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• Whats after the iPAD?? check out the new Augmented Reality Glasses

  - by Stephen Slade

  Everyone loves their new iPad! The rich features, portability, plethora of apps and ease of use make this the new clipboard on the factory floor or electronic notebook for meetings. But how many business people walk into an hours meeting and really start typing notes on their PC?..yes some do, but for the general business public there are new technologies coming down the road. The iPad is the latest holla-hoop; and the next gen device I feel is the Augmented Reality Glasses. Your glasses will be your screen, have an earpiece, be wireless enabled, your smart watch be your electronics and maybe your belt can be an extended battery pack.  I'm anxious to test one of these. The TELEGRAPH writes:  "Android software is believed to power the gadget, enabling similar features to its smartphone and tablets. A 3G /4G data connection, motion sensors and GPS navigation are believed to be included in the device's capabilities. The augmented-reality glasses are the culmination of a two-year initiative called Project Glass, developed in the clandestine Google X lab, ..in Mountain View, ...The New York Times suggested they could cost between $250-$500 " http://www.telegraph.co.uk/technology/news/9187547/Google-unveils-augmented-reality-glasses.html

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• View Link inConsistency

  - by Abhishek Dwivedi

  What is View Link Consistency? When multiple instances (say VO1, VO2, VO3 etc) of an EO-based VO are based on the same underlying EO, a new row created in one of these VO instances (say VO1)can be automatically added (without re-query) to the row sets of the others (VO2, VO3 etc ). This capability is known as the view link consistency. This feature works for any VO for which it is enabled, regardless of whether they are involved in a view link or not. What causes View Link inConsistency? Unless jbo.viewlink.consistent  is disabled for this VO (or globally), or setAssociationConsistent(false) is applied, any of the following can cause View Link inConsistency.  1. setWhereClause 2. Unreferenced secondary EO 3. findByViewCriteria() 4. Using view link accessor row set Why does this happen - View Link inConsistency? Well, there can be one of the following reasons. a. In case of 1 & 2, the view link consistency flag is disabled on that view object. b. As far as 3 is concerned, findByViewCriteria is used to retrieve a new row set to process programmatically without changing the contents of the default row set. In this case, unlike previous cases, the view link consistency flag is not disabled, meaning that the changes in the default row set would be reflected in the new row set.  However, the opposite doesn't hold true. For instance, if a row is deleted from this new row set, the corresponding row in the default row set does not get deleted. In one of my features, which involved deletion of row(s), I resolved the view link inconsistency issue by replacing findByViewCriteria by applyViewCriteria. b. For 4, it's similar to 3 - whenever a view link accessor row set is retrieved, a new row set is created. Now, creating new row set does not mean re-executing the query each time, only creating a new instance of a RowSet object with its default iterator reset to the "slot" before the first row. Also, please note that this new row set always originates from an internally created view object instance, not one you that added to the data model. This internal view object instance is created as needed and added with a system-defined name to the root application module. Anyway, the very reason a distinct, internally-created view object instance is used is to guarantee that it remains unaffected by developer-related changes to their own view objects instances in the data model.

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• Workshop in Denver canceled - thanks to hurricane Isaac

  - by Mike Dietrich

  Yesterday Roy did start his journey on time to travel to Denver, CO for today's Upgrade and Migration Workshop.  But unfortunately due to the remnants of  hurricane Issac moving up the East Coast and scrambling up flight schedules Roy's flight from NYC to Denver got canceled after a 3 hour delay leaving Manchester, NH, and there was no option to arrive in Denver this morning on time. So we apologize for canceling that workshop. The local marketing department will contact you regarding an alternative date. Sorry for any inconvenience!

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• Access-based Enumeration (December 04, 2009)

  - by user12612012

  Access-based Enumeration (ABE) is another recent addition to the Solaris CIFS Service - delivered into snv_124.  Designed to be compatible with Windows ABE, which was introduced in Windows Server 2003 SP1, this feature filters directory content based on the user browsing the directory.  Each user can only see the files and directories to which they have access.  This can be useful to implement an out-of-sight, out-of-mind policy or simply to reduce the number of files presented to each user - to make it easier to find files in directories containing a large number of files. ABE is managed on a per share basis by a new boolean share property called, as you might imagine, abe, which is described insharemgr(1M).  When set to true, ABE filtering is enabled on the share and directory entries to which the user has no access will be omitted from directory listings returned to the client.  When set to false or not defined, ABE filtering will not be performed on the share.  The abe property is not defined by default.Administration is straightforward, for example: # zfs sharesmb=abe=true,name=jane tank/home/jane# sharemgr show -vp    zfs       zfs/tank/home/jane nfs=() smb=()          jane=/export/home/jane     smb=(abe="true") ABE is also supported via sharemgr(1M) and on smbautohome(4) shares. Note that even though a file is visible in a share, with ABE enabled, it doesn't automatically mean that the user will always be able to open the file.  If a user has read attribute access to a file ABE will show the it but access will be denied if this user tries to open the file for reading or writing. We considered supporting ABE on NFS shares, as suggested by the name of PSARC/2009/375, but we ran into problems due to NFS client readdir caching.  NFS clients maintain a common directory entry cache for all users, which not only defeats the intent of ABE but can lead to very confusing results.  If multiple users are looking at the content of a directory with ABE enabled, the entries that get cached will depend on who looks at the directory first.  Subsequent users may see files that ABE on the server would have filtered out or files may be missing because they were filtered out for the original user. Although this issue can be resolved by disabling the NFS client readdir cache, this was deemed to be an unsuitable solution because it would create a dependency between a server share property and the configuration on all NFS clients, and there was the potential for differences in behavior across the various NFS clients.  It just seemed to add unnecessary administration complexity so we pulled it out. References for more information PSARC/2009/246 ZFS support for Access Based Enumeration PSARC/2009/375 ABE share property for NFS and SMB 6802734 Support for Access Based Enumeration 6802736 SMB share support for Access Based Enumeration Windows Access-based Enumeration

