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College Hosts Innovation Day

Wednesday, April 17, 2019


Innovation Day logoInnovation Day brought together students, faculty, alumni and industry representatives to showcase and celebrate the transformative research being performed in UTA’s engineering laboratories.

View project abstract and participants booklet

Nearly 400 graduate and undergraduate students presented 117 projects throughout the day, including 26 undergraduate projects, more than 60 senior design projects, and 24 projects by graduate students.

"Innovation Day was an excellent showing by our students. It's amazing to see the creativity and innovation, as well as the top-quality research, that our students are capable of. I was pleased that we had such great representation from our senior design groups as well, because their prototypes really showed that we're preparing students well for their careers after UTA,” said David Wetz, a professor in the Electrical Engineering Department and the College's Director of Strategic Initiatives.

"I want to be sure to recognize the support of our many sponsors, both monetarily and in their presence at the event. Their involvement was very much appreciated, and I hope that our future interactions with them will strengthen our ties to industry, open new avenues for our students and lead to continued growth of the event.”

Judges – industry representatives, faculty, graduate students and alumni – rated each poster and project throughout the day and chose prize winners in each category, plus L3/Link Innovation Awards for one undergraduate and one graduate project, chosen by L3 employees in attendance. Texas Instruments also provided prizes for each of the 1st place winners. 

The awards were:

Undergraduate

First Place:

Tyche Doe and Rachael Watson
"Wireless Soil Moisture Testing"
Abstract

Second Place:

James Brady, Joe Cloud and Michail Theofanidis* 
"Deep Reinforcement Learning for Robot Grasping”
Abstract 

Third Place:

Garrison Frost and Bijan Niaken
"Development of Cu-VACNT Composites for Nanoelectronic Applications"
Abstract

Honorable Mention:

Lorenzo Alba, Collin Chapin, Amelia Jackson, Regan Kubicek, Michaela Stallings and Jeremy Trollinger
"Wheelchair Attachable Assistive Robotic Arm”
Abstract

Honorable Mention:

Zhen Li and Nicole Ndegwa
"An Experimental Study of Evaluating the Effect of the Litter Layer on Evaporation”
Abstract 

* – Graduate student

Graduate

First Place:

HM Ashfiqul Hamid
"A Triboelectric MEMS Vibrational Nano-energy Harvesters for Nano-sensor Applications”
Abstract

Second Place:

Edidiong Inyang and Aneetta Kuriakose
"A Novel Theragnostic Approach to Repair and Restore Disrupted Brain Endothelium”
Abstract

Third Place:

Andrew McColloch
"Examination of Nuclear Morphology in Mesenchymal Stem Cells During Adipogenic Differentiation Using a Combined Experimental and Computational Modeling Approach”
Abstract

Honorable Mention:

Priyam Banerjee
"Implementation and Analysis of Caching Mechanism on Cloud Cluster for LHC ATLAS Experiment”
Abstract

Honorable Mention:

Caleb Liebman and Thao-Mi Vu
"Potential Applications for Non-Invasive Electric Field in Diabetic Therapies"
Abstract

Senior Design

First Place:

Cameron Howard, Abdul Mannan, Ivy Moore, Gaganeet Singh and William Truong
"iSpy"
Abstract

Second Place:

Joseph Herring, Jacob Lamotte-Dawaghreh, Logan Pechal, Tim Pugliese, Matthew Smith and Garrett Tolar
"Electric In-Wheel Drive System"
Abstract

Third Place:

Antonio Araujo, Chad Goodlow, Brandon Griffin, Jason Gulledge, Matthew McCormick and Mathew Niestroy
"Wheelchair Dynamometer
Abstract

Honorable Mention:

Jonathan Aguilar, Henry Bang and Khoa Pham
"Eye Gaze
Abstract

Honorable Mention:

Pavanaj Biyani, Robert Brady, Brandon Chase, Kartik Gupta and Nicholas Reimherr
"UTA-SC"
Abstract

L3/Link Innnovation Awards:

Saleh Abusalah, Bosah Agolua, Zeshan Ahmed, Noor Diya, Kaushik Iyer, Traevis Joshlin and Matthew Montoro
"3D-Printed Aircraft"
Abstract

Jonathan Aguilar, Henry Bang and Khoa Pham
"Eye Gaze"
Abstract

Andrew Miller
"Virtual Reality Tasks for Cognitive Assessment"
Abstract

Dean’s Freshman Challenge

Best Idea:

