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• Algorithm for finding the best routes for food distribution in game

  - by Tautrimas

  Hello, I'm designing a city building game and got into a problem. Imagine Sierra's Caesar III game mechanics: you have many city districts with one market each. There are several granaries over the distance connected with a directed weighted graph. The difference: people (here cars) are units that form traffic jams (here goes the graph weights). Note: in Ceasar game series, people harvested food and stockpiled it in several big granaries, whereas many markets (small shops) took food from the granaries and delivered it to the citizens. The task: tell each district where they should be getting their food from while taking least time and minimizing congestions on the city's roads. Map example Sample diagram Suppose that yellow districts need 7, 7 and 4 apples accordingly. Bluish granaries have 7 and 11 apples accordingly. Suppose edges weights to be proportional to their length. Then, the solution should be something like the gray numbers indicated on the edges. Eg, first district gets 4 apples from the 1st and 3 apples from the 2nd granary, while the last district gets 4 apples from only the 2nd granary. Here, vertical roads are first occupied to the max, and then the remaining workers are sent to the diagonal paths. Question What practical and very fast algorithm should I use? I was looking at some papers (Congestion Games: Optimization in Competition etc.) describing congestion games, but could not get the big picture. Any help is very appreciated! P. S. I can post very little links and no images because of new user restriction.

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• cannot override a concrete member without a third member that's overridden by both

  - by huynhjl

  What does the following error message mean? cannot override a concrete member without a third member that's overridden by both (this rule is designed to prevent ``accidental overrides''); I was trying to do stackable trait modifications. It's a little bit after the fact since I already have a hierarchy in place and I'm trying to modify the behavior without having to rewrite a lot of code. I have a base class called AbstractProcessor that defines an abstract method sort of like this: class AbstractProcessor { def onPush(i:Info): Unit } I have a couple existing traits, to implement different onPush behaviors. trait Pass1 { def onPush(i:Info): Unit = { ... } } trait Pass2 { def onPush(i:Info): Unit = { ... } } So that allows me to use new AbstractProcessor with Pass1 or new AbstractProcessor with Pass2. Now I would like to do some processing before and after the onPush call in Pass1 and Pass2 while minimizing code changes to AbstractProcessor and Pass1 and Pass2. I thought of creating a trait that does something like this: trait Custom extends AbstractProcessor { abstract override def onPush(i:Info): Unit = { // do stuff before super.onPush(i) // do stuff after } And using it with new AbstractProcessor with Pass1 with Custom and I got that error message.

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• What is the best way to iterate over a large result set in JDBC/iBatis 3?

  - by paul_sns

  We're trying to iterate over a large number of rows from the database and convert those into objects. Behavior will be as follows: Result will be sorted by sequence id, a new object will be created when sequence id changes. The object created will be sent to an external service and will sometimes have to wait before sending another one (which means the next set of data will not be immediately used) We already have invested code in iBatis 3 so an iBatis solution will be the best approach for us (we've tried using RowBounds but haven't seen how it does the iteration under the hood). We'd like to balance minimizing memory usage and reducing number of DB trips. We're also open to pure JDBC approach but we'd like the solution to work on different databases. UPDATE: We need to make as few calls to DB as possible (1 call would be the ideal scenario) while also preventing the application to use too much memory. Are there any other solutions out there for this type of problem may it be pure JDBC or any other technology? Thanks and hope to hear your insights on this.

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• Setting minimum size limit for a window in java swing

  - by shadyabhi

  I have a JFrame which has 3 JPanels in GridBagLayout.. Now, when I minimize a windows, after a certain limit, the third JPanel tends to disappear. I tried setting minimizing size of JFrame using setMinimumSize(new Dimension(int,int)) but no success. The windows can still be minimized. So, I actually want to make a threshhold, that my window cannot be minimized after a certain limit. How can I do so? Code:- import java.awt.Dimension; import javax.swing.JFrame; public class JFrameExample { public static void main(String[] args) { JFrame frame = new JFrame("Hello World"); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); frame.setMinimumSize(new Dimension(400, 400)); frame.setVisible(true); } } Also: shadyabhi@shadyabhi-desktop:~/java$ java --showversion java version "1.5.0" gij (GNU libgcj) version 4.4.1 Copyright (C) 2007 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Usage: gij [OPTION] ... CLASS [ARGS] ... to invoke CLASS.main, or gij -jar [OPTION] ... JARFILE [ARGS] ... to execute a jar file Try `gij --help' for more information. shadyabhi@shadyabhi-desktop:~/java$ Gives me output like

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• Javascript library: to obfuscate or not to obfuscate - that is the question

  - by morpheous

  I need to write a GUI related javascript library. It will give my website a bit of an edge (in terms of functionality I can offer) - up until my competitors play with it long enough to figure out how to write it by themselves. I can accept the fact that it will be emulated over time - thats par for the course (its part of business). However, what I cannot bear, is the idea of effectively, simply handing over all the hard work that would have gone into the library to my competitors, by using plain javascript that anyone can download and use. It is an established fact that no none in the industry I am "attacking" has this functionality, so the value of such a library is undeniable and is not up for discussion (i.e. thats not what I'm asking here). What I am seeking to find out are the pros and cons of obfuscating a javascript library, so that I can come to a final decision. Two of my biggest concerns are debugging, and subtle errors that may be introduced by the obfuscator. I would like to know: How can I manage those risks (being able to debug faulty code, ensuring/minimizing against obfuscation errors) Are there any good quality industry standard obfuscators you can recommend (preferably something you use yourself). What are your experiences of using obfuscated code in a production environment?

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• Using ZLib unit to compress files vs using ZipForge

  - by user193655

  There are many questions on zipping in Delphi, anyway this is not a duplicate. I am using ZipForge for zip/unzip capability in my application. Currently I use 2 features of ZipForge: 1) zip and unzip (!) 2) password protect the archives Now I am removing the password from all the archives so I need only to zip and unzip files. I zip them just for minimizing bandwith when uploading/downloading files from the server. So my idea is to process all files once for unzipping them (with password) and rezipping them without password. I have nothing against ZipForge, anyway it is an extra component, every time I upgrade to a newest Delphi version I have to wait for the new IDE support and moreover the more components the more problems during the installation. So since what I do is very simple I'd like to replace ZipForge with 2 simple functinos using the ZLib unit. I found (and tested) the functions here on Torry's. What do you think of using Zlib unit? Do you see any potential problem that I would not have with ZipForge? Can you comment on speed?

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• receiving data from serialport stops when main form is minimized or moved

  - by Rahul

  Sir, I apologize if this is already covered somewhere. I did a search and find something which I have already implemented. I am developing an application which receives data from a device connected via serialport. I am using SerialPort datareceived event to capture data. I am to display data in text boxes of the main form. Data is received frequently. I used Timer to send command to the device, in response device send some data. Timer interval is 100 ms. In every 100 ms interval some command is sent and correspondingly data is received. I used Invoke function to update the GUI elements like TExtbox, labels etc. Everything is fine. All the elements are updating beautifully. But during receiving data if I make any change in main form like moving form, minimizing, maximizing, or clicking somewhere in the form, then data receiving stops. I couldnot find the reason why its happening ? I also changed the timer interval to 200,300,400,500 but same problem is there. Please tell me why its happening? And possible solution... Thanks In advance.... :)

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• Avoid slowdowns while using off-site database

  - by Anders Holmström

  The basic layout of my problem is this: Website (ASP.NET/C#) hosted at a dedicated hosting company (location 1) Company database (SQL Server) with records of relevant data (location 2). Location 1 & 2 connected through VPN. Customer visiting the website and wanting to pull data from the company database. No possibility of changing the server locations or layout (i.e. moving the website to an in-office server isn't possible). What I want to do is figure out the best way to handle the data acces in this case, minimizing the need for time-expensive database calls over the VPN. The first idea I'm getting is this: When a user enters the section of the website needing the DB data, you pull all the needed tables from the database into a in-memory dataset. All subsequent views/updates to the data is done on this dataset. When the user leaves (logout, session timeout, browser closed etc) the dataset gets sent to the SQL server. I'm not sure if this is a realistic solution, and it obviously has some problems. If two web visitors are performing updates on the same data, the one finishing up last will have their changes overwriting the first ones. There's also no way of knowing you have the latest data (i.e. if a customer pulls som info on their projects and we update this info while they are viewing them, they won't see these changes PLUS the above overwriting issue will arise). The other solution would be to somehow aggregate database calls and make sure they only happen when you need them, e.g. during data updates but not during data views. But then again the longer a pause between these refreshing DB calls, the bigger a chance that the data view is out of date as per the problem described above. Any input on the above or some fresh ideas would be most welcome.