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• JavaOne Latin America 2012 Trip Report

  - by reza_rahman

  JavaOne Latin America 2012 was held at the Transamerica Expo Center in Sao Paulo, Brazil on December 4-6. The conference was a resounding success with a great vibe, excellent technical content and numerous world class speakers. Some notable local and international speakers included Bruno Souza, Yara Senger, Mattias Karlsson, Vinicius Senger, Heather Vancura, Tori Wieldt, Arun Gupta, Jim Weaver, Stephen Chin, Simon Ritter and Henrik Stahl. Topics covered included the JCP/JUGs, Java SE 7, HTML 5/WebSocket, CDI, Java EE 6, Java EE 7, JSF 2.2, JMS 2, JAX-RS 2, Arquillian and JavaFX. Bruno Borges and I manned the GlassFish booth at the Java Pavilion on Tuesday and Webnesday. The booth traffic was decent and not too hectic. We met a number of GlassFish adopters including perhaps one of the largest GlassFish deployments in Brazil as well as some folks migrating to Java EE from Spring. We invited them to share their stories with us. We also talked with some key members of the local Java community. Tuesday evening we had the GlassFish party at the Tribeca Pub. The party was definitely a hit and we could have used a larger venue (this was the first time we had the GlassFish party in Brazil). Along with GlassFish enthusiasts, a number of Java community leaders were there. We met some of the same folks again at the JUG leader's party on Wednesday evening. On Thursday Arun Gupta, Bruno Borges and I ran a hands-on-lab on JAX-RS, WebSocket and Server-Sent Events (SSE) titled "Developing JAX-RS Web Applications Utilizing Server-Sent Events and WebSocket". This is the same Java EE 7 lab run at JavaOne San Francisco. The lab provides developers a first hand glipse of how an HTML 5 powered Java EE application might look like. We had an overflow crowd for the lab (at one point we had about twenty people standing) and the lab went very well. The slides for the lab are here: Developing JAX-RS Web Applications Utilizing Server-Sent Events and WebSocket from Reza Rahman The actual contents for the lab is available here. Give me a shout if you need help getting it up and running. I gave two solo talks following the lab. The first was on JMS 2 titled "What’s New in Java Message Service 2". This was essentially the same talk given by JMS 2 specification lead Nigel Deakin at JavaOne San Francisco. I talked about the JMS 2 simplified API, JMSContext injection, delivery delays, asynchronous send, JMS resource definition in Java EE 7, standardized configuration for JMS MDBs in EJB 3.2, mandatory JCA pluggability and the like. The session went very well, there was good Q & A and someone even told me this was the best session of the conference! The slides for the talk are here: What’s New in Java Message Service 2 from Reza Rahman My last talk for the conference was on JAX-RS 2 in the keynote hall. Titled "JAX-RS 2: New and Noteworthy in the RESTful Web Services API" this was basically the same talk given by the specification leads Santiago Pericas-Geertsen and Marek Potociar at JavaOne San Francisco. I talked about the JAX-RS 2 client API, asyncronous processing, filters/interceptors, hypermedia support, server-side content negotiation and the like. The talk went very well and I got a few very kind complements afterwards. The slides for the talk are here: JAX-RS 2: New and Noteworthy in the RESTful Web Services API from Reza Rahman On a more personal note, Sao Paulo has always had a special place in my heart as the incubating city for Sepultura and Soulfy -- two of my most favorite heavy metal musical groups of all time! Consequently, the city has a perpertually alive and kicking metal scene pretty much any given day of the week. This time I got to check out a solid performance by local metal gig Republica at the legendary Manifesto Bar. I also wanted to see a Dio Tribute at the Blackmore but ran out of time and energy... Overall I enjoyed the conference/Sao Paulo and look forward to going to Brazil again next year!

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• New Cloud Security Book: Securing the Cloud by Vic Winkler

  - by user12608550

  It's rare that I read a technical book straight through; I usually read key chapters and save the rest for later reference. But Winkler's book, written by an accomplished and highly experienced security professional, was worth a complete read, cover to cover. Of the recently published cloud security books, such as... Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance, by Tim Mather, Subra Kumaraswamy, and Shahed Latif; O'Reilly Media Inc, 2009; Cloud Computing: Implementation, Management, and Security, by John Rittenhouse and James Ransome; CRC Press 2010; Cloud Security: A Comprehensive Guide to Secure Cloud Computing, by Ronald Krutz and Russell Vines; Wiley Publishing Inc, 2010 ...Securing the Cloud is the most useful and informative about all aspects of cloud security. Clearly, through his experience, the author has thought through many practical issues of securing large, virtualized IT installations. His Chapter 6 on Best Practices and Chapter 9 with its valuable checklists are worth the price of the book. If you are among the many new cloud computing professionals, Securing the Cloud is an essential reference for your work.

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• What's Old is New Again

  - by David Dorf

  Last night I told my son he could stream music to his tablet "from the cloud" (in this case, the Amazon Cloud).  He paused, then said, "what is the cloud?"  I replied, "a bunch of servers connected to the internet."  Apparently he had visions of something much more magnificent.  Another similar term is "big data."  These marketing terms help to quickly convey topics but are oversimplifications that are open to many interpretations.  At their core, those terms a shiny packages holding recycled ideas. I see many headlines declaring big data changes everything, but it doesn't.  Savvy retailers have been dealing with large volumes of data since the electronic cash register was invented.  But the there have a been a few changes to the landscape that make big data a topic of conversation: 1. Computing power has caught up to storage volumes. Its now possible to more thoroughly analyze the copious volumes of data retailers have been squirreling away.  CPUs are faster, sold state drives more plentiful, and new ways to store and search data are available.  My iPhone is more power than the computer used in the Apollo mission to the moon. 2. Unstructured data is everywhere.  The Web used to be where retailers published product information, but now users are generating the bulk of the content in the form of comments, videos, and "likes."  The variety of information available to retailers is huge, and it meaning difficult to discern. 3. Everything is connected.  Looking at a report from my router, there are no less than 20 active devices on my home network.  We can track the location of mobile phones, tag products with RFID, and set our thermostats (I love my Nest) from a thousand miles away.  Not only is there more data, but its arriving at higher velocity. Careful readers will note the three Vs that help define so-called big data: volume, variety, and velocity. We now have more volume, more variety, and more velocity and different technologies to deal with them.  But at the heart, the objectives are still the same: Informed decisions Accurate forecasts Improved optimizations So don't let the term "big data" throw you off the scent.  Retailers still need to execute on the basics.  But do take a fresh look at the data that's available and the new technologies to process it.  The landscape will continue to change and agile organizations will always be reevaluating their approaches.  You can just add some more weapons to the arsenal.

