&)': project/gnuplot-cpp/gnuplot_i.hpp:1041: multiple definition of `Gnuplot::set_smooth(std::basic_string, std::allocator const&)' CMakeFiles/bin.dir/main.cc.o:project/gnuplot-cpp/gnuplot_i.hpp:1041: first defined here CMakeFiles/bin.dir/SoundProjection.cc.o:/usr/include/eigen2/Eigen/src/Core/arch/SSE/PacketMath.h:41: multiple definition of `Gnuplot::m_sGNUPlotFileName' I know it's hard to see in this mess, but look at where the redefinitions are taking place. They take place in files like /usr/lib/gcc/x86_64-pc-linux-gnu/4.3.4/include/g++-v4/new:105. How is the new operator getting information about a gnuplot header? I can't even edit that file. How could that ever even be possible? I'm not even sure how to start debugging this. I hope I've provided enough information. I wasn't able to reproduce this in a small project. I mostly just looking for tips on how to find out why this is happening, and how to track it down. Thanks.

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  • how to implement a sparse_vector class

    - by Neil G
    I am implementing a templated sparse_vector class. It's like a vector, but it only stores elements that are different from their default constructed value. So, sparse_vector would store the index-value pairs for all indices whose value is not T(). I am basing my implementation on existing sparse vectors in numeric libraries-- though mine will handle non-numeric types T as well. I looked at boost::numeric::ublas::coordinate_vector and eigen::SparseVector. Both store: size_t* indices_; // a dynamic array T* values_; // a dynamic array int size_; int capacity_; Why don't they simply use vector<pair<size_t, T>> data_; My main question is what are the pros and cons of both systems, and which is ultimately better? The vector of pairs manages size_ and capacity_ for you, and simplifies the accompanying iterator classes; it also has one memory block instead of two, so it incurs half the reallocations, and might have better locality of reference. The other solution might search more quickly since the cache lines fill up with only index data during a search. There might also be some alignment advantages if T is an 8-byte type? It seems to me that vector of pairs is the better solution, yet both containers chose the other solution. Why?

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  • Overlapping template partial specialization when wanting an "override" case: how to avoid the error?

    - by user173342
    I'm dealing with a pretty simple template struct that has an enum value set by whether its 2 template parameters are the same type or not. template<typename T, typename U> struct is_same { enum { value = 0 }; }; template<typename T> struct is_same<T, T> { enum { value = 1 }; }; This is part of a library (Eigen), so I can't alter this design without breaking it. When value == 0, a static assert aborts compilation. So I have a special numerical templated class SpecialCase that can do ops with different specializations of itself. So I set up an override like this: template<typename T> struct SpecialCase { ... }; template<typename LT, typename RT> struct is_same<SpecialCase<LT>, SpecialCase<RT>> { enum { value = 1 }; }; However, this throws the error: more than one partial specialization matches the template argument list Now, I understand why. It's the case where LT == RT, which steps on the toes of is_same<T, T>. What I don't know is how to keep my SpecialCase override and get rid of the error. Is there a trick to get around this? edit: To clarify, I need all cases where LT != RT to also be considered the same (have value 1). Not just LT == RT.

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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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  • CodePlex Daily Summary for Friday, May 30, 2014