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• Designing a different kind of tag cloud.

  - by animuson

  Rather than having a bunch of links that are all different sizes, I want all of my tags to be the same size. However, my goal is to minimize the amount of space required to make the cloud, aka minimizing the number of lines used. Take this example: Looks like any normal tag cloud. However, look at all that extra space around the 'roughdiamond' tag, which could be filled in by other tags like 'stone' down near the bottom, which could effectively eliminate an entire extra line from the cloud. How would I go about getting the words to fill in whatever space possible above them before starting a new line? I'm not talking about reorganizing them to find the absolute minimum number of lines required. If I was going through the list in the image, 'pendant', 'howlite', and 'igrice' would go to line 1 filling it up, 'roughdiamond' would go to line 2 because line 1 is full, 'tourmaline' would go to line 3 because it can't fit on lines 1 or 2, same with 'emberald', but 'pearl' would go to line 2 because it can fit there since there is extra space. I figure there would probably be some way of doing this in CSS that would simply cause the links to collapse into any fillable space it can fit in to.

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• What's the "correct way" to organize this project?

  - by user571747

  I'm working on a project that allows multiple users to submit large data files and perform operations on them. The "backend" which performs these operations is written in Perl while the "frontend" uses PHP to load HTML template files and determines which content to deliver. Data is stored in a database (MySQL, SQLite, Oracle) and while there is data which has not yet been acted upon, Perl adds it to a running queue which delivers data to other threads based on system load. In addition, there may be pre- and post-processing of the data before and after the main Perl script operates (the specifications are unclear) so I may want to allow these processors to be user-selectable plugins. I had been writing this project in a more procedural fashion but I am quickly realizing the benefit of separating concerns as to limit the scope one change has on the rest of the project. I'm quite unexperienced with design patterns and am curious what the best way to proceed is. I've heard MVC thrown around quite a bit but I am unsure of how to apply it. Specifically, what are some good options to structure this code (in terms of design patterns and folder hierarchy)? How can I achieve this with both PHP and Perl while minimizing duplicated code between languages? Should I keep my PHP files in the top level so I don't have ugly paths in the URL? Also, if I want to provide interchangeable databases, does each table need its own DAO implementation?

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• Random begining index iterator for HashSet

  - by funktku

  I use HashSet for add(); remove(); clear(); iterator(); methods. So far everything worked like a charm. However, now I need to fulfill a different requirement. I'd like to be able to start iterating from a certain index. For example, I'd like the following two programs to have same output. Program 1 Iterator it=map.iterator(); for(int i=0;i<100;i++) { it.next(); } while (it.hasNext()) { doSomethingWith(it.next()); } Program 2 Iterator it=map.iterator(100); while (it.hasNext()) { doSomethingWith(it.next()); } The reason I don't want to use the Program 1 is that it creates un-neccesary overhead. From my researchs, I couldn't not find a practical way of creating an iterator with begining index. So, my question is, what would be a good way to achieve my goal while minimizing the overheads? Thank you.

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• Graph search problem with route restrictions

  - by Darcara

  I want to calculate the most profitable route and I think this is a type of traveling salesman problem. I have a set of nodes that I can visit and a function to calculate cost for traveling between nodes and points for reaching the nodes. The goal is to reach a fixed known score while minimizing the cost. This cost and rewards are not fixed and depend on the nodes visited before. The starting node is fixed. There are some restrictions on how nodes can be visited. Some simplified examples include: Node B can only be visited after A After node C has been visited, D or E can be visited. Visiting at least one is required, visiting both is permissible. Z can only be visited after at least 5 other nodes have been visited Once 50 nodes have been visited, the nodes A-M will no longer reward points Certain nodes can (and probably must) be visited multiple times Currently I can think of only two ways to solve this: a) Genetic Algorithms, with the fitness function calculating the cost/benefit of the generated route b) Dijkstra search through the graph, since the starting node is fixed, although the large number of nodes will probably make that not feasible memory wise. Are there any other ways to determine the best route through the graph? It doesn't need to be perfect, an approximated path is perfectly fine, as long as it's error acceptable. Would TSP-solvers be an option here?

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• Revolutionary brand powder packing machine price from affecting marketplace boom and put on uniform in addition to a lengthy service life

  - by user74606

  In mining in stone crushing, our machinery company's encounter becomes much more apparent. As a consequence of production capacity in between 600~800t/h of mining stone crusher, stone is mine Mobile Cone Crushing Plant Price 25~40 times, effectively solved the initially mining stone crusher operation because of low yield prices, no upkeep problems. Full chunk of mining stone crusher. Maximum particle size for crushing 1000x1200mm, an effective answer for the original side is mine stone provide, storing significant chunks of stone can not use complications in mines. Completed goods granularity is modest, only 2~15mm, an effective option for the original mine stone size, generally blocking chute production was an issue even the grinding machine. Two types of material mixed great uniformity, desulfurization of mining stone by adding weight considerably. Present quantity added is often reached 60%, effectively minimizing the cost of raw supplies. Electrical energy consumption has fallen. Dropped 1~2KWh/t tons of mining stone electrical energy consumption, annual electricity savings of one hundred,000 yuan. Efficient labor intensity of workers and also the atmosphere. Due to mine stone powder packing machine price a high degree of automation, with out human make contact with supplies, workers working circumstances enhanced significantly. Positive aspects, and along with mine for stone crushing, CS series cone Crusher has the following efficiency traits. CS series cone Crusher Chamber is divided into 3 unique designs, the user is usually chosen in accordance with the scenario on site crushing efficiency is high, uniform item size, grain shape, rolling mortar wall friction and put on uniform in addition to a extended service life of crushing cavity-. CS series cone Crusher utilizes a one of a kind dust-proof seal, sealing dependable, properly extend the service life of the lubricant replacement cycle and parts. CS series Sprial Sand washer price manufacture of important components to choose unique materials. Each and every stroke left rolling mortar wall of broken cone distances, by permitting a lot more products into the crushing cavity, as well as the formation of big discharge volume, speed of supplies by way of the crushing Chamber. This machine makes use of the principle of crushing cavity, also as unique laminated crushing, particle fragmentation, so that the completed product drastically improved the proportions of a cube, needle-shaped stones to lower particle levels extra evenly.

