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  • Is there any working implementation of reverse mode automatic differentiation for Haskell?

    - by Ian Fiske
    The closest-related implementation in Haskell I have seen is the forward mode at http://hackage.haskell.org/packages/archive/fad/1.0/doc/html/Numeric-FAD.html. The closest related related research appears to be reverse mode for another functional language related to Scheme at http://www.bcl.hamilton.ie/~qobi/stalingrad/. I see reverse mode in Haskell as kind of a holy grail for a lot of tasks, with the hopes that it could use Haskell's nested data parallelism to gain a nice speedup in heavy numerical optimization.

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  • C# WMI Process Differentiation!?

    - by Goober
    Scenario I have a method that returns a list of processes using WMI. If I have 3 processes running (all of which are C# applications) - and they all have THE SAME PROCESS NAME but different command line arguments, how can I differentiate between them If I want to start them or terminate them!? Thoughts As far as I can see, I physically cannot differentiate between them, at least not without having to use the Handle, but that doesn't tell me which one of them got terminated because the others will still sit there with the same name........ ....really stumped, help greatly appreciated!

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  • Facebook Connect for iOS: dialogDidComplete response differentiation

    - by Oh Danny Boy
    I was wondering how to differentiate between the user tapping submit or skip in the inline post-to-stream FBDialog. Anyone know what to test for? I am using the latest iOS Facebook Connect in a iOS 4.2 environment. /** * Called when a UIServer Dialog successfully return. */ - (void)dialogDidComplete:(FBDialog *)dialog { if user tapped submit and post was successful alert user of successful post if user tapped "skip" (cancel equivalent) do not display alert }

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  • Derivative of a Higher-Order Function

    - by Claudiu
    This is in the context of Automatic Differentiation - what would such a system do with a function like map, or filter - or even one of the SKI Combinators? Example: I have the following function: def func(x): return sum(map(lambda a: a**x, range(20))) What would its derivative be? What will an AD system yield as a result? (This function is well-defined on real-number inputs).

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  • Derivative Calculator

    - by burki
    Hi! I'm interested in building a derivative calculator. I've racked my brains over solving the problem, but I haven't found a right solution at all. May you have a hint how to start? Thanks

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  • Partnering with your Applications – The Oracle AppAdvantage Story

    - by JuergenKress
    So, what is Oracle AppAdvantage? A practical approach to adopting cloud, mobile, social and other trends A guided path to aligning IT more closely with business objectives Maximizing the value of existing investments in applications A layered approach to simplifying IT, building differentiation and bringing innovation All of the above? Enhance the value of your existing applications investment with #Oracle #AppAdvantage Aligning biz and IT expectations on Simplifying IT, building Differentiation and Innovation #AppAdvantage Adopt a pace layered approach to extracting biz value from your apps with #AppAdvantage Bringing #cloud, #social, #mobile to your apps with #Oracle #AppAdvantage Embracing Situational IT In the next IT Leaders Editorial, Rick Beers discusses the necessity of IT disruption and #AppAdvantage. Rick Beers sheds light on the Situational Leadership and the path to success #AppAdvantage. Rick Beers draws parallels with CIO’s strategic thinking and #Oracle #AppAdvantage approach. Do you have this paper in your summer reading list? Aligning biz and IT #AppAdvantage What does Situational leadership have to do with Oracle AppAdvantage? Catch the next piece in Rick Beers’ monthly series of IT Leaders Editorial and find out. #AppAdvantage Middleware Minutes with Howard Beader – August edition In the quarterly column, @hbeader discusses impact of #cloud, #mobile, #fastdata on #middleware Making #cloud, #mobile, #fastdata a part of your IT strategy with #middleware What keeps the #oracle #middleware team busy? Find out in the inaugural post in quarterly update on #middleware Recent #middleware news update along with a preview of things to come from #Oracle, in @hbeader ‘s quarterly column In his inaugural post, Howard Beader, senior director for Oracle Fusion Middleware, discusses the recent industry trends including mobile, cloud, fast data, integration and how these are shaping the IT and business requirements. SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Facebook Wiki Mix Forum Technorati Tags: AppAdvantage,SOA Community,Oracle SOA,Oracle BPM,Community,OPN,Jürgen Kress

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  • Partnering with your Applications – The Oracle AppAdvantage Story

    - by JuergenKress
    So, what is Oracle AppAdvantage? A practical approach to adopting cloud, mobile, social and other trends A guided path to aligning IT more closely with business objectives Maximizing the value of existing investments in applications A layered approach to simplifying IT, building differentiation and bringing innovation All of the above? Enhance the value of your existing applications investment with #Oracle #AppAdvantage Aligning biz and IT expectations on Simplifying IT, building Differentiation and Innovation #AppAdvantage Adopt a pace layered approach to extracting biz value from your apps with #AppAdvantage Bringing #cloud, #social, #mobile to your apps with #Oracle #AppAdvantage Embracing Situational IT In the next IT Leaders Editorial, Rick Beers discusses the necessity of IT disruption and #AppAdvantage. Rick Beers sheds light on the Situational Leadership and the path to success #AppAdvantage. Rick Beers draws parallels with CIO’s strategic thinking and #Oracle #AppAdvantage approach. Do you have this paper in your summer reading list? Aligning biz and IT #AppAdvantage What does Situational leadership have to do with Oracle AppAdvantage? Catch the next piece in Rick Beers’ monthly series of IT Leaders Editorial and find out. #AppAdvantage Middleware Minutes with Howard Beader – August edition In the quarterly column, @hbeader discusses impact of #cloud, #mobile, #fastdata on #middleware Making #cloud, #mobile, #fastdata a part of your IT strategy with #middleware What keeps the #oracle #middleware team busy? Find out in the inaugural post in quarterly update on #middleware Recent #middleware news update along with a preview of things to come from #Oracle, in @hbeader ‘s quarterly column In his inaugural post, Howard Beader, senior director for Oracle Fusion Middleware, discusses the recent industry trends including mobile, cloud, fast data, integration and how these are shaping the IT and business requirements. SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Facebook Wiki Mix Forum Technorati Tags: AppAdvantage,SOA Community,Oracle SOA,Oracle BPM,Community,OPN,Jürgen Kress

