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  • What did you develop using a microcontroller?

    - by DR
    I've always been fascinated by microcontrollers and I'm planning to do a few hobby projects just to satisfy my inner geek :) I'm looking for ideas and motivation, so what did you develop using a microcontroller? If possible please state the microcontroller and/or development environment and an estimate on hardware costs beyond the basic equipment (if applicable). I'm interested in both successful and failed projects and any problems you encountered.

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  • How to bring Paging File usage metric to zero?

    - by AngryHacker
    I am trying to tune a SQL Server. Per Brent Ozar's Performance Tuning Video, he says the PerfMon's Paging File:%Usage should be zero or ridiculously close to it. The average metric on my box is around 1.341% The box has 18 GB of RAM, the SQL Server is off, the Commit Charge Total is 1GB and yet the PerfMon metric is not 0. The Performance of the Task Manager states that PF Usage is 1.23GB. What should I do to better tune the box?

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  • A reliable, Australia-based ASP.NET Web Hosting

    - by Leonardo
    In the excellent Secret Geek’s Building a Micro-ISV series, Leon Bambrick admits that he prefers to host his sites in the US because of the prices and proximity to his target market. For Australian companies and start-ups, what’s the best ASP.NET web hosting in the country? Should a company consider hosting its website overseas even if the potential market is in here?

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  • How to log size of cookies in request header with apache

    - by chrisst
    We have an issue on our site with cookies growing too large. We have already expanded the acceptable header size and throttled the cookie sizes for now, but I'd like to figure out what the average client's header sizes are, specifically of the cookies. I've created an apache log that captures the cookies being set on each request: LogFormat "%{Cookie}i" cookies But this just spits out the entire contents of all cookies in the header. Is there a way to have apache just log the size (or just length of the string) per request?

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  • hard drive sectors vs. tracks

    - by Phenom
    In one rotation, how many sectors are passed over and how many tracks are passed over? If you know the average value of sectors per track for a hard drive, how do you use this to estimate the number of cylinders? Do all modern hard drives have 63 sectors per track? Are there any hard drives that have more than this?

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  • Swap implication in Linux and way to increase it

    - by vimalnath
    I used top command to print this on Linux box: [root@localhost ~]# top top - 23:38:38 up 361 days, 12:16, 2 users, load average: 0.09, 0.06, 0.01 Tasks: 129 total, 2 running, 126 sleeping, 1 stopped, 0 zombie Cpu(s): 0.0% us, 0.2% sy, 0.0% ni, 96.5% id, 3.4% wa, 0.0% hi, 0.0% si Mem: 2074712k total, 1996948k used, 77764k free, 16632k buffers Swap: 1052248k total, 1052248k used, 0k free, 331540k cached I am not sure what Swap:0k free means in the last line. Is this normal behavior for a linux box to have value of 0 Thanks

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  • php mysql cpanel high cpu usage

    - by Megahostzone Santu
    server taking high cpu usage load average: 108.87, 105.92, 85.82 netstat -ntu | awk '{print $5}' | cut -d: -f1 | sort | uniq -c | sort -n Reselt showing too much connect from server IP cpanel Process Manager showing 19.4 | 0.5 | /usr/sbin/mysqld --basedir=/ --datadir=/var/lib/mysql --user=mysql --log-error=/var/lib/mysql/zebra546.serverstall.com.err --pid-file=/var/lib/mysql/zebra546.serverstall.com.pid 3.0 | 0.2 | /usr/bin/php /home/nowwatch/public_html/index.php

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  • What reasons are there NOT to use OpenID?

    - by cletus
    You see a fair bit (in the Geek community anyway) about OpenID. It seems like a good idea. I'm developing a website that will be targeted at a somewhat less geeky audience (but not quite Mom and Pops either) so I have to wonder if OpenID is going to be "too hard" for some audiences. What do you think? That aside, are there any other technical or non-technical reasons NOT to use OpenID?

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  • C++ Program performs better when piped

    - by ET1 Nerd
    I haven't done any programming in a decade. I wanted to get back into it, so I made this little pointless program as practice. The easiest way to describe what it does is with output of my --help codeblock: ./prng_bench --help ./prng_bench: usage: ./prng_bench $N $B [$T] This program will generate an N digit base(B) random number until all N digits are the same. Once a repeating N digit base(B) number is found, the following statistics are displayed: -Decimal value of all N digits. -Time & number of tries taken to randomly find. Optionally, this process is repeated T times. When running multiple repititions, averages for all N digit base(B) numbers are displayed at the end, as well as total time and total tries. My "problem" is that when the problem is "easy", say a 3 digit base 10 number, and I have it do a large number of passes the "total time" is less when piped to grep. ie: command ; command |grep took : ./prng_bench 3 10 999999 ; ./prng_bench 3 10 999999|grep took .... Pass# 999999: All 3 base(10) digits = 3 base(10). Time: 0.00005 secs. Tries: 23 It took 191.86701 secs & 99947208 tries to find 999999 repeating 3 digit base(10) numbers. An average of 0.00019 secs & 99 tries was needed to find each one. It took 159.32355 secs & 99947208 tries to find 999999 repeating 3 digit base(10) numbers. If I run the same command many times w/o grep time is always VERY close. I'm using srand(1234) for now, to test. The code between my calls to clock_gettime() for start and stop do not involve any stream manipulation, which would obviously affect time. I realize this is an exercise in futility, but I'd like to know why it behaves this way. Below is heart of the program. Here's a link to the full source on DB if anybody wants to compile and test. https://www.dropbox.com/s/6olqnnjf3unkm2m/prng_bench.cpp clock_gettime() requires -lrt. for (int pass_num=1; pass_num<=passes; pass_num++) { //Executes $passes # of times. clock_gettime(CLOCK_PROCESS_CPUTIME_ID, &temp_time); //get time start_time = timetodouble(temp_time); //convert time to double, store as start_time for(i=1, tries=0; i!=0; tries++) { //loops until 'comparison for' fully completes. counts reps as 'tries'. <------------ for (i=0; i<Ndigits; i++) //Move forward through array. | results[i]=(rand()%base); //assign random num of base to element (digit). | /*for (i=0; i<Ndigits; i++) //---Debug Lines--------------- | std::cout<<" "<<results[i]; //---a LOT of output.---------- | std::cout << "\n"; //---Comment/decoment to disable/enable.*/ // | for (i=Ndigits-1; i>0 && results[i]==results[0]; i--); //Move through array, != element breaks & i!=0, new digits drawn. -| } //If all are equal i will be 0, nested for condition satisfied. -| clock_gettime(CLOCK_PROCESS_CPUTIME_ID, &temp_time); //get time draw_time = (timetodouble(temp_time) - start_time); //convert time to dbl, subtract start_time, set draw_time to diff. total_time += draw_time; //add time for this pass to total. total_tries += tries; //add tries for this pass to total. /*Formated output for each pass: Pass# ---: All -- base(--) digits = -- base(10) Time: ----.---- secs. Tries: ----- (LINE) */ std::cout<<"Pass# "<<std::setw(width_pass)<<pass_num<<": All "<<Ndigits<<" base("<<base<<") digits = " <<std::setw(width_base)<<results[0]<<" base(10). Time: "<<std::setw(width_time)<<draw_time <<" secs. Tries: "<<tries<<"\n"; } if(passes==1) return 0; //No need for totals and averages of 1 pass. /* It took ----.---- secs & ------ tries to find --- repeating -- digit base(--) numbers. (LINE) An average of ---.---- secs & ---- tries was needed to find each one. (LINE)(LINE) */ std::cout<<"It took "<<total_time<<" secs & "<<total_tries<<" tries to find " <<passes<<" repeating "<<Ndigits<<" digit base("<<base<<") numbers.\n" <<"An average of "<<total_time/passes<<" secs & "<<total_tries/passes <<" tries was needed to find each one. \n\n"; return 0;

