From 9892ed27acd7b45479444ff6eb7b3896429cb8c5 Mon Sep 17 00:00:00 2001
From: Navan Chauhan <navanchauhan@gmail.com>
Date: Sat, 14 Mar 2020 13:05:22 +0530
Subject: Publish deploy 2020-03-14 13:05

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-<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content"><channel><title>Navan Chauhan</title><description>Welcome to my personal fragment of the internet. Majority of the posts should be complete.</description><link>https://navanchauhan.github.io/</link><language>en</language><lastBuildDate>Tue, 10 Mar 2020 13:21:07 +0530</lastBuildDate><pubDate>Tue, 10 Mar 2020 13:21:07 +0530</pubDate><ttl>250</ttl><atom:link href="https://navanchauhan.github.io/feed.rss" rel="self" type="application/rss+xml"/><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-03-08-Making-Vaporwave-Track</guid><title>Making My First Vaporwave Track (Remix)</title><description>I made my first vaporwave remix</description><link>https://navanchauhan.github.io/posts/2020-03-08-Making-Vaporwave-Track</link><pubDate>Sun, 8 Mar 2020 23:17:00 +0530</pubDate><content:encoded><![CDATA[<h1>Making My First Vaporwave Track (Remix)</h1><p>I finally completed my first quick and dirty vaporwave remix of "I Want It That Way" by the Backstreet Boys</p><h1>V A P O R W A V E</h1><p>Vaporwave is all about A E S T H E T I C S. Vaporwave is a type of music genre that emmerged as a parody of Chillwave, shared more as a meme rather than a proper musical genre. Of course this changed as the genre become mature</p><h1>How to Vaporwave</h1><p>The first track which is considered to be actual Vaporwave is Ramona Xavier's Macintosh Plus, this unspokenly set the the guidelines for making Vaporwave</p><ul><li>Take a 1980s RnB song</li><li>Slow it down</li><li>Add Bass and Trebble</li><li>Add again</li><li>Add Reverb ( make sure its wet )</li></ul><p>There you have your very own Vaporwave track.</p><p>( Now, there are some tracks being produced which are not remixes and are original )</p><h1>My Remix</h1><iframe width="300" height="202" src="https://www.bandlab.com/embed/?id=aa91e786-6361-ea11-a94c-0003ffd1cad8&blur=false" frameborder="0" allowfullscreen></iframe><h1>Where is the Programming?</h1><p>The fact that there are steps on producing Vaporwave, this gave me the idea that Vaporwave can actually be made using programming, stay tuned for when I publish the program which I am working on ( Generating A E S T H E T I C artwork and remixes)</p>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-03-03-Playing-With-Android-TV</guid><title>Tinkering with an Android TV</title><description>Tinkering with an Android TV</description><link>https://navanchauhan.github.io/posts/2020-03-03-Playing-With-Android-TV</link><pubDate>Tue, 3 Mar 2020 18:37:00 +0530</pubDate><content:encoded><![CDATA[<h1>Tinkering with an Android TV</h1><p>So I have an Android TV, this posts covers everything I have tried on it</p><h2>Contents</h2><ol><li><a href="#IP-Address">Getting TV's IP Address</a></li><li><a href="#Developer-Settings">Enable Developer Settings</a></li><li><a href="#Enable-ADB">Enable ADB</a></li><li><a href="#Connect-ADB">Connect ADB</a></li><li><a href="#">Manipulating Packages</a></li></ol><h2>IP-Address</h2><p><em>These steps should be similar for all Android-TVs</em></p><ul><li>Go To Settings</li><li>Go to Network</li><li>Advanced Settings</li><li>Network Status</li><li>Note Down IP-Address</li></ul><p>The other option is to go to your router's server page and get connected devices</p><h2>Developer-Settings</h2><ul><li>Go To Settings</li><li>About</li><li>Continously click on the "Build" option until it says "You are a Developer"</li></ul><h2>Enable-ADB</h2><ul><li>Go to Settings</li><li>Go to Developer Options</li><li>Scroll untill you find ADB Debugging and enable that option</li></ul><h2>Connect-ADB</h2><ul><li>Open Terminal (Make sure you have ADB installed)</li><li>Enter the following command <code>adb connect &lt;IP_ADDRESS&gt;</code></li><li>To test the connection run <code>adb logcat</code></li></ul><h2>Manipulating Apps / Packages</h2><h3>Listing Packages</h3><ul><li><code>adb shell</code></li><li><code>pm list packages</code></li></ul><h3>Installing Packages</h3><ul><li><code>adb install -r package.apk</code></li></ul><h3>Uninstalling Packages</h3><ul><li><code>adb uninstall com.company.yourpackagename</code></li></ul>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-03-02-Open-Peeps</guid><title>Open