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• I'm a PHP programmer, how easy will it be to "master" c++?

  - by ThinkingInBits

  I've been a PHP programmer for 8 or so years, I'm familiar with OOP and try to consider best practices whenever programming. I would like to pick up C++ to possibly enter the 'game development' field, where now I'm doing web dev. I'm not a school person, but was wondering what people think about self-taught math to complement learning c++ for game dev. The last math course I took was algebra 2. Should I start delving myself into pre-calculus? Are there any other suggestions you may have to ease the process?

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• editText not centering

  - by Will Nasby

  I have a large editText that no matter what I try, won't center. I have tried putting it in a horizontal and vertical linear layout and then setting that gravity to center because setting the imageText's gravity to center, it still hugs the left of my activity. <EditText android:id="@+id/editText1" android:layout_width="250dp" android:layout_height="wrap_content" android:ems="10" android:gravity="center" android:lines="8" android:maxLines="8" android:minLines="8" > </EditText> And here is what it is doing:

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• How to see fragmentation of a specific file?

  - by Ghostrider

  Is there a tool that would show me for a specific file on disk, how fragmented it is? (How many seeks does physical disk need to make if I were to read that file in a linear fashion)

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• Need help with C# function to translate smoothly between numeric ranges

  - by Shachar Weis

  I'm trying to write a function : Input: Source range, Source value, output range, curve type (Linear, smooth) Output: The output is the "source value" converted into the "output range" according to the curve type. I hope I am making sense here... Any ideas ? Thanks.

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• What Math topics & resources to consider as beginner to indulge the book - Introduction to Algorithm

  - by sector7

  I'm a programmer who's beginning to appreciate the knowledge & usability of Algorithms in my work as I move forward with my skill-set. I don't want to take the short path by learning how to apply algorithms "as-is" but would rather like to know the foundation and fundamentals behind them. For that I need Math, at which I'm pretty "basic". I'm considering getting tuition's for that. What I would like is to have a concise syllabus/set of topics/book which I could hand over to my math tutor to get started. HIGHLY DESIRED: one book. the silver bullet. (fingers crossed!) PS: I've got some leads but want to hear you guys/gurus out: Discrete Math, Combinatorics, Graph theory, Calculus, Linear Algebra, and Number Theory. Looking forward to your answers. Thanks!

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• Class templating std::set key types

  - by TomFLuff

  I have a class to evaluate set algebra but wish to template it. At the minute it looks a bit like this set.h: template<typename T> class SetEvaluation { public: SetEvaluation<T>(); std::set<T> evaluate(std::string in_expression); } set.cpp template<typename T> std::set<T> SetEvaluation<T>::evaluate(std::string expression) { std::set<T> result; etc etc... } But i'm getting undefined reference errors when compiling. Is it possible to declare the return type as std::set<T> and then pass std::string as the class template param. There are no errors in the class but only when I try to instantiate SetEvaluation<std::string> Can anyone shed light on this problem? thanks

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• Algorithm to generate 1000 distinct integers in the range [0,8000]?

  - by The Last Ninja

  What are some alternative methods to generate 1000 distinct random integers in the range [0,8000] as opposed to the following: naive method: generating a number and checking if it's already in the array. O(n^2) linear shuffle: generate sequence 0 to 8000, shuffle, take the first 1000. O(n)

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• Is there a shorthand term for O(n log n)?

  - by jemfinch

  We usually have a single-word shorthand for most complexities we encounter in algorithmic analysis: O(1) == "constant" O(log n) == "logarithmic" O(n) == "linear" O(n^2) == "quadratic" O(n^3) == "cubic" O(2^n) == "exponential" We encounter algorithms with O(n log n) complexity with some regularity (think of all the algorithms dominated by sort complexity) but as far as I know, there's no single word we can use in English to refer to that complexity. Is this a gap in my knowledge, or a real gap in our English discourse on computational complexity?

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• How can I find the boundaries of a subset of a sorted list?

  - by Alex

  I have the following dilemma: I have a list of strings, and I want to find the set of string which start with a certain prefix. The list is sorted, so the naive solution is this: Perform binary search on the prefixes of the set, and when you find an element that starts with the prefix, traverse up linearly until you hit the top of the subset. This runs in linear time, however, and I was wondering if anyone can suggest a more efficient way to do it.

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• Number of the different elements in an array.

  - by AB

  Is it possible to compute the number of the different elements in an array in linear time and constant space? Let us say it's an array of long integers, and you can not allocate an array of length sizeof(long). P.S. Not homework, just curious. I've got a book that sort of implies that it is possible.

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• Mathematics and Game Programming

  - by Xfcn

  I want to program graphical 2D games more complex than the basic 2D stuff I already know. I don't want to do 3D programming. Just more complex 2D stuff. I dropped high school before I could learn a lot of stuff so I walked away with enough algebra knowledge to balance my checkbook and do some light 2D Cartesian programming. Are there any good resources out there for a guy with a limited attention span (say 20 minutes apiece for a subject I'm keenly interested in) to learn, gradually, how to do something more useful with math in programming?

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• A Guided Tour of Complexity

