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Advanced Education Program in General Dentistry graduates 2021-2022
No full textSchool composite: students included in composite: Jay Bhakta, Johnlason Nguyen, Megan Casserly, Seth Sherwood, Tommy Vu, Zachary Vogel.
Group photo: from left to right: Jay Bhakta, Johnlason Nguyen, Zachary Vogel, Megan Casserly, Tommy Vu, Seth Sherwood.Digitized by University Libraries' Technical Services Institutional Repository & Digitization group.Personal and non-profit use only. Contact [email protected] if you have any questions
Robust and scalable quantum repeaters using machine learning
No full textPoster project completed at College of Engineering, Department of Aerospace Engineering.
Presented at the Kansas Undergraduate Student Research Day at the Capitol, Topeka, KS, February 26, 2025.
Sponsored by Undergraduate Research and Creative Activity Hub, Dorothy and Bill Cohen Honors College.Quantum computers have shown their potential to revolutionize computing due to their exponentially faster speeds over current classical (non-quantum) digital computers. To evaluate if quantum repeaters can be trained to perform their task and remain resistant to noise and decoherence using machine learning. Using a simulation of a quantum machine in MATLAB, a system of 2-qubits is trained to sufficiently low error using machine learning. The system is then scaled up to 4-,6-, and 8-qubits using transfer learning of the previous system’s parameters, with no additional training. Once complete, noise and decoherence are added to the systems and tested to evaluate their resilience. Research is still in progress. Preliminary results show that the initial system of two qubits can be trained to very low errors, on the order of 10-7. Increasing system size to 4+ qubits led to only a very slight increase in error to a magnitude of 10-4, still less than 0.1%. Testing on a trained system demonstrated that the system could handle noise and decoherence up to a magnitude of 10-5 with no issue. Because of its flat geography and position, Kansas could become home to quantum networking and quantum satellite communications, making it a leader in groundbreaking quantum repeaters in quantum communication technology in the US and the world
Next Generation In-Situ Resource Utilization pilot excavator control room and facility design
No full textPublished in SOAR: Shocker Open Access Repository by Wichita State University Libraries Technical Services, November 2025. 2025 IEMS Officers: Gamal Weheba (Conference Chair); Hesham Mahgoub (Program Chair); Dalia Mahgoub (Technical Director); Ed Sawan (Publications Editor); Wilfredo Moscoso (Proceedings Editor); Abdulaziz G. Abdulaziz (Associate Editor)This study focused on identifying recommendations for designing the Next Generation In-Situ Resource Utilization (ISRU) Pilot Excavator (IPEx) control room and facility. This research highlights opportunities for incremental improvements across the control room's design, processes, and amenities, fostering a more efficient and supportive environment for the IPEx team. Participants consisted of IPEx control room operators who were recruited and interviewed; this resulted in 50 recommendations from the 33 open-ended questions asked of the eight participants. Spradley's domain analysis was used to code and analyze the open-ended question responses within 11 domains consisting of design considerations for IPEx displays, room layout, individual desk layout, lighting, shiftwork, shift changeover, control room employee interaction, control room environment, workload, rest area and breaks, and food area. Researchers employed an interview methodology. Spradley’s domain analysis was used to identify and further partition themes into sections called “Cover Terms.” These terms, or themes, were organized further into sub-themes called “Included Terms” for each of the 11 domains. The study implications and future research are also addressed
Forward Together: A monthly newsletter, March 2025
No full textWichita State offers opportunities for every stage of your journey -- (Forward Together podcast): Episode 31: Pierre Harter, research and industry on campus -- Episode 32: Justin Rorabaugh, Shocker Studios, digital arts -- Game-changing Shocker Fly Lab project kicks off with $1 million lead gift -- Shocker bowling wins conference championship in its first season in NCAA -- David Miller named senior vice president for Administration, Finance and Operations -- Wichita Biomedical Campus starts heading upward as construction continues -- (Shocker Nation scholarships): 2025 Rudd Scholars -- 2025 Wallace Scholars -- 2025 Jabara Scholars -- 2025 Barton Scholar -- Women's tennis rises in rankings after winning streak; men's basketball plays in postseason for first time since 2021 -- Wichita State pediatric physical therapy team receives grant to expand services in rural schools -- WSU’s 2024 annual report highlights key areas of interest and growth for the university -- WSU and Shocker Neighborhood host Open Streets ICT again in Apri
Spoofing and antispoofing
No full textClick on the DOI link to access this article at the publishers website (may not be free).[No abstract available
Wichita State Research and Innovation News, February 2025
No full textNIAR develops novel overmolded thermoplastic production process for EVTOL applications -- (Research and innovation on display from Wichita State University's faculty ): Dr. Jens Kreinath preserves Turkey's cultural memory following earthquakes -- Dr. Darren DeFrain receives 2.5 million to support Wichita Biomedical Campus, nursing scholarships -- WSU faculty profile: Dr. Moriah Beck empowers students while advancing cardiac and cancer research -- Hear from WSU physicist on President Muma's Forward Together podcast -- WSU College of Engineering partners with Groover Labs to support regional innovation -- Wichita Biomedical Campus construction proceeds through inclement weather -- NIAR offers industry-focused training courses -- WSU in the news -- Research at Wichita State -- Innovation at Wichita Stat
Revealing hidden IoT devices through passive detection, fingerprinting, and localization
No full textInternet-of-things (IoT) devices (e.g., micro camera and microphone) are usually small form factor, low-cost, and low-power, which makes them easy to conceal and deploy in the indoor environment to spy on people for human private information such as location and indoor activities. As a result, these IoT devices introduce a great privacy and ethical threat. Therefore, it is important to reveal these concealed IoT devices in the indoor environment for human privacy protection.
