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  • What's the best approach when it comes to updating a production(on ec2) machine that can't go down?

    - by Ryan Detzel
    We have three main servers on ec2, web, database, and search. I logged in today to find: 77 packages can be updated. 45 updates are security updates. which scares the crap out of me so I want to update these machines asap but I'm scared to just run the updates on a live running system. Is this safe to do, what's the best approach when it comes to doing security updates on production machines?

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  • SPARC T4-4 Delivers World Record Performance on Oracle OLAP Perf Version 2 Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered world record performance with subsecond response time on the Oracle OLAP Perf Version 2 benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 11. The SPARC T4-4 server achieved throughput of 430,000 cube-queries/hour with an average response time of 0.85 seconds and the median response time of 0.43 seconds. This was achieved by using only 60% of the available CPU resources leaving plenty of headroom for future growth. The SPARC T4-4 server operated on an Oracle OLAP cube with a 4 billion row fact table of sales data containing 4 dimensions. This represents as many as 90 quintillion aggregate rows (90 followed by 18 zeros). Performance Landscape Oracle OLAP Perf Version 2 Benchmark 4 Billion Fact Table Rows System Queries/hour Users* Response Time (sec) Average Median SPARC T4-4 430,000 7,300 0.85 0.43 * Users - the supported number of users with a given think time of 60 seconds Configuration Summary and Results Hardware Configuration: SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 1 TB memory Data Storage 1 x Sun Fire X4275 (using COMSTAR) 2 x Sun Storage F5100 Flash Array (each with 80 FMODs) Redo Storage 1 x Sun Fire X4275 (using COMSTAR with 8 HDD) Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option Benchmark Description The Oracle OLAP Perf Version 2 benchmark is a workload designed to demonstrate and stress the Oracle OLAP product's core features of fast query, fast update, and rich calculations on a multi-dimensional model to support enhanced Data Warehousing. The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle OLAP cube consisting of a number of years of sales data with fully pre-computed aggregations. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc. Results from version 2 of the benchmark are not comparable with version 1. The primary difference is the type of queries along with the query mix. Key Points and Best Practices Since typical BI users are often likely to issue similar queries, with different constants in the where clauses, setting the init.ora prameter "cursor_sharing" to "force" will provide for additional query throughput and a larger number of potential users. Except for this setting, together with making full use of available memory, out of the box performance for the OLAP Perf workload should provide results similar to what is reported here. For a given number of query users with zero think time, the main measured metrics are the average query response time, the median query response time, and the query throughput. A derived metric is the maximum number of users the system can support achieving the measured response time assuming some non-zero think time. The calculation of the maximum number of users follows from the well-known response-time law N = (rt + tt) * tp where rt is the average response time, tt is the think time and tp is the measured throughput. Setting tt to 60 seconds, rt to 0.85 seconds and tp to 119.44 queries/sec (430,000 queries/hour), the above formula shows that the T4-4 server will support 7,300 concurrent users with a think time of 60 seconds and an average response time of 0.85 seconds. For more information see chapter 3 from the book "Quantitative System Performance" cited below. -- See Also Quantitative System Performance Computer System Analysis Using Queueing Network Models Edward D. Lazowska, John Zahorjan, G. Scott Graham, Kenneth C. Sevcik external local Oracle Database 11g – Oracle OLAP oracle.com OTN SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 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 11/2/2012.

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  • FileUpload and UpdatePanel: ScriptManager.RegisterPostBackControl works the second time.

    - by VansFannel
    Hello. I'm developing an ASP.NET application with C# and Visual Studio 2008 SP1. I'm using WebForms. I have an ASPX page with two UpdatePanels, one on the left that holds a TreeView and other on the right where I load dynamically user controls. One user control, that I used on right panel, has a FileUpload control and a button to save that file on server. The ascx code to save control is: <asp:UpdatePanel ID="UpdatePanelBotons" runat="server" RenderMode="Inline" UpdateMode="Conditional"> <ContentTemplate> <asp:Button ID="Save" runat="server" Text="Guardar" onclick="Save_Click" CssClass="button" /> </ContentTemplate> <Triggers> <asp:PostBackTrigger ControlID="Save" /> </Triggers> </asp:UpdatePanel> I make a full postback to upload the file to the server and save it to database. But I always getting False on FileUpload.HasFile. I problem is the right UpdatePanel. I need it to load dynamically the user controls. This panel has three UpdatePanels to load the three user controls that I use. Maybe I can use an Async File Uploader or delete the right Update Panel and do a full postback to load controls dynamically. Any advice? UPDATE: RegisterPostBackControl works... the second time I click on save button. First time FileUpload.HasFile is FALSE, and second time is TRUE. Second Update On first click I also check ScriptManager.IsInAsyncPostBack and is FALSE. I don't understand ANYTHING!! Why? The code to load user control first time, and on each postback is: DynamicControls.CreateDestination ud = this.LoadControl(ucUrl) as DynamicControls.CreateDestination; if (ud != null) { Button save = ud.FindControl("Save") as Button; if (save != null) ScriptManager1.RegisterPostBackControl(save); PanelDestination.Controls.Add(ud); } Thank you.