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  • Is data transfer response related to cable bandwidth limit?

    - by John Paku
    Hello, Before this, I'm using shared 100Mbps bandwidth. Its fast enough. And now, the server running dedicated 10Mbps bandwidth. When running 10Mbps, it takes more time to completely load the same page. The server bandwidth usage is small, with average less than 5Mbps. (I can see some website hosted at same data center loads very fast.)

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  • How to output a simple network activity plot in console in Linux?

    - by Vi.
    There's tload that plots load average. There's iftop that network usage as bars. How to do something like this: # tcpdump -i eth0 --plot 'host 1.2.3.4' 13:45:03 | | 0 in 0 out 13:45:04 |O | 0 in 1MB out 13:45:05 |OOOI | 500 KB in 4MB out 13:45:06 |OIIII | 6MB in 1MB out 13:45:07 | | 0 in 0 out 13:45:08 |IIIIIIIIIIII | 53M in 0 out

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  • Error codes for C++

    - by billy
    #include <iostream> #include <iomanip> using namespace std; //Global constant variable declaration const int MaxRows = 8, MaxCols = 10, SEED = 10325; //Functions Declaration void PrintNameHeader(ostream& out); void Fill2DArray(double ary[][MaxCols]); void Print2DArray(const double ary[][MaxCols]); double GetTotal(const double ary[][MaxCols]); double GetAverage(const double ary[][MaxCols]); double GetRowTotal(const double ary[][MaxCols], int theRow); double GetColumnTotal(const double ary[][MaxCols], int theRow); double GetHighestInRow(const double ary[][MaxCols], int theRow); double GetLowestInRow(const double ary[][MaxCols], int theRow); double GetHighestInCol(const double ary[][MaxCols], int theCol); double GetLowestInCol(const double ary[][MaxCols], int theCol); double GetHighest(const double ary[][MaxCols], int& theRow, int& theCol); double GetLowest(const double ary[][MaxCols], int& theRow, int& theCol); int main() { int theRow; int theCol; PrintNameHeader(cout); cout << fixed << showpoint << setprecision(1); srand(static_cast<unsigned int>(SEED)); double ary[MaxRows][MaxCols]; cout << "The seed value for random number generator is: " << SEED << endl; cout << endl; Fill2DArray(ary); Print2DArray(ary); cout << " The Total for all the elements in this array is: " << setw(7) << GetTotal(ary) << endl; cout << "The Average of all the elements in this array is: " << setw(7) << GetAverage(ary) << endl; cout << endl; cout << "The sum of each row is:" << endl; for(int index = 0; index < MaxRows; index++) { cout << "Row " << (index + 1) << ": " << GetRowTotal(ary, theRow) << endl; } cout << "The highest and lowest of each row is: " << endl; for(int index = 0; index < MaxCols; index++) { cout << "Row " << (index + 1) << ": " << GetHighestInRow(ary, theRow) << " " << GetLowestInRow(ary, theRow) << endl; } cout << "The highest and lowest of each column is: " << endl; for(int index = 0; index < MaxCols; index++) { cout << "Col " << (index + 1) << ": " << GetHighestInCol(ary, theRow) << " " << GetLowestInCol(ary, theRow) << endl; } cout << "The highest value in all the elements in this array is: " << endl; cout << GetHighest(ary, theRow, theCol) << "[" << theRow << "]" << "[" << theCol << "]" << endl; cout << "The lowest value in all the elements in this array is: " << endl; cout << GetLowest(ary, theRow, theCol) << "[" << theRow << "]" << "[" << theCol << "]" << endl; return 0; } //Define Functions void PrintNameHeader(ostream& out) { out << "*******************************" << endl; out << "* *" << endl; out << "* C.S M10A Spring 2010 *" << endl; out << "* Programming Assignment 10 *" << endl; out << "* Due Date: Thurs. Mar. 25 *" << endl; out << "*******************************" << endl; out << endl; } void Fill2DArray(double ary[][MaxCols]) { for(int index1 = 0; index1 < MaxRows; index1++) { for(int index2= 0; index2 < MaxCols; index2++) { ary[index1][index2] = (rand()%1000)/10; } } } void Print2DArray(const double ary[][MaxCols]) { cout << " Column "; for(int index = 0; index < MaxCols; index++) { int column = index + 1; cout << " " << column << " "; } cout << endl; cout << " "; for(int index = 0; index < MaxCols; index++) { int column = index +1; cout << "----- "; } cout << endl; for(int index1 = 0; index1 < MaxRows; index1++) { cout << "Row " << (index1 + 1) << ":"; for(int index2= 0; index2 < MaxCols; index2++) { cout << setw(6) << ary[index1][index2]; } } } double GetTotal(const double ary[][MaxCols]) { double total = 0; for(int theRow = 0; theRow < MaxRows; theRow++) { total = total + GetRowTotal(ary, theRow); } return total; } double GetAverage(const double ary[][MaxCols]) { double total = 0, average = 0; total = GetTotal(ary); average = total / (MaxRows * MaxCols); return average; } double GetRowTotal(const double ary[][MaxCols], int theRow) { double sum = 0; for(int index = 0; index < MaxCols; index++) { sum = sum + ary[theRow][index]; } return sum; } double GetColumTotal(const double ary[][MaxCols], int theCol) { double sum = 0; for(int index = 0; index < theCol; index++) { sum = sum + ary[index][theCol]; } return sum; } double GetHighestInRow(const double ary[][MaxCols], int theRow) { double highest = 0; for(int index = 0; index < MaxCols; index++) { if(ary[theRow][index] > highest) highest = ary[theRow][index]; } return highest; } double GetLowestInRow(const double ary[][MaxCols], int theRow) { double lowest = 0; for(int index = 0; index < MaxCols; index++) { if(ary[theRow][index] < lowest) lowest = ary[theRow][index]; } return lowest; } double GetHighestInCol(const double ary[][MaxCols], int theCol) { double highest = 0; for(int index = 0; index < MaxRows; index++) { if(ary[index][theCol] > highest) highest = ary[index][theCol]; } return highest; } double GetLowestInCol(const double ary[][MaxCols], int theCol) { double lowest = 0; for(int index = 0; index < MaxRows; index++) { if(ary[index][theCol] < lowest) lowest = ary[index][theCol]; } return lowest; } double GetHighest(const double ary[][MaxCols], int& theRow, int& theCol) { theRow = 0; theCol = 0; double highest = ary[theRow][theCol]; for(int index = 0; index < MaxRows; index++) { for(int index1 = 0; index1 < MaxCols; index1++) { double highest = 0; if(ary[index1][theCol] > highest) { highest = ary[index][index1]; theRow = index; theCol = index1; } } } return highest; } double Getlowest(const double ary[][MaxCols], int& theRow, int& theCol) { theRow = 0; theCol = 0; double lowest = ary[theRow][theCol]; for(int index = 0; index < MaxRows; index++) { for(int index1 = 0; index1 < MaxCols; index1++) { double lowest = 0; if(ary[index1][theCol] < lowest) { lowest = ary[index][index1]; theRow = index; theCol = index1; } } } return lowest; } . 1>------ Build started: Project: teddy lab 10, Configuration: Debug Win32 ------ 1>Compiling... 1>lab 10.cpp 1>c:\users\owner\documents\visual studio 2008\projects\teddy lab 10\teddy lab 10\ lab 10.cpp(46) : warning C4700: uninitialized local variable 'theRow' used 1>c:\users\owner\documents\visual studio 2008\projects\teddy lab 10\teddy lab 10\ lab 10.cpp(62) : warning C4700: uninitialized local variable 'theCol' used 1>Linking... 1> lab 10.obj : error LNK2028: unresolved token (0A0002E0) "double __cdecl GetLowest(double const (* const)[10],int &,int &)" (?GetLowest@@$$FYANQAY09$$CBNAAH1@Z) referenced in function "int __cdecl main(void)" (?main@@$$HYAHXZ) 1> lab 10.obj : error LNK2019: unresolved external symbol "double __cdecl GetLowest(double const (* const)[10],int &,int &)" (?GetLowest@@$$FYANQAY09$$CBNAAH1@Z) referenced in function "int __cdecl main(void)" (?main@@$$HYAHXZ) 1>C:\Users\owner\Documents\Visual Studio 2008\Projects\ lab 10\Debug\ lab 10.exe : fatal error LNK1120: 2 unresolved externals 1>Build log was saved at "file://c:\Users\owner\Documents\Visual Studio 2008\Projects\ lab 10\teddy lab 10\Debug\BuildLog.htm" 1>teddy lab 10 - 3 error(s), 2 warning(s) ========== Build: 0 succeeded, 1 failed, 0 up-to-date, 0 skipped ==========

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  • I have finally traded my Blackberry in for a Droid!