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  • 2012 Oracle Fusion Middleware Innovation Awards for Oracle Exalogic

    - by Sanjeev Sharma
    Companies from around the world were honored for their innovative solutions using Oracle Fusion Middleware. This year’s 27 award winners, representing 11 countries and a wide span of industries, wowed the judges with a range of projects across eight product categories. 4 awards were given out to customers who demonstrated innovative application of Oracle Exalogic for their mission-critical applications.Below is an overview of the 4 businesses that won the Oracle Fusion Middleware Innovation Award for Oracle Exalogic this year. Company: Netshoes About: Leading online retailer of sporting goods in Latin America.Challenges: Rapid business growth resulted in frequent outages and poor response-time of online store-front Conventional ad-hoc approach to horizontal scaling resulted in high CAPEX and OPEX Poor performance and unavailability of online store-front resulted in revenue loss from purchase abandonment Solution: Consolidated ATG Commerce and Oracle WebLogic running on Oracle Exalogic.Business Impact:Reduced abandonment rates resulting in a two-digit increase in online conversion rates translating directly into revenue up-liftCompany: ClaroAbout: Leading communications services provider in Latin America.Challenges: Support business growth over the next 3  - 5 years while maximizing re-use of existing middleware and application investments with minimal effort and risk Solution: Consolidated Oracle Fusion Middleware components (Oracle WebLogic, Oracle SOA Suite, Oracle Tuxedo) and JAVA applications onto Oracle Exalogic and Oracle Exadata. Business Impact:Improved partner SLA’s 7x while improving throughput 5X and response-time 35x for  JAVA applicationsCompany: ULAbout: Leading safety testing and certification organization in the world.Challenges: Transition from being a non-profit to a profit oriented enterprise and grow from a $1B to $5B in annual revenues in the next 5 years Undertake a massive business transformation by aligning change strategy with execution Solution: Consolidated Oracle Applications (E-Business Suite, Siebel, BI, Hyperion) and Oracle Fusion Middleware (AIA, SOA Suite) on Oracle Exalogic and Oracle ExadataBusiness Impact:Reduced financial and operating risk in re-architecting IT services to support new business capabilities supporting 87,000 manufacturersCompany: Ingersoll RandAbout: Leading manufacturer of industrial, climate, residential and security solutions.Challenges: Business continuity risks due to complexity in enforcing consistent operational and financial controls; Re-active business decisions reduced ability to offer differentiation and compete Solution: Consolidated Oracle E-business Suite on Oracle Exalogic and Oracle ExadataBusiness Impact:Service differentiation with faster order provisioning and a shorter lead-to-cash cycle translating into higher customer satisfaction and quicker cash-conversionCheck out the winners of the Oracle Fusion Middleware Innovation awards in other categories here.

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  • Extreme Optimization Numerical Libraries for .NET – Part 1 of n

    - by JoshReuben
    While many of my colleagues are fascinated in constructing the ultimate ViewModel or ServiceBus, I feel that this kind of plumbing code is re-invented far too many times – at some point in the near future, it will be out of the box standard infra. How many times have you been to a customer site and built a different variation of the same kind of code frameworks? How many times can you abstract Prism or reliable and discoverable WCF communication? As the bar is raised for whats bundled with the framework and more tasks become declarative, automated and configurable, Information Systems will expose a higher level of abstraction, forcing software engineers to focus on more advanced computer science and algorithmic tasks. I've spent the better half of the past decade building skills in .NET and expanding my mathematical horizons by working through the Schaums guides. In this series I am going to examine how these skillsets come together in the implementation provided by ExtremeOptimization. Download the trial version here: http://www.extremeoptimization.com/downloads.aspx Overview The library implements a set of algorithms for: linear algebra, complex numbers, numerical integration and differentiation, solving equations, optimization, random numbers, regression, ANOVA, statistical distributions, hypothesis tests. EONumLib combines three libraries in one - organized in a consistent namespace hierarchy. Mathematics Library - Extreme.Mathematics namespace Vector and Matrix Library - Extreme.Mathematics.LinearAlgebra namespace Statistics Library - Extreme.Statistics namespace System Requirements -.NET framework 4.0  Mathematics Library The classes are organized into the following namespace hierarchy: Extreme.Mathematics – common data types, exception types, and delegates. Extreme.Mathematics.Calculus - numerical integration and differentiation of functions. Extreme.Mathematics.Curves - points, lines and curves, including polynomials and Chebyshev approximations. curve fitting and interpolation. Extreme.Mathematics.Generic - generic arithmetic & linear algebra. Extreme.Mathematics.EquationSolvers - root finding algorithms. Extreme.Mathematics.LinearAlgebra - vectors , matrices , matrix decompositions, solvers for simultaneous linear equations and least squares. Extreme.Mathematics.Optimization – multi-d function optimization + linear programming. Extreme.Mathematics.SignalProcessing - one and two-dimensional discrete Fourier transforms. Extreme.Mathematics.SpecialFunctions