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  • C# - Alternative to System.Timers.Timer, to call a function at a specific time.

    - by Fábio Antunes
    Hello everybody. I want to call a specific function on my C# application at a specific time. At first i thought about using a Timer (System.Time.Timer), but that soon became impossible to use. Why? Simple. The Timer Class requires a Interval in milliseconds, but considering that i might want the function to be executed, lets says in a week that would mean: 7 Days = 168 hours; 168 Hours = 10,080 minutes; 10,080 Minutes = 6,048,000 seconds; 6,048,000 Seconds = 6,048,000,000 milliseconds; So the Interval would be 6,048,000,000; Now lets remember that the Interval accepted data type is int, and as we know int range goes from -2,147,483,648 to 2,147,483,647. That makes Timer useless in this case once we cannot set a Interval bigger that 2,147,483,647 milliseconds. So i need a solution where i could specify when the function should be called. Something like this: solution.ExecuteAt = "30-04-2010 15:10:00"; solution.Function = "functionName"; solution.Start(); So when the System Time would reach "30-04-2010 15:10:00" the function would be executed in the application. How can this problem be solved? Thanks just by taking the time to read my question. But if you could provide me with some help i would be most grateful. Additional Info: What these functions will do? Getting climate information and based on that info: Starting / Shutting down other Applications (most of them Console Based); Sending custom Commands to those Console Applications; Power down, Rebooting, Sleep, Hibernate the computer; And if possible schedule the BIOS to Power Up the Computer; EDIT: It would seem that the Interval accepted data type is double, however if you set a value bigger that an int to the Interval, and call Start() it throws a exception [0, Int32.MaxValue]. EDIT 2: Jørn Schou-Rode suggested using Ncron to handle the scheduling tasks, and at first look this seems a good solution, but i would like to hear about some who as worked with it.

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  • Can a Mac Machine be used by Multiuser at same time? [closed]

    - by Amit Jain
    Hi All, Can a mac machine be used by different user at the same time ? I mean to say that we have a single mac machine but 3 users can they access the same machine remotely at the same time for developing application on iPhone or Mac. Does Mac OS X server allows us to do this ? If Yes please provide me with suitable link. Thanks Amit

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  • How do I parse a UTC date format string to local date time?

    - by Brian Scott
    I'm currently using the jQuery fullcalendar plugin but I've came across an issue regarding daylight savings time in Britain. After the daylight savings take effect the hours are being displayed an hour out of phase. The problem appears to be with the plugins parsing function. Can someone please provide me with the funciton to parse a UTC string which includes the 'Z' demonination into a local date time for display?

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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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  • Am I "wasting" my time learning C and other low level stuff ?

    - by Andreas Grech
    I have just recently started learning C and the reason I did that was because frankly, I consider myself to be of a "less-developer" than the people who know and work with C. Thus I planned to start learning ASM, C, C++ and bought the K&R book and started pushing myself to learn the C Programming Language and up till now I'm doing great...learning about arrays the low level way (ie the pointer + offset thing), pointers and all that and obviously asking questions on stackoverflow for guidance. My problem is that sometimes I get thinking if instead of learning this low level stuff, maybe I should maybe spend more time learning newer, more widely used technologies...basically, more web stuff. Now I am well versed with both C# and ASP.Net and currently that's what I do for a living, but still there exists Microsoft technologies that I haven't quite touched upon...such as ASP.Net MVC, The Entity Framework etc... And those are only Microsoft Technologies...obviously there are other stuff that I would like to touch upon...stuff like Ruby, which would lead me to Ruby on Rails, or Python for Django or even Java and J2EE, or maybe even PHP; ie, basically mainly Web Stuff. Mind you, I did touch upon some of the stuff I mentioned earlier on, such as PHP and Java but I am still not quite versed in them as I am in C# and ASP.Net...but still, I think that by learning other languages that are used in the web environment will broaden my horizons...both as a developer who loves learning, and also Career wise. My point is, am I really using up my time correctly by learning older, lower level stuff? Stuff that for my current line of work, will most probably never use, but still is interesting to know ? To be frankly honest, I am also learning C so that I could, maybe someday, get into Electronics and Micro-controller programming but that is a whole new world for me and, if I choose to go there, will take some time to get adjusted to. And even then, I don't know if I can get a career in working in that line of work. ...but I still wonder about this question over and over...Am I doing the right thing by learning C instead of something (Web-stuff) that will most probably be more useful for me career-wise? I'm sorry for such asking such a long and most probably a boring question, but I feel as if this is the only place where I can ask such a question and get an honest answer from experts in the field. Thank you for your time.

