Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (21752)
- Civil and Environmental Engineering (7860)
- Physical Sciences and Mathematics (7284)
- Electrical and Computer Engineering (5149)
- Geotechnical Engineering (3713)
-
- Physics (2388)
- Chemical Engineering (2339)
- Materials Science and Engineering (2218)
- Mechanical Engineering (2216)
- Structural Engineering (2014)
- Computer Sciences (1926)
- Chemistry (1552)
- Mining Engineering (1180)
- Aerospace Engineering (1154)
- Civil Engineering (1047)
- Operations Research, Systems Engineering and Industrial Engineering (839)
- Social and Behavioral Sciences (773)
- Earth Sciences (770)
- Architecture (762)
- Metallurgy (740)
- Architectural Engineering (737)
- Biochemical and Biomolecular Engineering (689)
- Geology (671)
- Ceramic Materials (635)
- Mathematics (633)
- Petroleum Engineering (605)
- Statistics and Probability (535)
- Life Sciences (489)
- Biology (391)
- Geological Engineering (370)
- Keyword
-
- Electromagnetic Interference (108)
- Machine learning (99)
- Electromagnetic Compatibility (98)
- Neurocontrollers (91)
- Additive manufacturing (89)
-
- Optimal Control (89)
- Optimization (83)
- Rheology (74)
- Neural Nets (69)
- Neural Networks (68)
- Deep learning (67)
- Simulation (66)
- Computer Simulation (64)
- Mathematical Models (63)
- Machine Learning (62)
- Stability (61)
- Ionization (60)
- Printed Circuits (60)
- Printed Circuit Boards (59)
- Finite Difference Time-Domain Analysis (58)
- Power System Control (58)
- Additive Manufacturing (57)
- Modeling (54)
- Hydrogen (53)
- Nonlinear Control Systems (53)
- EMI (51)
- Microstructure (51)
- Adaptive Control (49)
- Control System Synthesis (49)
- Capacitors (47)
- Publication Year
- Publication
-
- Masters Theses (4167)
- Electrical and Computer Engineering Faculty Research & Creative Works (3526)
- The Missouri Miner Newspaper (3345)
- Doctoral Dissertations (2088)
- International Conference on Case Histories in Geotechnical Engineering (2057)
-
- Physics Faculty Research & Creative Works (1974)
- International Conferences on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics (1566)
- Mechanical and Aerospace Engineering Faculty Research & Creative Works (1295)
- Civil, Architectural and Environmental Engineering Faculty Research & Creative Works (1274)
- CCFSS Proceedings of International Specialty Conference on Cold-Formed Steel Structures (1971 - 2018) (1036)
- Materials Science and Engineering Faculty Research & Creative Works (1023)
- Chemistry Faculty Research & Creative Works (949)
- Computer Science Faculty Research & Creative Works (913)
- Chemical and Biochemical Engineering Faculty Research & Creative Works (853)
- Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works (525)
- Engineering Management and Systems Engineering Faculty Research & Creative Works (489)
- Mathematics and Statistics Faculty Research & Creative Works (473)
- UMR-MEC Conference on Energy / UMR-DNR Conference on Energy (442)
- Missouri S&T Magazine (429)
- Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images (374)
- Bachelors Theses (358)
- Professional Degree Theses (338)
- Mining Engineering Faculty Research & Creative Works (312)
- Undergraduate Research Conference at Missouri S&T (281)
- Biological Sciences Faculty Research & Creative Works (269)
- Opportunities for Undergraduate Research Experience Program (OURE) (255)
- American Iron and Steel Institute (AISI) Specifications, Standards, Manuals and Research Reports (1946 - present) (237)
- CCFSS Library (1939 - present) (234)
- Computer Science Technical Reports (197)
- Minutes & Agendas (159)
- Publication Type
- File Type
Articles 391 - 420 of 33636
Full-Text Articles in Entire DC Network
Supersonic Wind Tunnel Free Stream Turbulence Characterization Using 2-Point Focused Laser Differential Interferometry, Joseph Villarreal, Joshua Gary, Davide Vigano
Supersonic Wind Tunnel Free Stream Turbulence Characterization Using 2-Point Focused Laser Differential Interferometry, Joseph Villarreal, Joshua Gary, Davide Vigano
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Non-intrusive laser-based diagnostics, such as Two-Point Focused Laser Differential Interfer-ometry (2-FLDI), play a crucial role in modern aerodynamic research by enabling simultaneous measurements of density and velocity in compressible flows. A 2-FLDI system has been developed and implemented for the Missouri S&T Supersonic Wind Tunnel to characterize free stream turbulence fluctuations and free stream convective velocity. Design choices that enabled the 2-FLDI to overcome low turbulence to measure free stream velocity are detailed. The free stream velocity measurements are validated against previous particle image velocimetry data, showing good agreement. Analysis of normalized velocities and density-based turbulence intensities found that the …