  - by JoshReuben

  I just re-read Complexity – A Guided Tour by Melanie Mitchell , protégé of Douglas Hofstadter ( author of “Gödel, Escher, Bach”) http://www.amazon.com/Complexity-Guided-Tour-Melanie-Mitchell/dp/0199798109/ref=sr_1_1?ie=UTF8&qid=1339744329&sr=8-1 here are some notes and links:   Evolved from Cybernetics, General Systems Theory, Synergetics some interesting transdisciplinary fields to investigate: Chaos Theory - http://en.wikipedia.org/wiki/Chaos_theory – small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for chaotic systems, rendering long-term prediction impossible. System Dynamics / Cybernetics - http://en.wikipedia.org/wiki/System_Dynamics – study of how feedback changes system behavior Network Theory - http://en.wikipedia.org/wiki/Network_theory – leverage Graph Theory to analyze symmetric  / asymmetric relations between discrete objects Algebraic Topology - http://en.wikipedia.org/wiki/Algebraic_topology – leverage abstract algebra to analyze topological spaces There are limits to deterministic systems & to computation. Chaos Theory definitely applies to training an ANN (artificial neural network) – different weights will emerge depending upon the random selection of the training set. In recursive Non-Linear systems http://en.wikipedia.org/wiki/Nonlinear_system – output is not directly inferable from input. E.g. a Logistic map: Xt+1 = R Xt(1-Xt) Different types of bifurcations, attractor states and oscillations may occur – e.g. a Lorenz Attractor http://en.wikipedia.org/wiki/Lorenz_system Feigenbaum Constants http://en.wikipedia.org/wiki/Feigenbaum_constants express ratios in a bifurcation diagram for a non-linear map – the convergent limit of R (the rate of period-doubling bifurcations) is 4.6692016 Maxwell’s Demon - http://en.wikipedia.org/wiki/Maxwell%27s_demon - the Second Law of Thermodynamics has only a statistical certainty – the universe (and thus information) tends towards entropy. While any computation can theoretically be done without expending energy, with finite memory, the act of erasing memory is permanent and increases entropy. Life & thought is a counter-example to the universe’s tendency towards entropy. Leo Szilard and later Claude Shannon came up with the Information Theory of Entropy - http://en.wikipedia.org/wiki/Entropy_(information_theory) whereby Shannon entropy quantifies the expected value of a message’s information in bits in order to determine channel capacity and leverage Coding Theory (compression analysis). Ludwig Boltzmann came up with Statistical Mechanics - http://en.wikipedia.org/wiki/Statistical_mechanics – whereby our Newtonian perception of continuous reality is a probabilistic and statistical aggregate of many discrete quantum microstates. This is relevant for Quantum Information Theory http://en.wikipedia.org/wiki/Quantum_information and the Physics of Information - http://en.wikipedia.org/wiki/Physical_information. Hilbert’s Problems http://en.wikipedia.org/wiki/Hilbert's_problems pondered whether mathematics is complete, consistent, and decidable (the Decision Problem – http://en.wikipedia.org/wiki/Entscheidungsproblem – is there always an algorithm that can determine whether a statement is true).  Godel’s Incompleteness Theorems http://en.wikipedia.org/wiki/G%C3%B6del's_incompleteness_theorems  proved that mathematics cannot be both complete and consistent (e.g. “This statement is not provable”). Turing through the use of Turing Machines (http://en.wikipedia.org/wiki/Turing_machine symbol processors that can prove mathematical statements) and Universal Turing Machines (http://en.wikipedia.org/wiki/Universal_Turing_machine Turing Machines that can emulate other any Turing Machine via accepting programs as well as data as input symbols) that computation is limited by demonstrating the Halting Problem http://en.wikipedia.org/wiki/Halting_problem (is is not possible to know when a program will complete – you cannot build an infinite loop detector). You may be used to thinking of 1 / 2 / 3 dimensional systems, but Fractal http://en.wikipedia.org/wiki/Fractal systems are defined by self-similarity & have non-integer Hausdorff Dimensions !!!  http://en.wikipedia.org/wiki/List_of_fractals_by_Hausdorff_dimension – the fractal dimension quantifies the number of copies of a self similar object at each level of detail – eg Koch Snowflake - http://en.wikipedia.org/wiki/Koch_snowflake Definitions of complexity: size, Shannon entropy, Algorithmic Information Content (http://en.wikipedia.org/wiki/Algorithmic_information_theory - size of shortest program that can generate a description of an object) Logical depth (amount of info processed), thermodynamic depth (resources required). Complexity is statistical and fractal. John Von Neumann’s other machine was the Self-Reproducing Automaton http://en.wikipedia.org/wiki/Self-replicating_machine  . Cellular Automata http://en.wikipedia.org/wiki/Cellular_automaton are alternative form of Universal Turing machine to traditional Von Neumann machines where grid cells are locally synchronized with their neighbors according to a rule. Conway’s Game of Life http://en.wikipedia.org/wiki/Conway's_Game_of_Life demonstrates various emergent constructs such as “Glider Guns” and “Spaceships”. Cellular Automatons are not practical because logical ops require a large number of cells – wasteful & inefficient. There are no compilers or general program languages available for Cellular Automatons (as far as I am aware). Random Boolean Networks http://en.wikipedia.org/wiki/Boolean_network are extensions of cellular automata where nodes are connected at random (not to spatial neighbors) and each node has its own rule –> they demonstrate the emergence of complex  & self organized behavior. Stephen Wolfram’s (creator of Mathematica, so give him the benefit of the doubt) New Kind of Science http://en.wikipedia.org/wiki/A_New_Kind_of_Science proposes the universe may be a discrete Finite State Automata http://en.wikipedia.org/wiki/Finite-state_machine whereby reality emerges from simple rules. I am 2/3 through this book. It is feasible that the universe is quantum discrete at the plank scale and that it computes itself – Digital Physics: http://en.wikipedia.org/wiki/Digital_physics – a simulated reality? Anyway, all behavior is supposedly derived from simple algorithmic rules & falls into 4 patterns: uniform , nested / cyclical, random (Rule 30 http://en.wikipedia.org/wiki/Rule_30) & mixed (Rule 110 - http://en.wikipedia.org/wiki/Rule_110 localized structures – it is this that is interesting). interaction between colliding propagating signal inputs is then information processing. Wolfram proposes the Principle of Computational Equivalence - http://mathworld.wolfram.com/PrincipleofComputationalEquivalence.html - all processes that are not obviously simple can be viewed as computations of equivalent sophistication. Meaning in information may emerge from analogy & conceptual slippages – see the CopyCat program: http://cognitrn.psych.indiana.edu/rgoldsto/courses/concepts/copycat.pdf Scale Free Networks http://en.wikipedia.org/wiki/Scale-free_network have a distribution governed by a Power Law (http://en.wikipedia.org/wiki/Power_law - much more common than Normal Distribution). They are characterized by hubs (resilience to random deletion of nodes), heterogeneity of degree values, self similarity, & small world structure. They grow via preferential attachment http://en.wikipedia.org/wiki/Preferential_attachment – tipping points triggered by positive feedback loops. 2 theories of cascading system failures in complex systems are Self-Organized Criticality http://en.wikipedia.org/wiki/Self-organized_criticality and Highly Optimized Tolerance http://en.wikipedia.org/wiki/Highly_optimized_tolerance. Computational Mechanics http://en.wikipedia.org/wiki/Computational_mechanics – use of computational methods to study phenomena governed by the principles of mechanics. This book is a great intuition pump, but does not cover the more mathematical subject of Computational Complexity Theory – http://en.wikipedia.org/wiki/Computational_complexity_theory I am currently reading this book on this subject: http://www.amazon.com/Computational-Complexity-Christos-H-Papadimitriou/dp/0201530821/ref=pd_sim_b_1   stay tuned for that review!

