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  • Sudoku solver evaluation function

    - by Rich
    Hi, So I'm trying to write a simple genetic algorithm for solving a sudoku (not the most efficient way, I know, but it's just to practice evolutionary algorithms). I'm having some problems coming up with an efficient evaluation function to test if the puzzle is solved or not and how many errors there are. My first instinct would be to check if each row and column of the matrix (doing it in octave, which is similar to matlab) have unique elements by ordering them, checking for duplicates and then putting them back the way they were, which seems long winded. Any thoughts? Sorry if this has been asked before...

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  • Conceal packet loss in PCM stream

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

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  • ASP.NET MVC Validation of ViewState MAC failed

    - by Kevin Pang
    After publishing a new build of my ASP.NET MVC web application, I often see this exception thrown when browsing to the site: System.Web.Mvc.HttpAntiForgeryException: A required anti-forgery token was not supplied or was invalid. --- System.Web.HttpException: Validation of viewstate MAC failed. If this application is hosted by a Web Farm or cluster, ensure that configuration specifies the same validationKey and validation algorithm. AutoGenerate cannot be used in a cluster. --- System.Web.UI.ViewStateException: Invalid viewstate. This exception will continue to occur on each page I visit in my web application until I close out of Firefox. After reopening Firefox, the site works perfectly. Any idea what's going on? Additional notes: I am not using any ASP.NET web controls (there are no instances of runat="server" in my application) If I take out the <%= Html.AntiForgeryToken % from my pages, this problem seems to go away

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  • Is there an easy to script 2d game world?

    - by Sandro
    For a school project we're developing a game that's a little like Conway's game of life, with different organisms taking up slots in the world and then eating each other. I would like to see this take place in a 2d world. Like being able to take starcraft and have zergling and marines play roles. The problem with starcraft is that the whole algorithm would have to be written inside of the game editor, and starcraft isn't free or open source. So is there another engine that is starcraft/warcraft/AOE-ish that can be scripted from outside of the game and is freely available? (I'm asking a lot here I know)

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  • Good implementations of reinforced learning?

    - by Paperino
    For an ai-class project I need to implement a reinforcement learning algorithm which beats a simple game of tetris. The game is written in Java and we have the source code. I know the basics of reinforcement learning theory but was wondering if anyone in the SO community had hands on experience with this type of thing. What would your recommended readings be for an implementation of reinforced learning in a tetris game? Are there any good open source projects that accomplish similar things that would be worth checking out? Thanks in advanced Edit: The more specific the better, but general resources about the subject are welcomed. Follow up: Thought it would be nice if I posted a followup. Here's the solution (code and writeup) I ended up with for any future students :). Paper / Code

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  • How do You Get a Specific Value From a System.Data.DataTable Object?

    - by Giffyguy
    I'm a low-level algorithm programmer, and databases are not really my thing - so this'll be a n00b question if ever there was one. I'm running a simple SELECT query through our development team's DAO. The DAO returns a System.Data.DataTable object containing the results of the query. This is all working fine so far. The problem I have run into now: I need to pull a value out of one of the fields of the first row in the resulting DataTable - and I have no idea where to even start. Microsoft is so confusing about this! Arrrg! Any advice would be appreciated. I'm not providing any code samples, because I believe that context is unnecessary here. I'm assuming that all DataTable objects work the same way, no matter how you run your queries - and therefore any additional information would just make this more confusing for everyone.

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  • Downsampling and applying a lowpass filter to digital audio

    - by twk
    I've got a 44Khz audio stream from a CD, represented as an array of 16 bit PCM samples. I'd like to cut it down to an 11KHz stream. How do I do that? From my days of engineering class many years ago, I know that the stream won't be able to describe anything over 5500Hz accurately anymore, so I assume I want to cut everything above that out too. Any ideas? Thanks. Update: There is some code on this page that converts from 48KHz to 8KHz using a simple algorithm and a coefficient array that looks like { 1, 4, 12, 12, 4, 1 }. I think that is what I need, but I need it for a factor of 4x rather than 6x. Any idea how those constants are calculated? Also, I end up converting the 16 byte samples to floats anyway, so I can do the downsampling with floats rather than shorts, if that helps the quality at all.