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• EBS Techstack Sessions at OAUG/Collaborate 2010

  - by Steven Chan

  We have a large contingent of E-Business Suite Applications Technology Group staff rolling out to the OAUG/Collaborate 2010 conference in Las Vegas new week.  Our Applications Technology Group staff will be appearing as guest speakers or full-speakers at the following E-Business Suite technology stack related sessions:Database Special Interest GroupSunday, April 18, 11:00 AM, Breakers FSIG Leaders:  Michael Brown, Colibri; Sandra Vucinic, Vlad GroupGuest Speaker:  Steven ChanCovering database upcoming and past desupport dates, and database support policies as they apply to E-Business Suite environments, general Q&A E-Business Suite Technology Stack Special Interest GroupSunday, April 18, 3:00 PM, Breakers FSIG Leaders:  Elke Phelps, Paul Jackson, HumanaGuest Speaker:  Steven ChanCovering the latest EBS technology stack certifications, roadmap, desupport noticesupgrade options for Discoverer, OID, SSO, Portal, general Q&A E-Business Suite Applications Technology Roadmap & VisionMonday, April 19, 8:00 AM, South Seas GOracle Speaker:  Uma PrabhalaLatest developments for SOA, AOL, OAF, Web ADI, SES, AMP, ACMP, security, and other technologies Oracle E-Business Suite Applications Strategy and General Manager UpdateMonday, April 19, 2:30 PM, Mandalay Bay Ballroom DOracle Speaker:  Cliff GodwinUpdate on the entire Oracle E-Business Suite product line. The session covers the value delivered by the current release of Oracle E-Business Suite applications, the momentum, and how Oracle E-Business Suite applications integrate into Oracle's overall applications strategy 10 Things You Can Do Today to Prepare for the Next Generation ApplicationsTuesday, April 20, 8:00 AM, South Seas FOracle Speaker:  Nadia Bendjedou"Common sense" and "practical" steps that can be taken today to increase the value of your Oracle Applications (E-Business Suite, PeopleSoft, Siebel, and JDE) investments by using the latest Oracle solutions and technologiesReducing TCO using Oracle E-Business Suite Management PacksTuesday, April 20, 10:30 AM, South Seas EOracle Speaker:  Angelo RosadoLearn how you can reduce the Total Cost of Ownership by implementing Application Management Pack (AMP) and Application Change Management Pack (ACP) for E-Business Suite 11i, R12, R12.1. AMP is Oracle's next generation system manageability product offering that provides a centralized platform to manage and maintain EBS. ACP is Oracle's offering to monitor and manage E-Business Suite changes in the areas of E-Business Suite Customizations, Patches and Functional Setups. E-Business Suite Upgrade Special Interest GroupTuesday, April 20, 3:15 PM, South Seas ESIG Leaders:  John Stouffer; Sandra Vucinic, Vlad GroupGuest Speaker:  Steven ChanParticipating in general Q&A E-Business Suite Technology Essentials: Using the Latest Oracle Technologies with E-Business Suite Wednesday, April 21, 8:00 AM, South Seas HOracle Speaker:  Lisa ParekhOracle continues to build new functionality into the Oracle Database, Fusion Middleware, and Enterprise Manager. Come see how you can enhance the value of E-Business Suite for your users and lower your costs of ownership by utilizing the latest features of these Oracle technologies with E-Business Suite. Learn about the latest advanced E-Business Suite topologies and features, including new options for security, performance, third-party integration, SOA, virtualization, clouds, systems management, and much more How to Leverage the New E-Business Suite R12.1 Solutions Without Upgrading your 11.5.10 EnvironmentWednesday, April 21, 10:30 AMOracle Speaker:  Nadia Bendjedou, South Seas ELearn how you can use the latest E-Business Suite 12.1 standalone solutions without upgrading from your E-Business Suite 11.5.10 environment Web 2.0 User Experience and Oracle Fusion Middleware Integration with Oracle E-Business SuiteWednesday, April 21, 4:00 PM, South Seas FOracle Speaker:  Padmaprabodh AmbaleSee the next generation Oracle E-Business Suite OA framework improvements that will provide new rich interactions in components such as LOV, Tables and Attachments.  See  new components like the Rich Container that allows any Web 2.0 content like Flash or OBIEE to be embedded in OA Framework pages. Advanced Technology Deployment Architectures for E-Business Suite Wednesday, April 21, 2:15 PM, South Seas EOracle Speaker:  Steven ChanLearn how to take advantage of the latest version of Oracle Fusion Middleware with Oracle E-Business Suite. Learn how to utilize identity management systems and LDAP directories. In addition, come to this session for answers about advanced network deployments involving reverse proxy servers, load balancers, and DMZ's, and to see how you can take benefit from virtualization and new system management capabilities. Upgrading to Oracle E-Business Suite 12.1 - Best PracticesThursday, April 22, 11:00 AM, South Seas EOracle Speaker:  Lester Gutierrez, Udayan ParvateFundamental of upgrading to Release 12.1, which includes the technology stack components and differences, the upgrade path from various releases of Oracle E-Business Suite, upgrade steps, monitoring the upgrade, hints and tips for minimizing downtime and upgrade best practices for making the upgrade to Release 12.1 a success.  We look forward to seeing you there!

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• Whitepaper list for the application framework