2-Point Focused Laser Differential Interferometry Measurements Of A Parallel Jet In Supersonic Flow, Joshua Gary, Joseph Villarreal, Davide Vigano
2-Point Focused Laser Differential Interferometry Measurements Of A Parallel Jet In Supersonic Flow, Joshua Gary, Joseph Villarreal, Davide Vigano
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Turbulence in compressible flows plays a central role in applications such as air-fuel mixing in supersonic combustors and is significantly more complex than incompressible turbulence due to the presence of fluctuating thermodynamic quantities. As such, models like the Strong Reynolds Analogy (SRA) are used to relate these quantities. However, SRA validity has been examined primarily in boundary-layer flows. In this work, a newly developed Two-Point Focused Laser Differential Interferometry (2-FLDI) system is implemented in a two-dimensional parallel supersonic jet. The diagnostic is described in detail, including optical alignment procedures, calibration methods, and data analysis techniques. Measurements acquired at multiple streamwise …
Adaptive Machine Learning Framework For Microstructural Optimization And Mechanical Performance Prediction In Steels, Henry Adekola Haffner
Adaptive Machine Learning Framework For Microstructural Optimization And Mechanical Performance Prediction In Steels, Henry Adekola Haffner
Doctoral Dissertations
Evolution of microstructures, such as polygonal ferrite, acicular ferrite, bainite, and martensite, plays a pivotal role in determining the final microstructural and mechanical properties of steel products. Given the established inter-relationship between processing parameters, microstructure, properties, and performance, precise control of phase transformation is essential to achieve pre-determined properties. To understand transformation routes in different steel grades, time-temperature-transformation (TTT) and continuous-cooling-transformation (CCT) diagrams are necessary and can be described using the Johnson-Mehl-Avrami-Kolmogorov equation and Scheil’s additivity rule. This study presents a comprehensive computational framework for predicting and optimizing microstructure and mechanical properties in advanced high-strength steels (AHSS) using adaptive machine …
Trust-Aware Algorithms For Stackelberg Ground Vehicle Routing, Doris Evelyn Meredith Brown
Trust-Aware Algorithms For Stackelberg Ground Vehicle Routing, Doris Evelyn Meredith Brown
Doctoral Dissertations
Despite decades of research focused on reducing ground vehicle traffic congestion, urban traffic networks worldwide continue to experience traffic flows that lead to increased network travel times, largely resulting from the routing decisions of individual vehicles. To address this challenge, this work leverages a Stackelberg game framework to model the interaction between a vehicle agent and a routing authority as a leader–follower game, in which the routing authority proposes routing interventions to which the agent responds. This research contributes to existing traffic mitigation literature by exploring the role of trust in route decision-making and providing trust-aware algorithms that influence vehicle …
Volatile Organic Compound Analysis Of Humboldt Penguin (Spheniscus Humboldti) Preen Oil: A Pilot Study, Dante E. Rojas, Mitchell M. Mccartney, Eva Borras, Michael O. Eze, Abigail Pietrow, Jennifer J. Valvo, Cristina E. Davis
Volatile Organic Compound Analysis Of Humboldt Penguin (Spheniscus Humboldti) Preen Oil: A Pilot Study, Dante E. Rojas, Mitchell M. Mccartney, Eva Borras, Michael O. Eze, Abigail Pietrow, Jennifer J. Valvo, Cristina E. Davis
Chemistry Faculty Research & Creative Works
Avian olfaction has gained prominence in recent decades for its roles in social communication and behavior. In penguins, the chemical characterization of preen oil remains limited. In this exploratory study, we characterized the volatile organic compound (VOC) profile of preen oil from Humboldt Penguins (Spheniscus humboldti). Preen oil from 12 captive individuals was analyzed using headspace sorptive extraction (HSSE) coupled to gas chromatography–mass spectrometry (GC–MS). Chemometric analyses examined variation in VOC profiles by sex, age class, and breeding activity. We detected 54 compounds (20 tentatively identified), including linear alcohols, methyl ketones, carboxylic acids, saturated hydrocarbons, oxygenated and nitrogen-containing organics, prenolipids, …
