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  • strategy /insights for avoiding document content loss due to encryption

    - by pbernatchez
    I'm about to encourage a group of people to begin using S-Mime and GPG for digital signatures and encryption. I foresee a nightmare of encrypted documents which can no longer be recovered because of lost keys. The thorniest issue is archiving. The natural way to preserve privacy in an archive is to archive the encrypted document. But that opens us up to the risk of a lost key when time comes to unarchive a document, or a forgotten password. After all it will be a long way in the future. This would be equivalent to having destroyed the document. First thought is archiving keys with documents, but that still leaves the forgotten pass phrase. Archiving the passphrase too would be tantamount to archiving in the clear. No privacy. What approaches do you use? What insights can you offer on the issue?

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  • VPN Connection Causes Internal LAN Connection Loss with Server

    - by sleepisfortheweak
    I've tried configuring basic PPTP VPN at my small business using a number of different tutorials. As far as I can tell, the actual VPN connection worked fine, but upon connecting a client, the Server 'disappears' from the internal LAN. The RRAS service must be stopped before the connection is restored. My Setup: The network is simply a DSL Gateway/Router to the outside functioning as NAT/Firewall/DHCP. The server is a Win Server 2008 machine at fixed IP 192.168.1.200. The server has 1 NIC, so I used the 'custom' option when configuring RRAS. The RRAS settings should be default except that I've disabled ports for connection types I'm not using and reduced PPTP ports to 10. I've also created an address pool and disabled DHCP packet forwarding. The server only functions as a File Share and now a VPN Server. Local LAN computers all have mapped network shares to the server authenticated based on Local User/Group setup on the server. The Problem: The moment a client connects through VPN, the server 'disappears' from the local network. All mapped drives disconnect and there is no response to a ping 192.168.1.200. Even if the client disconnects, the server does not re-appear at that address until the RRAS service is stopped. I've Tried: Using an Address Pool inside and outside the local subnet. Using DCHP Relay Checking Inbound/Outbound filters (none enabled) The fact that nothing I've tried has had any effect, and that I can connect and successfully obtain an IP tells me that it's something more fundamental I'm missing. My gut tells me that it's something to do with the second IP address added by the VPN client somehow taking over the interface or traffic from the local LAN accidently getting routed to the VPN client instead of handled at the server once RRAS has become 'active' when a client connects. Hopefully this may be obvious to someone with real IT experience. I've been doing this a while and almost never been stumped. I'm starting to think it might actually be something tricky since my setup is pretty basic yet refuses to work. I'll be happy to include more info if this doesn't ring any bells right away for anyone. Thanks

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  • Data loss with roaming profiles on login on two different computers

    - by Jurriaan Pijpers
    We have a Windows server 2003 system with Active Directory and all of our users have roaming profiles. One of the users let someone login with his username and password on a different computer (2) while he was working on his own computer (1). Now when this user logs in on his own computer (1), the profile that is loaded is one that dates back many months (i think from the last time he logged on to computer 2). My suspicion is that the profile that was cached on computer 2 from many months back when this user last logged on on this computer, on logoff, synced over the newer profile on the server. so that now when he logs in, he gets this old profile. Now my questions: Is it possible to retrieve te newer profile? Is it possible to keep this from happening in the future?

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  • Rescue data from damaged hard disk

    - by Lexsys
    Hello. I have a 500 GB hard drive with one NTFS-partition on it. I can mount it with Ubuntu and view the contents. But when I try to copy something, I get an I/O error. Ok, I tried to make its image with dd. I/O error as soon as it starts. I have installed ddrescue, but its manual page says not to use it with drives, failing on I/O. Can I manage to get some information from this drive and how to do this?

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  • Strange loss of format on pen drive

    - by Kiewic
    Hi, here is an screenshot of my pen drive. The files are impossible to open, and the names have been replaced by strange characters. In Ubuntu is worst, the Windows system crash. What can I do to recover my information?

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  • Zend Framework 2 loading slow and loss of connection using WAMP

    - by Charlie
    I've been facing an issue with Zend framework running on my local Wamp 2.2 server. I am not sure what I'm doing wrong but ZF2 seems to load really slow when making an http request. Any other request to a php or html file seems to run smoothly. Also, sometimes when the loading time takes longer, I get this message: "The connection to [virtualhostname] was interrupted" I then need to hit refresh to complete the request. I checked apache error log and everything looks fine. Please, I appreciate any type of guide/suggestion to take care of this issue. I followed the starter guide word by word.

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  • SQL SERVER – Configure Management Data Collection in Quick Steps – T-SQL Tuesday #005

    - by pinaldave
    This article was written as a response to T-SQL Tuesday #005 – Reporting. The three most important components of any computer and server are the CPU, Memory, and Hard disk specification. This post talks about  how to get more details about these three most important components using the Management Data Collection. Management Data Collection generates the reports for the three said components by default. Configuring Data Collection is a very easy task and can be done very quickly. Please note: There are many different ways to get reports generated for CPU, Memory and IO. You can use DMVs, Extended Events as well Perfmon to trace the data. Keeping the T-SQL Tuesday subject of reporting this post is created to give visual tutorial to quickly configure Data Collection and generate Reports. From Book On-Line: The data collector is a core component of the Data Collection platform for SQL Server 2008 and the tools that are provided by SQL Server. The data collector provides one central point for data collection across your database servers and applications. This collection point can obtain data from a variety of sources and is not limited to performance data, unlike SQL Trace. Let us go over the visual tutorial on how quickly Data Collection can be configured. Expand the management node under the main server node and follow the direction in the pictures. This reports can be exported to PDF as well Excel by writing clicking on reports. Now let us see more additional screenshots of the reports. The reports are very self-explanatory  but can be drilled down to get further details. Click on the image to make it larger. Well, as we can see, it is very easy to configure and utilize this tool. Do you use this tool in your organization? Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Reporting, SQL Reports

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  • Allen for Umbraco with location EXIF meta data

    - by Vizioz Limited
    The latest version of Allen for Umbraco has now hit the Apple App store, we have managed to add some nice improvements to this version that include:Storing location and direction information when photos are taken within the AppEmbedding EXIF data into the images when they are uploadBackground UploadingPull to refresh the media tree Location and DirectionBy default when the camera is used within an application the location and direction that the camera is pointing is not stored within the image meta data. We have now added full support so that this data is now added. We have added a setting which allows you to prevent this data from being uploaded to your website if you do not want the location data to be sent you can turn it off within Allen, Note: Please don't forget that location services do need to be turned on to allow the app to access the images in the phone's asset library.We have had quite a few ideas from users already for using this location data, including logging free parking in Denmark to geo-tagging holiday photos and linking the photos to Google street view. Embedding EXIF dataWe now embed all the meta data available on the iPhone into the image when it is uploaded to your server, this allows you to pull the data out and use it within your site. Have a look at Cultiv's Photo Meta Data package for great example code that allows you to automatically pull this data out and populate properties on your Umbraco media item.We slightly modified the source code of this package to allow the package to always extract the image data, as the default package requires a property to allow the data to be extracted, it's an easy change, if you get stuck add a comment to this post. Background UploadingIf you try to upload multiple images and need to start doing something else on your phone, you can now click the home button and the application will continue to upload your images in the background. As soon as it has finished you will receive a standard Apple notification. Pull to RefreshOur final enhancement has been to add "Pull to refresh" to the media trees, just pull the tree downwards with your finger and it will refresh, this is useful if you are adding items to your media tree while testing your site with Allen for Umbraco. Future enhancements.. your ideas?If you have any ideas for future enhancement feel free to add a comment below!

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  • What is the most time-effective way to monitor & manage threats from bots and/or humans?

    - by CheeseConQueso
    I'm usually overwhelmed by the amount of tools that hosting companies provide to track & quantify traffic data and statistics. I'm equally overwhelmed by the countless flavors of malicious 'attacks' that target any and every web site known to man. The security methods used to protect both the back and front end of a website are documented well and are straight-forward in terms of ease of implementation and application, but the army of autonomous bots knows no boundaries and will always find a niche of a website to infest. So what can be done to handle the inevitable swarm of bots that pound your domain with brute force? Whenever I look at error logs for my domains, there are always thousands of entries that look like bots trying to sneak sql code into the database by tricking the variables in the url into giving them schema information or private data within the database. My barbaric and time-consuming plan of defense is just to monitor visitor statistics for those obvious patterns of abuse and either ban the ips or range of ips accordingly. Aside from that, I don't know much else I could do to prevent all of the ping pong going on all day. Are there any good tools that automatically monitor this background activity (specifically activity that throws errors on the web & db server) and proactively deal with these source(s) of mayhem?

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  • Which data structure should I use for dynamically generated platforms?

