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Mathematics, Computer Science and Statistics.

Article Excerpt
Co-Chair: Constance Bland, Mississippi Valley State University

Co-Chair: Jason Hale, University of Mississippi

Vice-chair: Joseph Kolibal, University of Southern Mississippi

THURSDAY MORNING

Dogwood

O9.01

9:00 IMPLEMENTING VARIOUS CHECKLIST IN ELECTRONIC FORM USING XML AND PYTHON PROGRAMMING LANGUAGES

Marcus Winn

Mississippi Valley State University

The Electronic Logbook (E-Log) is an information storage and retrieval system that records daily activities of the particle detectors located in the DO Experimental Hall. The detector records collision of protons and antiprotons at Fermi National Accelerated Laboratory. E-Log was developed using XML, HTML and the Python programming languages. The problem with E-Log was that data had to be retrieved from an external database manually and keyed into a form for the E-Log database. My project was to create scripts that would automatically retrieve data from the external database and web pages and insert the data into the E-Log database. This process eliminated the tedious task of the crewmembers which allowed them to perform their job at a more efficient rate.

O9.02

9:30 IMPLEMENTING E-MAIL ALERTS TO THE GCC TEMPERATURE MONITORING PROGRAM

DeMarcus Thomas

Mississippi Valley State University

This document outlines efforts to determine an efficient means of monitoring a high density computing center remotely and efficiently through the use of a web browser. To accomplish this, a web-based temperature monitoring program was created, and implemented at Fermi National Accelerator Laboratory's Grid Computing Center (GCC). The Python program created was designed to read data from thermocouple heat sensors and to superimpose their values onto a floormap of GCC. The software created a virtual floormap which placed the temperature readings in the proper locations relative to the sensors in the actual room. Additions to the program included the creation of a temperature threshold. When the temperature threshold was exceeded, (temperature >95.0 oF), e-mail is sent to the appropriate personnel with a mailing list.

O9.03

10:00 EMWASTE DATABASE TRANSFER AND FUNCTIONALITY ASSESSMENT

Alvin McClerkin

Mississippi Valley State Univeristy

I conducted an assessment of the data transfer from the now inactive Waste Inventory Tracking System (WITS) to the active, operable eM Waste[R] System. The assessment involved two separate verification phases. The first assessment verification phase entailed a 100% review of the WITS inventory utilized for data port to eM Waste[R] This involved a one to one comparison of containers on the WITS inventory list against the operable eM Waste[R] production database. The second assessment verification phase involved random selection of containers within the eM Waste[R] inventory system for field comparison that included storage location, container size, type and weight. Waste containers were also randomly selected at field locations and cross-referenced against the eM Waste[R] inventory database. In addition, a small subset of the containers selected in the second assessment verification were also cross-referenced against the Facility Acceptance Testing-Container Analysis Tool (FATCAT) system to ensure that critical radiological parameters were accurately and adequately tracked to ensure waste management storage facility categorization levels were maintained.

O9.04

10:30 A DEM CONVERSION TOOL

Sufian Ahmad (1), Pamela Lawhead (1)

(1) University of Mississippi, (2) Institude of Advanced Eduacation for Geospacial Sciences

This is a program that converts Digital Elevation Models[DEM] to a 3D polygon file of type PLY. The research done opens possibilities towards creating Binary Spacial Partitioning[BSP] file and using files from Mississippi Auto Resources Information System[MARIS] of type E00.

O9.05

11:00 RESEARCH ON HYBRID ARIMA AND SUPPORT VECTOR MACHINE MODEL IN FORECASTING ENVIRONMENTAL SUSTAINABILITY

Benjamin Harvey, Joshua Fu

Mississippi Valley State University

Due to the complexity of environmental sustainability and the historical forecast data and the randomness of a lot of uncertain influence factors, the observed historical data showed linear and nonlinear characteristics. Currently, the autoregressive integrated moving average (ARIMA) is one of the popular linear models in time series forecasting, and the SVM, which is closely related to the neutral networks model, is the model recent researchers have successfully used in solving nonlinear regression and time series problems. This research presents a hybrid methodology that combines both ARIMA and SVM model to take advantage of the unique strength of ARIMA and SVM models in linear and nonlinear modeling to help forecast environmental sustainability....

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