Soft-Chemical Scalable One-Pot Aqueous-Medium Synthesis Of Na3(Vo)2(Po4)2f-Based Cathodes: Compositional Tuning And Electrochemical Performance In Na- And Li-Ion Batteries, Prashanth Sandineni, Subal Chandra Manna, Sutapa Bhattacharya, Santhoshkumar Sundaramoorthy, Ramesh Deokate, Milad Aghayi-Anaraki, George E. Sterbinsky, Kartik Ghosh, Amitava Choudhury
Soft-Chemical Scalable One-Pot Aqueous-Medium Synthesis Of Na3(Vo)2(Po4)2f-Based Cathodes: Compositional Tuning And Electrochemical Performance In Na- And Li-Ion Batteries, Prashanth Sandineni, Subal Chandra Manna, Sutapa Bhattacharya, Santhoshkumar Sundaramoorthy, Ramesh Deokate, Milad Aghayi-Anaraki, George E. Sterbinsky, Kartik Ghosh, Amitava Choudhury
Chemistry Faculty Research & Creative Works
One of the most important cathode materials for Na-ion batteries, Na3(VO)2(PO4)2F, and its compositional variants have been synthesized using four different and facile one-step soft chemical routes. The as-synthesized compounds, Na2.95(VO)2(PO4)2F (I), Na2.93(VO)2(PO4)2F (II), and Na2.58(VO)2(PO4)2F (IV), crystallize in the tetragonal crystal system in the P42/mnm space group, while Na3(VO)2(PO4)2F (III) crystallizes in the orthorhombic crystal system in …
Closing The Nitrogen Loop In Groundwater With Biohybrid Technologies, Linjie Zhou, Biao Li, Jianhua Guo, Shelley D. Minteer, Yifeng Zhang
Closing The Nitrogen Loop In Groundwater With Biohybrid Technologies, Linjie Zhou, Biao Li, Jianhua Guo, Shelley D. Minteer, Yifeng Zhang
Chemistry Faculty Research & Creative Works
Nitrate in groundwater should be treated as a nitrogen source rather than a contaminant. Biohybrid technologies coupling microbial selectivity with renewable electro(photo)chemical energy offer opportunities to convert nitrate to value-added ammonium, although challenges remain in scalability, microbial stability, material–microbe integration, process engineering, regulatory compliance, and economic feasibility.
A Four-Step Thermocatalytic Route For Converting Co2 Into High-Purity Oxalic Acid, Hao Feng, Muhammad Kashif Khan, Lei Li, Hongyan Ma, Xinhua Liang
A Four-Step Thermocatalytic Route For Converting Co2 Into High-Purity Oxalic Acid, Hao Feng, Muhammad Kashif Khan, Lei Li, Hongyan Ma, Xinhua Liang
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This research outlines a four-step methodology for transforming CO2 into high-purity oxalic acid. CO2 was first sequestered as KHCO3 through its reaction with aqueous KOH, followed by hydrogenation using a supported AgPd/CNT catalyst in a batch reactor at an initial H2 pressure of 60 bar and a temperature of 150°C. The formate yield reached 91.8% at optimum conditions. Potassium formate in the solid state was thermally coupled in the presence of KOH at 400°C under N2 flow, yielding potassium oxalate of up to 76% yield. The final step was the selective precipitation of potassium oxalate with ferrous …
The Impact Of Value Homophily, Rational And Emotional Persuasion On Information Passing Of Social Media Advertisements: A Model Comparison Approach, Gloria Hui Wen Liu, Cecil Eng Huang Chua, Neil Chueh An Lee, Jenny Hua Jen Wu
The Impact Of Value Homophily, Rational And Emotional Persuasion On Information Passing Of Social Media Advertisements: A Model Comparison Approach, Gloria Hui Wen Liu, Cecil Eng Huang Chua, Neil Chueh An Lee, Jenny Hua Jen Wu
Business and Information Technology Faculty Research & Creative Works
Increasingly, businesses collaborate with influencers and content creators (the source) to advertise on social media, with social media users being exposed to an environment saturated with unsolicited advertisements. With social contacts remaining the most trusted advertisement sources, users' passing of such advertisements helps their dissemination and creates a specific kind of electronic word of mouth called information passing. Information passing involves users forwarding advertisements about products/services to someone else. Prior studies have found at least three factors influence information passing, including value homophily (similarity with the source as perceived by users), rational appeal (information about how a product can meet …
Hardware Without Humanware: Robot Adoption, Talent Structure Degradation, And Firm Innovation, Wenhao Sun, Zhenyu Wu, Chevy-Hanqing Fang
Hardware Without Humanware: Robot Adoption, Talent Structure Degradation, And Firm Innovation, Wenhao Sun, Zhenyu Wu, Chevy-Hanqing Fang