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• Creating Custom validation rule and register it

  - by FormsEleven

  What is Validation Rule? A validation rule is a piece of code that performs some check ensuring that data meets given constraints.In an enterprise application development environment, often it might require developers to have validation be performed based on some logic at several places across projects. Instead of redundant validation creation, a custom validation rule provides a library with a validation rules that can be registered and used across applications.A custom Validation is encapsulated in a reusable component so that you do not have to write it every time when you need to do input validation. Here is how we can easily implement a custom validation that checks for name of an employee to be "KING" For creating a custom Validation , 1.         Create Generic Application Workspace "CustomValidator" with the project "Model" 2.         Create an BC4J based on emp table. 3.         Create a custom validation rule.In EmpNamerule class, update the validateValue(..) method as follows:  public boolean validateValue(Object value) { EntityImpl emp = (EntityImpl)value; if(emp.getAttribute("Ename").toString().equals("KING")){ return false; } return true; } Create ADF Library: Next step would be to create ADF library. Create ADF library with name lets say testADFLibrary1.jarRegister ADF Library Next step is to register the ADF library , so that its available across the applications. Invoke the menu "Tools -> Preferences"Select the option "Business Components -> Registered Rules" from left paneClick on button "Pick Library". The dialog "Select Library" comes up with  the user library addedAdd new library' that points to the above jarCheck the checkbox "Register" and set the name for the rule Sample UsageHere is how we can easily implement a validation rule that restrict the name of the employee not to be "KING".Create new Application with BC4J based on EMP table.Create new validation under Business rule tab for Ename & select the above custom validation rule.Run the AppModule tester.

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• Why Ultra-Low Power Computing Will Change Everything

  - by Tori Wieldt

  The ARM TechCon keynote "Why Ultra-Low Power Computing Will Change Everything" was anything but low-powered. The speaker, Dr. Johnathan Koomey, knows his subject: he is a Consulting Professor at Stanford University, worked for more than two decades at Lawrence Berkeley National Laboratory, and has been a visiting professor at Stanford University, Yale University, and UC Berkeley's Energy and Resources Group. His current focus is creating a standard (computations per kilowatt hour) and measuring computer energy consumption over time. The trends are impressive: energy consumption has halved every 1.5 years for the last 60 years. Battery life has made roughly a 10x improvement each decade since 1960. It's these improvements that have made laptops and cell phones possible. What does the future hold? Dr. Koomey said that in the past, the race by chip manufacturers was to create the fastest computer, but the priorities have now changed. New computers are tiny, smart, connected and cheap. "You can't underestimate the importance of a shift in industry focus from raw performance to power efficiency for mobile devices," he said. There is also a confluence of trends in computing, communications, sensors, and controls. The challenge is how to reduce the power requirements for these tiny devices. Alternate sources of power that are being explored are light, heat, motion, and even blood sugar. The University of Michigan has produced a miniature sensor that harnesses solar energy and could last for years without needing to be replaced. Also, the University of Washington has created a sensor that scavenges power from existing radio and TV signals.Specific devices designed for a purpose are much more efficient than general purpose computers. With all these sensors, instead of big data, developers should focus on nano-data, personalized information that will adjust the lights in a room, a machine, a variable sign, etc.Dr. Koomey showed some examples:The Proteus Digital Health Feedback System, an ingestible sensor that transmits when a patient has taken their medicine and is powered by their stomach juices. (Gives "powered by you" a whole new meaning!) Streetline Parking Systems, that provide real-time data about available parking spaces. The information can be sent to your phone or update parking signs around the city to point to areas with available spaces. Less driving around looking for parking spaces!The BigBelly trash system that uses solar power, compacts trash, and sends a text message when it is full. This dramatically reduces the number of times a truck has to come to pick up trash, freeing up resources and slashing fuel costs. This is a classic example of the efficiency of moving "bits not atoms." But researchers are approaching the physical limits of sensors, Dr. Kommey explained. With the current rate of technology improvement, they'll reach the three-atom transistor by 2041. Once they hit that wall, it will force a revolution they way we do computing. But wait, researchers at Purdue University and the University of New South Wales are both working on a reliable one-atom transistors! Other researchers are working on "approximate computing" that will reduce computing requirements drastically. So it's unclear where the wall actually is. In the meantime, as Dr. Koomey promised, ultra-low power computing will change everything.