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  • On-the-fly lossless image compression

    - by geschema
    I have an embedded application where an image scanner sends out a stream of 16-bit pixels that are later assembled to a grayscale image. As I need to both save this data locally and forward it to a network interface, I'd like to compress the data stream to reduce the required storage space and network bandwidth. Is there a simple algorithm that I can use to losslessly compress the pixel data? I first thought of computing the difference between two consecutive pixels and then encoding this difference with a Huffman code. Unfortunately, the pixels are unsigned 16-bit quantities so the difference can be anywhere in the range -65535 .. +65535 which leads to potentially huge codeword lengths. If a few really long codewords occur in a row, I'll run into buffer overflow problems.

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  • Problem with stackless python, cannot write to a dict

    - by ANON
    I have simple map-reduce type algorithm, which I want to implement in python and make use of multiple cores. I read somewhere that threads using native thread module in 2.6 dont make use of multiple cores. is that true? I even implemented it using stackless python however i am getting into weird errors [Update: a quick search showed that the stack less does not allows multiple cores So are their any other alternatives?] def Propagate(start,end): print "running Thread with range: ",start,end def maxVote(nLabels): count = {} maxList = [] maxCount = 0 for nLabel in nLabels: if nLabel in count: count[nLabel] += 1 else: count[nLabel] = 1 #Check if the count is max if count[nLabel] > maxCount: maxCount = count[nLabel]; maxList = [nLabel,] elif count[nLabel]==maxCount: maxList.append(nLabel) return random.choice(maxList) for num in range(start,end): node=MapList[num] nLabels = [Label[k] for k in Adj[node]] if (nLabels!=[]): Label[node] = maxVote(nLabels) else: Label[node]=node However in above code the values assigned to Label, that is the change in dictionary are lost. Above propagate function is used as callable for MicroThreads (i.e. TaskLets)

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  • Comparing datafeeds from different networks (Affiliate Marketing)

    - by Logistetica
    Hi, I am working on integrating affiliate sales into few existing sites. We are using a few merchants who work via different networks (cj, shareasale, linkshare, avantlink). Now my observation is that all these networks provide data feeds in different formats. But that's not a big problem. My main concern is actually merchants using different titles on same products. I don't want to run into these situations: a) two listings of the SAME product from N merchants (if titles are just a bit different) b) one listing of N different products from merchants (if we don't use strict comparison algorithm) We want to automate everything as much as possible, want to avoid operators scanning listings under question all the time. How is this problem typically handled?

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  • WP: AesManaged encryption vs. mcrypt_encrypt