  1. An Interconnected Approach
  2. Smartwatch
  3. Plastic Roads

Best Representation of UTA:

  1. Plastic Roads
  2. Smartwatch
  3. An Interconnected Approach

Best Mentor Organization:

  1. Smartwatch
  2. Plastic Roads

Abstracts – Undergraduate

Wireless Soil Moisture Testing

Tyche Doe and Rachael Watson
Advisor: Saibun Tjuatja
Electrical Engineering Department 

Soils are the foundation of terrestrial ecosystems which provide services that are essential for humanity. Our knowledge of subsurface dynamic changes in soils is limited due to the lack of observation capabilities for measurement of key soil variables over large areas and long periods of time. This project seeks to establish the feasibility of a novel, subsurface soil variables sensing system that can be scaled to provide large measurement area and cost-effective long term measurements. The proposed system consists of in-situ backscatter soil sensors, a polarimetric radar/remote sensor interrogator, and a soil parameters estimation algorithm. The backscatter soil sensor is modeled using HFSS. The sensor is modeled with an excitation between two rods which had a set diameter of 3mm. The probe was modeled as inserted into sandy loam soil. The length of both rods were equal and varied together in increments of 0.175m The spacing between the rods was also varied in increments of 1.75cm. Each probe variation was modeled with four different moisture levels of medium to begin determining a pattern between soil moisture level and S11 backscattering. The sensor is also modeled having the two rods shorted together, with all other variables the same. These 200 preliminary simulations are to determine closer approximation of optimum sensing polarization, frequency range, backscatter soil sensor design and configuration, data processing and soil parameter retrieval algorithms.

Deep Reinforcement Learning for Robot Grasping

James Brady, Joe Cloud and Michail Theofanidis
Advisor: Fillia Makedon
Computer Science and Engineering Department

Our work describes a two-phase system for motor skill learning. As an input, the system receives data from a demonstration of the desired motor skill. In the first phase, a series of actions are performed based on a pair of pre-trained forward and inverse models. In the second phase, the system learns an initial state-action policy by using the Dynamic Movement Primitive framework. This system is tested on the Rethink Robotics Sawyer manipulator.

Development of Cu-VACNT Composites for Nanoelectronic Applications

Garrison Frost and Bijan Niakan
Advisor: Leila Ladani
Mechanical and Aerospace Engineering Department

Copper is the most common material for interconnects in microelectronics. However, it is losing its advantage for nanoscale applications due to electromigration and high resistance. New 2D materials such as graphene, CNTs, and TMD materials are being developed for the next generation of interconnects. Fabrication of these materials often requires high temperatures that exceed the limitations of copper in microelectronic processing. When these 2D materials are used in conjunction with copper, it is desirable to delay copper deposition to the later stages of fabrication to avoid exposing copper to high temperatures. It is proposed that a seed layer be deposited before deposition/growth of CNTs/graphene or other TMD materials, so that later deposition of copper via electroplating is feasible. This seed layer must be able to withstand high temperatures, must not migrate or diffuse into silicon or barrier layers, and must also be a suitable seed layer for copper electroplating. This research focuses on the development of a seed layer and method of electrodeposition for construction of this composite. SEM and EDX are then performed on the samples to verify satisfactory copper coating. The effect of the deposited copper layer’s interactions with the CNTs at high temperatures is also analyzed by utilizing simulations. By using COMSOL, wettability contact angles between a melted copper sheet and the interspatial walls of CNTs are observed at various temperatures.

Wheelchair Attachable Assistive Robotic Arm

Lorenzo Alba, Collin Chapin, Amelia Jackson, Regan Kubicek, Michaela Stallings, Jeremy Trollinger
Advisor: Panayiotis Shiakolas
Mechanical and Aerospace Engineering Department

The ARMS (Assistive Robotic Machines) team has been tasked with creating an assistive robotic arm to append to an electric wheelchair. The arm should be capable of reaching a distance of 2 feet and returning a water bottle to the operator. The cost goal for our prototype is $1,500. Current robotic arms on the commercial market with this capability cost around $35,000 and are not covered by insurance. Through the completion of our project, ARMS hopes to return mobility to those who could not previously afford it.

