Engineering Commons^™

Shear Strengthening Of Reinforced Concrete Beams Using Pre-Fabricated Ultra-High Performance Fiber Reinforced Concrete (Uhpfrc) Laminates: Experimental Investigation, Mostafa Khairy Elkady, Khalid Mohamed El-Sayed, Marwa Ibrahim Badawi, Gamal Ismaail Khaleel

Mansoura Engineering Journal

This study examines the effectiveness of prefabricated ultra-high-performance fiberreinforced concrete (UHPFRC) laminates in shear strengthening reinforced concrete (RC) beams. A total of nine reinforced concrete beams were cast and tested under a four-point loading till failure. The following key parameters were investigated: the number of strengthening sides, the thickness of the UHPFRC layer, the reinforcement of the strengthening layer (by using two different types of steel mesh, and also, in case of no-steel mesh), the volume fraction of steel fibers, and bonding schemes steel dowels and / or epoxy. The ultimate load and ductility of the strengthened beams have increased …

Optimization Of Persulfate Activation System Using Ferrous Sulfate For Toc Removal From Real Domestic Wastewater, Mohamed Fouad, Mohamed Mossad, Mohamed Gar Alalm, Mahmoud Samy

Mansoura Engineering Journal

The reuse of treated wastewater is increasingly recognized as a sustainable solution to address global water shortage. This study investigates the effectiveness of a persulfate-based advanced oxidation process (AOP) using sodium persulfate (Na2S2O8) activated by ferrous sulfate (FeSO4) as a tertiary treatment for secondary effluents. Real municipal wastewater was collected from Agouzain Wastewater Treatment Plant (WWTP) in Kafr El-Sheikh, Egypt. A Box Benkhen design (BBD) was employed to optimize three key variables: FeSO4 dose (0.5–2.0 g/L), Na2S2O8 dose (0.5–2.0 g/L), and pH (3.0–9.0), with total organic carbon (TOC) removal as the main response. Under optimized conditions (0.50 g/L FeSO4, 2.00 …

Effect Of Raw Materials And Loop Length On Thermal Comfort Properties Of Pique Fleece Fabrics, Aya E. Elemam, Abd Elmonem Fouda, Ahmed S. Eldeeb, Rehab Abd Elkhalek

Mansoura Engineering Journal

Technological developments of knitting machines made it possible to produce evolved fabric structures to obtain various properties that suit consumer needs. Pique fleece is a variation of the special popular fleece knitted structure with aim of combining the features of pique and fleece structures. The aim of this research was to study the effect of yarns material type and loop length on thermal comfort properties of un-napped pique fleece fabrics that used as apparel textiles during transitional seasons. Two types of fleece yarn (100% cotton and 65% cotton/ 35%polyester) and three types of face and binding yarns (cotton, polyester and …

Contextual Memory Recall: A Novel Metric For Class Incremental Learning, Balasubramanian S, Sai Subramaniam M., Sai Sriram Talasu, Yedu Krishna P., Pranav Phanindra Sai M., Darshan Gera, Ravi Mukkamala

Computer Science Faculty Publications

We propose a novel metric for class incremental learning (CIL) called Contextual Memory Recall (CMR), which evaluates how well a CIL model recalls previously learned classes when given relevant past cues. Inspired by human memory, CMR offers newer insights into continual aspects of a CIL model that were not addressed by previously proposed metrics for CIL. Specifically, the standard metric, average incremental accuracy (AIA), overlooks the quality of evolving feature representations, whereas our proposed CMR accounts for it. As a result, methods using feature distillation perform well under AIA but poorly under CMR, while those without feature distillation excel under …

Development Of A Compliant Soft Gripper With Embedded Force Sensors, Ayman Abbas, Abdelrahman Said, Tamer Kahlil, Mahmoud Magdy

Mechanical Engineering

Robotic manipulators have the capability to perform repetitive tasks with a level of efficiency and precision that exceeds the capabilities of human operators. Currently, they are commonly found and extensively utilized across various disciplines. However, robotic manipulators have gradually begun to make inroads into fields beyond manufacturing, such as medicine and agriculture. Due to the diverse range of industries utilizing robotic manipulators, the nature of tasks assigned to these devices can often be more intricate and multifaceted than conventional assignments. Hence, conventional mechanical grippers may not always be suitable, prompting a growing need for grippers capable of adapting to effectively …