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• CRM vs VRM

  - by David Dorf

  In a previous post, I discussed the potential power of combining social, interest, and location graphs in order to personalize marketing and shopping experiences for consumers.  Marketing companies have been trying to collect detailed information for that very purpose, a large majority of which comes from tracking people on the internet.  But their approaches stem from the one-way nature of traditional advertising.  With TV, radio, and magazines there is no opportunity to truly connect to customers, which has trained marketing companies to [covertly] collect data and segment customers into easily identifiable groups.  To a large extent, we think of this as CRM. But what if we turned this viewpoint upside-down to accommodate for the two-way nature of social media?  The notion of marketing as conversations was the basis for the Cluetrain, an early attempt at drawing attention to the fact that customers are actually unique humans.  A more practical implementation is Project VRM, which is a reverse CRM of sorts.  Instead of vendors managing their relationships with customers, customers manage their relationships with vendors. Your shopping experience is not really controlled by you; rather, its controlled by the retailer and advertisers.  And unfortunately, they typically don't give you a say in the matter.  Yes, they might tailor the content for "female age 25-35 interested in shoes" but that's not really the essence of you, is it?  A better approach is to the let consumers volunteer information about themselves.  And why wouldn't they if it means a better, more relevant shopping experience?  I'd gladly list out my likes and dislikes in exchange for getting rid of all those annoying cookies on my harddrive. I really like this diagram from Beyond SocialCRM as it captures the differences between CRM and VRM. The closest thing to VRM I can find is Buyosphere, a start-up that allows consumers to track their shopping history across many vendors, then share it appropriately.  Also, Amazon does a pretty good job allowing its customers to edit their profile, which includes everything you've ever purchased from Amazon.  You can mark items as gifts, or explicitly exclude them from their recommendation engine.  This is a win-win for both the consumer and retailer. So here is my plea to retailers: Instead of trying to infer my interests from snapshots of my day, please just ask me.  We'll both have a better experience in the long-run.

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• CRM Evolution 2014: Mediocrity is the New Horrible in Customer Service

  - by Tuula Fai

  "Mediocrity is the new horrible in customer service," Blair McHaney, Gold's Gym Almost everyone knows that customers' expectations have risen. But, after listening to two days of presentations at CRM Evolution, I think it’s more accurate to say that customers' expectations have skyrocketed. Fortunately, most companies have gotten the message and are taking their customer service to a higher level. For those who've been hesitant to 'boldly go where their customer service organization has not gone before,' take heart. I’ve got some statistics that will encourage you to take those first few steps. Why should I change? By engaging customers online, ancestry.com achieved a 99.5% customer satisfaction score (CSAT) while improving retention and saving millions on greater efficiency, including a 38%-50% drop in inbound calls and emails.1 By empowering employees to delight customers, Gold’s Gym achieved a 77.5% Net Promoter Score (NPS) and 22% customer churn rate. No small feat when you consider the industry averages are 40% NPS and 45% churn.2 By adapting quickly to social media, brands like Verizon have benefited from social community members spending 2.5x-10x more than average customers.3 ‘The fierce urgency of now’ is upon us in customer service. You can take your customer service to a higher level! To find out more, click here CRM Evolution Customer Service Experience Footnotes: 1. Arvindh Balakrishnan, Is Your Customer Service Modern?2. Blair McHaney, Wire Your Organization with Customer Feedback3. Becky Carroll, The Power of Communities for Improving the Service Experience and Building Advocates

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• Sneak Peak: Social Developer Program at JavaOne

  - by Mike Stiles

  By guest blogger Roland Smart We're just days away from what is gunning to be the most exciting installment of OpenWorld to date, so how about an exciting sneak peak at the very first Social Developer Program? If your first thought is, "What's a social developer?" you're not alone. It’s an emerging term and one we think will gain prominence as social experiences become more prevalent in enterprise applications. For those who keep an eye on the ever-evolving Facebook platform, you'll recall that they recently rebranded their PDC (preferred developer consultant) group as the PMD (preferred marketing developer), signaling the importance of development resources inside the marketing organization to unlock the potential of social. The marketing developer they're referring to could be considered a social developer in a broader context. While it's true social has really blossomed in the marketing context and CMOs are winning more and more technical resources, social is starting to work its way more deeply into the enterprise with the help of developers that work outside marketing. Developers, like the rest of us, have fallen in "like" with social functionality and are starting to imagine how social can transform enterprise applications in the way it has consumer-facing experiences. The thesis of my presentation is that social developers will take many pages from the marketing playbook as they apply social inside the enterprise. To support this argument, lets walk through a range of enterprise applications and explore how consumer-facing social experiences might be interpreted in this context. Here's one example of how a social experience could be integrated into a sales enablement application. As a marketer, I spend a great deal of time collaborating with my sales colleagues, so I have good insight into their working process. While at Involver, we grew our sales team quickly, and it became evident some of our processes broke with scale. For example, we used to have weekly team meetings at which we'd discuss what was working and what wasn't from a messaging perspective. One aspect of these sessions focused on "objections" and "responses," where the salespeople would walk through common objections to purchasing and share appropriate responses. We tried to map each context to best answers and we'd capture these on a wiki page. As our team grew, however, participation at scale just wasn't tenable, and our wiki pages quickly lost their freshness. Imagine giving salespeople a place where they could submit common objections and responses for their colleagues to see, sort, comment on, and vote on. What you'd get is an up-to-date and relevant repository of information. And, if you supported an application like this with a social graph, it would be possible to make good recommendations to individual sales people about the objections they'd likely hear based on vertical, product, region or other graph data. Taking it even further, you could build in a badging/game element to reward those salespeople who participate the most. Both these examples are based on proven models at work inside consumer-facing applications. If you want to learn about how HR, Operations, Product Development and Customer Support can leverage social experiences, you’re welcome to join us at JavaOne or join our Social Developer Community to find some of the presentations after OpenWorld.