An Experimental Study of Evaluating the Effect of the Litter Layer on Evaporation 

Caleb Liebman and Thao-Mi Vu
Advisor: Kathleen Smits
Civil Engineering Department

The litter layer plays a significant role in conserving soil water and reducing diurnal amplitude of soil temperature. The characterization of the litter layer in numerical models and its effects on the soil evaporation have been a challenge due to lack of experimental data. In this study, a series of evaporation experiments with different types of litter layers and varying litter layer thickness will be conducted. The effects of the litter layer on evaporation will be analyzed based on measurements of the evaporation rate, soil water content and soil temperature underneath the litter layer of different scenarios.

Abstracts – Graduate

A Triboelectric MEMS Vibrational Nano-energy Harvester for Nano-sensor Applications

HM Ashfiqul Hamid
Advisor: Zeynep Çelik-Butler
Electrical Engineering Department

The power requirements for portable and wireless sensors are continuously decreasing due to the increasing importance of the Internet of Things (IoT) and technological advancements, which continuously push for more power-efficient devices. As a result, powering these devices through green energy from environmental vibrations using nano-scale energy harvesters is becoming much more viable. This work presents a novel design, optimization and fabrication technique of a triboelectric nano-energy harvester to harvest energy from high frequency ambient vibration sources. The integrated design, modeling and dynamic optimization of the triboelectric energy harvester enables it to be fabricated and packaged as a Micro Electro Mechanical System (MEMS) in a traditional cleanroom environment. Simulation shows that at 800 Hz vibration frequency with an acceleration magnitude of 9.8 ms-2, which is the primary vibration frequency coming out of an aircraft skin, the triboelectric nano-energy harvester can generate an average power of 196.91 nW with surface and volume power densities of 13.1 mWm-2 and 1544.4 Wm-3, respectively. The dynamic optimization on the geometric structure of the device reduced the device dimensions and mass while increasing the output power and power density dramatically. Due to this small size, low mass and comparatively high power density output from the triboelectric nano-energy harvester, it can have a significant impact in expanding the applications of the nano-sensors in wireless sensor nodes, in automobile industry, in space exploration programs, in micro-robotics and in prosthetics.

A Novel Theragnostic Approach to Repair and Restore Disrupted Brain Endothelium

Edidiong Inyang and Aneetta Kuriakose
Advisor: Michael Cho
Bioengineering Department

Traumatic brain injury is a serious concern among military personnel. Although the mechanisms responsible for the disruption of the brain endothelium (BE) are not well understood, the development of reliable diagnosis along with effective treatment is urgently warranted. One mechanism is microcavitation (MC) following exposure to a blast. We previously demonstrated that MC caused cell death/disruption of tight junctions. Also, the injured BE expresses a high level of E-Selectins (CD62e). The upregulation of this protein can be exploited for theragnosis. We hypothesized that BE disrupted by an explosive blast could be targeted and treated for restoration. To test this hypothesis, we engineered nanoparticles (NPs) that are decorated with antibodies to specifically bind to the injured endothelial cells (EC) and loaded with therapeutic reagents to enhance cell proliferation. Poly (lactic-co-glycolic acid; PLGA) NPs, which have stable and tunable properties, were successfully fabricated and characterized using dynamic light scattering and SEM/TEM imaging. The PLGA NPs were loaded with potential therapeutic reagents, conjugated and functionalized with ligands (CD162) to target CD62e on the injured ECs. The cells showed high affinity to conjugated NPs compared to unconjugated. The conjugated NPs internalizations were quantified by measuring the accumulation of intracellular NPs. Preliminary data show internalization of a surfactant poloxamer P188 induces proliferation of BE. Quantitative analyses are being performed to establish a statistical significance of the BE restoration in response to the P188 treatment. This study provides a platform for the validation of potential theranostic approaches for the treatment of TBI.

Examination of Nuclear Morphology in Mesenchymal Stem Cells During Adipogenic Differentiation Using a Combined Experimental and Computational Modeling Approach

