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  • Oracle WebCenter: The Best of the Best

    - by kellsey.ruppel(at)oracle.com
    You may remember that the key goals of the new release of WebCenter are providing a Modern User Experience, unparalleled Application Integration, converging all the best of the existing portal platforms into WebCenter and delivering a Common User Experience Architecture.  Last week, we provided an overview of Oracle WebCenter, and this week, we'll focus on Convergence and how the new release of Oracle WebCenter is the Best of the Best..Our development team has been working very hard to bring all the best capabilities from each of the existing portal products into one modern user experience platform that provides a robust foundation for moving customers into the future.  Each of the development teams still maintain their existing products to support the current customers,  but they've been tasked with converging their unique best of breed features into the new WebCenter release so that it will meet the broadest set of use cases possible. For example, we've taken the fastest and most scalable portlet engine in the industry with Oracle WebLogic Portal, integrated it within WebCenter, and improved performance further, to deliver even more performance for our customers.  In addition, we've focused on extending the reach of all the different user experience resources so that customers can deliver robust capabilities into their existing portals, applications, composite applications, dashboards, mobile applications, really any channel that requires information.  And finally, we've combined a whole set of community and multi-site capabilities leveraging the pioneering capabilities of Plumtree portal directly into the new WebCenter release.  While at the same time we've built and delivered the new WebCenter release, we've also provided new feature releases of all the existing products.  In this way, customers can continue to gain value out of their existing investments while at the same time have the smoothest path to upgrading to the new WebCenter release. With the new WebCenter release, we are delivering a converged platform to address all portal requirements that have been delivered by different point products in our portal portfolio in the past. Additionally, this release delivers the most modern user experience that goes well beyond the experience the other portal products provided. This is because the new WebCenter release has been built from the ground up with modern technologies around rich clients, SOA, and customizations compared with other portal products whose architecture has been adapted to add capabilities like AJAX, personalization, and social computing.The new WebCenter release addresses the broadest set of use cases using single product set and single architecture spanning extranet sites to social communities. It helps customers manage, maintain and develop one technology set, but leverage it throughout their organization whether it's embedded in an application or a new destination for improved customer and employee productivity. Additionally, the new release of WebCenter leverages the best and most performant features of all the existing portfolio products to deliver the fastest and most scalable portal platform.  Most importantly, it supports the broadest development models spanning from J2EE/Java to HTML/REST to .NET.Keep checking back this week as we provide additional resources and information on how the new release of Oracle WebCenter is the Best of the Best - converging all the best capabilities from each of the existing portal products into one modern user experience platform.

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  • July 17th Live Webcast with Oracle's Tom Kyte

    - by jgelhaus
    Webcast: Oracle Maximum Availability Architecture Best Practices Date: Tuesday, July 17, 2012 Time: 10 a.m. PT/1 p.m. ET Update Your Knowledge with Oracle Expert Tom Kyte With Oracle’s Maximum Availability Architecture (MAA), organizations can minimize the cost and risk associated with downtime. Oracle’s MAA best practices extend beyond Oracle Database to span a broad range of products, including Oracle Exadata and Oracle Database Appliance. Join Oracle expert Tom Kyte for this interactive Webcast to learn how to: Protect your systems from planned and unplanned downtime Achieve the highest quality of service at the lowest cost Eliminate idle redundancy in the data center Register today and ask Tom your questions around availability best practices.

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  • Neural Networks in C# using NeuronDotNet

    - by kingrichard2005
    Hello, I'm testing the NeuronDotNet library for a class assignment using C#. I have a very simple console application that I'm using to test some of the code snippets provided in the manual fro the library, the goal of the assignment is to teach the program how to distinguish between random points in a square which may or may not be within a circle that is also inside the square. So basically, which points inside the square are also inside the circle. Here is what I have so far: namespace _469_A7 { class Program { static void Main(string[] args) { //Initlaize the backpropogation network LinearLayer inputLayer = new LinearLayer(2); SigmoidLayer hiddenLayer = new SigmoidLayer(8); SigmoidLayer outputLayer = new SigmoidLayer(2); new BackpropagationConnector(inputLayer, hiddenLayer); new BackpropagationConnector(hiddenLayer, outputLayer); BackpropagationNetwork network = new BackpropagationNetwork(inputLayer, outputLayer); //Generate a training set for the ANN TrainingSet trainingSet = new TrainingSet(2, 2); //TEST: Generate random set of points and add to training set, //for testing purposes start with 10 samples; Point p; Program program = new Program(); //Used to access randdouble function Random rand = new Random(); for(int i = 0; i < 10; i++) { //These points will be within the circle radius Type A if(rand.NextDouble() > 0.5) { p = new Point(rand.NextDouble(), rand.NextDouble()); trainingSet.Add(new TrainingSample(new double[2] { p.getX(), p.getY() }, new double[2] { 1, 0 })); continue; } //These points will either be on the border or outside the circle Type B p = new Point(program.randdouble(1.0, 4.0), program.randdouble(1.0, 4.0)); trainingSet.Add(new TrainingSample(new double[2] { p.getX(), p.getY() }, new double[2] { 0, 1 })); } //Start network learning network.Learn(trainingSet, 100); //Stop network learning //network.StopLearning(); } //generates a psuedo-random double between min and max public double randdouble(double min, double max) { Random rand = new Random(); if (min > max) { return rand.NextDouble() * (min - max) + max; } else { return rand.NextDouble() * (max - min) + min; } } } //Class defines a point in X/Y coordinates public class Point { private double X; private double Y; public Point(double xVal, double yVal) { this.X = xVal; this.Y = yVal; } public double getX() { return X; } public double getY() { return Y; } } } This is basically all that I need, the only question I have is how to handle output?? More specifically, I need to output the value of the "step size" and the momentum, although it would be nice to output other information as well. Anyone with experience using NeuronDotNet, your input is appreciated.

