As part of one of the engineering capstone projects, a calibration testing system was improved with the aid of computer vision. Computer vision was integrated into this project as a solution to a rotating pedestal calibration test that was previously performed by the naked eye. The main goal of this system was to detect and track a red 635 nm wavelength laser spot with offsets as small as 0.025 inches on a 10 x 10 inch grid accurately and precisely. Designing this system involved three major criteria: camera selection, data processing hardware, and algorithm performance.
The first criteria studied in the design process was the camera. The system required a camera that was compact in size, covered the entirety of the grid at less than 11 inches, and captured high quality images. Furthermore, two main data processing hardwares were explored: Raspberry Pi and a standard test laptop. The processing hardware criteria considered were speed, portability, and maintenance. Finally, RGB and houghcircles were the two algorithms used to detect the red laser dot. Testing was conducted to compare the algorithms based on their ability to detect the laser spot, precision in tracking, and repeatability. These design considerations guided the down selects for the final components used in this system.

The LabVIEW team for the Applied Avionics Inc. project focuses on fully integrating the programming of all electrical components with LabVIEW. The major requirements for this project include utilizing LabVIEW to display and capture data feedback, completely automate the testing process, and to read and send data directly to AAI’s database. By creating an actuation and extraction feedback machine that is fully LabVIEW controlled, a variety of switch body types were able to be accommodated and tested. The machine has been shown to decrease variability of results and improve the efficiency of AAI’s current process in all aspects required.

Cloud based services such as IBM Cloud and Amazon Web Services provides a new platform for data collection, storage and processing through the internet that enables environment monitoring via wireless sensor networks. In this project, we would like to develop a cloud-based low power monitoring and notification platform using AWS. Most existing notification platforms are provided as an expensive, closed system that do not allow flexibility and is often difficult to troubleshoot. These systems require special hardware (such as unique walkie-talkies) and upgrades are pushed back due to costs.
Our system will utilize AWS Lambda functions, a cloud database, and IOT buttons so that medical staff can receive and store real time patient vitals and notifications with a data forwarding device such as a smart phone, tablet, or computer. AWS solutions are low-cost and flexible, allowing the care centers to customize the functionality to their specific needs. These buttons do not require wired power supply and have a long-lasting battery.

We are presenting a method referred to as Hydrogen Production by HyPIR Electrolysis. The method increases the rate of hydrogen production from a 1 molar potassium hydroxide and water solution under 6 volts when an infrared laser is irradiated with an optimum wavelength of light through a cell and concentrated on exposed copper electrodes. The irradiating light facilitates the dissociation of water by stretching the hydrogen oxygen bonds and increasing the rate of hydrogen production. Production of hydrogen due to the class 4 laser is altered by the specifications of laser energy, pulses per second, and spot size.

In this experiment, the mechanical properties of 3D printed specimens of different printing parameters were tested under tension. The printing parameters of these specimens were: surface resolution, infill density, and print orientation. Parts were printed in Onyx nylon with a Fused Deposition Modeling (FDM) printer called the Markforged Onyx Pro. Factorial sets of specimens using all various parameters are printed and tested to create a reference table for future engineering projects. Specimens are then printed as composite variations with continuous fibers in order to understand the benefits a composite may have.

A racecar’s suspension is one of the key contributors to its performance on a track. Each component – springs, shocks, links, etc. – can be dealt with as a variable within a mathematical model. There are hundreds of combinations of these variables, with each change affecting the stiffness ratio. Using the sway bar as the variable of interest, data acquisition, and computer modeling, a mathematical was developed for predicting the stiffness ratio as a function of sway bar diameter. This model can simplify the time-consuming iterative process that is “racecar setup” by allowing a race team to plug numbers into an equation to make predictions instead of conducting on-track test sessions to determine the results of each component change.
PDF: Attached to this email.

