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Southern Polytechnic College of Engineering and Engineering Technology 2022-2023 Projects

Click here to return to the main project listings page. Questions: Email our@kennesaw.edu.

    • To enable NASA's science and exploration missions, the use of new materials and actuators to perform space operations is always needed as stated by NASA’s Human Robotic Systems. Inspired by nature, this research proposes the design, fabrication and control of soft-bodied robots composed of novel materials. Soft robots are autonomous systems that are primarily constructed of materials with stiffness in the range of that of soft biological materials. The final design of this project will be a soft robot prototype that is capable to operate in hostile environments, investigate candidate destinations and provide vital information to prepare for human explorers. 

      1. The student will learn how to work with a 3D Printer to design and fabricate different components for the robot.
      2. The student will learn how to work with a microcontroller to control robot.
      3. The student will learn how to model a robot in a simulation environment and study its behavior and movement. 
      1. Read papers to learn about robots.
      2. Learn and practice with Simulink to model robots.
      3. Learn and practice to work with a 3D Printer.
      4. Learn and work with microcontrollers such as Arduino and Raspberry PI. 

    • The students will work on this project in hybrid form with majority of the work as face-to-face. 

    • Dr. Turaj Ashuri, tashuri@kennesaw.edu 

    • The purpose of daytime tunnel lighting is to reduce the visual difference outside and inside a tunnel to ensure that motorists can safely approach, cross, and pass through the tunnel at the design or posted speed. For short tunnels, an assumption is often made that sunlight can penetrate them so that daytime artificial lighting would not be necessary. However, this assumption does not always hold. In fact, the research shows the crash rate is much higher in the short tunnels in absence of artificial lighting even during the daytime. The objective of this project is to analyze the field data to develop artificial intelligence for lighting short tunnels.

      • Design problem-solving process for engineering problems
      • Analyze statistical data 
      • Generate numerical results
      • Write technical papers 
      • Biweekly meetings
      • Complete the assigned tasks 

    • Hybrid

    • Dr. Mahyar Amirgholy, mayhar.amirgholy@kennesaw.edu

    • The economic cost associated with motorcycle crashes is in the range of millions of dollars every year. Fatal motorcycle crashes in the state of Georgia have increased rapidly in recent years. During the last five years from 2017 to 2021, there were 808 fatal motorcycle crashes and as a result, 835 Georgians have lost their lives. In addition, there were 16,322 injuries involving motorcyclists during the same time period. The change in fatal motorcycle crashes during the five-year period from 2017 to 2021 was nearly 38% making this a serious highway safety concern affecting Georgians.

      This study will therefore investigate crash data from GA in relation to motorcycle crashes and apply the commonly used statistical methods to identify the critical factors associated with the high number of fatal motorcycle crashes. Crash data related to the proposed study will be acquired from the Georgia Department of Transportation and the detailed information gathered will include motorcycle rider characteristics such as age, gender, riding-under-the-influence, etc., and crash characteristics such as time and day, environmental factors at the time of the crash, level of speeding, type of the roadway, cause of the crash, movement at the time, location of the crash etc. to name a few. Various characteristics will be studied and analyzed to identify the risk factors associated with motorcycle crashes. These will assist the FYS to identify the measures that would be helpful in reducing the number and severity of motorcycle crashes in GA so that the highway safety of all road users could be improved.

    • Upon the completion of the project the student will:

      • Understand the basic concepts in conducting research in the broad area of engineering
      • Understand how a literature review is conducted
      • Learn about basic data analysis practices
      • Understand how findings could be derived by analyzing data
      • Be familiar with how research could be used to provide guidance on how motorcycle safety could be improved
      • Educate themselves and others about the importance of good highway safety practices and the economic benefits associated with reducing motorcycle-related crashes

    • Following are the major tasks the student will engage in depending on the stage of the project

      • Conducting a literature review about motorcycle safety and understanding the general issues
      • Gather data related to motorcycle crashes in Georgia for the last five years
      • Learn basic statistical methods that could be applied to analyze crash data
      • Apply the most suitable methodology to analyze motorcycle crash data and identify the critical factors affecting motorcycle safety
      • Write down the activities completed, and time spent working on the project
      • Write an abstract and participate in the symposium
    • Hybrid

    • Dr. Sunanda Dissanayake, sdissan1@kennesaw.edu

    • Production of crushed aggregates involves quarrying rock by drilling and blasting followed by a series of crushing and screening operations until the desired gradation is achieved. This process generates by-product mineral fine materials commonly known as quarry waste or quarry-by-products (QB). The particle sizes of QB are typically less than 1/4 in. in size. The amount of QB production is continuously increasing every year and its deposition will require significant investments. According to National Cooperative Highway Research Program (NCHRP) Synthesis 435, the amounts of QB generated from quarry processing can be up to 25% of the total aggregate produced. In Georgia, more than 5 million tons of the QB are produced per year. However, the utilization of QB in construction is still very limited due to the lack of economically viable solutions.

      This study aims to synthesize the information about QB usage in construction projects in Georgia. The student/s will acquire information on general characteristics, production volume, and application areas of QB through a literature review, and surveys and interviews with Georgia aggregate producers. The findings of this study should be useful to transportation agencies in their efforts to develop a beneficial use of QB.

      • Understand how a literature review is conducted
      • Learn about basic data analysis practices
      • Present the findings of their research at conferences
      • Learn how to write technical report 
      • Meet with the faculty advisor for guidance/direction
      • Conduct the tasks related to the project 
      • Record the completed activity
      • Travel might be required to visit quarries
    • Hybrid

    • Dr. Jayhyun Kwon, jkwon9@kennesaw.edu

    • Illicit discharges are considered a threat to local water quality. Each year, approximately 860 billion gallons of sewage spills are reported throughout the country. In Georgia, sewer spills data shows that spills may range from hundreds of gallons to millions of gallons depending on the severity of the leak. The undetected sewer leaks may degrade the water quality in nearby streams, therefore causing undesirable consequences. A smart illicit discharge monitoring system may be the answer to mitigate the damages due to illicit discharge. 