  - by Rick Finley

  We're reposting the list of technical whitepapers for the Oracle ETPM framework (called OUAF, Oracle Utilities Application Framework).  These are are available from My Oracle Support at the Doc Id's mentioned below. Some have been updated in the last few months to reflect new advice and new features.  This is reposted from the OUAF blog:  http://blogs.oracle.com/theshortenspot/entry/whitepaper_list_as_at_november Doc Id Document Title Contents 559880.1 ConfigLab Design Guidelines This whitepaper outlines how to design and implement a data management solution using the ConfigLab facility. This whitepaper currently only applies to the following products: Oracle Utilities Customer Care And Billing Oracle Enterprise Taxation Management Oracle Enterprise Taxation and Policy Management           560367.1 Technical Best Practices for Oracle Utilities Application Framework Based Products Whitepaper summarizing common technical best practices used by partners, implementation teams and customers. 560382.1 Performance Troubleshooting Guideline Series A set of whitepapers on tracking performance at each tier in the framework. The individual whitepapers are as follows: Concepts - General Concepts and Performance Troublehooting processes Client Troubleshooting - General troubleshooting of the browser client with common issues and resolutions. Network Troubleshooting - General troubleshooting of the network with common issues and resolutions. Web Application Server Troubleshooting - General troubleshooting of the Web Application Server with common issues and resolutions. Server Troubleshooting - General troubleshooting of the Operating system with common issues and resolutions. Database Troubleshooting - General troubleshooting of the database with common issues and resolutions. Batch Troubleshooting - General troubleshooting of the background processing component of the product with common issues and resolutions. 560401.1 Software Configuration Management Series  A set of whitepapers on how to manage customization (code and data) using the tools provided with the framework. The individual whitepapers are as follows: Concepts - General concepts and introduction. Environment Management - Principles and techniques for creating and managing environments. Version Management - Integration of Version control and version management of configuration items. Release Management - Packaging configuration items into a release. Distribution - Distribution and installation of releases across environments Change Management - Generic change management processes for product implementations. Status Accounting - Status reporting techniques using product facilities. Defect Management - Generic defect management processes for product implementations. Implementing Single Fixes - Discussion on the single fix architecture and how to use it in an implementation. Implementing Service Packs - Discussion on the service packs and how to use them in an implementation. Implementing Upgrades - Discussion on the the upgrade process and common techniques for minimizing the impact of upgrades. 773473.1 Oracle Utilities Application Framework Security Overview A whitepaper summarizing the security facilities in the framework. Now includes references to other Oracle security products supported. 774783.1 LDAP Integration for Oracle Utilities Application Framework based products Updated! A generic whitepaper summarizing how to integrate an external LDAP based security repository with the framework. 789060.1 Oracle Utilities Application Framework Integration Overview A whitepaper summarizing all the various common integration techniques used with the product (with case studies). 799912.1 Single Sign On Integration for Oracle Utilities Application Framework based products A whitepaper outlining a generic process for integrating an SSO product with the framework. 807068.1 Oracle Utilities Application Framework Architecture Guidelines This whitepaper outlines the different variations of architecture that can be considered. Each variation will include advice on configuration and other considerations. 836362.1 Batch Best Practices for Oracle Utilities Application Framework based products This whitepaper outlines the common and best practices implemented by sites all over the world. 856854.1 Technical Best Practices V1 Addendum Addendum to Technical Best Practices for Oracle Utilities Customer Care And Billing V1.x only. 942074.1 XAI Best Practices This whitepaper outlines the common integration tasks and best practices for the Web Services Integration provided by the Oracle Utilities Application Framework. 970785.1 Oracle Identity Manager Integration Overview This whitepaper outlines the principals of the prebuilt intergration between Oracle Utilities Application Framework Based Products and Oracle Identity Manager used to provision user and user group security information. For Fw4.x customers use whitepaper 1375600.1 instead. 1068958.1 Production Environment Configuration Guidelines A whitepaper outlining common production level settings for the products based upon benchmarks and customer feedback. 1177265.1 What's New In Oracle Utilities Application Framework V4? Whitepaper outlining the major changes to the framework since Oracle Utilities Application Framework V2.2. 1290700.1 Database Vault Integration Whitepaper outlining the Database Vault Integration solution provided with Oracle Utilities Application Framework V4.1.0 and above. 1299732.1 BI Publisher Guidelines for Oracle Utilities Application Framework Whitepaper outlining the interface between BI Publisher and the Oracle Utilities Application Framework 1308161.1 Oracle SOA Suite Integration with Oracle Utilities Application Framework based products This whitepaper outlines common design patterns and guidelines for using Oracle SOA Suite with Oracle Utilities Application Framework based products. 1308165.1 MPL Best Practices Oracle Utilities Application Framework This is a guidelines whitepaper for products shipping with the Multi-Purpose Listener. This whitepaper currently only applies to the following products: Oracle Utilities Customer Care And Billing Oracle Enterprise Taxation Management Oracle Enterprise Taxation and Policy Management 1308181.1 Oracle WebLogic JMS Integration with the Oracle Utilities Application Framework This whitepaper covers the native integration between Oracle WebLogic JMS with Oracle Utilities Application Framework using the new Message Driven Bean functionality and real time JMS adapters. 1334558.1 Oracle WebLogic Clustering for Oracle Utilities Application Framework New! This whitepaper covers process for implementing clustering using Oracle WebLogic for Oracle Utilities Application Framework based products. 1359369.1 IBM WebSphere Clustering for Oracle Utilities Application Framework New! This whitepaper covers process for implementing clustering using IBM WebSphere for Oracle Utilities Application Framework based products 1375600.1 Oracle Identity Management Suite Integration with the Oracle Utilities Application Framework New! This whitepaper covers the integration between Oracle Utilities Application Framework and Oracle Identity Management Suite components such as Oracle Identity Manager, Oracle Access Manager, Oracle Adaptive Access Manager, Oracle Internet Directory and Oracle Virtual Directory. 1375615.1 Advanced Security for the Oracle Utilities Application Framework New! This whitepaper covers common security requirements and how to meet those requirements using Oracle Utilities Application Framework native security facilities, security provided with the J2EE Web Application and/or facilities available in Oracle Identity Management Suite.

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• Run Oracle E-Business Suite Period Close Diagnostic

  - by Get Proactive Customer Adoption Team

  Untitled Document Be Proactive & Save Time—Use the Period Close Diagnostic During the Month Have you ever closed your books at the end of the month and, due to problems with your Oracle E-Business Suite Period Close, you found yourself working all night or all weekend to resolve your issues? You can avoid issues by running the Oracle E-Business Suite Period Close Diagnostics throughout the month, prior to closing Oracle Financial Assets, General Ledger, Payables, and/or Receivables. You can identify issues that will interfere with your period close early, preventing last minute fire drills. Correct your errors or, if you need Oracle Support’s assistance, attach the output to a service request for faster resolution by the support engineer. Oracle E-Business Suite Diagnostics are included in your Oracle Premier Support agreement at no extra charge. They are proactive, easy to use, tools provided by Oracle Support to ease the gathering and analyzing of information from your E-Business Suite, specific to an existing issue or setup. Formatted output displays the information gathered, the findings of the analysis, and the appropriate actions to take if necessary. These tools are designed for both the functional and technical user, providing no EBS administration features, so you can safely assign this responsibility to users who are not administrators. A good place to start with the Support Diagnostics is the install patch Note 167000.1. Everything you need is in this patch and you install it on top of your E-Business Suite. If you are on EBS 12.0.6 or below, Oracle delivers the diagnostic tests in a standard Oracle patch and you apply it using the adpatch utility. If you are on EBS release 12.1.1 or above, your diagnostics are already there. Oracle E-Business Suite Diagnostics: Prevent Issues—resolving configuration and data issues that would cause processes to fail Identify Issues Quickly—resolving problems without the need to contact Oracle Support Reduce Resolution Time—minimizing the time spent to resolve an issue by increasing support engineer efficiency In the example below, you will see how to run the EBS Period Close Diagnostic step-by-step using an SQLGL Period Closing Activity Test. This allows you to check throughout the month to identify and resolve any issue that might prevent closing the period in the General Ledger on schedule.   Click the Select Application button. Select your Application. In this example, we will use the Period Close test. Scroll down to Period Close Place a check mark in the Period Closing box in the Select column. Click the Execute button at the bottom of the page Input the parameters. Click the Submit button Click the Refresh button, until the Status of the test changes from “In Progress” to “Completed” Click the icon under, View Report to view the test results   The report will complete successfully or show completed with errors. The report will show where the error is located, what the error is, and what action(s) to take for resolution. Remember, if you need to work with Oracle Support to resolve your issue, attach the report to your Service Request so the engineer can start working the issue. Completed with errors Completed successfully with no errors If you have questions, please ask in the E-Business Suite Category’s Diagnostic Tools Community. You may find the answer waiting for you in a prior community discussion or in one of the resources posted by an Oracle Support moderator. Oracle’s Period Close Diagnostic, and the other E-Business Suite Diagnostics, save you time and help keep you on schedule. If you run the Period Close Diagnostic throughout the month, you can identify issues to resolve and get help, if needed. When opening a Service Request, attaching the output from the diagnostic report, speeds resolution. With the issues resolved ahead of time, your Period Close should complete without errors. Avoiding the unexpected, helps to close your books on time and without late nights or working through your weekend. Recommended Reads E-Business Suite Diagnostics Period / Year End Close [ID 402237.1] lists all of the Closing Period Diagnostic Tests. I highly recommend that customers execute these tests prior to closing a period. The period closing tests listed in this document help you identify known issues that prevent a successful period close. Use these tests prior to closing a period. To learn about all the available EBS Diagnostics, please review the E-Business Suite Diagnostics Overview [ID 342459.1].