    - by Joey Green
    I'm creating a platform type of game with various types of platforms. Platforms that move, shake, rotate, etc. Multiple types and multiple of each type can be on the screen at once. The platforms will be procedural generated. I'm trying to figure out which of the following would be a better platform system: Pre-allocate all platforms when the scene loads, storing each platform type into different platform type arrays( i.e. regPlatformArray ), and just getting one when I need one. The other option is to allocate and load what I need when my code needs it. The problem with 1 is keeping up with the indices that are in use on screen and which aren't. The problem with 2 is I'm having a hard time wrapping my head around how I would store these platforms so that I can call the update/draw methods on them and managing that data structure that holds them. The data structure would constantly be growing and shrinking. It seems there could be too much complexity. I'm using the cocos2d iPhone game engine. Anyways, which option would be best or is there a better option?

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  • When someone deletes a shared data source in SSRS

    - by Rob Farley
    SQL Server Reporting Services plays nicely. You can have things in the catalogue that get shared. You can have Reports that have Links, Datasets that can be used across different reports, and Data Sources that can be used in a variety of ways too. So if you find that someone has deleted a shared data source, you potentially have a bit of a horror story going on. And this works for this month’s T-SQL Tuesday theme, hosted by Nick Haslam, who wants to hear about horror stories. I don’t write about LobsterPot client horror stories, so I’m writing about a situation that a fellow MVP friend asked me about recently instead. The best thing to do is to grab a recent backup of the ReportServer database, restore it somewhere, and figure out what’s changed. But of course, this isn’t always possible. And it’s much nicer to help someone with this kind of thing, rather than to be trying to fix it yourself when you’ve just deleted the wrong data source. Unfortunately, it lets you delete data sources, without trying to scream that the data source is shared across over 400 reports in over 100 folders, as was the case for my friend’s colleague. So, suddenly there’s a big problem – lots of reports are failing, and the time to turn it around is small. You probably know which data source has been deleted, but getting the shared data source back isn’t the hard part (that’s just a connection string really). The nasty bit is all the re-mapping, to get those 400 reports working again. I know from exploring this kind of stuff in the past that the ReportServer database (using its default name) has a table called dbo.Catalog to represent the catalogue, and that Reports are stored here. However, the information about what data sources these deployed reports are configured to use is stored in a different table, dbo.DataSource. You could be forgiven for thinking that shared data sources would live in this table, but they don’t – they’re catalogue items just like the reports. Let’s have a look at the structure of these two tables (although if you’re reading this because you have a disaster, feel free to skim past). Frustratingly, there doesn’t seem to be a Books Online page for this information, sorry about that. I’m also not going to look at all the columns, just ones that I find interesting enough to mention, and that are related to the problem at hand. These fields are consistent all the way through to SQL Server 2012 – there doesn’t seem to have been any changes here for quite a while. dbo.Catalog The Primary Key is ItemID. It’s a uniqueidentifier. I’m not going to comment any more on that. A minor nice point about using GUIDs in unfamiliar databases is that you can more easily figure out what’s what. But foreign keys are for that too… Path, Name and ParentID tell you where in the folder structure the item lives. Path isn’t actually required – you could’ve done recursive queries to get there. But as that would be quite painful, I’m more than happy for the Path column to be there. Path contains the Name as well, incidentally. Type tells you what kind of item it is. Some examples are 1 for a folder and 2 a report. 4 is linked reports, 5 is a data source, 6 is a report model. I forget the others for now (but feel free to put a comment giving the full list if you know it). Content is an image field, remembering that image doesn’t necessarily store images – these days we’d rather use varbinary(max), but even in SQL Server 2012, this field is still image. It stores the actual item definition in binary form, whether it’s actually an image, a report, whatever. LinkSourceID is used for Linked Reports, and has a self-referencing foreign key (allowing NULL, of course) back to ItemID. Parameter is an ntext field containing XML for the parameters of the report. Not sure why this couldn’t be a separate table, but I guess that’s just the way it goes. This field gets changed when the default parameters get changed in Report Manager. There is nothing in dbo.Catalog that describes the actual data sources that the report uses. The default data sources would be part of the Content field, as they are defined in the RDL, but when you deploy reports, you typically choose to NOT replace the data sources. Anyway, they’re not in this table. Maybe it was already considered a bit wide to throw in another ntext field, I’m not sure. They’re in dbo.DataSource instead. dbo.DataSource The Primary key is DSID. Yes it’s a uniqueidentifier... ItemID is a foreign key reference back to dbo.Catalog Fields such as ConnectionString, Prompt, UserName and Password do what they say on the tin, storing information about how to connect to the particular source in question. Link is a uniqueidentifier, which refers back to dbo.Catalog. This is used when a data source within a report refers back to a shared data source, rather than embedding the connection information itself. You’d think this should be enforced by foreign key, but it’s not. It does allow NULLs though. Flags this is an int, and I’ll come back to this. When a Data Source gets deleted out of dbo.Catalog, you might assume that it would be disallowed if there are references to it from dbo.DataSource. Well, you’d be wrong. And not because of the lack of a foreign key either. Deleting anything from the catalogue is done by calling a stored procedure called dbo.DeleteObject. You can look at the definition in there – it feels very much like the kind of Delete stored procedures that many people write, the kind of thing that means they don’t need to worry about allowing cascading deletes with foreign keys – because the stored procedure does the lot. Except that it doesn’t quite do that. If it deleted everything on a cascading delete, we’d’ve lost all the data sources as configured in dbo.DataSource, and that would be bad. This is fine if the ItemID from dbo.DataSource hooks in – if the report is being deleted. But if a shared data source is being deleted, you don’t want to lose the existence of the data source from the report. So it sets it to NULL, and it marks it as invalid. We see this code in that stored procedure. UPDATE [DataSource]    SET       [Flags] = [Flags] & 0x7FFFFFFD, -- broken link       [Link] = NULL FROM    [Catalog] AS C    INNER JOIN [DataSource] AS DS ON C.[ItemID] = DS.[Link] WHERE    (C.Path = @Path OR C.Path LIKE @Prefix ESCAPE '*') Unfortunately there’s no semi-colon on the end (but I’d rather they fix the ntext and image types first), and don’t get me started about using the table name in the UPDATE clause (it should use the alias DS). But there is a nice comment about what’s going on with the Flags field. What I’d LIKE it to do would be to set the connection information to a report-embedded copy of the connection information that’s in the shared data source, the one that’s about to be deleted. I understand that this would cause someone to lose the benefit of having the data sources configured in a central point, but I’d say that’s probably still slightly better than LOSING THE INFORMATION COMPLETELY. Sorry, rant over. I should log a Connect item – I’ll put that on my todo list. So it sets the Link field to NULL, and marks the Flags to tell you they’re broken. So this is your clue to fixing it. A bitwise AND with 0x7FFFFFFD is basically stripping out the ‘2’ bit from a number. So numbers like 2, 3, 6, 7, 10, 11, etc, whose binary representation ends in either 11 or 10 get turned into 0, 1, 4, 5, 8, 9, etc. We can test for it using a WHERE clause that matches the SET clause we’ve just used. I’d also recommend checking for Link being NULL and also having no ConnectionString. And join back to dbo.Catalog to get the path (including the name) of broken reports are – in case you get a surprise from a different data source being broken in the past. SELECT c.Path, ds.Name FROM dbo.[DataSource] AS ds JOIN dbo.[Catalog] AS c ON c.ItemID = ds.ItemID WHERE ds.[Flags] = ds.[Flags] & 0x7FFFFFFD AND ds.[Link] IS NULL AND ds.[ConnectionString] IS NULL; When I just ran this on my own machine, having deleted a data source to check my code, I noticed a Report Model in the list as well – so if you had thought it was just going to be reports that were broken, you’d be forgetting something. So to fix those reports, get your new data source created in the catalogue, and then find its ItemID by querying Catalog, using Path and Name to find it. And then use this value to fix them up. To fix the Flags field, just add 2. I prefer to use bitwise OR which should do the same. Use the OUTPUT clause to get a copy of the DSIDs of the ones you’re changing, just in case you need to revert something later after testing (doing it all in a transaction won’t help, because you’ll just lock out the table, stopping you from testing anything). UPDATE ds SET [Flags] = [Flags] | 2, [Link] = '3AE31CBA-BDB4-4FD1-94F4-580B7FAB939D' /*Insert your own GUID*/ OUTPUT deleted.Name, deleted.DSID, deleted.ItemID, deleted.Flags FROM dbo.[DataSource] AS ds JOIN dbo.[Catalog] AS c ON c.ItemID = ds.ItemID WHERE ds.[Flags] = ds.[Flags] & 0x7FFFFFFD AND ds.[Link] IS NULL AND ds.[ConnectionString] IS NULL; But please be careful. Your mileage may vary. And there’s no reason why 400-odd broken reports needs to be quite the nightmare that it could be. Really, it should be less than five minutes. @rob_farley

