Road Map
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First, the annotated bibliography, the preliminary version submitted two days ago: craig_annotated_bibliography.

Second, I want to outline my general plan here. After a meeting with Charlie this week and carefully reading some of the more fundamental papers for the topic, I have greater clarity about the project.

My general plan, subject to – potentially major – modification as the class assignments are posted, is as follows (each date is a deadline):

  • 10-01: Read all papers and complete an annotated bibliography which can be melded into a survey paper
  • 10-04: Complete the survey paper (technically due 10-05)
  • 11-01: Produce outline of the paper and high-level software design
  • 12-01: Done with paper, poster content ready, have some software developed
  • 12-?: Poster and presentation with the others who will not be at Earlham next semester
  • Regular presentations as they come due

I graduate in December so my project is somewhat more limited in scope than those who will be here the full year, but I anticipate a complete paper and a decent initial version of a piece of software by the end.

UPDATE: The annotated bibliography included here has been updated to correct a citation. Wang 2013, not Wang 2011, is the correct citation for the Facebook study.

Updated Project Idea
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Topic: Augmented Reality to enhance campus tour experience

Advisor: Xunfei Jiang

I would like to develop an interactive and informative mobile application that will assist the prospies and other outside visitors during their campus visits with the use of Augmented Reality. By using Augmented Reality’s ability to create virtual overlays on the mobile screens, I would like to provide the users with rich information about the buildings on the campus, the departments and their curriculums, the current on-campus events and many other things that are available to the public. On top of providing information, the application will also help people navigate their ways on campus, offer interactive and fun mini game activities and has some features like scheduling a short meeting with a professor. Currently I am planning to use the fiducial markers and text recognition (OCR ?) for target object recognition. I can also resort to geolocation to explore more possibilities of making the user experience better. However, I am still working on the details and have to consider what is possible and what is not.

New Project Proposal
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Now that I have a better understanding of what I want (and need) to do, here’s the first draft of my new plan:

Using the 3D motion tracking data of the Microsoft Kinect, our goal is to create a virtual conductor application that uses gesture recognition algorithms in order to detect beats and control the tempo and volume of the music. Care must also be taken in order to minimize the latency of the system from gestural input to audio output for the system to be suitable for live performance. We will be testing various beat detection algorithms proposed by other papers in order to determine which is best in terms of latency. Moreover, in regards to the audio playback itself, we will generate the desired music from appropriate synthesizers, further allowing for the possibility of live musical performance as well as the possibility for custom instrument creation and music composition.

Advisors: Charlie Peck and Forrest Tobey

Project Topic
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I have chosen to do my senior project on data compression and my adviser for the project will be Xunfei Jiang.

Data compression is the concept of compressing data to fit into a smaller space.  Lossless compression is when when some form of data, like a video file, is compressed into less space with no loss in quality.  In lossy compression, a file can be compression even more, but at the expense of the quality of the data.

There are many different types of data one may want to compress.  For instance, we can compress the amount of space it takes to store text using a technique like run-length encoding.  In run-length encoding, we count the repetitions of characters, and store the number of times that character repeats itself.  If the sequence EEEEE appears in a string, we could instead store it as 5E so that it takes up less space.  This would be an example of lossless compression since the original string can still be perfectly reproduced despite requiring less storage space.

If one was compressing a video file, one might use bit rate compression.  In bit rate compression, the number of bits used to determine the colors the pixels can turn is reduced.  This will cause the video to require far less storage space, but at the cost of quality, since not as many color options are available.  Thus, this would be an example of lossy compression.

For my personal project, I will read papers published on various data compression techniques.  I will write my paper describing various compression techniques used in computer science.  I will also come up with my own method of compressing data, probably for video files.  I will write code to demonstrate this compression technique, and I will explain the method and how it works in my paper.

Project Topic
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Project Idea (Charlie is the Advisor):

Developing some sort of hardware/software combination that would allow for monitoring of washers and dryers on Earlham’s campus. I would then create an app of some sort so that students could go on to the app and be able to 1) get notifications when a machine is done 2) look to see which machines are available so that they do not have to make the trek to their closest washing machine only to find out that that the machines are all taken.  Right now, my idea for the hardware is just a machine that is plugged into the outlet at the same spot as the machine, kind of like an adaptor, and will broadcast a signal telling whether the machine is running or not.  The software will then simply read the broadcast to determine if a machine is running or not.

Topic Statement
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Deeksha Srinath

Senior Seminar Topic Statement

Advisor: Charlie Peck

 

My interest in how social media today is influencing our lives influenced my topic. I will be working to design a unified data model for Facebook and Twitter data. I will be doing this in order to be able to query a pool of data that spans multiple social media platforms. This is useful to the scientific process because people interact with different social media sites differently. In designing a unified data model, I will be able to analyse trends across platforms.

 

Once my data model is established and I have moved my data into it, I am interested in exploring the different scenarios around disordered eating on social media. In a day and age when everyone has access to everyone else’s pictures at the touch of a button, I am curious about what this is doing to body image and body positivity among young women in the US, particularly women of color. Eating disorders in the US are steadily climbing, with thousands of young women losing their lives to disordered eating. Body positivity is also on the rise, with more and more people speaking out about loving their body as is and embracing the beauty in difference.
 I am interested in exploring how to mine trends in the data across platforms. I do not have an ample psychological background to understand all the facets to this part of my project. I will be working with the Psychology department in order to better understand what to look for and how to query my data usefully once it is in a unified format.

