Digital Commons Network^™

Spatiotemporal Deep Learning To Forecast Storm Surge Water Levels And Storm Trajectory: Case Study Hurricane Harvey, Junqin Hou, Muhammad K. Akbar, Manar D. Samad, Lizhi Ouyang

Mechanical and Manufacturing Engineering Faculty Research

No abstract provided.

Non-Invasive Wearables In Pediatric Healthcare: A Comprehensive Review Of Uses And Implications, Kyra-Angela Magsayo, Seyedeh F. Khatami Firoozabadi

Pacific Faculty Work

Wearable technology is rapidly evolving, with increasing efforts to integrate a wide range of sensors capable of capturing real-time physiological and behavioral health data from users. These devices have shown significant promise in supporting health monitoring and promoting well-being by providing continuous, objective feedback based on data analytics. Importantly, they enable early detection of potential health issues, allowing for timely intervention and more personalized healthcare. While a wide variety of commercially available wearable devices are designed for adults—tracking metrics such as physical activity, heart rate, body temperature, electrocardiograms (ECG), and oxygen saturation—there remains a notable gap in the availability and …

Novel Biomolecule-Infused Gelatin Injectable For Treatment Of Recurrent Laryngeal Nerve Injury, Ananya Tadikonda, Sunjay Anekal, Lena W. Chen, Gabriel Sobczak, Troy Wesson, Carmilya Jackson, Marisa A. Egan, Julie C. Liu, Patrick R. Finnegan, Stacey Halum

School of Chemical Engineering Faculty Publications

Objective

Unilateral vocal fold paralysis (UVFP) due to recurrent laryngeal nerve injury (RLN) is a major cause of voice disorders. We have recently identified three biomolecules (agrin, acetylcholine, and neuregulin) with the potential to promote reinnervation after RLN injury. This study aimed to determine if a gelatin injectable with the reinnervating biomolecules will induce site-specific amplification of neurotrophic factor release and reinnervation after RLN injury in unilateral vocal fold paralysis.

Methods

C57BL/6 mice underwent RLN transection with the following treatment allocations: saline control (N = 16), biomolecule cocktail only (N = 16), and biomolecule-infused gelatin (N = …

Experimental And Numerical Investigation On The Effect Of Projectile Mass And Apex Angle On Penetration Depth Into Sandy Soils, Abdul-Rahman K. Osman, Ahmed Elshesheny Dr, Mohamed S. Zahran Dr, Nabil M. Nagy Prof.

Journal of Engineering Research

Projectile penetration in granular soils remains a critical concern in defense engineering and ballistics research. This study presents an experimental and numerical investigation of rigid cone-tip projectile penetration into very dense sand, examining the influence of apex angle and projectile weight on penetration depth. Laboratory experiments were conducted using metallic projectiles with apex angles of 10°, 30°, 60°, and 90° and weights of 2.445, 3.87, 5.33, and 6.81 kg, dropped from a height of 4.295 m into a 500×500×500 mm wooden tank filled with sand to 400 mm height at 95% relative density. Through systematic testing, two empirical correlation …

Enhancement Of The Received Signal Strength In Smart Grid Communication Systems, Doaa Talaat Elsherbiny, Mona Mohamed Shokair Prof., Mohamed Shalaby, Salah Elden Khamis, Sameh A. Napoleon

Journal of Engineering Research

Smart grids are networks that contain intelligence from the generation stage to the distribution stage. These grids can actually have excellent power efficiency and automated control thanks to intelligence. Within smart grids, the communication mechanism is a crucial area of study. There should be a dependable communication system in the smart grid. A comprehensive mathematical model for a communication system within smart grids is derived in this work. Additionally, the simulation findings validate the mathematical model that was derived. Additionally, experiments are being conducted to apply polar convolutional parallel code PCPC to enhance the performance of the suggested communication system. …

Comparative Evaluation Of Change Detection Techniques In New Alamein City Using Sentinel-2 Satellite Imagery, Mohammed Adham Elsharkawy, Hafez Abbas Afify, Samah Ramadan Abo Ramadan