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• First impressions of Scala

  - by Scott Weinstein

  I have an idea that it may be possible to predict build success/failure based on commit data. Why Scala? It’s a JVM language, has lots of powerful type features, and it has a linear algebra library which I’ll need later. Project definition and build Neither maven or the scala build tool (sbt) are completely satisfactory. This maven **archetype** (what .Net folks would call a VS project template) mvn archetype:generate `-DarchetypeGroupId=org.scala-tools.archetypes `-DarchetypeArtifactId=scala-archetype-simple `-DremoteRepositories=http://scala-tools.org/repo-releases `-DgroupId=org.SW -DartifactId=BuildBreakPredictor gets you started right away with “hello world” code, unit tests demonstrating a number of different testing approaches, and even a ready made `.gitignore` file - nice! But the Scala version is behind at v2.8, and more seriously, compiling and testing was painfully slow. So much that a rapid edit – test – edit cycle was not practical. So Lab49 colleague Steve Levine tells me that I can either adjust my pom to use fsc – the fast scala compiler, or use sbt. Sbt has some nice features It’s fast – it uses fsc by default It has a continuous mode, so  `> ~test` will compile and run your unit test each time you save a file It’s can consume (and produce) Maven 2 dependencies the build definition file can be much shorter than the equivalent pom (about 1/5 the size, as repos and dependencies can be declared on a single line) And some real limitations Limited support for 3rd party integration – for instance out of the box, TeamCity doesn’t speak sbt, nor does IntelliJ IDEA Steeper learning curve for build steps outside the default Side note: If a language has a fast compiler, why keep the slow compiler around? Even worse, why make it the default? I choose sbt, for the faster development speed it offers. Syntax Scala APIs really like to use punctuation – sometimes this works well, as in the following map1 |+| map2 The `|+|` defines a merge operator which does addition on the `values` of the maps. It’s less useful here: http(baseUrl / url >- parseJson[BuildStatus] sure you can probably guess what `>-` does from the context, but how about `>~` or `>+`? Language features I’m still learning, so not much to say just yet. However case classes are quite usefull, implicits scare me, and type constructors have lots of power. Community A number of projects, such as https://github.com/scalala and https://github.com/scalaz/scalaz are split between github and google code – github for the src, and google code for the docs. Not sure I understand the motivation here.

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• StreamInsight and Reactive Framework Challenge

  In his blogpost Roman from the StreamInsight team asked if we could create a Reactive Framework version of what he had done in the post using StreamInsight.  For those who don’t know, the Reactive Framework or Rx to its friends is a library for composing asynchronous and event-based programs using observable collections in the .Net framework.  Yes, there is some overlap between StreamInsight and the Reactive Extensions but StreamInsight has more flexibility and power in its temporal algebra (Windowing, Alteration of event headers) Well here are two alternate ways of doing what Roman did. The first example is a mix of StreamInsight and Rx var rnd = new Random(); var RandomValue = 0; var interval = Observable.Interval(TimeSpan.FromMilliseconds((Int32)rnd.Next(500,3000))) .Select(i => { RandomValue = rnd.Next(300); return RandomValue; }); Server s = Server.Create("Default"); Microsoft.ComplexEventProcessing.Application a = s.CreateApplication("Rx SI Mischung"); var inputStream = interval.ToPointStream(a, evt => PointEvent.CreateInsert( System.DateTime.Now.ToLocalTime(), new { RandomValue = evt}), AdvanceTimeSettings.IncreasingStartTime, "Rx Sample"); var r = from evt in inputStream select new { runningVal = evt.RandomValue }; foreach (var x in r.ToPointEnumerable().Where(e => e.EventKind != EventKind.Cti)) { Console.WriteLine(x.Payload.ToString()); } This next version though uses the Reactive Extensions Only   var rnd = new Random(); var RandomValue = 0; Observable.Interval(TimeSpan.FromMilliseconds((Int32)rnd.Next(500, 3000))) .Select(i => { RandomValue = rnd.Next(300); return RandomValue; }).Subscribe(Console.WriteLine, () => Console.WriteLine("Completed")); Console.ReadKey();   These are very simple examples but both technologies allow us to do a lot more.  The ICEPObservable() design pattern was reintroduced in StreamInsight 1.1 and the more I use it the more I like it.  It is a very useful pattern when wanting to show StreamInsight samples as is the IEnumerable() pattern.

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• SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

  - by Brian

  Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

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• Oracle Expands Sun Blade Portfolio for Cloud and Highly Virtualized Environments