    - by Bob Porter
    Over the years I have used a number of different types of phones. Windows Mobile, Blackberry, Nokia, and now Android. Until the Blackberry, which was my last phone (and I still have one issued from my office) I had never found a phone that “just worked” especially with email and messaging. The Blackberry did, and does, excel at those functions. My last personal phone was a Storm 1 which was Blackberry’s first touch screen phone. The Storm 2 was an improved version that fixed some screen press detection issues from the first model and it added Wifi. Over the last few years I have watched others acquire and fall in love with their ‘Droid’s including a number of iPhone users which surprised me. Our office has until recently only supported Blackberry phones, adding iPhones within the last year or so. When I spoke with our internal telecom folks they confirmed they were evaluating Android phones, but felt they still were not secure enough out of the box for corporate use and SOX compliance. That being said, as a personal phone, the Droid Rocks! I am impressed with its speed, the number of apps available, and the overall design. It is not as “flashy” as an iPhone but it does everything that I care about and more. The model I bought is the Motorola Droid 2 Global from Verizon. It is currently running Android 2.2 for it’s OS, 2.3 is just around the corner. It has 8 gigs of internal flash memory and can handle up to a 32 gig SDCard. (I currently have 2 8 gig cards, one for backups, and have ordered a 16 gig card!) Being a geek at heart, I “rooted” the phone which means gained superuser access to the OS on the phone. And opens a number of doors for further modifications down the road. Also being a geek meant I have already setup a development environment and built and deployed the obligatory “Hello Droid” application. I will be writing of my development experiences with this new platform here often, to start off I thought I would share my current application list to give you an idea what I am using. Zedge: http://market.android.com/details?id=net.zedge.android XDA: http://market.android.com/details?id=com.quoord.tapatalkxda.activity WRAL.com: http://market.android.com/details?id=com.mylocaltv.wral Wireless Tether: http://market.android.com/details?id=android.tether Winamp: http://market.android.com/details?id=com.nullsoft.winamp Win7 Clock: http://market.android.com/details?id=com.androidapps.widget.toggles.win7 Wifi Analyzer: http://market.android.com/details?id=com.farproc.wifi.analyzer WeatherBug: http://market.android.com/details?id=com.aws.android Weather Widget Forecast Addon: http://market.android.com/details?id=com.androidapps.weather.forecastaddon Weather & Toggle Widgets: http://market.android.com/details?id=com.androidapps.widget.weather2 Vlingo: http://market.android.com/details?id=com.vlingo.client VirtualTENHO-G: http://market.android.com/details?id=jp.bustercurry.virtualtenho_g Twitter: http://market.android.com/details?id=com.twitter.android TweetDeck: http://market.android.com/details?id=com.thedeck.android.app Tricorder: http://market.android.com/details?id=org.hermit.tricorder Titanium Backup PRO: http://market.android.com/details?id=com.keramidas.TitaniumBackupPro Titanium Backup: http://market.android.com/details?id=com.keramidas.TitaniumBackup Terminal Emulator: http://market.android.com/details?id=jackpal.androidterm Talking Tom Free: http://market.android.com/details?id=com.outfit7.talkingtom Stock Blue: http://market.android.com/details?id=org.adw.theme.stockblue ST: Red Alert Free: http://market.android.com/details?id=com.oldplanets.redalertwallpaper ST: Red Alert: http://market.android.com/details?id=com.oldplanets.redalertwallpaperplus Solitaire: http://market.android.com/details?id=com.kmagic.solitaire Skype: http://market.android.com/details?id=com.skype.raider Silent Time Lite: http://market.android.com/details?id=com.QuiteHypnotic.SilentTime ShopSavvy: http://market.android.com/details?id=com.biggu.shopsavvy Shopper: http://market.android.com/details?id=com.google.android.apps.shopper Shiny clock: http://market.android.com/details?id=com.androidapps.clock.shiny ShareMyApps: http://market.android.com/details?id=com.mattlary.shareMyApps Sense Glass ADW Theme: http://market.android.com/details?id=com.dtanquary.senseglassadwtheme ROM Manager: http://market.android.com/details?id=com.koushikdutta.rommanager Roboform Bookmarklet Installer: http://market.android.com/details?id=roboformBookmarkletInstaller.android.com RealCalc: http://market.android.com/details?id=uk.co.nickfines.RealCalc Package Buddy: http://market.android.com/details?id=com.psyrus.packagebuddy Overstock: http://market.android.com/details?id=com.overstock OMGPOP Toggle: http://market.android.com/details?id=com.androidapps.widget.toggle.omgpop OI File Manager: http://market.android.com/details?id=org.openintents.filemanager nook: http://market.android.com/details?id=bn.ereader MyAtlas-Google Maps Navigation ext: http://market.android.com/details?id=com.adaptdroid.navbookfree3 MSN Droid: http://market.android.com/details?id=msn.droid.im Matrix Live Wallpaper: http://market.android.com/details?id=com.jarodyv.livewallpaper.matrix LogMeIn: http://market.android.com/details?id=com.logmein.ignitionpro.android Liveshare: http://market.android.com/details?id=com.cooliris.app.liveshare Kobo: http://market.android.com/details?id=com.kobobooks.android Instant Heart Rate: http://market.android.com/details?id=si.modula.android.instantheartrate IMDb: http://market.android.com/details?id=com.imdb.mobile Home Plus Weather: http://market.android.com/details?id=com.androidapps.widget.skin.weather.homeplus Handcent SMS: http://market.android.com/details?id=com.handcent.nextsms H7C Clock: http://market.android.com/details?id=com.androidapps.widget.clock.skin.h7c GTasks: http://market.android.com/details?id=org.dayup.gtask GPS Status: http://market.android.com/details?id=com.eclipsim.gpsstatus2 Google Voice: http://market.android.com/details?id=com.google.android.apps.googlevoice Google Sky Map: http://market.android.com/details?id=com.google.android.stardroid Google Reader: http://market.android.com/details?id=com.google.android.apps.reader GoMarks: http://market.android.com/details?id=com.androappsdev.gomarks Goggles: http://market.android.com/details?id=com.google.android.apps.unveil Glossy Black Weather: http://market.android.com/details?id=com.androidapps.widget.weather.skin.glossyblack Fox News: http://market.android.com/details?id=com.foxnews.android Foursquare: http://market.android.com/details?id=com.joelapenna.foursquared FBReader: http://market.android.com/details?id=org.geometerplus.zlibrary.ui.android Fandango: http://market.android.com/details?id=com.fandango Facebook: http://market.android.com/details?id=com.facebook.katana Extensive Notes Pro: http://market.android.com/details?id=com.flufflydelusions.app.extensive_notes_donate Expense Manager: http://market.android.com/details?id=com.expensemanager Espresso UI (LightShow w/ Slide): http://market.android.com/details?id=com.jaguirre.slide.lightshow Engadget: http://market.android.com/details?id=com.aol.mobile.engadget Earth: http://market.android.com/details?id=com.google.earth Drudge: http://market.android.com/details?id=com.iavian.dreport Dropbox: http://market.android.com/details?id=com.dropbox.android DroidForums: http://market.android.com/details?id=com.quoord.tapatalkdrodiforums.activity DroidArmor ADW: http://market.android.com/details?id=mobi.addesigns.droidarmorADW Droid Weather Icons: http://market.android.com/details?id=com.androidapps.widget.weather.skins.white Droid 2 Bootstrapper: http://market.android.com/details?id=com.koushikdutta.droid2.bootstrap doubleTwist: http://market.android.com/details?id=com.doubleTwist.androidPlayer Documents To Go: http://market.android.com/details?id=com.dataviz.docstogo Digital Clock Widget: http://market.android.com/details?id=com.maize.digitalClock Desk Home: http://market.android.com/details?id=com.cowbellsoftware.deskdock Default Clock: http://market.android.com/details?id=com.androidapps.widget.clock.skins.defaultclock Daily Expense Manager: http://market.android.com/details?id=com.techahead.ExpenseManager ConnectBot: http://market.android.com/details?id=org.connectbot Colorized Weather Icons: http://market.android.com/details?id=com.androidapps.widget.weather.colorized Chrome to Phone: http://market.android.com/details?id=com.google.android.apps.chrometophone CardStar: http://market.android.com/details?id=com.cardstar.android Books: http://market.android.com/details?id=com.google.android.apps.books Black Ipad Toggle: http://market.android.com/details?id=com.androidapps.toggle.widget.skin.blackipad Black Glass ADW Theme: http://market.android.com/details?id=com.dtanquary.blackglassadwtheme Bing: http://market.android.com/details?id=com.microsoft.mobileexperiences.bing BeyondPod Unlock Key: http://market.android.com/details?id=mobi.beyondpod.unlockkey BeyondPod: http://market.android.com/details?id=mobi.beyondpod BeejiveIM: http://market.android.com/details?id=com.beejive.im Beautiful Widgets Animations Addon: http://market.android.com/details?id=com.levelup.bw.forecast Beautiful Widgets: http://market.android.com/details?id=com.levelup.beautifulwidgets Beautiful Live Weather: http://market.android.com/details?id=com.levelup.beautifullive BBC News: http://market.android.com/details?id=net.jimblackler.newswidget Barnacle Wifi Tether: http://market.android.com/details?id=net.szym.barnacle Barcode Scanner: http://market.android.com/details?id=com.google.zxing.client.android ASTRO SMB Module: http://market.android.com/details?id=com.metago.astro.smb ASTRO Pro: http://market.android.com/details?id=com.metago.astro.pro ASTRO Bluetooth Module: http://market.android.com/details?id=com.metago.astro.network.bluetooth ASTRO: http://market.android.com/details?id=com.metago.astro AppBrain App Market: http://market.android.com/details?id=com.appspot.swisscodemonkeys.apps App Drawer Icon Pack: http://market.android.com/details?id=com.adwtheme.appdrawericonpack androidVNC: http://market.android.com/details?id=android.androidVNC AndroidGuys: http://market.android.com/details?id=com.handmark.mpp.AndroidGuys Android System Info: http://market.android.com/details?id=com.electricsheep.asi AndFTP: http://market.android.com/details?id=lysesoft.andftp ADWTheme Red: http://market.android.com/details?id=adw.theme.red ADWLauncher EX: http://market.android.com/details?id=org.adwfreak.launcher ADW.Theme.One: http://market.android.com/details?id=org.adw.theme.one ADW.Faded theme: http://market.android.com/details?id=com.xrcore.adwtheme.faded ADW Gingerbread: http://market.android.com/details?id=me.robertburns.android.adwtheme.gingerbread Advanced Task Killer Free: http://market.android.com/details?id=com.rechild.advancedtaskkiller Adobe Reader: http://market.android.com/details?id=com.adobe.reader Adobe Flash Player 10.1: http://market.android.com/details?id=com.adobe.flashplayer Adobe AIR: http://market.android.com/details?id=com.adobe.air 3G Auto OnOff: http://market.android.com/details?id=com.yuantuo --- Generated by ShareMyApps http://market.android.com/details?id=com.mattlary.shareMyApps Sent from my Droid