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• Pace Layering Comes Alive

  - by Tanu Sood

  v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Rick Beers is Senior Director of Product Management for Oracle Fusion Middleware. Prior to joining Oracle, Rick held a variety of executive operational positions at Corning, Inc. and Bausch & Lomb. With a professional background that includes senior management positions in manufacturing, supply chain and information technology, Rick brings a unique set of experiences to cover the impact that technology can have on business models, processes and organizations. Rick hosts the IT Leaders Editorial on a monthly basis. By now, readers of this column are quite familiar with Oracle AppAdvantage, a unified framework of middleware technologies, infrastructure and applications utilizing a pace layered approach to enterprise systems platforms. 1. Standardize and Consolidate core Enterprise Applications by removing invasive customizations, costly workarounds and the complexity that multiple instances creates. 2. Move business specific processes and applications to the Differentiate Layer, thus creating greater business agility with process extensions and best of breed applications managed by cross- application process orchestration. 3. The Innovate Layer contains all the business capabilities required for engagement, collaboration and intuitive decision making. This is the layer where innovation will occur, as people engage one another in a secure yet open and informed way. 4. Simplify IT by minimizing complexity, improving performance and lowering cost with secure, reliable and managed systems across the entire Enterprise. But what hasn’t been discussed is the pace layered architecture that Oracle AppAdvantage adopts. What is it, what are its origins and why is it relevant to enterprise scale applications and technologies? It’s actually a fascinating tale that spans the past 20 years and a basic understanding of it provides a wonderful context to what is evolving as the future of enterprise systems platforms. It all begins in 1994 with a book by noted architect Stewart Brand, of ’Whole Earth Catalog’ fame. In his 1994 book How Buildings Learn, Brand popularized the term ‘Shearing Layers’, arguing that any building is actually a hierarchy of pieces, each of which inherently changes at different rates. In 1997 he produced a 6 part BBC Series adapted from the book, in which Part 6 focuses on Shearing Layers. In this segment Brand begins to introduce the concept of ‘pace’. Brand further refined this idea in his subsequent book, The Clock of the Long Now, which began to link the concept of Shearing Layers to computing and introduced the term ‘pace layering’, where he proposes that: “An imperative emerges: an adaptive [system] has to allow slippage between the differently-paced systems … otherwise the slow systems block the flow of the quick ones and the quick ones tear up the slow ones with their constant change. Embedding the systems together may look efficient at first but over time it is the opposite and destructive as well.” In 2000, IBM architects Ian Simmonds and David Ing published a paper entitled A Shearing Layers Approach to Information Systems Development, which applied the concept of Shearing Layers to systems design and development. It argued that at the time systems were still too rigid; that they constrained organizations by their inability to adapt to changes. The findings in the Conclusions section are particularly striking: “Our starting motivation was that enterprises need to become more adaptive, and that an aspect of doing that is having adaptable computer systems. The challenge is then to optimize information systems development for change (high maintenance) rather than stability (low maintenance). Our response is to make it explicit within software engineering the notion of shearing layers, and explore it as the principle that systems should be built to be adaptable in response to the qualitatively different rates of change to which they will be subjected. This allows us to separate functions that should legitimately change relatively slowly and at significant cost from that which should be changeable often, quickly and cheaply.” The problem at the time of course was that this vision of adaptable systems was simply not possible within the confines of 1st generation ERP, which were conceived, designed and developed for standardization and compliance. It wasn’t until the maturity of open, standards based integration, and the middleware innovation that followed, that pace layering became an achievable goal. And Oracle is leading the way. Oracle’s AppAdvantage framework makes pace layering come alive by taking a strategic vision 20 years in the making and transforming it to a reality. It allows enterprises to retain and even optimize their existing ERP systems, while wrapping around those ERP systems three layers of capabilities that inherently adapt as needed, at a pace that’s optimal for the enterprise.

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• Cloud to On-Premise Connectivity Patterns

  - by Rajesh Raheja

  Do you have a requirement to convert an Opportunity in Salesforce.com to an Order/Quote in Oracle E-Business Suite? Or maybe you want the creation of an Oracle RightNow Incident to trigger an on-premise Oracle E-Business Suite Service Request creation for RMA and Field Scheduling? If so, read on. In a previous blog post, I discussed integrating TO cloud applications, however the use cases above are the reverse i.e. receiving data FROM cloud applications (SaaS) TO on-premise applications/databases that sit behind a firewall. Oracle SOA Suite is assumed to be on-premise with with Oracle Service Bus as the mediation and virtualization layer. The main considerations for the patterns are are security i.e. shielding enterprise resources; and scalability i.e. minimizing firewall latency. Let me use an analogy to help visualize the patterns: the on-premise system is your home - with your most valuable possessions - and the SaaS app is your favorite on-line store which regularly ships (inbound calls) various types of parcels/items (message types/service operations). You need the items at home (on-premise) but want to safe guard against misguided elements of society (internet threats) who may masquerade as postal workers and vandalize property (denial of service?). Let's look at the patterns. Pattern: Pull from Cloud The on-premise system polls from the SaaS apps and picks up the message instead of having it delivered. This may be done using Oracle RightNow Object Query Language or SOAP APIs. This is particularly suited for certain integration approaches wherein messages are trickling in, can be centralized and batched e.g. retrieving event notifications on an hourly schedule from the Oracle Messaging Service. To compare this pattern with the home analogy, you are avoiding any deliveries to your home and instead go to the post office/UPS/Fedex store to pick up your parcel. Every time. Pros: On-premise assets not exposed to the Internet, firewall issues avoided by only initiating outbound connections Cons: Polling mechanisms may affect performance, may not satisfy near real-time requirements Pattern: Open Firewall Ports The on-premise system exposes the web services that needs to be invoked by the cloud application. This requires opening up firewall ports, routing calls to the appropriate internal services behind the firewall. Fusion Applications uses this pattern, and auto-provisions the services on the various virtual hosts to secure the topology. This works well for service integration, but may not suffice for large volume data integration. Using the home analogy, you have now decided to receive parcels instead of going to the post office every time. A door mail slot cut out allows the postman can drop small parcels, but there is still concern about cutting new holes for larger packages. Pros: optimal pattern for near real-time needs, simpler administration once the service is provisioned Cons: Needs firewall ports to be opened up for new services, may not suffice for batch integration requiring direct database access Pattern: Virtual Private Networking The on-premise network is "extended" to the cloud (or an intermediary on-demand / managed service offering) using Virtual Private Networking (VPN) so that messages are delivered to the on-premise system in a trusted channel. Using the home analogy, you entrust a set of keys with a neighbor or property manager who receives the packages, and then drops it inside your home. Pros: Individual firewall ports don't need to be opened, more suited for high scalability needs, can support large volume data integration, easier management of one connection vs a multitude of open ports Cons: VPN setup, specific hardware support, requires cloud provider to support virtual private computing Pattern: Reverse Proxy / API Gateway The on-premise system uses a reverse proxy "API gateway" software on the DMZ to receive messages. The reverse proxy can be implemented using various mechanisms e.g. Oracle API Gateway provides firewall and proxy services along with comprehensive security, auditing, throttling benefits. If a firewall already exists, then Oracle Service Bus or Oracle HTTP Server virtual hosts can provide reverse proxy implementations on the DMZ. Custom built implementations are also possible if specific functionality (such as message store-n-forward) is needed. In the home analogy, this pattern sits in between cutting mail slots and handing over keys. Instead, you install (and maintain) a mailbox in your home premises outside your door. The post office delivers the parcels in your mailbox, from where you can securely retrieve it. Pros: Very secure, very flexible Cons: Introduces a new software component, needs DMZ deployment and management Pattern: On-Premise Agent (Tunneling) A light weight "agent" software sits behind the firewall and initiates the communication with the cloud, thereby avoiding firewall issues. It then maintains a bi-directional connection either with pull or push based approaches using (or abusing, depending on your viewpoint) the HTTP protocol. Programming protocols such as Comet, WebSockets, HTTP CONNECT, HTTP SSH Tunneling etc. are possible implementation options. In the home analogy, a resident receives the parcel from the postal worker by opening the door, however you still take precautions with chain locks and package inspections. Pros: Light weight software, IT doesn't need to setup anything Cons: May bypass critical firewall checks e.g. virus scans, separate software download, proliferation of non-IT managed software Conclusion The patterns above are some of the most commonly encountered ones for cloud to on-premise integration. Selecting the right pattern for your project involves looking at your scalability needs, security restrictions, sync vs asynchronous implementation, near real-time vs batch expectations, cloud provider capabilities, budget, and more. In some cases, the basic "Pull from Cloud" may be acceptable, whereas in others, an extensive VPN topology may be well justified. For more details on the Oracle cloud integration strategy, download this white paper.