Project Topic
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For my Senior Research, my topic will be a data mining project using data collected from Twitter. Twitter’s API offers 1% of a spatial bandwidth (in my case, the continental U.S.A.) for users to collect. This data has been collected for over 3 years, and represents well over one billion tweets. Of these, a significant percentage of tweets contains at least one hashtag, which is one kind of data I will be looking at. The other datatype I have an interest in is geo-tags, which are an optional GPS coordinate which users may choose to include. Using machine learning algorithms, I hope to identify regular hashtags, in order to classify different kinds of signals based on hashtag frequency. The purpose of this is to see if I can predict hashtag occurrence, or whether hashtags are too noisy to classify or group into reliable frequencies.

My goal is to then study the noise, and to give that noise a geo-spatial context in which to understand the events which contributed to that noise.

Here’s a simple example:
Given that the State of Indiana tests tornado sirens on the first Tuesday of each month, it is likely that hashtags similar to #tornado or #siren appear in greater numbers on the same days as tests. This is a regular signal which could be reduced to a variability of +- 6 hours. This signal can be ignored. However, should a tornado strike on a different day, the sirens will go off, and #tornado or #siren might appear on an irregular day. The siren creates a spatial event which only affects the region which hears it, which might distinguish it from the more regular signals.

At a larger scale, looking at the noisy hashtags might give insights into real time, less predictable events. This can help de-obfuscate growing stories or events in real time, allowing us to find the meaningful information which hides under layers of signals.

I will be doing this research with David Barbella (Dave). Dave and I will be working with resources hosted by NCSA, including the CyberGIS Supercomputer ROGER (an XSEDE resource, for others that are interested).

Revised Project Proposal
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. . ., but it may be revised again soon.

Our goal is to make a 3D rhythm game that would, among other possible applications, teach players the gestural motions of an orchestral conductor and act as a teacher for conducting music. The basic gameplay is that at certain points in the music, the game will show where the wand needs to be placed in 3D space and calculate score based on the distance between the intended position and the actual position of the wand. The gameplay would be comparable to the free game osu!, except no other inputs (e.g. mouse buttons) are required to play the game.
The project will consist of both software and hardware components, namely the game itself and a controller made specifically for said game, respectively. Currently, the game is planned to be built from scratch while including libraries such as OpenGL for a graphical interface and PortAudio for interacting with audio. Meanwhile, the required hardware may include just two infrared cameras/sensors as well as one infrared emitter on the tip of a wand for the cameras to detect. The reason for using infrared is to minimize any background interference that may occur when tracking a specific object as opposed to tracking by color.

Senior Project in HCI
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Big Picture

Topic: Software Interfaces and Human Behavior

Adviser: Charlie Peck

Description

While this requires some additional refinement, I’ve settled on the general topic and hope to incorporate some of my interests from the other topics along the way.

I will study how interfaces affect interactions between humans and computers. There is a rich history in this area, both in academia and in history/current events. Charlie recommended the Apple design guidelines, an outstanding trove of insights about why components of a software or OS interface should be designed in a particular way. From my own research I see that human-computer interaction (HCI) contributes to choices about everything from Facebook privacy to nuclear meltdowns.

In a potential paper, I would introduce the history of some high-profile HCI choices before zooming in on a few particular factors (to be determined) for more careful analysis and software design. This is a new area of study to me, so which factors I choose in particular will be determined upon completion of further research.

For the software project, I will approach this from the perspective of optimizing the response time for a given interaction. I intend to create a simple application, likely web-based to make scale feasible, with two simple interfaces and a series of prescribed interactions to be done in a given order. I have considered using a few of our local datasets: Iceland data, 911 emergency call data, transportation data, and a few public datasets on key topics. My intention with the software is to focus on the HCI components, so my preference is to use the data environment I am already familiar with as the backend for the project.

Since the major concern with my and most projects is getting directly to the CS, I intend to focus in particular on these subdomains:

  • Human-Computer Interaction: Trivial from the description.
  • Software Engineering: Trivial from the need to design and implement the application.
  • Algorithms: Choosing the correct algorithm to optimize the interaction; evaluate the time data
  • Relational Databases: The backend data will be stored in a PostgreSQL database

In addition, this project draws on insights from several topics in the social sciences – behavioral economics, psychology, business – but I consider these topics as launch sites rather than journeys or landing sites.

Updated Project Idea
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Intelligent Personal Assistant for Medicine

Research Supervisor: Dave Barbella

I want to build a software (potentially mobile application) that acts as an intelligent personal assistant for medical purpose. The inspiration comes from modern programs like Siri, but instead of being a general purpose, I want it to have a narrower focus (i.e. medicine). While I am still working on the details, I envision that you can talk to the app about various things such as diseases, medicines, hospitals and so on. I want the communication between the user and the app/program to be as human-like as possible. The app will also do other things like remind you to take your medicine, tell you if your physical health is matching with the symptoms of some disease, tell you when it’s time to go for a regular check-up and so on. I anticipate integrating other 3rd party web services to make some of these functionalities possible. I am also expecting to go through the works of CALO (Cognitive Assistant that Learns and Organizes) a lot among other resources.

There will be various aspects of computer science (or Artificial Intelligence specifically) that will be at the heart of this project such as:

  • Natural language processing
  • Question Analysis
  • Data collection/mashup
  • Reasoning/Pattern detection

While these are all new fields of study for me, I am excited to learn more about these and apply these while conducting my research/project.