Andrew McColloch
Advisor: Michael Cho
Bioengineering Department

While much research has been done regarding cytoskeletal remodeling, relatively little has been done on identifying the structural changes of the nuclei. As stem cells progress toward distinct lineages, specific gene activation must occur to generate unique cell types. Studies have shown the positioning of chromosomes determines genetic activation, and that the major structural component of the nuclear envelope, lamin a/c, influences nuclear shape. This work attempts to quantify the nuclear remodeling of human mesenchymal stem cells during biochemically-induced adipogenic differentiation. Nuclear deformation and lipid deposition were quantified by fluorescence microscopy. Results show the size of nuclei decreased over time as the lipid expression is up-regulated. Stem cell nuclei exhibited an exponential decay over time. Increases in the lipid expression appear to lag the nuclear reorganization, suggesting the nuclear deformation is a prerequisite to adipocyte maturation. Furthermore, lamin a/c expression was increased and redistributed to the nuclear periphery, along with a subsequent increase in nuclear aspect ratio. To further assess the nuclear shape influence on differentiation, a nuclear morphology with high aspect ratio was achieved using a microcontact-printed substrate to regulate the cell and nuclear morphology. This nuclei shape failed to differentiate stem cells more efficiently, suggesting the cellular process of nuclear reorganization cannot be overcome mechanically. Finally, a bio-mechanical model was generated to track the nuclear shape change during differentiation and attempt to predict the forces acting upon the nucleus to direct this change.

Implementation and Analysis of Caching Mechanism on Cloud Cluster for LHC ATLAS Experiment

Priyam Banerjee
Advisor: David Levine
Computer Science and Engineering Department

This research focuses on how feasible the adoption of Xcache into ARDC cluster would be, finding the network dependencies, performance parameters of the cache (hit rate for reusability, rollover or cache rotation using high and low watermark, bytes input and bytes output for monitoring the network). This is to find an alternative for limited storage space and, at the same time, using a sub-system (Xcache) to reduce bandwidth and access latency (reduced network traffic).

Potential Applications for Non-Invasive Electric Field in Diabetic Therapies

Caleb Liebman and Thao-Mi Vu
Advisor: Michael Cho
Bioengineering Department

For those affected by Type I diabetes, blood glucose monitoring and insulin analog injections are an everyday part of life. A more permanent solution would require replacement of the insulin producing beta cells destroyed by the disease. Experimental procedures such as islet transplantation and various stem cell therapies could provide such cells; however, the impairment of these cells’ functionality hinder their efficacy. Previous research has demonstrated that exogenous electric fields can affect various areas of cell physiology including proliferation, differentiation, and migration. Therefore, we aimed to determine the physiological response of beta cells to non-invasive electric field stimulation (EFS) in order to elucidate its capacity for improving beta cell functionality. Our results demonstrate the capacity for EFS to elevate intracellular calcium via L-type voltage gated calcium channels (VGCCs). In addition, further experimentation indicated an elevation of the transcription factor PDX1 which is linked to beta cell functionality, proliferation, and cell survival. Given this, EFS could have potential for improving the functionality of insulin producing cells and overcoming challenges facing both diabetic islet transplantation and stem cell therapy.

Abstracts – Senior Design

iSpy

Cameron Howard, Abdul Mannan, Ivy Moore, Gaganeet Singh and William Truong
Advisor: Chris Conly
Computer Science and Engineering Department

iSpy is an Android smart-phone app that uses the camera to photograph and find the object in the picture in local stores. iSpy will use machine vision to identify the object in the image, which can be taken from the app itself or uploaded from gallery. iSpy will search online for the object, and then find where it can be purchased locally, using the phone’s GPS to identify the user’s location. iSpy will use machine learning to better its search and identification algorithms. With the information it collects, iSpy will recommend a store based on price and distance.

Electric In-Wheel Drive System

Joseph Herring, Jacob Lamotte-Dawaghreh, Logan Pechal, Tim Pugliese, Matthew Smith and Garrett Tolar
Advisor: Yawen Wang
Mechanical and Aerospace Engineering Department

Electric cars serve as a promising, though partial, solution to the issues facing our global climate. However, problems of range and efficiency have proved to be barriers for mass adoption. In this project, NextGen Drive is developing an alternative, more efficient drivetrain design. Specifically, while most vehicles are powered via a central motor connected to the wheels through a transmission, driveshaft and differential, our design uses motors mounted inside the wheel hub to directly drive each wheel. This eliminates the losses experienced in the various mechanical joints and reduces the overall weight of the vehicle, freeing up the engine compartment for alternative uses and enabling completely adaptive torque vectoring. At this point, the team has developed a preliminary design and is finalizing the suspension and steering geometry, as well as performing a stress analysis, quarter car analysis, and performance analysis for a hypothetical vehicle using this system.