      This project is continuation of last year’s project and our team is seeking motivated to continue this research. The selected freshman will be guided by previous year’s First Year Scholars in this research effort. This research can make use of students with various skills and background. The expected outcome for this year is to improve and update last year’s system and to acquire long term field data. 

    • At the end of the project, students should be able to:

      • Understand the describe issues with illicit discharge
      • Develop critical thinking skills for problems encountered in the lab and field
      • Work effectively as part of a team
      • Learn required programming skills
      • Present their research to an audience (e.g., poster, oral presentation, performance, display)

    • Typical activities for this research include:

      • Going to the field to troubleshoot problems with sensors
      • Working in the lab to incorporate new sensors
      • Improving web server dashboard to display collected data
    • Face-to-Face

    • Dr. Tien Yee, tyee@kennesaw.edu

    • A Software Defined Radio (SDR) is a radio transceiver that is primarily defined in software. It allows radio engineers and researchers to easily control the hardware and implement and configure the physical layer in software. SDRs have been used in many scientific platforms to implement, test, and study different wireless technologies and protocols. In this project, we explore the 5G waveform generation function of the MATLAB 5G Toolbox to generate different uplink-downlink transmission frames.

      The 5GNR (5G New Radio) 'knobs' include the bandwidth (BW), the physical resource block (PRB) allocation within the BW, the time slot occupation, the numerology, and the number of transmission layers, and the transmit (Tx) power. The generated waveform is transmitted over the air (OTA) using the GNU Radio software framework in conjunction with Universal Software Radio Peripheral (USRP) or other commercial SDR hardware.

      In the proposed work, two SDRs are used to implement the test bed's transmitter and receiver sides. Each SDR is connected by USB 3.0 to a GNU Radio Companion computer. The transmitter and the receiver GNU Radio flowgraphs have a built-in spectrum analyzer (SA) block to visualize the fast Fourier transform of the signal for spectral analysis. We use the 5G Toolbox because of its flexibility to customize the uplink and downlink 5G NR transmission that complies with the 3GPP specifications. In addition, we use another MATLAB function to convert the in-phase and quadrature (IQ) samples to binary points for use with GNU Radio. GNU Radio is a free and open-source software development toolkit that provides the mechanisms and sample signal processing blocks to implement radios in software. It is compatible with low-cost SDR hardware to enable RF transmission.

      Furthermore, it has a graphical user interface—GNU Radio Companion—to assemble radios by connecting blocks. Moreover, we use a Software Defined Radio (SDR) and P21XXCSR-EVB Energy Harvesting module (existing) to conduct experiments on RF energy harvesting from the SDR transmissions. Specifically, we are interested in obtaining insight into joint communication and RF energy harvesting, aiming to transmit as much information as possible under the constraints of providing sufficient RF energy for the receiving device to operate. Experiments that will enable our insights into this problem include comparing communication waveform designs, comparing power emission via USRP, and the effect of environmental conditions like separation distance, presence of nearby in-band transmissions, and other factors. 

    • There are many high-impact situations where there is loss of telecommunication, for example natural disasters such as hurricanes and places where conventional telecommunication infrastructure is damaged such as in Ukraine, currently. In these cases, software definable, rapid deployable wireless communication systems are urgently needed. Our students will conduct high-impact research to solve crucial telecommunication problems, develop soft and entrepreneurial, and networking skills. We target external grants and industry support. We also prepare the students to use the analytical approach of an engineer, be able to integrate software, hardware and communication systems, and network infrastructures, and develop proof-of-concept projects related to future telecommunications.

      The students will develop essential articulation skills as we plan to present the work in seminars and other undergraduate symposiums. 

    • Specifically, using the proposed test framework described above together with the related tutorials, the participant will be tasked with:

      • Understand the basics of modern communications using the provided tutorials and simulations
      • Develop basic programming and testing of communications using the Matlab framework
      • Perform test simulations using the 5G toolbox in Matlab to learn and utilize the various aspects of the toolbox
      • Familiarize with and utilize GNU Radio tools
      • Generate a variety of 5G NR frames using the testbed (data generation in Matlab followed by transmission via GNU Radio
      • Manipulate the test parameters, including system bandwidth, waveform power, system gain, modulation, and subcarrier specifications. Analyze the results
      • Compare the testbed performance to simulation results
      • Measure the energy harvested via signal transmission
      • Innovate and Implement strategies to improve energy harvesting while maintaining transmission rates
    • Hybrid

    • Dr.Sumit Chakravarty, schakra2@kennesaw.edu

    • Radiation sensors and detectors are indispensable in various important fields including medical imaging and healthcare, cancer diagnosis, environmental monitoring, nuclear safety, high energy astronomy, homeland security, and space exploration. Radiation sensors are devices that are engineered to detect high energy radiation such as alpha particles, cosmic rays, X-rays, gamma rays etc. Such radiations are emitted by radioactive atoms present in the environment around us and are abundant in outer space which come from the stars and distant galaxies.

      In this project, we aim to fabricate a radiation detection device using a solid-state semiconductor with electronic readout circuits integrated into a small portable packaging. By the end of the project, we will demonstrate a working device capable of detecting gamma-rays. A modified version of the device will also enable detection of cosmic rays entering the earth from the outer space. The ultimate goal is to develop a highly compact off-the-shelf prototype that is less than one pound in weight and can operate for prolonged period of time at higher temperatures without any degradation in resolution. By integrating solar cells on the device packaging our portable detector will be self-sustainable for lifelong outdoor operation or space missions. This innovation can reduce the payload for space exploration missions and enable low-cost sustainable environmental monitoring for nuclear safety, such as at underground mines, or nuclear power plants, their waste disposal sites or the nearby river streams.