Journal of Engineering Research

The rapid growth and development of newly established cities has created a pressing need for effective tools to monitor and manage land use and land cover changes in these emerging urban centers. Remote sensing and change detection techniques offer valuable capabilities for assessing urban development, making them essential for providing insights into the spatial and temporal dynamics of modern cities, such as New Alamein City. New Alamein city is a newly integrated city located in the heart of the northwestern coast of Egypt, along the international road (Alexandria–Matruh), within the administrative boundaries of Marsa Matruh Governorate. New Alamein city is …

Analyzing Temporal Morphometric Changes In River Nile's Forced Bends Via Rs/Gis Methods: A Case Study Of The Damietta Branch In Egypt, Reham Abdel-Bar Aborahma, Ibrahim Rashwa, Asaad Matter Armanuos

Journal of Engineering Research

River Nile, among the world's longest rivers, features the crucial Damietta branch in Egypt, serving as a vital irrigation source and navigation pathway from Cairo to the Mediterranean Sea. Post the Aswan High Dam's construction, significant morphological shifts occurred in this branch, particularly impacting sedimentation and erosive patterns, notably at river bends. This study investigates the long-term morphometric evolution of six forced bends along the Damietta branch of the Nile River from 1987 to 2015 using remote sensing (RS) and geographic information system (GIS) techniques. Three image classification methods—onscreen digitizing, maximum likelihood classification, and histogram thresholding—were compared for shoreline delineation …

Design And Performance Analysis Of A Frequency-Reconfigurable Rectangular Patch Antenna With Dual-Slot Defected Ground Structure For Gsm Band, Sara Abdelbaset, Ashraf Khalaf, Amr Hussien, Ahmed A. Kabeel

Journal of Engineering Research

In this paper, an innovative frequency-tunable rectangular patch antenna is presented, featuring interlaced circular and U-shaped narrow slots, combined with a rectangular-shaped defected ground structure (DGS). This design is specifically developed to produce radiation patterns similar to those of traditional dipole antennas. The integration of the rectangular DGS with three RF varactor diodes, along with two equivalent microstrip conductors, enables a tunable operating frequency band that ranges from 1.08 GHz to 1.7 GHz, achieving a total bandwidth of 0.62 GHz. The DC biasing network connected to the three RF varactor diodes is utilized to finely tune and adjust the resonance …

Design And Implementation Of A Smart Solar Tracking System Using Hydraulic Actuation, Bassem Nashaat Zakher, Mahmoud M. Ramzi, Kirolos A. Amin

Journal of Engineering Research

This research presents the design and implementation of a smart single-axis solar tracking system that introduces a novel integration of hydraulic actuation with minimalistic sensor control. Unlike traditional trackers that rely on multiple light sensors and complex mechanical setups, the proposed system uses a simplified control mechanism driven by a single-point light detection strategy to maintain panel alignment with the sun. The core innovation lies in replacing motor-driven tracking mechanisms with a hydraulic actuator, offering smoother, more durable movement with reduced maintenance. Additionally, the system integrates smart monitoring via Arduino, enabling real-time data processing and decision-making without relying on costly …

Development Of A Water Temperature Modeling Platform To Support Short- And Long-Term Water Temperature Management In Reservoir-River Systems, Michael Deas, Yung-Hsin Sun, John Degeorge, Benjamin T. Saenz, Thomas A. Evans, Scott Burdick-Yahya, Stephen Andrews, Jeff Schuyler, William Candy, Lin Zheng, Scott Wells, Multiple Additional Authors

Civil and Environmental Engineering Faculty Publications and Presentations

The U.S. Department of the Interior, Bureau of Reclamation (Reclamation) supports water temperature management for fishery species protection in downstream river reaches below Central Valley Project (CVP) reservoirs in the Sacramento, American, and Stanislaus River systems. The Water Temperature Modeling Platform (WTMP) Project was initiated to modernize and enhance modeling capabilities to predict summer–fall water temperature through reservoir cold water pool management using temperature control facilities designed for temperature management. The WTMP supports forecasts, historical analyses, and long-term planning efforts and advances previous modeling approaches by using an integrated modeling platform. This platform includes a data management system that acquires …