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  • Oracle Exalogic Customer Momentum @ OOW'12

    - by Sanjeev Sharma
    [Adapted from here]  At Oracle Open World 2012, i sat down with some of the Oracle Exalogic early adopters  to discuss the business benefits these businesses were realizing by embracing the engineered systems approach to data-center modernization and application consolidation. Below is an overview of the 4 businesses that won the Oracle Fusion Middleware Innovation Award for Oracle Exalogic this year. Company: Netshoes About: Leading online retailer of sporting goods in Latin America.Challenges: Rapid business growth resulted in frequent outages and poor response-time of online store-front Conventional ad-hoc approach to horizontal scaling resulted in high CAPEX and OPEX Poor performance and unavailability of online store-front resulted in revenue loss from purchase abandonment Solution: Consolidated ATG Commerce and Oracle WebLogic running on Oracle Exalogic.Business Impact:Reduced abandonment rates resulting in a two-digit increase in online conversion rates translating directly into revenue up-liftCompany: ClaroAbout: Leading communications services provider in Latin America.Challenges: Support business growth over the next 3  - 5 years while maximizing re-use of existing middleware and application investments with minimal effort and risk Solution: Consolidated Oracle Fusion Middleware components (Oracle WebLogic, Oracle SOA Suite, Oracle Tuxedo) and JAVA applications onto Oracle Exalogic and Oracle Exadata. Business Impact:Improved partner SLA’s 7x while improving throughput 5X and response-time 35x for  JAVA applicationsCompany: ULAbout: Leading safety testing and certification organization in the world.Challenges: Transition from being a non-profit to a profit oriented enterprise and grow from a $1B to $5B in annual revenues in the next 5 years Undertake a massive business transformation by aligning change strategy with execution Solution: Consolidated Oracle Applications (E-Business Suite, Siebel, BI, Hyperion) and Oracle Fusion Middleware (AIA, SOA Suite) on Oracle Exalogic and Oracle ExadataBusiness Impact:Reduced financial and operating risk in re-architecting IT services to support new business capabilities supporting 87,000 manufacturersCompany: Ingersoll RandAbout: Leading manufacturer of industrial, climate, residential and security solutions.Challenges: Business continuity risks due to complexity in enforcing consistent operational and financial controls; Re-active business decisions reduced ability to offer differentiation and compete Solution: Consolidated Oracle E-business Suite on Oracle Exalogic and Oracle ExadataBusiness Impact:Service differentiation with faster order provisioning and a shorter lead-to-cash cycle translating into higher customer satisfaction and quicker cash-conversionCheck out the winners of the Oracle Fusion Middleware Innovation awards in other categories here.

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  • Oracle WebCenter Partner Program

