Experimental Investigation On Metakaolin/Coal Fly Ash-Based Porous Geopolymer Grouting Material For Geotechnical Applications, Karla Sierra, Philip Park, Chu-Lin Cheng, Yong Je Kim, Jae-Hoon Hwang, Bubryur Kim, Boo Hyun Nam, Jinwoo An

Civil Engineering Faculty Publications

This research investigates the development of a porous geopolymer cement grout for soil grouting applications, aiming to reduce carbon emissions associated with Portland cement while maintaining critical performance characteristics such as strength and permeability. Class F fly ash and metakaolin were used as aluminosilicate precursors, activated by sodium silicate and sodium hydroxide solutions. The addition of hydrogen peroxide served as a foaming agent to introduce porosity. Compressive strength and porosity were evaluated, with results showing that metakaolin significantly increased compressive strength due to its smaller particle size and higher reactivity. A higher molarity of sodium silicate enhanced strength by reducing …

Llm-Enhanced Multiple Instance Learning For Joint Rumor And Stance Detection With Social Context Information, Ruichao Yang, Jing Ma, Wei Gao, Hongzhan Lin

Research Collection School Of Computing and Information Systems

The proliferation of misinformation, such as rumors on social media, has drawn significant attention, prompting various expressions of stance among users. Although rumor detection and stance detection are distinct tasks, they can complement each other. Rumors can be identified by cross-referencing stances in related posts, and stances are influenced by the nature of the rumor. However, existing stance detection methods often require post-level stance annotations, which are costly to obtain. We propose a novel LLM-enhanced Multiple Instance Learning (MIL) approach to jointly predict post stance and claim class labels, supervised solely by claim labels, using an undirected microblog propagation model. …

Updated Document On Standard Terminology For Foot And Ankle, Jason T. Bariteau, Constantine A. Demetracopoulos, Ahmed Khalil Attia, Nacime Salomão Barbachan Mansur, Daniel J. Scott, Karen M. Kruger, Amy L. Lenz

Biomedical Engineering Faculty Research and Publications

The Standardized Terminology and Measurement Subcommittee was established as an ad hoc academic entity at the behest of Dr Ian Alexander in 1990. Members who have served on the committee include Ian Alexander, David Katcherian, Harold Kitaoka, Bright McConnell, Chris Reynolds, Charles Saltzman, and Saul Trevino. This subcommittee met twice yearly at the annual winter and summer meetings. This initial work was coordinated with members of the POSNA’s Committee on Terminology and Measurement.   These definitions were published in Foot & Ankle International and were expected to be included in the Guidelines for Manuscript Preparation, which was never done.

Estimating Snow Coverage Percentage On Solar Panels Using Drone Imagery And Machine Learning For Enhanced Energy Efficiency, Ashraf Saleem, Ali Awad, Amna Mazen, Zoe Mazurkiewicz, Ana Dyreson

Michigan Tech Publications

Snow accumulation on solar panels presents a significant challenge to energy generation in snowy regions, reducing the efficiency of solar photovoltaic (PV) systems and impacting economic viability. While prior studies have explored snow detection using fixed-camera setups, these methods suffer from scalability limitations, stationary viewpoints, and the need for reference images. This study introduces an automated deep-learning framework that leverages drone-captured imagery to detect and quantify snow coverage on solar panels, aiming to enhance power forecasting and optimize snow removal strategies in winter conditions. We developed and evaluated two approaches using YOLO-based models: Approach 1, a high-precision method utilizing a …

Painting Rich Six-Dimensional Pictures Using Polarized Fluorescence Microscopy, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

No abstract provided.

