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<!DOCTYPE HTML>
<html>
<head>
<title>Gun Violence Study | Home</title>
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<h1>Gun Violence in USA</h1>
<p>Gun Violence Prediction by Long Short-Term Memory and Beyond</p>
<h6> </h6>
<a href="#about" class="button scroll"><img src="images/down.png"></a>
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<li class="scroll"><a href="#home">Home</a></li>
<li class="scroll"><a href="#about">Introduction</a></li>
<li class="scroll"><a href="#services">Methodologies</a></li>
<li class="scroll"><a href="#portfolio">Visualization</a></li>
<li class="scroll"><a href="https://en.wikipedia.org/wiki/Long_short-term_memory">Github</a></li>
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<h2>Introduction</h2>
<h6> </h6>
<p class="para_a"> U.S. has the 28th highest rank
of deaths from gun violence in the world, the highest one among wealthy countries
and next to Thailand and Phillipine for gun-related death rates. Since January of 2019,
a total of 13,973 deaths has been caused by gun violence. Thus, worries of safety and
fear of possible occurrence of gun violence become quite a headache for the majority of U.S. residents.
Of course, given the statistics above, it is rather understandable and natural for such anxiety.
Thus, we want to use data mining algorithms to help people by predicting the possible amount
of gun violence in each state in the future.
Unfortunately, there has not been a vast amount of studies focusing on prediction and prevention for gun violence.
Therefore, any probability for prediction of possible occurrence of gun violence to a person from our model
can be rather naitve and even misleading.
The major goal for this project is to at least become a motivation for researchers to start utilizing the powerful data methodologies to help diminish the
anxiety and fear of possible gun-related incidence and thus benefit the entire society
</p>
<p class="para_a">Therefore, to predict the possible amount of gun-related incident in the future,
we decide to apply the Long Short-Term Memory.
We train a Long Short-Term Memory model based on records from previous years and such model
is able to make prediction.
</p>
</div>
<div class="grids-of_4">
<div class="wrap">
<div class="grid_of_1">
<div class="sub_grid">
<span>13,973</span>
<p>Gun Violence Death in 2019</p>
</div>
<div class="clear"> </div>
</div>
<div class="grid_of_1">
<div class="sub_grid">
<span>389</span>
<p>Number of Mass Shootings in 2019</p>
</div>
<div class="clear"> </div>
</div>
<div class="grid_of_1">
<div class="sub_grid">
<span>710</span>
<p>Number of Teenagers Killed in 2019</p>
</div>
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</div>
<div class="grid_of_1">
<div class="sub_grid">
<span>27,291</span>
<p>Number of Injuries in 2019</p>
</div>
<div class="clear"> </div>
</div>
<div class="clear"> </div>
</div>
</div>
<script type="text/javascript" src="js/jquery.flexisel.js"></script>
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<div class="services" id="services">
<h3 class="heading"> DataBase </h3>
<p class="desc">Gun Violence Data </p>
<p class="desc"><a href="https://github.com/jamesqo/gun-violence-data">Database source</a></p>
<h6> </h6>
<div class="wrap">
<div class="service_grids">
<div class="grid1">
<div class="grid_sub">
<h3><span>About DataBase</span></h3>
<p>There's currently a lack of large and easily-accessible
amounts of detailed data on gun violence. This database aims
to change that; it makes a record of more than 260k gun violence
incidents, with detailed information about each incident, available
in CSV format. We hope that this will make it easier for data
scientists and statisticians to study gun violence and predict future trends.
</p>
</div>
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</div>
<div class="grid1">
<div class="grid_sub">
<h3><span>Observation </span></h3>
<p>During the initial data cleaning process, we notice the amount of data
recorded in 2013 is quite low. Such low volumn may lead to possible training
or evaluation error later for our model. Thus, we decided to discard all data
in 2013. In addition, despite 29 columns of different data, the most important
columns are "State".
</p>
</div>
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</div>
<div class="grid1">
<div class="grid_sub">
<h3><span>Data Process</span></h3>
<p>We find that each state and each month have some internal
tendency by visualization results. Therefore, we collect the
killed number sequence by the order of year and then split the
data to per state and per month, thus we got 50 states with each
has 12 months data, 600 sequences. Each data contains the killed
number from 2013-2018 years. We further split the whole dataset
into training and testing set to evaluate our method.</p>
</div>
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<h6> </h6>
<h4></h4>
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<h3 class="heading"> Methodologies </h3>
<p class="desc">Long Short-Term Memory </p>
<h6> </h6>
<div class="wrap">
<div class="service_grids">
<div class="grid1">
<div class="grid_sub">
<h3><span>LSTM Model Structure</span></h3>
<img src="images/lstm.png">
<p>LSTM: Long short-term memory (LSTM) is an artificial
recurrent neural network (RNN) architecture used in the
field of deep learning. Unlike standard feedforward neural
networks, LSTM has feedback connections. It can not only process
single data points (such as images), but also entire sequences of
data (such as speech or video).