    - by kellsey.ruppel
    In competitive marketplaces, your company needs to quickly respond to changes and new trends, in order to open opportunities and build long-term growth. Oracle has a variety of next-generation services, solutions and resources that will leverage the differentiators in your offerings. Name your partnering needs: Oracle has the answer. This week we’d like to focus on Partners and the value your organization can gain from working with the Oracle PartnerNetwork. The Oracle PartnerNetwork will empower your company with exceptional resources to distinguish your offerings from the competition, seize opportunities, and increase your sales. We’re happy to welcome Christine Kungl, and Brian Buzzell, from Oracle’s World Wide Alliances & Channels (WWA&C) WebCenter Partner Enablement team, as today’s guests on the Oracle WebCenter blog. Q: What is the Oracle PartnerNetwork (OPN)?A: Christine: Oracle’s PartnerNetwork (OPN) is a collaborative partnership which allows registered companies specific added value resources to help differentiate themselves from their competition. Through OPN programs it provides companies the ability to seize and target opportunities, educate and train their teams, and leverage unparalleled opportunity given Oracle’s large market footprint. OPN’s multi-level programs are targeted at different levels allowing companies to grow and evolve with Oracle based on their business needs.  As part of their OPN memberships partners are encouraged to become OPN Specialized allowing those partners additional differentiation in Oracle’s Partner Network Community.  Q: What is an OPN Specialization and what resources are available for Specialized Partners?A: Brian: Oracle wanted a better way for our partners to differentiate their special skills and expertise, as well a more effective way to communicate that difference to customers.  Oracle’s expanding product portfolio demanded that we be able to identify partners with significant product knowledge—those who had made an investment in Oracle and a continuing commitment to deliver Oracle solutions. And with more than 30,000 Oracle partners around the world, Oracle needed a way for our customers to choose the right partner for their business. So how did Oracle meet this need? With the new partner program:  Oracle PartnerNetwork (OPN) Specialized. In this new program, Oracle partners are: Specialized :  Differentiating themselves from the competition with expertise that set them apart Recognized:  Being acknowledged for investing in becoming Oracle experts in specialized areas. Preferred :  Connecting with potential customers who are seeking  value-added solutions for their business OPN Specialized provides all partners with educational opportunities, training, and tools specially designed to build competency and grow business.  Partners can serve their customers better through key resources:OPN Specialized Knowledge Zones – Located on the updated and enhanced OPN portal— provide a single point of entry for all education and training information for Oracle partners. Enablement 2.0 Resources —Enablement 2.0 helps Oracle partners build their competencies and skills through a variety of educational opportunities and expanded training choices. These resources include: Enablement 2.0 “Boot camps” provide three-tiered learning levels that help jump-start partner training The role-based training covers Oracle’s application and technology products and offers a combination of classroom lectures, hands-on lab exercises, and case studies. Enablement 2.0 Interactive guided learning paths (GLPs) with recommendations on how to achieve specialization Upgraded partner solution kits Enhanced, specialized business centers available 24/7 around the globe on the OPN portal OPN Competency Center—Tracking ProgressThe OPN Competency Center keeps track as a partner applies for and achieves specialization in selected areas. You start with an assessment that compares your organization’s current skills and experience with the requirements for specialization in the area you have chosen. The OPN Competency Center then provides a roadmap that itemizes the skills and the knowledge you need to earn specialized status. In summary, OPN Specialization not only includes key training resources but a way to track and show progression for your partner organization. Q: What is are the OPN Membership Levels and what are the benefits?A:  Christine: The base OPN membership levels are: Remarketer: At the Remarketer level, retailers can choose to resell select Oracle products with the backing of authorized, regionally located, value-added distributors (VADs). The Remarketer level has no fees and no partner agreement with Oracle, but does offer online training and sales tools through the OPN portal.Program Details: RemarketerSilver Level: The Silver level is for Oracle partners who are focused on reselling and developing business with products ordered through the Oracle 1-Click Ordering Program. The Silver level provides a cost-effective, yet scalable way for partners to start an OPN Specialized membership and offers a substantial set of benefits that lets partners increase their competitive positioning. Program Details: SilverGold Level: Gold-level partners have the ability to specialize, helping them grow their business and create differentiation in the marketplace. Oracle partners at the Gold level can develop, sell, or implement the full stack of Oracle solutions and can apply to resell Oracle Applications.Program Details: GoldPlatinum Level: The Platinum level is for Oracle partners who want the highest level of benefits and are committed to reaching a minimum of five specializations. Platinum partners are recognized for their expertise in a broad range of products and technology, and receive dedicated support from Oracle.Program Details: PlatinumIn addition we recently introduced a new level:Diamond Level: This level is the most prestigious level of OPN Specialized. It allows companies to differentiate further because of their focused depth and breadth of their expertise. Program Details: DiamondSo as you can see there are various levels cost effective ways that Partners can get assistance, differentiation through OPN membership. Q: What role does the Oracle's World Wide Alliances & Channels (WWA&C), Partner Enablement teams and the WebCenter Community play?  A: Brian: Oracle’s WWA&C teams are responsible for manage relationships, educating their teams, creating go-to-market solutions and fostering communities for Oracle partners worldwide.  The WebCenter Partner Enablement Middleware Team is tasked to create, manage and distribute Specialization resources for the WebCenter Partner community. Q: What WebCenter Specializations are currently available?A: Christine:  As of now here are the following WebCenter Specializations and their availability: Oracle WebCenter Portal Specialization (Oracle WebCenter Portal): Available NowThe Oracle WebCenter Specialization provides insight into the following products: WebCenter Services, WebCenter Spaces, and WebLogic Portal.Oracle WebCenter Specialized Partners can efficiently use Oracle WebCenter products to create social applications, enterprise portals, communities, composite applications, and Internet or intranet Web sites on a standards-based, service-oriented architecture (SOA). The suite combines the development of rich internet applications; a multi-channel portal framework; and a suite of horizontal WebCenter applications, which provide content, presence, and social networking capabilities to create a highly interactive user experience. Oracle WebCenter Content Specialization: Available NowThe Oracle WebCenter Content Specialization provides insight into the following products; Universal Content Management, WebCenter Records Management, WebCenter Imaging, WebCenter Distributed Capture, and WebCenter Capture.Oracle WebCenter Content Specialized Partners can efficiently build content-rich business applications, reuse content, and integrate hundreds of content services with other business applications. This allows our customers to decrease costs, automate processes, reduce resource bottlenecks, share content effectively, minimize the number of lost documents, and better manage risk. Oracle WebCenter Sites Specialization: Available Q1 2012Oracle WebCenter Sites is part of the broader Oracle WebCenter platform that provides organizations with a complete customer experience management solution.  Partners that align with the new Oracle WebCenter Sites platform allow their customers organizations to: Leverage customer information from all channels and systems Manage interactions across all channels Unify commerce, merchandising, marketing, and service across all channels Provide personalized, choreographed consumer journeys across all channels Integrate order orchestration, supply chain management and order fulfillment Q: What criteria does the Partner organization need to achieve Specialization? What about individual Sales, PreSales & Implementation Specialist/Technical consultants?A: Brian: Each Oracle WebCenter Specialization has unique Business Criteria that must be met in order to achieve that Specialization.  This includes a unique number of transactions (co-sell, re-sell, and referral), customer references and then unique number of specialists as part of a partner team (Sales, Pre-Sales, Implementation, and Support).   Each WebCenter Specialization provides training resources (GLPs, BootCamps, Assessments and Exams for individuals on a partner’s staff to fulfill those requirements.  That criterion can be found for each Specialization on the Specialize tab for each WebCenter Knowledge Zone.  Here are the sample criteria, recommended courses, exams for the WebCenter Portal Specialization: WebCenter Portal Specialization Criteria Q: Do you have any suggestions on the best way for partners to get started if they would like to know more?A: Christine:   The best way to start is for partners is look at their business and core Oracle team focus and then look to become specialized in one or more areas.  Once you have selected the Specializations that are right for your business, you need to follow the first 3 key steps described below. The fourth step outlines the additional process to follow if you meet the criteria to be Advanced Specialized. Note that Step 4 may not be done without first following Steps 1-3.1. Join the Knowledge Zone(s) where you want to achieve Specialized status Go to the Knowledge Zone lick on the "Why Partner" tab Click on the "Join Knowledge Zone" link 2. Meet the Specialization criteria - Define and implement plans in your organization to achieve the competency and business criteria targets of the Specialization. (Note: Worldwide OPN members at the Gold, Platinum, or Diamond level and their Associates at the Gold, Platinum, or Diamond level may count their collective resources to meet the business and competency criteria required for specialization in this area.) 3. Apply for Specialization – when you have met the business and competency criteria required, inform Oracle by completing the following steps: Click on the "Specialize" tab in the Knowledge Zone Click on the "Apply Now" button Complete the online application form Oracle will validate the information provided, and once approved, you will receive notification from Oracle of your awarded Specialized status. Need more information? Access our Step by Step Guide (PDF) 4. Apply for Advanced Specialization (Optional) – If your company has on staff 50 unique Certified Implementation Specialists in your company's approved Specialization's product set, let Oracle know by following these steps: Ensure that you have 50 or more unique individuals that are Certified Implementation Specialists in the specific Specialization awarded to your company If you are pooling resources from another Associate or Worldwide entity, ensure you know that company’s name and country Have your Oracle PRM Administrator complete the online Advanced Specialization Application Oracle will validate the information provided, and once approved, you will receive notification from Oracle of your awarded Advanced Specialized status. There are additional resources on OPN as well as the broader WebCenter Community: v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false false EN-US X-NONE X-NONE /* 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;}