Peeps</title><description>Trying out Open Peeps, a CC0 Library</description><link>https://navanchauhan.github.io/posts/2020-03-02-Open-Peeps</link><pubDate>Mon, 2 Mar 2020 13:52:00 +0530</pubDate><content:encoded><![CDATA[<h1>Open Peeps</h1><h4>About Open Peeps</h4><blockquote><p>Open Peeps is a hand-drawn illustration library to create scenes of people. You can use them in product illustration, marketing, comics, product states, user flows, personas, storyboarding, quinceañera invitations, or whatever you want! - Product Hunt</p></blockquote><h2>Some Examples</h2><h3>Standing</h3><img src="https://navanchauhan.github.io//assets/posts/open-peeps/ex-1.svg" width="20%">
+<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content"><channel><title>Navan Chauhan</title><description>Welcome to my personal fragment of the internet. Majority of the posts should be complete.</description><link>https://navanchauhan.github.io/</link><language>en</language><lastBuildDate>Sat, 14 Mar 2020 13:05:12 +0530</lastBuildDate><pubDate>Sat, 14 Mar 2020 13:05:12 +0530</pubDate><ttl>250</ttl><atom:link href="https://navanchauhan.github.io/feed.rss" rel="self" type="application/rss+xml"/><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-03-08-Making-Vaporwave-Track</guid><title>Making My First Vaporwave Track (Remix)</title><description>I made my first vaporwave remix</description><link>https://navanchauhan.github.io/posts/2020-03-08-Making-Vaporwave-Track</link><pubDate>Sun, 8 Mar 2020 23:17:00 +0530</pubDate><content:encoded><![CDATA[<h1>Making My First Vaporwave Track (Remix)</h1><p>I finally completed my first quick and dirty vaporwave remix of "I Want It That Way" by the Backstreet Boys</p><h1>V A P O R W A V E</h1><p>Vaporwave is all about A E S T H E T I C S. Vaporwave is a type of music genre that emmerged as a parody of Chillwave, shared more as a meme rather than a proper musical genre. Of course this changed as the genre become mature</p><h1>How to Vaporwave</h1><p>The first track which is considered to be actual Vaporwave is Ramona Xavier's Macintosh Plus, this unspokenly set the the guidelines for making Vaporwave</p><ul><li>Take a 1980s RnB song</li><li>Slow it down</li><li>Add Bass and Trebble</li><li>Add again</li><li>Add Reverb ( make sure its wet )</li></ul><p>There you have your very own Vaporwave track.</p><p>( Now, there are some tracks being produced which are not remixes and are original )</p><h1>My Remix</h1><iframe width="300" height="202" src="https://www.bandlab.com/embed/?id=aa91e786-6361-ea11-a94c-0003ffd1cad8&blur=false" frameborder="0" allowfullscreen></iframe><h1>Where is the Programming?</h1><p>The fact that there are steps on producing Vaporwave, this gave me the idea that Vaporwave can actually be made using programming, stay tuned for when I publish the program which I am working on ( Generating A E S T H E T I C artwork and remixes)</p>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-03-03-Playing-With-Android-TV</guid><title>Tinkering with an Android TV</title><description>Tinkering with an Android TV</description><link>https://navanchauhan.github.io/posts/2020-03-03-Playing-With-Android-TV</link><pubDate>Tue, 3 Mar 2020 18:37:00 +0530</pubDate><content:encoded><![CDATA[<h1>Tinkering with an Android TV</h1><p>So I have an Android TV, this posts covers everything I have tried on it</p><h2>Contents</h2><ol><li><a href="#IP-Address">Getting TV's IP Address</a></li><li><a href="#Developer-Settings">Enable Developer Settings</a></li><li><a href="#Enable-ADB">Enable ADB</a></li><li><a href="#Connect-ADB">Connect ADB</a></li><li><a href="#">Manipulating Packages</a></li></ol><h2>IP-Address</h2><p><em>These steps should be similar for all Android-TVs</em></p><ul><li>Go To Settings</li><li>Go to Network</li><li>Advanced Settings</li><li>Network Status</li><li>Note Down IP-Address</li></ul><p>The other option is to go to your router's server page and get connected devices</p><h2>Developer-Settings</h2><ul><li>Go To Settings</li><li>About</li><li>Continously click on the "Build" option until it says "You are a Developer"</li></ul><h2>Enable-ADB</h2><ul><li>Go to Settings</li><li>Go to Developer Options</li><li>Scroll untill you find ADB Debugging and enable that option</li></ul><h2>Connect-ADB</h2><ul><li>Open Terminal (Make sure you have ADB installed)</li><li>Enter the following command <code>adb connect &lt;IP_ADDRESS&gt;</code></li><li>To