Business and Information Technology Faculty Research & Creative Works
Contrary to the prevailing view that automation complements skilled labor in advanced economies, this study examines the unintended consequences of robot adoption in emerging markets. Drawing on strategic human capital theory, we exploit China's manufacturing sector as a natural experiment to identify the causal impact of industrial intelligence on firm-level innovation. Using a unique dataset of more than 90,000 public and private firms from the National Enterprise Innovation Database (2008–2014), we uncover a counterintuitive result: robot adoption significantly reduces firm innovation, which is notably more pronounced for private-owned firms and those with weaker innovation capabilities. Mediation analyses further show that …
One Size Doesn’T Fit All: Navigating Gendered Ageism In Older Women’S Entry Into Entrepreneurship, Yanying Chen, Zijie Song, Chevy-Hanqing Fang
One Size Doesn’T Fit All: Navigating Gendered Ageism In Older Women’S Entry Into Entrepreneurship, Yanying Chen, Zijie Song, Chevy-Hanqing Fang
Business and Information Technology Faculty Research & Creative Works
Though older women may choose entrepreneurship as a way to escape discrimination in the labor market, they may face other forms of discrimination in the entrepreneurial domain. Drawing on intersectionality theory, we posit that older women encounter amplified discrimination due to the stereotype-consistent implications from gender and age norms, namely gendered ageism. Using 815,428 individual observations pooled across country–year surveys from 56 countries between 2009 and 2018, we found that older women were least likely to enter entrepreneurship. And this intersectional disadvantage could be mitigated by weakening the normative exclusion and possessing resource endowments that signal capability. However, strategies focused …
Counterfactual Indeterminacy Bias In Family Firm Research, Chevy-Hanqing Fang, James J. Chrisman, Alfredo De Massis
Counterfactual Indeterminacy Bias In Family Firm Research, Chevy-Hanqing Fang, James J. Chrisman, Alfredo De Massis
Business and Information Technology Faculty Research & Creative Works
Ever since scholars recognized that family firms are heterogeneous, many studies have attempted to compare different types of family firms without ensuring that the source of heterogeneity is unique to family firms. When the source of heterogeneity among family firms resembles the source of heterogeneity among nonfamily firms, the problem of counterfactual indeterminacy bias can lead to misleading or irrelevant findings that fail to distinguish the effects of family influence from factors that affect all firms. We delineate common forms of this bias and offer recommendations to prevent it in research on family firm behavior and performance.
Gubernatorial Re-Election Incentives, Local Investment Bias, And Pension Fund Performance, Hongxian Zhang, Liang Guo, Jun Hao, Yu Liu
Gubernatorial Re-Election Incentives, Local Investment Bias, And Pension Fund Performance, Hongxian Zhang, Liang Guo, Jun Hao, Yu Liu
Business and Information Technology Faculty Research & Creative Works
We investigate the impact of gubernatorial re-election incentive and political factors on US public pension funds from 1990 to 2022. Our empirical analysis finds no significant overall relationship between gubernatorial re-election incentives and local bias in the full sample. However, the effect of gubernatorial re-election incentives on local bias is influenced by a state's level of corruption. Specifically, in states within the lowest corruption quantile, governors eligible for re-election tend to prioritize local investments to gain consistent support. In contrast, in states within the highest corruption quantile, heightened scrutiny may encourage re-election-eligible governors to adopt conservative investment policies that do …
A Case Of Acquired Amusia And Misophonia Following Right Temporal Resection, Emily R. Dappen, Joel I. Berger, Amy M. Belfi, Joel Bruss, Timothy D. Griffiths, Alexander J. Billig, Ariane E. Rhone, Kirill V. Nourski, Daniel Tranel, Brian J. Dlouhy
A Case Of Acquired Amusia And Misophonia Following Right Temporal Resection, Emily R. Dappen, Joel I. Berger, Amy M. Belfi, Joel Bruss, Timothy D. Griffiths, Alexander J. Billig, Ariane E. Rhone, Kirill V. Nourski, Daniel Tranel, Brian J. Dlouhy
Psychological Science Faculty Research & Creative Works