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  • Agile Manifesto, Revisited

    - by GeekAgilistMercenary
    Again, conversations give me a zillion things to write about.  The recent conversation that has cropped up again is my various viewpoints of the Agile Manifesto.  Not all the processes that came after the manifesto was written, but just the core manifesto itself.  Just for context, here is the manifesto in all the glory. We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value: Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan That is, while there is value in the items on the right, we value the items on the left more. Several of the key signatories at the time went on to write some of the core books that really gave Agile Software Development traction.  If you check out the Agile Manifesto Site and do a search for any of those people, you will find a treasure trove of software development information. My 2 Cents First off, I agree with a few people out there.  Agile is not Scrum for instance.  Do NOT get these things confused when checking out Agile, or pushing forward with Scrum.  As David Starr points out in his blog entry, "About 35 minutes into this discussion, I realized I hadn?t heard a question or comment that wasn?t related to Scrum. I asked the room, ?How many people are on an agile team that is NOT using Scrum?? 5 hands. Seriously, out of about 150 people of so. 5 hands." So know, as this is one of my biggest pet peves these days, that Scrum is not Agile.  Another quote David writes, "I assure you, dear reader, 2 week time boxes does not an agile team make." This is the exact problem.  Take a look at the actual manifesto above.  First ideal, "Individuals and interactions over processes and tools".  There are a couple of meanings in this ideal, just as there are in the other written ideals.  But this one has a lot of contention with a set practice such as Scrum.  There are other formulas, namely XP (eXtreme) and Kanban are two that come to mind often.  But none of these are Agile, but instead a process based on the ideals of Agile. Some of you may be thinking, "that?s the same thing".  Well, no, it is not.  This type of differentiation is vitally important.  Agile is a set of ideals.  Processes are nice, but they can change, they may work for some and not others.  The Agile Manifesto covers the ideals behind what is intended, that intention being to learn and find new ways to build better software. Ideals, not processes.  Definition versus implementation.  Class versus object.  The ideals are of utmost importance, the processes are secondary, the first ideal is what really lays this out for me "Individuals and interactions over processes and tools".  Yes, we need tools but we need the individuals and their interactions more. For those coming into a development team, I hope you take this to mind.  It is of utmost importance that this differentiation is known and fought for.  The second the process becomes more important than the individuals and interactions, the team will effectively lose the advantages of Agile Ideals. This is just one of my first thoughts on the topic of Agile.  I will be writing more in the near future about each of the ideals.  I will make a point to outline more of my thoughts, my opinions, and experience with the ideals of Agile and the various processes that are out there.  Maybe, I may stumble upon something new with the help of my readers?  It would be a grand overture to the ideals I hold. For the original entry, check out my personal blog with other juicy tech tidbits, rants, raves, and the like. Agilist Mercenary

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  • Java Embedded @ JavaOne: Q & A