In our project, image tracking was employed to provide a honing mechanism for a robotic "scorpion tail" attached to a small Remotely Controlled Vehicle. The car will be controlled wirelessly through a web interface, with mobile phones being the target user. Like the Mario Kart Versus Mode, where multiple cars drive and bump into each other, the vehicle will be controlled wirelessly while the "tail" is actively seeking targets and upon close proximity will "pop" the balloon. Each car will have 3-5 balloons to start, and the objective of the tournament will be to hunt down the remaining cars and “pop” their balloons, until all cars lose their balloons and the victor remains with at least one balloon intact. Python and Google Cloud were used to make a server with for the mobile website, and C++ was used to relay the commands sent wirelessly to the vehicle's two DC motors. Image tracking was implemented using the popular computer vision OpenCV library in python. The research will conclude with a tournament on Pi day (March 22, 2019).

In our project, we aimed to design an autonomous rover similar to that of the popular Mars rovers such as Curiosity. Our rover employs a differential drive system with two continuous rotation servo motors that are controlled with the popular ROS robotic programming library in C++ and Python. A navigation algorithm employs the known position of the robot gathered from a magnetic encoder on the motors and the multiple optical range fidners placed around the vehicle to avoid obstacles on route to its destination. A camera is employed to detect target objects for simple pick-and-place tasks using its DC motorized gripper placed at the front of the vehicle. We have successfully built this vehicle and will demonstrate its capabilities at the 2019 IEEE R5 robotics competition in Lafayette, Louisiana as well as at the SRS presentation day.

Rotating Precision Mechanisms, Inc. (RPM) requested that TCU Senior Design update their current Laser Position Accuracy Test Set, which utilizes a laser to calibrate rotating pedestals. RPM positions this test system at a range of distances from a rotating mirror, passes a laser beam through an optical system to the rotating mirror, and measures the offset of the reflected laser dot in order to test the pointing accuracy and repeatability of their positioners. RPM requested that the redesigned test set deliver a reflected laser dot size within 0.125 inches when the test system is any distance between 10 and 100 feet from the rotating mirror. Our prototype for the redesigned Laser Position Accuracy Test Set relies on an optical component called a beam expander to cleanly extend the laser beam at the desired dot size over the specified range of distances. In order to design and manufacture this beam expander, our team researched optical collimators, beam expanders, and lenses in addition to using an Optical Ray Tracing software to model potential beam expander designs. After constructing and testing a working prototype, we completed several iterations in order to improve the resulting laser dot size. Finally, we compared our beam expander design to an Edmund Optics research grade beam expander to further quantify the success of our design.

In our project, a control-theory based algorithm would be employed to develop a small electric vehicle that can self-navigate through an unknown course to arrive at the desired location while avoiding obstacles and walls. This project is an extension of our successful project funded last year, in which we were able to operate a partially autonomous car to run around a location, and generate a virtual map. Our team expects to grant the car full autonomy like a self-driving car and let it travel through a relative abundance of places to create computer models of critical infrastructures without the help of humans. The success of this project will have a broad impact on society. First, this capability would be useful in self-driving cars, which allow drivers to spend their time more productively instead of driving to work or assist disabled people. Second, the car can generate a simulated model of places that help to analyze unknown locations. Finally, the project can surely create a platform for future TCU engineering students to learn about self-driving car technology and machine learning. This project is expected to succeed due to the achievements we gained from the previous project.
The algorithm will be written in Python/ROS, controlled by Raspberry Pi 3, and tested on a walled course constructed by us. It should be able to navigate a course, without having already driven through it. Another special feature is that the car will also precisely arrive at a pre-determined location.

Flatfoot and cavus foot are postural issues that affect approximately 40% of people and can be corrected by means of orthotic inserts for shoes. A digitally reconfigurable mold is being developed as a tool for orthotists to visualize and fabricate orthotic inserts. The surface will be formed by an array of solenoid actuators controlled by the orthotist. The patient will stand on the reconfigurable surface while the orthotist evaluates the patient’s needs by manipulating the surface. Once the orthotist is satisfied with the array, the surface position will be held by a clutch system, so the patient can step off the surface and the surface positions can be recorded. This work describes my development of a prototype mechanical clutch for the digitally reconfigurable surface. The result of this project is a proof-of-concept design of an array of twenty-five physical clutch points which may be individually addressed by means of servo motors controlled by an Arduino microcontroller. With the development of this prototype, it is believed that such a control interface could be implemented on a system large enough for an adult human to stand on. This proof-of-concept is a small step in a larger project of developing a full-scale reconfigurable surface by which an orthotist could create posture correcting devices.