    - by invalidusername
    I'm trying to synchronize my encryption and decryption methods between C# and PHP but something seems to be going wrong. In the Windows Phone 7 SDK you can use AESManaged to encrypt your data I use the following method: public static string EncryptA(string dataToEncrypt, string password, string salt) { AesManaged aes = null; MemoryStream memoryStream = null; CryptoStream cryptoStream = null; try { //Generate a Key based on a Password, Salt and HMACSHA1 pseudo-random number generator Rfc2898DeriveBytes rfc2898 = new Rfc2898DeriveBytes(password, Encoding.UTF8.GetBytes(salt)); //Create AES algorithm with 256 bit key and 128-bit block size aes = new AesManaged(); aes.Key = rfc2898.GetBytes(aes.KeySize / 8); aes.IV = new byte[] { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; // rfc2898.GetBytes(aes.BlockSize / 8); // to check my results against those of PHP var blaat1 = Convert.ToBase64String(aes.Key); var blaat2 = Convert.ToBase64String(aes.IV); //Create Memory and Crypto Streams memoryStream = new MemoryStream(); cryptoStream = new CryptoStream(memoryStream, aes.CreateEncryptor(), CryptoStreamMode.Write); //Encrypt Data byte[] data = Encoding.Unicode.GetBytes(dataToEncrypt); cryptoStream.Write(data, 0, data.Length); cryptoStream.FlushFinalBlock(); //Return Base 64 String string result = Convert.ToBase64String(memoryStream.ToArray()); return result; } finally { if (cryptoStream != null) cryptoStream.Close(); if (memoryStream != null) memoryStream.Close(); if (aes != null) aes.Clear(); } } I solved the problem of generating the Key. The Key and IV are similar as those on the PHP end. But then the final step in the encryption is going wrong. here is my PHP code <?php function pbkdf2($p, $s, $c, $dk_len, $algo = 'sha1') { // experimentally determine h_len for the algorithm in question static $lengths; if (!isset($lengths[$algo])) { $lengths[$algo] = strlen(hash($algo, null, true)); } $h_len = $lengths[$algo]; if ($dk_len > (pow(2, 32) - 1) * $h_len) { return false; // derived key is too long } else { $l = ceil($dk_len / $h_len); // number of derived key blocks to compute $t = null; for ($i = 1; $i <= $l; $i++) { $f = $u = hash_hmac($algo, $s . pack('N', $i), $p, true); // first iterate for ($j = 1; $j < $c; $j++) { $f ^= ($u = hash_hmac($algo, $u, $p, true)); // xor each iterate } $t .= $f; // concatenate blocks of the derived key } return substr($t, 0, $dk_len); // return the derived key of correct length } } $password = 'test'; $salt = 'saltsalt'; $text = "texttoencrypt"; #$iv_size = mcrypt_get_iv_size(MCRYPT_RIJNDAEL_128, MCRYPT_MODE_CBC); #echo $iv_size . '<br/>'; #$iv = mcrypt_create_iv($iv_size, MCRYPT_RAND); #print_r (mcrypt_list_algorithms()); $iv = "\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00"; $key = pbkdf2($password, $salt, 1000, 32); echo 'key: ' . base64_encode($key) . '<br/>'; echo 'iv: ' . base64_encode($iv) . '<br/>'; echo '<br/><br/>'; function addpadding($string, $blocksize = 32){ $len = strlen($string); $pad = $blocksize - ($len % $blocksize); $string .= str_repeat(chr($pad), $pad); return $string; } echo 'text: ' . $text . '<br/>'; echo 'text: ' . addpadding($text) . '<br/>'; // -- works till here $crypttext = mcrypt_encrypt(MCRYPT_RIJNDAEL_256, $key, $text, MCRYPT_MODE_CBC, $iv); echo '1.' . $crypttext . '<br/>'; $crypttext = base64_encode($crypttext); echo '2.' . $crypttext . '<br/>'; $crypttext = mcrypt_encrypt(MCRYPT_RIJNDAEL_256, $key, addpadding($text), MCRYPT_MODE_CBC, $iv); echo '1.' . $crypttext . '<br/>'; $crypttext = base64_encode($crypttext); echo '2.' . $crypttext . '<br/>'; ?> So to point out, the Key and IV look similar on both .NET and PHP, but something seems to be going wrong in the final call when executing mcrypt_encrypt(). The end result, the encrypted string, differs from .NET. Can anybody tell me what i'm doing wrong. As far as i can see everything should be correct. Thank you! EDIT: Additional information on the AESManaged object in .NET Keysize = 256 Mode = CBC Padding = PKCS7

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  • Why are primes important in cryptography?

    - by Michael Stum
    One thing that always strikes me as a non-cryptographer: Why is it so important to use Prime numbers? What makes them so special in cryptography? Does anyone have a simple short explanation? (I am aware that there are many primers and that Applied Cryptography is the Bible, but as said: I am not looking to implement my own cryptographic algorithm, and the stuff that I found just made my brain explode - no 10 pages of math formulas please :)) Thanks for all the answers. I've accepted the one that made the actual concept most clear to me.

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  • How do i start with Gomoku?

    - by firstTry
    I read about Gomoku that it can be implemented using Minimax and Alpha-Beta Pruning algorithms. So, i read these algorithms and now understand how the game will be solved. But when i sat to down to code, I am facing problem how to approach it. As in , How to design the prototype functions like getNextMove or Max(Move) ? How will the next move searched? Till when should i apply the minimax algorithm. I know i can find the code online, but i want to do it myself. Can anyone please point me in the right direction?