    - by terrencebarr
    There has been a lot of interest in Java Embedded @ JavaOne since it was announced a short while ago (see my previous post). As this is a new conference we did get a number of questions regarding the conference. So we put together a brief Q & A on audience focus, dates, registrations, pricing, submissions, etc. Hope this helps and, remember, the Call for Papers ends next week, Jul 18th 2012! Cheers, – Terrence    Java Embedded @ JavaOne : Q & A  Q. Where can I learn more about “Java Embedded @ JavaOne”? A. Please visit: http://oracle.com/javaone/embedded Q. What is the purpose of “Java Embedded @ JavaOne”? A. This net-new event is designed to provide business and technical decision makers, as well as Java embedded ecosystem partners, a unique occasion to come together and learn about how they can use Java Embedded technologies for new business opportunities. Q. What broad audiences would benefit by attending “Java Embedded @ JavaOne”? A. Java licensees; Government agencies; ISVs, Device Manufacturers; Service Providers such as Telcos, Utilities, Healthcare, Energy, Smart Grid/Smart Metering; Automotive/Telematics; Home/Building Automation; Factory Automation; Media/TV; and Payment vendors. Q. What business titles would benefit by attending “Java Embedded @ JavaOne”? A. The ideal audience for this event is business and technical decision makers (e.g. System Integrators, CTO, CXO, Chief Architects/Architects, Business Development Managers, Project Managers, Purchasing managers, Technical Leads, Senior Decision Makers, Practice Leads, R&D Heads, and Development Managers/Leads). Q. When is “Java Embedded @ JavaOne” taking place? A. The event takes place on Wednesday, Oct. 3th through Thursday, Oct. 4th. Q. Where is “Java Embedded @ JavaOne” taking place? A. The event takes place in the Hotel Nikko. Q. Won’t “Java Embedded @ JavaOne” impact the flagship JavaOne conference since the Hotel Nikko is one of the 3 flagship JavaOne conference’s venue hotels? A. No. Separate space in the Hotel Nikko will be used for “Java Embedded @ JavaOne” and will in no way impact scale and scope of the flagship JavaOne conference’s content mix. Q. Will there be a call for papers for “Java Embedded @ JavaOne”? A. Yes.  The call for papers has started but is ONLY for business focused submissions. Q. What type of business submissions can I make for “Java Embedded @ JavaOne”? A. We are accepting 3 types of business submissions: Best Practices: Java Embedded business solutions, methods, and techniques that consistently show results superior to those achieved with other means, as well as discussions on how Java Embedded can improve business operations, and increase competitive differentiation and profitability. Case Studies: Discussions with Oracle customers and partners that describe the unique business drivers that convinced them to implement Java Embedded as part of an infrastructure technology mix. The discussions will highlight the issues they faced, the decision making involved, and the implementation choices made to create value and improve business differentiation. Panel: Moderator-driven open discussion focused on the emerging opportunities Java Embedded offers businesses, as well as other topics such as strategy, overcoming common challenges, etc. Q. What is the call for papers timeline for “Java Embedded @ JavaOne”? A. The timeline is as follows: CFP Launched – June 18th Deadline for submissions – July 18th Notifications (Accepts/Declines) – week of July 29th Deadline for speakers to accept speaker invitation – August 10th Presentations due for review – August 31st Q. Where can I find more call for paper details for “Java Embedded @ JavaOne”? A. Please go to: http://www.oracle.com/javaone/embedded/call-for-papers/information/index.html Q. How much does it cost to attend “Java Embedded @ JavaOne”? A. The cost to attend is: $595.00 U.S. — Early Bird (Launch date – July 13, 2012) $795.00 U.S. — Pre-Registration (July 14 – September 28, 2012) $995.00 U.S. — Onsite Registration (September 29 – October 4, 2012) Q. Can an attendee of the flagship JavaOne event and Oracle OpenWorld attend “Java Embedded @ JavaOne”? ?A. Yes.  Attendees of both the flagship JavaOne event and Oracle OpenWorld can attend “Java Embedded @ JavaOne” by purchasing a $100.00 U.S. upgrade to their full conference pass. Filed under: Mobile & Embedded Tagged: Call for Papers, Java Embedded @ JavaOne, JavaOne San Francisco

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  • A Taxonomy of Numerical Methods v1