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  • ASP/AJAX - How to get the time between an server request and response?

    - by Julian
    Whenver Ajax requests new data from the server this can sometimes take a a second or two. Now I want to know, how can I get this time between the ajax request and the response it gets from the server? I need this because an ajax timer I'm running ain't perfectly doing his stuff. It got some delay whenever it needs to reset to it's original time. Thanks in Advance. Edit: Help needed fast please, just try.

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  • how get the date and time of the last modified particular TYPE file in that directory in c#

    - by Arunachalam
    how get the date and time of the last modified particular TYPE file in that directory let me explain with an example there are many files in directory say y:\tempfiles now i want to get the date and time of last modified file of txt format files like 9-03-2010 11.35 arun.reo 9-03-2010 11.31 arun1.reo 9-03-2010 11.31 arun.txt 9-03-2010 11.31 arun.avi now i want the out put as 9-03-2010 11.35 which is last modified file for reo type files .

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  • Strange: Planner takes decision with lower cost, but (very) query long runtime

    - by S38
    Facts: PGSQL 8.4.2, Linux I make use of table inheritance Each Table contains 3 million rows Indexes on joining columns are set Table statistics (analyze, vacuum analyze) are up-to-date Only used table is "node" with varios partitioned sub-tables Recursive query (pg = 8.4) Now here is the explained query: WITH RECURSIVE rows AS ( SELECT * FROM ( SELECT r.id, r.set, r.parent, r.masterid FROM d_storage.node_dataset r WHERE masterid = 3533933 ) q UNION ALL SELECT * FROM ( SELECT c.id, c.set, c.parent, r.masterid FROM rows r JOIN a_storage.node c ON c.parent = r.id ) q ) SELECT r.masterid, r.id AS nodeid FROM rows r QUERY PLAN ----------------------------------------------------------------------------------------------------------------------------------------------------------------- CTE Scan on rows r (cost=2742105.92..2862119.94 rows=6000701 width=16) (actual time=0.033..172111.204 rows=4 loops=1) CTE rows -> Recursive Union (cost=0.00..2742105.92 rows=6000701 width=28) (actual time=0.029..172111.183 rows=4 loops=1) -> Index Scan using node_dataset_masterid on node_dataset r (cost=0.00..8.60 rows=1 width=28) (actual time=0.025..0.027 rows=1 loops=1) Index Cond: (masterid = 3533933) -> Hash Join (cost=0.33..262208.33 rows=600070 width=28) (actual time=40628.371..57370.361 rows=1 loops=3) Hash Cond: (c.parent = r.id) -> Append (cost=0.00..211202.04 rows=12001404 width=20) (actual time=0.011..46365.669 rows=12000004 loops=3) -> Seq Scan on node c (cost=0.00..24.00 rows=1400 width=20) (actual time=0.002..0.002 rows=0 loops=3) -> Seq Scan on node_dataset c (cost=0.00..55001.01 rows=3000001 width=20) (actual time=0.007..3426.593 rows=3000001 loops=3) -> Seq Scan on node_stammdaten c (cost=0.00..52059.01 rows=3000001 width=20) (actual time=0.008..9049.189 rows=3000001 loops=3) -> Seq Scan on node_stammdaten_adresse c (cost=0.00..52059.01 rows=3000001 width=20) (actual time=3.455..8381.725 rows=3000001 loops=3) -> Seq Scan on node_testdaten c (cost=0.00..52059.01 rows=3000001 width=20) (actual time=1.810..5259.178 rows=3000001 loops=3) -> Hash (cost=0.20..0.20 rows=10 width=16) (actual time=0.010..0.010 rows=1 loops=3) -> WorkTable Scan on rows r (cost=0.00..0.20 rows=10 width=16) (actual time=0.002..0.004 rows=1 loops=3) Total runtime: 172111.371 ms (16 rows) (END) So far so bad, the planner decides to choose hash joins (good) but no indexes (bad). Now after doing the following: SET enable_hashjoins TO false; The explained query looks like that: QUERY PLAN ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- CTE Scan on rows r (cost=15198247.00..15318261.02 rows=6000701 width=16) (actual