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  • How to secure licensekey generation

    - by Jakob Gade
    Scenario, simplified for brevity: A developer creates an application for a customer. The customer sells this app to end-users. The app requires a license key to run, and this key is generated by the customer for each end-user with a simple tool created by the developer. The license key contains an expiry date for the license and is encrypted so the end-user can’t tamper with it. The problem here is that the developer (or anybody who has a copy of the license key generator) can easily create valid license keys. Should this generator fall into the wrong hands, it could spell disaster for the customers business. Ideally, the customer would have to use a password to create new license keys. And this password would be unknown to the developer, and somehow baked into the decryption algorithm in the application so it will fail if an attempt to use an unauthorized key is made. How would you implement a solution for this problem that is both transparent and secure?

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  • MPI: is there mpi libraries capable of message compression?

    - by osgx
    Sometimes MPI is used to send low-entropy data in messages. So it can be useful to try to compress messages before sending it. I know that MPI can work on very fast networks (10 Gbit/s and more), but many MPI programs are used with cheap network like 0,1G or 1Gbit/s Ethernet and with cheap (slow, low bisection) network switch. There is a very fast Snappy (wikipedia) compression algorithm, which has Compression speed is 250 MB/s and decompression speed is 500 MB/s so on compressible data and slow network it will give some speedup. Is there any MPI library which can compress MPI messages (at layer of MPI; not the compression of ip packets like in PPP). MPI messages are also structured, so there can be some special method, like compression of exponent part in array of double.

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  • How do I plot the warping of DTW result using gnuplot?

    - by Ekkmanz
    Hello, Right now I have implemented Dynamic Time Warping algorithm for warping two 3D trajectories. Currently, gnuplot is my plotting tool of choice and it works fine when I plot multiple trajectories at a time. However, when I implement DTW one of the real use for plotting tool is to visualize the point warping, like this picture. Currently, the output of my DTW program is two time series in CSV files and another CSV file which indicate the warp (X in series 1 - Y in series 2). Is there any possible way to do that in gnuplot?

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  • Graph and permutation problem

    - by user319771
    I have a graph (with nodes and edges) containing symmetry and a group of permutations to label the nodes so no edges are changed (automorphisms). Now I would like to determine for which nodes a permutation exchanges two equivalent (i.e. nodes with the same color or symmetry class) neighboring nodes. When the nodes with equivalent neighbors stay the same, simply checking if the neighbors are exchanged in the permutation is enough. However, when the nodes with equivalent neighbors are also permuted (i.e. there are multiple nodes with the same color/symmetry class with the same equivalent neighbors), the problem becomes more complex. Is there any known algorithm for such a problem? Some remarks: The graph has no coordinates, it's a topology only

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  • Using boost unordered map

    - by Amrish
    Guys, I am using dynamic programming approach to solve a problem. Here is a brief overview of the approach Each value generated is identified using 25 unique keys. I use the boost::hash_combine to generate the seed for the hash table using these 25 keys. I store the values in a hash table declared as boost::unordered_map<Key_Object, Data_Object, HashFunction> hashState; I did a time profiling on my algorithm and found that nearly 95% of the run time is spent towards retrieving/inserting data into the hash table. These were the details of my hash table hashState.size() 1880 hashState.load_factor() 0.610588 hashState.bucket_count() 3079 hashState.max_size() 805306456 hashState.max_load_factor() 1 hashState.max_bucket_count() 805306457 I have the following two questions Is there anything which I can do to improve the performance of the Hash Table's insert/retrieve operations? C++ STL has hash_multimap which would also suit my requirement. How does boost libraries unordered_map compare with hash_multimap in terms of insert/retrieve performance.

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  • What one-time-password devices are compatible with mod_authn_otp?

    - by netvope
    mod_authn_otp is an Apache web server module for two-factor authentication using one-time passwords (OTP) generated via the HOTP/OATH algorithm defined in RFC 4226. The developer's has listed only one compatible device (the Authenex's A-Key 3600) on their website. If a device is fully compliant with the standard, and it allows you to recover the token ID, it should work. However, without testing, it's hard to tell whether a device is fully compliant. Have you ever tried other devices (software or hardware) with mod_authn_otp (or other open source server-side OTP program)? If yes, please share your experience :)

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  • Optimizing a large iteration of PHP objects (EAV-based)

    - by Aron Rotteveel
    I am currently working on a project that utilizes the EAV model. This turns out to work quite well, but like many others I am now stumbling upon some performance issues. The data set in this particular case consists of aproximately 2500 entities, each with aprox. 150 attributes. Each entity and each attribute is represented by a PHP-object. Since most parts of the application only iterate through a filtered set of entities, we have not had very large issues yet. Now, however, I am working on an algorithm that requires iteration over the entire dataset, which causes a major impact on performance. This information is perhaps not very much to work with, but since this is an architectural problem, I am hoping for a architectural pattern to help me on the way as well. Each entity, including it's attributes takes up aprox. 500KB of memory.