    - by JoshReuben
    Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

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  • NET Math Libraries

    - by JoshReuben
    NET Mathematical Libraries   .NET Builder for Matlab The MathWorks Inc. - http://www.mathworks.com/products/netbuilder/ MATLAB Builder NE generates MATLAB based .NET and COM components royalty-free deployment creates the components by encrypting MATLAB functions and generating either a .NET or COM wrapper around them. .NET/Link for Mathematica www.wolfram.com a product that 2-way integrates Mathematica and Microsoft's .NET platform call .NET from Mathematica - use arbitrary .NET types directly from the Mathematica language. use and control the Mathematica kernel from a .NET program. turns Mathematica into a scripting shell to leverage the computational services of Mathematica. write custom front ends for Mathematica or use Mathematica as a computational engine for another program comes with full source code. Leverages MathLink - a Wolfram Research's protocol for sending data and commands back and forth between Mathematica and other programs. .NET/Link abstracts the low-level details of the MathLink C API. Extreme Optimization http://www.extremeoptimization.com/ a collection of general-purpose mathematical and statistical classes built for the.NET framework. It combines a math library, a vector and matrix library, and a statistics library in one package. download the trial of version 4.0 to try it out. Multi-core ready - Full support for Task Parallel Library features including cancellation. Broad base of algorithms covering a wide range of numerical techniques, including: linear algebra (BLAS and LAPACK routines), numerical analysis (integration and differentiation), equation solvers. Mathematics leverages parallelism using .NET 4.0's Task Parallel Library. Basic math: Complex numbers, 'special functions' like Gamma and Bessel functions, numerical differentiation. Solving equations: Solve equations in one variable, or solve systems of linear or nonlinear equations. Curve fitting: Linear and nonlinear curve fitting, cubic splines, polynomials, orthogonal polynomials. Optimization: find the minimum or maximum of a function in one or more variables, linear programming and mixed integer programming. Numerical integration: Compute integrals over finite or infinite intervals, over 2D and higher dimensional regions. Integrate systems of ordinary differential equations (ODE's). Fast Fourier Transforms: 1D and 2D FFT's using managed or fast native code (32 and 64 bit) BigInteger, BigRational, and BigFloat: Perform operations with arbitrary precision. Vector and Matrix Library Real and complex vectors and matrices. Single and double precision for elements. Structured matrix types: including triangular, symmetrical and band matrices. Sparse matrices. Matrix factorizations: LU decomposition, QR decomposition, singular value decomposition, Cholesky decomposition, eigenvalue decomposition. Portability and performance: Calculations can be done in 100% managed code, or in hand-optimized processor-specific native code (32 and 64 bit). Statistics Data manipulation: Sort and filter data, process missing values, remove outliers, etc. Supports .NET data binding. Statistical Models: Simple, multiple, nonlinear, logistic, Poisson regression. Generalized Linear Models. One and two-way ANOVA. Hypothesis Tests: 12 14 hypothesis tests, including the z-test, t-test, F-test, runs test, and more advanced tests, such as the Anderson-Darling test for normality, one and two-sample Kolmogorov-Smirnov test, and Levene's test for homogeneity of variances. Multivariate Statistics: K-means cluster analysis, hierarchical cluster analysis, principal component analysis (PCA), multivariate probability distributions. Statistical Distributions: 25 29 continuous and discrete statistical distributions, including uniform, Poisson, normal, lognormal, Weibull and Gumbel (extreme value) distributions. Random numbers: Random variates from any distribution, 4 high-quality random number generators, low discrepancy sequences, shufflers. New in version 4.0 (November, 2010) Support for .NET Framework Version 4.0 and Visual Studio 2010 TPL Parallellized – multicore ready sparse linear program solver - can solve problems with more than 1 million variables. Mixed integer linear programming using a branch and bound algorithm. special functions: hypergeometric, Riemann zeta, elliptic integrals, Frensel functions, Dawson's integral. Full set of window functions for FFT's. Product  Price Update subscription Single Developer License $999  $399  Team License (3 developers) $1999  $799  Department License (8 developers) $3999  $1599  Site License (Unlimited developers in one physical location) $7999  $3199    NMath http://www.centerspace.net .NET math and statistics libraries matrix and vector classes random number generators Fast Fourier Transforms (FFTs) numerical integration linear programming linear regression curve and surface fitting optimization hypothesis tests analysis of variance (ANOVA) probability distributions principal component analysis cluster analysis built on the Intel Math Kernel Library (MKL), which contains highly-optimized, extensively-threaded versions of BLAS (Basic Linear Algebra Subroutines) and LAPACK (Linear Algebra PACKage). Product  Price Update subscription Single Developer License $1295 $388 Team License (5 developers) $5180 $1554   DotNumerics http://www.dotnumerics.com/NumericalLibraries/Default.aspx free DotNumerics is a website dedicated to numerical computing for .NET that includes a C# Numerical Library for .NET containing algorithms for Linear Algebra, Differential Equations and Optimization problems. The Linear Algebra library includes CSLapack, CSBlas and CSEispack, ports from Fortran to C# of LAPACK, BLAS and EISPACK, respectively. Linear Algebra (CSLapack, CSBlas and CSEispack). Systems of linear equations, eigenvalue problems, least-squares solutions of linear systems and singular value problems. Differential Equations. Initial-value problem for nonstiff and stiff ordinary differential equations ODEs (explicit Runge-Kutta, implicit Runge-Kutta, Gear's BDF and Adams-Moulton). Optimization. Unconstrained and bounded constrained optimization of multivariate functions (L-BFGS-B, Truncated Newton and Simplex methods).   Math.NET Numerics http://numerics.mathdotnet.com/ free an open source numerical library - includes special functions, linear algebra, probability models, random numbers, interpolation, integral transforms. A merger of dnAnalytics with Math.NET Iridium in addition to a purely managed implementation will also support native hardware optimization. constants & special functions complex type support real and complex, dense and sparse linear algebra (with LU, QR, eigenvalues, ... decompositions) non-uniform probability distributions, multivariate distributions, sample generation alternative uniform random number generators descriptive statistics, including order statistics various interpolation methods, including barycentric approaches and splines numerical function integration (quadrature) routines integral transforms, like fourier transform (FFT) with arbitrary lengths support, and hartley spectral-space aware sequence manipulation (signal processing) combinatorics, polynomials, quaternions, basic number theory. parallelized where appropriate, to leverage multi-core and multi-processor systems fully managed or (if available) using native libraries (Intel MKL, ACMS, CUDA, FFTW) provides a native facade for F# developers

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  • Partner Webcast – Weblogic for Developers - 12 July 2012

    - by Thanos
    Oracle Weblogic Server is the industry’s leading application server for deploying Java EE applications with support for new features for lowering cost of operations, improving performance and enhancing scalability. But it’s also a great choice for the Java developers because of the differentiating capabilities that facilitate integration with other tools and frameworks, promote reusability and rapid redeployment of your applications. During the webinar we’re going to explore these differentiation features in more detail. Agenda: Java EE standards support in different Weblogic Server versions Weblogic  Classloading How Weblogic load the classes Filtering classloader Shared libraries Classloader Analisys Tool Spring support in Weblogic Weblogic integration with Apache Maven Advanced deployment features Fast Swap Side by Side deployment Q&A session 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. Duration: 1 hour Register Now! For any questions please contact us at [email protected] Visit regularly our ISV Migration Center blog Or Follow us @oracleimc to learn more on Oracle Technologies as well as upcoming partner webcasts and events.

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  • Oracle Virtual Networking Partner Sales Playbook Now Available

    - by Cinzia Mascanzoni
    Oracle Virtual Networking Partner Sales Playbook now available to partners registered in OPN Server and Storage Systems Knowledge Zones. Equips you to sell, identify and qualify opportunities, pursue specific sales plays, and deliver competitive differentiation. Find out where you should plan to focus your resources, and how to broaden your offerings by leveraging the OPN Specialized enablement available to your organization. Playbook is accessible to member partners through the following Knowledge Zones: Sun x86 Servers, Sun Blade Servers, SPARC T-Series Servers, SPARC Enterprise High-End M-Series Servers, SPARC Enterprise Entry-Level and Midrange M-Series Servers, Oracle Desktop Virtualization, NAS Storage, SAN Storage, Sun Flash Storage, StorageTek Tape Storage.