  - by Ferhat Hatay

  Oracle announced the expansion of Sun Blade Portfolio for cloud and highly virtualized environments that deliver powerful performance and simplified management as tightly integrated systems.  Along with the SPARC T3-1B blade server, Oracle VM blade cluster reference configuration and Oracle's optimized solution for Oracle WebLogic Suite, Oracle introduced the dual-node Sun Blade X6275 M2 server module with some impressive benchmark results.   Benchmarks on the Sun Blade X6275 M2 server module demonstrate the outstanding performance characteristics critical for running varied commercial applications used in cloud and highly virtualized environments.  These include best-in-class SPEC CPU2006 results with the Intel Xeon processor 5600 series, six Fluent world records and 1.8 times the price-performance of the IBM Power 755 running NAMD, a prominent bio-informatics workload.   Benchmarks for Sun Blade X6275 M2 server module  SPEC CPU2006  The Sun Blade X6275 M2 server module demonstrated best in class SPECint_rate2006 results for all published results using the Intel Xeon processor 5600 series, with a result of 679.  This result is 97% better than the HP BL460c G7 blade, 80% better than the IBM HS22V blade, and 79% better than the Dell M710 blade.  This result demonstrates the density advantage of the new Oracle's server module for space-constrained data centers.     Sun Blade X6275M2 (2 Nodes, Intel Xeon X5670 2.93GHz) - 679 SPECint_rate2006; HP ProLiant BL460c G7 (2.93 GHz, Intel Xeon X5670) - 347 SPECint_rate2006; IBM BladeCenter HS22V (Intel Xeon X5680)  - 377 SPECint_rate2006; Dell PowerEdge M710 (Intel Xeon X5680, 3.33 GHz) - 380 SPECint_rate2006.  SPEC, SPECint, SPECfp reg tm of Standard Performance Evaluation Corporation. Results from www.spec.org as of 11/24/2010 and this report.    For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   Fluent The Sun Fire X6275 M2 server module produced world-record results on each of the six standard cases in the current "FLUENT 12" benchmark test suite at 8-, 12-, 24-, 32-, 64- and 96-core configurations. These results beat the most recent QLogic score with IBM DX 360 M series platforms and QLogic "Truescale" interconnects.  Results on sedan_4m test case on the Sun Blade X6275 M2 server module are 23% better than the HP C7000 system, and 20% better than the IBM DX 360 M2; Dell has not posted a result for this test case.  Results can be found at the FLUENT website.   ANSYS's FLUENT software solves fluid flow problems, and is based on a numerical technique called computational fluid dynamics (CFD), which is used in the automotive, aerospace, and consumer products industries. The FLUENT 12 benchmark test suite consists of seven models that are well suited for multi-node clustered environments and representative of modern engineering CFD clusters. Vendors benchmark their systems with the principal objective of providing comparative performance information for FLUENT software that, among other things, depends on compilers, optimization, interconnect, and the performance characteristics of the hardware.   FLUENT application performance is representative of other commercial applications that require memory and CPU resources to be available in a scalable cluster-ready format.  FLUENT benchmark has six conventional test cases (eddy_417k, turbo_500k, aircraft_2m, sedan_4m, truck_14m, truck_poly_14m) at various core counts.   All information on the FLUENT website (http://www.fluent.com) is Copyrighted1995-2010 by ANSYS Inc. Results as of November 24, 2010. For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   NAMD Results on the Sun Blade X6275 M2 server module running NAMD (a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems) show up to a 1.8X better price/performance than IBM's Power 7-based system.  For space-constrained environments, the ultra-dense Sun Blade X6275 M2 server module provides a 1.7X better price/performance per rack unit than IBM's system.     IBM Power 755 4-way Cluster (16U). Total price for cluster: $324,212. See IBM United States Hardware Announcement 110-008, dated February 9, 2010, pp. 4, 21 and 39-46.  Sun Blade X6275 M2 8-Blade Cluster (10U). Total price for cluster:  $193,939. Price/performance and performance/RU comparisons based on f1ATPase molecule test results. Sun Blade X6275 M2 cluster: $3,568/step/sec, 5.435 step/sec/RU. IBM Power 755 cluster: $6,355/step/sec, 3.189 step/sec/U. See http://www-03.ibm.com/systems/power/hardware/reports/system_perf.html. See http://www.ks.uiuc.edu/Research/namd/performance.html for more information, results as of 11/24/10.   For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   Reverse Time Migration The Reverse Time Migration is heavily used in geophysical imaging and modeling for Oil & Gas Exploration.  The Sun Blade X6275 M2 server module showed up to a 40% performance improvement over the previous generation server module with super-linear scalability to 16 nodes for the 9-Point Stencil used in this Reverse Time Migration computational kernel.  The balanced combination of Oracle's Sun Storage 7410 system with the Sun Blade X6275 M2 server module cluster showed linear scalability for the total application throughput, including the I/O and MPI communication, to produce a final 3-D seismic depth imaged cube for interpretation. The final image write time from the Sun Blade X6275 M2 server module nodes to Oracle's Sun Storage 7410 system achieved 10GbE line speed of 1.25 GBytes/second or better performance. Between subsequent runs, the effects of I/O buffer caching on the Sun Blade X6275 M2 server module nodes and write optimized caching on the Sun Storage 7410 system gave up to 1.8 GBytes/second effective write performance. The performance results and characterization of this Reverse Time Migration benchmark could serve as a useful measure for many other I/O intensive commercial applications. 3D VTI Reverse Time Migration Seismic Depth Imaging, see http://blogs.sun.com/BestPerf/entry/3d_vti_reverse_time_migration for more information, results as of 11/14/2010.                            

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• Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

  - by aspiringgeek

  Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario   Conventional Structures   Columnstore   Δ SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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• Waterfall Model (SDLC) vs. Prototyping Model

  The characters in the fable of the Tortoise and the Hare can easily be used to demonstrate the similarities and differences between the Waterfall and Prototyping software development models. This children fable is about a race between a consistently slow moving but steadfast turtle and an extremely fast but unreliable rabbit. After closely comparing each character’s attributes in correlation with both software development models, a trend seems to appear in that the Waterfall closely resembles the Tortoise in that Waterfall Model is typically a slow moving process that is broken up in to multiple sequential steps that must be executed in a standard linear pattern. The Tortoise can be quoted several times in the story saying “Slow and steady wins the race.” This is the perfect mantra for the Waterfall Model in that this model is seen as a cumbersome and slow moving. Waterfall Model Phases Requirement Analysis & Definition This phase focuses on defining requirements for a project that is to be developed and determining if the project is even feasible. Requirements are collected by analyzing existing systems and functionality in correlation with the needs of the business and the desires of the end users. The desired output for this phase is a list of specific requirements from the business that are to be designed and implemented in the subsequent steps. In addition this phase is used to determine if any value will be gained by completing the project. System Design This phase focuses primarily on the actual architectural design of a system, and how it will interact within itself and with other existing applications. Projects at this level should be viewed at a high level so that actual implementation details are decided in the implementation phase. However major environmental decision like hardware and platform decision are typically decided in this phase. Furthermore the basic goal of this phase is to design an application at the system level in those classes, interfaces, and interactions are defined. Additionally decisions about scalability, distribution and reliability should also be considered for all decisions. The desired output for this phase is a functional  design document that states all of the architectural decisions that have been made in regards to the project as well as a diagrams like a sequence and class diagrams. Software Design This phase focuses primarily on the refining of the decisions found in the functional design document. Classes and interfaces are further broken down in to logical modules based on the interfaces and interactions previously indicated. The output of this phase is a formal design document. Implementation / Coding This phase focuses primarily on implementing the previously defined modules in to units of code. These units are developed independently are intergraded as the system is put together as part of a whole system. Software Integration & Verification This phase primarily focuses on testing each of the units of code developed as well as testing the system as a whole. There are basic types of testing at this phase and they include: Unit Test and Integration Test. Unit Test are built to test the functionality of a code unit to ensure that it preforms its desired task. Integration testing test the system as a whole because it focuses on results of combining specific units of code and validating it against expected results. The output of this phase is a test plan that includes test with expected results and actual results. System Verification This phase primarily focuses on testing the system as a whole in regards to the list of project requirements and desired operating environment. Operation & Maintenance his phase primarily focuses on handing off the competed project over to the customer so that they can verify that all of their requirements have been met based on their original requirements. This phase will also validate the correctness of their requirements and if any changed need to be made. In addition, any problems not resolved in the previous phase will be handled in this section. The Waterfall Model’s linear and sequential methodology does offer a project certain advantages and disadvantages. Advantages of the Waterfall Model Simplistic to implement and execute for projects and/or company wide Limited demand on resources Large emphasis on documentation Disadvantages of the Waterfall Model Completed phases cannot be revisited regardless if issues arise within a project Accurate requirement are never gather prior to the completion of the requirement phase due to the lack of clarification in regards to client’s desires. Small changes or errors that arise in applications may cause additional problems The client cannot change any requirements once the requirements phase has been completed leaving them no options for changes as they see their requirements changes as the customers desires change. Excess documentation Phases are cumbersome and slow moving Learn more about the Major Process in the Sofware Development Life Cycle and Waterfall Model. Conversely, the Hare shares similar traits with the prototyping software development model in that ideas are rapidly converted to basic working examples and subsequent changes are made to quickly align the project with customers desires as they are formulated and as software strays from the customers vision. The basic concept of prototyping is to eliminate the use of well-defined project requirements. Projects are allowed to grow as the customer needs and request grow. Projects are initially designed according to basic requirements and are refined as requirement become more refined. This process allows customer to feel their way around the application to ensure that they are developing exactly what they want in the application This model also works well for determining the feasibility of certain approaches in regards to an application. Prototypes allow for quickly developing examples of implementing specific functionality based on certain techniques. Advantages of Prototyping Active participation from users and customers Allows customers to change their mind in specifying requirements Customers get a better understanding of the system as it is developed Earlier bug/error detection Promotes communication with customers Prototype could be used as final production Reduced time needed to develop applications compared to the Waterfall method Disadvantages of Prototyping Promotes constantly redefining project requirements that cause major system rewrites Potential for increased complexity of a system as scope of the system expands Customer could believe the prototype as the working version. Implementation compromises could increase the complexity when applying updates and or application fixes When companies trying to decide between the Waterfall model and Prototype model they need to evaluate the benefits and disadvantages for both models. Typically smaller companies or projects that have major time constraints typically head for more of a Prototype model approach because it can reduce the time needed to complete the project because there is more of a focus on building a project and less on defining requirements and scope prior to the start of a project. On the other hand, Companies with well-defined requirements and time allowed to generate proper documentation should steer towards more of a waterfall model because they are in a position to obtain clarified requirements and have to design and optimal solution prior to the start of coding on a project.