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  • Reference Data Management

    - by rahulkamath
    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:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} table.MsoTableColorfulListAccent2 {mso-style-name:"Colorful List - Accent 2"; mso-tstyle-rowband-size:1; mso-tstyle-colband-size:1; mso-style-priority:72; mso-style-unhide:no; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-tstyle-shading:#F8EDED; mso-tstyle-shading-themecolor:accent2; mso-tstyle-shading-themetint:25; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; color:black; mso-themecolor:text1;} table.MsoTableColorfulListAccent2FirstRow {mso-style-name:"Colorful List - Accent 2"; mso-table-condition:first-row; mso-style-priority:72; mso-style-unhide:no; mso-tstyle-shading:#9E3A38; mso-tstyle-shading-themecolor:accent2; mso-tstyle-shading-themeshade:204; mso-tstyle-border-bottom:1.5pt solid white; mso-tstyle-border-bottom-themecolor:background1; color:white; mso-themecolor:background1; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableColorfulListAccent2LastRow {mso-style-name:"Colorful List - Accent 2"; mso-table-condition:last-row; mso-style-priority:72; mso-style-unhide:no; mso-tstyle-shading:white; mso-tstyle-shading-themecolor:background1; mso-tstyle-border-top:1.5pt solid black; mso-tstyle-border-top-themecolor:text1; color:#9E3A38; mso-themecolor:accent2; mso-themeshade:204; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableColorfulListAccent2FirstCol {mso-style-name:"Colorful List - Accent 2"; mso-table-condition:first-column; mso-style-priority:72; mso-style-unhide:no; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableColorfulListAccent2LastCol {mso-style-name:"Colorful List - Accent 2"; mso-table-condition:last-column; mso-style-priority:72; mso-style-unhide:no; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableColorfulListAccent2OddColumn {mso-style-name:"Colorful List - Accent 2"; mso-table-condition:odd-column; mso-style-priority:72; mso-style-unhide:no; mso-tstyle-shading:#EFD3D2; mso-tstyle-shading-themecolor:accent2; mso-tstyle-shading-themetint:63; mso-tstyle-border-top:cell-none; mso-tstyle-border-left:cell-none; mso-tstyle-border-bottom:cell-none; mso-tstyle-border-right:cell-none; mso-tstyle-border-insideh:cell-none; mso-tstyle-border-insidev:cell-none;} table.MsoTableColorfulListAccent2OddRow {mso-style-name:"Colorful List - Accent 2"; mso-table-condition:odd-row; mso-style-priority:72; mso-style-unhide:no; mso-tstyle-shading:#F2DBDB; mso-tstyle-shading-themecolor:accent2; mso-tstyle-shading-themetint:51;} Reference Data Management Oracle Data Relationship Management (DRM) has always been extremely powerful as an Enterprise MDM solution that can help manage changes to master data in a way that influences enterprise structure, whether it be mastering chart of accounts to enable financial transformation, or revamping organization structures to drive business transformation and operational efficiencies, or mastering sales territories in light of rapid fire acquisitions that require frequent sales territory refinement, equitable distribution of leads and accounts to salespersons, and alignment of budget/forecast with results to optimize sales coverage. Increasingly, DRM is also being utilized by Oracle customers for reference data management, an emerging solution space that deserves some explanation. What is reference data? Reference data is a close cousin of master data. While master data may be more rapidly changing, requires consensus building across stakeholders and lends structure to business transactions, reference data is simpler, more slowly changing, but has semantic content that is used to categorize or group other information assets – including master data – and give them contextual value. The following table contains an illustrative list of examples of reference data by type. Reference data types may include types and codes, business taxonomies, complex relationships & cross-domain mappings or standards. Types & Codes Taxonomies Relationships / Mappings Standards Transaction Codes Industry Classification Categories and Codes, e.g., North America Industry Classification System (NAICS) Product / Segment; Product / Geo Calendars (e.g., Gregorian, Fiscal, Manufacturing, Retail, ISO8601) Lookup Tables (e.g., Gender, Marital Status, etc.) Product Categories City à State à Postal Codes Currency Codes (e.g., ISO) Status Codes Sales Territories (e.g., Geo, Industry Verticals, Named Accounts, Federal/State/Local/Defense) Customer / Market Segment; Business Unit / Channel Country Codes (e.g., ISO 3166, UN) Role Codes Market Segments Country Codes / Currency Codes / Financial Accounts Date/Time, Time Zones (e.g., ISO 8601) Domain Values Universal Standard Products and Services Classification (UNSPSC), eCl@ss International Classification of Diseases (ICD) e.g., ICD9 à IC10 mappings Tax Rates Why manage reference data? Reference data carries contextual value and meaning and therefore its use can drive business logic that helps execute a business process, create a desired application behavior or provide meaningful segmentation to analyze transaction data. Further, mapping reference data often requires human judgment. Sample Use Cases of Reference Data Management Healthcare: Diagnostic Codes The reference data challenges in the healthcare industry offer a case in point. Part of being HIPAA compliant requires medical practitioners to transition diagnosis codes from ICD-9 to ICD-10, a medical coding scheme used to classify diseases, signs and symptoms, causes, etc. The transition to ICD-10 has a significant impact on business processes, procedures, contracts, and IT systems. Since both code sets ICD-9 and ICD-10 offer diagnosis codes of very different levels of granularity, human judgment is required to map ICD-9 codes to ICD-10. The process requires collaboration and consensus building among stakeholders much in the same way as does master data management. Moreover, to build reports to understand utilization, frequency and quality of diagnoses, medical practitioners may need to “cross-walk” mappings -- either forward to ICD-10 or backwards to ICD-9 depending upon the reporting time horizon. Spend Management: Product, Service & Supplier Codes Similarly, as an enterprise looks to rationalize suppliers and leverage their spend, conforming supplier codes, as well as product and service codes requires supporting multiple classification schemes that may include industry standards (e.g., UNSPSC, eCl@ss) or enterprise taxonomies. Aberdeen Group estimates that 90% of companies rely on spreadsheets and manual reviews to aggregate, classify and analyze spend data, and that data management activities account for 12-15% of the sourcing cycle and consume 30-50% of a commodity manager’s time. Creating a common map across the extended enterprise to rationalize codes across procurement, accounts payable, general ledger, credit card, procurement card (P-card) as well as ACH and bank systems can cut sourcing costs, improve compliance, lower inventory stock, and free up talent to focus on value added tasks. Specialty Finance: Point of Sales Transaction Codes and Product Codes In the specialty finance industry, enterprises are confronted with usury laws – governed at the state and local level – that regulate financial product innovation as it relates to consumer loans, check cashing and pawn lending. To comply, it is important to demonstrate that transactions booked at the point of sale are posted against valid product codes that were on offer at the time of booking the sale. Since new products are being released at a steady stream, it is important to ensure timely and accurate mapping of point-of-sale transaction codes with the appropriate product and GL codes to comply with the changing regulations. Multi-National Companies: Industry Classification Schemes As companies grow and expand across geographies, a typical challenge they encounter with reference data represents reconciling various versions of industry classification schemes in use across nations. While the United States, Mexico and Canada conform to the North American Industry Classification System (NAICS) standard, European Union countries choose different variants of the NACE industry classification scheme. Multi-national companies must manage the individual national NACE schemes and reconcile the differences across countries. Enterprises must invest in a reference data change management application to address the challenge of distributing reference data changes to downstream applications and assess which applications were impacted by a given change.

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  • Partner Webcast - Oracle Data Integration Competency Center (DICC): A Niche Market for services

    - by Thanos Terentes Printzios
    Market success now depends on data integration speed. This is why we collected all best practices from the most advanced IT leaders, simply to prove that a Data Integration competency center should be the primary new IT team you should establish. This is a niche market with unlimited potential for partners becoming, the much needed, data integration services provider trusted by customers. We would like to elaborate with OPN Partners on the Business Value Assessment and Total Economic Impact of the Data Integration Platform for End Users, while justifying re-organizing your IT services teams. We are happy to share our research on: The Economical impact of data integration platform/competency center. Justifying strongest reasons and differentiators, using numeric analysis and best-practice in customer case studies from specific industries Utilizing diagnostics and health-check analysis in building a business case for your customers What exactly is so special in the technology of Oracle Data Integration Impact of growing data volume and amount of data sources Analysis of usual solutions that are being implemented so far, addressing key challenges and mistakes During this partner webcast we will balance business case centric content with extensive numerical ROI analysis. Join us to find out how to build a unified approach to moving/sharing/integrating data across the enterprise and why this is an important new services opportunity for partners. Agenda: Data Integration Competency Center Oracle Data Integration Solution Overview Services Niche Market For OPN Summary Q&A Delivery Format This FREE online LIVE eSeminar will be delivered over the Web. Registrations received less than 24hours prior to start time may not receive confirmation to attend. Presenter: Milomir Vojvodic, EMEA Senior Business Development Manager for Oracle Data Integration Product Group Date: Thursday, September 4th, 10pm CEST (8am UTC/11am EEST)Duration: 1 hour Register Today For any questions please contact us at [email protected]

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  • Should one use a separate database for application data and user data?