      The first-year research scholars will gain invaluable knowledge and experience on radiation detection techniques, receive hands-on training in electrical measurements and testing of detectors, learn to build electronic circuits, analog and digital signal processing, computer programming, and develop important and useful engineering research skills through this project. We are looking forward to forming a multidisciplinary team with students from various Engineering and Physics majors to work on this project.

      • Conduct literature survey and learn the working principle of radiation detectors
      • Develop hands-on skills for electrical testing and measurements of radiation detectors
      • Design, simulate, and fabricate electronic circuits
      • Operate laboratory instruments to perform electrical tests and measurements
      • Work in a multidisciplinary team environment with other undergraduate/graduate engineering and science students to develop teamwork skills
      • Learn computer aided design to create 3D models
      • Use 3D printing, laser cutting, machining and milling techniques to fabricate the device parts and assemble the complete device
      • Perform programming for signal processing and data acquisition
      • Develop professional communication and presentation skills
      • Develop scientific or technical writing skills
      • Conduct literature study and learn about radiation detection techniques
      • Design, simulate and test electronic circuits
      • Design and build device enclosure and experimental setup
      • Collect measurement data from lab instruments
      • Perform data analysis and plot graphs
      • Coordinate with other group members and solve engineering problems in a team
      • Meet with the PI every week and update the research progress in group meetings
      • Prepare presentations and write reports
    • Hybrid

    • Dr. Sandip Das, sdas2@kennesaw.edu

    • Visual processing tasks such as detection, tracking, and localization are essential to the automation of unmanned aerial vehicles (UAV), robots, surveillance, and defense systems.  However, these intelligent tasks become challenging in high-speed motion and limited computing resources, and low power supplies. This research will explore a brain-inspired framework to process the visual information from two complementary visual sensors, event-based cameras, and frame-based standard cameras, in a sensor-fusion style. The specific objective is to address the challenge of high-speed and energy-efficient visual processing with end-to-end closed-loop control for UAVs and drones. 

      Event cameras are a novel class of visual sensors that generate asynchronous events when the illumination of pixels changes in the field. Compared to standard cameras, DVS holds advantages in low latency (high temporal resolution, 10μs vs 3ms), high dynamic range (140dB vs 60dB) and low power consumption (10mW vs 3W). Thus, it is specialized to capture high-speed motion, which blurs a frame-based camera.

      In the proposed project, our first-year scholar will collaborate with other members of our research lab, build an autonomous drone and configure vision sensors and computing platforms. More importantly, the scholar will explore the computer vision models and related brain-inspired computing algorithms that can smoothly operate on an edge computing device. Students will learn computer vision and machine learning basics and software-hardware co-design to facilitate such a process. 

      The proposed research will benefit numerous applications in robotics, surveillance, and IoT security. This work will also explore novel hybrid neural networks, thus contributing to the quest to general AI and enhancing the interdisciplinary collaboration between computer science and neuroscience.

      • Gain essential knowledge and skills in AI, machine learning, and embedded systems
      • Learn skills related to the assembly and configuration of drones
      • Understand the event camera and be able to design related algorithms
      • Explore the algorithm design under the hardware constraints and tradeoffs
      • Collaborate with undergraduate and graduate students in other teams 
      • Gain research skills systematically and understand the research process
      • Acquire abilities in academic writing, presentation, and communication
      • Improve skills in solving practical engineering problems
      • Weekly meeting and report the progress
      • Discuss the project with the advisor and collaborators
      • Study algorithms and explore the implementation on hardware
      • Evaluate the system performance
      • Accomplish a final report and complete a research paper
      • Participate in drafting external grant proposals
    • Hybrid

    • Dr. Yan Fang, yfang9@kennesaw.edu

    • Background

      The research on next-generation energy storage devices become a very important topic due to the increasing demand for high performance and reliable energy storage systems (e.g. Li-ion battery) in the fields of electric vehicles, biocompatible medical devices, and consumer electronics. Lots of efforts are being made in the fields of developing innovative materials and improving device fabrication methods so that the device performance can be significantly improved. One of the biggest challenges is to quickly test the device performance to evaluate the changes being made to the design. However, current battery testing method can take up to months to finish, which significantly slows down the development. It is therefore urgent and necessary to improve the current battery testing methodology to meet the needs of fast development in the market of electric vehicle. 

      Method and Objective 

      The project proposed a way to enable quick testing through data-driven machine learning prediction and experimental validation. Firstly, large amount of data will be collected to build the machine learning model through some basic data science skills. Secondly, physical model will be introduced to improve the accuracy of the model. Finally, the model predicted results will be validated by experimental data, which in turn will also be used to improve the model. 

      The goal of the first-phase of the model is to improve prediction accuracy to >95%. During the second-phase of model development, the goal is to reduce testing time to < 24 hours. During the third-phase of model development, the goal is to improve prediction accuracy to >99% and to reduce testing time to < 12 hours.