Reweighting Configurations Generated By Transferable, Machine Learned Models For Protein Sidechain Backmapping, Jacob Monroe

Chemical Engineering Faculty Publications and Presentations

Multiscale modeling requires the linking of models at different levels of detail, with the goal of gaining accelerations from lower fidelity models while recovering fine details from higher resolution models. Communication across resolutions is particularly important in modeling soft matter, where tight couplings exist between molecular-level details and mesoscale structures. While multiscale modeling of biomolecules has become a critical component in exploring their structure and self-assembly, backmapping from coarse-grained to fine-grained, or atomistic, representations presents a challenge, despite recent advances through machine learning. A major hurdle, especially for strategies utilizing machine learning, is that backmappings can only approximately recover the …

Evaluation Of Gfap And Ptau Protein Expression In Male And Female Cci Mouse Models, Sara Wallace

Honors Program: Senior Projects (Public)

Traumatic Brain Injury (TBI) is a serious public health concern that leads to the death or disability of thousands of individuals in the US annually. Progression of TBI involves primary damage from the initial, mechanical injury and secondary damage, from nonmechanical, pathological dysfunction. The secondary damage mechanisms can be better understood, diagnosed, and treated through the quantification of TBI biomarkers. The two biomarkers of interest in this study are pTau and GFAP. The male and female mouse models showed similar significant increase in GFAP following injury, as well as a general lack of increase in pTau expression following the injury. …

Evaluating Coal-Jatropha Curcas Composite Briquettes As Sustainable Fuel Alternatives, Amad Ullah Khan, Muhammad Saleem, Muhammad Abas, Zakir Ullah, Khan Muhammad, Farida Anjum, Aamer Sharif, Melkamu Tadesse Getachew

Research outputs 2022 to 2026

Coal is a major fuel source but raises environmental concerns. This study investigated the feasibility of utilizing a composite briquette sustainable fuel produced from subbituminous coal and Jatropha curcas biomass. Briquettes were prepared with varying weight ratios of coal to J. curcas biomass (90:0–0:90) using corn starch as a binder. The influence of this ratio on the briquettes’ properties was comprehensively evaluated through proximate analysis, ultimate analysis, scanning electron microscopy (SEM), and X-ray fluorescence (XRF) analysis. The results revealed that increasing the J. curcas content in the briquettes gradually decreased the moisture content, ash content, and fixed carbon content while …

Exploring The Impact Of Multiwall Carbon Nanotubes On Enhancing Water-Based Mud Performance, Attia Attia, Mohamed Saad Elhossieny Dr., Hesham Abuseda Dr., Ahmed Gouish Prof., Adel Salem Prof.

Petroleum Engineering and Gas

Drilling fluids are critical components in hydrocarbon and geothermal well construction, particularly in extreme downhole environments such as deep reservoirs and high-temperature geothermal systems. Key challenges in designing water-based drilling muds (WBDM) for these applications include effective thermal management, maintenance of rheological stability, and enhancement of thermal conductivity under high-temperature, high-pressure (HTHP) conditions. Recent advances in nanotechnology suggest that nanoscale additives, such as uniformly dispersed carbon nanotubes (CNTs), can significantly improve the thermorheological performance of drilling fluids compared to conventional formulations. However, stabilizing critical fluid properties—including viscosity, filtration efficiency, mud cake integrity, and gel strength—remains a persistent challenge in WBDM …

Stable Heteroclinic Channels As A Decision-Making Model: Overcoming Low Signal-To-Noise Ratio With Mutual Inhibition, Natasha A. Rouse

Faculty Scholarship

Bio-inspired robot controllers are becoming more complex as we strive to make them more robust to, and flexible in, noisy, real-world environments. A stable heteroclinic network (SHN) is a dynamical system that produces cyclical state transitions using noisy input. SHN-based robot controllers enable sensory input to be integrated at the phase-space level of the controller, thus simplifying sensor-integrated, robot control methods. In this work, we investigate the mechanism that drives branching state trajectories in SHNs. We liken the branching state trajectories to decision-splits imposed into the system, which opens the door for more sophisticated controls-all driven by sensory input. This …

Scalable Mxene-Based Textile Supercapacitors, Abaigeal Aydt

Honors Program: Senior Projects (Public)