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• MatheMagics - Guess My Age Method 1

  - by PointsToShare

  © 2011 By: Dov Trietsch. All rights reserved MatheMagic – Guess My Age – Method 1 The Mathemagician stands on the stage and asks an adult to do the following: ·         Do the next few steps on your calculator, or the calculator in your phone, or even on a piece of paper. ·         Do it silently! Don’t tell me the results until I ask for them directly ·         Compute a single digit multiple of 9 – any one of 9, 18, 27, … all the way to 81, will do. ·         Now multiply your age by 10 ·         Subtract the 9 multiple from this number. ·         Tell me the result. Notice that I don’t know which multiple of 9 you subtracted from 10 times your age. I will nonetheless immediately tell you what your age is. How do I do this? Let’s do the algebra. 10X – 9Y = 10X – 10Y + Y = 10(X – Y) + Y Now remember, you asked an adult, so his/her age is a two digit number (maybe even 3 digits), thus reducing it by the single digit multiplied by nine is still positive – the lowest is can be is 100 – 81 which yields 19. Now make two numbers out of the result. The last digit and the number before it. This number is X – Y or the age minus the single digit you selected. The last digit is this very single digit. This is always so regardless of the digit you selected. So… Add tis digit to the other number and you get back the age! Q.E.D Example: I am 76 years old and here is what happens when I do the steps 76 x 10 = 760 760 – 18 = 742 made of 74 and 2. My age is 74 + 2 760 – 81 = 679 made of 67 and 9. My age is 67 + 9 A note to the socially aware mathemagician – it is safer to do it with a man. The chances of a veracious answer are much, much higher! The trick may be accomplished on any 2 or 3 digit number, not just one’s age, but if you want to know your date’s age, it’s a good way to elicit it. That’s All Folks PS for more Ageless “Age” mathemagics go to www.mgsltns.com/games.htm and also here: http://geekswithblogs.net/PointsToShare/archive/2011/11/15/mathemagics---guess-my-age---method-2.aspx

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• CodePlex Daily Summary for Sunday, August 10, 2014