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• Tyrus 1.8

  - by Pavel Bucek

  Another version of Tyrus, the reference implementation of JSR 356 – Java API for WebSocket is out! Complete list of fixes and features is below, but let me describe some of the new features in more detail. All information presented here is also available in Tyrusdocumentation. What’s new? First to mention is that JSR 356 Maintenance review Ballot is over and the change proposed for 1.1 release was accepted. More details about changes in the API can be found in this article. Important part is that Tyrus 1.8 implements this API, meaning you can use Lambda expressions and some features of Nashorn without the need for any workarounds. Almost all other features are related to client side support, which was significantly improved in this release. Firstly – I have to admit, that Tyrus client contained security issue – SSL Hostname verification was not performed when connecting to “wss” endpoints. This was fixed as part of TYRUS-339 and resulted in some changes in the client configuration API. Now you can control whether HostnameVerification should be performed (SslEngineConfigurator#setHostnameVerificationEnabled(boolean)) or even set your own HostnameVerifier (please use carefully): #setHostnameVerifier(…). Detailed description can be found in Host verification chapter. Another related enhancement is support for Http Basic and Digest authentication schemes. Tyrus client now enables users to provide credentials and underlying implementation will take care of everything else. Our implementation is strictly non pre-emptive, so the login information is sent always as a response to 401 Http Status Code. If the Basic and Digest are not good enough and there is a need to use some custom scheme or something which is not yet supported in Tyrus, custom Authenticator can be registered and the authentication part of the handshake process will be handled by it. Please seeClient HTTP Authentication chapter in the user guide for more details. There are other features, like fine-grain threadpool configuration for JDK client container, build-in Http redirect support and some reshuffling related to unifying the location of client configuration classes and properties definition – every property should be now part of ClientProperties class. All new features are described in the user guide – in chapterTyrus proprietary configuration. Update – Tyrus 1.8.1 There was another slightly late reported issue related to running in environments with SecurityManager enabled, so this version fixes that. Another noteworthy fixes are TYRUS-355 and TYRUS-361; the first one is about incorrect thread factory used for shared container timeout, which resulted in JVM waiting for that thread and not exiting as it should. The other issue enables relative URIs in Location header when using redirect feature. Links Tyrus homepage mailing list JIRA Complete list of changes: Bug [TYRUS-333] – Multiple endpoints on one client [TYRUS-334] – When connection is closed by a peer, periodic heartbeat pong is not stopped [TYRUS-336] – ReaderBuffer.getNextChars() keeps blocking a server thread after client has closed the session [TYRUS-338] – JDK client SSL filter needs better synchronization during handshake phase [TYRUS-339] – SSL hostname verification is missing [TYRUS-340] – Test PathParamTest are not stable with JDK client [TYRUS-341] – A control frame inside a stream of continuation frames is treated as the part of the stream [TYRUS-343] – ControlFrameInDataStreamTest does not pass on GF [TYRUS-345] – NPE is thrown, when shared container timeout property in JDK client is not set [TYRUS-346] – IllegalStateException is thrown, when using proxy in JDK client [TYRUS-347] – Introduce better synchronization in JDK client thread pool [TYRUS-348] – When a client and server close connection simultaneously, JDK client throws NPE [TYRUS-356] – Tyrus cannot determine the connection port for a wss URL [TYRUS-357] – Exception thrown in MessageHandler#OnMessage is not caught in @OnError method [TYRUS-359] – Client based on Java 7 Asynchronous IO makes application unexitable Improvement [TYRUS-328] – JDK 1.7 AIO Client container – threads – (setting threadpool, limits, …) [TYRUS-332] – Consolidate shared client properties into one file. [TYRUS-337] – Create an SSL version of Basic Servlet test New Feature [TYRUS-228] – Add client support for HTTP Basic/Digest Task [TYRUS-330] – create/run tests/servlet/basic via wss [TYRUS-335] – [clustering] – introduce RemoteSession and expose them via separate method (not include remote sessions in the getOpenSessions()) [TYRUS-344] – Introduce Client support for HTTP Redirect

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• Hai mai pensato a quanto ti costa qualificare le tue opportunità commerciali?

  - by user812481

  Il successo delle attività di marketing è dovuto alla profonda conoscenza dei propri clienti: chi sono, cosa acquistano e perché, come preferiscono essere contattati. Se i dati sui clienti sono distribuiti su più sistemi, rispondere a queste domande diventa difficile ed oneroso. Hai bisogno di un mix di strumenti best-in-class per l'automazione della forza di vendita e per l'efficienza delle attività di marketing, facendo confluire i dati chiave in un unico punto di accesso, per una visione a 360 gradi dei clienti. Vorresti incrementare il ROI delle campagne di marketing, proponendo diversi messaggi in funzione dei differenti target, ottenendo così un maggior successo delle iniziative? Scopri come ottenere una conoscenza maggiore del target per creare campagne di successo, mirate e personalizzate, attraverso video in italiano e docuemtni da condividere con i vostri colleghi.

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• Customisation / overriding of the Envelop ecs files

  - by Dheeraj Kumar M

  There are few usecases where the requirement is to customise the envelop information (Interchange/Group ecs file). Such scenarios might be required to be used for only few of the customers. Hence, in addition to the default seeded envelop definitions, it also required to upload the customised definitions. Here is the steps for achieving the same. 1. Create only the Interchange ecs and save 2. Create only the group ecs and save 3. Use the same in B2B 1. Create only the Interchange ecs and save :       Open the document editor and select the required version and doctype. During creating new ecs, ensure to select the checkbox for insert envelop.       Once created, delete the group and transactionset nodes and retain only the Interchange ecs nodes, including both header and trailer. Save this file. 2. Create only the group ecs and save       After creating the ecs file as mentioned in steps of Interchange creation, delete the Interchange and transactionset nodes and retain only the group ecs nodes, including both header and trailer. Save this file. 3. Use the same in B2B       These newly created ecs can be used in B2B by 2 ways.              a. By overriding at the trading partner Level:              This will be very useful when the configuration is complete and then need to incorporate the customisation. In this case, just select the Trading partner - document - select the document which need to be customised.              Upload the newly created Interchange and group ECS files under the Interchange and group tabs respectively and re-deply the associated agreement.              The advantage of this approach is              - Flexibility to add customised envelop definitions to the partners              - Save the re-work of design time effort.              b. By adding another document definition in Administration - document screen:              This scenario can be used if there is no configuration done at the trading partner level. Create the required document revision and overtide the Interchange and group ECS files under the Interchange and group tabs respectively. Add the document in Trading partner - document. Create and deploy the agreements

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• Announcing Upcoming SOA and JMS Introductory Blog Posts