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  • Announcing SonicAgile – An Agile Project Management Solution

    - by Stephen.Walther
    I’m happy to announce the public release of SonicAgile – an online tool for managing software projects. You can register for SonicAgile at www.SonicAgile.com and start using it with your team today. SonicAgile is an agile project management solution which is designed to help teams of developers coordinate their work on software projects. SonicAgile supports creating backlogs, scrumboards, and burndown charts. It includes support for acceptance criteria, story estimation, calculating team velocity, and email integration. In short, SonicAgile includes all of the tools that you need to coordinate work on a software project, get stuff done, and build great software. Let me discuss each of the features of SonicAgile in more detail. SonicAgile Backlog You use the backlog to create a prioritized list of user stories such as features, bugs, and change requests. Basically, all future work planned for a product should be captured in the backlog. We focused our attention on designing the user interface for the backlog. Because the main function of the backlog is to prioritize stories, we made it easy to prioritize a story by just drag and dropping the story from one location to another. We also wanted to make it easy to add stories from the product backlog to a sprint backlog. A sprint backlog contains the stories that you plan to complete during a particular sprint. To add a story to a sprint, you just drag the story from the product backlog to the sprint backlog. Finally, we made it easy to track team velocity — the average amount of work that your team completes in each sprint. Your team’s average velocity is displayed in the backlog. When you add too many stories to a sprint – in other words, you attempt to take on too much work – you are warned automatically: SonicAgile Scrumboard Every workday, your team meets to have their daily scrum. During the daily scrum, you can use the SonicAgile Scrumboard to see (at a glance) what everyone on the team is working on. For example, the following scrumboard shows that Stephen is working on the Fix Gravatar Bug story and Pete and Jane have finished working on the Product Details Page story: Every story can be broken into tasks. For example, to create the Product Details Page, you might need to create database objects, do page design, and create an MVC controller. You can use the Scrumboard to track the state of each task. A story can have acceptance criteria which clarify the requirements for the story to be done. For example, here is how you can specify the acceptance criteria for the Product Details Page story: You cannot close a story — and remove the story from the list of active stories on the scrumboard — until all tasks and acceptance criteria associated with the story are done. SonicAgile Burndown Charts You can use Burndown charts to track your team’s progress. SonicAgile supports Release Burndown, Sprint Burndown by Task Estimates, and Sprint Burndown by Story Points charts. For example, here’s a sample of a Sprint Burndown by Story Points chart: The downward slope shows the progress of the team when closing stories. The vertical axis represents story points and the horizontal axis represents time. Email Integration SonicAgile was designed to improve your team’s communication and collaboration. Most stories and tasks require discussion to nail down exactly what work needs to be done. The most natural way to discuss stories and tasks is through email. However, you don’t want these discussions to get lost. When you use SonicAgile, all email discussions concerning a story or a task (including all email attachments) are captured automatically. At any time in the future, you can view all of the email discussion concerning a story or a task by opening the Story Details dialog: Why We Built SonicAgile We built SonicAgile because we needed it for our team. Our consulting company, Superexpert, builds websites for financial services, startups, and large corporations. We have multiple teams working on multiple projects. Keeping on top of all of the work that needs to be done to complete a software project is challenging. You need a good sense of what needs to be done, who is doing it, and when the work will be done. We built SonicAgile because we wanted a lightweight project management tool which we could use to coordinate the work that our team performs on software projects. How We Built SonicAgile We wanted SonicAgile to be easy to use, highly scalable, and have a highly interactive client interface. SonicAgile is very close to being a pure Ajax application. We built SonicAgile using ASP.NET MVC 3, jQuery, and Knockout. We would not have been able to build such a complex Ajax application without these technologies. Almost all of our MVC controller actions return JSON results (While developing SonicAgile, I would have given my left arm to be able to use the new ASP.NET Web API). The controller actions are invoked from jQuery Ajax calls from the browser. We built SonicAgile on Windows Azure. We are taking advantage of SQL Azure, Table Storage, and Blob Storage. Windows Azure enables us to scale very quickly to handle whatever demand is thrown at us. Summary I hope that you will try SonicAgile. You can register at www.SonicAgile.com (there’s a free 30-day trial). The goal of SonicAgile is to make it easier for teams to get more stuff done, work better together, and build amazing software. Let us know what you think!

