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  • How to convert closed bezier curves to Bitmaps?

    - by Sorush Rabiee
    I need an algorithm to convert a closed bezier curve (perhaps self-crossing) to a binary bitmap: 0 for inside pixels and 1 for outside. I'm writing a code that needs to implement some operations on bezier curves, could anybody give me some resources or tutorials about beziere? Wikipedia and others didn't say anything about optimization, subtracting, union, knot insertion and deletion and other operations :-)

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  • Training sets for AdaBoost algorithm

    - by palau1
    How do you find the negative and positive training data sets of Haar features for the AdaBoost algorithm? So say you have a certain type of blob that you want to locate in an image and there are several of them in your entire array - how do you go about training it? I'd appreciate a nontechnical explanation as much as possible. I'm new to this. Thanks.

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  • Big O, how do you calculate/approximate it?

    - by Sven
    Most people with a degree in CS will certainly know what Big O stands for. It helps us to measure how (in)efficient an algorithm really is and if you know in what category the problem you are trying to solve lays in you can figure out if it is still possible to squeeze out that little extra performance.* But I'm curious, how do you calculate or approximate the complexity of your algorithms? *: but as they say, don't overdo it, premature optimization is the root of all evil, and optimization without a justified cause should deserve that name as well.

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  • Download acceleration

    - by Nilks
    I have Google'd my butt off, and I can't find anything on this topic. I am trying to create a download client using Java, and I have figured out how to download files with Java, but I want to accelerate the download speed. I know how this works (opening several connections to the download server), but how can I achieve this? I am looking for either some detailed explanation of such an algorithm or some code examples.

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  • Optimizing spacing of mesh containing a given set of points

    - by Feynman
    I tried to summarize the this as best as possible in the title. I am writing an initial value problem solver in the most general way possible. I start with an arbitrary number of initial values at arbitrary locations (inside a boundary.) The first part of my program creates a mesh/grid (I am not sure which is the correct nuance), with N points total, that contains all the initial values. My goal is to optimize the mesh such that the spacing is as uniform as possible. My solver seems to work half decently (it needs some more obscure debugging that is not relevant here.) I am starting with one dimension. I intend to generalize the algorithm to an arbitrary number of dimensions once I get it working consistently. I am writing my code in fortran, but feel free to reply with pseudocode or the language of your choice. Allow me to elaborate with an example: Say I am working on a closed interval [1,10] xmin=1 xmax=10 Say I have 3 initial points: xmin, 5 and xmax num_ivc=3 known(num_ivc)=[xmin,5,xmax] //my arrays start at 1. Assume "known" starts sorted I store my mesh/grid points in an array called coord. Say I want 10 points total in my mesh/grid. N=10 coord(10) Remember, all this is arbitrary--except the variable names of course. The algorithm should set coord to {1,2,3,4,5,6,7,8,9,10} Now for a less trivial example: num_ivc=3 known(num_ivc)=[xmin,5.5,xmax or just num_ivc=1 known(num_ivc)=[5.5] Now, would you have 5 evenly spaced points on the interval [1, 5.5] and 5 evenly spaced points on the interval (5.5, 10]? But there is more space between 1 and 5.5 than between 5.5 and 10. So would you have 6 points on [1, 5.5] followed by 4 on (5.5 to 10]. The key is to minimize the difference in spacing. I have been working on this for 2 days straight and I can assure you it is a lot trickier than it sounds. I have written code that only works if N is large only works if N is small only works if it the known points are close together only works if it the known points are far apart only works if at least one of the known points is near a boundary only works if none of the known points are near a boundary So as you can see, I have coded the gamut of almost-solutions. I cannot figure out a way to get it to perform equally well in all possible scenarios (that is, create the optimum spacing.)

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  • Finding a Minimum Equivalent Graph of a Digraph

    - by kohlerm
    I'm looking for an implementation preferably in Java of an algorithm for finding a Minimum Equivalent Graph of a Digraph (http://portal.acm.org/citation.cfm?id=321526.321534). Even better would be an implementation of "Approximating the minimum equivalent digraph" http://cat.inist.fr/?aModele=afficheN&cpsidt=3634076 (requires ACM membership, sorry) alternative link http://www.cs.umd.edu/~samir/grant/kry94b.ps (postscript)

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  • reflection paths between points in2d

    - by Chris H
    Just wondering if there was a nice (already implemented/documented) algorithm to do the following Given any shape (without crossing edges) and two points inside that shape, compute all the paths between the two points such that all reflections are perfect reflections. The path lengths should be limited to a certain length otherwise there are infinite solutions. I'm not interested in just shooting out rays to try to guess how close I can get, I'm interested in algorithms that can do it perfectly. Search based, not guess/improvement based.

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  • Ten latest files on disk

    - by Artic
    I need effective algorithm to keep only ten latest files on disk in particular folder to support some kind of publishing process. Only 10 files should present in this folder at any point of time. Please, give your advises what should be used here.