Ontology Features-Based Arabic Text Augmentation Using Word2vec, Enas Tariq Khudair, Onsa Lazzez, Mourad Zaied, Tarek M. Hamdani, Ahmed T. Sadiq, Habib Chabchoub, Adel M. Alimi

Iraqi Journal for Computer Science and Mathematics

Text augmentation plays a major role when data is scarce. In this context, there are few Arabic news texts for specific purposes, and hence, there is a dire need to generate Arabic text, especially news. This paper presents an enhanced approach to Arabic text augmentation based on Arabic ontology features. The Arabic part of speech, particularly adjectives, verbs, and prepositions, and the ontology properties regarding such parts to create new texts, make up the first stage of the system, which has multiple stages. Word2Vector (Word2Vec) plays a pivotal role in giving Arabic ontology features to the specific Arabic Part of …

Leveraging Computational Modelling/Simulation, Machine Learning, And Additive Manufacturing For Customized Design Of Periodontal And Bone Tissue Scaffolds, Rakesh Pemmada

All ETDs from UAB

The current dissertation presents an overarching pipeline for the development and production of custom-made scaffolds for periodontal tissue regeneration using finite element analysis (FEA), machine learning (ML), and additive manufacturing (AM).CAD anatomically realistic scaffolds were generated from CT-based maxilla and mandible models. The FEA simulation results under masticatory (100 N), parafunctional (500–550 N), and traumatic (800–850 N) loads showed region-specific distribution of stresses and strains, which guided structural reinforcement strategies. Over 1000 3D-printed PCL scaffolds were printed using various pore diameters (200–300 µm) and filament diameters. Five ML models were constructed for predicting print quality based on process factors. Classification …

Self-Organization In Metal Plasticity: An Ilg Update †, Avraam Konstantinidis, Konstantinos Spiliotis, Amit Chattopadhyay, Elais C. Aifantis

Michigan Tech Publications

In a 1987 article of the last author dedicated to the memory of a pioneer of classical plasticity Aris Philips of Yale, the last author outlined three examples of self-organization during plastic deformation in metals: persistent slip bands (PSBs), shear bands (SBs) and Portevin Le Chatelier (PLC) bands. All three have been observed and analyzed experimentally for a long time, but there was no theory to capture their spatial characteristics and evolution in the process of deformation. By introducing the Laplacian of dislocation density and strain in the standard constitutive equations used for these phenomena, corresponding mathematical models and nonlinear …

Energy-Aware Optimal Reconfiguration Of A Heterogeneous Connected And Automated Vehicle Cohort On A Limited-Access Highway, Pruthwiraj Santhosh, Darrell Robinette, Daniel Knopp, Jeffrey Naber, Jungyun Bae

Michigan Tech Publications

This paper presents an optimized vehicular reordering methodology designed to minimize energy consumption within heterogeneous cohorts operating at constant velocity on limited-access highways. The approach addresses the challenge of optimizing vehicle sequencing by considering both aerodynamic drag reduction benefits and the energy costs of reconfiguring a cohort from a stochastic initial state. This study provides empirical validation through on-road vehicle tests, demonstrating significant energy savings, achieving up to 10% reduction in axle energy for optimally configured cohorts compared to independent operation. A System of Systems (SoS) simulation environment, integrating micro-traffic, validated powertrain, and aerodynamic drag reduction models, was developed to …

Terra Lunaris: Assessment Of A Lunar Habitat For Scientific Astronauts, Space Miners, Or Space Tourists, Dirk Schumann, Robert A. Goehlich

Publications

This conceptual paper explores ground- based habitable space modules for various applications. The Terra Lunaris concept serves as the baseline and is evaluated in comparison to existing and theoretical studies in this field. Terra Lunaris is a compact hybrid habitat that expands to offer nearly four times its transport volume by combining rigid modules with an inflatable shell. With most interior elements pre-installed and foldable, setup time and complexity are minimized. The design integrates technical zones, living quarters, and shared spaces, while also supporting psychological well-being under extreme conditions. The paper provides both qualitative and quantitative analyses of lunar habitation …