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• Cloud to On-Premise Connectivity Patterns

  - by Rajesh Raheja

  Do you have a requirement to convert an Opportunity in Salesforce.com to an Order/Quote in Oracle E-Business Suite? Or maybe you want the creation of an Oracle RightNow Incident to trigger an on-premise Oracle E-Business Suite Service Request creation for RMA and Field Scheduling? If so, read on. In a previous blog post, I discussed integrating TO cloud applications, however the use cases above are the reverse i.e. receiving data FROM cloud applications (SaaS) TO on-premise applications/databases that sit behind a firewall. Oracle SOA Suite is assumed to be on-premise with with Oracle Service Bus as the mediation and virtualization layer. The main considerations for the patterns are are security i.e. shielding enterprise resources; and scalability i.e. minimizing firewall latency. Let me use an analogy to help visualize the patterns: the on-premise system is your home - with your most valuable possessions - and the SaaS app is your favorite on-line store which regularly ships (inbound calls) various types of parcels/items (message types/service operations). You need the items at home (on-premise) but want to safe guard against misguided elements of society (internet threats) who may masquerade as postal workers and vandalize property (denial of service?). Let's look at the patterns. Pattern: Pull from Cloud The on-premise system polls from the SaaS apps and picks up the message instead of having it delivered. This may be done using Oracle RightNow Object Query Language or SOAP APIs. This is particularly suited for certain integration approaches wherein messages are trickling in, can be centralized and batched e.g. retrieving event notifications on an hourly schedule from the Oracle Messaging Service. To compare this pattern with the home analogy, you are avoiding any deliveries to your home and instead go to the post office/UPS/Fedex store to pick up your parcel. Every time. Pros: On-premise assets not exposed to the Internet, firewall issues avoided by only initiating outbound connections Cons: Polling mechanisms may affect performance, may not satisfy near real-time requirements Pattern: Open Firewall Ports The on-premise system exposes the web services that needs to be invoked by the cloud application. This requires opening up firewall ports, routing calls to the appropriate internal services behind the firewall. Fusion Applications uses this pattern, and auto-provisions the services on the various virtual hosts to secure the topology. This works well for service integration, but may not suffice for large volume data integration. Using the home analogy, you have now decided to receive parcels instead of going to the post office every time. A door mail slot cut out allows the postman can drop small parcels, but there is still concern about cutting new holes for larger packages. Pros: optimal pattern for near real-time needs, simpler administration once the service is provisioned Cons: Needs firewall ports to be opened up for new services, may not suffice for batch integration requiring direct database access Pattern: Virtual Private Networking The on-premise network is "extended" to the cloud (or an intermediary on-demand / managed service offering) using Virtual Private Networking (VPN) so that messages are delivered to the on-premise system in a trusted channel. Using the home analogy, you entrust a set of keys with a neighbor or property manager who receives the packages, and then drops it inside your home. Pros: Individual firewall ports don't need to be opened, more suited for high scalability needs, can support large volume data integration, easier management of one connection vs a multitude of open ports Cons: VPN setup, specific hardware support, requires cloud provider to support virtual private computing Pattern: Reverse Proxy / API Gateway The on-premise system uses a reverse proxy "API gateway" software on the DMZ to receive messages. The reverse proxy can be implemented using various mechanisms e.g. Oracle API Gateway provides firewall and proxy services along with comprehensive security, auditing, throttling benefits. If a firewall already exists, then Oracle Service Bus or Oracle HTTP Server virtual hosts can provide reverse proxy implementations on the DMZ. Custom built implementations are also possible if specific functionality (such as message store-n-forward) is needed. In the home analogy, this pattern sits in between cutting mail slots and handing over keys. Instead, you install (and maintain) a mailbox in your home premises outside your door. The post office delivers the parcels in your mailbox, from where you can securely retrieve it. Pros: Very secure, very flexible Cons: Introduces a new software component, needs DMZ deployment and management Pattern: On-Premise Agent (Tunneling) A light weight "agent" software sits behind the firewall and initiates the communication with the cloud, thereby avoiding firewall issues. It then maintains a bi-directional connection either with pull or push based approaches using (or abusing, depending on your viewpoint) the HTTP protocol. Programming protocols such as Comet, WebSockets, HTTP CONNECT, HTTP SSH Tunneling etc. are possible implementation options. In the home analogy, a resident receives the parcel from the postal worker by opening the door, however you still take precautions with chain locks and package inspections. Pros: Light weight software, IT doesn't need to setup anything Cons: May bypass critical firewall checks e.g. virus scans, separate software download, proliferation of non-IT managed software Conclusion The patterns above are some of the most commonly encountered ones for cloud to on-premise integration. Selecting the right pattern for your project involves looking at your scalability needs, security restrictions, sync vs asynchronous implementation, near real-time vs batch expectations, cloud provider capabilities, budget, and more. In some cases, the basic "Pull from Cloud" may be acceptable, whereas in others, an extensive VPN topology may be well justified. For more details on the Oracle cloud integration strategy, download this white paper.

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• CPU Usage in Very Large Coherence Clusters