time=0.038..49.221 rows=4 loops=1) CTE rows -> Recursive Union (cost=0.00..15198247.00 rows=6000701 width=28) (actual time=0.032..49.201 rows=4 loops=1) -> Index Scan using node_dataset_masterid on node_dataset r (cost=0.00..8.60 rows=1 width=28) (actual time=0.028..0.031 rows=1 loops=1) Index Cond: (masterid = 3533933) -> Nested Loop (cost=0.00..1507822.44 rows=600070 width=28) (actual time=10.384..16.382 rows=1 loops=3) Join Filter: (r.id = c.parent) -> WorkTable Scan on rows r (cost=0.00..0.20 rows=10 width=16) (actual time=0.001..0.003 rows=1 loops=3) -> Append (cost=0.00..113264.67 rows=3001404 width=20) (actual time=8.546..12.268 rows=1 loops=4) -> Seq Scan on node c (cost=0.00..24.00 rows=1400 width=20) (actual time=0.001..0.001 rows=0 loops=4) -> Bitmap Heap Scan on node_dataset c (cost=58213.87..113214.88 rows=3000001 width=20) (actual time=1.906..1.906 rows=0 loops=4) Recheck Cond: (c.parent = r.id) -> Bitmap Index Scan on node_dataset_parent (cost=0.00..57463.87 rows=3000001 width=0) (actual time=1.903..1.903 rows=0 loops=4) Index Cond: (c.parent = r.id) -> Index Scan using node_stammdaten_parent on node_stammdaten c (cost=0.00..8.60 rows=1 width=20) (actual time=3.272..3.273 rows=0 loops=4) Index Cond: (c.parent = r.id) -> Index Scan using node_stammdaten_adresse_parent on node_stammdaten_adresse c (cost=0.00..8.60 rows=1 width=20) (actual time=4.333..4.333 rows=0 loops=4) Index Cond: (c.parent = r.id) -> Index Scan using node_testdaten_parent on node_testdaten c (cost=0.00..8.60 rows=1 width=20) (actual time=2.745..2.746 rows=0 loops=4) Index Cond: (c.parent = r.id) Total runtime: 49.349 ms (21 rows) (END) - incredibly faster, because indexes were used. Notice: Cost of the second query ist somewhat higher than for the first query. So the main question is: Why does the planner make the first decision, instead of the second? Also interesing: Via SET enable_seqscan TO false; i temp. disabled seq scans. Than the planner used indexes and hash joins, and the query still was slow. So the problem seems to be the hash join. Maybe someone can help in this confusing situation? thx, R.

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  • how to limit the number of images to be displayed at a time in android imageswitcher control?

    - by Rupesh Chavan
    Hello Everyone, I have checked the working demo of ImageSwitcher and gallery. Actually i want to display 4 images at a time on screen and by default it displays number of images that it can fit in a screen say for ex. 6 images. Now i want to limit the number of images(to 4 images ) to be displayed on ImageSwitcher at the same time. Any help will be appreciated. Thank you, Rupesh

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  • How can I demonstrate the benefits of abstractions to an old-time C programmer?

    - by Zaban Khuli
    Hi, there's this senior developer in my company that programs in C. I happen to be from functional background (ML, to be specific). This senior C programmer refuses to use abstractions because "abstraction is for lame programmers and _real_ programmers do not need it." I can not seem to convince him otherwise Is it a problem with only this programmer or do all C (and other lower level language) programmers have this opinion that abstraction is for lame programmers?

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  • Why does Joda time change the PM in my input string to AM?

    - by Tree
    My input string is a PM time: log(start); // Sunday, January 09, 2011 6:30:00 PM I'm using Joda Time's pattern syntax as follows to parse the DateTime: DateTimeFormatter parser1 = DateTimeFormat.forPattern("EEEE, MMMM dd, yyyy H:mm:ss aa"); DateTime startTime = parser1.parseDateTime(start); So, why is my output string AM? log(parser1.print(startTime)); // Sunday, January 09, 2011 6:30:00 AM

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  • How do I aggregate activerecord model data for a specific time period?