Background: Our perception of the auditory world allows us to enjoy the richness of music and communicate effectively with others. These everyday processes are disrupted in conditions such as amusia, an inability to perceive music accurately, and misophonia, an intense emotional reaction to common sounds produced by others. We describe a case of acquired, concurrent amusia and misophonia in a 21-year-old right-handed woman following a right posterior insula, posterior temporal, supramarginal cortex, and sensory cortex resection for the treatment of drug-resistant epilepsy. Methods: The patient participated in interviews between 4–8 months post-resection. She completed an extensive testing battery designed to …
Teaching Effectiveness On Secondary Mathematics: Evidence From Pisa—Shanghai-China, Ting Shen
Teaching Effectiveness On Secondary Mathematics: Evidence From Pisa—Shanghai-China, Ting Shen
Psychological Science Faculty Research & Creative Works
Educational researchers and policymakers around the world have a strong interest in understanding the underlying reasons for the remarkable academic achievement of Chinese students in the Programme for International Student Assessment (PISA). Although teachers have a significant impact on student achievement, empirical evidence on teaching effectiveness in the Chinese education system has been scarce. This study uses the PISA 2012 Shanghai-China data and employs both multilevel models and quantile regression models to investigate effective teaching factors and their differential effects for students at different mathematics achievement levels. The results reveal the importance of cognitive activation and disciplinary climate as consistent, …
Five Tensions Of Artificial Intelligence Adoption For Organ Allocation: Applying The Technology–Organization–Environment Framework, Amaneh Babaee, Daniel Burton Shank, Casey I. Canfield, Joely Grace Hall, Krista L. Lentine, Henry Randall, Mark Schnitzler
Five Tensions Of Artificial Intelligence Adoption For Organ Allocation: Applying The Technology–Organization–Environment Framework, Amaneh Babaee, Daniel Burton Shank, Casey I. Canfield, Joely Grace Hall, Krista L. Lentine, Henry Randall, Mark Schnitzler
Psychological Science Faculty Research & Creative Works
Background: The US organ transplantation system is pursuing modernization of the allocation process through the integration of new technologies such as artificial intelligence (AI). However, the legal and ethical issues within the transplantation industry are still of concern. Objective: We explore the opportunities and challenges for Organ Procurement Organizations (OPOs) to adopt AI. The US organ transplant system is a highly regulated industry yet open to innovation. Methods: Ten structured interviews were conducted with OPO representatives using the Extended Technology, Organization, Environment (TOE) framework. Results: Overall, we identified five core tensions in AI adoption: (1) misconceptions, (2) approach to training, …
Character Judgements Of Rap Music Fans, Kaila C. Putter, Dan J. Miller, Amy M. Belfi, James Rees, Amanda E. Krause
Character Judgements Of Rap Music Fans, Kaila C. Putter, Dan J. Miller, Amy M. Belfi, James Rees, Amanda E. Krause
Psychological Science Faculty Research & Creative Works
Extending Fischoff, we used vignettes to examine people's perceptions of a hypothetical rap fan accused of murder. Study 1 (N = 300) used a 2 (murder accusation) x 2 (inclusion of rap lyrics) x 2 (fan gender) experiment, asking participants to judge how capable of murder and sexually aggressive they found the fan. The presentation of lyrics and murder accusation were associated with the fan being more capable of murder, while rap lyrics and participants' rap attitudes were associated with the fan being more sexually aggressive. Thematic analysis revealed that, in conditions containing both the lyrics and the murder accusation, …
Exploring Aggregate Morphological Characteristics Under Laboratory Polishing For Enhanced Pavement Skid Resistance, Ahmed S. El-Ashwah, Magdy Abdelrahman
Exploring Aggregate Morphological Characteristics Under Laboratory Polishing For Enhanced Pavement Skid Resistance, Ahmed S. El-Ashwah, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
As the use of recycled asphalt pavement (RAP) in pavement construction grows for sustainable development, it becomes essential to investigate potential frictional deterioration over time. This study evaluated the friction properties of recovered RAP material aggregates compared with raw aggregates across various polishing cycles. The micro-Deval test was employed to simulate aggregate loss of texture, while morphological and friction properties were measured using an aggregate imaging measurement system (AIMS-II), along with a British pendulum tester (BPT) and dynamic friction tester (DFT). Additionally, Fourier transform infrared spectroscopy (FTIR) was employed to assess its potential in determining the origin and composition of …
Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández
Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández
Electrical and Computer Engineering Faculty Research & Creative Works
Objective: To compare the performance of eight large language models (LLMs) with neurology residents on board-style multiple-choice questions across seven subspecialties and two cognitive levels. Methods: In a cross-sectional benchmarking study, we evaluated Bard, Claude, Gemini v1, Gemini 2.5, ChatGPT-3.5, ChatGPT-4, ChatGPT-4o, and ChatGPT-5 using 107 text-only items spanning movement disorders, vascular neurology, neuroanatomy, neuroimmunology, epilepsy, neuromuscular disease, and neuro-infectious disease. Items were labeled as lower- or higher-order per Bloom's taxonomy by two neurologists. Models answered each item in a fresh session and reported confidence and Bloom classification. Residents completed the same set under exam-like conditions. Outcomes included overall and …
Evaluation Of Chromium-Crosslinked Amps-Hpam Copolymer Gels: Effects Of Key Parameters On Gelation Time And Strength, Maryam Sharifi Paroushi, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei
Evaluation Of Chromium-Crosslinked Amps-Hpam Copolymer Gels: Effects Of Key Parameters On Gelation Time And Strength, Maryam Sharifi Paroushi, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Controlling CO2 channeling in heterogeneous reservoirs remains a major challenge for both enhanced oil recovery (EOR) and secure geological storage. AMPS-HPAM copolymers exhibit high-temperature resistance and brine tolerance compared with conventional HPAM gels, making them well suited for the harsh environments associated with CO2 injection. Chromium-based crosslinkers (CrAc and CrCl3) were investigated because sulfonic acid groups in AMPS can coordinate with trivalent chromium ions, enabling dual ionic crosslinking and the formation of a robust gel network. While organic crosslinked AMPS-HPAM gels have been widely studied, the behavior of chromium-crosslinked AMPS-containing systems, particularly their gelation kinetics under …
Solubility And Dissolution Mechanism Of Novel Multi-Ester Headgroup Surfactants In Supercritical Co2, Ning Xu, Yan Ling Wang, Baojun Bai, Shi Zhang Cui, Yu Zhang, Wen Jing Shi, Zhao Nian Zhang, Wen Hui Ding, Pei Xu Ma, Zan Gao
Solubility And Dissolution Mechanism Of Novel Multi-Ester Headgroup Surfactants In Supercritical Co2, Ning Xu, Yan Ling Wang, Baojun Bai, Shi Zhang Cui, Yu Zhang, Wen Jing Shi, Zhao Nian Zhang, Wen Hui Ding, Pei Xu Ma, Zan Gao
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
To address the limited solubility and applicability of conventional hydrocarbon surfactants in supercritical CO2, a series of multi-ester headgroup surfactants were designed and synthesized by leveraging the CO2-philic properties of ester groups. The molecular structures were characterized using Fourier transform infrared (FT-IR) spectroscopy and 1H NMR. A custom-designed laser-based apparatus was developed to quantify surfactant solubility and systematically investigate phase behavior in CO2. Molecular dynamics (MD) simulations were employed to elucidate structure–solubility relationships across multiple scales, including solubility parameters, interaction energies, radial distribution functions (RDFs), and free volume fractions. Results indicate that, at 323.15 K, …
Waveguide-Assisted Single-Mode Fiber Bragg Gratings In A Highly Multimode Coreless Fiber Via Femtosecond Laser Inscription For Extreme Temperature Quasi-Distributed Thermal Sensing, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang
Waveguide-Assisted Single-Mode Fiber Bragg Gratings In A Highly Multimode Coreless Fiber Via Femtosecond Laser Inscription For Extreme Temperature Quasi-Distributed Thermal Sensing, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
This research reports a potential quasi-distributed thermal mapping optical sensing system for extreme temperatures, leveraging femtosecond (fs) laser inscribed single-mode fiber Bragg gratings (FBGs) and a waveguide within coreless, highly multimode optical fiber, resulting in a single-mode structure. Unlike doped single-mode fibers, coreless fibers composed of silica rods prevent issues associated with dopant migration and ensure data accuracy. The strategic placement of point-by-point FBGs in a cascaded formation on the fs-laser inscribed waveguide facilitates localized multipoint sensing. The long-term stability of the proposed waveguide-assisted FBG system was assessed over 24 hours at elevated temperatures (1000°C), showing no hysteresis during heating …