Wheelchair Dynamometer

Antonio Araujo, Chad Goodlow, Brandon Griffin, Jason Gulledge, Matthew McCormick and Mathew Niestroy
Advisor: Robert Woods
Mechanical and Aerospace Engineering Department

The team was tasked to design and build a wheelchair dynamometer for application in research and physical fitness. People who use wheelchairs perform a unique, complex set of motions to move from place to place. A wheelchair user’s driving motion is strongly dependent on both physical capability and level of disability. For biomechanists, to better understand a wheelchair user’s strength and disability, it is helpful to quantify the output of this motion: the rotation of the main wheels. This rotation can be measured by comparing the rotational velocity of a user’s wheels to a predetermined resistance. This information produces a quantifiable torque output which can then be compared from user to user. When the variable resistance electric motors are coupled with an externally mounted variable-weight flywheel, the wheelchair dynamometer can simulate a coasting like effect and serve as a physical fitness device.

Eye Gaze

Jonathan Aguilar, Henry Bang and Khoa Pham
Advisor: Chris Conly
Computer Science and Engineering Department

Our mission is to support an eye-tracking system that can assist users in identifying which object they are looking at. We will obtain two dedicated high-quality cameras, to be placed on ski goggles, that will capture the user’s eye movements. One camera will face the eye and the other will face outward to the user’s surroundings. Further, they will have a wireless or wired connection to a raspberry pi, where our built program can feed in the images and translate them into vectors. The vectors will provide a clear direction to where the eye’s pupil is pointing. The program will then exploit its algorithm to analyze related information about the object based on stored databases, and these details will be displayed on the user’s monitor. Lastly, one of the main requirements is that the system must be able to perform its operation on various eye colors and shapes.

UTA-SC

Pavanaj Biyani, Robert Brady, Brandon Chase, Kartik Gupta and Nicholas Reimherr
Advisor: Chris McMurrough
Computer Science and Engineering Department

UTA Summer Conferences hosts close to 100 camps every summer but due to loosely tied applications and human error, the organization has an estimated $50,000 in lost revenue each summer. By providing a streamlined complete solution to manage tasks, from requesting to host a camp to managing billing, Summer Conferences will reduce their losses, improve efficiency, and increase their professional appearance. Our team’s mission is to migrate Summer Conferences from their old processes rooted in Google Sheets to a full stack web application that can be accessed from any networked device. This application will manage most areas that Summer Conferences needs such as contract details, registering camps, managing rosters, check-in and check-out of campers, checking out equipment, parking and billing. A major aspect of the system will be its usability and its efficiency to interact with custom-made API requests.

Abstracts – L3/Link Innovation Awards

3D-Printed Aircraft

Saleh Abusalah, Bosah Agolua, Zeshan Ahmed, Noor Diya, Kaushik Iyer, Traevis Joshlin and Matthew Montoro
Advisor: Robert Taylor
Mechanical and Aerospace Engineering Department

Forward Air is conducting research and development on 3D printing aircraft components. 3D printing, specifically additive manufacturing, is a very promising field for research and fabrication, especially in aerospace applications. From printing small components to designing jet engines, additive manufacturing holds great promise in maximizing the performance and minimizing the weight of aerospace components.

Eye Gaze

Jonathan Aguilar, Henry Bang and Khoa Pham
Advisor: Chris Conly
Computer Science and Engineering Department

Our mission is to support an eye-tracking system that can assist users in identifying which object they are looking at. We will obtain two dedicated high-quality cameras, to be placed on ski goggles, that will capture the user’s eye movements. One camera will face the eye and the other will face outward to the user’s surroundings. Further, they will have a wireless or wired connection to a raspberry pi, where our built program can feed in the images and translate them into vectors. The vectors will provide a clear direction to where the eye’s pupil is pointing. The program will then exploit its algorithm to analyze related information about the object based on stored databases, and these details will be displayed on the user’s monitor. Lastly, one of the main requirements is that the system must be able to perform its operation on various eye colors and shapes.

Virtual Reality Tasks for Cognitive Assessment

Andrew Miller
Advisor: Shawn Gieser
Computer Science and Engineering Department

Virtual reality, which most would relate to video games, has been applied in medical and industrial fields. We propose to create a VR environment where the user has to perform a task, or tasks, while the system is monitoring the user’s behavior to detect physical and cognitive fatigue. Data will be collected from the sensors used to interact with the virtual environment. This data, as well as the user’s performance in the task, will be used to calculate the level of fatigue the user experienced. Survey data will also be collected to verify any results.

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