    - by trycatch
    I’ve been working on a project for a little while and I’m unsure which is the better architecture. I’m interested in the consensus. The answer to me seems fairly obvious but something about it is digging at me and I can't pick out what. The TL;DR is: how do you handle a program with application data and user data in the same DB which needs to be able to receive updates to the application data periodically? One database for user data and one for application, or both in one? The detailed version is.. if an application has a database which needs to maintain application data AND user data, and the user data all references application data, it feels more natural to me to store them in the same database. But if there exists a need to be able to update the application data within this database periodically, should this be stripped into two databases so that one can simply download the updated application data database file as an update and replace the old one? Or should they remain as one database, and the application data be updated via a script which inserts the new data into the existing database? The second sounds clearly preferable to me... but for some reason just doesn’t feel right, and I can't pick out quite why.

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  • WCF Data Service BeginSaveChanges not saving changes in Silverlight app

    - by Enigmativity
    I'm having a hell of a time getting WCF Data Services to work within Silverlight. I'm using the VS2010 RC. I've struggled with the cross domain issue requiring the use of clientaccesspolicy.xml & crossdomain.xml files in the web server root folder, but I just couldn't get this to work. I've resorted to putting both the Silverlight Web App & the WCF Data Service in the same project to get past this issue, but any advice here would be good. But now that I can actually see my data coming from the database and being displayed in a data grid within Silverlight I thought my troubles were over - but no. I can edit the data and the in-memory entity is changing, but when I call BeginSaveChanges (with the appropriate async EndSaveChangescall) I get no errors, but no data updates in the database. Here's my WCF Data Services code: public class MyDataService : DataService<MyEntities> { public static void InitializeService(DataServiceConfiguration config) { config.SetEntitySetAccessRule("*", EntitySetRights.All); config.SetServiceOperationAccessRule("*", ServiceOperationRights.All); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } protected override void OnStartProcessingRequest(ProcessRequestArgs args) { base.OnStartProcessingRequest(args); HttpContext context = HttpContext.Current; HttpCachePolicy c = HttpContext.Current.Response.Cache; c.SetCacheability(HttpCacheability.ServerAndPrivate); c.SetExpires(HttpContext.Current.Timestamp.AddSeconds(60)); c.VaryByHeaders["Accept"] = true; c.VaryByHeaders["Accept-Charset"] = true; c.VaryByHeaders["Accept-Encoding"] = true; c.VaryByParams["*"] = true; } } I've pinched the OnStartProcessingRequest code from Scott Hanselman's article Creating an OData API for StackOverflow including XML and JSON in 30 minutes. Here's my code from my Silverlight app: private MyEntities _wcfDataServicesEntities; private CollectionViewSource _customersViewSource; private ObservableCollection<Customer> _customers; private void UserControl_Loaded(object sender, RoutedEventArgs e) { if (!System.ComponentModel.DesignerProperties.GetIsInDesignMode(this)) { _wcfDataServicesEntities = new MyEntities(new Uri("http://localhost:7156/MyDataService.svc/")); _customersViewSource = this.Resources["customersViewSource"] as CollectionViewSource; DataServiceQuery<Customer> query = _wcfDataServicesEntities.Customer; query.BeginExecute(result => { _customers = new ObservableCollection<Customer>(); Array.ForEach(query.EndExecute(result).ToArray(), _customers.Add); Dispatcher.BeginInvoke(() => { _customersViewSource.Source = _customers; }); }, null); } } private void button1_Click(object sender, RoutedEventArgs e) { _wcfDataServicesEntities.BeginSaveChanges(r => { var response = _wcfDataServicesEntities.EndSaveChanges(r); string[] results = new[] { response.BatchStatusCode.ToString(), response.IsBatchResponse.ToString() }; _customers[0].FinAssistCompanyName = String.Join("|", results); }, null); } The response string I get back data binds to my grid OK and shows "-1|False". My intent is to get a proof-of-concept working here and then do the appropriate separation of concerns to turn this into a simple line-of-business app. I've spent hours and hours on this. I'm being driven insane. Any ideas how to get this working?

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  • Serial port : Read data problem, not reading complete data

    - by Anuj Mehta
    Hi I have an application where I am sending data via serial port from PC1 (Java App) and reading that data in PC2 (C++ App). The problem that I am facing is that my PC2 (C++ App) is not able to read complete data sent by PC1 i.e. from my PC1 I am sending 190 bytes but PC2 is able to read close to 140 bytes though I am trying to read in a loop. Below is code snippet of my C++ App Open the connection to serial port serialfd = open( serialPortName.c_str(), O_RDWR | O_NOCTTY | O_NDELAY); if (serialfd == -1) { /* * Could not open the port. */ TRACE << "Unable to open port: " << serialPortName << endl; } else { TRACE << "Connected to serial port: " << serialPortName << endl; fcntl(serialfd, F_SETFL, 0); } Configure the Serial Port parameters struct termios options; /* * Get the current options for the port... */ tcgetattr(serialfd, &options); /* * Set the baud rates to 9600... */ cfsetispeed(&options, B38400); cfsetospeed(&options, B38400); /* * 8N1 * Data bits - 8 * Parity - None * Stop bits - 1 */ options.c_cflag &= ~PARENB; options.c_cflag &= ~CSTOPB; options.c_cflag &= ~CSIZE; options.c_cflag |= CS8; /* * Enable hardware flow control */ options.c_cflag |= CRTSCTS; /* * Enable the receiver and set local mode... */ options.c_cflag |= (CLOCAL | CREAD); // Flush the earlier data tcflush(serialfd, TCIFLUSH); /* * Set the new options for the port... */ tcsetattr(serialfd, TCSANOW, &options); Now I am reading data const int MAXDATASIZE = 512; std::vector<char> m_vRequestBuf; char buffer[MAXDATASIZE]; int totalBytes = 0; fcntl(serialfd, F_SETFL, FNDELAY); while(1) { bytesRead = read(serialfd, &buffer, MAXDATASIZE); if(bytesRead == -1) { //Sleep for some time and read again usleep(900000); } else { totalBytes += bytesRead; //Add data read to vector for(int i =0; i < bytesRead; i++) { m_vRequestBuf.push_back(buffer[i]); } int newBytesRead = 0; //Now keep trying to read more data while(newBytesRead != -1) { //clear contents of buffer memset((void*)&buffer, 0, sizeof(char) * MAXDATASIZE); newBytesRead = read(serialfd, &buffer, MAXDATASIZE); totalBytes += newBytesRead; for(int j = 0; j < newBytesRead; j++) { m_vRequestBuf.push_back(buffer[j]); } }//inner while break; } //while

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  • Join and sum not compatible matrices through data.table