Evaluation And Design Of A Footing Hybrid Connection For Innovative Hollow-Core Fiber-Reinforced Polymer–Concrete–Steel Composite Columns, Mohanad M. Abdulazeez, Mohamed A. Elgawady
Evaluation And Design Of A Footing Hybrid Connection For Innovative Hollow-Core Fiber-Reinforced Polymer–Concrete–Steel Composite Columns, Mohanad M. Abdulazeez, Mohamed A. Elgawady
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
To support the advancement of accelerated bridge construction in high-seismic regions, this study investigates a novel prefabricated column-to-footing connection designed for improved resiliency, constructability, and cost efficiency. The socket connection utilizes hollow-core fiber-reinforced polymer–concrete–steel (HC-FCS) columns with embedded corrugated steel pipes (CSPs). The composite HC-FCS column consists of a concrete shell sandwiched between an outer fiber-reinforced polymer tube and an inner steel tube. The inner steel tube is embedded into the footing connection of the HC-FCS column. The same authors tested the innovative socket connection on a large HC-FCS column under seismic loads, showing high ductility, strong moment and drift …
You Only Need One Stage: Novel-View Synthesis From A Single Blind Face Image, Taoyue Wang, Xiang Zhang, Xiaotian Li, Huiyuan Yang, Lijun Yin
You Only Need One Stage: Novel-View Synthesis From A Single Blind Face Image, Taoyue Wang, Xiang Zhang, Xiaotian Li, Huiyuan Yang, Lijun Yin
Computer Science Faculty Research & Creative Works
We propose a novel one-stage method, NVB-Face, for generating consistent Novel-View images directly from a single Blind Face image. Existing approaches to novel-view synthesis for objects or faces typically require a high-resolution RGB image as input. When dealing with degraded images, the conventional pipeline follows a two-stage process: first restoring the image to high resolution, then synthesizing novel views from the restored result. However, this approach is highly dependent on the quality of the restored image, often leading to inaccuracies and inconsistencies in the final output. To address this limitation, we extract single-view features directly from the blind face image …
Qura: Reinforcement Learning Based Routing For Quantum Networks, Tasdiqul Islam, Engin Arslan, Md Arifuzzaman
Qura: Reinforcement Learning Based Routing For Quantum Networks, Tasdiqul Islam, Engin Arslan, Md Arifuzzaman
Computer Science Faculty Research & Creative Works
Quantum routing deals with identifying a set of quantum repeaters to use to create entanglement between distant endpoints. Previous approaches proposed shortest-path and linear programming methods to find a solution to this problem. While the shortest path approach results in suboptimal performance, linear programming takes too long to find a solution as the network size and constraints increase. In this paper, we apply Deep Q-Reinforcement Learning (DQRL) to optimize routing in quantum networks both in terms of execution time and performance. The proposed Quantum Routing Algorithm (QuRA) first chooses which request to schedule among all requests. It then determines which …
Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness, Renqiang Luo, Huafei Huang, Shuo Yu, Fengqi Yu, Feng Xia, Sajal K. Das, Chengqi Zhang
Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness, Renqiang Luo, Huafei Huang, Shuo Yu, Fengqi Yu, Feng Xia, Sajal K. Das, Chengqi Zhang
Computer Science Faculty Research & Creative Works
Fairness-aware federated graph neural networks (FedGNNs) necessitate consideration of both the server and the clients. However, fairness-aware methods struggle to enhance dual-perspective (i.e., server and clients) fairness without sacrificing utility due to the distributed learning framework. As a consequence, the utility sacrifices of fairness-aware graph learning methods are even exacerbated in federated frameworks. In this work we propose F3GL, a dual-perspective fairness federated graph learning method that enhances both global (for the server) and local fairness (for clients) while preserving utility. Through theoretical analysis, we delineate the similarity between original sensitive features and those after convolution under different spectra. Our …