Urban Heat Islands (UHI) describe a phenomenon of increasing ambient temperature in densely built areas of cities as compared to rural areas. Impervious cover, ubiquitous in urban areas, appears to absorb solar radiation and reemit that radiation as heat. Urbanization and UHIs have impacts that range from local to global scales and can be found in cities of all sizes and climatic regions (Fernando 2013). This study focused on Tarrant County, Texas and analyzed changes in impervious surface cover and average monthly temperatures at four different NOAA weather monitoring stations over approximately 60 years in a search for urban heat island effect. Temperature analysis indicates an increase in temperature over the 60-year period. This study aims to determine whether that temperature increase is due to UHI.

The Urban Heat Island effect, or UHI, describes a phenomena involving heighted temperature indices in metropolitan areas when compared to surrounding rural landscapes. An increasingly relevant area of study following the advent of global warming, today, the associated “infernos” plaguing urban landscapes across the globe have the capacity to seep beyond concrete jungle walls, to reap havoc on once lush and vibrant vegetation and ecosystems. The following analysis combines an understanding of the Urban Heat Island effect with Remote Sensing technologies and Landsat Aerial Imagery to uncover the impact of urbanization in Seattle, Washington. With an emphasis on illustrating change over time, historical data surrounding imaging and climate trends further support this GIS analysis of vegetation in Seattle.

Water resources are critical to areas experiencing urbanization and a rapidly increasing population. The depletion of these resources due to either human usage or environmental factors has the potential to lead to water scarcity in surrounding areas. A GIS analysis was conducted on Lake Mead near Las Vegas to assess the change in water level over time.

Coffee is one of the most popular drinks in the world. Americans generate on average 12600 tons (around a thousand school buses) of coffee grounds per day – which is most often landfilled. This typical waste stream represents a potential feedstock for developing carbon-based materials with applications across numerous disciplines. For example, initial research in Dr. Harvey’s Lab on spent coffee grounds, received from Avoca Coffee Roasters in Fort Worth, has shown that charring the grounds at 350 ℃ improved its Lead removal abilities. Our research will build upon this previous research by conducting more controlled studies to evaluate those earlier results and determine the optimal charring temperature for producing charcoals for water filtration applications. Since we had no control over how the previously donated coffee grounds were brewed by Avoca Coffee Roasters, we decided to design an experiment that will give us more control over the brewing process. The coffee beans were obtained from Avoca Coffee Roasters and brewed according to the Golden Ratio. We will also study the surface properties of charred coffee grounds produced at 350 ℃, 450 ℃, and 650 ℃ from Ethiopian and Mexican coffee grounds.

A GIS and remote sensing analysis of Rwanda was conducted to analyze changes in land cover, urbanization, and croplands over time. Data mapping changes in major crops productivity throughout time was also analyzed and combined with information on elevation and soil conditions. All factors were analyzed to identify the location and suitability of soils for each major crop.

The long term effects of urbanization on soil properties in Fort Worth, Texas remain largely unknown, making future predictions of soil health and the development of environmentally beneficial practices difficult. The rapid expansion of the Fort Worth Metroplex begs the question of how can cities best prepare for or mitigate the effects of disturbance due to construction and constant lawn care. In order to understand how soil properties change with time after an initial disturbance, many different methods were implemented to quantify and qualify the different stages of post-urbanized recovery in order to find the trend the soils at the houses of varying age ranges took relative to the natural area. Overall, the soil properties trended towards recovery and the deviation from the natural park area decreased as the houses increased with age. The only variable that did not follow this trend was amount of organic matter at each site, which was determined to be affected uniquely by lawn care and the continued use and accumulation of nutrients from fertilizer applications. These results can be used to identify and understand the effects caused by future construction projects and possibly be used to establish more sustainable development in the DFW area.