  CodePlex Daily Summary for Sunday, August 10, 2014Popular ReleasesWinForms MVP: WinForms MVP v1.0.1008.2014: Issues Fixed Issue 1 New Added MessageBus and AppState features. Added tests in support of the MessageBus and AppState features Added dependency injection support for Ninject. Added tests in support of the NinjectPresenterFactory.WP8 Native Access Webserver: Version alpha 0.5.3: Figured I should post a newer version. This build includes pretty broad registry browsing (especially if you can use the AllCapabilities version) and (in the AC version) also fairly broad file system access. It also includes the ability to download .REG files. There have been tons of bugfixes and performance improvements as well, plus a slightly better UI in both the app and the web interface. For more info, please read the forum post here: http://forum.xda-developers.com/showthread.php?t=23...ClosedXML - The easy way to OpenXML: ClosedXML 0.74.0: Many updates. See history.SEToolbox: SEToolbox 01.042.019 Release 1: Added RadioAntenna broadcast name to ship name detail. Added two additional columns for Asteroid material generation for Asteroid Fields. Added Mass and Block number columns to main display. Added Ellipsis to some columns on main display to reduce name confusion. Added correct SE version number in file when saving. Re-added in reattaching Motor when drag/dropping or importing ships (KeenSH have added RotorEntityId back in after removing it months ago). Added option to export and r...Instant Beautiful Browsing: IBB 14.3 Alpha: An alpha release of IBB. After 3 years of the last release this version is made from scratch, with tons of new features like: Make your own IBB aps. HTML 5. Better UI. Extreme Windows 8 resemblance. Photos. Store. Movement TONS of times smother compared to previous versions. Remember that this is AN ALPHA release, I hope I will have "IBB 14" finished by December. The documentation on how to create a new application for IBB will come next monthjQuery List DragSort: jQuery List DragSort 0.5.2: Fixed scrollContainer removing deprecated use of $.browser so should now work with latest version of jQuery. Added the ability to return false in dragEnd to revert sort order Project changes Added nuget package for dragsort https://www.nuget.org/packages/dragsort Converted repository from SVN to MercurialCRM 2013 One Click Navigation: CRM2013OneClickNavigation_1_0_0_4_managed.zip: Fixed some minor issues and added support for the following languages Spanish German French Italian Portuguese Russian Arabic Chinese Japanese Hindi Hebrew Korean Polish ThaiBraintree Client Library: Braintree 2.32.0: Allow credit card verification options to be passed outside of the nonce for PaymentMethod.create Allow billingaddress parameters and billingaddress_id to be passed outside of the nonce for PaymentMethod.create Add Subscriptions to paypal accounts Add PaymentMethod.update Add failonduplicatepaymentmethod option to PaymentMethod.create Add support for dispute webhooksThe Mario Kart 8 App: V1.0.2.1: First Codeplex release. WINDOWS INSTALLER ONLYAspose Java for Docx4j: Aspose.Words vs Docx4j - v 1.0: Release contain the Code Comparison for Features in Docx4j SDK and Aspose.Words What's New ?Following Examples: Accessing Document Properties Add Bookmarks Convert to Formats Delete Bookmarks Working with Comments Feedback and Suggestions Many more examples are available at Aspose Docs. Raise your queries and suggest more examples via Aspose Forums or via this social coding site.File System Security PowerShell Module: NTFSSecurity 2.4.1: Add-Access and Remove-Access now take multiple accoutsYourSqlDba: YourSqlDba 5.2.1.: This version improves alert message that comes a while after you install the script. First it says to get it from YourSqlDba.CodePlex.com If you don't want to update now, just-rerun the script from your installed version. To get actual version running just execute install.PrintVersionInfo. . You can go to source code / history and click on change set 72957 to see changes in the script.Manipulator: Manipulator: manipulatorXNB filetype plugin for Paint.NET: Paint.NET XNB plugin v0.4.0.0: CHANGELOG Reverted old incomplete changes. Updated library for compatibility with Paint .NET 4. Updated project to NET 4.5. Updated version to 0.4.0.0. INSTALLATION INSTRUCTIONS Extract the ZIP file to your Paint.NET\FileTypes folder.EdiFabric: Release 4.1: Changed MessageContextWix# (WixSharp) - managed interface for WiX: Release 1.0.0.0: Release 1.0.0.0 Custom UI Custom MSI Dialog Custom CLR Dialog External UIMath.NET Numerics: Math.NET Numerics v3.2.0: Linear Algebra: Vector.Map2 (map2 in F#), storage-optimized Linear Algebra: fix RemoveColumn/Row early index bound check (was not strict enough) Statistics: Entropy ~Jeff Mastry Interpolation: use Array.BinarySearch instead of local implementation ~Candy Chiu Resources: fix a corrupted exception message string Portable Build: support .Net 4.0 as well by using profile 328 instead of 344. .Net 3.5: F# extensions now support .Net 3.5 as well .Net 3.5: NuGet package now contains pro...Virto Commerce Enterprise Open Source eCommerce Platform (asp.net mvc): Virto Commerce 1.11: Virto Commerce Community Edition version 1.11. To install the SDK package, please refer to SDK getting started documentation To configure source code package, please refer to Source code getting started documentation This release includes many bug fixes and minor improvements. More details about this release can be found on our blog at http://blog.virtocommerce.com.BoxStarter: Boxstarter 2.4.80: Running the Setup.bat file will install Chocolatey if not present and then install the Boxstarter modules.ProjkyAddin ssms addin script shortcut ssmsaddin: projkyaddin source code and msi files.: projkyaddin source code and msi files.New ProjectsBolos: BolosBWQS - The BitWise Query Service: Generic object queries with a bitwise syntax.DocX Razor: A DocX scaffolding engine with Razor syntaxJQuery Simple Logger: Its a very simple jQuery extension for logging client side events. There are four levels of logging: Error, Warning, Info, Debug ???????: ???????QQ:2281595668，?????，????，????　　?????????????????????，??1998?7??????，??????????，?????????，?????????????，????????????????????????. ????????????????????，????????: ?????QQ:2281595668，?????，????，????。???????????????????，??????????????，????，?????????????????????，??????。???????，??????????????????????。????????，????????????，?????????: ???????????: ?????QQ:2281595668，?????，????，????。????????????????????????，????????????，??????98???????????，????，??????????，?????????. 　　?????????,????????????????，????????????????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????，???????????????????????!?????????????????????????????????????????????、?????????、??????、???????: ???????????: ?????QQ：2281595668，?????，????，????。???????????????????，??1998?7??????，??????????，?????????，?????????????，??????????????????????. ????????????????????，????????????????: ????????????: ???????????: ?????QQ：2281595668，?????，????，????。???????????????????，??????????????，????，?????????????????????，??????。??，??????????????????????。????????，????????????，??????，???????: ??????QQ:2281595668，?????，????，????。??????????????????，????????。????????????????、???????。??????????????。?????????????????,??????,??????,??????,??????????????，????????: ??????QQ:2281595668，?????，????，????　　????????????????????，????????。????????????????、???????。??????????????。???????????????????,??????,??????,??????,??????????????????: ???????????: ??????????: ?????QQ：2281595668，?????，????，????。???????????????????，??1998?7??????，??????????，?????????，?????????????，??????????????????????. ????????????????????，????????????????: ??????QQ:2281595668，?????，????，????　　 ????????????????????，??1998?7??????，??????????，??????? ????????，?????????????， ???????????????????????. ???????????????????????: ?????QQ:2281595668，?????，????，????。??????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，??????????，??????: ????????????: ??????QQ:2281595668，?????，????，????　　?????2004?，??????????????，??????????????????。?????? ?????，????????????????，????????????。????，????????????，????，??“??????”????????: ??????QQ:2281595668，?????，????，????。??????????????????????????，????????????!??????????????????????????????????????????、???????、????、??????、??????????。???????????????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????，???????????????????????!?????????????????????????????????????????????、?????????、??????、???????: ???????????: ?????QQ:2281595668，?????，????，????。?????????????????，????????。????????????????、???????。??????????????。????????????????,??????,??????,??????,??????????????，????,?????: ?????QQ：2281595668，?????，????，????。　　??????98???????????，???????????????????，????????????，????，??????????，?????????，?????????,????????????????，???????????，??????????: ??????????QQ:2281595668，?????，????，????　　?????2004?，??????????????，??????????????????。?????? ?????，????????????????，????????????。????，???????????，????，??“???????????: ?????QQ：2281595668，?????，????，????。??????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，??????????，?????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????????，????????????!?????????????????????????????????????????、???????、????、??????、???????????????: ????????????: ???????????: ?????QQ：2281595668，?????，????，????。???????????????????，??1998?7??????，??????????，?????????，?????????????，??????????????????????. ????????????????????，???????????????: ?????QQ：2281595668，?????，????，????。?????????????????，????????。????????????????、???????。??????????????。????????????????,??????,??????,??????,??????????????，????,?????: ?????QQ：2281595668，?????，????，????。　　??????98???????????，???????????????????，????????????，????，??????????，?????????，?????????,????????????????，???????????，??????????: ?????QQ:2281595668，?????，????，????。?????????????????!????????????????????????????????????????????、?????????、??????、????????、????????????。??????????，???????????，???????: ??????????????QQ:2281595668，?????，????，????　　????? ????????、??、??、??????????????????，???????，???????，?????????????，??????????????，?????、??????????、??、???