  - by jpurdy

  When sizing Coherence installations, one of the complicating factors is that these installations (by their very nature) tend to be application-specific, with some being large, memory-intensive caches, with others acting as I/O-intensive transaction-processing platforms, and still others performing CPU-intensive calculations across the data grid. Regardless of the primary resource requirements, Coherence sizing calculations are inherently empirical, in that there are so many permutations that a simple spreadsheet approach to sizing is rarely optimal (though it can provide a good starting estimate). So we typically recommend measuring actual resource usage (primarily CPU cycles, network bandwidth and memory) at a given load, and then extrapolating from those measurements. Of course there may be multiple types of load, and these may have varying degrees of correlation -- for example, an increased request rate may drive up the number of objects "pinned" in memory at any point, but the increase may be less than linear if those objects are naturally shared by concurrent requests. But for most reasonably-designed applications, a linear resource model will be reasonably accurate for most levels of scale. However, at extreme scale, sizing becomes a bit more complicated as certain cluster management operations -- while very infrequent -- become increasingly critical. This is because certain operations do not naturally tend to scale out. In a small cluster, sizing is primarily driven by the request rate, required cache size, or other application-driven metrics. In larger clusters (e.g. those with hundreds of cluster members), certain infrastructure tasks become intensive, in particular those related to members joining and leaving the cluster, such as introducing new cluster members to the rest of the cluster, or publishing the location of partitions during rebalancing. These tasks have a strong tendency to require all updates to be routed via a single member for the sake of cluster stability and data integrity. Fortunately that member is dynamically assigned in Coherence, so it is not a single point of failure, but it may still become a single point of bottleneck (until the cluster finishes its reconfiguration, at which point this member will have a similar load to the rest of the members). The most common cause of scaling issues in large clusters is disabling multicast (by configuring well-known addresses, aka WKA). This obviously impacts network usage, but it also has a large impact on CPU usage, primarily since the senior member must directly communicate certain messages with every other cluster member, and this communication requires significant CPU time. In particular, the need to notify the rest of the cluster about membership changes and corresponding partition reassignments adds stress to the senior member. Given that portions of the network stack may tend to be single-threaded (both in Coherence and the underlying OS), this may be even more problematic on servers with poor single-threaded performance. As a result of this, some extremely large clusters may be configured with a smaller number of partitions than ideal. This results in the size of each partition being increased. When a cache server fails, the other servers will use their fractional backups to recover the state of that server (and take over responsibility for their backed-up portion of that state). The finest granularity of this recovery is a single partition, and the single service thread can not accept new requests during this recovery. Ordinarily, recovery is practically instantaneous (it is roughly equivalent to the time required to iterate over a set of backup backing map entries and move them to the primary backing map in the same JVM). But certain factors can increase this duration drastically (to several seconds): large partitions, sufficiently slow single-threaded CPU performance, many or expensive indexes to rebuild, etc. The solution of course is to mitigate each of those factors but in many cases this may be challenging. Larger clusters also lead to the temptation to place more load on the available hardware resources, spreading CPU resources thin. As an example, while we've long been aware of how garbage collection can cause significant pauses, it usually isn't viewed as a major consumer of CPU (in terms of overall system throughput). Typically, the use of a concurrent collector allows greater responsiveness by minimizing pause times, at the cost of reducing system throughput. However, at a recent engagement, we were forced to turn off the concurrent collector and use a traditional parallel "stop the world" collector to reduce CPU usage to an acceptable level. In summary, there are some less obvious factors that may result in excessive CPU consumption in a larger cluster, so it is even more critical to test at full scale, even though allocating sufficient hardware may often be much more difficult for these large clusters.

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• SetWindowLong in CustomDraw causes unhandled exception

  - by neeul

  Hello, I am making some changes to a CSliderCtrl using the Custom Draw, the control is to be used in a dialog. Here is the structure: In my MessageMap I have : ON_NOTIFY_REFLECT_EX(NM_CUSTOMDRAW, OnNMCustomdraw) The OnNMCustomdraw method looks like the following: BOOL CCustomSliderCtrl::OnNMCustomdraw(NMHDR *pNMHDR, LRESULT *pResult) { *pResult = CDRF_DODEFAULT; LPNMCUSTOMDRAW pNMCD = reinterpret_cast<LPNMCUSTOMDRAW>(pNMHDR); switch(pNMCD->dwDrawStage) { case CDDS_PREPAINT: { //Dialogs don't receive CDRF_NOTIFYITEMDRAW notifcations by returning it as part of pResult, we must //use the following so we ensure we receive the msg SetWindowLong(pNMHDR->hwndFrom, DWL_MSGRESULT, CDRF_NOTIFYITEMDRAW); return TRUE; } case CDDS_ITEMPREPAINT: if(pNMCD->dwItemSpec == TBCD_CHANNEL) { ...SNIP... SetWindowLong(pNMHDR->hwndFrom, DWL_MSGRESULT, CDRF_SKIPDEFAULT); return TRUE; } } return FALSE; } Reading around I learnt that you had to use SetWindowLong to set the return value for the custom draw, otherwise your method will not always receive the CDDS_ITEMPREPAINT message. However, when using SetWindowLong my application will never receive the CDDS_ITEMPREPAINT and so my slider just looks like a standard slider. The application crashes when any sort of interaction takes place upon the slider, such as hovering over it or minimizing and maximizing the dialog. I snipped the TBCD_CHANNEL code as it is never reached. When running in debug mode, it crashes at the end of the AfxUnlockGlobals method, in afxcrit.cpp. Here is a stack trace: Update: Since adding debug symbols, the crash seems to be picked up at CWnd::DefWindowProc mwthod. comctl32.dll!_TrackBarWndProc@16() + 0x551 bytes user32.dll!_InternalCallWinProc@20() + 0x28 bytes user32.dll!_UserCallWinProcCheckWow@32() + 0xb7 bytes user32.dll!_CallWindowProcAorW@24() + 0x51 bytes user32.dll!_CallWindowProcW@20() + 0x1b bytes mfc90ud.dll!CWnd::DefWindowProcW(unsigned int nMsg=15, unsigned int wParam=0, long lParam=0) Line 1043 + 0x20 bytes C++ mfc90ud.dll!CWnd::WindowProc(unsigned int message=15, unsigned int wParam=0, long lParam=0) Line 1756 + 0x1c bytes C++ mfc90ud.dll!AfxCallWndProc(CWnd * pWnd=0x0012fdbc, HWND__ * hWnd=0x000308fe, unsigned int nMsg=15, unsigned int wParam=0, long lParam=0) Line 240 + 0x1c bytes C++ mfc90ud.dll!AfxWndProc(HWND__ * hWnd=0x000308fe, unsigned int nMsg=15, unsigned int wParam=0, long lParam=0) Line 403 C++ mfc90ud.dll!AfxWndProcBase(HWND__ * hWnd=0x000308fe, unsigned int nMsg=15, unsigned int wParam=0, long lParam=0) Line 441 + 0x15 bytes C++ user32.dll!_InternalCallWinProc@20() + 0x28 bytes user32.dll!_UserCallWinProcCheckWow@32() + 0xb7 bytes user32.dll!_DispatchClientMessage@20() + 0x4d bytes user32.dll!___fnDWORD@4() + 0x24 bytes ntdll.dll!_KiUserCallbackDispatcher@12() + 0x13 bytes user32.dll!_NtUserDispatchMessage@4() + 0xc bytes user32.dll!_DispatchMessageW@4() + 0xf bytes mfc90ud.dll!AfxInternalPumpMessage() Line 183 C++ mfc90ud.dll!CWinThread::PumpMessage() Line 900 C++ mfc90ud.dll!AfxPumpMessage() Line 190 + 0xd bytes C++ mfc90ud.dll!CWnd::RunModalLoop(unsigned long dwFlags=4) Line 4386 + 0x5 bytes C++ mfc90ud.dll!CDialog::DoModal() Line 584 + 0xc bytes C++ SetSelection.exe!CSetSelectionApp::InitInstance() Line 64 + 0xb bytes C++ mfc90ud.dll!AfxWinMain(HINSTANCE__ * hInstance=0x00400000, HINSTANCE__ * hPrevInstance=0x00000000, wchar_t * lpCmdLine=0x00020a84, int nCmdShow=1) Line 37 + 0xd bytes C++ SetSelection.exe!wWinMain(HINSTANCE__ * hInstance=0x00400000, HINSTANCE__ * hPrevInstance=0x00000000, wchar_t * lpCmdLine=0x00020a84, int nCmdShow=1) Line 34 C++ SetSelection.exe!__tmainCRTStartup() Line 578 + 0x35 bytes C SetSelection.exe!wWinMainCRTStartup() Line 403 C kernel32.dll!_BaseProcessStart@4() + 0x23 bytes So, does anyone have any insight into this matter? If you need more info just let me know.

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• Is there a scheduling algorithm that optimizes for "maker's schedules"?