    CodePlex Daily Summary for Friday, May 30, 2014Popular ReleasesSEToolbox: 01.032.014 Release 2: Fixed flaw in startup if second Toolbox was started. Added thumbnail zooming in load dialog. Added mirror for new ConveyorTubeCurvedMedium. Added dedicated server support :- Repair will not add missing player to dedicated server. Distances measured to origin (0,0,0) when no player exists. Dedicated Service Server game denied write access unless SEToolbox is run as Admin. Additional information in Load dialog. Installation of this version will replace older version.Vi-AIO SearchBar: Vi – AIO Search Bar: Version 1.0Composite Iconote: Composite Iconote: This is a composite has been made by Microsoft Visual Studio 2013. Requirement: To develop this composite or use this component in your application, your computer must have .NET framework 4.5 or newer.HigLabo: HigLabo_20140529: Fixed HttpClient ContentLength bug.Magick.NET: Magick.NET 6.8.9.101: Magick.NET linked with ImageMagick 6.8.9.1. Breaking changes: - Int/short Set methods of WritablePixelCollection are now unsigned. - The Q16 build no longer uses HDRI, switch to the new Q16-HDRI build if you need HDRI.StudioShell: StudioShell 1.6.6: placeholder release for WIX issue work artifactsMath.NET Numerics: Math.NET Numerics v3.0.0-beta02: Full History Linear Algebra: optimized sparse-sparse and sparse-diagonal matrix products. ~Christian Woltering transpose at storage level, optimized sparse transpose. ~Christian Woltering optimized inplace-map, indexed submatrix-map. optimized clearing a set of rows or columns. matrix FoldRows/FoldColumns. matrix column/row norms, normalization. prefer enums over boolean parameters (e.g. `Zeros.AllowSkip`). IsSymmetric is now a method, add IsConjugateSymmetric. breaking Eigen...QuickMon: Version 3.13: 1. Adding an Audio/sound notifier that can be used to simply draw attention to the application of a warning pr error state is returned by a collector. 2. Adding a property for Notifiers so it can be set to 'Attended', 'Unattended' or 'Both' modes. 3. Adding a WCF method to remote agent host so the version can be checked remotely. 4. Adding some 'Sample' monitor packs to installer. Note: this release and the next release (3.14 aka Pie release) will have some breaking changes and will be incom...fnr.exe - Find And Replace Tool: 1.7: Bug fixes Refactored logic for encoding text values to command line to handle common edge cases where find/replace operation works in GUI but not in command line Fix for bug where selection in Encoding drop down was different when generating command line in some cases. It was reported in: https://findandreplace.codeplex.com/workitem/34 Fix for "Backslash inserted before dot in replacement text" reported here: https://findandreplace.codeplex.com/discussions/541024 Fix for finding replacing...VG-Ripper & PG-Ripper: VG-Ripper 2.9.59: changes NEW: Added Support for 'GokoImage.com' links NEW: Added Support for 'ViperII.com' links NEW: Added Support for 'PixxxView.com' links NEW: Added Support for 'ImgRex.com' links NEW: Added Support for 'PixLiv.com' links NEW: Added Support for 'imgsee.me' links NEW: Added Support for 'ImgS.it' linksXsemmel - XML Editor and Viewer: 29-MAY-2014: WINDOWS XP IS NO LONGER SUPPORTED If you need support for WinXP, download release 15-MAR-2014 instead. FIX: Some minor issues NEW: Better visualisation of validation issues NEW: Printing CHG: Disabled Jumplist CHG: updated to .net 4.5, WinXP NO LONGER SUPPORTEDPerformance Analyzer for Microsoft Dynamics: DynamicsPerf 1.20: Version 1.20 Improved performance in PERFHOURLYROWDATA_VW Fixed error handling encrypted triggers Added logic ACTIVITYMONITORVW to handle Context_Info for Dynamics AX 2012 and above with this flag set on AOS Added logic to optional blocking to handle Context_Info for Dynamics AX 2012 and above with this flag set on AOS Added additional queries for investigating blocking Added logic to collect Baseline capture data (NOTE: QUERY_STATS table has entire procedure cache for that db during...Toolbox for Dynamics CRM 2011/2013: XrmToolBox (v1.2014.5.28): XrmToolbox improvement XrmToolBox updates (v1.2014.5.28)Fix connecting to a connection with custom authentication without saved password Tools improvement New tool!Solution Components Mover (v1.2014.5.22) Transfer solution components from one solution to another one Import/Export NN relationships (v1.2014.3.7) Allows you to import and export many to many relationships Tools updatesAttribute Bulk Updater (v1.2014.5.28) Audit Center (v1.2014.5.28) View Layout Replicator (v1.2014.5.28) Scrip...Microsoft Ajax Minifier: Microsoft Ajax Minifier 5.10: Fix for Issue #20875 - echo switch doesn't work for CSS