Location: Bloomington Indiana, Indiana University (Summer 2011)

Mentor(s): Thilina Gunarathne, Stephen Wu, and Bingjing Zhang

Analyzing Map Reduce frameworks Hadoop and Twister

Key Terms: MapReduce, Hadoop, Twister,


The primary focus of this research project was to analyze the attributes of MapReduce frameworks for data intensive

computing and to compare two different MapReduce frameworks, Hadoop and Twister. MapReduce is a data processing framework that allows developers to write applications that can process large sets of data in a timely manner with the use of distributed computing resources. One of its main features is the ability to partition a large computation in to a set of discrete tasks to enable of parallel processing of the computation. Google, the most popular search Engine on the internet, uses MapReduce to simplify data processing on its large clusters. We analyze the performance of Hadoop and Twister using the Word Count application and compare the scalability and efficiency of the two frameworks for this particular application.


Location: Elizabeth City North Carolina, Elizabeth City Sate University (academic school year 2010-2011)

Mentor: Dr. Malcolm LeCompte

Validation of the 2003 Antartic Groundling Line through the use of ENVI


Key Terms: ENVI, GloVis, ground control points, grounding line, hinge point, Landsat 7 ETM+, LIMA, PIG


Dynamics and mass balance of an ice sheet can be derived from an accurate measurement of its area. To measure the area of a continental ice sheet, the grounding line must first be accurately determined. The grounding line is the boundary between the ‘grounded’ ice resting on land and any associated floating ice comprising a retaining ice shelf.

During a project entitled Antarctic Surface Accumulation and Ice Discharge or ASAID, Dr. Robert Bindschadler, lead an international team of glaciologists and computer scientists, including ECSU students, in an effort to obtain a more accurate measure of the area of the Antarctic ice sheet and determine its mass balance. That is, whether the amount of ice is growing or diminishing over long time intervals. Bindschadler’s team determined the grounding line using methods of photoclinometry with LANDSAT Enhanced Thematic Mapper (ETM) image brightness and surface elevation data from the Geoscience Laser Altimeter System (GLAS) aboard NASA’s Ice, Land and Cloud Elevation Satellite (ICESat). The ASAID grounding line (GL) was established using LANDSAT 7 and GLAS data obtained in 2003. However its accuracy and utility had not been tested.

With the current ASAID 2003 Grounding Line (GL), the CERSER GL Validation Team was tasked by Dr. Bindschadler with determining its accuracy in two coastal regions and whether changes have occurred over long time intervals. The team over-laid the 2003 GL on LANDSAT Seven ETM imagery temporally proximate to 2003. This modified image was then compared to decades older LANDSAT 4 & 5 Thematic Mapper (TM) imagery. GL validation and change determination were planned for two geographic areas known to exhibit rapid changes potentially due to climate warming: Pine Island Glacier (PIG) and Larsen Ice Shelf. However, due to time constraints, the team only examined a limited portion of the PIG. The GL was tested along a portion of the Antarctic coast near the PIG. To accomplish the validation, LANDSAT 7 images from 2003 used in creating the GL, were obtained from the USGS archive (lima.usgs.gov). Other LANDSAT images were obtained from the USGS GLOVIS on-line archive (glovis.usgs.gov). The oldest possible, cloud-free LANDSAT 4 and 5 TM images were obtained for the regions of interest. To facilitate data manipulation and image comparisons, the extremely large GL vector file, obtained from Dr. Bindschadler. was truncated to include only the geographic regions of interest. Truncation and image comparisons were accomplished using ITT Visualization System’s ENVI image processing software. Any departure from perfect geographic pixel registration was corrected by using the 2003 image as a reference and then warping the older image to conform to the common fixed control points visible on both images. The grounding line overlying the 2003 image was then examined and compared to the older image. The geographic coordinates and extent of any departures from coincidence were recorded and reported.

A possible deviation in the GL was found while comparing a 2001 LANDSAT 7 image to a 1986 LANDSAT 5 image, near a small glacier feeding into Pine Island Bay. Comparison with a 2003 image of the same area revealed no GL inaccuracy; however a small ice shelf appeared to have progressively diminished over time until it disappeared in 2003.