This paper presents RFScan 1, a system that can passively detect, fingerprint, and localize diverse concealed IoT devices in the indoor environment by sensing their unintentional electromagnetic emanations. However, sensing these emanations is challenging due to the weak emanation strength and the interference from the ambient wireless communication signals. To this end, we boost the emanation strength through the non-coherent averaging based on the emanation signal’s characteristics and design a novel suppression algorithm to mitigate interference from the wireless communication signals. We further profile emanations across frequency and time that act as the emanation source’s unique signature and customize a deep neural network architecture to fingerprint the emanation sources. Furthermore, we can localize the emanation source with an angle-of-arrival (AoA) based triangulation approach. Our experimental results demonstrate the efficiency of the IoT devices’ detection, fingerprinting, and localization across different indoor environments
Design and synthesizing of hemoglobin-based multifunctional fibers for improved carbon monoxide absorption rates
No full textThis is an open access article under the CC BY license.This study is aimed at developing advanced materials for carbon monoxide (CO) capture by producing hemoglobin (Hb)-based electrospun multifunctional micro- and nanofibers blended with polyvinylpyrrolidone (PVP). Unlike conventional CO trapping materials such as activated carbon, ammoniacal cuprous chloride, zeolites, and metal-organic frameworks (MOFs), Hb/PVP fibers leverage the simplicity and scalability of electrospinning to produce continuous, defect-free flexible fibers with tunable micron- to nanoscale diameters. The process enables precise control over fiber morphology, surface area, porosity, and hydrophilicity, providing significant advantages for optimizing CO adsorption rates. Moreover, the inclusion of Hb introduces a biomimetic advantage through its intrinsic CO-binding affinity, offering higher specificity and interaction potential compared to traditional physical adsorption or chemical frameworks. Experimental results revealed that fibers with 8 wt.% PVP exhibited the smallest and most uniform diameters, while higher PVP concentrations (16, 32 wt.%) enhanced hydrophilicity, with complete water absorption occurring within 400 and 200 seconds, respectively. Structural and compositional analyses using confocal laser scanning microscopy (CLSM) and Fourier transform infrared spectroscopy (FTIR) confirmed the integrity and chemical characteristics of the fibers. Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) established their thermal stability, with critical transitions at approximately 80 ℃ (denaturation) and 200 ℃ (decomposition). Degradation was observed between 200 and 430 ℃, corresponding to significant weight loss. These findings demonstrate the potential of Hb/PVP fibers as exceptional alternatives for CO capture. This study may open new possibilities for increasing the absorption rate of highly porous fibers for toxic CO capture in the bloodstream and address other related concerns. © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2025
Soft robot workspace estimation via finite element analysis and machine learning
No full textThis is an open access article under the CC BY license.Soft robots with compliant bodies offer safe human–robot interaction as well as adaptability to unstructured dynamic environments. However, the nonlinear dynamics of a soft robot with infinite motion freedom pose various challenges to operation and control engineering. This research explores the motion of a pneumatic soft robot under diverse loading conditions by conducting finite element analysis (FEA) and using machine learning. The pneumatic soft robot consists of two parallel hyper-elastic tubular chambers that convert pneumatic pressure inputs into soft robot motion to mimic an elephant trunk and its motion. The body of each pneumatic chamber consists of a series of bellows to effectively facilitate the expansion, contraction, and bending of the body. The first chamber spans the entire length of the soft robot’s body, and the second chamber spans half of it. This unique asymmetric design enables the soft robot to bend and curl in various ways. Machine learning is used to establish a forward kinematic relationship between the pressure inputs and the motion responses of the soft robot using data from FEA. Accordingly, this research employs an artificial neural network that is trained on FEA data to estimate the reachable workspace of the soft robot for given pressure inputs. The trained neural network demonstrates promising estimation accuracy with an R-squared value of 0.99 and a root mean square error of 0.783. The workspaces of asymmetric double-chamber and single-chamber soft robots were compared, revealing that the double-chamber robot offers approximately 185 times more reachable workspace than the single-chamber soft robot. © 2025 by the authors