CSS should honor the SASS source-file comments JS should allow multi-line comment directivesClosedXML - The easy way to OpenXML: ClosedXML 0.71.1: More performance improvements. It's faster and consumes less memory.Kartris E-commerce: Kartris v2.6002: Minor release: Double check that Logins_GetList sproc is present, sometimes seems to get missed earlier if upgrading which can give error when viewing logins page Added CSV and TXT export option; this is not Google Products compatible, but can give a good base for creating a file for some other systems such as Amazon Fixed some minor combination and options issues to improve interface back and front Turn bitcoin and some other gateways off by default Minor CSS changes Fixed currenc...SimCityPak: SimCityPak 0.3.1.0: Main New Features: Fixed Importing of Instance Names (get rid of the Dutch translations) Added advanced editor for Decal Dictionaries Added possibility to import .PNG to generate new decals Added advanced editor for Path display entriesTiny Deduplicator: Tiny Deduplicator 1.0.1.0: Increased version number to 1.0.1.0 Moved all options to a separate 'Options' dialog window. Allows the user to specify a selection strategy which will help when dealing with large numbers of duplicate files. Available options are "None," "Keep First," and "Keep Last"Player Framework by Microsoft: Player Framework for Windows and WP v2.0: Support for new Universal and Windows Phone 8.1 projects for both Xaml and JavaScript projects. See a detailed list of improvements, breaking changes and a general overview of version 2 ADDITIONAL DOWNLOADSSmooth Streaming Client SDK for Windows 8 Applications Smooth Streaming Client SDK for Windows 8.1 Applications Smooth Streaming Client SDK for Windows Phone 8.1 Applications Microsoft PlayReady Client SDK for Windows 8 Applications Microsoft PlayReady Client SDK for Windows 8.1 Applicat...TerraMap (Terraria World Map Viewer): TerraMap 1.0.6: Added support for the new Terraria v1.2.4 update. New items, walls, and tiles Added the ability to select multiple highlighted block types. Added a dynamic, interactive highlight opacity slider, making it easier to find highlighted tiles with dark colors (and fixed blurriness from 1.0.5 alpha). Added ability to find Enchanted Swords (in the stone) and Water Bolt books Fixed Issue 35206: Hightlight/Find doesn't work for Demon Altars Fixed finding Demon Hearts/Shadow Orbs Fixed inst...New ProjectsBooki-Framework: A very super simple framework for develop application on .net (University assignment)C# Datalayer Using Stored Procedures for CRUD Operations: A C# .net data layer that uses stored procedures for crud operations working on any database, while still utilizing object orientated design practices.CoMaSy: Contact Management InfoComposite Iconote: Composite Iconote is a .NET composite. This is a Final Project of Component-Oriented Programming subject in Duta Wacana Christian University YogyakartaCredit Component: CreditComponent give you more attractive view to present who is the developer from any desktop software, many animation can introduce whom the developer isDaQiu: ?????????,??????????????????Database Helper: Rapid Development of CRUD Operationdi_academy_test: Test projectEasy Rent - Car rental software: Easy Rent software is an open source vehicle rental software.Excel Trader: Current project aims to provide an Excel(TM) interface through ExcelDNA for the IBRx, QFIXRx and SusicoTrader API.FXJ Learning Project: This is a learning project with TFS serviceImage View Slider: This is a .NET component. We create this using VB.NET. Here you can use an Image Viewer with several properties to your application form. Try this out!Indonesian Red-Letter Day Calendar: This is an Indonesian version of Red Letter Day Calendar, a final project for Component Oriented Programming course in Duta Wacana Christian University.jquery learning: jquery learningMakePanoForGoogle: Converts Panorama created by Microsoft ICE to format compatible to Google ViewsPWA_AppWeb: This page and all its content were developed by José Brazeta, Luis Carta and João Martins as an assignment for Advanced Web Programing (AEP).SoccerEvaluator: Proyecto para realizar evaluaciones de marcadores de futbolTooltip Web Preview: WebPreview is a component which was made to preview a web page before the link is clicked.Traditional Calendar Component: Hello this is a component which will help you to convert BC calendar to Javanese Calendar and Chinese Calendar. Hope this can help you on developing aps :)Typed YetiBowl The Game: Typescript Version of Yetibowl, intended for comparing Yetibowl in Javascript vs Typescript

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