，???????????: ?????QQ：2281595668，?????，????，????。??????????????????????????,??????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????;??????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????????，????????????!?????????????????????????????????????????、???????、????、??????、??????????????: ???????????: ????????????: ????????????: ????????????: ????????????QQ:2281595668，?????，????，????　　???????????1998?????????。????????????，???????????????，?????????????，???????????，?2003?????????????，????????????????????????: ?????????????: ???????QQ：2281595668，?????，????，????。???????????????????!????????????????????????????????????????????、?????????、??????、????????、????????????。??????????，??????????????: ??????QQ：2281595668，?????，????，????。???????????????????????????,???????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????????: ?????QQ：2281595668，?????，????，????。??????????1998?????????。????????????，???????????????，?????????????，???????????，?2003?????????????，????????????????????????????????: ?????QQ:2281595668，?????，????，????。????????????????????????，????????????，??????98???????????，????，??????????，?????????. 　　?????????,????????????????，????????????????: ?????QQ:2281595668，?????，????，????。?????????????????，????????。????????????????、???????。??????????????。????????????????,??????,??????,??????,??????????????，????,?????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????，???????????????????????!?????????????????????????????????????????????、?????????、??????、??????: ?????QQ:2281595668，?????，????，????。??????????????，??????、????、?????????????????????????，???????????? 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?????，????????????????，????????????。????，????????????，????，??“????????: ?????QQ:2281595668，?????，????，????。?????????????????????????，????????????!?????????????????????????????????????????、???????、????、??????、??????????。??????????????????: ?????QQ：2281595668，?????，????，????。?????????，??????????????????。?????? ?????，????????????????，????????????。????，???????????，????，??“??????”???? ?????，???????????????: ?????QQ：2281595668，?????，????，????。?????????????????，????????。????????????????、???????。??????????????。????????????????,??????,??????,??????,??????????????，????,??????: ????????????: ??????QQ:2281595668，?????，????，????　　????? ????????、??、??、??????????????????，???????，???????，?????????????，??????????????，?????、??????????、??、???，???????? ??????????: ?????QQ:2281595668，?????，????，????　　????? ????????、??、??、??????????????????，???????，???????，?????????????，??????????????，?????、??????????、??、???，???????? ?????，?????: ?????QQ:2281595668，?????，????，????。??????????????，?????????????????????，???????????????????????!?????????????????????????????????????????????、?????????、??????、???????: ??????QQ:2281595668，?????，????，????　　???????????????????????????,???????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????????: ??????QQ:2281595668，?????，????，????　　???????????????????????????,???????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????????: ??????QQ:2281595668，?????，????，????　　????? ????????、??、??、??????????????????，???????，???????，?????????????，??????????????，?????、??????????、??、???，???????? ??????????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????????，????????????!?????????????????????????????????????????、???????、????、??????、???????????????: ??????QQ:2281595668，?????，????，????。???????????????????????????,???????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;?????????: ????????????: ???????????: ?????QQ:2281595668，?????，????，????。??????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，??????????，?????: ?????QQ：2281595668，?????，????，????。?????????????????，????????。????????????????、???????。??????????????。????????????????,??????,??????,??????,??????????????，????,?????: ??????????: ????????????: ????????????: ??????????: ????? QQ:2281595668，?????，????，????。????? ?????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，???????????????: ??????QQ:2281595668，?????，????，????。????????????????????，??????????????，????，?????????????????????，??????。????????，??????????????????????。????????，????????????，??????: ??????QQ:2281595668，?????，????，????　　???????????????????????????,???????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;???????: ?????QQ:2281595668，?????，????，????。?????????????????!????????????????????????????????????????????、?????????、??????、????????、????????????。??????????，???????????，??????: ??????QQ:2281595668，?????，????，????　　???????????????????，????????????，???????98???????????，????，??????????，?????????. 　　?????????,????????????????，???????????，??????: ?????QQ：2281595668，?????，????，????。???????????????????，??????????????，????，?????????????????????，??????。??，??????????????????????。????????，????????????，??????，???????: ??????QQ:2281595668，?????，????，????。????????????????????，??????????????，????，?????????????????????，??????。????????，??????????????????????。????????，????????????，????????: ????????QQ:2281595668，?????，????，????　　????????????????????，????????。????????????????、???????。??????????????。???????????????????,??????,??????,??????,??????????????????: ????????QQ:2281595668，?????，????，????　　?????2004?，??????????????，??????????????????。?????? ?????，????????????????，????????????。????，??????????????，????，??“???????????: ???????????: ?????QQ:2281595668，?????，????，????。??????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，??????????，??????: ????????????: ??????QQ：2281595668，?????，????，????。????????????????????，??1998?7??????，??????????，?????????，?????????????，???????????????????????. ????????????????????，?????????????: ???????????: ?????QQ:2281595668，?????，????，????　　??????????1998?????????。????????????，???????????????，?????????????，???????????，?2003?????????????，???????????????????????????????: ?????QQ：2281595668，?????，????，????。??????????????????????????,??????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????;???????: ????????????QQ:2281595668，?????，????，????　　????? ????????、??、??、??????????????????，???????，???????，?????????????，??????????????，?????、??????????、??、???，??????????????: ??????QQ:2281595668，?????，????，????。??????????????????，????????。????????????????、???????。??????????????。?????????????????,??????,??????,??????,??????????????，????????: ????????????: ????????????QQ:2281595668，?????，????，????　　?????2004?，??????????????，??????????????????。?????? ?????，????????????????，????????????。????，????????????，????，??“????????: ???????????: ?????????????: ???????QQ:2281595668，?????，????，????。????????????????，?????????????????????，?????????????????????????!???????????????????????????????????????????????、?????????、??????: ??????QQ:2281595668，?????，????，????。???????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，??????????????: ?????QQ:2281595668，?????，????，????。??????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，??????????，??????: ???????????: ?????QQ:2281595668，?????，????，????。???????????????????，??????????????，????，?????????????????????，??????。???????，??????????????????????。????????，????????????，?????????: ??????QQ:2281595668，?????，????，????。??????????????????????????，????????????!??????????????????????????????????????????、???????、????、??????、??????????。????????????????: ??????QQ:2281595668，?????，????，????。????????????????????，??????????????，????，?????????????????????，??????。????????，??????????????????????。????????，????????????，??????: ??????QQ:2281595668，?????，????，????。?????????????????????????，????????????，???????98???????????，????，??????????，?????????. 　　?????????,????????????????，??????????????: ????????????: ???????????: ?????QQ:2281595668，?????，????，????。??????????????????????????,??????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????;???????: ????????????: ????????????: ??????QQ:2281595668，?????，????，????　　???????????????????，????????????，???????98???????????，????，??????????，?????????. 　　?????????,????????????????，???????????，???????: ??????QQ:2281595668，?????，????，????。???????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，???????????????: ??????QQ:2281595668，?????，????，????。???????????????，?????????????????????，????????????????????????!??????????????????????????????????????????????、?????????、?????????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????????，????????????!?????????????????????????????????????????、???????、????、??????、??????????????: ?????QQ：2281595668，?????，????，????。??????????????，?????????????????????????，????????????!?????????????????????????????????????????、???????、????、??????、???????????????: ??????QQ:2281595668，?????，????，????。???????????????????????????,???????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????????: ?????QQ:2281595668，?????，????，????　　????????????????????，????????。????????????????、???????。??????????????。???????????????????,??????,??????,??????,??????????????????: ?????QQ:2281595668，?????，????，????。　　?????????????、??、??、??????????????????，???????，???????，?????????????，??????????????，?????、??????????、??、???，?????????????，???????: ??????QQ:2281595668，?????，????，????。??????????????????!????????????????????????????????????????????、?????????、??????、????????、????????????。??????????，????????????????: ???????????: ?????QQ：2281595668，?????，????，????。　　??????98???????????，???????????????????，????????????，????，??????????，?????????，?????????,????????????????，???????????，??????????: ?????QQ：2281595668，?????，????，????。??????????1998?????????。????????????，???????????????，?????????????，???????????，?2003?????????????，?????????????????????????????????: ????????????: ????????????: ??????QQ:2281595668，?????，????，????。????????????????????，??????????????，????，?????????????????????，??????。??，??????????????????????。????????，????????????，????????????: ????????????: ???????????: ?????QQ：2281595668，?????，????，????。?????????，??????????????????。?????? ?????，????????????????，????????????。????，???????????，????，??“??????”???? ?????，???????????????: ?????QQ:2281595668，?????，????，????　　??????????????????????????,??????????,???????????????????????,???????:????,????;?????????????;??;??;????;????????;????;????;?????: ?????QQ：2281595668，?????，????，????。??????????????，??????、????、?????????????????????????，???????????? ??。???????????，??????????，???????????，????2000?，??????????，??????: ??????

