dhfromkorea

<Response>
    <Dial action="https://app.close.io/calls/forward_or_voicemail/" sipHeaders="Call-ID=acti_WFzoC1SQhHiLgCiAAQOKCExwcCwdrskXIoH57gCBHY1,Organization-ID=orga_3XfAe7NxJVQ6sxplkj6LHOF8Towrb90zHOTAyDTxJGh" timeout="30">
      <User>sip:closeio_sip_user@phone.plivo.com</User>
    </Dial>
  </Response>

dhfromkorea

<Response>
    <Dial action="https://app.close.io/calls/voicemail/" confirmKey="1" confirmSound="https://app.close.io/calls/press_1_to_accept/" timeout="30">
      <User sipHeaders="Call-ID=acti_dOqGeD17hRQRaP7t5QUcTVsZjYb3JuOSRsNKgwBYRYy,User-ID=user_3Fd6uKJx1YEnNzdxLYpinzrEKe0tLtFq4PmcOYlAFQp,Organization-ID=orga_TdFaRupCS0Cb7E1agBfcXu2DFXUQyN3k4LitSINID8v">sip:closeiocloseio_sip_user_1@phone.plivo.com</User>
      <User sipHeaders="Call-ID=acti_dOqGeD17hRQRaP7t5QUcTVsZjYb3JuOSRsNKgwBYRYy,User-ID=user_JzXh7wUoXMP1oRRPJM7tCujOWMSTruIXSCCHTtZ8y9S,Organization-ID=orga_TdFaRupCS0Cb7E1agBfcXu2DFXUQyN3k4LitSINID8v">sip:closeio_sip_user_2@phone.plivo.com</User>
      <Number>18008889999</Number>
    </Dial>
  </Response>

dhfromkorea

{
     'Direction':'inbound',
     'X-PH-Contact-ID':'cont_XpV6S7xJz4TMMzR7fyjrqtIOFkuZc256G6yjFtiZXXw',
     'From':'sip:closeio_sip_endpoint_username@phone.plivo.com',
     'CallerName':'closeio_sip_endpoint_username',
     'X-PH-Call-ID':'acti_WYzqqMLJSraAB8Pzwm3vcYixW5wEyIyk5tdkBYvG2vZ',
     'BillRate':'0.1',
     'X-PH-Organization-ID':'orga_IwDwdnJk2n2GZAGxN0U4ZRJVM8tndgCCFf9jJypQ0Pu',
     'To':'15556667777',
     'X-PH-Lead-ID':'lead_ZUpJKIfsyt6PIf4enKfr42zZFhsQguVviHNXDqE32oB',

dhfromkorea

<Response>
    <Dial callerId="16501112222" dialMusic="real">
      <Number>15556667777</Number>
    </Dial>
  </Response>

dhfromkorea

// by default, it fetches pdf
// change pdf to an extension you want
var pdflinks = [];
Array.prototype.map.call(document.querySelectorAll("a[href$=\".pdf\"]"), function(e, i) {
  if ((pdflinks || []).indexOf(e.href) == -1) {
    pdflinks.push(e.href);
  }
});
console.log(pdflinks.join(" "));
// copy the logged file names

dhfromkorea

if (!require(phaseR)){
    install.packages('phaseR')
    require(phaseR)
}

# a system of two non-linear autonomous ODE's
ode = function (t, y, parameters) {
    x <- y[1]
    y <- y[2]
    dy <- numeric(2)

dhfromkorea

var fibonacci = function(){
  var _cache = [];
  
  var fib = function(i){
      if (i < 0) {
         console.err('invalid input. i must be >= 0');
         return;
      }
      if (i < 2) {
         _cache[i] = i;

dhfromkorea

var fizzbuzz = function(n){
    var answer = '';
    if (n % 3 === 0) {          
        answer = 'Fizz';        
    }
    if (n % 5 === 0) {
        answer += 'Buzz';
    }
    if (!answer){
        answer = n;

dhfromkorea

fp = FingerPrint(path_to_dejavu_config_file)
timestamp_pb = 20000 # program boundary timestamp in secs from
PAD = 10 # temporal padding to apply to the timestamp

# slice an audio segement off the video
fp.slice_audio_segment(path_to_full_video_or_audio, pb - PAD, pb + PAD, "mp4")

# extract the fingerprint of the segment and save it to db
# db's configured in the .config file
# the path for the full video/audio and the segment may be different

dhfromkorea

# this model is the most naive one
# find the occurences of the keywords listed and consider them to be matched.
# TODO will be to apply a Bag of Words model or some sort and assign credit score

# read raw caption files
caption_data, metadata = next(load_caption_files(path_to_caption_file))                        
# combine captions by 10 seconds (i.e. make time blocks)
X = split_caption_to_X(caption_data)

keywords = ['caption', 'type=story', 'type=commercial']