Digital Commons Network^™

Internet Of Things For Sustainable Transportation Systems, Ayodeji Akinsoji Okubanjo, Ignatius Kema Okakwu, Oluyinka Esther Olaifa, Matthew Babatunde Olajide, Olufemi Peter Alao, Olayiwola Abisola

Al-Mustaqbal Journal of Sustainability in Engineering Sciences

This paper highlights the opportunities for the Internet of Things in the transportation industry. The need for the Internet of Things and its architecture to address various complex challenges in the transportation sector are discussed. Various smart applications of the Internet of Things and its noticeable benefits over the existing technology are well articulated. In addition, the role of new and emerging technology such as artificial intelligence, machine learning, big data, cloud, data storage, and analysis for future sustainable transportation are highlighted with specific cases. Furthermore, smart areas of the Internet of Things in transportation are pictorially discussed. In addition, …

Improving The Methodology Of Complex Organization Of Rural Areas Based On Gis Technologies, Anvarjon Pardaboyev

Technical science and innovation

In the world, scientific research is being conducted aimed at improving the efficiency of complex organization of rural areas by utilizing modern geographic information systems (GIS) and remote sensing data. These studies focus on shaping the land allocated to these areas, organizing their activities, and forming the basis of cartographic information. Additionally, the use of modern GIS and remote sensing data has become widespread in the complex organization of rural areas in many countries. This method stands out for its effectiveness in organizing regions today.

In our republic, comprehensive measures are being implemented to consistently develop production through structural, institutional, …

Training Stages And Algorithms Of Multilayer Neural Networks For The Control System, Abdishukurov Maqsudovich Shavkat, Xuecheng Li

Technical science and innovation

The application of neural network technologies in control systems consists of several stages. In technological object control systems, each layer of the multilayer perceptron neural networks is represented using separate transfer functions. The result of synthesizing neural network technology into control systems allows for the rapid solution of many problems. Using neural network technology, it is possible to perform many calculations. Chain rules of neural networks are added this paper. Lots of training algorithms are compared to choose better to train network. Backpropagation neural networks is seen deeply in the last page. Problems of interpolation and extrapolation are solved. Algorithms …

Unveiling Degradation Patterns In Dye-Sensitized Solar Cells: A Machine Learning Perspective, Ahmed Alali, Mahmoud Ashraf, Ahmad Muhammad, Sameh O. Abdellatif

Electrical Engineering

This study examines the time-dependent degradation of dye-sensitized solar cells (DSSCs) by systematically investigating several critical parameters, including TiO2 thickness, porosity, dye concentration, and iodine-based electrolyte concentration. We developed a novel figure of merit (FOM) to quantify the degradation rates, utilizing a finite element model (FEM) in COMSOL to simulate performance over time. 400 DSSC samples were fabricated, resulting in a comprehensive dataset comprising over 228,000 data points derived from experimental results and simulations. The findings reveal that PCE declines significantly over time, with an average initial efficiency of 4.0% for the DSSCs, dropping to approximately 0.5% after 360 h. …

Investigating Vacuum Insulator Flashover Resistance Of Rexolite And Acrylic Before And After Applying Novel Insulator Cleaning Techniques, Ritin Joseph

Electrical and Computer Engineering ETDs

Pulsed power involves accumulating large amounts of electrical energy and releasing it instantaneously. Large pulsed power accelerators use a vacuum insulator stack to facilitate power transfer from the liquid to vacuum section. Limiting the probability of surface flashover in this setting to acceptable levels improves machine longevity and prevents energy loss. Post-shot debris deposition requires a refurbishment process to prevent deterioration of dielectric performance, though the current technique of hand-sanding is long, labor-intensive, and pose serious health hazards. I have collected flashover data on frustrum-shaped Acrylic and C-Lec Rexolite® (cross-linked polystyrene) samples using a 500-kV, 20-ns risetime pulsed power test …

A Comprehensive Review Of Software Requirements Dependencies Analysis Techniques, Nahla Mohamed, Sherif Mazen, Waleed Helmy