    - by leodido
    My goal is to "sum" two not compatible matrices (matrices with different dimensions) using (and preserving) row and column names. I've figured this approach: convert the matrices to data.table objects, join them and then sum columns vectors. An example: > M1 1 3 4 5 7 8 1 0 0 1 0 0 0 3 0 0 0 0 0 0 4 1 0 0 0 0 0 5 0 0 0 0 0 0 7 0 0 0 0 1 0 8 0 0 0 0 0 0 > M2 1 3 4 5 8 1 0 0 1 0 0 3 0 0 0 0 0 4 1 0 0 0 0 5 0 0 0 0 0 8 0 0 0 0 0 > M1 %ms% M2 1 3 4 5 7 8 1 0 0 2 0 0 0 3 0 0 0 0 0 0 4 2 0 0 0 0 0 5 0 0 0 0 0 0 7 0 0 0 0 1 0 8 0 0 0 0 0 0 This is my code: M1 <- matrix(c(0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0), byrow = TRUE, ncol = 6) colnames(M1) <- c(1,3,4,5,7,8) M2 <- matrix(c(0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0), byrow = TRUE, ncol = 5) colnames(M2) <- c(1,3,4,5,8) # to data.table objects DT1 <- data.table(M1, keep.rownames = TRUE, key = "rn") DT2 <- data.table(M2, keep.rownames = TRUE, key = "rn") # join and sum of common columns if (nrow(DT1) > nrow(DT2)) { A <- DT2[DT1, roll = TRUE] A[, list(X1 = X1 + X1.1, X3 = X3 + X3.1, X4 = X4 + X4.1, X5 = X5 + X5.1, X7, X8 = X8 + X8.1), by = rn] } That outputs: rn X1 X3 X4 X5 X7 X8 1: 1 0 0 2 0 0 0 2: 3 0 0 0 0 0 0 3: 4 2 0 0 0 0 0 4: 5 0 0 0 0 0 0 5: 7 0 0 0 0 1 0 6: 8 0 0 0 0 0 0 Then I can convert back this data.table to a matrix and fix row and column names. The questions are: how to generalize this procedure? I need a way to automatically create list(X1 = X1 + X1.1, X3 = X3 + X3.1, X4 = X4 + X4.1, X5 = X5 + X5.1, X7, X8 = X8 + X8.1) because i want to apply this function to matrices which dimensions (and row/columns names) are not known in advance. In summary I need a merge procedure that behaves as described. there are other strategies/implementations that achieve the same goal that are, at the same time, faster and generalized? (hoping that some data.table monster help me) to what kind of join (inner, outer, etc. etc.) is assimilable this procedure? Thanks in advance. p.s.: I'm using data.table version 1.8.2 EDIT - SOLUTIONS @Aaron solution. No external libraries, only base R. It works also on list of matrices. add_matrices_1 <- function(...) { a <- list(...) cols <- sort(unique(unlist(lapply(a, colnames)))) rows <- sort(unique(unlist(lapply(a, rownames)))) out <- array(0, dim = c(length(rows), length(cols)), dimnames = list(rows,cols)) for (m in a) out[rownames(m), colnames(m)] <- out[rownames(m), colnames(m)] + m out } @MadScone solution. Used reshape2 package. It works only on two matrices per call. add_matrices_2 <- function(m1, m2) { m <- acast(rbind(melt(M1), melt(M2)), Var1~Var2, fun.aggregate = sum) mn <- unique(colnames(m1), colnames(m2)) rownames(m) <- mn colnames(m) <- mn m } BENCHMARK (100 runs with microbenchmark package) Unit: microseconds expr min lq median uq max 1 add_matrices_1 196.009 257.5865 282.027 291.2735 549.397 2 add_matrices_2 13737.851 14697.9790 14864.778 16285.7650 25567.448 No need to comment the benchmark: @Aaron solution wins. I'll continue to investigate a similar solution for data.table objects. I'll add other solutions eventually reported or discovered.

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  • Design review for application facing memory issues

    - by Mr Moose
    I apologise in advance for the length of this post, but I want to paint an accurate picture of the problems my app is facing and then pose some questions below; I am trying to address some self inflicted design pain that is now leading to my application crashing due to out of memory errors. An abridged description of the problem domain is as follows; The application takes in a “dataset” that consists of numerous text files containing related data An individual text file within the dataset usually contains approx 20 “headers” that contain metadata about the data it contains. It also contains a large tab delimited section containing data that is related to data in one of the other text files contained within the dataset. The number of columns per file is very variable from 2 to 256+ columns. The original application was written to allow users to load a dataset, map certain columns of each of the files which basically indicating key information on the files to show how they are related as well as identify a few expected column names. Once this is done, a validation process takes place to enforce various rules and ensure that all the relationships between the files are valid. Once that is done, the data is imported into a SQL Server database. The database design is an EAV (Entity-Attribute-Value) model used to cater for the variable columns per file. I know EAV has its detractors, but in this case, I feel it was a reasonable choice given the disparate data and variable number of columns submitted in each dataset. The memory problem Given the fact the combined size of all text files was at most about 5 megs, and in an effort to reduce the database transaction time, it was decided to read ALL the data from files into memory and then perform the following; perform all the validation whilst the data was in memory relate it using an object model Start DB transaction and write the key columns row by row, noting the Id of the written row (all tables in the database utilise identity columns), then the Id of the newly written row is applied to all related data Once all related data had been updated with the key information to which it relates, these records are written using SqlBulkCopy. Due to our EAV model, we essentially have; x columns by y rows to write, where x can by 256+ and rows are often into the tens of thousands. Once all the data is written without error (can take several minutes for large datasets), Commit the transaction. The problem now comes from the fact we are now receiving individual files containing over 30 megs of data. In a dataset, we can receive any number of files. We’ve started seen datasets of around 100 megs coming in and I expect it is only going to get bigger from here on in. With files of this size, data can’t even be read into memory without the app falling over, let alone be validated and imported. I anticipate having to modify large chunks of the code to allow validation to occur by parsing files line by line and am not exactly decided on how to handle the import and transactions. Potential improvements I’ve wondered about using GUIDs to relate the data rather than relying on identity fields. This would allow data to be related prior to writing to the database. This would certainly increase the storage required though. Especially in an EAV design. Would you think this is a reasonable thing to try, or do I simply persist with identity fields (natural keys can’t be trusted to be unique across all submitters). Use of staging tables to get data into the database and only performing the transaction to copy data from staging area to actual destination tables. Questions For systems like this that import large quantities of data, how to you go about keeping transactions small. I’ve kept them as small as possible in the current design, but they are still active for several minutes and write hundreds of thousands of records in one transaction. Is there a better solution? The tab delimited data section is read into a DataTable to be viewed in a grid. I don’t need the full functionality of a DataTable, so I suspect it is overkill. Is there anyway to turn off various features of DataTables to make them more lightweight? Are there any other obvious things you would do in this situation to minimise the memory footprint of the application described above? Thanks for your kind attention.

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  • Using Transaction Logging to Recover Post-Archived Essbase data

    - by Keith Rosenthal
    Data recovery is typically performed by restoring data from an archive.  Data added or removed since the last archive took place can also be recovered by enabling transaction logging in Essbase.  Transaction logging works by writing transactions to a log store.  The information in the log store can then be recovered by replaying the log store entries in sequence since the last archive took place.  The following information is recorded within a transaction log entry: Sequence ID Username Start Time End Time Request Type A request type can be one of the following categories: Calculations, including the default calculation as well as both server and client side calculations Data loads, including data imports as well as data loaded using a load rule Data clears as well as outline resets Locking and sending data from SmartView and the Spreadsheet Add-In.  Changes from Planning web forms are also tracked since a lock and send operation occurs during this process. You can use the Display Transactions command in the EAS console or the query database MAXL command to view the transaction log entries. Enabling Transaction Logging Transaction logging can be enabled at the Essbase server, application or database level by adding the TRANSACTIONLOGLOCATION essbase.cfg setting.  The following is the TRANSACTIONLOGLOCATION syntax: TRANSACTIONLOGLOCATION [appname [dbname]] LOGLOCATION NATIVE ENABLE | DISABLE Note that you can have multiple TRANSACTIONLOGLOCATION entries in the essbase.cfg file.  For example: TRANSACTIONLOGLOCATION Hyperion/trlog NATIVE ENABLE TRANSACTIONLOGLOCATION Sample Hyperion/trlog NATIVE DISABLE The first statement will enable transaction logging for all Essbase applications, and the second statement will disable transaction logging for the Sample application.  As a result, transaction logging will be enabled for all applications except the Sample application. A location on a physical disk other than the disk where ARBORPATH or the disk files reside is recommended to optimize overall Essbase performance. Configuring Transaction Log Replay Although transaction log entries are stored based on the LOGLOCATION parameter of the TRANSACTIONLOGLOCATION essbase.cfg setting, copies of data load and rules files are stored in the ARBORPATH/app/appname/dbname/Replay directory to optimize the performance of replaying logged transactions.  The default is to archive client data loads, but this configuration setting can be used to archive server data loads (including SQL server data loads) or both client and server data loads. To change the type of data to be archived, add the TRANSACTIONLOGDATALOADARCHIVE configuration setting to the essbase.cfg file.  Note that you can have multiple TRANSACTIONLOGDATALOADARCHIVE entries in the essbase.cfg file to adjust settings for individual applications and databases. Replaying the Transaction Log and Transaction Log Security Considerations To replay the transactions, use either the Replay Transactions command in the EAS console or the alter database MAXL command using the replay transactions grammar.  Transactions can be replayed either after a specified log time or using a range of transaction sequence IDs. The default when replaying transactions is to use the security settings of the user who originally performed the transaction.  However, if that user no longer exists or that user's username was changed, the replay operation will fail. Instead of using the default security setting, add the REPLAYSECURITYOPTION essbase.cfg setting to use the security settings of the administrator who performs the replay operation.  REPLAYSECURITYOPTION 2 will explicitly use the security settings of the administrator performing the replay operation.  REPLAYSECURITYOPTION 3 will use the administrator security settings if the original user’s security settings cannot be used. Removing Transaction Logs and Archived Replay Data Load and Rules Files Transaction logs and archived replay data load and rules files are not automatically removed and are only removed manually.  Since these files can consume a considerable amount of space, the files should be removed on a periodic basis. The transaction logs should be removed one database at a time instead of all databases simultaneously.  The data load and rules files associated with the replayed transactions should be removed in chronological order from earliest to latest.  In addition, do not remove any data load and rules files with a timestamp later than the timestamp of the most recent archive file. Partitioned Database Considerations For partitioned databases, partition commands such as synchronization commands cannot be replayed.  When recovering data, the partition changes must be replayed manually and logged transactions must be replayed in the correct chronological order. If the partitioned database includes any @XREF commands in the calc script, the logged transactions must be selectively replayed in the correct chronological order between the source and target databases. References For additional information, please see the Oracle EPM System Backup and Recovery Guide.  For EPM 11.1.2.2, the link is http://docs.oracle.com/cd/E17236_01/epm.1112/epm_backup_recovery_1112200.pdf