Developing Workflows For Passive Acoustic Detection Of Bedload Transport, Quinn Morgan

Dissertations and Theses

Bedload transport is defined as the amount of sediment, including gravel and rocks, traveling down stream. Monitoring bedload transport is important for river safety, hydrological studies and conservation efforts. Existing methods of directly measuring bedload transport (or bedload flux) involve lowering a collection device into a river and measuring the sediment collected; which can be expensive and time consuming. Hydroacoustic sensors, such as hydrophones, have had success tracking bedload flux remotely. This works by measuring the relatively high frequency of sediment impacts to map onto total bedload transported. No perfected method for detection of sediment generated noise (SGN) currently exists. …

A Polar Turbulence Invariant Map With Applicability To Realisable Machine Learning Turbulence Models, James G. Wnek, Christopher Schrock, Eric M. Wolf, Mitch Wolff

Mechanical and Materials Engineering Faculty Publications

Invariant maps are a useful tool for turbulence modelling, and the rapid growth of machine learning-based turbulence modelling research has led to renewed interest in them. They allow different turbulent states to be visualised in an interpretable manner and provide a mathematical framework to analyse or enforce realisability. Current invariant maps, however, are limited in machine learning models by the need for costly coordinate transformations and eigendecomposition at each point in the flow field. This paper introduces a new polar invariant map based on an angle that parametrises the relationship of the principal anisotropic stresses, and a scalar that describes …

Detecting Electrical Submersible Pump (Esp) Failures And Estimating Run Life Using Artificial Neural Networks, Mostafa Ahmed Sobhy

Theses and Dissertations

Electric Submersible Pumps (ESPs) are one of the important artificial lift methods for sustaining production in mature and high-water-cut wells; but may suffer frequent failures due to mechanical, electrical, hydraulic, chemical, and operational failures. These failures can yield substantial deferred production and intervention costs. Plenty of ESP installations are fitted with downhole sensors. Yet, it is observed that the current industry practice underutilizes the wealth of available sensor and operational data and lacks standardized, explainable failure-type identification and classification.

In this thesis, a comprehensive Machine Learning (ML) and Deep Learning (DL) framework was introduced for ESPs that simultaneously estimates remaining …

Evaluation Of User Interactions And Preferences Of Shared Bicycle And Pedestrian Transit Platforms, Nathan Mcneil, Sirisha Kothuri, Jennifer Dill, Chris Monsere, Elizabeth Yates, Julia Plotts

Civil and Environmental Engineering Faculty Publications and Presentations

Shared bike and bus platforms have been deployed in an effort to minimize conflicts between bicycles and buses (and other motor vehicles) on streets with bike lanes and bus transit service. This paper assesses bicycle/micromobility user and pedestrian behavior in shared bicycle and transit platforms along a bus rapid transit corridor in Portland, OR. Research objectives include understanding interactions between these users and potential conflicts between people on foot (or wheelchair/mobility devices) who are waiting for, boarding, and/or alighting a bus and people on bicycles riding in the bike lane. The research also assessed how well the shared transit platforms …

A Framework For Test Planning Of A Vision System Supporting Aerial Refueling, Jonathon K. Parry, Donald H. Costello, Michael D. M. Kutzer, Charles J. Doherty, Sarah M. Hubbard

Journal of Aviation Technology and Engineering

This essay presents a framework for evaluating a computer vision system providing perception for an uncrewed aircraft completing the automated air-to-air refueling (A3R) task. As the Department of Defense acquires capabilities that exhibit increasing levels of autonomy, the test and evaluation community must adapt the current framework to provide airworthiness officials the information required to accurately access the risks associated with the system underdoing testing. Following a brief introduction to A3R, this essay lays out a testing framework that leverages dendritic analysis and effectively deconstructs the critical issue into measurable data elements that can be used to support test and …