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  • Spectral Reconstruction

    - by Hani
    I have a small system which consist of: Led Clusters, camera(RGB or grayscale) and an object to be detected. I am emitting a light from the LED clusters (ex: yellow). After emitting light on the object, I am capturing an image for the object from the camera. I want to get the spectral image of the object from the captured image. Please if any one knows the algorithm or a code for this purpose(grayscale or RGB camera), tell me. Thanks.....

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  • Checking for any lowercase letters in a string

    - by pcampbell
    Consider a JavaScript method that needs to check whether a given string is in all uppercase letters. The input strings are people's names. The current algorithm is to check for any lowercase letters. var check1 = "Jack Spratt"; var check2 = "BARBARA FOO-BAR"; var check3 = "JASON D'WIDGET"; var isUpper1 = HasLowercaseCharacters(check1); var isUpper2 = HasLowercaseCharacters(check2); var isUpper3 = HasLowercaseCharacters(check3); function HasLowercaseCharacters(string input) { //pattern for finding whether any lowercase alpha characters exist var allLowercase; return allLowercase.test(input); } Is a regex the best way to go here? What pattern would you use to determine whether a string has any lower case alpha characters?

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  • Fastest way to list all primes below N in python

    - by jbochi
    This is the best algorithm I could come up with after struggling with a couple of Project Euler's questions. def get_primes(n): numbers = set(range(n, 1, -1)) primes = [] while numbers: p = numbers.pop() primes.append(p) numbers.difference_update(set(range(p*2, n+1, p))) return primes >>> timeit.Timer(stmt='get_primes.get_primes(1000000)', setup='import get_primes').timeit(1) 1.1499958793645562 Can it be made even faster? EDIT: This code has a flaw: Since numbers is an unordered set, there is no guarantee that numbers.pop() will remove the lowest number from the set. Nevertheless, it works (at least for me) for some input numbers: >>> sum(get_primes(2000000)) 142913828922L #That's the correct sum of all numbers below 2 million >>> 529 in get_primes(1000) False >>> 529 in get_primes(530) True EDIT: The rank so far (pure python, no external sources, all primes below 1 million): Sundaram's Sieve implementation by myself: 327ms Daniel's Sieve: 435ms Alex's recipe from Cookbok: 710ms EDIT: ~unutbu is leading the race.

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  • setsockopt TCP_NODELAY question on Windows Mobile

    - by weki
    Hi all, I have a problem on Windows Mobile 6.0. I would like to create a TCP connection which does not use the Nagle algorithm, so it sends my data when I call "send" function, and does not buffer calls, having too small amount of data. I tried the following: BOOL b = TRUE; setsockopt(socketfd, IPPROTO_TCP, TCP_NODELAY, (char*)(&b), sizeof(BOOL)); It works fine on desktop. But on Windows Mobile, if I set this value, than I make a query for it, the returned value is 8. And the network traffic analysis shows that the nothing changed. Is there any way to force a flush to my socket?

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  • Facebook App Wall Posting no longer showing in Facebook iPhone App

    - by David Hsu
    I use the GRAPH API with django for Facebook wall postings. Since yesterday, the wall posts only show on the Facebook web app but not the Facebook iPhone app. I tried Yelp, and their postings still show up. How can I debug this? Anyone notice this issue with their Facebook connect? Is this a Facebook algorithm issue. Code for Wall Post: graph = facebook.GraphAPI(access_token) attachment = {"name": name, "link": link, #"caption": "{*actor*} posted a new review", "description": desc, "picture": picture } graph.put_wall_post("",attachment)

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