Non-Invasive Glucose Monitoring Using Ppg, Ai, And Iot-Driven Mobile Integration For Real-Time Diabetes Management, Mostafa Abdelaziz, Amr Refaie

Mechanical Engineering

Diabetes mellitus patients must regularly monitor their blood glucose levels to manage glycaemia, typically requiring capillary tests at least three times daily and laboratory tests one to two times per month. These conventional methods involve finger pricking, causing significant discomfort and stress. This study introduces an innovative non-invasive glucose monitoring approach by integrating photoplethysmography (PPG) technology with an artificial intelligence (AI) algorithm, complemented by a mobile application using Flutter, IoT systems, and Firebase cloud for real-time data access. Among the AI models tested, polynomial regression demonstrated superior accuracy in glucose prediction, achieving a Mean Squared Error (MSE) of 14.76 and …

Design Of Modular Soft Gripper For Harvesting, Mostafa Abdelaziz, Ahmed Reda, Abdulrhman Atef, Mahmoud Magdy

Mechanical Engineering

Soft robotics presents a transformative approach to agricultural automation, addressing the limitations of traditional mechanical systems in handling delicate crops. This paper introduces a modular soft robotic gripper designed for gentle harvesting applications, with a focus on adaptability, precision, and crop safety. The gripper's performance was evaluated through Finite Element Analysis (FEA) and experimental testing, targeting its ability to conform to objects of varying shapes, sizes, and fragility. The FEA confirmed the gripper's capability to apply a load based on the gripped crop of the range 0.6 – 0.75 N, sufficient for damage-free harvesting of sensitive produce like strawberries and …

Design And Implementation Of Smart Automation For Sustainable Plastic Recycling With Iot Integration, Mostafa Abdelaziz, Mahmoud Khedr, Amr Bakkar, Yossef Zidan, Abdelrahman Youssef, Mahmoud Magdy

Mechanical Engineering

Plastic pollution poses a critical environmental challenge, infiltrating ecosystems and impacting human health. One innovative solution involves repurposing recycled plastics into interlocking blocks as a sustainable alternative to concrete in construction. However, manual production methods hinder scalability, efficiency, and product consistency while generating material waste. This research addresses these limitations by automating the production process using PLC and IoT technologies. The findings demonstrate that automation significantly enhances production rates, ensures consistent quality, and minimizes waste, thereby improving operational efficiency and environmental sustainability. IoT is integrated to enhance the system's capabilities by providing real-time connectivity and data exchange. The IoT dashboard, …

Ai-Driven Robotic System For Predictive Maintenance: Urban Road Defect Detection In Smart Cities, Mostafa Abdelaziz, Mahmoud Khedr

Mechanical Engineering

This paper presents the development and evaluation of an integrated AI & robotic solution for predictive maintenance in smart cities, focusing on urban road defect detection. The proposed system integrates a mobile robot equipped with a high-resolution camera and a GPS module to capture video footage and geolocation data of road surfaces. The collected data is processed using cloud-based AI models, with YOLOv9 and Roboflow 3.0 Object Detection (Fast) identified as the most effective for analyzing footage to detect cracks and potholes. Experimental results validate the system's ability to accurately identify defects and generate timely reports for maintenance teams. While …

Pre-Programmable Directional Stiffness In Continuum Robotic Arms: Effects Of Truss Configurations, Mostafa Abdelaziz, Zahy Elgendy, Mahmoud Magdy

Mechanical Engineering

This paper investigates the implementation of trussed designs in modular tendon-driven continuum arms (CAs) to address stiffness and stability limitations while maintaining adaptability. Various truss configurations— Single-Level, Combined-Level, and Alternated trusses—were analyzed using Finite Element Analysis (FEA) to evaluate their impact on flexural and axial stiffness under realistic loading conditions. Results demonstrate that truss placement significantly influences performance, with bottom-level trusses improving flexural stiffness by up to 33%, middle-level trusses enhancing axial stiffness by 43%. Further, Combined-Level configurations provide superior overall stiffness, with MiddleBottom trusses achieving a 66.5% improvement in flexural stiffness and a 70.9% increase in axial stiffness, while …

Multi-Objective Monitoring Of Cvd Diamond Micro-Grinding Tools Using Acoustic Emission And Force Signals With Neural Network Optimization, Ahmed Elkaseer, Jianfei Jia, Bianbian Meng, Bing Guo, Jun Qin, Guicheng Wu, Huan Zhao, Zhenfei Guo, Qingyu Meng, Qingliang Zhao, Honghui Yao, Amr Monier