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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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  • Silverlight Cream Top Posted Authors June to November, 2010

    - by Dave Campbell
    It's just past the first of December, but I've been busy and it's now time to recognize devs that have a large number of posts in Silverlight Cream. Ground Rules I pick what posts are on the blog Only posts that go in the database are included The author has to appear in SC at least 4 of the 6 months considered I averaged the monthly posts and am only showing Authors with an average greater than 1. Here are the Top Posted Authors at Silverlight Cream for June 1, 2010 through November 30, 2010: It is my intention to post a new list sometime shortly after the 1st of every month to recognize the top posted in the previous 6 months, so next up is January 1! Some other metrics for Silverlight Cream: At the time of this posting there are 7087 articles aggregated and searchable by partial Author, partial Title, keywords (in the synopsis), or partial URL. There are also 116 tags by which the articles can be searched. At the time of this posting there are 664 articles tagged wp7dev. Stay in the 'Light!

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  • ClickThrough on Google Webmaster Tool and Traffic Source in Google Analytics

    - by Svetlana
    I'm new to SEO and website management, but eager to learn. I manage a newly revamped site and I'm tracking it on Google Analytics and in Google Webmaster tools. The Webmaster tools show that I get about 3200 impressions and 180 click through's a week. Google Analytics show that no traffic comes from search engins, all of the traffic is direct. On average, I get about 60-80 visitors a day, shouldn't Google Analytics show at least a few of those visitors as having come from the search engines?. What does that discrepancy mean? I can't seem to wrap my mind around it... Thank you in advance, Svetlana

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  • World Record Oracle Business Intelligence Benchmark on SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server configured with four SPARC T4 3.0 GHz processors delivered the first and best performance of 25,000 concurrent users on Oracle Business Intelligence Enterprise Edition (BI EE) 11g benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 10. A SPARC T4-4 server running Oracle Business Intelligence Enterprise Edition 11g achieved 25,000 concurrent users with an average response time of 0.36 seconds with Oracle BI server cache set to ON. The benchmark data clearly shows that the underlying hardware, SPARC T4 server, and the Oracle BI EE 11g (11.1.1.6.0 64-bit) platform scales within a single system supporting 25,000 concurrent users while executing 415 transactions/sec. The benchmark demonstrated the scalability of Oracle Business Intelligence Enterprise Edition 11g 11.1.1.6.0, which was deployed in a vertical scale-out fashion on a single SPARC T4-4 server. Oracle Internet Directory configured on SPARC T4 server provided authentication for the 25,000 Oracle BI EE users with sub-second response time. A SPARC T4-4 with internal Solid State Drive (SSD) using the ZFS file system showed significant I/O performance improvement over traditional disk for the Web Catalog activity. In addition, ZFS helped get past the UFS limitation of 32767 sub-directories in a Web Catalog directory. The multi-threaded 64-bit Oracle Business Intelligence Enterprise Edition 11g and SPARC T4-4 server proved to be a successful combination by providing sub-second response times for the end user transactions, consuming only half of the available CPU resources at 25,000 concurrent users, leaving plenty of head room for increased load. The Oracle Business Intelligence on SPARC T4-4 server benchmark results demonstrate that comprehensive BI functionality built on a unified infrastructure with a unified business model yields best-in-class scalability, reliability and performance. Oracle BI EE 11g is a newer version of Business Intelligence Suite with richer and superior functionality. Results produced with Oracle BI EE 11g benchmark are not comparable to results with Oracle BI EE 10g benchmark. Oracle BI EE 11g is a more difficult benchmark to run, exercising more features of Oracle BI. Performance Landscape Results for the Oracle BI EE 11g version of the benchmark. Results are not comparable to the Oracle BI EE 10g version of the benchmark. Oracle BI EE 11g Benchmark System Number of Users Response Time (sec) 1 x SPARC T4-4 (4 x SPARC T4 3.0 GHz) 25,000 0.36 Results for the Oracle BI EE 10g version of the benchmark. Results are not comparable to the Oracle BI EE 11g version of the benchmark. Oracle BI EE 10g Benchmark System Number of Users 2 x SPARC T5440 (4 x SPARC T2+ 1.6 GHz) 50,000 1 x SPARC T5440 (4 x SPARC T2+ 1.6 GHz) 28,000 Configuration Summary Hardware Configuration: SPARC T4-4 server 4 x SPARC T4-4 processors, 3.0 GHz 128 GB memory 4 x 300 GB internal SSD Storage Configuration: "> Sun ZFS Storage 7120 16 x 146 GB disks Software Configuration: Oracle Solaris 10 8/11 Oracle Solaris Studio 12.1 Oracle Business Intelligence Enterprise Edition 11g (11.1.1.6.0) Oracle WebLogic Server 10.3.5 Oracle Internet Directory 11.1.1.6.0 Oracle Database 11g Release 2 Benchmark Description Oracle Business Intelligence Enterprise Edition (Oracle BI EE) delivers a robust set of reporting, ad-hoc query and analysis, OLAP, dashboard, and scorecard functionality with a rich end-user experience that includes visualization, collaboration, and more. The Oracle BI EE benchmark test used five different business user roles - Marketing Executive, Sales Representative, Sales Manager, Sales Vice-President, and Service Manager. These roles included a maximum of 5 different pre-built dashboards. Each dashboard page had an average of 5 reports in the form of a mix of charts, tables and pivot tables, returning anywhere from 50 rows to approximately 500 rows of aggregated data. The test scenario also included drill-down into multiple levels from a table or chart within a dashboard. The benchmark test scenario uses a typical business user sequence of dashboard navigation, report viewing, and drill down. For example, a Service Manager logs into the system and navigates to his own set of dashboards using Service Manager. The BI user selects the Service Effectiveness dashboard, which shows him four distinct reports, Service Request Trend, First Time Fix Rate, Activity Problem Areas, and Cost Per Completed Service Call spanning 2002 to 2005. The user then proceeds to view the Customer Satisfaction dashboard, which also contains a set of 4 related reports, drills down on some of the reports to see the detail data. The BI user continues to view more dashboards – Customer Satisfaction and Service Request Overview, for example. After navigating through those dashboards, the user logs out of the application. The benchmark test is executed against a full production version of the Oracle Business Intelligence 11g Applications with a fully populated underlying database schema. The business processes in the test scenario closely represent a real world customer scenario. See Also SPARC T4-4 Server oracle.com OTN Oracle Business Intelligence oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN WebLogic Suite oracle.com OTN Oracle Solaris oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 30 September 2012.