The demand for flexible and wearable energy storage devices for portable applications has led to the exploration of textile-based supercapacitors (TSCs). TSCs will allow for the creation of a new class of energy harvesting and storing technology directly into our clothing and will require using non-toxic and/or biocompatible materials. This will result in a greener and more sustainable path to address the challenges at the nexus of energy, mobility, and sustainability. To fabricate a TSC, a yarn made of fibers, such as wool or cotton, is coated with MXene flakes; MXenes are composed of transition metal carbides, nitrides, or carbonitrides …

In-Situ Density Measurement For Enhanced Electrorefining Material Accountancy, Edward Mercado, Carlos Mejia, Ranon Fuller, Devin Rappleye

Student Works

To further enhance the proliferation resistance of electrorefining (ER) processes, precise and reliable analytical methods are essential for determining the inventory of fissile material. This can be achieved by electrochemically measuring the salt concentration and converting it to mass using its density. However, the density within the refiner is not fixed, and small variations in salt composition can significantly impact its thermophysical properties. While an ideal mixing model provides reasonable density estimates (with errors up to 2-3%), such errors are unacceptable when precise material accountancy of fissile material is crucial. This study developed a methodology to measure density in situ …

Synergy In Materials: Leveraging Phosphosilicate Waste Forms For Electrochemical Salt Waste, Jonathan S. Evarts, Brian J. Riley, Charmayne E. Lonergan, Michaella S. Harris, Jincheng Bai, Eric W. Bohannan, Iheanyichukwu Ajoku, Saehwa Chong, John S. Mccloy

Materials Science and Engineering Faculty Research & Creative Works

Waste forms containing glassy and crystalline phosphate and silicate phases were produced to immobilize salt waste simulants from pyro processing and characterized by using Raman spectroscopy, Mössbauer spectroscopy, X-ray diffraction, scanning electron microscopy, heat capacity, and chemical durability measurements. In this work, a phosphosilicate waste form is presented to leverage the benefits of both borosilicate glasses and iron phosphate glasses. To improve waste loading, prior to immobilization, salt simulants were successfully dechlorinated using ammonium dihydrogen phosphate, mixed with a borosilicate frit (5–30 wt. %) and Fe2O3, and vitrified. Additions of 2.5–15 wt. % borosilicate glass (NBS3) improved normalized release rates …

Per- And Polyfluoroalkyl Substance (Pfas) Degradation In Water And Soil Using Cold Atmospheric Plasma (Cap): A Review, Victor Somtochukwu Mbanugo, Boluwatife Stephen Ojo, Ta Chun Lin, Yue-Wern Huang, Marek Locmelis, Daoru Han

Biological Sciences Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFASs) are persistent organic chemicals found in numerous industrial applications and everyday products. The excessive amounts of PFASs in water and soil, together with their link to severe health issues, have prompted substantial public concerns, making their removal from the environment a necessity. Existing degradation techniques are frequently lacking due to their low efficiency, cost-effectiveness, and potential for secondary contamination. Cold Atmospheric Plasma (CAP) technology has emerged as a promising alternative, utilizing energized reactive species to break down PFASs under ambient conditions. Therefore, this review examines the efficacy and effectiveness of CAP in degrading PFASs by …

A Beginner’S Guide To Artificial Intelligence (Ai) And Generative Ai (Gen Ai) For Small Businesses, Stanley Mierzwa, Iassen Christov

Center for Cybersecurity

Generative Artificial Intelligence (GenAI) guide for small businesses.

Support and funding for this effort was received from the United States Small Business Administration (Contract 73351023C0016) for this activity and research. Formulated and ultimately created as a result of this grant was the New Jersey Cybersecurity Regional Cluster (NJCRC), which included the partners of NTouch-BCT Strategies, Covenant Business Concepts, and the Kean University Center for Cybersecurity. As part of the free cybersecurity risk assessments offered to small businesses in the community, organizations were introduced to GenAI through a demonstration, with the key information provided in this booklet.