    - by gsiener
    I'm collecting data from a system every ~10s (this time difference varies due to communication time with networked devices). I'd like to calculate averages and sums of the stored values for this activerecord model on a daily basis. All records are stored in UTC. What's the correct way to sum and average values for, e.g., the previous day from midnight to midnight EST? I can do this in sql but don't know the "rails way" to make this calculation.

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  • Is there a problem when I call SqlAdapter.Update and at the same time call SqlDataReader.Read

    - by Ahmed Said
    I have two applications, one updates a single table which has constant number of rows (128 rows) using SqlDataAdapter.Update method , and another application that select from this table periodically using SqlDataReader. sometimes the DataReader returns only 127 rows not 128, and the update application does not remove or even insert any new rows, it just update. I am asking what is the cause of this behaviour?

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  • How can i interpret a time value in ascii into a numerical value?

    - by Bilal
    I have a file which is as follows: 15:03:21 II 0.88 0.64 15:03:31 II 0.88 0.64 15:03:42 II 0.40 0.40 etc. after loading the file in matlab, I want to be able to read the first column (which corresponds to time) and interpret them as numerical values. At the moment, they are interpreted as a string of ascii characters and i can't perform any mathematical operations on them. Does anyone have any suggestions as to how i can read the time as numbers instead of a string of ascii characters?

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  • Screen Casting using ffmpeg (too fast)