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  • The DOS DEBUG Environment

    - by MarkPearl
    Today I thought I would go back in time and have a look at the DEBUG command that has been available since the beginning of dawn in DOS, MS-DOS and Microsoft Windows. up to today I always knew it was there, but had no clue on how to use it so for those that are interested this might be a great geek party trick to pull out when you want the awe the younger generation and want to show them what “real” programming is about. But wait, you will have to do it relatively quickly as it seems like DEBUG was finally dumped from the Windows group in Windows 7. Not to worry, pull out that Windows XP box which will get you even more geek points and you can still poke DEBUG a bit. So, for those that are interested and want to find out a bit about the history of DEBUG read the wiki link here. That all put aside, lets get our hands dirty.. How to Start DEBUG in Windows Make sure your version of Windows supports DEBUG. Open up a console window Make a directory where you want to play with debug – in my instance I called it C221 Enter the directory and type Debug You will get a response with a – as illustrated in the image below…   The commands available in DEBUG There are several commands available in DEBUG. The most common ones are A (Assemble) R (Register) T (Trace) G (Go) D (Dump or Display) U (Unassemble) E (Enter) P (Proceed) N (Name) L (Load) W (Write) H (Hexadecimal) I (Input) O (Output) Q (Quit) I am not going to cover all these commands, but what I will do is go through a few of them briefly. A is for Assemble Command (to write code) The A command translates assembly language statements into machine code. It is quite useful for writing small assembly programs. Below I have written a very basic assembly program. The code typed out is as follows mov ax,0015 mov cx,0023 sub cx,ax mov [120],al mov cl,[120]A nop R is for Register (to jump to a point in memory) The r command turns out to be one of the most frequent commands you will use in DEBUG. It allows you to view the contents of registers and to change their values. It can be used with the following combinations… R – Displays the contents of all the registers R f – Displays the flags register R register_name – Displays the contents of a specific register All three methods are illustrated in the image above T is for Trace (To execute a program step by step) The t command allows us to execute the program step by step. Before we can trace the program we need to point back to the beginning of the program. We do this by typing in r ip, which moves us back to memory point 100. We then type trace which executes the first line of code (line 100) (As shown in the image below starting from the red arrow). You can see from the above image that the register AX now contains 0015 as per our instruction mov ax,0015 You can also see that the IP points to line 0103 which has the MOV CX,0023 command If we type t again it will now execute the second line of the program which moves 23 in the cx register. Again, we can see that the line of code was executed and that the CX register now holds the value of 23. What I would like to highlight now is the section underlined in red. These are the status flags. The ones we are going to look at now are 1st (NV), 4th (PL), 5th (NZ) & 8th (NC) NV means no overflow, the alternate would be OV PL means that the sign of the previous arithmetic operation was Plus, the alternate would be NG (Negative) NZ means that the results of the previous arithmetic operation operation was Not Zero, the alternate would be ZR NC means that No final Carry resulted from the previous arithmetic operation. CY means that there was a final Carry. We could now follow this process of entering the t command until the entire program is executed line by line. G is for Go (To execute a program up to a certain line number) So we have looked at executing a program line by line, which is fine if your program is minuscule BUT totally unpractical if we have any decent sized program. A quicker way to run some lines of code is to use the G command. The ‘g’ command executes a program up to a certain specified point. It can be used in connection with the the reset IP command. You would set your initial point and then run the G command with the line you want to end on. P is for Proceed (Similar to trace but slightly more streamlined) Another command similar to trace is the proceed command. All that the p command does is if it is called and it encounters a CALL, INT or LOOP command it terminates the program execution. In the example below I modified our example program to include an int 20 at the end of it as illustrated in the image below… Then when executing the code when I encountered the int 20 command I typed the P command and the program terminated normally (illustrated below). D is for Dump (or for those more polite Display) So, we have all these assembly lines of code, but if you have ever opened up an exe or com file in a text/hex editor, it looks nothing like assembly code. The D command is a way that we can see what our code looks like in memory (or in a hex editor). If we examined the image above, we can see that Debug is storing our assembly code with each instruction following immediately after the previous one. For instance in memory address 110 we have int and 111 we have 20. If we examine the dump of memory we can see at memory point 110 CD is stored and at memory point 111 20 is stored. U is for Unassemble (or Convert Machine code to Assembly Code) So up to now we have gone through a bunch of commands, but probably one of the most useful is the U command. Let’s say we don’t understand machine code so well and so instead we want to see it in its equivalent assembly code. We can type the U command followed by the start memory point, followed by the end memory point and it will show us the assembly code equivalent of the machine code. E is for a bunch of things… The E command can be used for a bunch of things… One example is to enter data or machine code instructions directly into memory. It can also be used to display the contents of memory locations. I am not going to worry to much about it in this post. N / L / W is for Name, Load & Write So we have written out assembly code in debug, and now we want to save it to disk, or write it as a com file or load it. This is where the N, L & W command come in handy. The n command is used to give a name to the executable program file and is pretty simple to use. The w command is a bit trickier. It saves to disk all the memory between point bx and point cx so you need to specify the bx memory address and the cx memory address for it to write your code. Let’s look at an example illustrated below. You do this by calling the r command followed by the either bx or cx. We can then go to the directory where we were working and will see the new file with the name we specified. The L command is relatively simple. You would first specify the name of the file you would like to load using the N command, and then call the L command. Q is for Quit The last command that I am going to write about in this post is the Q command. Simply put, calling the Q command exits DEBUG. Commands we did not Cover Out of the standard DEBUG commands we covered A, T, G, D, U, E, P, R, N, L & W. The ones we did not cover were H, I & O – I might make mention of these in a later post, but for the basics they are not really needed. Some Useful Resources Please note this post is based on the COS2213 handouts for UNISA A Guide to DEBUG - http://mirror.href.com/thestarman/asm/debug/debug.htm#NT