3d Printed Living Hinges In Deployable Origami Structures, Davis Wing, Robert J. Lang, Spencer Magleby, Larry Howell

Student Works

Origami-based geometries are often difficult to prototype and construct. Although methods exist for creating surrogate folds in many materials, doing so often requires multiple manufacturing steps. While engineers studying foldable models can use single-material additive manufacturing to construct living hinges in their models, current techniques are limited. We present an approach for generating living hinges in stowed, deployable mechanisms using single-material 3D printing. This approach enables new models to be constructed with accurate geometry and kinematics in a single print and with no further manufacturing necessary beyond an initial folding step. Additionally, by printing deployable structures in their stowed form, …

The Impact Of Solar Angle And Cloud Shadows On 3d Reconstruction Of Rolling Stock Cargo, Carlina M. Ostrand, Adam D. Reiman, Frank W. Ciarallo, Scott L. Nykl, Clark N. Taylor, Joshua F. Krutz

Faculty Publications

Meeting the relentless demand for more efficient air cargo transportation is of paramount importance for commercial needs and military missions. This study describes an experiment to test an innovative approach that harnesses cutting-edge stereoscopic vision technology to create 3D point clouds of rolling stock cargo across varying solar angles and cloud shadow conditions. Virtual cargo point clouds are generated by calibrating and systematically organizing the depth and location points from an RGB-D camera and then reprojecting them in a virtual environment. Measurement accuracy was rigorously tested across six camera positions in various combinations of weather conditions against physical ground truth …

Green Building Information Modeling Framework For Sustainable Residential Development In Egypt, Mohamed Nabawy

Civil Engineering

Rapid urbanization and environmental challenges necessitate innovative construction solutions in Egypt. This study presents a 6D Green Building Information Modeling (BIM) framework designed to enhance sustainability, reduce costs, and optimize construction processes. Integrating energy consumption, carbon footprint, and lifecycle performance metrics, the framework addresses critical gaps in Egypt’s construction sector, including limited technical expertise, high costs, and regulatory challenges. A mixed-methods approach was employed, combining global case study analysis, 3D modeling using Autodesk Revit, energy simulations with Autodesk Insight, and project scheduling through Primavera P6. Expert interviews with industry professionals further refined and validated the framework, ensuring its practicality and …

Green Building Information Modeling Framework For Sustainable Residential Development In Egypt, Mohamed Ahmed Nabawy Dr., Ahmed Gouda Mohamed, Ahmed Osama Daoud Dr.

Civil Engineering

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Green Building Information Modeling Framework for Sustainable Residential Development in Egypt

by Mohamed Nabawy *, Ahmed Gouda Mohamed , Israa Awad and Ahmed Osama Daoud * Construction Engineering and Management Programme, Civil Engineering Department, Faculty of Engineering, The British University in Egypt (BUE), El Sherouk City, Cairo 11837, Egypt * Authors to whom correspondence should be addressed. Buildings 2025, 15(7), 1035; https://doi.org/10.3390/buildings15071035 Submission received: 20 January 2025 / Revised: 23 February 2025 / Accepted: 27 February 2025 / Published: 24 March 2025 (This article belongs to the Special Issue Building …

Analysis Of An Ultra-Broadband Terahertz Metamaterial Absorber, Md Ariful Islam, Md Rezwan Ahmed, Oishi Jyoti, Pritu Sarkar, Md. Samiul Habib

Mechanical Engineering Faculty Publications

This paper introduces a metamaterial absorber (MA) based on vanadium dioxide (VO2) that achieves over 90% absorption of incident terahertz (THz) waves in between 4.50 THz to 11.90 THz with an average absorption of 94.64% and a relative absorption bandwidth (RAB) of 90.18% — the highest reported absorption bandwidth for VO2-based absorbers to our knowledge. The proposed metamaterial absorber features a design with a central square surrounded by four ’T’-shaped elements on each side, symmetrically arranged on a TOPAS dielectric substrate. We perform all numerical analyses keeping the phase-changing material VO2 in the metallic state, and our simulation results show …