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  • Optimizing collision engine bottleneck

    - by Vittorio Romeo
    Foreword: I'm aware that optimizing this bottleneck is not a necessity - the engine is already very fast. I, however, for fun and educational purposes, would love to find a way to make the engine even faster. I'm creating a general-purpose C++ 2D collision detection/response engine, with an emphasis on flexibility and speed. Here's a very basic diagram of its architecture: Basically, the main class is World, which owns (manages memory) of a ResolverBase*, a SpatialBase* and a vector<Body*>. SpatialBase is a pure virtual class which deals with broad-phase collision detection. ResolverBase is a pure virtual class which deals with collision resolution. The bodies communicate to the World::SpatialBase* with SpatialInfo objects, owned by the bodies themselves. There currenly is one spatial class: Grid : SpatialBase, which is a basic fixed 2D grid. It has it's own info class, GridInfo : SpatialInfo. Here's how its architecture looks: The Grid class owns a 2D array of Cell*. The Cell class contains two collection of (not owned) Body*: a vector<Body*> which contains all the bodies that are in the cell, and a map<int, vector<Body*>> which contains all the bodies that are in the cell, divided in groups. Bodies, in fact, have a groupId int that is used for collision groups. GridInfo objects also contain non-owning pointers to the cells the body is in. As I previously said, the engine is based on groups. Body::getGroups() returns a vector<int> of all the groups the body is part of. Body::getGroupsToCheck() returns a vector<int> of all the groups the body has to check collision against. Bodies can occupy more than a single cell. GridInfo always stores non-owning pointers to the occupied cells. After the bodies move, collision detection happens. We assume that all bodies are axis-aligned bounding boxes. How broad-phase collision detection works: Part 1: spatial info update For each Body body: Top-leftmost occupied cell and bottom-rightmost occupied cells are calculated. If they differ from the previous cells, body.gridInfo.cells is cleared, and filled with all the cells the body occupies (2D for loop from the top-leftmost cell to the bottom-rightmost cell). body is now guaranteed to know what cells it occupies. For a performance boost, it stores a pointer to every map<int, vector<Body*>> of every cell it occupies where the int is a group of body->getGroupsToCheck(). These pointers get stored in gridInfo->queries, which is simply a vector<map<int, vector<Body*>>*>. body is now guaranteed to have a pointer to every vector<Body*> of bodies of groups it needs to check collision against. These pointers are stored in gridInfo->queries. Part 2: actual collision checks For each Body body: body clears and fills a vector<Body*> bodiesToCheck, which contains all the bodies it needs to check against. Duplicates are avoided (bodies can belong to more than one group) by checking if bodiesToCheck already contains the body we're trying to add. const vector<Body*>& GridInfo::getBodiesToCheck() { bodiesToCheck.clear(); for(const auto& q : queries) for(const auto& b : *q) if(!contains(bodiesToCheck, b)) bodiesToCheck.push_back(b); return bodiesToCheck; } The GridInfo::getBodiesToCheck() method IS THE BOTTLENECK. The bodiesToCheck vector must be filled for every body update because bodies could have moved meanwhile. It also needs to prevent duplicate collision checks. The contains function simply checks if the vector already contains a body with std::find. Collision is checked and resolved for every body in bodiesToCheck. That's it. So, I've been trying to optimize this broad-phase collision detection for quite a while now. Every time I try something else than the current architecture/setup, something doesn't go as planned or I make assumption about the simulation that later are proven to be false. My question is: how can I optimize the broad-phase of my collision engine maintaining the grouped bodies approach? Is there some kind of magic C++ optimization that can be applied here? Can the architecture be redesigned in order to allow for more performance? Actual implementation: SSVSCollsion Body.h, Body.cpp World.h, World.cpp Grid.h, Grid.cpp Cell.h, Cell.cpp GridInfo.h, GridInfo.cpp

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