    • I expect the students to learn and develop the followings skills-based outcomes and techniques: 

      • Develop scientific research method and strict research attitude
      • Be able to find research resources through reading research papers
      • Familiar with testing and data collection, especially for Li-ion batteries
      • Familiar with data cleaning and data processing 
      • Familiar with curve fitting using linear and nonlinear regression 
      • Basic understanding of physical models and mechanisms related to Li-ion battery failure
      • Basic knowledge and usage of machine learning algorithms to predict the desired performance of Li-ion battery
      • Basic knowledge of testing method development to validate machine learning predictions
      • Patents and publications are expected to be the outcome of this project. There is chance to present this work in professional conferences

    • I expect students to work 5-10 hrs per week. I expect to meet with students 1-2 times each week for mentoring and discussion.  Here is the type of activities that students will engage in each week:

      • Monitor battery testing and collect battery testing data
      • Data processing, data cleaning, and data fitting using basic data science techniques
      • Exploration of physics models for the data 
      • Exploration of machine learning algorithms for data prediction 
      • Validation of predicted data by experimental testing 
    • Hybrid

    • Dr. Beibei Jiang, bjiang1@kennesaw.edu

    • The project goal is to develop a light-based wearable sensor that can non-invasively and continuously assess the muscle health in older adults.  Sarcopenia, the age-related reduction in muscle function and loss is present up to 20% of adults over 65 years. It significantly reduces mobility, which is essential for a good quality of life, and increases the risk of fractures and fall in older people. In daily activities, the energy for skeletal muscle function mostly comes from oxidative metabolism. Adequate oxygen delivery to muscles is critical to meeting the metabolic demand during daily activities and exercise. Thus, continuous measurement of the oxygen level in muscles provides an important information on muscle health and function. 

      The proposed wearable sensor utilizes an optical technique called near-infrared spectroscopy to measure the changes of muscle oxygenation. The near-infrared light can penetrate deep (~1cm) into a skin so that it can collect data on oxy- and deoxy-hemoglobin concentrations in muscle tissues. The wearable sensor will consist of miniaturized LEDs and photodetectors, analog circuits and microcontroller, and Bluetooth module for wireless communication. The compact form factor of the sensor will allow for attachment on forearm muscle or thigh for data collection during activity. 

      In this project, undergraduate students will assist with design/build/verification of light-based medical devices. If the prototype is successfully built, validation test will be performed during human.   Then, students can indirectly experience the entire cycle of medical device development. Also, “Biomedical optics” is an emerging field that studies the basic principles of interaction between light and biological tissues. Light as a medium for tissue sensing has a huge potential of clinical translation or wearable health monitoring like Apple Watch.

      • Gain essential knowledge on biomedical optics 
      • Understand a principle of light-based sensors (Like Apple Watch) 
      • Learn an electronic system to operate light sources and detectors
      • Apply 3D printing to build a custom enclosure for wearable sensor 
      • Perform optical spectroscopic sensing and data analysis 
      • Implement Bluetooth module 
      • Enhance professional communication skills
      • Literature study in biomedical optics 
      • Prototype development (assist with circuit and PCB design) 
      • Perform the device tests and experimental data analysis 
      • Present research progress in a weekly lab group meeting
      • Prepare presentations for conferences
    • Hybrid

    • Dr. Paul Lee, slee274@kennesaw.edu

    • Solar power has the potential to provide free energy in a clean and sustainable manner. One difficulty of extracting solar power occurs during shading caused by adjacent objects, clouds...etc. The project will develop a new technology for mitigating the negative impact of shading on solar power generation to increase the generated power.

      The technology relies on a camera for collecting images for a solar system which are utilized through image processing to extract important information for optimal operation of the solar system. The research outcome conducted in this program will be used for validating the technology and support its commercialization.

      • Define terminologies associated with solar energy research and theory in the power engineering field
      • Describe past research studies in the area of partially shaded PV systems
      • Articulate the contributions in the conducted research
      • Synthesize and critically analyze past research in their field of study and identify the literature gap
      • Collect data for training a neural network mode
      • Analyze, synthesize, organize, and interpret the experimental data
      • Write one or two research papers
      • Present their research/creative activity to an audience in a conference
      • Understand the value of scientific research and the value of science and investigation
      • Articulate the ways in which their research participation helps prepare them for graduate school and/or a career
      • Describe appropriate professional conduct and build proper communication skills
      • Research the operation and components of solar PV systems
      • Research partial shading in PV systems and contemporary industrial standards of operation and protection
      • Model and simulate electrical systems using computer software’s such as MATLAB/Simulink
      • Write high quality weekly reports
      • Conduct experiments and collect data
      • Test experimental prototypes
      • Use library to search for existing research relevant to their research
    • Hybrid

    • Dr. Yousef Mahmoud, ymahmoud@kennesaw.edu

    • This project aims to use the following Research and Development Tools within the KSU-Army Research Office Visualization & Simulation Research Center- (1) 14-Channel EMOTIV EPOC X Sensor Systems; (2) Real & Virtual Visualization & Simulation Environment and Tools; (3) Immersion & 3D Content Development Tools (zSpace); 3D GOVIS; 3D Oculus and other VR Goggles, to achieve and study Brain augmentation for the reinforcement of learning engineering concepts and enhance attention. Creating environments that can calculate how much reward will adequately motivate an operand is of great interest in engineering, and in this research exercise, 3D Immersive Environments, EEG sensing, monitoring, and processing Tools will be developed and used.

      The relationships with Marietta Schools and Development assistance from Texas Instruments TI, for the Robotic System Learning Kit (TI-RSLK) and our EEG research Lab on Brain Augmented Technology studies, will help to foster and further develop the pathways for STEM-PASS Program between the Electrical & Computer Engineering Department Students & Faculty, and the Marietta Schools' Teachers and students (especially Females & Minority students). This effort will also provide a foundation for responses to RFPs from Agencies such as the National Science Foundation NSF and the Army research Office in the foreseeable future.