Location: Bloomington Indiana , Indiana University (Summer 2010)

Mentors: Jong Youl Choi, Ruan Yang, and Seung-Hee Bae

Data Point Visualization and Clustering Analysis

Site: http://www.stem.indiana.edu/


Key Terms: BH-Tree, K means, Hiearchical Clustering, XNA, Plotviz, C # (Sharp)


The primary purpose of this research project was to create a research tool for 3D data point visualization and clustering analysis, which is one of the most popular data analysis methods in bioinformatics and cheminformatics. For this purpose, we have implemented the Barnes-Hut Tree algorithm in C# to visualize cluster structures of 3-dimenisional data and added the function to a visualization tool, called PlotViz, which is written in C# and Microsoft XNA graphic libraries, developed by the CGL research lab in Indiana University. We have also performed clustering analysis of real research data used in IU bio- and chem-informatics research groups. Among many clustering algorithms available, in our analysis, we have applied two popular clustering algorithms, k-means and hierarchical clustering, by using R, which is a standard statistical analysis tool, and compared the qualities by measuring “withinness” which is the sum of Euclidean distances between cluster centers and points for each cluster group. The results are also compared by visualizing the data points in 3D by using PlotViz.


Location: Elizabeth City State University , Elizabeth City State University (academic school year 2009-2010)

Mentor: Dr Eric Akers

Analyzing CISIM data

Members: Joyce Bevins, MyAsia Reid, Justin Deloatch

Site: http://crism.jhuapl.edu/ or http://nia.ecsu.edu/ur/0910/teams/crism/index.html


Key Terms: Mineral (Reflectance) spectroscopy Oxidized iron minerals Mafic mineralogy Hydroxlated sillicates Bound water Kitoto


Creating a Program in Mat Lab to Classify CRISM Data For years many people have had questions concerning Mars atmosphere climate, and surface. If water had ever existed on Mars and if so where and when did the water occur? Is Mars suitable for life? Can there be human exploration and colonization on Mars? NASA uses it’s high tech seeking instrument known as CRISM (The Compact Reconnaissance Imaging Spectrometer for Mars) to trace the past and present water on Martian Mars to try and answer these questions that have yet to be fully answered. The CRISM instrument is sent to Mars to take images of Mars surface in search for minerals that may indicate that water is present. The 2009-2010 undergrad Research team primary focus was to create a program using map lab that will classify CRISM data in a shorter time frame than what it will take to classify by hand. The CRISM research consisted of manually classifying images from Mars and placing them into excel’s data base, downloading images and storing them into Kitoto’s server so that the program can read and return results of the overall images and mineral images. These images can be classified as excellent, fair, poor, and absent. The classification of each image will show whether there is a lot, little, or no water in each kind of mineral. The five minerals are oxidized iron minerals, mafic mineralogy, hydroxylated silicates, bound water and CO2 water. The images that show the most signs of water in certain areas on Martian will be examined more closely. Currently, the CRISM team working is on creating this program in Mat Lab.


Location: Indiana University , Bloomington Indiana (summer 2009)

Mentor: Marlon Peirce

Group membe(s): Jean Bevins


Key Words: XML, Apahce, MySQL

ABSTRACT: Creating Social Networking Applications for PolarGrid by applying Facebook Application Programming Interface, using web technologies such as MySQL, Apahce, and XML and Filtering PolarGrid Photo Shots of Ice Sheet Data from Greenland The Center for the Remote Sensing of Ice Sheets (CReSIS) has been compiling Greenland ice sheet thickness data since 1993 from yearly expeditions to Antarctica and Greenland. The PolarGrid project is tasked with creating a method whereby the data can be visualized and shared through the research and education communities. The primary concentration of this research project is to create a social networking application for the usage of sharing the processed data sets for PolarGrid. To accomplish this task the Facebook Application Programming Interface (API) will be utilized. The Facebook API consist of online communities, which form an ample number of ways to interact, visualize, share, and view data while also allowing users to create profiles.


Location: Elizabeth City State University, Elizabeth City North Carolina (Spring 2009)

Mentor: Jeff Woods

Group member(s): Robyn Evans, Micheal Auston, Tevins Baskervile, Jean Bevins


Key Words: Web 2.0, Drupal, Joomla, WordPress, MediaWiki, Content Management System, CReSIS, Polar Research

ABSTRACT: Evaluation and Implementation of Web 2.0 Technologies in Support of CReSIS Polar and Cyberinfrastructure Research Projects at Elizabeth City State University.The primary focus of this research project was to study the implementation of Web 2.0 technologies to support scientific research and provide educational resources. Web 2.0 technologies include social networking, text and data mining, knowledge incorporation environments, tagging, visualization, and mashups. These technologies are widely used in popular sites such as MySpace, Facebook, and iGoogle. Various research and government organizations such as NASA, Harvard’s Science and Engineering department, and the Technology Student Association have also implemented these technologies. The 2008-2009 Multimedia Team focused on specific server software packages to execute Content Management Systems (CMS) for future inclusion in several ongoing projects under the Center of Excellence in Remote Sensing and Education (CERSER) umbrella. Four open source software packages were evaluated, installed, and documented as models for future installations. These software packages were Joomla, WordPress, Drupal, and MediaWiki.