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  • HDFC Bank's Journey to Oracle Private Database Cloud

    - by Nilesh Agrawal
    One of the key takeaways from a recent post by Sushil Kumar is the importance of business initiative that drives the transformational journey from legacy IT to enterprise private cloud. The journey that leads to a agile, self-service and efficient infrastructure with reduced complexity and enables IT to deliver services more closely aligned with business requirements. Nilanjay Bhattacharjee, AVP, IT of HDFC Bank presented a real-world case study based on one such initiative in his Oracle OpenWorld session titled "HDFC BANK Journey into Oracle Database Cloud with EM 12c DBaaS". The case study highlighted in this session is from HDFC Bank’s Lending Business Segment, which comprises roughly 50% of Bank’s top line. Bank’s Lending Business is always under pressure to launch “New Schemes” to compete and stay ahead in this segment and IT has to keep up with this challenging business requirement. Lending related applications are highly dynamic and go through constant changes and every single and minor change in each related application is required to be thoroughly UAT tested certified before they are certified for production rollout. This leads to a constant pressure in IT for rapid provisioning of UAT databases on an ongoing basis to enable faster time to market. Nilanjay joined Sushil Kumar, VP, Product Strategy, Oracle, during the Enterprise Manager general session at Oracle OpenWorld 2012. Let's watch what Nilanjay had to say about their recent Database cloud deployment. “Agility” in launching new business schemes became the key business driver for private database cloud adoption in the Bank. Nilanjay spent an hour discussing it during his session. Let's look at why Database-as-a-Service(DBaaS) model was need of the hour in this case  - Average 3 days to provision UAT Database for Loan Management Application Silo’ed UAT environment with Average 30% utilization Compliance requirement consume UAT testing resources DBA activities leads to $$ paid to SI for provisioning databases manually Overhead in managing configuration drift between production and test environments Rollout impact/delay on new business initiatives The private database cloud implementation progressed through 4 fundamental phases - Standardization, Consolidation, Automation, Optimization of UAT infrastructure. Project scoping was carried out and end users and stakeholders were engaged early on right from planning phase and including all phases of implementation. Standardization and Consolidation phase involved multiple iterations of planning to first standardize on infrastructure, db versions, patch levels, configuration, IT processes etc and with database level consolidation project onto Exadata platform. It was also decided to have existing AIX UAT DB landscape covered and EM 12c DBaaS solution being platform agnostic supported this model well. Automation and Optimization phase provided the necessary Agility, Self-Service and efficiency and this was made possible via EM 12c DBaaS. EM 12c DBaaS Self-Service/SSA Portal was setup with required zones, quotas, service templates, charge plan defined. There were 2 zones implemented - Exadata zone  primarily for UAT and benchmark testing for databases running on Exadata platform and second zone was for AIX setup to cover other databases those running on AIX. Metering and Chargeback/Showback capabilities provided business and IT the framework for cloud optimization and also visibility into cloud usage. More details on UAT cloud implementation, related building blocks and EM 12c DBaaS solution are covered in Nilanjay's OpenWorld session here. Some of the key Benefits achieved from UAT cloud initiative are - New business initiatives can be easily launched due to rapid provisioning of UAT Databases [ ~3 hours ] Drastically cut down $$ on SI for DBA Activities due to Self-Service Effective usage of infrastructure leading to  better ROI Empowering  consumers to provision database using Self-Service Control on project schedule with DB end date aligned to project plan submitted during provisioning Databases provisioned through Self-Service are monitored in EM and auto configured for Alerts and KPI Regulatory requirement of database does not impact existing project in queue This table below shows typical list of activities and tasks involved when a end user requests for a UAT database. EM 12c DBaaS solution helped reduce UAT database provisioning time from roughly 3 days down to 3 hours and this timing also includes provisioning time for database with production scale data (ranging from 250 G to 2 TB of data) - And it's not just about time to provision,  this initiative has enabled an agile, efficient and transparent UAT environment where end users are empowered with real control of cloud resources and IT's role is shifted as enabler of strategic services instead of being administrator of all user requests. The strong collaboration between IT and business community right from planning to implementation to go-live has played the key role in achieving this common goal of enterprise private cloud. Finally, real cloud is here and this cloud is accompanied with rain (business benefits) as well ! For more information, please go to Oracle Enterprise Manager  web page or  follow us at :  Twitter | Facebook | YouTube | Linkedin | Newsletter

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  • App Store: Profitability for Game Developers

    - by Bunkai.Satori
    Recent days, I've been spending significant time in discovering chances of profitability of AppStore for developers. I have found many articles. Some of them are highly optimistic, while other are extremely skeptical. This article is extremely skeptical. It even claims to have backed its conclusions by objective sales numbers. This is another pesimistic article saying that games developed by single individuals get 20 downloads a day. Can I kindly ask to clarify from business viewpoint whether average developers publishing games and software on AppStore can cover their living expenses, even, whether they can become profitable? Is it achievable to generate revenues of 50.000 USD yearly on AppStore for a single developer? I would like to stay as realistic as possible. Despite the question might look subjective, a good business man will be able to esitmate chances for profitability and prosperity within AppStore.

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  • App Store: Profitability for Game Developers

    - by Bunkai.Satori
    Recent days, I've been spending significant time in discovering chances of profitability of AppStore for developers. I have found many articles. Some of them are highly optimistic, while other are extremely skeptical. This article is extremely skeptical. It even claims to have backed its conclusions by objective sales numbers. This is another pesimistic article saying that games developed by single individuals get 20 downloads a day. Can I kindly ask to clarify from business viewpoint whether average developers publishing games and software on AppStore can cover their living expenses, even, whether they can become profitable? Is it achievable to generate revenues of 50.000 USD yearly on AppStore for a single developer? I would like to stay as realistic as possible. Despite the question might look subjective, a good business man will be able to esitmate chances for profitability and prosperity within AppStore.

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  • Dynamic Memory Allocation and Memory Management

    - by Bunkai.Satori
    In an average game, there are hundreds or maybe thousands of objects in the scene. Is it completely correct to allocate memory for all objects, including gun shots (bullets), dynamically via default new()? Should I create any memory pool for dynamic allocation, or is there no need to bother with this? What if the target platform are mobile devices? Is there a need for a memory manager in a mobile game, please? Thank you. Language Used: C++; Currently developed under Windows, but planned to be ported later.

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