diff --git a/images/MRS-thumb.png b/images/MRS-thumb.png new file mode 100644 index 0000000..c210206 Binary files /dev/null and b/images/MRS-thumb.png differ diff --git a/images/bargraph.png b/images/bargraph.png new file mode 100644 index 0000000..a842b83 Binary files /dev/null and b/images/bargraph.png differ diff --git a/images/diseaseovertime.png b/images/diseaseovertime.png new file mode 100644 index 0000000..074be3d Binary files /dev/null and b/images/diseaseovertime.png differ diff --git a/images/lego.png b/images/lego.png new file mode 100644 index 0000000..d82d21b Binary files /dev/null and b/images/lego.png differ diff --git a/images/mocostar_icon.png b/images/mocostar_icon.png deleted file mode 100755 index c480f61..0000000 Binary files a/images/mocostar_icon.png and /dev/null differ diff --git a/images/piecharts.png b/images/piecharts.png new file mode 100644 index 0000000..f8793f0 Binary files /dev/null and b/images/piecharts.png differ diff --git a/index.html b/index.html index 2b69d70..d494753 100755 --- a/index.html +++ b/index.html @@ -1,136 +1,138 @@ - - - - - CS Projects - - - - - - - - - - - - - - - - - - - - - - + + + + + CS Projects + + + + + + + + + + + + + + + + + + + + + + - - + + - - - +
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Department Projects

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Sharing Major CS Projects

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The Moravian CS Program site is where we show off all of the major computer science projects that our students have developed and collaborated on. Some of the projects are completed, while others are still being worked on and improved!

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Department Projects

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Student Experience

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All of our projects give our students experience with real problems and for some of the projects, the students get to work with businesses and clients to produce a usable product. This allows our students to get a more practical education than other computer science programs, making our students more competitive candidates for post-graduation jobs.

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Sharing Major CS Projects

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The Moravian CS Program site is where we show off all of the major computer science projects that our students have developed and collaborated on. Some of the projects are completed, while others are still being worked on and improved!

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Student Experience

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All of our projects give our students experience with real problems and for some of the projects, the students get to work with businesses and clients to produce a usable product. This allows our students to get a more practical education than other computer science programs, making our students more competitive candidates for post-graduation jobs.

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Projects on Github

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We use Github as we develop our programs because it makes it easier for groups and individuals to cooperate while it also gives us the option of making our projects open for the public to see.

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MorningStar

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MorningStar is a project intended to introduce CS students to health data visualization. It was originally assigned to a senior capstone class in the spring of 2015 where the students would use d3 and diabetic poke data to show poke ratios on the state and county level. The tool is now being developed so that users may upload their own data files and access web APIs such as the Census Bureau, Google, and the CDC.

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Developing Team Summer 2015:

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Megan Biernat, William Collins, Alec Gerhart, Anna Lamoureux, Steve MacDonald, Charles McDonald, Martin Nesbitt, Andrew Reed, Josh Russett, Michael Turnbach, John Vonelli

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Senior Capstone Contributors Spring 2015:

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Jason Boccuti, Steve Chakif, Lewis Cooper, Jon Diehl, Hansen Huang, Michael Vitone

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Projects on Github

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We use Github as we develop our programs because it makes it easier for groups and individuals to cooperate while it also gives us the option of making our projects open for the public to see.

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OpenMRS

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OpenMRS is an open source EMR used in over 23 countries throughout the world, including 400+ installations in Nigeria. The OpenMRS core supports a modular design, which allows our module to function as an optional add-on to an active instance of OpenMRS. The module supports parameterized queries to provide anonymized data. Users can obtain data from one or more instances of OpenMRS to aggregate data to answer questions about population health.

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Developing Team Summer 2014:

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Megan Biernat, Jason Boccuti, Steve Chakif, Lewis Cooper, Alec Gerhart, Charlie McDonald, Vincent Pillinger

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Senior Capstone Contributors Spring 2014:

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Myles Barros, David Cariello, Justin Dilts, Michael Eckhart, Nick Forouraghi, Karli Gnehm, Rachel Johnson, Jesse Perry, Alli Samson, Alek Szilagy

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MorningStar

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MorningStar is a project intended to introduce CS students to health data visualization. It was originally assigned to a senior capstone class in the spring of 2015 where the students would use d3 and diabetic poke data to show poke ratios on the state and county level. The tool is now being developed so that users may upload their own data files and access web APIs such as the Census Bureau, Google, and the CDC.