Iraqi Journal for Computer Science and Mathematics

The software Requirements Prioritization (RP) process is essential for producing a successful software project. Requirements are interdependent in software projects, so handling their dependency during the RP process is mandatory. Many researchers have shown that requirements dependency is challenging for large-scale systems. Extracting requirements dependency is difficult since requirements are documented in natural language. Improper handling of dependencies among requirements while prioritization can cause inaccurate prioritization results and deadlocks, which cause project delays, rework, and redesign. Many techniques have been introduced to automate the dependency analysis process among software requirements, including artificial intelligence (AI) and other logic-based methods such as …

Enhanced Detection Of Intracranial Hemorrhage: A New Hybrid Model Design Based On The U-Net Segmentation Method, Hassan F. Hassan, Hadeel K. Aljobouri, Oktay Algin

Iraqi Journal for Computer Science and Mathematics

Intracranial hemorrhage (ICH) denotes bleeding inside the skull, which can occur in or around the brain. Computed tomography (CT) has been used to detect ICH due to its high efficiency and accuracy. Nowadays, deep learning model design is introduced to allow an accurate and efficient classification of ICH in CT images. This work focused on developing U-Net-based models for the segmenting of ICH. Furthermore, the proposed model employed two transfer learning models, MobileNet and Xception, as the backbones of the U-Net topology. This approach aims to establish metrics that improve ICH treatment through precise segmentation techniques. A free dataset from …

Retracted: A Novel Benchmarking Framework For Selecting The Best Deep Learning Model Diagnosing Covid-19 Based On New Development For Dual Mcdm Methods, Mahmood M. Salih, Yousif Raad Muhsen, M.A. Ahmed, Reem D. Ismael, Moceheb Lazam Shuwandy, Z.T. Al-Qaysi

Iraqi Journal for Computer Science and Mathematics

COVID-19 was diagnosed using deep learning models by a group of studies. Evaluating and benchmarking these models are essential to achieving the most suitable model for diagnosing coronavirus. Objective: In this investigation, we offer an inclusive valuation of several deep learning models to detect the maximum appropriate and active model which gratifies doctors' requirements and assessment criteria. Method: This study combines Fuzzy decision by the opinion score method (FDOSM) and Fuzzy-Weighted Zero-Inconsistency (FWZIC). According to the advantage of Trapezoidal Intuitionistic fuzzy, we developed FWZIC into Trapezoidal Intuitionistic fuzzy named (TrIF-FWZIC) for weighting criteria and FDOSM into Trapezoidal Intuitionistic fuzzy FDOSM …

الأمن السيبراني والذكاء الاصطناعي: حلول لإدارة أزمات البنية التحتية الرقمية, عبدالله سعد الغامدي

Journal of the Association of Arab Universities for Research in Higher Education مجلة اتحاد الجامعات العربية للبحوث في التعليم العالي

في ظل التحول الرقمي المتسارع، أصبحت إدارة الأزمات التقنية تحديًا استراتيجيًا يستوجب تبني حلول مبتكرة للحفاظ على استمرارية الأعمال وحماية البنية التحتية الرقمية. ناقشت هذه الورقة دور الأمن السيبراني والذكاء الاصطناعي في تعزيز قدرات المنظمات والجهات على التنبؤ بالأزمات والاستجابة لها بفعالية ، وتعتمد على منهجية تحليلية تجمع بين دراسة الحالات الواقعية وتحليل البيانات باستخدام تقنيات التعلم العميق Deep Learning ونظم الأمن السيبراني المتقدمة مثل SIEM وSOAR ومدى الاستفادة من دمج هذه التقنيات لتحسين زمن الاستجابة وتقليل معدل الهجمات الناجحة، مع التدليل على أمثلة من المملكة العربية السعودية والتي سجلت أكثر من 38 مليون محاولة هجوم سيبراني في عام 2024. …

Cognitive Diversity, The Keystone To Effective Ptd In The Medical Research And Medical Device Industries, John Gilmartin

ASEM Capstones

2025 ASEM 620 Capstone Project

Application Of Polymer Nanocomposites In The Design Of Prosthetic Sockets That Feature Auxetic Meta-Structures, Sumit Suryakant Kolte, Vinayak Vijayan, Lihua Lou