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• Problem after resizing partition for Fedora under Vmware fusion

  - by user20196

  Hi, I am running FC9 under VMware Fusion 3.0 I wanted to resize my /dev/sda2 partition. In order to do that I did the following: 0. changed the size of the vmware file (under VMware settings). 1. rebooted the host to rescue mode without mounted disks 2. fdisk - removed & added /dev/sda2 - i had bigger /dev/sda2 3. lvm pvresize /dev/sda2 4. lvm pvdisplay - it showed me bigger size on /dev/VolGroup00 for /dev/sda2 5. lvm vgchange -a y - device-mapper: reload ioctl failed: Invalid argument - 2 logical volume(s) in volume group "VolGroup00" now active This is not true because there is no /dev/VolGroup00/LogVol00 My whole "/" disappeared. dmsetup table, shows: VolGroup00-LogVol01: 0 2097152 linear 8:2 38338944 VolGroup00-LogVol00: Can some one help me to solve this? Thank You.

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• LVM2 vs MDADM performance

  - by archer

  I've used MDADM + LVM2 on many boxes for quite a while. MDADM was serving for both RAID0 and RAID1 arrays, while LVM2 where used for logical volumes on top of MDADM. Recently I've found that LVM2 could be used w/o MDADM (thus minus one layer, as the result - less overhead) for both mirroring and stripping. However, some guys claims that READ PERFORMANCE on LVM2 for mirrored array is not that fast as for LVM2 (linear) on top of MDADM (RAID1) as LVM2 does not read from 2+ devices at a time, but use 2nd and higher devices in case of 1st device failure. MDADM reads from 2 devices at a time (even in mirrored mode). Who could confirm that?

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• Adding multiple gradients to object in Adobe Illustrator

  - by Vass

  Hi, I have an object which is a path (a nose to be specific). Now I want both a linear gradient and a radial gradient to be added to the object. So these must be separate gradient objects I guess, and I can't find a way to add multiple separate gradients to a complete path so do I duplicate the object and then apply a new gradient to each object? And what would the layer transparency features look like? Would the 'normal' overlay of the layers work? I am afraid of multiple shadows creating double dark regions, but maybe that is as its supposed to be if you think in terms of classical art and draw shadows in terms of each light obstruction.

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• Basic video editor for AVCHD Lite files?

  - by davr

  I have a camera (Panasonic Lumix GF-1) that outputs "AVCHD Lite" files, 720p h264 in a MTS container. I saw this question that said Movie Maker in Windows 7 supports AVCHD...but I just tried, and unfortunately it does not support AVCHD Lite. Are there any free or inexpensive non-linear video editors (NLE) that can natively handle AVCHD Lite files, without requiring some 3rd party driver? If not, are there any 3rd party drivers that are especially stable? (In my experience they usually have some problems...I got AVCHD Lite loading into VirtualDub using a 3rd party plugin, but it's very slow and sometimes crashes, and seeking takes ages.

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• Probability of failure with larger number of network elements

  - by MikeKulls

  I'm having a discussion with a work colleague. I'm saying that a network with 100 elements will have pretty much 10 times as many failures as a network with 10 elements, ie a tech will need to replace faulty hardware 10 times more often. He suggests that the failure rate doesn't go up in a linear fashion and the failure rate will be significantly less than 10x, in fact only slightly more failures. This is not the probability of an outage etc, we are just talking in relation to the amount of parts that a tech would need to swap out in a given time frame.

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