Over the last 20 years significant growth has occurred in the northern part of Fort Worth, Texas defined by the zip codes 76131, 76137, 76177, and 76244. Using GIS analysis, this project measured the amount of open area lost and the growth of residential and commercial areas.

The World Stress Map (WSM) is a global compilation of information on the stress field of the present-day earth crust and is maintained since 2009 at the Helmholtz Center Potsdam GFZ German Research Center for Geosciences. This database uses data from earthquake focal mechanisms, well bore breakouts, drilling induced fractures, and geologic data to generate a map of the stresses in the Earth. Using GIS, the data was mapped and examined for the Permian Basin area of West Texas which is currently one of the largest and most active oil fields in the United States. This database in conjunction with data collected on the direction of horizontal well bores was examined to determine if or how stress directions in the Earth influenced the drilling bore direction. This data was also used to see if there is a correlation between stress direction and a company’s decision to place a well in a certain location or orientation.

Professors and Texas Christian University Chemistry students collaborated with O.D. Wyatt High School faculty and students for the rewrite of laboratory experiments. This was done through the lens of green chemistry to best meet the needs of the school’s curriculum scope and sequence with a minimal budget. The primary focus was safety. Safer disposal of hazardous waste, the use of less hazardous chemicals, and a cleanup to provide a safe workspace. Following the redesign of the experiments with the implementation of green chemistry concepts, a thorough cleaning and reorganization of the high school’s storeroom took place. Excess chemicals were safely disposed of, an inventory system was adopted to track presence and location of the remaining chemicals, and all waste and recycling was properly discarded. At the end of this outreach program, O.D. Wyatt gained a revamped curriculum utilizing less hazardous materials, a green chemistry outlook, and a redesigned and safe storeroom. We TCU students gained practical experience redesigning laboratory protocols and adapting them to a green chemistry standard. Additionally, physically applying the techniques learned in the curriculum being taught is invaluable knowledge gained by many students involved. Furthermore, we have also gained the interpersonal communication skills required to simplify complicated concepts to an audience of high school students without scientific backgrounds. This outreach will have long-term positive effects on the high school. The students will be exposed to green chemistry principles and the faculty will see the ease with which green chemistry principles can be added and relished within their curriculum. This program will continue to impact O.D. Wyatt with long-term safety and cost efficiency tactics being employed.

Background: Nutrition plays a vital role in disease prevention and health promotion; however, few health professions curriculums provide adequate nutrition education. The Culinary Medicine program (CM) was developed at Tulane University Goldring Center for Culinary Medicine in 2012 to train health professions students about nutrition and healthy eating practices. Students also participate in a 10-year longitudinal study (Cooking for Health Optimization with Patients, CHOP) to assess learning outcomes.
Objective: Assess outcomes of a CM course for improving nutrition and dietary competencies of health professions students.
Design: Cohort of 77 medical and 13 physician assistant students (57/female; 33/male) from University of North Texas Health Science Center (UNTHSC) and Texas College of Osteopathic Medicine (TCOM).
Methods: The CM curriculum was first offered in Fort Worth, TX in 2014 and taught by faculty from UNTHSC, TCOM, Texas Christian University (TCU) and Moncrief Cancer Institute. During 2016-2018, students participating in the CM course were assessed using the 4-part CHOP survey including demographics, attitudes, dietary habits, and degree of proficiency in competencies related to nutrition/dietary knowledge and application. Study procedures were approved by TCU IRB, and informed consent was obtained. Data were analyzed to meet study objectives (SPSS, p<0.05).
Results: Results showed that students who participated in the CM course reported greater proficiency in their ability to inform patients about nutrition/dietary competencies: (1) health effects of the Mediterranean, Dash, and low fat diets; (2) weight loss strategies, portion control, food label facts and serving sizes; (3) dietary practices for type 2 diabetes, celiac disease, and food allergies; (4) role of dietary cholesterol/saturated fats in blood lipids; (5) recognizing warning signs/symptoms for eating disorders; and (6) role of fiber and omega-3 fatty acids in disease prevention and heart health (p<0.05).
Conclusion: Study results underline the value of dietetics educators providing innovative learning opportunities that integrate nutrition into training for health professions students.