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  • 81% of European Shoppers Willing to Pay More for Better Customer Experience

    - by Richard Lefebvre
    Customer Experience provides strategic driver for business growth Research released today from Oracle has revealed that customer experience is now a key driver for revenue growth in Europe, and an effective channel for brand differentiation in a globalized economy where products and services are increasingly commoditized. The research report, “Why Customer Satisfaction is No Longer Good Enough,” reveals that 81% of consumers surveyed are willing to pay more for superior customer experience. With nearly half (44%) willing to pay a premium of more than 5%. Improvement of the overall customer experience (40%), providing quick access to information and making it easier for customers to ask questions (35%) were cited as key drivers for spending more with a brand. The pan-European research, carried out in June 2012 by independent research company Loudhouse, surveyed 1400 online shoppers (50% female, 50% male) who had made a complaint or enquiry to a customer service department in the last 12 months. For full research findings please go to: http://bit.ly/UwmB3j or check the Press Release

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  • BPM in Financial Services Industry

    - by Sanjeev Sharma
    The following series of blog posts discuss common BPM use-cases in the Financial Services industry: Financial institutions view compliance as a regulatory burden that incurs a high initial capital outlay and recurring costs. By its very nature regulation takes a prescriptive, common-for-all, approach to managing financial and non-financial risk. Needless to say, no longer does mere compliance with regulation will lead to sustainable differentiation. For details, check out the 2 part series on managing operational risk of financial services process (part 1 / part 2). Payments processing is a central activity for financial institutions, especially retail banks, and intermediaries that provided clearing and settlement services. Visibility of payments processing is essentially about the ability to track payments and handle payments exceptions as payments flow from initiation to settlement. For details, check out the 2 part series on improving visibility of payments processing (part 1 / part 2).

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  • EE&CIS Oracle University Partner Enablement Update (5th April)

    - by swalker
    Untitled Document Let Oracle University help you become a BI 11g expert! The 5-day Oracle BI Enterprise Edition 11g Implementation Boot Camp has been scheduled exclusively for our partners in Bucharest (Romania) to give them the opportunity to gain differentiation and a competitive advantage today’s market. Oracle BI Enterprise Edition 11g Implementation Bucharest 11-15 June 2012 Click here * Bookmark the EMEA OPN Only Boot Camp schedule web page to view new locations and dates as they are scheduled ** Your OPN discount applies to these bootcamps. Spaces are limited for these events, so register now to guarantee your seat! For a complete list of OPN Bootcamps - both In Class Events and Live Virtual Classes, please refer to the following OPN Schedule. For more information, advice and assistance, please contact us at: Oracle University Romania+4021 3678820 [email protected] oracle.com/ro/education Stay Connected to Oracle University: LinkedIn OracleMix Twitter Facebook Google+

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  • Generic overriding tells me this is the same function. Not agree.

    - by serhio
    base class: Class List(Of T) Function Contains(ByVal value As T) As Boolean derived class: Class Bar : List(Of Exception) ' Exception type as example ' Function Contains(Of U)(ByVal value As U) As Boolean compiler tells me that that two are the same, so I need to declare Overloads/new this second function. But I want use U to differentiate the type (one logic) like NullReferenceException, ArgumentNull Exception, etc. but want to leave the base function(no differentiation by type - other logic) as well.

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  • What is the difference between the Control.Enter and Control.GotFocus events?

    - by jameswelle
    This may be a basic question, but I have to admit I've never truly understood what the difference between the Control.Enter and Control.GotFocus events is. http://msdn.microsoft.com/en-us/library/system.windows.forms.control.enter.aspx http://msdn.microsoft.com/en-us/library/system.windows.forms.control.gotfocus.aspx Is it a differentiation between capturing keyboard or mouse input or something else?

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  • Generic overloading tells me this is the same function. Not agree.

    - by serhio
    base class: Class List(Of T) Function Contains(ByVal value As T) As Boolean derived class: Class Bar : List(Of Exception) ' Exception type as example ' Function Contains(Of U)(ByVal value As U) As Boolean compiler tells me that that two are the same, so I need to declare Overloads/new this second function. But I want use U to differentiate the type (one logic) like NullReferenceException, ArgumentNull Exception, etc. but want to leave the base function(no differentiation by type - other logic) as well.

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  • Attend my Fusion sessions

    - by Daniel Moth
    The inaugural Fusion conference was 1 year ago in June 2011 and I was there doing a demo in the keynote, and also presenting a breakout session. If you look at the abstract and title for that session you won't see the term "C++ AMP" in there because the technology wasn't announced and we didn't want to spill the beans ahead of the keynote, where the technology was announced. It was only an announcement, we did not give any bits out, and in fact the first bits came three months later in September 2011 with the Beta following in February 2012. So it really feels great 1 year later, to be back at Fusion presenting two sessions on C++ AMP, demonstrating our progress from that announcement, to the Visual Studio 2012 Release Candidate that came out last week. If you are attending Fusion (in person or virtually later), be sure to watch my two-part session. Part 1 is PT-3601 on Tuesday 4pm and part 2 is PT-3602 on Wednesday 4pm. Here is the shared abstract for both parts: Harnessing GPU Compute with C++ AMP C++ AMP is an open specification for taking advantage of accelerators like the GPU. In this session we will explore the C++ AMP implementation in Microsoft Visual Studio 2012. After a quick overview of the technology understanding its goals and its differentiation compared with other approaches, we will dive into the programming model and its modern C++ API. This is a code heavy, interactive, two-part session, where every part of the library will be explained. Demos will include showing off the richest parallel and GPU debugging story on the market, in the upcoming Visual Studio release. See you there! Comments about this post by Daniel Moth welcome at the original blog.

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