  - by John-Brown.Evans

  Announcing Upcoming SOA and JMS Introductory Blog Posts Beginning next week, SOA Proactive Support will begin posting a series of introductory blogs here on working with JMS in a SOA context. The posts will begin with how to set up JMS in WebLogic server, lead you through reading and writing to a JMS queue from the WLS Java samples, continue with how to access it from a SOA composite and, finally, describe how to set up and access AQ JMS (Advanced Queuing JMS) from a SOA/BPEL process. The posts will be of a tutorial nature and include step-by-step examples. Your questions and feedback are encouraged. The following topics are planned: How to Create a Simple JMS Queue in Weblogic Server 11g Using the QueueSend.java Sample Program to Send a Message to a JMS Queue Using the QueueReceive.java Sample Program to Read a Message from a JMS Queue How to Create an 11g BPEL Process Which Writes a Message Based on an XML Schema to a JMS Queue How to Create an 11g BPEL Process Which Reads a Message Based on an XML Schema from a JMS Queue How to Set Up an AQ JMS (Advanced Queueing JMS) for SOA Purposes How to Write to an AQ JMS Queue from a BPEL Process How to Read from an AQ JMS Queue from a BPEL Process

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• Demo on Data Guard Protection From Lost-Write Corruption

  - by Rene Kundersma

  Today I received the news a new demo has been made available on OTN for Data Guard protection from lost-write corruption. Since this is a typical MAA solution and a very nice demo I decided to mention this great feature also in this blog even while it's a recommended best practice for some time. When lost writes occur an I/O subsystem acknowledges the completion of the block write even though the write I/O did not occur in the persistent storage. On a subsequent block read on the primary database, the I/O subsystem returns the stale version of the data block, which might be used to update other blocks of the database, thereby corrupting it.  Lost writes can occur after an OS or storage device driver failure, faulty host bus adapters, disk controller failures and volume manager errors. In the demo a data block lost write occurs when an I/O subsystem acknowledges the completion of the block write, while in fact the write did not occur in the persistent storage. When a primary database lost write corruption is detected by a Data Guard physical standby database, Redo Apply (MRP) will stop and the standby will signal an ORA-752 error to explicitly indicate a primary lost write has occurred (preventing corruption from spreading to the standby database). Links: MOS (1302539.1). "Best Practices for Corruption Detection, Prevention, and Automatic Repair - in a Data Guard Configuration" Demo MAA Best Practices Rene Kundersma

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• Update: GTAS and EBS

  - by jeffrey.waterman

  Provided below are updated target date timeframes for provided patches for upcoming legislative enhancements.   Dates have been pushed out from previous dates provided due to changes in Treasury mandatory dates.  Mandatory dates for GTAS and IPAC have changes since previous target dates for patches were provided.   These are target dates, not commitments to deliver functionality. Deliverable Target Timeframes for Customer Patches Comments R12 GTAS Configuration Apr 2012 Patch is available GTAS Key Processes Oct/Nov 2012 Includes GTAS processes necessary to create the GTAS interface file, migration of FACTS balances to GTAS, GTAS Trial Balance, and GTAS Transaction Register. GTAS Reports Nov/Dec 2012 GTAS Trial Balance GTAS Transaction Register Capture of Trading Partner TAS/BETC Apr/May 2013 Includes modification necessary to capture BETC, Trading Partner TAS/BETC on relevant transactions. GTAS Other Processes May/Jun  2013 Includes GTAS Customer and Vendor  update processes. IPAC Aug/Sep Includes modification required to IPAC to accommodate Componentized TAS and BETC. 11i GTAS Configuration May 2012 Patch is available GTAS Key Processes Nov/Dec 2012 Includes GTAS processes necessary to create the GTAS interface file, migration of FACTS balances to GTAS, GTAS Trial Balance, and GTAS Transaction Register. GTAS Reports Dec/Jan 2012 GTAS Trial Balance GTAS Transaction Register Capture of Trading Partner TAS/BETC May/Jun 2013 Includes modification necessary to capture BETC, Trading Partner TAS/BETC on relevant transactions. GTAS Other Processes Jun/Jul 2013 Includes GTAS Customer and Vendor  update processes. IPAC Sep/Oct 2013 Includes modification required to IPAC to accommodate Componentized TAS and BETC.

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• Using Exception Handler in an ADF Task Flow

  - by anmprs

  Problem Statement: Exception thrown in a task flow gets wrapped in an exception that gives an unintelligible error message to the user. Figure 1 Solution 1. Over-writing the error message with a user-friendly error message. Figure 2 Steps to code 1. Generating an exception: Write a method that throws an exception and drop it in the task flow.2. Adding an Exception Handler: Write a method (example below) to overwrite the Error in the bean or data control and drop the method in the task flow. Figure 3 This method is marked as the Exception Handler by Right-Click on method > Mark Activity> Exception Handler or by the button that is displayed in this screenshot Figure 4 The Final task flow should look like this. This will overwrite the exception with the error message in figure 2. Note: There is no need for a control flow between the two method calls (as shown below). Figure 5 Solution 2: Re-Routing the task flow to display an error page Figure 6 Steps to code 1. This is the same as step 1 of solution 1.2. Adding an Exception Handler: The Exception handler is not always a method; in this case it is implemented on a task flow return.  The task flow looks like this. Figure 7 In the figure below you will notice that the task flow return points to a control flow ‘error’ in the calling task flow. Figure 8 This control flow in turn goes to a view ‘error.jsff’ which contains the error message that one wishes to display.  This can be seen in the figure below. (‘withErrorHandling’ is a  call to the task flow in figure 7) Figure 9

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• Are you ready for the needed changes to your Supply Chain for 2013?