Publications

This research evaluates the response of prosthetic sockets constructed using polymer nanocomposites and incorporating auxetic meta-structures. The prosthetic sockets feature lightweight meta-structures between the inner and outer walls of the socket. Three different prosthetic designs featuring chiral, reentrant hexagon, and honeycomb meta-structures are evaluated in this study. The prosthetic sockets were designed in SolidWorks and compared using finite element analysis. The polymer nanocomposites used in this study include polypropylene and ultra-high molecular weight polyethylene containing uniformly distributed inclusions of either titanium dioxide, zinc oxide, or graphene nanoplatelets. Our results show a favorable pressure profile at the interface between the prosthetic …

Geophysical Tools For Agricultural Management: Trends, Challenges, And Opportunities, Sophia Becker, Trenton Franz, Yufeng Ge, Joe Luck, Derek M. Heeren

School of Natural Resources: Faculty Publications

Agrogeophysics is a convergence of proximal soil sensing and hydrogeophysics in which geophysical methods are used to describe soil patterns and dynamics that shape agronomic management (including precision agriculture). To fully realize its potential for optimizing agricultural production, current barriers and targets for future agrogeophysics research must be identified. In this review, we compare the trajectory of agrogeophysics within peer-reviewed literature, patents, and the US university extension literature and examine the current challenges and opportunities for supporting agricultural production and sustainability with agrogeophysical tools. We conducted a repeatable search of Web of Science and Scopus for seven geophysical methods (electromagnetic …

Aeolus-Ds: Dust-Aware Ai Decision Support For Coccidioidomycosis (Valley Fever) — A Design Science Research Framework Integrating Aerosol Remote Sensing, Land Disturbance, And Clinical Sentinel Signals, Harsha Sammangi, Aditya Jagatha, Harshini Balaga

Research & Publications

This paper presents Aeolus-DS, a design science research (DSR) artifact that integrates aerosol remote sensing (MAIAC AOD; dust fraction), mesoscale meteorology and soil moisture (ERA5), land-disturbance telemetry (construction, off-road vehicle activity, nightlights) and clinical sentinel signals (syndromic ED chief complaints, pneumonia rule-out) into a dust-aware, AI-driven early warning and decision-support system for Coccidioidomycosis (Valley Fever). Methodologically, we propose a graph spatiotemporal transformer with direction-aware attention and physics-guided regularisation reflecting aeolian transport. Using county-week panels (2014-2024) for the U.S. Southwest (AZ–CA–NV), Aeolus-DS improves now-casting mean absolute error (MAE) by 18% and two-week area under precision-recall curve (AUPRC) by 21% over …

Building Social Butterflies And Learning Circles: The Key To Organizational Safety Potential, Trevor Farr

ASEM Capstones

2025 ASEM 620 Capstone Project

Tkbe : Two Key Broadcast Encryption For The Iot, Rachit Parikh

Master’s Dissertations

The growing usage of the Internet of Things (IoT) has made it necessary to ensure

the security of these interconnected devices. Key management becomes particularly

challenging when devices are not always online due to resource constraints or business

decisions. Moreover, the IoT infrastructure typically relies on the publish-subscribe

model for communication, which raises additional security considerations since the

message broker becomes a central point of attack. Existing solutions with end-toend

encryption from publisher to subscriber are either computationally expensive for

resource constrained devices or compromise on the decoupling in publish/subscribe

systems. This thesis tackles the problem of efficient key management …

Sidesense: Robust Physiological Motion Detection Via Mmwave Joint Communication And Sensing Systems With Multiple Beams, Mohammed Shadman Ishrak, Jannatun Noor Sameera, Alvin Yang, Yanjun Pan, Yao Zheng, Olga Boric-Lubecke, Victor M. Lubecke

Electrical Engineering and Computer Science Faculty Publications and Presentations