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Moravian College Summer Team 2015:

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Megan Biernat, William Collins, Alec Gerhart, Anna Lamoureux, Steve MacDonald, Charles McDonald, Martin Nesbitt, Andrew Reed, Josh Russett, Michael Turnbach, John Vonelli

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Senior Capstone Contributors Spring 2015:

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Jason Boccuti, Steve Chakif, Lewis Cooper, Jon Diehl, Hansen Huang, Michael Vitone

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Title of Project

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A brief description of the project goes here. In porta velit quis mauris luctus, eget luctus neque gravida. Nullam pellentesque pretium rhoncus. Nulla pretium scelerisque sem nec tincidunt. Praesent cursus, nulla vel ultricies venenatis, urna ligula pharetra metus, et mattis elit nunc sed lacus. Sed at elit fringilla, pellentesque eros vel, luctus diam. Donec egestas nisi semper odio dignissim egestas. Etiam vitae lacus a nibh mattis sodales eu sit amet ex. Ut suscipit auctor lacus nec finibus. Vestibulum venenatis imperdiet facilisis. Vivamus in condimentum turpis, in euismod mauris. Nulla facilisi. Ut at nulla aliquam, sodales dui sit amet, tristique lacus.

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Developing Team:

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Title of Project

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A brief description of the project goes here. In porta velit quis mauris luctus, eget luctus neque gravida. Nullam pellentesque pretium rhoncus. Nulla pretium scelerisque sem nec tincidunt. Praesent cursus, nulla vel ultricies venenatis, urna ligula pharetra metus, et mattis elit nunc sed lacus. Sed at elit fringilla, pellentesque eros vel, luctus diam. Donec egestas nisi semper odio dignissim egestas. Etiam vitae lacus a nibh mattis sodales eu sit amet ex. Ut suscipit auctor lacus nec finibus. Vestibulum venenatis imperdiet facilisis. Vivamus in condimentum turpis, in euismod mauris. Nulla facilisi. Ut at nulla aliquam, sodales dui sit amet, tristique lacus.

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Developing Team:

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MorningStar

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If you'd like to check out the blog that the group has written about the progress of the project, you can click here, or for the Github repository for the project is located here.

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Map Description

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We want to be able to show easy-to-understand maps so that one can effectively explore multiple data sets on a large scale and create hypotheses about possible links between elements before then taking it to a more complex data analysis tool. Even though the project started out as a data visualization of HA1c data, it has morphed into a much more generalized tool that can be used to visualized any data sats. At the moment, the data sets being using are HA1c poke ratio and migrant housing, but any number of data sets could be used and compared in the future. See the ReadMe.md of the repository for more details.

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Map Description

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We want to be able to show easy-to-understand maps so that one can effectively explore multiple data sets on a large scale and create hypotheses about possible links between elements before then taking it to a more complex data analysis tool. Even though the project started out as a data visualization of HA1c data, it has morphed into a much more generalized tool that can be used to visualized any data sats. At the moment, the data sets being using are HA1c poke ratio and migrant housing, but any number of data sets could be used and compared in the future. See the ReadMe.md of the repository for more details.

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The Hemoglobin A1c (HA1c) test is a blood test measuring the average blood sugar level over the past 2 to 3 months, and is used to see how well a person's diabetes is being controlled. Poke ratio is a ratio represented by the average number of tests done per patient over the number of tests, with an ideal number of 4 tests per year per patient. The Medicare billing data used in this project is collected in 2013. The maps below show poke ratio (left) and migrant housing (right) by Blue-White Scale, while areas without any data available are in grey. You may change the gradient level and colors for more details.

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The Hemoglobin A1c (HA1c) test is a blood test measuring the average blood sugar level over the past 2 to 3 months, and is used to see how well a person's diabetes is being controlled. Poke ratio is a ratio represented by the average number of tests done per patient over the number of tests, with an ideal number of 4 tests per year per patient. The Medicare billing data used in this project is collected in 2013. The maps below show poke ratio (left) and migrant housing (right) by Blue-White Scale, while areas without any data available are in grey. You may change the gradient level and colors for more details.

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Play around with the data! To navigate the map simply click on any state to enter the state and view county data. To return to the Country Map, click on the state again or click on Reload Map Button. You can pan by dragging the map around and zoom by scrolling. See if you can find any patterns between the two.

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* Note - The zoom function is not compatible with Mozilla Firefox.

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Play around with the data! To navigate the map simply click on any state to enter the state and view county data. To return to the Country Map, click on the state again or click on Reload Map Button. You can pan by dragging the map around and zoom by scrolling. See if you can find any patterns between the two.

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Map Description

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    OpenMRS

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    Example: Trends Over Time

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    A hospital administrator wants to see the trends in disease burden during an 8-month period. For the nine diseases of interest, she queries her hospital’s OpenMRS instance for the disease burden for each month. Graphing the data, she discovers that the cases of influenza have decreased while the number of cases of viral meningitis have risen.

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    Example: Regional Data

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    A government official wants to know how cities are coping with various diseases. His sends a query to OpenMRS instances at seven different cities with parameters that specify the diseases of interest. By tallying the results, the official is able to visually compare the disease burden between the cities and see that Dar.es.Salaam has the largest number of cases for all three diseases.

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