  - by Stephen Slade

  With the initiation of the Dodd-Frank Act, companies need to determine if their products contain 'conflict materials' from certain global markets as the Rep of Congo. The materials include metals such as gold, tin, tungsten and tantalum. Compaines with global sourcing face new disclosure requirements in Feb'13 related to business being done in Iran. Public companies are required to disclose to U.S. security regulators if they or their affiliates are engaged in business in Iran either directly or indirectly.  Is your supply chain compliant?  Do you have sourcing reports to validate?  Where are the materials in your chips & circuit boards coming from? In the next few weeks, responsible companies will be scrutinizing their supply chains, subs, JVs, and affiliates to search for exposure. Source: Brian Lane, Atty at Gibson Dunn Crutcher, as printed in the WSJ Tues, Dec 11, 2012 p.B8

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• Java EE @ No Fluff Just Stuff Tour

  - by reza_rahman

  If you work in the US and still don't know what the No Fluff Just Stuff (NFJS) Tour is, you are doing yourself a very serious disfavor. NFJS is by far the cheapest and most effective way to stay up to date through some world class speakers and talks. This is most certainly true for US enterprise Java developers in particular. Following the US cultural tradition of old-fashioned roadshows, NFJS is basically a set program of speakers and topics offered at major US cities year round. Many now famous world class technology speakers can trace their humble roots to NFJS. Via NFJS you basically get to have amazing training without paying for an expensive venue, lodging or travel. The events are usually on the weekends so you don't need to even skip work if you want (a great feature for consultants on tight budgets and deadlines). I am proud to share with you that I recently joined the NFJS troupe. My hope is that this will help solve the lingering problem of effectively spreading the Java EE message here in the US. For NFJS I hope my joining will help beef up perhaps much desired Java content. In any case, simply being accepted into this legendary program is an honor I could have perhaps only dreamed of a few years ago. I am very grateful to Jay Zimmerman for seeing the value in me and the Java EE content. The current speaker line-up consists of the likes of Neal Ford, Venkat Subramaniam, Nathaniel Schutta, Tim Berglund and many other great speakers. I actually had my tour debut on April 4-5 with the NFJS New York Software Symposium - basically a short train commute away from my home office. The show is traditionally one of the smaller ones and it was not that bad for a start. I look forward to doing a few more in the coming months (more on that a bit later). I had four talks back to back (really my most favorite four at the moment). The first one was a talk on JMS 2 - some of you might already know JMS is one of my most favored Java EE APIs. The slides for the talk are posted below: What’s New in Java Message Service 2 from Reza Rahman The next talk I delivered was my Cargo Tracker/Java EE + DDD talk. This talk basically overviews DDD and describes how DDD maps to Java EE using code examples/demos from the Cargo Tracker Java EE Blue Prints project. Applied Domain-Driven Design Blue Prints for Java EE from Reza Rahman The third talk I delivered was our flagship Java EE 7/8 talk. As you may know, currently the talk is basically about Java EE 7. I'll probably slowly evolve this talk to gradually transform it into a Java EE 8 talk as we move forward (I'll blog about that separately shortly). The following is the slide deck for the talk: JavaEE.Next(): Java EE 7, 8, and Beyond from Reza Rahman My last talk for the show was my JavaScript+Java EE 7 talk. This talk is basically about aligning EE 7 with the emerging JavaScript ecosystem (specifically AngularJS). The slide deck for the talk is here: JavaScript/HTML5 Rich Clients Using Java EE 7 from Reza Rahman Unsurprisingly this talk was well-attended. The demo application code is posted on GitHub. The code should be a helpful resource if this development model is something that interests you. Do let me know if you need help with it but the instructions should be fairly self-explanatory. My next NFJS show is the Central Ohio Software Symposium in Columbus on June 6-8 (sorry for the late notice - it's been a really crazy few weeks). Here's my tour schedule so far, I'll keep you up-to-date as the tour goes forward: June 6 - 8, Columbus Ohio. June 24 - 27, Denver Colorado (UberConf) - my most extensive agenda on the tour so far. July 18 - 20, Austin Texas. I hope you'll take this opportunity to get some updates on Java EE as well as the other awesome content on the tour?

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• Webcast: Applications Integration Architecture

  - by LuciaC

  Webcast: Applications Integration Architecture - Overview and Best Practices Date:  November 12, 2013.Join us for an Overview and Best Practices live webcast on Applications Integration Architecture (AIA). We are covering following topics in this Webcast : AIA Overview AIA - Where it Stands Pre-Install, Pre-Upgrade Concerns Understanding Dependency Certification Matrix Documentation Information Center Demonstration - How to evaluate certified combination Software Download/Installable Demonstration - edelivery Download Overview Reference Information Q & A (15 Minutes)  We will be holding 2 separate sessions to accommodate different timezones: EMEA / APAC - timezone Session : Tuesday, 12-NOV-2013 at 09:00 UK / 10:00 CET / 14:30 India / 18:00 Japan / 20:00 AEDT Details & Registration : Doc ID 1590146.1 Direct registration link USA - timezone Session : Wednesday, 13-NOV-2013 at 18:00 UK / 19:00 CET / 10:00 PST / 11:00 MST / 13:00 EST Details & Registration : Doc ID 1590147.1 Direct registration link If you have any question about the schedules or if you have a suggestion for an Advisor Webcast to be planned in future, please send an E-Mail to Ruediger Ziegler. Remember that you can access a full listing of all future webcasts as well as replays from Doc ID 740966.1.