test the connection run <code>adb logcat</code></li></ul><h2>Manipulating Apps / Packages</h2><h3>Listing Packages</h3><ul><li><code>adb shell</code></li><li><code>pm list packages</code></li></ul><h3>Installing Packages</h3><ul><li><code>adb install -r package.apk</code></li></ul><h3>Uninstalling Packages</h3><ul><li><code>adb uninstall com.company.yourpackagename</code></li></ul>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-03-02-Open-Peeps</guid><title>Open Peeps</title><description>Trying out Open Peeps, a CC0 Library</description><link>https://navanchauhan.github.io/posts/2020-03-02-Open-Peeps</link><pubDate>Mon, 2 Mar 2020 13:52:00 +0530</pubDate><content:encoded><![CDATA[<h1>Open Peeps</h1><h4>About Open Peeps</h4><blockquote><p>Open Peeps is a hand-drawn illustration library to create scenes of people. You can use them in product illustration, marketing, comics, product states, user flows, personas, storyboarding, quinceañera invitations, or whatever you want! - Product Hunt</p></blockquote><h2>Some Examples</h2><h3>Standing</h3><img src="https://navanchauhan.github.io//assets/posts/open-peeps/ex-1.svg" width="20%">
 
 
 ]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminal</guid><title>How to setup Bluetooth on a Raspberry Pi</title><description>Connecting to Bluetooth Devices using terminal, tested on Raspberry Pi Zero W</description><link>https://navanchauhan.github.io/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminal</link><pubDate>Sun, 19 Jan 2020 15:27:00 +0530</pubDate><content:encoded><![CDATA[<h1>How to setup Bluetooth on a Raspberry Pi</h1><p><em>This was tested on a Raspberry Pi Zero W</em></p><h2>Enter in the Bluetooth Mode</h2><p><code>pi@raspberrypi:~ $ bluetoothctl</code></p><p><code>[bluetooth]# agent on</code></p><p><code>[bluetooth]# default-agent</code></p><p><code>[bluetooth]# scan on</code></p><h2>To Pair</h2><p>While being in bluetooth mode</p><p><code>[bluetooth]# pair XX:XX:XX:XX:XX:XX</code></p><p>To Exit out of bluetoothctl anytime, just type exit</p>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate</guid><title>Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</title><description>Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle</description><link>https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate</link><pubDate>Thu, 16 Jan 2020 10:36:00 +0530</pubDate><content:encoded><![CDATA[<h1>Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</h1><p><em>For setting up Kaggle with Google Colab, please refer to <a href="https://navanchauhan.github.io//posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab/"> my previous post</a></em></p><h2>Dataset</h2><h3>Mounting Google Drive</h3><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">os</span>
@@ -932,7 +932,7 @@
 </code></pre><p>Extracting Files</p><p>First we need to collect all parts, then</p><pre><code><div class="highlight"><span></span><span class="nt">zip</span><span class="na"> -F oodlesofnoodles.zip --out merged.zip</span>
 </div>
 
-</code></pre>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2019-12-04-Google-Teachable-Machines</guid><title>Image Classifier With Teachable Machines</title><description>Tutorial on creating a custom image classifier quickly with Google Teachanle Machines</description><link>https://navanchauhan.github.io/posts/2019-12-04-Google-Teachable-Machines</link><pubDate>Wed, 4 Dec 2019 18:23:00 +0530</pubDate><content:encoded><![CDATA[<h1>Image Classifier With Teachable Machines</h1><p>Made for Google Code-In</p><p><strong>Task Description</strong></p><p>Using Glitch and the Teachable Machines, build a Book Detector with Tensorflow.js. When a book is recognized, the code would randomly suggest a book/tell a famous quote from a book. Here is an example Project to get you started: https://glitch.com/~voltaic-acorn</p><h3>Details</h3><ol><li>Collecting Data</li></ol><p>Teachable Machine allows you to create your dataset just by using your webcam! I created a database consisting of three classes ( Three Books ) and approximately grabbed 100 pictures for each book/class</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/01-collect.png"/><ol start="2"><li>Training</li></ol><p>Training on teachable machines is as simple as clicking the train button. I did not even have to modify any configurations.