Mechanical Engineering

Micro-grinding has been widely used in aerospace and other industry, and its application was mainly the asymmetric microstructure. Chemical Vapor Deposition (CVD) diamond has drawn attention for its good wear resistance. However, the small diameter and high spindle speed may cause difficulties on the monitoring of the micro-grinding processes. In order to solve the mentioned problem, a novel multi-objective monitoring method of structured CVD diamond micro-grinding tool based on acoustic emission (AE) and force signals is presented in this study to achieve the high efficiency of the tool condition and grinding quality. The relationship between the grinding quality, tool condition, …

Perspectives Of Corporate Instructional Design Experts On Effectiveness, Personal Traits And Attributes, And Technology, Thomas A. Gant

Theses and Dissertations

This qualitative phenomenological descriptive study explored corporate instructional design experts' perspectives on effectiveness, personal traits and attributes, and technology that enhance their expertise. Three central themes emerged: "Mastering Instructional Design: The Journey of Continuous Learning and Skill Development," highlighting the importance of mentorship, lifelong learning, and professional development; "Accessing Instructional Design Expertise Through Individual Strengths," emphasizing adaptability, problem-solving, and empathy; and "Navigating Technological Integration and Innovation in Instructional Design," showcasing the transformative role of tools such as virtual reality, learning management systems, and authoring software. Semi-structured interviews conducted via Zoom with 10 corporate instructional designers with at least 10 years …

Csc 22100 Software Development Laboratory Homework Assignment #1, Mitch Gershonowitz

Open Educational Resources

This is the first homework assignment for an Introduction to Java Programming course, which requires the students to write Java code using industry-accepted conventions. The assignment requires the student to write a Java method that accepts a date in an internationally-recognized format and returns a String object in Julian Date Format (JDF) with format YYDDD.

Csc 22100 Software Development Laboratory Homework Assignment #3, Mitch Gershonowitz

Open Educational Resources

This is the third homework assignment for an Introduction to Java Programming course, which requires the students to write Java code using industry-accepted conventions. The assignment requires the student to write a Java classes and interfaces that demonstrate usage of passing lambda expressions to methods, as well as demonstrating polymorphism and inheritance.

Nebraska Water Center Annual Report 2025

Nebraska Water Center: Administrative Materials

Training Nebraska's future water professionals, research publications, water sciences laboratory impact and know your well curriculums and community impact

Systematic Analysis Of Fatal Collisions Between Mobile Equipment And Pedestrian Workers To Inform The Use Of Proximity Detection Devices, Damien Burlet-Vienney, François Gauthier, Chantal Gauvin

Articles dans des actes de congrès

Context.

Collisions between mobile industrial equipment and pedestrian workers (PWs) are a major occupational health and safety concern, particularly on construction sites (e.g., during earth-moving operations). The use of driver aids, such as proximity warning devices designed to alert workers and drivers of potential collisions, is a growing and constantly developing avenue of prevention (e.g., AI-enhanced cameras; RFID tags). However, structured feedback to guide the implementation of these technologies on mobile equipment remains rare (e.g., technology choice, installation and settings).

Objective/Methodology.

 In this context, a systematic analysis of all fatal accident reports related to this issue for the province of …

Human Masters/Robot Servants: Highly Automated Vehicle Design, Intoxicated Drivers & Vicarious Liability, William H. Widen, Marilyn Wolf

Journal of Law and Mobility

A traditional engineering role is to design a safe product. Safety engineering is an exercise in harm avoidance ex ante. In contrast, liability attribution is an exercise to compensate for loss post hoc—traditionally viewed as a legal matter. We observe that, when a natural person incurs liability for a loss that exceeds insurance coverage, economic ruin can follow. Neither engineering nor law focus on the loss suffered by defendants considering law as a “safety risk.” The highly automated vehicle (HAV) design space, however, provides an opportunity to prevent this kind of economic harm from occurring ex ante just as attention …

How Inclusive Are Degree Programs In Operations Research And Analytics In The U.S.?, Michael P. Johnson Jr., Tayo Fabusuyi, Elham Hesari, Salina Chu

Public Policy and Public Affairs Faculty Publication Series

Academic programs in colleges and universities in the United States have increasingly embraced principles of equity and inclusion to support student success and diversity within professions. Innovations in diversity, equity, and inclusion (DEI) in university programs require baseline data on students, faculty and administrators, curricula, and programmatic support. A review of data shows that underrepresented groups in the US workforce have limited visibility in operations research and analytics. A review of DEI-related research reveals some relevant insights including a gap in studies specific to operations research and analytics.