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• Linking to BIP reports from BIEE Analyses

  - by Tim Dexter

  Bryan found a great blog post from Fiston over on the OBIEEStuff blog. It covers the ability to link to a BIP report from a BIEE analyses report with the ability to pass parameters to it. I have doubled checked and you need to be on OBIEE 11.1.1.5 to see the 'Shared Report Link' mentioned in Fiston's post when you open a BIP report from the /analytics side of the house. Enjoy! OBIEE to BIP trick

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• Analytics in an Omni-Channel World

  - by David Dorf

  Retail has been around ever since mankind started bartering.  The earliest transactions were very specific to the individuals buying and selling, then someone had the bright idea to open a store.  Those transactions were a little more generic, but the store owner still knew his customers and what they wanted.  As the chains rolled out, customer intimacy was sacrificed for scale, and retailers began to rely on segments and clusters.  But thanks to the widespread availability of data and the technology to convert said data into information, retailers are getting back to details. The retail industry is following a maturity model for analytics that is has progressed through five stages, each delivering more value than the previous. Store Analytics Brick-and-mortar retailers (and pure-play catalogers as well) that collect anonymous basket-level data are able to get some sense of demand to help with allocation decisions.  Promotions and foot-traffic can be measured to understand marketing effectiveness and perhaps focus groups can help test ideas.  But decisions are influenced by the majority, using faceless customer segments and aggregated industry data points.  Loyalty programs help a little, but in many cases the cost outweighs the benefits. Web Analytics The Web made it much easier to collect data on specific, yet still anonymous consumers using cookies to track visits. Clickstreams and product searches are analyzed to understand the purchase journey, gauge demand, and better understand up-selling opportunities.  Personalization begins to allow retailers target market consumers with recommendations. Cross-Channel Analytics This phase is a minor one, but where most retailers probably sit today.  They are able to use information from one channel to bolster activities in another. However, there are technical challenges combining data silos so its not an easy task.  But for those retailers that are able to perform analytics on both sources of data, the pay-off is pretty nice.  Revenue per customer begins to go up as customers have a better brand experience. Mobile & Social Analytics Big data technologies are enabling a 360-degree view of the customer by incorporating psychographic data from social sites alongside traditional demographic data.  Retailers can track individual preferences, opinions, hobbies, etc. in order to understand a consumer's motivations.  Using mobile devices, consumers can interact with brands anywhere, anytime, accessing deep product information and reviews.  Mobile, combined with a loyalty program, presents an opportunity to put shopping into geographic context, understanding paths to the store, patterns within the store, and be an always-on advertising conduit. Omni-Channel Analytics All this data along with the proper technology represents a new paradigm in which the clock is turned back and retail becomes very personal once again.  Rich, individualized data better illuminates demand, allows for highly localized assortments, and helps tailor up-selling.  Interactions with all channels help build an accurate profile of each consumer, and allows retailers to tailor the retail experience to meet the heightened expectations of today's sophisticated shopper.  And of course this culminates in greater customer satisfaction and business profitability.

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• Short Season, Long Models - Dealing with Seasonality

  - by Michel Adar

  Accounting for seasonality presents a challenge for the accurate prediction of events. Examples of seasonality include: ·         Boxed cosmetics sets are more popular during Christmas. They sell at other times of the year, but they rise higher than other products during the holiday season. ·         Interest in a promotion rises around the time advertising on TV airs ·         Interest in the Sports section of a newspaper rises when there is a big football match There are several ways of dealing with seasonality in predictions. Time Windows If the length of the model time windows is short enough relative to the seasonality effect, then the models will see only seasonal data, and therefore will be accurate in their predictions. For example, a model with a weekly time window may be quick enough to adapt during the holiday season. In order for time windows to be useful in dealing with seasonality it is necessary that: The time window is significantly shorter than the season changes There is enough volume of data in the short time windows to produce an accurate model An additional issue to consider is that sometimes the season may have an abrupt end, for example the day after Christmas. Input Data If available, it is possible to include the seasonality effect in the input data for the model. For example the customer record may include a list of all the promotions advertised in the area of residence. A model with these inputs will have to learn the effect of the input. It is possible to learn it specific to the promotion – and by the way learn about inter-promotion cross feeding – by leaving the list of ads as it is; or it is possible to learn the general effect by having a flag that indicates if the promotion is being advertised. For inputs to properly represent the effect in the model it is necessary that: The model sees enough events with the input present. For example, by virtue of the model lifetime (or time window) being long enough to see several “seasons” or by having enough volume for the model to learn seasonality quickly. Proportional Frequency If we create a model that ignores seasonality it is possible to use that model to predict how the specific person likelihood differs from average. If we have a divergence from average then we can transfer that divergence proportionally to the observed frequency at the time of the prediction. Definitions: Ft = trailing average frequency of the event at time “t”. The average is done over a suitable period of to achieve a statistical significant estimate. F = average frequency as seen by the model. L = likelihood predicted by the model for a specific person Lt = predicted likelihood proportionally scaled for time “t”. If the model is good at predicting deviation from average, and this holds over the interesting range of seasons, then we can estimate Lt as: Lt = L * (Ft / F) Considering that: L = (L – F) + F Substituting we get: Lt = [(L – F) + F] * (Ft / F) Which simplifies to: (i)                  Lt = (L – F) * (Ft / F)  +  Ft This latest expression can be understood as “The adjusted likelihood at time t is the average likelihood at time t plus the effect from the model, which is calculated as the difference from average time the proportion of frequencies”. The formula above assumes a linear translation of the proportion. It is possible to generalize the formula using a factor which we will call “a” as follows: (ii)                Lt = (L – F) * (Ft / F) * a  +  Ft It is also possible to use a formula that does not scale the difference, like: (iii)               Lt = (L – F) * a  +  Ft While these formulas seem reasonable, they should be taken as hypothesis to be proven with empirical data. A theoretical analysis provides the following insights: The Cumulative Gains Chart (lift) should stay the same, as at any given time the order of the likelihood for different customers is preserved If F is equal to Ft then the formula reverts to “L” If (Ft = 0) then Lt in (i) and (ii) is 0 It is possible for Lt to be above 1. If it is desired to avoid going over 1, for relatively high base frequencies it is possible to use a relative interpretation of the multiplicative factor. For example, if we say that Y is twice as likely as X, then we can interpret this sentence as: If X is 3%, then Y is 6% If X is 11%, then Y is 22% If X is 70%, then Y is 85% - in this case we interpret “twice as likely” as “half as likely to not happen” Applying this reasoning to (i) for example we would get: If (L < F) or (Ft < (1 / ((L/F) + 1)) Then  Lt = L * (Ft / F) Else Lt = 1 – (F / L) + (Ft * F / L)  

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