</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/02-train.png"/><ol start="3"><li>Finding Labels</li></ol><p>Because I originally entered the entire name of the book and it's author's name as the label, the class name got truncated (Note to self, use shorter class names :p ). I then modified the code to print the modified label names in an alert box.</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/03-label.png"/><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/04-alert.png"/><ol start="4"><li>Adding a suggestions function</li></ol><p>I first added a text field on the main page and then modified the JavaScript file to suggest a similar book whenever the model predicted with an accuracy &gt;= 98%</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/05-html.png"/><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/06-js.png"/><ol start="5"><li>Running!</li></ol><p>Here it is running!</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/07-eg.png"/><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/08-eg.png"/><p>Remix this project:-</p><p>https://luminous-opinion.glitch.me</p>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response</guid><title>Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response</title><description>This paper is about Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response.</description><link>https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response</link><pubDate>Tue, 14 May 2019 02:42:00 +0530</pubDate><content:encoded><![CDATA[<h1>Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response</h1><blockquote><p>Based on the project showcased at Toyota Hackathon, IITD - 17/18th December 2018</p></blockquote><p><a href="https://www.irjet.net/archives/V6/i5/IRJET-V6I5318.pdf">Download paper here</a></p><p>Recommended citation:</p><h3>ATP</h3><pre><code><div class="highlight"><span></span><span class="n">Chauhan</span><span class="p">,</span> <span class="n">N</span><span class="p">.</span> <span class="p">(</span><span class="mi">2019</span><span class="p">).</span> <span class="p">&amp;</span><span class="n">quot</span><span class="p">;</span><span class="n">Detecting</span> <span class="n">Driver</span> <span class="n">Fatigue</span><span class="p">,</span> <span class="n">Over</span><span class="o">-</span><span class="n">Speeding</span><span class="p">,</span> <span class="n">and</span> <span class="n">Speeding</span> <span class="n">up</span> <span class="n">Post</span><span class="o">-</span><span class="n">Accident</span> <span class="n">Response</span><span class="p">.&amp;</span><span class="n">quot</span><span class="p">;</span> <span class="p">&lt;</span><span class="n">i</span><span class="p">&gt;</span><span class="n">International</span> <span class="n">Research</span> <span class="n">Journal</span> <span class="n">of</span> <span class="n">Engineering</span> <span class="n">and</span> <span class="n">Technology</span> <span class="p">(</span><span class="n">IRJET</span><span class="p">),</span> <span class="mi">6</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span><span class="o">&lt;/</span><span class="n">i</span><span class="p">&gt;.</span>
+</code></pre>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2019-12-04-Google-Teachable-Machines</guid><title>Image Classifier With Teachable Machines</title><description>Tutorial on creating a custom image classifier quickly with Google Teachanle Machines</description><link>https://navanchauhan.github.io/posts/2019-12-04-Google-Teachable-Machines</link><pubDate>Wed, 4 Dec 2019 18:23:00 +0530</pubDate><content:encoded><![CDATA[<h1>Image Classifier With Teachable Machines</h1><p>Made for Google Code-In</p><p><strong>Task Description</strong></p><p>Using Glitch and the Teachable Machines, build a Book Detector with Tensorflow.js. When a book is recognized, the code would randomly suggest a book/tell a famous quote from a book. Here is an example Project to get you started: https://glitch.com/~voltaic-acorn</p><h3>Details</h3><ol><li>Collecting Data</li></ol><p>Teachable Machine allows you to create your dataset just by using your webcam! I created a database consisting of three classes ( Three Books ) and approximately grabbed 100 pictures for each book/class</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/01-collect.png"/><ol start="2"><li>Training</li></ol><p>Training on teachable machines is as simple as clicking the train button. I did not even have to modify any configurations.