      • Learn and understand Electrical Engineering concepts such as Voltage, Current, Power & Energy
      • Learn about and understand Component Design, Assembly and Testing
      • Learn and understand Micro-Controller interfaces with Sensors, Actuators & Motors
      • Learn and understand EEG Sensing and Artifacts identification and removal strategies
      • Learn and use zSpace/Scaniverse Tools to create 3D Lesson Plans.
      • Get in Group discussions about how to be a good Team Player
      • Review the Literature on EEG Applications and Robotics System Engineering & Technology
      • Assemble and operate a TI-RSLK
      • Guided CODE Development exercises
      • Implement and utilize SCANIVERSE Tools
      • Data study and Analysis
      • Create Presentations on the Study
      • Write Reports on the Study
      • Participate in regular Group Meetings to build rapport and relationships
      • Publish to present at STEM Conferences
    • Face-to-Face

    • Dr. Cyril Okhio, cokhio@kennesaw.edu

    • Rehabilitation is the most effective procedure for the stroke patients to regain their physical skills and improve activities of daily living. Recovering upper limb function after stroke requires intensive rehabilitation under the guidance of physical therapists: a costly and protracted process. Rehabilitation protocols that can be performed using robotic systems remotely at home with minimal assistance would decrease the cost of rehabilitation while reducing recovery time. Exoskeleton based robotic-assisted rehabilitation devices that can deliver high intensity, high-frequency training have been recently introduced. Such systems can be used independently without supervision of physical therapist, utilizes actuators and kinematic sensors to improve voluntary wrist movement of the stroke survivor while interacting with a goal-oriented interface (virtual environment). Although it has been clinically shown to improve functional abilities, motivation, and commitment to the rehabilitation programs, it requires users to have some degree of voluntary movement on their upper limb. This limits severely impaired stroke survivors who have very limited or even no motion on their limbs to benefit from these robotic-assisted systems. Fortunately, many of these users have trace neuromotor activity in their limbs that could provide useful signals to derive control mechanisms to actively engage in rehabilitation activities in the virtual environment. This neural or muscle activity which can be recorded in the form of electromyographic and ultrasound signals using relevant sensors provide important information to infer user’s movement intent. Therefore, these signals could be used to control an exoskeleton or could directly control a virtual environment.

      In this ongoing research, we aim to use abovementioned biomedical sensors to develop a model which can augment rehabilitation assistance capabilities of robotic systems by providing continuous motion intent recognition of the wrist. Students will be working on the development of experimental data collection as well as integration of the control mechanism into available robotic rehabilitation device.

    • This project is conducted with an industry partner which would generate the below outcomes for the first-year scholars:

      • Learn how to use biomedical sensors to interface with hardware
      • Develop and conduct appropriate experimentation, analyze and interpret data
      • Exposed to neural network based classification methods
      • Experience in a biomedical research field
      • Interact with the industry partner which would help career development 
      • Participate in group/individual weekly meetings
      • Literature review in the field
      • Experimental Data collection setup development
      • Progress Report
      • Conduct real model validation tests
    • Hybrid

    • Dr. Coskun Tekes, ctekes@kennesaw.edu

    • Global aviation is suffering pilot shortage, and by 2032, it is expected that international aviation will be 80,000 pilots short. Hence, there is an immediate need to identify ways to expedite pilot training. Researchers have found that gaming positively impacts cognition and hand coordination. Specifically, the abilities of people with expertise levels in video gaming have significantly affected performance scores in many flight simulators. However, these studies lack generalization due to the small sample size.

      This study investigates whether prior gaming experience impacts the flight performance of novice pilots using a large sample size, flight simulator, and eye-tracking metrics. We will gather data on two student groups for this study: students with little or no prior experience with gaming and with significant gaming experience. Both groups will receive initial training on basic operations and controls of an aircraft using KSU’s FAA approved flight simulator. After the initial training, students will be asked to fly a straight and level mission (maintaining a consistent altitude, heading, and attitude). During this task, participants will wear eye-tracking glasses to record what controls their eyes were attending to. They will also be graded based on a rubric.

      Student researchers will take part in data collection and get hands on experience with participants and data acquisition in addition to basic research skills. This project is the first of its kind at KSU to use gaze tracking device and a flight simulator, so the results from this research will not only determine whether there are statistically significant differences in how the two groups learn to fly the aircraft, but also set a precedent for gaze tracking in aviation research at KSU.  

      • Describe ethical research practices and apply those practices to a research study
      • Complete Citi training and become IRB certified
      • Collect data for a research study
      • Analyze, synthesize, organize, and interpret data from their research study
      • Use the eye tracking device and flight simulator
      • Use the iMotions software
      • Use Minitab software
      • Work effectively as part of a team
      • Contribute to a research paper
      • Present their research/creative activity to an audience (e.g., poster, oral presentation, performance, display)

    • Student weekly activities will vary from week to week but will involve the following activities:

      • Conduct literature review
      • Get Citi certified (IRB)
      • Recruit participants
      • Setup the experiment and run it
      • Analyze data
      • Use the eye tracking device and flight simulator
      • Attend research meetings
      • Contribute to discussions
    • Students are required to work 90% face-to-face and 10 % online. 

    • Dr. Awatef Ergai, aergai@kennesaw.edu  

    • Models and theories have been adopted to explain key attributes in the donation process. Potential intention to give blood has been modeled using the social cognition model, Theory of Planned Behavior (TPB). However, there remains a critical gap in the knowledge base of designing a successful blood donation campaign around the Voice of the Donor while employing optimization techniques, as is proposed in our research, particularly with respect to targeting a sustainable younger (ages 18-39), diverse donor base. This limitation has severely hampered ongoing efforts to increase the level of blood supply products among the younger generation of donors. The proposed research is expected to contribute a marked improvement of sustainable blood donors in the 18-39 age group at a core regional blood donation center. This contribution is significant because this framework will expand the original TPB model and include the Voice of the Donor via surveys and resource optimization techniques to serve as a successful recruiting model targeting the next generation of sustainable blood donors in a younger 18-39 age group nationwide.