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  • Conceal packet loss in PCM stream

    - by ZeroDefect
    I am looking to use 'Packet Loss Concealment' to conceal lost PCM frames in an audio stream. Unfortunately, I cannot find a library that is accessible without all the licensing restrictions and code bloat (...up for some suggestions though). I have located some GPL code written by Steve Underwood for the Asterisk project which implements PLC. There are several limitations; although, as Steve suggests in his code, his algorithm can be applied to different streams with a bit of work. Currently, the code works with 8kHz 16-bit signed mono streams. Variations of the code can be found through a simple search of Google Code Search. My hope is that I can adapt the code to work with other streams. Initially, the goal is to adjust the algorithm for 8+ kHz, 16-bit signed, multichannel audio (all in a C++ environment). Eventually, I'm looking to make the code available under the GPL license in hopes that it could be of benefit to others... Attached is the code below with my efforts. The code includes a main function that will "drop" a number of frames with a given probability. Unfortunately, the code does not quite work as expected. I'm receiving EXC_BAD_ACCESS when running in gdb, but I don't get a trace from gdb when using 'bt' command. Clearly, I'm trampimg on memory some where but not sure exactly where. When I comment out the *amdf_pitch* function, the code runs without crashing... int main (int argc, char *argv[]) { std::ifstream fin("C:\\cc32kHz.pcm"); if(!fin.is_open()) { std::cout << "Failed to open input file" << std::endl; return 1; } std::ofstream fout_repaired("C:\\cc32kHz_repaired.pcm"); if(!fout_repaired.is_open()) { std::cout << "Failed to open output repaired file" << std::endl; return 1; } std::ofstream fout_lossy("C:\\cc32kHz_lossy.pcm"); if(!fout_lossy.is_open()) { std::cout << "Failed to open output repaired file" << std::endl; return 1; } audio::PcmConcealer Concealer; Concealer.Init(1, 16, 32000); //Generate random numbers; srand( time(NULL) ); int value = 0; int probability = 5; while(!fin.eof()) { char arr[2]; fin.read(arr, 2); //Generate's random number; value = rand() % 100 + 1; if(value <= probability) { char blank[2] = {0x00, 0x00}; fout_lossy.write(blank, 2); //Fill in data; Concealer.Fill((int16_t *)blank, 1); fout_repaired.write(blank, 2); } else { //Write data to file; fout_repaired.write(arr, 2); fout_lossy.write(arr, 2); Concealer.Receive((int16_t *)arr, 1); } } fin.close(); fout_repaired.close(); fout_lossy.close(); return 0; } PcmConcealer.hpp /* * Code adapted from Steve Underwood of the Asterisk Project. This code inherits * the same licensing restrictions as the Asterisk Project. */ #ifndef __PCMCONCEALER_HPP__ #define __PCMCONCEALER_HPP__ /** 1. What does it do? The packet loss concealment module provides a suitable synthetic fill-in signal, to minimise the audible effect of lost packets in VoIP applications. It is not tied to any particular codec, and could be used with almost any codec which does not specify its own procedure for packet loss concealment. Where a codec specific concealment procedure exists, the algorithm is usually built around knowledge of the characteristics of the particular codec. It will, therefore, generally give better results for that particular codec than this generic concealer will. 2. How does it work? While good packets are being received, the plc_rx() routine keeps a record of the trailing section of the known speech signal. If a packet is missed, plc_fillin() is called to produce a synthetic replacement for the real speech signal. The average mean difference function (AMDF) is applied to the last known good signal, to determine its effective pitch. Based on this, the last pitch period of signal is saved. Essentially, this cycle of speech will be repeated over and over until the real speech resumes. However, several refinements are needed to obtain smooth pleasant sounding results. - The two ends of the stored cycle of speech will not always fit together smoothly. This can cause roughness, or even clicks, at the joins between cycles. To soften this, the 1/4 pitch period of real speech preceeding the cycle to be repeated is blended with the last 1/4 pitch period of the cycle to be repeated, using an overlap-add (OLA) technique (i.e. in total, the last 5/4 pitch periods of real speech are used). - The start of the synthetic speech will not always fit together smoothly with the tail of real speech passed on before the erasure was identified. Ideally, we would like to modify the last 1/4 pitch period of the real speech, to blend it into the synthetic speech. However, it is too late for that. We could have delayed the real speech a little, but that would require more buffer manipulation, and hurt the efficiency of the no-lost-packets case (which we hope is the dominant case). Instead we use a degenerate form of OLA to modify the start of the synthetic data. The last 1/4 pitch period of real speech is time reversed, and OLA is used to blend it with the first 1/4 pitch period of synthetic speech. The result seems quite acceptable. - As we progress into the erasure, the chances of the synthetic signal being anything like correct steadily fall. Therefore, the volume of the synthesized signal is made to decay linearly, such that after 50ms of missing audio it is reduced to silence. - When real speech resumes, an extra 1/4 pitch period of sythetic speech is blended with the start of the real speech. If the erasure is small, this smoothes the transition. If the erasure is long, and the synthetic signal has faded to zero, the blending softens the start up of the real signal, avoiding a kind of "click" or "pop" effect that might occur with a sudden onset. 3. How do I use it? Before audio is processed, call plc_init() to create an instance of the packet loss concealer. For each received audio packet that is acceptable (i.e. not including those being dropped for being too late) call plc_rx() to record the content of the packet. Note this may modify the packet a little after a period of packet loss, to blend real synthetic data smoothly. When a real packet is not available in time, call plc_fillin() to create a sythetic substitute. That's it! */ /*! Minimum allowed pitch (66 Hz) */ #define PLC_PITCH_MIN(SAMPLE_RATE) ((double)(SAMPLE_RATE) / 66.6) /*! Maximum allowed pitch (200 Hz) */ #define PLC_PITCH_MAX(SAMPLE_RATE) ((SAMPLE_RATE) / 200) /*! Maximum pitch OLA window */ //#define PLC_PITCH_OVERLAP_MAX(SAMPLE_RATE) ((PLC_PITCH_MIN(SAMPLE_RATE)) >> 2) /*! The length over which the AMDF function looks for similarity (20 ms) */ #define CORRELATION_SPAN(SAMPLE_RATE) ((20 * (SAMPLE_RATE)) / 1000) /*! History buffer length. The buffer must also be at leat 1.25 times PLC_PITCH_MIN, but that is much smaller than the buffer needs to be for the pitch assessment. */ //#define PLC_HISTORY_LEN(SAMPLE_RATE) ((CORRELATION_SPAN(SAMPLE_RATE)) + (PLC_PITCH_MIN(SAMPLE_RATE))) namespace audio { typedef struct { /*! Consecutive erased samples */ int missing_samples; /*! Current offset into pitch period */ int pitch_offset; /*! Pitch estimate */ int pitch; /*! Buffer for a cycle of speech */ float *pitchbuf;//[PLC_PITCH_MIN]; /*! History buffer */ short *history;//[PLC_HISTORY_LEN]; /*! Current pointer into the history buffer */ int buf_ptr; } plc_state_t; class PcmConcealer { public: PcmConcealer(); ~PcmConcealer(); void Init(int channels, int bit_depth, int sample_rate); //Process a block of received audio samples. int Receive(short amp[], int frames); //Fill-in a block of missing audio samples. int Fill(short amp[], int frames); void Destroy(); private: int amdf_pitch(int min_pitch, int max_pitch, short amp[], int channel_index, int frames); void save_history(plc_state_t *s, short *buf, int channel_index, int frames); void normalise_history(plc_state_t *s); /** Holds the states of each of the channels **/ std::vector< plc_state_t * > ChannelStates; int plc_pitch_min; int plc_pitch_max; int plc_pitch_overlap_max; int correlation_span; int plc_history_len; int channel_count; int sample_rate; bool Initialized; }; } #endif PcmConcealer.cpp /* * Code adapted from Steve Underwood of the Asterisk Project. This code inherits * the same licensing restrictions as the Asterisk Project. */ #include "audio/PcmConcealer.hpp" /* We do a straight line fade to zero volume in 50ms when we are filling in for missing data. */ #define ATTENUATION_INCREMENT 0.0025 /* Attenuation per sample */ #if !defined(INT16_MAX) #define INT16_MAX (32767) #define INT16_MIN (-32767-1) #endif #ifdef WIN32 inline double rint(double x) { return floor(x + 0.5); } #endif inline short fsaturate(double damp) { if (damp > 32767.0) return INT16_MAX; if (damp < -32768.0) return INT16_MIN; return (short)rint(damp); } namespace audio { PcmConcealer::PcmConcealer() : Initialized(false) { } PcmConcealer::~PcmConcealer() { Destroy(); } void PcmConcealer::Init(int channels, int bit_depth, int sample_rate) { if(Initialized) return; if(channels <= 0 || bit_depth != 16) return; Initialized = true; channel_count = channels; this->sample_rate = sample_rate; ////////////// double min = PLC_PITCH_MIN(sample_rate); int imin = (int)min; double max = PLC_PITCH_MAX(sample_rate); int imax = (int)max; plc_pitch_min = imin; plc_pitch_max = imax; plc_pitch_overlap_max = (plc_pitch_min >> 2); correlation_span = CORRELATION_SPAN(sample_rate); plc_history_len = correlation_span + plc_pitch_min; ////////////// for(int i = 0; i < channel_count; i ++) { plc_state_t *t = new plc_state_t; memset(t, 0, sizeof(plc_state_t)); t->pitchbuf = new float[plc_pitch_min]; t->history = new short[plc_history_len]; ChannelStates.push_back(t); } } void PcmConcealer::Destroy() { if(!Initialized) return; while(ChannelStates.size()) { plc_state_t *s = ChannelStates.at(0); if(s) { if(s->history) delete s->history; if(s->pitchbuf) delete s->pitchbuf; memset(s, 0, sizeof(plc_state_t)); delete s; } ChannelStates.erase(ChannelStates.begin()); } ChannelStates.clear(); Initialized = false; } //Process a block of received audio samples. int PcmConcealer::Receive(short amp[], int frames) { if(!Initialized) return 0; int j = 0; for(int k = 0; k < ChannelStates.size(); k++) { int i; int overlap_len; int pitch_overlap; float old_step; float new_step; float old_weight; float new_weight; float gain; plc_state_t *s = ChannelStates.at(k); if (s->missing_samples) { /* Although we have a real signal, we need to smooth it to fit well with the synthetic signal we used for the previous block */ /* The start of the real data is overlapped with the next 1/4 cycle of the synthetic data. */ pitch_overlap = s->pitch >> 2; if (pitch_overlap > frames) pitch_overlap = frames; gain = 1.0 - s->missing_samples * ATTENUATION_INCREMENT; if (gain < 0.0) gain = 0.0; new_step = 1.0/pitch_overlap; old_step = new_step*gain; new_weight = new_step; old_weight = (1.0 - new_step)*gain; for (i = 0; i < pitch_overlap; i++) { int index = (i * channel_count) + j; amp[index] = fsaturate(old_weight * s->pitchbuf[s->pitch_offset] + new_weight * amp[index]); if (++s->pitch_offset >= s->pitch) s->pitch_offset = 0; new_weight += new_step; old_weight -= old_step; if (old_weight < 0.0) old_weight = 0.0; } s->missing_samples = 0; } save_history(s, amp, j, frames); j++; } return frames; } //Fill-in a block of missing audio samples. int PcmConcealer::Fill(short amp[], int frames) { if(!Initialized) return 0; int j =0; for(int k = 0; k < ChannelStates.size(); k++) { short *tmp = new short[plc_pitch_overlap_max]; int i; int pitch_overlap; float old_step; float new_step; float old_weight; float new_weight; float gain; short *orig_amp; int orig_len; orig_amp = amp; orig_len = frames; plc_state_t *s = ChannelStates.at(k); if (s->missing_samples == 0) { // As the gap in real speech starts we need to assess the last known pitch, //and prepare the synthetic data we will use for fill-in normalise_history(s); s->pitch = amdf_pitch(plc_pitch_min, plc_pitch_max, s->history + plc_history_len - correlation_span - plc_pitch_min, j, correlation_span); // We overlap a 1/4 wavelength pitch_overlap = s->pitch >> 2; // Cook up a single cycle of pitch, using a single of the real signal with 1/4 //cycle OLA'ed to make the ends join up nicely // The first 3/4 of the cycle is a simple copy for (i = 0; i < s->pitch - pitch_overlap; i++) s->pitchbuf[i] = s->history[plc_history_len - s->pitch + i]; // The last 1/4 of the cycle is overlapped with the end of the previous cycle new_step = 1.0/pitch_overlap; new_weight = new_step; for ( ; i < s->pitch; i++) { s->pitchbuf[i] = s->history[plc_history_len - s->pitch + i]*(1.0 - new_weight) + s->history[plc_history_len - 2*s->pitch + i]*new_weight; new_weight += new_step; } // We should now be ready to fill in the gap with repeated, decaying cycles // of what is in pitchbuf // We need to OLA the first 1/4 wavelength of the synthetic data, to smooth // it into the previous real data. To avoid the need to introduce a delay // in the stream, reverse the last 1/4 wavelength, and OLA with that. gain = 1.0; new_step = 1.0/pitch_overlap; old_step = new_step; new_weight = new_step; old_weight = 1.0 - new_step; for (i = 0; i < pitch_overlap; i++) { int index = (i * channel_count) + j; amp[index] = fsaturate(old_weight * s->history[plc_history_len - 1 - i] + new_weight * s->pitchbuf[i]); new_weight += new_step; old_weight -= old_step; if (old_weight < 0.0) old_weight = 0.0; } s->pitch_offset = i; } else { gain = 1.0 - s->missing_samples*ATTENUATION_INCREMENT; i = 0; } for ( ; gain > 0.0 && i < frames; i++) { int index = (i * channel_count) + j; amp[index] = s->pitchbuf[s->pitch_offset]*gain; gain -= ATTENUATION_INCREMENT; if (++s->pitch_offset >= s->pitch) s->pitch_offset = 0; } for ( ; i < frames; i++) { int index = (i * channel_count) + j; amp[i] = 0; } s->missing_samples += orig_len; save_history(s, amp, j, frames); delete [] tmp; j++; } return frames; } void PcmConcealer::save_history(plc_state_t *s, short *buf, int channel_index, int frames) { if (frames >= plc_history_len) { /* Just keep the last part of the new data, starting at the beginning of the buffer */ //memcpy(s->history, buf + len - plc_history_len, sizeof(short)*plc_history_len); int frames_to_copy = plc_history_len; for(int i = 0; i < frames_to_copy; i ++) { int index = (channel_count * (i + frames - plc_history_len)) + channel_index; s->history[i] = buf[index]; } s->buf_ptr = 0; return; } if (s->buf_ptr + frames > plc_history_len) { /* Wraps around - must break into two sections */ //memcpy(s->history + s->buf_ptr, buf, sizeof(short)*(plc_history_len - s->buf_ptr)); short *hist_ptr = s->history + s->buf_ptr; int frames_to_copy = plc_history_len - s->buf_ptr; for(int i = 0; i < frames_to_copy; i ++) { int index = (channel_count * i) + channel_index; hist_ptr[i] = buf[index]; } frames -= (plc_history_len - s->buf_ptr); //memcpy(s->history, buf + (plc_history_len - s->buf_ptr), sizeof(short)*len); frames_to_copy = frames; for(int i = 0; i < frames_to_copy; i ++) { int index = (channel_count * (i + (plc_history_len - s->buf_ptr))) + channel_index; s->history[i] = buf[index]; } s->buf_ptr = frames; return; } /* Can use just one section */ //memcpy(s->history + s->buf_ptr, buf, sizeof(short)*len); short *hist_ptr = s->history + s->buf_ptr; int frames_to_copy = frames; for(int i = 0; i < frames_to_copy; i ++) { int index = (channel_count * i) + channel_index; hist_ptr[i] = buf[index]; } s->buf_ptr += frames; } void PcmConcealer::normalise_history(plc_state_t *s) { short *tmp = new short[plc_history_len]; if (s->buf_ptr == 0) return; memcpy(tmp, s->history, sizeof(short)*s->buf_ptr); memcpy(s->history, s->history + s->buf_ptr, sizeof(short)*(plc_history_len - s->buf_ptr)); memcpy(s->history + plc_history_len - s->buf_ptr, tmp, sizeof(short)*s->buf_ptr); s->buf_ptr = 0; delete [] tmp; } int PcmConcealer::amdf_pitch(int min_pitch, int max_pitch, short amp[], int channel_index, int frames) { int i; int j; int acc; int min_acc; int pitch; pitch = min_pitch; min_acc = INT_MAX; for (i = max_pitch; i <= min_pitch; i++) { acc = 0; for (j = 0; j < frames; j++) { int index1 = (channel_count * (i+j)) + channel_index; int index2 = (channel_count * j) + channel_index; //std::cout << "Index 1: " << index1 << ", Index 2: " << index2 << std::endl; acc += abs(amp[index1] - amp[index2]); } if (acc < min_acc) { min_acc = acc; pitch = i; } } std::cout << "Pitch: " << pitch << std::endl; return pitch; } } P.S. - I must confess that digital audio is not my forte...