To provide evidence in support of DEI initiatives in OR/analytics, we describe …

Nanomaterial-Enabled Enhancements In Thylakoid-Based Biofuel Cells, Amit Sarode, Gymama Slaughter

Center for Bioelectronics Publications

Thylakoid-based photosynthetic biofuel cells (TBFCs) harness the inherent light-driven electron transfer pathways of photosynthesis to enable sustainable solar-to-electrical energy conversion. While TBFCs offer a unique route toward biohybrid energy systems, their practical deployment is hindered by sluggish electron transfer kinetics, unstable redox mediators, and inefficient interfacing between biological and electrode components. This review critically examines recent advances in TBFCs, with a focus on three key surface engineering strategies: (i) incorporation of nanostructured materials to enhance electrode conductivity and surface area; (ii) application of redox mediators to facilitate charge transfer between photosynthetic proteins and electrodes; and (iii) functional exploitation of individual …

Improving Onboard Training For Deck Cadets : An Analysis Through The Lens Of Learning Theories, Yusuke Mori

World Maritime University Ph.D. Dissertations

As a critical component of skill development and identity construction for prospective seafarers, onboard training has played a central role in Maritime Education and Training (MET). Each Maritime Education and Training Institution (METI) implements distinct onboard training arrangements based on its environmental, socio-cultural, and historical context, as well as the learning theories that inform its approach. However, the absence of a rigorous examination of the factors influencing national variations in onboard training creates challenges in establishing legal norms at the international level. Furthermore, the literature has identified a wide range of issues and challenges in the implementation of onboard training, …

Effect Of Manufacturing Process On Mechanical Properties Of Polyetheretherketone (Peek) Cranial Implants Produced By Single-Point Incremental Forming (Spif), Elizabeth M. Mamros, Ihab Ragai, Brian Young

Faculty Conference Papers and Presentations

Polyetheretherketone (PEEK) is one of the most commonly used materials for cranioplasty due to its biocompatibility, relatively high strength, and light weight. Cranial implants manufactured from PEEK sheets using the same manufacturing process, e.g., single point incremental forming (SPIF), will have differing part properties based on the selected polymer forming process. Three fabrication methods for PEEK sheets were investigated: extrusion, modified hot pressing, and injection molding. Material characterization specimens were extracted for tensile, impact, and differential scanning calorimetry (DSC) experiments. The PEEK sheets were also subjected to formability tests at room temperature using SPIF. Slight differences in ultimate tensile strength …

Investigation Using Single Point Incremental Forming (Spif) To Fabricate Patient-Specific, Titanium Orbital Floor Implants, Elizabeth M. Mamros, Lauren E. Blaha Md, Christian A. Kauffman Md

Faculty Conference Papers and Presentations

The floor of the human orbit is composed of thin bone that is prone to traumatic fracture. This leads to a loss of support for the eye, which can cause vision changes. Therefore, fractures may need surgical reconstruction using a thin, sheet-like implant. Titanium implants are available off-the-shelf in standard sizes, but fitting to each patient’s unique anatomy requires surgeons to cut, file, and bend these plates. This can be time-consuming and imprecise. To both save time and ensure a perfect fit for the patient, a custom plate can be created prior to surgery. This investigation focuses on single-point incremental …

The Effect Of Participation In A Place-Based Engineering Learning Experience On Engineering Career Aspiration Of Nebraska’S Rural Students: A Mixed Method Study, Samereh Soleimani Babadi

Department of Agricultural and Biological Systems Engineering: Masters Project Reports

This study investigates the influence of a place-based, hands-on engineering learning experience on rural middle school students' engineering career aspirations, using Social Cognitive Career Theory (SCCT) as a framework. Employing a mixed-methods approach, we explored how these localized learning experiences shape students' career goals through socio-cognitive factors such as self-efficacy, outcome expectations, goals, and interest. Quantitative analysis of pre- and post-activity surveys revealed significant increases in career aspiration scores, particularly among students from farming backgrounds and female students with initially lower expectations. Path analyses indicated that self-efficacy and interest were the strongest mediators between Place-based learning and engineering career aspirations. …

Bot Detection In Social Media Using Graphsage And Bert, Abhishek Deshmukh

Master's Projects

This project details a novel bot detection system developed to battle the ever- changing challenge of disinformation, misinformation, and other bot-generated content.