Ada-Application Of Decision Analysis For Developing A Healthcare System To Predict Fetal Health, Melfi Alrasheedi, Theyazn.H.H Aldhyani

Iraqi Journal for Computer Science and Mathematics

A fatal health condition involves an unborn baby that persists throughout the embryonic stage until delivery. The fetus grows and develops during each trimester of pregnancy. Obstetricians may detect fetal anomalies and select medical interventions based on cardiotocogram (CTG) data. However, the obstetrician's visual assessment of CTG data can sometimes be subjective or inaccurate. Therefore, automated analysis using machine learning approaches for CTG data is essential. This research employs decision analysis techniques, including decision trees (DT), gradient boosting (GB), and type-2 fuzzy neural networks (FNN), for prenatal analysis and prediction. The system was tested using a standard dataset consisting of …

Memf-Net: A Mega-Ensemble Of Multi-Feature Cnns For Classification Of Breast Histopathological Images, Alaa Hussein Abdulaal, Ali H. Abdulwahhab, Aqeel Majeed Breesam, Zahra Hasan Oleiwi, Riyam Ali Yassin, Morteza Valizadeh, Saja Nafea Mohsin

Iraqi Journal for Computer Science and Mathematics

Pathological anatomical images play a pivotal role in diagnosing diseases, notably breast cancer, which affects women globally. These images, obtained through biopsies or post-mortem examinations, are preserved to maintain their structural integrity. Software tools, like computer-aided diagnosis, aid doctors in early detection and treatment planning, contributing to reduced mortality rates. In this context, convolutional neural networks (CNNs) have emerged as valuable tools for diagnosing benign and malignant breast cancers. This paper introduces a Mega Ensemble Net method, leveraging multi-scale combination features on the breast histopathology dataset. Three fine-tuned deep learning models, namely ResNet-18, ResNet-34, and ResNet-50, are integrated into this …

Retracted: Capsule Network Model For Detecting Spoofing Attack In The Internet Of Medical Things (Iomt), Mohammad A. Alsharaiah, Mohammed Amin Almaiah, Mansour Obeidat, Rami Shehab

Iraqi Journal for Computer Science and Mathematics

The Internet of Medical Things (IoMT) has transformed healthcare delivery through real-time monitoring and data exchange. However, this integration of smart medical devices has also introduced critical cybersecurity threats, particularly spoofing attacks, which can compromise patient safety and system reliability. Conventional Intrusion Detection Systems (IDS) often fail to address IoMT-specific challenges such as class imbalance, computational constraints, and the need for real-time adaptability. This study proposes a Capsule Network (CapsNet)-based IDS that leverages spatial dependency modeling and hierarchical feature relationships to detect spoofing attacks in IoMT environments. Using the CICIoMT2024 dataset, we implemented a binary classification framework where spoofing instances …

Optimizing Beer Fermentation Through Intelligent Control, Azizbek Nodirbekovich Yusupbekov, Mirjalol Yusupov

Chemical Technology, Control and Management

This paper presents an intelligent control approach for optimizing the beer fermentation process using fuzzy logic and adaptive neuro-fuzzy inference systems. By incorporating multivariable inputs—temperature error and pH deviation—the proposed system effectively handles the nonlinear dynamics and biological variability inherent in fermentation. Simulation results demonstrate improved control accuracy, responsiveness, and robustness compared to conventional methods, making the approach suitable for integration in modern brewery automation systems.