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  • Find max integer size that a floating point type can handle without loss of precision

    - by Checkers
    Double has range more than a 64-bit integer, but its precision is less dues to its representation (since double is 64-bit as well, it can't fit more actual values). So, when representing larger integers, you start to lose precision in the integer part. #include <boost/cstdint.hpp> #include <limits> template<typename T, typename TFloat> void maxint_to_double() { T i = std::numeric_limits<T>::max(); TFloat d = i; std::cout << std::fixed << i << std::endl << d << std::endl; } int main() { maxint_to_double<int, double>(); maxint_to_double<boost::intmax_t, double>(); maxint_to_double<int, float>(); return 0; } This prints: 2147483647 2147483647.000000 9223372036854775807 9223372036854775800.000000 2147483647 2147483648.000000 Note how max int can fit into a double without loss of precision and boost::intmax_t (64-bit in this case) cannot. float can't even hold an int. Now, the question: is there a way in C++ to check if the entire range of a given integer type can fit into a loating point type without loss of precision? Preferably, it would be a compile-time check that can be used in a static assertion, and would not involve enumerating the constants the compiler should know or can compute.

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  • Data Structures for Logic Games / Deduction Rules / Sufficient Set of Clues?

    - by taserian
    I've been cogitating about developing a logic game similar to Einstein's Puzzle , which would have different sets of clues for every new game replay. What data structures would you use to handle the different entities (pets, colors of houses, nationalities, etc.), deduction rules, etc. to guarantee that the clues you provide point to a unique solution? I'm having a hard time thinking about how to get the deduction rules to play along with the possible clues; any insight would be appreciated.

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  • How do we keep dependent data structures up to date?

    - by Geo
    Suppose you have a parse tree, an abstract syntax tree, and a control flow graph, each one logically derived from the one before. In principle it is easy to construct each graph given the parse tree, but how can we manage the complexity of updating the graphs when the parse tree is modified? We know exactly how the tree has been modified, but how can the change be propagated to the other trees in a way that doesn't become difficult to manage? Naturally the dependent graph can be updated by simply reconstructing it from scratch every time the first graph changes, but then there would be no way of knowing the details of the changes in the dependent graph. I currently have four ways to attempt to solve this problem, but each one has difficulties. Nodes of the dependent tree each observe the relevant nodes of the original tree, updating themselves and the observer lists of original tree nodes as necessary. The conceptual complexity of this can become daunting. Each node of the original tree has a list of the dependent tree nodes that specifically depend upon it, and when the node changes it sets a flag on the dependent nodes to mark them as dirty, including the parents of the dependent nodes all the way down to the root. After each change we run an algorithm that is much like the algorithm for constructing the dependent graph from scratch, but it skips over any clean node and reconstructs each dirty node, keeping track of whether the reconstructed node is actually different from the dirty node. This can also get tricky. We can represent the logical connection between the original graph and the dependent graph as a data structure, like a list of constraints, perhaps designed using a declarative language. When the original graph changes we need only scan the list to discover which constraints are violated and how the dependent tree needs to change to correct the violation, all encoded as data. We can reconstruct the dependent graph from scratch as though there were no existing dependent graph, and then compare the existing graph and the new graph to discover how it has changed. I'm sure this is the easiest way because I know there are algorithms available for detecting differences, but they are all quite computationally expensive and in principle it seems unnecessary so I'm deliberately avoiding this option. What is the right way to deal with these sorts of problems? Surely there must be a design pattern that makes this whole thing almost easy. It would be nice to have a good solution for every problem of this general description. Does this class of problem have a name?

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  • Data structures for a 2D multi-layered and multi-region map?

    - by DevilWithin
    I am working on a 2D world editor and a world format subsequently. If I were to handle the game "world" being created just as a layered set of structures, either in top or side views, it would be considerably simple to do most things. But, since this editor is meant for 3rd parties, I have no clue how big worlds one will want to make and I need to keep in mind that eventually it will become simply too much to check, handling and comparing stuff that are happening completely away from the player position. I know the solution for this is to subdivide my world into sub regions and stream them on the fly, loading and unloading resources and other data. This way I know a virtually infinite game area is achievable. But, while I know theoretically what to do, I really have a few questions I'd hoped to get answered for some hints about the topic. The logic way to handle the regions is some kind of grid, would you pick evenly distributed blocks with equal sizes or would you let the user subdivide areas by taste with irregular sized rectangles? In case of even grids, would you use some kind of block/chunk neighbouring system to check when the player transposes the limit or just put all those in a simple array? Being a region a different data structure than its owner "game world", when streaming a region, would you deliver the objects to the parent structures and track them for unloading later, or retain the objects in each region for a more "hard-limit" approach? Introducing the subdivision approach to the project, and already having a multi layered scene graph structure on place, how would i make it support the new concept? Would you have the parent node have the layers as children, and replicate in each layer node, a node per region? Or the opposite, parent node owns all the regions possible, and each region has multiple layers as children? Or would you just put the region logic outside the graph completely(compatible with the first suggestion in Q.3) When I say virtually infinite worlds, I mean it of course under the contraints of the variable sizes and so on. Using float positions, a HUGE world can already be made. Do you think its sane to think beyond that? Because I think its ok to stick to this limit since it will never be reached so easily.. As for when to stream a region, I'm implementing it as a collection of watcher cameras, which the streaming system works with to know what to load/unload. The problem here is, i will be needing some kind of warps/teleports built in for my game, and there is a chance i will be teleporting a player to a unloaded region far away. How would you approach something like this? Is it sane to load any region to memory which can be teleported to by a warp within a radius from the player? Sorry for the huge question, any answers are helpful!

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  • Move Data into the Grid for Scalable, Predictable Response Times

    - by JuergenKress
    CloudTran is pleased to introduce the availability of the CloudTran Transaction and Persistence Manager for creating scalable, reliable data services on the Oracle Coherence In-Memory Data Grid (IMDG). Use of IMDG architectures has been key to handling today’s web-scale loads because it eliminates database latency by storing important and frequently access data in memory instead of on disk. The CloudTran product lets developers easily use an IMDG for full ACID-compliant transactions without having to be concerned about the location or spread of data. The system has its own implementation of fast, scalable distributed transactions that does NOT depend on XA protocols but still guarantees all ACID properties. Plus, CloudTran asynchronously replicates data going into the IMDG to back-end datastores and back-up data centers, again ensuring ACID properties. CloudTran can be accessed through Java Persistence API (JPA via TopLink Grid) and now, through a new Low-Level API, or LLAPI. This is ideal for use in SOA applications that need data reliability, high availability, performance, and scalability. Still in limited beta release, the LLAPI gives developers the ability to use standard put/remove logic available in Coherence and then wrap logic with simple Spring annotations or XML+AspectJ to start transactions. An important feature of LLAPI is the ability to join transactions. This is a common outcome for SOA applications that need to reduce network traffic by aggregating data into single cache entries and then doing SOA service processing in the node holding the data. This results in the need to orchestrate transaction processing across multiple service calls. CloudTran has the capability to handle these “multi-client” transactions at speed with no loss in ACID properties. Developing software around an IMDG like Oracle Coherence is an important choice for today’s web-scale applications and services. But this introduces new architectural considerations to maintain scalability in light of increased network loads and data movement. Without using CloudTran, developers are faced with an incredibly difficult task to ensure data reliability, availability, performance, and scalability when working with an IMDG. Working with highly distributed data that is entirely volatile while stored in memory presents numerous edge cases where failures can result in data loss. The CloudTran product takes care of all of this, leaving developers with the confidence and peace of mind that all data is processed correctly. For those interested in evaluating the CloudTran product and IMDGs, take a look at this link for more information: http://www.CloudTran.com/downloadAPI.php, or, send your questions to [email protected]. WebLogic Partner Community For regular information become a member in the WebLogic Partner Community please visit: http://www.oracle.com/partners/goto/wls-emea ( OPN account required). If you need support with your account please contact the Oracle Partner Business Center. BlogTwitterLinkedInMixForumWiki Technorati Tags: Coherence,cloudtran,cache,WebLogic Community,Oracle,OPN,Jürgen Kress

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