How Engineering Students Learn And Are Impacted By Empathy Training: A Multi-Year Study Of An Empathy Program Focused On Disability And Technology, Eric Schearer

Faculty Scholarship

Measurable results of efforts to teach empathy to engineering students are sparse and somewhat mixed. This study’s objectives are (O1) to understand how empathy training affects students’ professional development relative to other educational experiences, (O2) to track empathy changes due to training over multiple years, and (O3) to understand how and what students learn in empathy training environments.

Confirmation Of The Scanpyramids North Face Corridor In The Great Pyramid Of Giza Using Multi-Modal Image Fusion From Three Non-Destructive Testing Techniques, Thomas Schumacher, Polina Pugacheva, Hussien Allam, Alejandro Ramirez-Pinero, Benedikt Maier, Johannes Rupfle, Khalid Helal, Olga Popovych, Amr G. Hamza, Mohamed Sholqamy, Multiple Additional Authors

Civil and Environmental Engineering Faculty Publications and Presentations

Abstract While non-destructive testing (NDT) measurements have been reported individually for archeological surveys of cultural heritage structures, only a few studies to date have attempted to combine NDT images by means of image fusion (IF). In this article, novel multimodal IF results from three different NDT techniques collected at the Chevron located on the Great Pyramid of Giza (aka. as Khufu’s Pyramid) are presented. The Chevron is an assembly of limestone blocks located in front of the recently confirmed ScanPyramids North Face Corridor (SP-NFC), which had been previously hidden for 4500 years. Under the research activities of the ScanPyramids mission, …

Arduino-Esp32 Based Smart Irrigation System, Ahmed D. Hassebo, Kevin B. Montes, Erick Cabrera

Publications and Research

In response to the growing demand for efficient water management in agriculture, this research presents the development of an Arduino-ESP32 based automated irrigation system. The project integrates an Arduino microcontroller with an ESP32 module to facilitate real-time data collection and control of irrigation processes. Sensors monitor soil moisture, water levels, and local weather conditions, with data displayed on an LCD I2C screen for user accessibility. The ESP32 module handles alert notifications via text messages, keeping users informed remotely. Key components, including a water pump, valve, relay module, OLED screen, and LED display, are synchronized to ensure precise irrigation control. Additionally, …

Insect Wing Flexibility Improves The Aerodynamic Performance Of Small Revolving Wings, Gal Ribak, Ori Stearns, Kiruthika Sundararajan, Duvall Dickerson-Evans, Dana Melamed, Maya Rabinovich, Roi Gurka

Physics and Engineering Science

Insect wings are flexible, elastically deforming under loads experienced during flapping. The adaptive value of this flexibility was tested using a revolving wing set-up. We show that the wing flexibility of the beetle Batocera rufomaculata, suppresses the reduction in lift coefficient that is expected to occur with a reduction of wing size compared to rigid propeller blades. Moreover, the scaling of wing flexibility with size is intra-specifically tuned through changes in wing-vein cross-section, resulting in smaller wings achieving proportionally larger chordwise deformations compared to larger wings, when loaded with aerodynamic forces. These elastic deformations control the separation of flow from …

The Artificial Intelligence-Enhanced Echocardiographic Detection Of Congenital Heart Defects In The Fetus: A Mini-Review, Khadiza Tun Suha, Hugh Lubenow, Stefania Soria-Zurita, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

Michigan Tech Publications

Artificial intelligence (AI) is rapidly gaining attention in radiology and cardiology for accurately diagnosing structural heart disease. In this review paper, we first outline the technical background of AI and echocardiography and then present an array of clinical applications, including image quality control, cardiac function measurements, defect detection, and classifications. Collectively, we answer how integrating AI technologies and echocardiography can help improve the detection of congenital heart defects. Particularly, the superior sensitivity of AI-based congenital heart defect (CHD) detection in the fetus (>90%) allows it to be potentially translated into the clinical workflow as an effective screening tool in …

