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github-actions 2021-06-23 23:13:25 +00:00
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<tr>
<td>Phone Activity Recognition</td>
<td>RAPIDS</td>
<td>N</td>
<td>N</td>
<td>N</td>
<td>Y</td>
<td>Y</td>
<td>Y</td>
</tr>
<tr>
<td>Phone Applications Foreground</td>
@ -2484,7 +2484,7 @@ When generating test data, all traces for iOS device need to be unique otherwise
</table>
<h2 id="wifi">WIFI<a class="headerlink" href="#wifi" title="Permanent link">&para;</a></h2>
<p>There are two wifi features (<code>phone wifi connected</code> and <code>phone wifi visible</code>). The raw test data are seperatly stored in the <code>phone_wifi_connected_raw.csv</code> and <code>phone_wifi_visible_raw.csv</code>.</p>
<p>Description</p>
<p>Description </p>
<ul>
<li>One episode for each <code>epoch</code> (<code>night</code>, <code>morining</code>, <code>afternoon</code> and <code>evening</code>)</li>
<li>Two two episodes in the same time segment (<code>daily</code> and <code>30-min</code>)</li>
@ -2640,31 +2640,81 @@ When generating test data, all traces for iOS device need to be unique otherwise
(i.e. for iPhone) are empty data files.</li>
</ul>
<h2 id="activity-recognition">Activity Recognition<a class="headerlink" href="#activity-recognition" title="Permanent link">&para;</a></h2>
<p>Description</p>
<ul>
<li>The raw Activity Recognition data file contains data for 1 day.</li>
<li>The raw Activity Recognition data each <code>epoch</code> period contains
rows that records 2 - 5 different <code>activity_types</code>. The is such
that durations of activities can be tested. Additionally, there
are records that mimic the duration of an activity over the time
boundary of neighboring epochs. (For example, there a set of
records that mimic the participant <code>in_vehicle</code> from <code>afternoon</code>
into <code>evening</code>)</li>
<li>There is one file each with raw Activity Recognition data for
testing both iOS and Android data formats.
(plugin_google_activity_recognition_raw.csv for android and
plugin_ios_activity_recognition_raw.csv for iOS)</li>
<li>There is also an additional empty data file for both android and
iOS for testing empty data files.</li>
<li>The 4-day raw conversation data is contained in <code>plugin_google_activity_recognition_raw.csv</code> and <code>plugin_ios_activity_recognition_raw.csv</code>.</li>
<li>Two episodes locate in the same 30-min segment (<code>Fri 04:01:54</code> and <code>Fri 04:13:52</code>)</li>
<li>One episode for each daily segment (<code>night</code>, <code>morning</code>, <code>afternoon</code> and <code>evening</code>)</li>
<li>Two episodes locate in the same daily segment (<code>Fri 05:03:09</code> and <code>Fri 05:50:36</code>)</li>
<li>Two episodes with the time difference less than <code>5 mins</code> threshold (<code>Fri 07:14:21</code> and <code>Fri 07:18:50</code>)</li>
<li>One episode before the time switch (<code>Sun 00:46:00</code>) and one episode after the time switch (<code>Sun 03:42:00</code>)</li>
</ul>
<p>Checklist</p>
<table>
<thead>
<tr>
<th>time segment</th>
<th>single tz</th>
<th>multi tz</th>
<th>platform</th>
</tr>
</thead>
<tbody>
<tr>
<td>30min</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>morning</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>daily</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>threeday</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>weekend</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>beforeMarchEvent</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
<tr>
<td>beforeNovemberEvent</td>
<td>OK</td>
<td>OK</td>
<td>android, iOS</td>
</tr>
</tbody>
</table>
<h2 id="conversation">Conversation<a class="headerlink" href="#conversation" title="Permanent link">&para;</a></h2>
<p>The 4-day raw conversation data is contained in <code>phone_conversation_raw.csv</code>. The different <code>inference</code> records are
randomly distributed throughout the <code>epoch</code>. </p>
<p>Description
- One episode for each daily segment (<code>night</code>, <code>morning</code>, <code>afternoon</code> and <code>evening</code>) on each day
- Two episodes near the transition of the daily segment, one starts at the end of the afternoon, <code>Fri 17:10:00</code> and another one starts at the beginning of the evening, <code>Fri 18:01:00</code>
- One episode across two segments, <code>daily</code> and <code>30-mins</code>, (from <code>Fri 05:55:00</code> to <code>Fri 06:00:41</code>)
- Two episodes locate in the same daily segment (<code>Sat 12:45:36</code> and <code>Sat 16:48:22</code>)
- One episode before the time switch, <code>Sun 00:15:06</code>, and one episode after the time switch, <code>Sun 06:01:00</code></p>
<p>Description</p>
<ul>
<li>One episode for each daily segment (<code>night</code>, <code>morning</code>, <code>afternoon</code> and <code>evening</code>) on each day</li>
<li>Two episodes near the transition of the daily segment, one starts at the end of the afternoon, <code>Fri 17:10:00</code> and another one starts at the beginning of the evening, <code>Fri 18:01:00</code></li>
<li>One episode across two segments, <code>daily</code> and <code>30-mins</code>, (from <code>Fri 05:55:00</code> to <code>Fri 06:00:41</code>)</li>
<li>Two episodes locate in the same daily segment (<code>Sat 12:45:36</code> and <code>Sat 16:48:22</code>)</li>
<li>One episode before the time switch, <code>Sun 00:15:06</code>, and one episode after the time switch, <code>Sun 06:01:00</code></li>
</ul>
<p>Data format</p>
<table>
<thead>

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<tr>
<td>durationstationary</td>
<td>minutes</td>
<td>The total duration of <code>[ACTIVITY_CLASSES][STATIONARY]</code> episodes</td>
<td>The total duration of <code>[ACTIVITY_CLASSES][STATIONARY]</code> episodes of still and tilting activities</td>
</tr>
<tr>
<td>durationmobile</td>

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