Modeling Of Urea Drying And Granulation Process In Fluidized Bed, Jalolitdin Pakhritdinovich Mukhitdinov, Aleksey Viktorovich Schulz

Chemical Technology, Control and Management

This article is devoted to the mathematical modeling of urea drying and granulation processes in a fluidized bed. A brief description is provided for the functional blocks included in the mathematical model, along with the required parameters that form an integrated representation of the technological process. The SR-POLAR model is used to describe a phase equilibrium between the components involved. The interconnections between functional blocks are shown in the process flow diagram. Block diagrams for modeling a multi-chamber granulation unit and the cooling system for the resulting granules are presented. Granule growth in the fluidized bed is described using a …

Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems, Elbek Ortiqov

Chemical Technology, Control and Management

This article investigates various methods and tools for self-monitoring and fault tolerance in flow measurement transducers used in industrial processes. The study focuses on key techniques such as the use of redundancy, generation of reference values, analysis of measurement signals, and control of disturbance variables. These methods allow transducers to detect potential faults, ensure reliable operation, and maintain measurement accuracy even under adverse conditions. The article highlights how self-monitoring contributes to improving system safety, increasing reliability, and reducing downtime. It also discusses the integration of intelligent monitoring systems that support predictive maintenance and real-time diagnostics. Fault-tolerant sensors with self-monitoring capabilities …

Synthesis Of A Control System For Thermal Energy Facilities Using The Quantum Photon Spin Method, Isomiddin Siddikov, N.S Yakubova

Chemical Technology, Control and Management

Increasing energy efficiency and reducing fuel consumption in the process of generating electricity and heat at thermal power plants is one of the urgent tasks. Such systems operate under conditions of random changes in external and internal influences, as well as measurement uncertainties, which reduce the quality of control. In order to overcome this problem, it was proposed to develop an intelligent control system using the quantum photon-spin method to control technological units of thermal power plants. In the proposed approach, a multi-dimensional heating boiler device was taken as a control object, and the simulation modeling of the control system …

Increasing The Robustness Of A Control System For A Complex Dynamic Plant By Correcting Nonlinearity In The Warping Process, Tukhtamurod Khayitmurodovich Avezov, Zokhid Ergashboyevich Iskandarov

Chemical Technology, Control and Management

The paper discusses the challenges of enhancing the robustness of a control system for a complex dynamic plant by addressing nonlinearity in the warping process. Devices that ensure the stability of the control system against parameter non-stationarity on the warping machine are referred to as state controllers. The operating principle of these devices relies on providing artificial nonlinearity to the rear connection circuit of the control system's actuator. However, this nonlinearity is implemented using components that consider the parameters of low control quality. Therefore, it is necessary to continuously adjust the nonlinearity parameters to, on one hand, reduce the load …

Retracted: Automated Diagnosis Of Orthopedic Patients With Vertebral Column Disorders Using Advanced Mathematical Modeling, Chen Feng, Zhenhua Sun, Xinheng Dai, Hongli Wen

Iraqi Journal for Computer Science and Mathematics

Orthopedic disorders are multifactorial, making accurate diagnosis a significant challenge. This study introduces a novel method for classifying patients into three categories—normal, disc herniation, and spondylolisthesis—using biomechanical parameters derived from diagnostic datasets. To enhance classification accuracy, two meta-heuristic optimization algorithms—the Zebra Optimization Algorithm (ZOA) and Chaos Game Optimization (CGO)—are integrated with Adaptive Boosting (ADAC) and Light Gradient Boosting Machine (LGBM) classifiers. The experimental results reveal that ZOA significantly improves model performance, particularly in the ADAC classifier. The baseline ADAC model achieved a mean accuracy of 0.916, which increased to 0.952 after optimization with ZOA (referred to as the ADZO model). …

Deep Learning And Texture Analysis For Lung And Colon Cancer Predicting, Mohamed M. Neamah, Laith A. Al-Ani, Loay E. George

Iraqi Journal for Computer Science and Mathematics

Cancer remains a major cause of death worldwide, with lung and colon (LC) cancers presenting significant challenges to healthcare systems due to their high rates of occurrence and mortality. Early and precise diagnosis is essential for better patient outcomes. This research utilizes recent advances in deep learning (DL) and texture analysis (TA) to create a reliable predictive model for detecting LC cancer through histopathological images (HPI). A hybrid method is proposed that combines a gray-level co-occurrence matrix (GLCM) for extracting texture features with an adaptive modified EfficientNet B2 model (AM-EfficientNet B2) for deep feature extraction. These features are used to …