Artificial Intelligence Approaches To Energy Management In Hvac Systems A Systematic Review, Seyed Abolfazl Aghili, Amin Haji Mohammad Rezaei, Mohammadsoroush Tafazzoli, Mostafa Khanzadi, Morteza Rahbar

Civil Engineering & Construction: Faculty Publications

Heating, Ventilation, and Air Conditioning (HVAC) systems contribute a considerable share of total global energy consumption and carbon dioxide emissions, putting them at the heart of the issues of decarbonization and removing barriers to achieving net-zero emissions and sustainable development goals. Nevertheless, the effective implementation of artificial intelligence (AI)-based methods to optimize energy efficiency while ensuring occupant comfort in multifarious settings remains to be fully realized. This paper provides a systematic review of state-of-the-art practices (2018 and later) using AI algorithms like machine learning (ML), deep learning (DL), and other computation-based techniques that have been deployed to boost HVAC system …

Synergistic Effects Of Copper Oxide-Stigmasterol Nanoparticles: A Novel Therapeutic Strategy For Oral Pathogen Biofilms And Oral Cancer, Althaf Hussain, Rym Ghimouz, Siva Prasad Panda, Uttam Prasad Panigrahy, Vanitha Marunganathan, Mohammed Rafi Shaik, Paramasivam Deepak, Nathiya Thiyagarajulu, Baji Shaik, Anahas Perianaika Matharasi Antonyraj, Mohd Asif Shah, Ajay Guru

All Works

Oral pathogen biofilms contribute to chronic infections, while oral cancer remains a significant health threat, emphasizing the need for effective therapeutic strategies. This study investigates the fabrication, characterization, and therapeutic potential of copper oxide-stigmasterol nanoparticles (CuO-SS NPs) for oral pathogen biofilm disruption and oral cancer treatment. The antimicrobial activity of CuO-SS NPs was evaluated against oral pathogens, including S. aureus, S. mutans, E. faecalis, and C. albicans. In cancer cell studies, CuO-SS NPs exhibited a concentration-dependent cytotoxicity, reducing cell viability from 88% at 15 µg/mL to 29.33% at 120 µg/mL, comparable to doxorubicin (24.3%). The CuO-SS NPs significantly upregulated the …

Increasing Electric Vehicle Charger Availability With A Mobile, Self-Contained Charging Station, Robert Serrano, Arifa Sultana, Declan Kavanaugh, Hongjie Wang

Electrical and Computer Engineering Student Research

As the transition to sustainable transportation has accelerated with the rise of electric vehicles (EVs), ensuring drivers have access to charging to maximize the electric miles driven is critical to lowering carbon emissions in the transportation sector. Limited charging station capacity and poor reliability, especially during peak travel times, long distance travels, holidays, and events, have hindered the adoption of EVs and threaten the progress toward reducing greenhouse gas emissions. Adaptive, flexible deployment strategies combined with innovative approaches integrating mobility and renewable energy are essential to address these systemic challenges and bridge the current infrastructure gap. To address these challenges, …

New Method Of Impact Localization On Plate-Like Structures Using Deep Learning And Wavelet Transform, Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu

Faculty Publications

This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. A network of four piezoelectric wafer active sensors (PWAS) was installed on the tested plate to acquire impact signals. These signals consisted of reflection waves that provided valuable information about impact events. In this methodology, each of the received signals was divided into several equal segments. Then, a wavelet transform (WT)-based time-frequency analysis was used for processing each segment signal. The generated WT diagrams of these segments’ signals were cropped and resized using MATLAB code …

New Hydrographic Survey Specifications - Updates And Enhancements, Matt Wilson, Tyanne Faulkes, Giuseppe Masetti

Center for Coastal and Ocean Mapping

No abstract provided.