The document describes a student capstone project that analyzes traffic data through collecting tweets, traffic camera images, and weather data to provide users with a traffic analysis for Cincinnati. Various techniques are used like sentiment analysis of tweets, image processing of traffic cameras to count cars, and analyzing weather patterns. A web application was created to display the current traffic analysis on a scale and provide additional context to help users understand the reported traffic status.

1. Student Innovations:
CS Senior Capstone Projects

3. Mike McCarthy Chris Samuelson Chris Beals
Created By:
with
Adivsor:
Fred Annexstein
2014
Controller Behaviors
Left Trigger
Right Trigger
Left Bumper
Right Bumper
DPad/ Left Analog
Right Analog
Block
Ranged Attack
Dash
Melee Attack
Move
Aim
What is EVO?
Desciption
Method
Goals
Future of EVO
Results
Enemy Evolutionary Process
Example Evolution
Genetic Algorithm

4. 3D Stereoscopic Modeling
Andrew Janson, Josh Ellis
Advisor: Dr. Paul Talaga
College of Engineering and Applied Science, University of Cincinnati, Cincinnati, OH 45221
Introduction
How Stereo Vision Works
Methods
Future Work
1
• 3-D scanning is the process of converting physical objects to
numerical data that can be geometrically represented.
• Digital models allow for testing and redesign of real objects without
wasting physical resources.
3
4
Image Capture
Disparity Maps
3-D Representation
• Easy to setup/use software and hardware
• Quickly capture sets of stereoscopic images
• Generate 3D model from disparity map
Objectives 2
http://qz.com/96806/with-3d-printing-youll-be-able-to-replicate-
the-worlds-famous-sculptures/
5 Image Sets
i. Front
ii. Right
iii. Back
iv. Left
v. Top
Actual Depth Calculation
Digital representation
of each side
Calculated height for
each pixel in image
Hexagonal Prism Front View Side View
MeshlabApply Mesh (each side) Point Cloud
ImportSave to file
• Higher resolution for better modeling
• 3-D Printing integration
• Larger scanning area
• Faster processing time
Known
• D-wall
• D-center
Calculate
• D-object
• Object size
• 2 images of same object (slightly different angles)
• Find pixels on each image corresponding to same point on real object
• Triangulation to calculate distance from real object to cameras
Stereoscopic Camera Human Eyes
5
Stereoscopic
Image

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6. For Android™
Daniel
Hagerstrand
Alex Morgan
Advisor:
Dr. Michael Helmick
Background
Design
Cascade LMSis an open source Learning
Management System, piloted by the University of
Cincinnati's computer science department, that
combines course management with social
networking to connect students and professors.
With Cascade LMSfor Android, students can view
and post status updates, submit assignments, and
check their grades all from their Android device.
Android is a trademark of Google Inc.
Results
➔ We have successfully produced a
client for Cascade LMSusing OAuth
and the XML API.
➔ Users can log into Cascade LMSfrom
any supported Android device.
➔ The app provides viewing access to
the Social Stream, Course Blog,
Documents, Assignments, and Grades.
Goals
➔ Create a free, open-source
Android application that can
communicate with a Cascade LMS
server.
➔ Design a UI that allows access to
Cascade LMSwhile also providing
the experience Android users
expect.
➔ Let students interact with their
professors and classmates
through the Social Stream and
Course Blog.
➔ Allow students to view and
manage their Documents,
Assignments, and Grades for each
course.
➔ Focus on the social aspect of
Cascade LMSby placing the Social
Stream front and center.
We’re on GitHub!
http://git.io/dP-AGw
Future
➔ Let students submit assignments
from their device.
➔ Push notifications to students when
grades or assignments are posted.
➔ Publish the application to the Google
Play Store.

8. GUARDS II
Goal-driven Users and Agents for Recognition , Di s covery and Synthesis of Knowledge II
Introduction
Technologies and Tools
Datasets
GUARDS II analyzes trafficda ta through the
collectio
n
of tw eets, trafficc amera images and
weather data. Techniques such as twitter
sentime n t analysis, image processing of traffic
images, and in-depth analysis of weather data
patterns are util
i
z ed to give users an analysis of
the current trafficin Ci nci nn ati.
Programming:
Python 2.6, Java, CSS, Bootstrap, HTML 5
Infrastructure:
EECS Cloud running OpenStack
CentOS operating s ystem
MySQL databases
Twitter Feed Data Pull:
Twitter Feed (Python)
Tweets are pulled with a script using
Tweepy API
Util
i
z es keyword searching algorithm
Sentiment Analysis (Java)
Uses Stanford Natural Language
Processing Algorithm (CoreNLP) to
analyze tweet meaning and sentime n t
Categorizes sentime n t of each state-
ment: Positiv
e
, Neutral, and Negative
Added a custom key word analysis based
on trafficr elated terms
- wreck, incident, construction ,
blocked, backed-up, etc.
Detects anomalous language
The Team and Project Sponsors
Motivation
GUARDS II is a proof-of-concept project that can
be used to detect anomalies in various applica-
tio
n
s. W e have demonstrated the project
application f or traffic datasets.
Other application s include:
Natio
n
al Secur it y and Crime-related datasets
Banking and Finance datasets
Insurance datasets
Image Processing:
TrafficCame r a Image Capture (Python)
Download images every 4 seconds
Initia
l
I mage Processing (Java)
Converts image to grayscale
Reduces quality of image to assist in
recognizing individual vehicles
Car Counting (Java)
Takes two images as input
Finds the differences in images to detect
and count moving vehicles
TrafficIma g es
Weather Data Pull:
Weather Analysis (Python)
Uses Weather Underground API
Analyzes weather data for given city:
-Temperature
-Precipitation
-Humidity
-Wind Gust
Main component is precipitation in the
last hour
Weather Analysis (Java)
Uses thresholds to determine the effect
that weather factors have on traffic
tim
e
Weather DataTwitter Feed
Design
The Project Customer
The main purpose of the project is to work with
Edaptive Computing Inc. to mine heterogeneous
datasets and analyze data. GUARDS II focuses on
trafficda ta and displays results to users based on
the program’s find ings. The results of the project
are aimed to assist Edaptive Computing with
detectin
g
pa tterns for their AFRL based projects.
GUARDS II Web Application
Craig Ashworth Priya Chawla
Samuel ReedAndrew Yingling
Functio
n
al it y:
Users select a location on the hi g hway
they would like to examine
- A map is displayed with the selected location
We present the current traffican alysis
on a 5-tier sc ale:
- Significantly Faster
- Slightly Faster
- Average
- Slightly Slower
- Significantly Slower
Additional data is provided to help the
user understand the purpose of the
traffics tatus
Users can view the project background,
history of past results, and information
about the team on the other tabs of the
web application
Before Image Processing: After Image Processing:
Advisor: Dr. Raj Bhatnagar