  - by John Feminella

  You may be familiar with Paul Graham's essay, "Maker's Schedule, Manager's Schedule". The crux of the essay is that for creative and technical professionals, meetings are anathema to productivity, because they tend to lead to "schedule fragmentation", breaking up free time into chunks that are too small to acquire the focus needed to solve difficult problems. In my firm we've seen significant benefits by minimizing the amount of disruption caused, but the brute-force algorithm we use to decide schedules is not sophisticated enough to handle scheduling large groups of people well. (*) What I'm looking for is if there's are any well-known algorithms which minimize this productivity disruption, among a group of N makers and managers. In our model, There are N people. Each person pi is either a maker (Mk) or a manager (Mg). Each person has a schedule si. Everyone's schedule is H hours long. A schedule consists of a series of non-overlapping intervals si = [h1, ..., hj]. An interval is either free or busy. Two adjacent free intervals are equivalent to a single free interval that spans both. A maker's productivity is maximized when the number of free intervals is minimized. A manager's productivity is maximized when the total length of free intervals is maximized. Notice that if there are no meetings, both the makers and the managers experience optimum productivity. If meetings must be scheduled, then makers prefer that meetings happen back-to-back, while managers don't care where the meeting goes. Note that because all disruptions are treated as equally harmful to makers, there's no difference between a meeting that lasts 1 second and a meeting that lasts 3 hours if it segments the available free time. The problem is to decide how to schedule M different meetings involving arbitrary numbers of the N people, where each person in a given meeting must place a busy interval into their schedule such that it doesn't overlap with any other busy interval. For each meeting Mt the start time for the busy interval must be the same for all parties. Does an algorithm exist to solve this problem or one similar to it? My first thought was that this looks really similar to defragmentation (minimize number of distinct chunks), and there are a lot of algorithms about that. But defragmentation doesn't have much to do with scheduling. Thoughts? (*) Practically speaking this is not really a problem, because it's rare that we have meetings with more than ~5 people at once, so the space of possibilities is small.

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• DCVS + hosting for a startup commercial multiplatform phone app

  - by AG

  I'm in lean startup mode, working on a simple phone app that will be published initially as a iThingy app and an Android app with, possibly, Blackberry and Symbian versions to follow. I'm about to go from no repository to needing a central repository that up to 4 very part-time resources will be sharing. Two of us have no version control background, one has used Subversion, and I've used most of the major centralized VCS systems. I'm not going to be pushing the technical limitations of any VCS for a long time; I'm sure that any of the major systems would work fine. And the hosting accounts I've looked at seem reasonable. So I'm really focussed on minimizing the downside risks. That is, I'd like to find a stable setup that is easy to learn in general, easy to use from Windows/Eclipse, and won't paint me into any obvious corners for the next 12 months or so. A quick search of the web had led me to consider the following pairs of DVCS and hosting service, with what I think I'm hearing as their strengths and weaknesses (for my purposes): Bazaar/Launchpad -- My initial choice since I need to get more familiar with this pair for the Google Summer of Code mentoring I'm doing. But, whatever the technical merits, a non-starter for me because they are purely open source, no private repositories plans to purchase that I can see. Git/GitHub -- Git: Fast, light, ultimately flexible, but relatively less Windows friendly, Eclipse plugin (eGit) available but relatively young, GitHub: widely used, pricing is fine Mercurial/BitBucket -- Mercurial: a little less flexible, a little more Windows friendly, Eclipse plugin seems a bit more mature, BitBucket: widely used, pricing is fine, includes a wiki and an issue tracker that we might be able to use instead of something like BaseCamp, at least for a while. Mercurial/BitBucket seem like the winning pair so far for my particular situation; at least two of us are definitely going to be working mostly from Eclipse on Windows and reducing my own learning curve is a priority. ;-) But I have two specific questions: 1) Am I wrong about Bazaar/Launchpad and is there a viable, secure way to use them for proprietary code? 2) Any reason to think that the Mecurial/Bitbucket pair will end up being a headache for my Mac developer, soon, or for Blackberry or Symbian developers a little later? ag

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• segmented reduction with scattered segments

  - by Christian Rau

  I got to solve a pretty standard problem on the GPU, but I'm quite new to practical GPGPU, so I'm looking for ideas to approach this problem. I have many points in 3-space which are assigned to a very small number of groups (each point belongs to one group), specifically 15 in this case (doesn't ever change). Now I want to compute the mean and covariance matrix of all the groups. So on the CPU it's roughly the same as: for each point p { mean[p.group] += p.pos; covariance[p.group] += p.pos * p.pos; ++count[p.group]; } for each group g { mean[g] /= count[g]; covariance[g] = covariance[g]/count[g] - mean[g]*mean[g]; } Since the number of groups is extremely small, the last step can be done on the CPU (I need those values on the CPU, anyway). The first step is actually just a segmented reduction, but with the segments scattered around. So the first idea I came up with, was to first sort the points by their groups. I thought about a simple bucket sort using atomic_inc to compute bucket sizes and per-point relocation indices (got a better idea for sorting?, atomics may not be the best idea). After that they're sorted by groups and I could possibly come up with an adaption of the segmented scan algorithms presented here. But in this special case, I got a very large amount of data per point (9-10 floats, maybe even doubles if the need arises), so the standard algorithms using a shared memory element per thread and a thread per point might make problems regarding per-multiprocessor resources as shared memory or registers (Ok, much more on compute capability 1.x than 2.x, but still). Due to the very small and constant number of groups I thought there might be better approaches. Maybe there are already existing ideas suited for these specific properties of such a standard problem. Or maybe my general approach isn't that bad and you got ideas for improving the individual steps, like a good sorting algorithm suited for a very small number of keys or some segmented reduction algorithm minimizing shared memory/register usage. I'm looking for general approaches and don't want to use external libraries. FWIW I'm using OpenCL, but it shouldn't really matter as the general concepts of GPU computing don't really differ over the major frameworks.

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• Methodology for a Rails app

  - by Aaron Vegh

  I'm undertaking a rather large conversion from a legacy database-driven Windows app to a Rails app. Because of the large number of forms and database tables involved, I want to make sure I've got the right methodology before getting too far. My chief concern is minimizing the amount of code I have to write. There are many models that interact together, and I want to make sure I'm using them correctly. Here's a simplified set of models: class Patient < ActiveRecord::Base has_many :PatientAddresses has_many :PatientFileStatuses end class PatientAddress < ActiveRecord::Base belongs_to :Patient end class PatientFileStatus < ActiveRecord::Base belongs_to :Patient end The controller determines if there's a Patient selected; everything else is based on that. In the view, I will be needing data from each of these models. But it seems like I have to write an instance variable in my controller for every attribute that I want to use. So I start writing code like this: @patient = Patient.find(session[:patient]) @patient_addresses = @patient.PatientAddresses @patient_file_statuses = @patient.PatientFileStatuses @enrollment_received_when = @patient_file_statuses[0].EnrollmentReceivedWhen @consent_received = @patient_file_statuses[0].ConsentReceived @consent_received_when = @patient_file_statuses[0].ConsentReceivedWhen The first three lines grab the Patient model and its relations. The next three lines are examples of my providing values to the view from one of those relations. The view has a combination of text fields and select fields to show the data above. For example: <%= select("patientfilestatus", "ConsentReceived", {"val1"="val1", "val2"="val2", "Written"="Written"}, :include_blank=true )% <%= calendar_date_select_tag "patient_file_statuses[EnrollmentReceivedWhen]", @enrollment_complete_when, :popup=:force % (BTW, the select tag isn't really working; I think I have to use collection_select?) My questions are: Do I have to manually declare the value of every instance variable in the controller, or can/should I do it within the view? What is the proper technique for displaying a select tag for data that's not the primary model? When I go to save changes to this form, will I have to manually pick out the attributes for each model and save them individually? Or is there a way to name the fields such that ActiveRecord does the right thing? Thanks in advance, Aaron.

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