</p>
</div>
<div class="clear"> </div>
</div>
<div class="grid1">
<div class="grid_sub">
<h3><span>Training </span></h3>
<img src="images/train.png">
<p>As shown on the loss curve figure, the model successfully
learns the variation tendency on training set. And there is an
obvious downtrend when applied it on testing set. This demonstrates
the effectiveness of our long short-term memory model. Thus, by further
applying data in 2018, we can use the model to predict the killed number
on each state on 2019.</p>
</div>
<div class="clear"> </div>
</div>
<div class="grid1">
<div class="grid_sub">
<h3><span>Testing</span></h3>
<img src="images/test.png">
<p><p>We use Stochastic Gradient Descent (SGD) as
the optimization method, with momenta = 0.9 and weight
decay = 5e-03. We use 0.1 learning rate and decay it by
1/10 on 100 and 200 training epochs. Since the dataset is
small, we conduct data augmentation by randomly plus or minus
0~3 for each killed number sequence.</p>
</p>
</div>
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</div>
<div class="grid1">
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<div class="slider2">
<div class=" bg_mask1 bg_mask2">
<div class="wrap">
<p><img src="images/lg.png">In this project, we analyze the deaths caused by gun from 2013 to 2018. Specifically, we give a detailed discussion on the deaths number on different states and visualize the tendency for each month. We find that more people are killed on summer and less people are killed on February. </p>
<p>Furthermore, we count the killed number on each state and find that California, Texas, Florida are the Top. 3 state that gun violence occurs. Moreover, we analyze the age distribution and found juvenile criminals are surprisingly accounts for 11%, which should be taken seriously.<img src="images/lg.png"></p>
<h6> </h6>
<h4>Conclusion</h4>
</div>
</div>
</div>
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<h3 class="heading">Visualization</h3>
<p class="desc"></p>
<h6> </h6>
</div><!--end:section-title-->
<div id="options" class="clearfix">
<ul id="filters" class="option-set clearfix" data-option-key="filter">
<li><a href="#filter" data-option-value=".date">Date</a></li>
<li><a href="#filter" data-option-value=".state">States</a></li>
<li><a href="#filter" data-option-value=".age">Age</a></li>
<li><a href="#filter" data-option-value="">All</a></li>
</ul><!--end:filters-->
</div>
</div><!--end:wrapper-->
<ul id="container" class="clickable cs-style-5 grid clearfix">
<li class="element date">
<figure>
<img src="images/peoplekill.png" alt="" />
<figcaption>
<h3>People Killed By Gun Violence</h3>
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</div>
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<img src="images/generalage.png" alt="" />
<figcaption>
<h3>Age Distribution</h3>
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</figcaption>
</figure>
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<li class="element age">
<figure>
<img src="images/age.png" alt="" />
<figcaption>
<h3>Crime Participant Age</h3>
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</figcaption>
</figure>
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<li class="element state">
<figure>
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<figcaption>
<h3>Top 5 States of People Killed</h3>
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<figure>
<img src="images/all_states.png" alt="" />
<figcaption>
<h3>Total Death By Gun in All States</h3>
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<li class="element state">
<figure>
<img src="images/2017states.png" alt="" />
<figcaption>
<h3>States Death by Gun 2017</h3>
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<h3>States Death by Gun 2017</h3>
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<figure>
<img src="images/2015.png" alt="" />
<figcaption>
<h3>States Death by Gun 2015</h3>
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<li class="element state">
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<figcaption>
<h3>States Death by Gun 2014</h3>
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<div style="color:grey;font-size:110%;margin:10px 80px 10px 80px;">
<p><img src="images/peoplekill.png" height="60%" width="60%" ></p>
<br></br>
<p>Figure shows the relationship between death counts and months.</p>
<p>Each line represents the trends of people killed by gun violence through certain year.</p>
<p>More people are killed on summer and less people are killed on February.</p>
<br></br>
</div>
<div style="color:grey;font-size:110%;margin:10px 80px 10px 80px;">
<p><img src="images/pf-3.jpg" height="60%" width="60%"></p>
<br></br>
<p>We calculated the number of incidents according to age groups through 2013 - 2018.</p>
<p>The number of participants in gun violence is 23899, 154342, 40132 in age range 0 - 18, 18 - 40, 40 - 100 respectively.</p>
<p>Moreover, as shown in the picture, among all age groups, participants in 18-40 age range commit the most crimes.</p></div>
<br></br>
<div style="color:grey;font-size:110%;margin:10px 80px 10px 80px;">
<p><img src="images/all_states.png" height="60%" width="60%"></p>
<br></br>
<p>The maps vividly represent the fatal incidents in the total 50 states of the U.S.</p>
<p>According to the pictures, California, Texas, Florida, and Illinois are always among the top 5 states with highest death counts both in total and from 2015 – 2017.</p>
<p>Hence, these four states need special input on gun violence supervision.</p>
<br></br>
</div>
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