      • Read current published literature in this field 
      • Increase analytical skills by examining qualitative survey data
      • Develop tables and charts using software such as Excel or Minitab
      • Enhance ability to interpret and explain results
      • Contribute to writing a journal paper
      • Present their research activity at the Symposium of Student Scho
      • Comprehend common themes in the current published literature
      • Increase analytical skills by examining qualitative survey data
      • Develop tables and charts using software such as Excel or Minitab
      • Enhance ability to interpret and explain results
      • Meet weekly with Dr. Keyser
      • Contribute to writing a journal paper 
    • Hybrid

    • Dr. Robert Keyser, rkeyser@kennesaw.edu

    • The aging baby boomer blood donor base, coupled with decreases from younger age groups, is an ongoing public health concern and impacts all people in need of blood transfusions regardless of gender, age, racial, or ethnic background. There is an urgent need to expand the blood donor pool to include more younger generations, first-time donors, and minorities. This project supports a larger study effort of recruiting and retaining young blood donors. Collaborating with Medic Regional Blood Center, our focus for this project is to design and prototype a mobile app that helps recruit new blood donors and retain existing donors.  We plan to conduct surveys to collect data on blood donors’ perceptions of mobile apps and identify factors/features that help improve the blood donation experience.

    • The student will:

      • Describe past research studies in their field of study 
      • Evaluate research studies they see in the media or encounter in literature 
      • Write papers and research reports 
      • Develop problem-solving skills
      • Present their research activity to an audience
      • Find papers related to the problem
      • Summarize papers
      • Find gaps in the research
      • Discuss research directions with Dr. Li
      • Meet weekly with Dr. Li
      • Write a research paper 
    • Hybrid

    • Dr. Lin Li, lli19@kennesaw.edu

    • Mental workload has become a topic of increasing importance since the introduction of technology in modern working environments. Mental workload in ergonomics is a multidimensional construct involving the characteristics of the task, operator, and the environment where the task is performed. 

      The assessment of mental workload is an important component in the design of occupational tasks because inappropriate levels can cause errors and incidents, delayed information processing, affect performance, and be responsible for occupational diseases and musculoskeletal disorders. The challenge nowadays is to find ways of measuring workload with the operators at the center of their dynamic operating environments. The NASA Task Load Index (NASA-TLX) is considered the most robust tool available for reporting mental workload perceptions and overall workload perceptions. It is questionnaire designed to obtain a subjective measure of mental workload on six dimensions: mental demand, physical demand, temporal demand, performance, effort, and frustration. The Surgical Task Load Index (SURG-TLX) is one of the most recent tools developed to measure mental workload in surgery settings. It was derived from the NASA-TLX and has been validated across various workloads in surgery and healthcare occupations. SURG-TLX measures responses across six dimensions of mental workload: mental demands, physical demands, temporal demands, task complexity, situational stress, and distractions. 

      The objective of this project is to compare the performance of both tools, the researcher is interested in discovering the similarities and differences with respect to the total score as well as explore if dimensions from one tool correlate to the dimensions of the other and vice versa. The need for this analysis is the possibility of using SURG-TLX in place of NASA-TLX in future studies, as SURG-TLX incorporates task complexity, situational stress, and distractions dimensions. 

      Students will conduct a literature review searching in different journal data bases identifying research in which similar comparisons between mental workload measurement tools have been conducted, pros/cons of the use of both questionnaires, mental workload measure accuracy, and general performance of both tools. Students will also conduct statistical analysis to investigate and explored linear relationships and correlations between the dimensions of NASA-TLX with respect to the total score of SURG-TLX and vice versa, and to determine possible associations between the dimensions.

    • Students will learn in a structured and systematic manner how to conduct a literature review (searching, reading, classifying, summarizing) as the first step to identifying research gaps or discovering research needs, and getting the necessary literature validation to support a research project or research idea. The outcome will be a spreadsheet that contains the information that was collected and processed during the literature review process. Likewise, the student will prepare the initial draft of the introduction/literature review section of a journal paper. 

      Students will conduct and present correlation and linear regression statistical analysis to identify the similarities and/or differences between the tools been compared. The student will prepare an initial draft of the results section of a journal paper.

      • Searching journal articles, conference articles, books related with the topic
      • Reading the articles/books
      • Identifying if the articles meet the criteria to be part of the study
      • Summarizing (incorporating the articles into the spreadsheet)
      • Writing the introduction/literature review section
      • Running and interpreting statistical analysis
      • Identifying similarities, differences, relationships between the tools
      • Preparing visual representations of the data (graphs, images)
      • Writing the result section of a journal paper
    • Hybrid

    • Dr. Luisa Valentina Nino de Valladares, lvallad1@kennesaw.edu

    • There is an immense need to develop high performing energy storage systems to meet the ever-increasing energy demand and to reduce harmful emissions generated from fossil fuels. We seek to develop a robust nanocomposite material as a next generation electrode for application in electrochemical ultracapacitor devices. A combination of atomically thick carbon nanomaterial and conducting polymer will be used for synthesizing electrode films. Electrochemical and morphology characterization will be conducted to analyze the electrode material to establish its performance.

      The First-Year Scholar will conduct basic research toward development, fabrication, and testing of energy storage devices under various electrolyte system. A detailed literature survey will be conducted to identify processes and materials. The student will document the state-of-the-art electrode materials and potential research gaps will be identified. Investigate possible reaction mechanisms established at the electrode/electrolyte interface. A detailed experimental procedure will be developed and discussed. The First-Year Scholar will learn various aspects of nanomaterials, processing techniques, and will learn the state-of-the-art methods to test these devices. Student will be involved in writing reports and publishing manuscripts.

      • Exposure to nanotechnology based energy storage technology
      • Conduct hands-on experimental research, generating results and performing data analysis for making meaningful conclusions
      • Learn the cutting-edge characterization techniques used in materials science
      • Engage in writing research articles and conference proceedings

    • The student will participate in weekly meetings with the research group to discuss the progress and plan for future experimental work. The student will conduct hand-on experiments in lab and analyze the generated data.