DETERMINING LEVEL OF ADHERANCE TO THE MEDITERRANEAN DIET BY INDIVIDUALS LIVING IN THE UNITED STATES

S. Cowart,1 R. Seguin,1 A. VanBeber PhD, RD, LD, FAND1; L. Dart, PhD, RD, LD1;
1Texas Christian University

Learning Outcome: To determine how closely components of the Mediterranean Diet are followed by individuals living in the United States.

Learning Needs Codes:
Primary: 3020 Assessment of Target Groups
Secondary: 4040 Disease Prevention

Background: Research indicates those who follow a diet and lifestyle resembling the Mediterranean Diet have lower chronic disease risk.

Objectives: The objectives of this study were to determine how closely the Mediterranean Diet was followed by individuals living in the United States and to analyze correlations between dietary patterns and chronic disease risk.

Design: This un-blinded, randomized trial was approved by Texas Christian University IRB. Participants were recruited via social media, email/text messaging, and in-person communication. Following informed consent, participants completed an online questionnaire through Survey Monkey™. Analyses assessed consumption of fruits, vegetables, whole grains, dairy, legumes, animal protein, nuts, water, and red wine compared to Mediterranean Diet Score recommendations.

Methods: Data were analyzed using SPSS (p<0.05) and (p<0.01), and frequency distributions and correlations were analyzed for trends in adherence to Mediterranean Diet and USDA dietary recommendations.

Results: Participants included 258 females and males (86% and 14%, respectively). Sixty-nine percent identified as Caucasian, 21% Hispanic, 10% other ethnicity, and 13% reported chronic disease diagnosis. High school diploma was the highest education earned by 13% of participants; 28% obtained some college, and 59% received a bachelor’s degree or higher. Forty-six percent were married; 41% were single. A strong inverse relationship existed between age and physical activity, with participants ages 18-34 years reporting greater physical activity compared to participants >35 years old (r=-.131; p=0.05). With participants who performed >30-60 minutes physical activity/day, a positive relationship existed with greater consumption of vegetables and fruits (r=.200; p=0.05). Results also indicated only 36% of participants consumed the Mediterranean Diet Score recommendations for >2-3 cups vegetables/day, and only 22% consumed the recommended >2 cups fruit/day.

Conclusions: To lower chronic disease risk in the United States, nutrition education efforts should focus on importance of increasing fruit and vegetable consumption and greater adherence to Mediterranean Diet principles.

Funding Source: N/A
Word Count: 296
Key Contact: Anne VanBeber RD, LD, PhD, FAND, a.vanbeber@tcu.edu

Learning Outcome: Provide education about the knowledge, behaviors and attitudes individuals have towards dietary fatty acids.

Background: Research has shown a strong relationship between dietary fatty acids (FAs) and their impact on blood cholesterol. Few studies have examined knowledge, behaviors and attitudes (KBA) towards dietary FAs impact on blood lipid levels.
Objective: To determine: 1) KBA of FAs using the modified General Nutrition Knowledge Questionnaire (GNKQ); and 2) correlations between anthropometric data, GNKQ responses and blood lipid levels.
Design: This study utilized a cross-sectional research design.
Methods: Upon IRB approval, 104 women ages 18-40yr consented and completed the modified GNKQ via Qualtrics®. The GNKQ consisted of 42 questions and took approximately 15min to complete. Additionally, a subset of nine women also were instructed to fast for 12-15hrs prior to testing at the Obesity Prevention Laboratory at TCU. Height (cm), weight (kg), BMI (kg/m2), waist-to-hip ratio were recorded. Next, a fasting blood sample (5mL) was obtained. The blood samples were sent to AnyLabTestNow® (Fort Worth, Texas) for a lipid panel. Results were analyzed via IBM SPSS® (Statistics Version 25.0. Armonk, NY). Significance was set at p<0.05.
Results: More than 80% of participants were aware of saturated, monounsaturated, and polyunsaturated FAs, but only 33.3% were able to identify their proper food sources. Of the survey responses, approximately 1.9% demonstrated poor knowledge (answered 0-11 questions correctly), 54.3% moderate knowledge (12-23 questions correctly), and 43.8% strong knowledge (24-34 questions correctly). 100% of lipid panel participants had normal total cholesterol and HDL levels. Risk ratio (LDL/HDL) and weight showed a strong positive correlation (p=0.004, r=0.846**).
Conclusion: Despite self-reported awareness, participants lack knowledge of dietary FAs. The subset results showed strong correlation between risk ratio and weight representing the relationship between weight and lipid levels. Overall, more research should ensue with a larger sample.

