Student Research Showcased During 3rd Annual Lyle Research Day


Lyle Research Days 2015

More than 50 graduate and undergraduate students at SMU’s Lyle School of Engineering presented research projects during the third annual Lyle Research Day. This year’s competition included two components, Departmental and Social Media Awards. Departmental Awards were chosen by the Lyle School of Engineering’s Executive Board which, after reviewing the submissions, chose the top competitor from each of Lyle’s five academic departments, Civil and Environmental Engineering; Computer Science and Engineering; Electrical Engineering; Engineering Management, Information, and Systems; and Mechanical Engineering. The Social Media Awards were decided by peers who attended the oral presentations and poster sessions, before casting their votes for their favorite presentation on Twitter and Facebook.

“We are excited to add the new departmental awards voted by members of Lyle School’s Executive Board, said Senior Associate Dean Volkan Otugen. “The board members are always eager to spend time with our students and learn more about the exciting research performed in the Lyle School. The students gain valuable experience explaining their projects and honing their presentation skills.”

Civil and Environmental Engineering Poster Winner:

Mahdi Heidarizad (#GOMghydrOxide) – Advisor: Sevinc Sengor

Abstract:
Human health and aquatic life are challenged by various contaminants in drinking water resources. Removing these harmful contaminants requires novel techniques that are highly efficient and practical to be applied for water treatment. Adsorption is one of the easiest and cheapest removal processes for contaminants. Grapheneis a promising material to be used for this purpose, as it has extraordinary characteristics such as large surface area. Graphene Oxide (GO), oxidized derivative of graphene, contains some functional groups which cause it to be easily dispersed in water. However, it’s separation from water is an issue after treatment. Magnesium oxide (MgO) nanoparticles have a high destructive adsorption potential in degradation of various contaminants. Thus, it is a potential hybrid material for GO to overcome this problem. This study presents the novel GO/Mg(hydr)Oxide Nano-Composite material and its investigation for the removal of a model organic contaminant, methylene blue dye in aquatic solutions.

Computer Science and Engineering Poster Winner:

Adel Alharbi (#DemographicGroupClassification) – Advisor: Mitchell Thornton

Abstract:
Interacting with smart devices is a common experience and is becoming an integral part of daily life for many people. Modern smart devices are equipped with a large variety of environmental and user input sensors. We hypothesize that a fusion of smart device sensor data can provide biometric data that allows for classification of user demographics such as age, gender, and native language. A smart device is instrumented with sensor data collection software and with user demographic classification software. An experiment is devised where data is collected for a sample group of users. The data is analyzed, and two classification algorithms are implemented based on the fusion of the different sensors. The classification methods are based upon decision tree and principle component analysis. The results of the experiment indicate that high accuracy is achieved for user demographic classification. Finally, we further discuss the future work of the study’s approach.

Electrical Engineering Poster Winner:

Mehdi Nouri (#OrbitalComm) – Advisor: Duncan MacFarlane

Abstract:
The next generation of telecommunication technologies (5G) is intended to support the anticipated increase in data traffic demand. This presentation reports on the use of engineered laser beams with orthogonal basis sets to increase the capacity of current optical networks. Multiple twisted beams of light exhibiting orbital angular momentum (OAM) twist at different rates while propagating along the same axis with very little cross talk because of their orthogonality. Taking advantage of higher order modes beyond conventional zero-order Gaussian beams allows for transmission of multiple channels through the existing global single-mode optical fiber network using the same frequency or wavelength. In addition to optical fiber based communications systems, this work may also be applied to free space communication links such as microwave backhaul and may be a step toward fully software-defined networks (SDN).

Engineering, Management, Information, and Systems Poster Winner:

Ted Munger (#TaleOfTwoStates) – Advisor: Dick Barr

Abstract:
Recent news reports said that Texas was growing economically but California was not. Based on GSP, both were growing but Texas was growing faster on a per-capita basis. To understand what drives economic growth for each state, 50 years of annual state-level data was collected on 486 variables to build a regression model for each state and compare the dominant factors. To identify the dominant factors, the traditional statistical approach is Principal Component Analysis applied to stationary transformations of the data. This research uses a new alternative approach, k-Variable Adjudication Methodology (kVAM), a mixed-integer, nonlinear programming technique that optimizes classic statistical goodness-of-fit measures. The results revealed new insights into the underpinnings of economic growth (both short-term and long-term) in each state and provides valuable lessons for policy makers.

Mechanical Engineering Poster Winner:

Yongqiang Li (#ballisticimpact) – Advisor: Xin-Lin Gao

Abstract:
The use of combat helmets has greatly reduced penetrating injuries and saved lives of many soldiers. However, behind helmet blunt trauma (BHBT) has emerged as a serious injury type experienced by soldiers in battlefields. BHBT results from non-penetrating ballistic impacts and is often associated with helmet back face deformation (BFD). In the current study, a finite element-based computational model is developed for simulating the ballistic performance of the Advanced Combat Helmet (ACH), which is validated against the experimental data obtained at the Army Research Laboratory. Both the maximum value and time history of the BFD are considered. The simulation results show that the maximum BFD, the time history of the BFD, and the shape and size of the effective area of the helmet shell agree fairly well with the experimental findings.

Facebook Winner:

Monica John (#ObscureNetwork) – Advisor: Daniel Engels

Abstract:
All the devices in Internet of things are connected using the Ad-hoc network. So, it important to secure the communication between these devices. We plan to take network security to the next level by evaluating the performance of a newly researched type of network “Black Network”, wherein the identity of the sender and the receiver is hidden. We would be creating a mechanism where we can investigate the traffic attacks between the source and destination in an ad hoc network. Most importantly, the attacker would be able to see the communication going on but still wouldn't be able to identify the sender as well as the receiver. We plan to use a few techniques to evaluate the performance of such network. We would be simulating a network to study and analyze its performance.

Twitter Winner:

Adel Alharbi (#DemographicGroupClassification) – Advisor: Mitchell Thornton

Abstract:
Interacting with smart devices is a common experience and is becoming an integral part of daily life for many people. Modern smart devices are equipped with a large variety of environmental and user input sensors. We hypothesize that a fusion of smart device sensor data can provide biometric data that allows for classification of user demographics such as age, gender, and native language. A smart device is instrumented with sensor data collection software and with user demographic classification software. An experiment is devised where data is collected for a sample group of users. The data is analyzed, and two classification algorithms are implemented based on the fusion of the different sensors. The classification methods are based upon decision tree and principle component analysis. The results of the experiment indicate that high accuracy is achieved for user demographic classification. Finally, we further discuss the future work of the study’s approach.

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SMU is a nationally ranked private university in Dallas founded 100 years ago. Today, SMU enrolls approximately 11,000 students who benefit from the academic opportunities and international reach of seven degree-granting schools.

SMU’s Bobby Lyle School of Engineering, founded in 1925, is one of the oldest engineering schools in the Southwest. The school offers eight undergraduate and 29 graduate programs, including master’s and doctoral degrees.