    • Face-to-Face
    • Dr. Ashish Aphale, aaphale@kennesaw.edu

    • Solar power has emerged as a potential sustainable and renewable energy source. The most widely used solar panels use solar cells made of silicon. The silicon cells absorb the energy from the sunlight and directly convert the light energy into electricity. However, silicon solar cells are prone to develop defects and undergo degradation after deployment in the field. Panels in the field often experience degradation due to various factors, such as UV radiation, electrical fault induced degradation, impacts during hailstorms, high wind gust induced stress etc. As a result, if persistent and considerable amounts of defects are introduced in a solar panel, then the power output would reduce significantly. More concerning is that some degraded cells may lead to hotspot generation which, if not isolated timely, can cause catastrophic failures and develop risks of fire hazard. Therefore, monitoring and assessment of solar panels’ health is a dire necessity in the industry. However, this is not an easy task for a large solar power plant. Inspecting a large number of solar panels manually and regularly is impossible. More challenging is that some defects cannot be detected by regular photographs. In addition, analysis of thousands of images would take significant manpower and is not cost efficient.

      In this project, our goal is to develop a proof-of-concept low-cost infrared imaging system for autonomous inspection and monitoring of solar cell and solar panels’ health. We plan to accomplish it by developing a novel low-cost imaging system capable of taking infrared and thermal images of test solar cells in the laboratory. Then by developing a computer program to automatically analyze the infrared images and comparing images with electrical parameters, we will create a robust method to assess the solar cell/panel health without any human intervention. Our innovations will potentially reduce the time and cost of inspection, and improve the maintenance efficiency, thereby making solar power more affordable and reliable. The first-year scholars will perform various research tasks toward the development of the Autonomous Infrared Imaging System including design of the test setup, system assembly, data acquisition, thermal and electrical tests, and basic computer programming using python. The student team will also be involved in writing reports and publishing manuscripts.

      • Students will gain knowledge on solar cells and solar panels.
      • Students will learn about infrared imaging techniques.
      • Students will learn how to design a laboratory experiment
      • Students will learn the methods to automate an experiment or a process
      • Students will learn how to apply basic computer programming for image analysis
      • Students will learn how to perform basic tests to assess a solar cell performance
      • Students will develop scientific writing, presentation, and communication skills
      • Perform literature study and document important information.
      • Design experiments and construct an imaging system using infrared cameras.
      • Meet with the research mentors in a weekly basis
      • Perform data collection and data analysis.
      • Identify challenges and brainstorm to come up with potential solutions
      • The students will be expected to be able to work independently, as well as in a team to solve engineering problems while conducting the project
    • Hybrid
    • Dr. Sathish Gurupatham, sgurupat@kennesaw.edu

    • Hexapod robots have been highlighted in the last few decades because of their stable locomotion in complex and uneven terrain. Multiple legs are controlled with a degree of insect autonomy so that the robot can move in an uneven and complex environment to complete a planned task. A Hexapod robot has advanced features such as accessibility and stability in an extraterrestrial environment.

      Biomimicry is one of the most innovative methods to create a solution by mimicking the phenomena in nature. Insects can flexibly alter their gaiting pattern to adapt to various locomotor conditions. Various six-legged insects such as an ant and cockroach have been used as a model for biomimetic robots because legged animals can easily outperform the robots over rough ground.  

      In this project, we plan to develop a hexapod robot, which creates biomimetic locomotions from gaiting patterns found in a fire ant. To achieve this goal, we formulate the following research objectives: (1) design and fabricate a hexapod robot using 24 degrees of freedom based on an insect, (2) study a gaiting pattern by characterizing locomotions in a fire ant, and (3) develop a control method of a hexapod robot based on the characterized locomotion. The recent development in our lab demonstrated the omnidirectional locomotion tracking system for a walking insect in real time. We will utilize this system to observe the ant's walking behavior, and design various gait patterns (e.g., tripod, tetrapod gait pattern)based on observation. The machine learning-based image processing algorithm (deepLabCut) will be utilized for analyzing a gait pattern. Eventually, we will test the biomimetic locomotion for the developed hexapod robot in various ground conditions. 

      In the future, this work will be extended to study an adapted gait pattern for a damaged hexapod robot because a robot cannot be fully operating when one or more legs are not fully functional during the operations such as rescue and search operations, disaster responses, and human-inaccessible environments such as distant planets.

      • Describe biomimetic motion in engineering
      • Describe past research studies of biomimetics from literatures.
      • Analyze, synthesize, organize, and interpret data using the computing program platform (MATLAB)
      • Write a research paper/article based on the analysis from the study.
      • Present their research/creative activity to an audience (e.g., poster, oral presentation, performance, display)
      • Reflect on their research project, including strengths, weaknesses, and things they would do differently in another research context

      Students will also promote improvements in the following areas: time management, self-confidence/self-esteem, independent thinking, problem-solving, and organizational skills.