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  • 2D Array values frequency

    - by Morano88
    If I have a 2D array that is arranged as follows : String X[][] = new String [][] {{"127.0.0.9", "60", "75000","UDP", "Good"}, {"127.0.0.8", "75", "75000","TCP", "Bad"}, {"127.0.0.9", "75", "70000","UDP", "Good"}, {"127.0.0.1", "", "70000","UDP", "Good"}, {"127.0.0.1", "75", "75000","TCP", "Bad"} }; I want to know the frequency of each value .. so I27.0.0.9 gets 2. How can I do a general solution for this ? In Java or any algorithm for any language ?

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  • Initialization vector - DES/triple-des algorithm

    - by user312373
    Hi, In order to generate the encrypted data we would need to define a Key that should suffice generating the data. But in .net DESCryptoServiceProvider requires Key and Intialisation Vector to generate the encrypted data. In this regard, I would like to know the importance & the benefit gained by defining this initialisation vector field. Is this mandatory while encryption using DES algorithm. Pls share your thoughts on the same. Regards, Balu

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  • Separate groups of people based on members

    - by tevch
    I have groups of people. I need to move groups with at least one same member as far as possible from each other. Example: GroupA - John, Bob, Nick GroupB - Jack, Nick GroupC - Brian, Alex, Steve As you can see GroupA and GroupB overlap(they both contain Nick) I need an algorithm to set groups as GroupA-GroupC-GroupB Thank you

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  • i need your advise please help

    - by davit-datuashvili
    for example we have array of color String s[]=new String[]{"red","black..............}; all color is red or black i need algorithm which partition array such that all red came before to black so how compare it and exchange to accomplish this task ,

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  • How do i pack multiple rectangles in a 2d box tetris style

    - by mglmnc
    I have a number of rectangles of various widths and heights. I have a larger rectangular platform to put them on. I want to pack them on one side of the platform so they spread in the lengthwise (X) dimension but keep the widthwise (Y) dimension to a minimal. That is to place them like a tetris game. There can be no overlaps but there can be gaps. Is there an algorithm out there to do this?

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  • Comparison of algorithmic approaches to the N queens problem

    - by iceman
    I wanted to evaluate performance comparisons for various approaches to solving the N queens problem. Mainly AI metaheuristics based algorithms like simulated annealing, tabu search and genetic algorithm etc compared to exact methods(like backtracking). Is there any code available for study? A lot of real-world optimization problems like it consider cooperative schemes between exact methods and metaheuristics.

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  • Divide and conquer method to compute roots [SOLVED]

    - by hellsoul153
    Hello, Knowing that we can use Divide-and-Conquer algorithm to compute large exponents, for exemple 2 exp 100 = 2 exp(50) * 2 exp(50), which is quite more efficient, is this method efficient using roots ? For exemple 2 exp (1/100) = (2 exp(1/50)) exp(1/50) ? In other words, I'm wondering if (n exp(1/x)) is more efficient to (n exp(1/y)) for x < y and where x and y are integers.

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  • count of paths from A[a,b] to A[c,d] without duplicating?

    - by Sorush Rabiee
    I write a sokoban solver for fun and practice, it uses a simple algorithm (something like BFS). now i want to estimate its running time ( O and omega). but i need to know how to calculate count of paths from a vertex to another in a network. each path from a to b is a sequence of edges with no circuit. for example this is a correct path: http://www.imgplace.com/viewimg143/4789/501k.png but this is not: http://www.imgplace.com/viewimg143/6140/202.png

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  • Dijkstras Algorithm exaplination java

    - by alchemey89
    Hi, I have found an implementation for dijkstras algorithm on the internet and was wondering if someone could help me understand how the code works. Many thanks private int nr_points=0; private int[][]Cost; private int []mask; private void dijkstraTSP() { if(nr_points==0)return; //algorithm=new String("Dijkstra"); nod1=new Vector(); nod2=new Vector(); weight=new Vector(); mask=new int[nr_points]; //initialise mask with zeros (mask[x]=1 means the vertex is marked as used) for(int i=0;i<nr_points;i++)mask[i]=0; //Dijkstra: int []dd=new int[nr_points]; int []pre=new int[nr_points]; int []path=new int[nr_points+1]; int init_vert=0,pos_in_path=0,new_vert=0; //initialise the vectors for(int i=0;i<nr_points;i++) { dd[i]=Cost[init_vert][i]; pre[i]=init_vert; path[i]=-1; } pre[init_vert]=0; path[0]=init_vert; pos_in_path++; mask[init_vert]=1; for(int k=0;k<nr_points-1;k++) { //find min. cost in dd for(int j=0;j<nr_points;j++) if(dd[j]!=0 && mask[j]==0){new_vert=j; break;} for(int j=0;j<nr_points;j++) if(dd[j]<dd[new_vert] && mask[j]==0 && dd[j]!=0)new_vert=j; mask[new_vert]=1; path[pos_in_path]=new_vert; pos_in_path++; for(int j=0;j<nr_points;j++) { if(mask[j]==0) { if(dd[j]>dd[new_vert]+Cost[new_vert][j]) { dd[j]=dd[new_vert]+Cost[new_vert][j]; } } } } //Close the cycle path[nr_points]=init_vert; //Save the solution in 3 vectors (for graphical purposes) for(int i=0;i<nr_points;i++) { nod1.addElement(path[i]); nod2.addElement(path[i+1]); weight.addElement(Cost[path[i]][path[i+1]]); } }

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