Feddot: Defending Federated Learning Against Overwhelming Targeted Attacks, Priyesh Ranjan, Ashish Gupta, Federico Coro, Sajal K. Das
Feddot: Defending Federated Learning Against Overwhelming Targeted Attacks, Priyesh Ranjan, Ashish Gupta, Federico Coro, Sajal K. Das
Computer Science Faculty Research & Creative Works
Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the identities of the participants, FL may attract adversaries in order to hamper the underlying model. In this paper, we propose an FL framework, FedDOT, to defend against adversaries performing targeted attacks. FedDOT incorporates two powerful defense algorithms, Maximum Spanning Tree based attacker detection (MSTAD) and Densest graph-based attacker detection (Density-AD), which leverage correlation between weight updates and graph …
Dcmm-Transformer: Degree-Corrected Mixed-Membership Attention For Medical Imaging, Huimin Cheng, Xiaowei Yu, Shushan Wu, Luyang Fang, Chao Cao, Jing Zhang, Tianming Liu, Dajiang Zhu, Wenxuan Zhong, Ping Ma
Dcmm-Transformer: Degree-Corrected Mixed-Membership Attention For Medical Imaging, Huimin Cheng, Xiaowei Yu, Shushan Wu, Luyang Fang, Chao Cao, Jing Zhang, Tianming Liu, Dajiang Zhu, Wenxuan Zhong, Ping Ma
Computer Science Faculty Research & Creative Works
Medical images exhibit latent anatomical groupings, such as organs, tissues, and pathological regions, that standard Vision Transformers (ViTs) fail to exploit. While recent work like SBM-Transformer attempts to incorporate such structures through stochastic binary masking, they suffer from non-differentiability, training instability, and the inability to model complex community structure. We present DCMM-Transformer, a novel ViT architecture for medical image analysis that incorporates a Degree-Corrected Mixed-Membership (DCMM) model as an additive bias in self-attention. Unlike prior approaches that rely on multiplicative masking and binary sampling, our method introduces community structure and degree heterogeneity in a fully differentiable and interpretable manner. Comprehensive …
High-Resolution, Fast-Response Optical Fiber Temperature Sensor With A Large Measurement Range Based On Fiber-Tip Alumina Fabry-Pérot Interferometer, Ruimin Jie, Chen Zhu, Robert Abbott, Michael Davis, Xiong Zhang, Jie Huang
High-Resolution, Fast-Response Optical Fiber Temperature Sensor With A Large Measurement Range Based On Fiber-Tip Alumina Fabry-Pérot Interferometer, Ruimin Jie, Chen Zhu, Robert Abbott, Michael Davis, Xiong Zhang, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
We present an alumina-tip optical fiber Fabry-Pérot interferometric temperature sensor exhibiting high-temperature performance, rapid response, and high resolution. Fabricated by fusion splicing an alumina micro disk directly to a single-mode fiber, the sensor achieves robust, stable operation without complex fabrication processes or adhesives. Experimental evaluation confirms a measurement range extending to 1000°C, with sensitivity of 28.66 pm/°C, a resolution of 0.042°C, and a rapid response time of approximately 13 ms. Compared to state-of-the-art optical fiber FPI sensors, our alumina-tip sensor offers superior overall performance, effectively addressing critical demands for high-resolution, fast-response temperature measurement in extreme environments including aerospace, structural monitoring, …
Embeddable Optical Fiber Sensor For Simultaneous Strain And Temperature Monitoring, Amardeep Kaur, Sudharshan Anandan, Steve Eugene Watkins, Yinan Zhang, Kumbla Chandrashekhara, Hai Xiao
Embeddable Optical Fiber Sensor For Simultaneous Strain And Temperature Monitoring, Amardeep Kaur, Sudharshan Anandan, Steve Eugene Watkins, Yinan Zhang, Kumbla Chandrashekhara, Hai Xiao
Electrical and Computer Engineering Faculty Research & Creative Works
We present an embeddable hybrid optical fiber sensor based on a cascaded extrinsic Fabry–Pérot interferometer (EFPI) and intrinsic Fabry–Pérot interferometer (IFPI) for simultaneous strain and temperature monitoring in high-performance composite materials. The sensor is fabricated using femtosecond laser micromachining and is embedded within bismaleimide composite laminates manufactured via an out-of-autoclave process. Experimental results demonstrate linear and decoupled responses to strain and temperature, with the EFPI showing minimal temperature sensitivity (1.7 pm/°C) and the IFPI exhibiting high temperature sensitivity (16.1 pm/°C). Strain sensitivities for both components were consistent at 0.6pm/με in embedded conditions. The sensor maintained structural integrity and stable spectral …