The methodology employed in this project combines the text-based analytical strength of BERT (Bidirectional Encoder Representations from Transformers) with the strength of GraphSage (Graph Sample and Aggregation) for analyzing network structures. The project concatenates BERT and GraphSage vectors to create an 896-size feature embedding with a rich blend of network and text features. This project employs a Support Vector Machine to process the concatenated embeddings, as SVM works well with high-dimensional data. This project was evaluated on two …

Multimodal Feature Fusion And Machine Learning For Adhd Detection Using Neuroimaging Data, Isabel Pham

Master's Projects

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopment disorder that can significantly affect a person’s attention, impulse control, and executive function. Currently, the traditional diagnosis method often relies on clinical assessments and observations. However, these methods can be subjective and lead to inconsistencies in diagnosis between individuals. To address this challenge, neuroimaging and machine learning (ML) are promising tools for providing a more objective diagnosis of ADHD. The goal of this project is to apply a multimodal approach in which structural and functional features of specific regions of the brain are used to develop a more accurate and objective …

Adaptive Cobot Interaction Via Smartwatch Data Fusion For Car Assembly Automation, Riddhik Tilawat

Master's Projects

In modern car manufacturing, collaborative robots (cobots) work with human operators during shared workcell interactions to maximize production speed and flexibility. Collaboration between humans and robots is safe and effective only when operator intent recognition via a single wrist-worn inertial measurement unit (IMU) is accurate and low-latency. This thesis develops an IMU-only intent recognition pipeline, and is evaluated on three datasets: the public OPPORTUNITY dataset, the Sony Smartwatch Gesture dataset and a custom Samsung Galaxy watch 6 dataset. The proposed framework leverages five step sequence-to-label problems which are stepwise posed as data streams transforming raw IMU data into trainable tensors. …

Simple Vs. Complex Human Activity Classification Via Hybrid Machine Learning Models, Anusha Kukreja

Master's Projects

In-depth understanding of the complexity of daily human activities is crucial for building responsive health monitoring and assistive technologies. However, limited research has focused on distinguishing activities based on their involvement level, as most existing work classifies only the type of activity performed. In this thesis, we address this gap by proposing a method to classify human activities as either simple or complex using sensor data from the Opportunity dataset. We define complex activities as those involving object interactions or multiple coordinated movements (e.g., drinking from a cup, cleaning a table), and simple activities as static or low-effort postures (e.g., …

Visionmate: Ai-Powered Image Captioning Web Application, Sai Anoushka Kokku

Master's Projects

VisionMate is a web application that generates captions for camera-captured images. It is designed
to assist users with visual impairments by converting visual input into spoken and written text. The
application uses the GIT-base model from Hugging Face, which processes the image and returns a
descriptive caption. Users can take a picture using the device camera—either via webcam on
desktop or the native camera interface on mobile. The app provides audio output using the
SpeechSynthesis API and uses full-screen tap interaction to simplify accessibility.

The frontend is implemented in React.js, and the backend is built with FastAPI. The backend calls …

Phishing Detection Using Continual Learning And Large Language Models, Gopi Prajeev Battula

Master's Projects

Adaptive phishing detection remains crucial as the nature of cyber-attacks changes over time, which renders static models obsolete. This project extends phishing detection through the implementation of continual learning approaches, namely Elastic Weight Consolidation (EWC) and Learning Without Forgetting (LWF) with RoBERTa, a Large Language Model (LLM) and compares the results of these approaches against GPT-4o-mini, another LLM. Our approach begins with fine-tuning RoBERTa on multiple phishing datasets to establish an effective baseline. EWC is then implemented to preserve vital model parameters based on their importance measured by the Fisher Information Matrix, while LWF uses knowledge distillation to retain prior …

On The Adversarial Robustness Of Quantized Neural Networks Against Common Adversaries In Time-Series Forecasting, Maanak Arora

Master's Projects

Real-world edge applications now use modern machine learning models which require both resource efficiency and robustness against adversarial threats. Deep neural networks which include time series forecasting models still face risks from adversarial perturbations while quantization techniques used for memory and compute efficiency create unpredictable robustness challenges. This project investigates the adversarial resistance of Long Short-Term Memory (LSTM) models after applying post-training quantization at three different precision levels: 16-bit floating point (FP16), 8-bit integer (INT8) and custom 4-bit quantization. The Jena Climate dataset serves as our main benchmark for training a fullprecision LSTM model followed by multiple quantization strategies which …