    - by rowman
    I can use ffmpeg to make screen casts: ffmpeg -f x11grab -s 1280x800 -i :0.0 -c:v libx264 -framerate 30 -r 30 -crf 18 out.mkv However the output comes out to be too fast paced. It also happens with GTK RecordMyDesktop if I enable the encode on the fly. So, the questions is how to get a normal video pace. Also in order to capture the sound with ffmpeg what option should be used? FFmpeg Output: ffmpeg -f x11grab -s 1280x800 -r 30 -i :0.0 -c:v libx264 -framerate 30 -r 30 -crf 18 out.mkv ffmpeg version N-35162-g87244c8 Copyright (c) 2000-2012 the FFmpeg developers built on Oct 7 2012 15:56:19 with gcc 4.6 (Ubuntu/Linaro 4.6.3-1ubuntu5) configuration: --enable-gpl --enable-libfaac --enable-libfdk-aac --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-librtmp --enable-libtheora --enable-libvorbis --enable-libvpx --enable-x11grab --enable-libx264 --enable-nonfree --enable-version3 libavutil 51. 73.102 / 51. 73.102 libavcodec 54. 64.100 / 54. 64.100 libavformat 54. 29.105 / 54. 29.105 libavdevice 54. 3.100 / 54. 3.100 libavfilter 3. 19.102 / 3. 19.102 libswscale 2. 1.101 / 2. 1.101 libswresample 0. 16.100 / 0. 16.100 libpostproc 52. 1.100 / 52. 1.100 [x11grab @ 0xab896a0] device: :0.0 -> display: :0.0 x: 0 y: 0 width: 1280 height: 800 [x11grab @ 0xab896a0] shared memory extension found [x11grab @ 0xab896a0] Estimating duration from bitrate, this may be inaccurate Input #0, x11grab, from ':0.0': Duration: N/A, start: 1350136942.608988, bitrate: 983040 kb/s Stream #0:0: Video: rawvideo (BGR[0] / 0x524742), bgr0, 1280x800, 983040 kb/s, 30 tbr, 1000k tbn, 30 tbc [libx264 @ 0xab87320] using cpu capabilities: MMX2 SSE2Fast SSSE3 Cache64 SlowCTZ SlowAtom [libx264 @ 0xab87320] profile High 4:4:4 Predictive, level 3.2, 4:4:4 8-bit [libx264 @ 0xab87320] 264 - core 128 r2 198a7ea - H.264/MPEG-4 AVC codec - Copyleft 2003-2012 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=4 threads=6 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=18.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00 Output #0, matroska, to 'out.mkv': Metadata: encoder : Lavf54.29.105 Stream #0:0: Video: h264, yuv444p, 1280x800, q=-1--1, 1k tbn, 30 tbc Stream mapping: Stream #0:0 -> #0:0 (rawvideo -> libx264) Press [q] to stop, [?] for help frame= 10 fps=0.0 q=0.0 size= 1kB time=00:00:00.00 bitrate= 0.0kbits/sframe= 19 fps= 17 q=0.0 size= 1kB time=00:00:00.00 bitrate= 0.0kbits/sframe= 28 fps= 17 q=0.0 size= 1kB time=00:00:00.00 bitrate= 0.0kbits/sframe= 37 fps= 17 q=0.0 size= 1kB time=00:00:00.00 bitrate= 0.0kbits/sframe= 45 fps= 16 q=0.0 size= 1kB time=00:00:00.00 bitrate= 0.0kbits/sframe= 47 fps= 14 q=0.0 size= 1kB time=00:00:00.00 bitrate= 0.0kbits/sframe= 52 fps= 13 q=24.0 size= 257kB time=00:00:00.00 bitrate=2101632.0kbiframe= 55 fps= 12 q=24.0 size= 257kB time=00:00:00.10 bitrate=20808.2kbitsframe= 59 fps= 11 q=24.0 size= 289kB time=00:00:00.23 bitrate=10145.0kbitsframe= 64 fps= 11 q=24.0 size= 289kB time=00:00:00.40 bitrate=5894.7kbits/frame= 70 fps= 11 q=24.0 size= 289kB time=00:00:00.60 bitrate=3933.1kbits/frame= 72 fps= 10 q=24.0 size= 289kB time=00:00:00.66 bitrate=3549.2kbits/frame= 77 fps=9.8 q=24.0 size= 289kB time=00:00:00.83 bitrate=2837.7kbits/frame= 80 fps=9.6 q=24.0 size= 289kB time=00:00:00.93 bitrate=2533.5kbits/frame= 85 fps=9.3 q=24.0 size= 289kB time=00:00:01.10 bitrate=2146.9kbits/frame= 89 fps=9.3 q=24.0 size= 289kB time=00:00:01.23 bitrate=1917.1kbits/frame= 92 fps=9.1 q=24.0 size= 289kB time=00:00:01.33 bitrate=1773.3kbits/frame= 96 fps=9.0 q=24.0 size= 289kB time=00:00:01.46 bitrate=1612.4kbits/frame= 99 fps=8.8 q=24.0 size= 321kB time=00:00:01.56 bitrate=1676.8kbits/frame= 104 fps=8.7 q=24.0 size= 321kB time=00:00:01.73 bitrate=1515.2kbits/frame= 109 fps=5.3 q=24.0 Lsize= 1093kB time=00:00:03.56 bitrate=2511.5kbits/s video:1092kB audio:0kB subtitle:0 global headers:0kB muxing overhead 0.120198% [libx264 @ 0xab87320] frame I:3 Avg QP:18.93 size:142610 [libx264 @ 0xab87320] frame P:43 Avg QP:20.79 size: 15751 [libx264 @ 0xab87320] frame B:63 Avg QP:23.75 size: 195 [libx264 @ 0xab87320] consecutive B-frames: 21.1% 1.8% 11.0% 66.1% [libx264 @ 0xab87320] mb I I16..4: 50.0% 21.1% 28.9% [libx264 @ 0xab87320] mb P I16..4: 6.1% 0.9% 3.2% P16..4: 5.5% 1.2% 0.6% 0.0% 0.0% skip:82.5% [libx264 @ 0xab87320] mb B I16..4: 0.4% 0.1% 0.0% B16..8: 2.9% 0.1% 0.0% direct: 0.0% skip:96.5% L0:40.7% L1:57.0% BI: 2.3% [libx264 @ 0xab87320] 8x8 transform intra:14.5% inter:46.1% [libx264 @ 0xab87320] coded y,u,v intra: 33.5% 24.1% 25.4% inter: 0.9% 0.4% 0.4% [libx264 @ 0xab87320] i16 v,h,dc,p: 70% 26% 1% 3% [libx264 @ 0xab87320] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 11% 21% 30% 5% 7% 5% 7% 4% 10% [libx264 @ 0xab87320] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 32% 35% 12% 2% 4% 3% 4% 3% 5% [libx264 @ 0xab87320] Weighted P-Frames: Y:0.0% UV:0.0% [libx264 @ 0xab87320] ref P L0: 57.0% 5.6% 26.8% 10.6% [libx264 @ 0xab87320] ref B L0: 69.4% 22.6% 8.0% [libx264 @ 0xab87320] ref B L1: 93.7% 6.3% [libx264 @ 0xab87320] kb/s:2460.40

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