</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/02-train.png"/><ol start="3"><li>Finding Labels</li></ol><p>Because I originally entered the entire name of the book and it's author's name as the label, the class name got truncated (Note to self, use shorter class names :p ). I then modified the code to print the modified label names in an alert box.</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/03-label.png"/><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/04-alert.png"/><ol start="4"><li>Adding a suggestions function</li></ol><p>I first added a text field on the main page and then modified the JavaScript file to suggest a similar book whenever the model predicted with an accuracy &gt;= 98%</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/05-html.png"/><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/06-js.png"/><ol start="5"><li>Running!</li></ol><p>Here it is running!</p><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/07-eg.png"/><img src="https://navanchauhan.github.io//assets/gciTales/01-teachableMachines/08-eg.png"/><p>Remix this project:-</p><p>https://luminous-opinion.glitch.me</p>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response</guid><title>Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response</title><description>This paper is about Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response.</description><link>https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response</link><pubDate>Tue, 14 May 2019 02:42:00 +0530</pubDate><content:encoded><![CDATA[<h1>Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response</h1><blockquote><p>Based on the project showcased at Toyota Hackathon, IITD - 17/18th December 2018</p></blockquote><p>Edit: It seems like I haven't mentioned Adrian Rosebrock of PyImageSearch anywhere. I apologize for this mistake.</p><p><a href="https://www.irjet.net/archives/V6/i5/IRJET-V6I5318.pdf">Download paper here</a></p><p>Recommended citation:</p><h3>ATP</h3><pre><code><div class="highlight"><span></span><span class="n">Chauhan</span><span class="p">,</span> <span class="n">N</span><span class="p">.</span> <span class="p">(</span><span class="mi">2019</span><span class="p">).</span> <span class="p">&amp;</span><span class="n">quot</span><span class="p">;</span><span class="n">Detecting</span> <span class="n">Driver</span> <span class="n">Fatigue</span><span class="p">,</span> <span class="n">Over</span><span class="o">-</span><span class="n">Speeding</span><span class="p">,</span> <span class="n">and</span> <span class="n">Speeding</span> <span class="n">up</span> <span class="n">Post</span><span class="o">-</span><span class="n">Accident</span> <span class="n">Response</span><span class="p">.&amp;</span><span class="n">quot</span><span class="p">;</span> <span class="p">&lt;</span><span class="n">i</span><span class="p">&gt;</span><span class="n">International</span> <span class="n">Research</span> <span class="n">Journal</span> <span class="n">of</span> <span class="n">Engineering</span> <span class="n">and</span> <span class="n">Technology</span> <span class="p">(</span><span class="n">IRJET</span><span class="p">),</span> <span class="mi">6</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span><span class="o">&lt;/</span><span class="n">i</span><span class="p">&gt;.</span>
 </div>
 
 </code></pre><h3>BibTeX</h3><pre><code><div class="highlight"><span></span><span class="p">@</span><span class="n">article</span><span class="p">{</span><span class="n">chauhan_2019</span><span class="p">,</span> <span class="n">title</span><span class="p">={</span><span class="n">Detecting</span> <span class="n">Driver</span> <span class="n">Fatigue</span><span class="p">,</span> <span class="n">Over</span><span class="o">-</span><span class="n">Speeding</span><span class="p">,</span> <span class="n">and</span> <span class="n">Speeding</span> <span class="n">up</span> <span class="n">Post</span><span class="o">-</span><span class="n">Accident</span> <span class="n">Response</span><span class="p">},</span> <span class="n">volume</span><span class="p">={</span><span class="mi">6</span><span class="p">},</span> <span class="n">url</span><span class="p">={</span><span class="n">https</span><span class="p">:</span><span class="c1">//www.irjet.net/archives/V6/i5/IRJET-V6I5318.pdf}, number={5}, journal={International Research Journal of Engineering and Technology (IRJET)}, author={Chauhan, Navan}, year={2019}}</span>
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