      • Literature survey and review of research articles
      • Fabricate and test a robot and compare it with simulation
      • Measure/Analyze the motion of an animal
      • Learn Multiphysics program and simulate a motion
      • Conduct experiment and analysis data
      • Write reports and present the experimental results
      • Participate in a weekly group/individual meeting 
    • Face-to-Face
    • Dr. Dal Hyung Kim, dkim97@kennesaw.edu

    • Traditionally, electric motors and hydraulic or pneumatic actuators have been used for robotic and wearable devices. However, these actuators and motors are heavy, rigid, and noisy. They cannot provide high specific power comparable to that of human muscles because of their heavy and bulky components. Next-generation robotic or wearable devices require advanced actuators with high flexibility, large stroke, and low weight that natural muscles have. In this regard, artificial muscles have been drawing attention from researchers for futuristic robotic and wearable devices. Recently, a new artificial muscle called twisted and coiled actuator (TCA) was developed using fishing lines or sewing threads. TCAs are fabricated by the extreme twist-insertion process of polymer fibers and activated by changing the actuator temperature. Under contraction, the TCA generates a specific power of 5.3 kW/kg, which is 100 times higher than that of human muscles. TCAs have several advantages, including a large amount of deformation, high flexibility, low weight, quiet operation, and low cost. However, their dynamic performance is greatly affected by heat transfer during the heating and cooling processes because TCAs are operated by repeatedly heating and cooling the polymer fibers. Therefore, practical applications of TCAs require the development of TCAs with a better thermal response for rapid heating and cooling. In the present research project, we utilize carbon nanomaterials such as graphene and carbon nanotubes (CNTs) to improve the dynamic response of TCAs. Scientists repeatedly reported the excellent thermal transport properties of graphene and CNTs. The excellent thermal conductivities of carbon nanomaterials will reduce the thermal contact resistance between fibers in TCAs, increasing the heat dissipation from TCAs during cooling. In addition, their low specific heat capacities and high thermal diffusivity will enable even faster cooling in TCAs. This faster cooling will improve the dynamic response of TCAs significantly.

    • Students will be asked to work together to fabricate artificial muscles by coiling fish lines. They will be asked to learn how to measure the dynamic response of the developed artificial muscles using different equipment such as lock-in amplifier. They will be asked to measure thermal and mechanical properties of the developed artificial muscles. In addition, they will write a scientific report such as conference papers and journal papers. The students will also be asked to disseminate their research findings in academic conferences.

    • Students will be asked to attend weekly research meetings. Although the selected students will work independently, they will be asked to work with other undergraduate researchers in the lab. The students will have a chance to receive feedback from the faculty mentor and fellow undergraduate researchers frequently.

    • Face-to-Face
    • Dr. Jungkyu Park, jpark186@kennesaw.edu
    • I am establishing my new research team (Dynamics and Control Group) starting in August 2022. We have two main research topics:

      Design and Development of Compliant Mechanisms and Soft Robots

      • Design and Development of Compliant (Flexible) Mechanisms
      • Design and Development of Soft Robots (Funded by NIH, $364,000, 2022-2025, Tekes is the co-PI)
      • MATLAB Simscape Modeling of Compliant Mechanisms and Soft Robot

      Educational Research:

      • Design and development of 3D-Printed Lab Equipment (Funded by NSF, $297,000, 2020-2023, 
        Tekes is the PI)
      • Development of MMATLAB Simscape App for Engineering Courses (Funded by Mathworks, 
        $24,390, 2021-2022, Tekes is the PI)

    • We are aiming to facilitate quality research by promoting and attracting more undergraduate researchers to our Dynamics and Control Research Group. 

      Through research, students will be able to:

      • Experience in the research field by identifying the design specifications and the objectives to be achieved
      • Increase multidisciplinary knowledge (collaborative research between mechanical engineering, electrical engineering and computer engineering)
      • Articulate a clear research question and formulate a hypothesis
      • Compare and evaluate alternative designs
      • Use library to search for existing research relevant to their research
      • Develop the final solution
      • Work collaboratively as a team
      • Work timely in an effective manner following the meeting dates and deadlines
      • Communicate confidently and constructively with their group members and mentors
      • Present their findings to other researchers in the same field and broader audience

    • Students are expected to attend biweekly meets and be present at the weekly face-to-face meetings and depending on the team’s availability, we will also schedule weekly meetings through Teams. In addition to the biweekly meetings, student needs to work on the assigned project.

    • Face-to-Face
    • Dr.Ayse Tekes, atekes@kennesaw.edu

    • We will develop a master/slave system using a twin Stewart mechanism as a special joystick with 6 DOF. This design is advantageous because the robot’s motion would be very intuitive, and the surgeon can control the robot end-effector just by one hand. Consequently, as the surgeon moves or rotates the joystick in any given position or orientation the robot follows that accordingly.

      Design objectives: The joystick must have 6 DOF, be fully controlled with one hand, and be intuitive to use. Also, for convenience the workspace of the joystick must be a small volume within the range of surgeon’s hand motion.

      Design process: The overview of design process, and the components of the user interface system are demonstrated in Fig 3b, and Fig 11 respectively. A Stewart mechanism is chosen as a joystick since it has 6 DOF, and acks as a master system for the soft robot. The kinematics of the Stewart mechanism will be used to obtain its size based on the required workspace. Next, the structure of the mechanism can be 3D printed and assembled. Linear potentiometers will be mounted on each leg of the Stewart mechanism so that it can sense its displacement. This will translate the surgeon’s hand motion to its equivalent motion in the passive legs that must be mapped to required bending motions in the active links of the soft robot. This will be done through calibration and nonlinear mapping based on the bending profile of the soft robots’ legs. Finally, this data will be used as a desired input motion of the soft robot. 

      The position of the robot will be sensed by an EM tracker attached to the robot end-effector which will be mapped to the equivalent bending deformation of the robot legs through the kinematics model and feedback to the controller.

      • Performing literature review on research topics using google scholar
      • Design of robot parts using Solidworks
      • Understanding the Kinematics of robotic systems
      • 3D printing of robot parts
      • Writing research reports
      • Data acquisition using microcontroller
      • Programing a microcontroller to control electromotor
      • Design CAD models of the robot
      • 3D printing the required part
      • Assembling the robot parts
      • Writing weekly progress reports
      • Be a team player and work with the graduate students for the project success.

    • Face-to-Face

    • Dr. Amir Ali Amiri Moghadam, aamirimo@kennesaw.edu














 

 

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