Background: Over 42 million Americans face food insecurity (FI). Simultaneously, approximately 40% of food produced in the U.S. is wasted. Where FI and food waste (FW) coexist, it is necessary to develop and implement programs to decrease the negative consequences caused by these issues.
Objective: The objective of this study was to create a standardized model for implementing a student-led food recovery program (FRP) for other universities to access and utilize. The secondary objective was to measure the effectiveness of the FRP at TCU.
Researchers hypothesized that by incorporating the FRP into the dietetics program, the FRP would achieve program sustainability and enhance dietetic students’ knowledge of FI and FW.
Design: This study utilized a mixed methods study design.
Methods: Over three academic semesters, researchers observed the overall operations of the FRP at TCU. Researchers collected quantitative data on food types (i.e. vegetables, grains, proteins, mixed), quantities (pounds), and raw food costs ($). Researchers conducted semi-structured interviews with nutrition and dietetics students, foodservice personnel, and faculty and analyzed interview transcriptions for prevalent theme codes. A codebook was created based on frequently identified phrases, and themes were extracted. Participants provided written consent. This project received IRB approval.
Results: Over 12,700 pounds of food were recovered during the study period. By weight, protein-containing foods were the most recovered type of food (~5700 lbs.), followed by grains (~2900 lbs.), vegetables (~2100 lbs.), and mixed foods (~2000 lbs.). Five major themes were extracted from interviews; all respondents identified the FRP as a meaningful and practical program.
Conclusions: FRP offers a sustainable solution for benefitting the environment, combating FI, and providing dietetics students with experience working with FI and FW. Efforts should be made to incorporate a FRP at the university level, and a dietetics program may offer an effective means to achieve this integration.

Background: Athletes increasingly skip meals because they lack time or knowledge to prepare their own meals; mobile applications have been proposed as a potential solution to this problem. Adherence to mobile app tracking may vary, but self-motivation and nutrition knowledge has been shown to increase chances of behavior change while using an app.
Objective: Determine if female college athletes’ nutrition/fueling behaviors changed over four weeks by utilizing a mobile application for tracking fueling practices.
Design: Pilot study with cohort of 17 female TCU NCAA Beach Volleyball athletes.
Methods: Pre and post-study questionnaires examined attitudes toward mobile applications, dietary behaviors, and frequency of fueling habits. Athletes also attended a pre-study training session about utilizing the Eat2Win app. Data analyses included recorded frequency of application usage and logged meals per/day plus impact on dietary behaviors/fueling habits. Study procedures were approved by TCU IRB. Participant informed consent was obtained. Data were analyzed to meet study objectives (SPSS, p<0.05).
Results: Most athletes (82%) disliked using the Eat2Win app, where app usage decreased from 88% in week one to 18% app usage at the completion of the study. Reasons for the pronounced decrease in usage included frequent app crashes, too time consuming, and limited phone storage space. Additionally, results did not show improvement in athletes’ eating habits with app usage. Although pre-study results showed 42% of athletes did not consistently eat breakfast and/or eat/drink something every 3-4 hours, those athletes who reported greater frequency of eating breakfast and/or every 3-4 hours or refueling one hour after practice, maintained consistent positive eating behaviors throughout the study. These same athletes also reported greater energy levels overall (r=.671; p=0.01).
Conclusions: Study results emphasize the importance of implementing user-friendly mobile apps for athletes that are time-use efficient and offers calorie-counting and picture logging functions to promote change in dietary and refueling practices.