A 28-GHz multibeam joint communication and sensing system called SideSense is presented, in which a line-of-sight (LoS) beam is used to maintain reliable communication, while other sensing beams are used to enhance physiological motion detection. SideSense decodes the motion frequency and shape from the channel state information (CSI) by first tuning the gain ratio and phase differences between the LoS communication beam and non-LoS (NLoS) beam to maximize the sensing signal-to-noise ratio (SSNR) without significantly degrading the communication channel capacity (CCC). Analytical results based on a bistatic model are presented to show a gain ratio of around 1 and a …

Differential Privacy Enabled Deep Skin Image Classification Model Development, Prasun Kumar Mandal

Master’s Dissertations

Abstract In the era of big data, the explosive growth in data volume has significantly accelerated the development of deep learning. Deep learning is the most promising area of AI, yielding significant advancements in medical image classification. However, healthcare data contains important sensitive information and so privacy and security are crucial to preventing unauthorized access. Note that there are several data protection rules from multiple regulations to penalize any kind of data security violation, for example, the data protection principles (Article 5.1-2) and the data protection by design and by default (Article 25) of the General Data Protection Regulation from …

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Ziad Khalifa, Kyrillos Selim, Amira Ali, Sameh Abdellatif

Chemical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)- based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a …

A Wearable-Based Approach To Spinal Posture Tracking And Assessment, Sydney Marie Sherman, Noah Jeffery

Biomedical Engineering: Graduate Reports and Projects

This paper describes the design, manufacturing, and testing of a novel spinal posture tracking wearable device with embedded sensors. Currently on the market, most of the spinal posture tracking devices only focus on one segment of the spine and therefore do not track the entirety of human posture. The objective for this project was to create a wearable device in the form of a “smart shirt” that offers insights into posture trends throughout the day by tracking the entire spine. To begin the project, multiple designs were developed for the sensor array and wearable materials. These concepts were compared against …

Ai Tools In Natural Resources And Environmental Systems For The Classroom, Research, Extension And Industry, Derek M. Heeren, C. T. Agouridis, Debabrata Sahoo, Isaya Kisekka, Trisha L. Moore

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

This white paper synthesizes a series of panel insights on AI adoption across education, Extension, research and industry contexts within natural resources and environmental systems. It emphasizes that while advanced machine learning and generative AI introduce structural shifts in autonomy, scale, and cognitive augmentation, their value lies in augmenting, not replacing, human expertise. Applied tool examples include decision‑support systems for rural water operators, HAB‑diagnosis apps integrating image classification and natural‑language guidance, an irrigation educational chatbot tailored to user background, and sensor‑driven orchard AI for light interception estimation and data gap filling. A recurring design imperative involves co‑development with end users, …

Data-Driven Methods For Signal Analysis And Nonlinear System Identification, Cristian Felipe López Ruano

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

In recent years, data-driven modeling has gained considerable attention in nonlinear system identification, offering a powerful alternative to traditional physics-based methods. This has been possible by advances in machine learning, sparse regression, and differential equations in a weak form, which allow the accurate capture of complex nonlinear dynamics, even when the measurements are in strong background noise. Moreover, integrating these models with physical knowledge further enhances their reliability and interpretability, making them suitable for a wide range of science and engineering applications.

In this dissertation, we investigate algorithms for data-driven nonlinear system identification to obtain ordinary differential equations that govern …

Biocomputing Approach To Modeling And Modulating Calcium Signaling, Sehee Sun

School of Computing: Dissertations, Theses, and Student Research

Biocomputing is an emerging field that seeks to perform computational tasks using biological substrates and processes. Unlike conventional computing systems based on silicon hardware, biocomputing leverages the parallelism, energy efficiency, and complex dynamics of living systems. Among various cellular mechanisms, calcium (Ca2+) signaling stands out as a central regulator of diverse biological functions, offering a promising basis for programmable logic and control in living cells.

This thesis introduces a novel framework for modeling and modulating Ca2+ dynamics using biologically inspired Boolean logic circuits. Specifically, we propose the Ca2+ Boolean Logic (CaBL) model, in which Ca2+ fluxes and interactions are abstracted …

Statistical Monitoring Of Hard Faults In Digital Systems, Dany Akshay Deep Isukapalli

Electrical Engineering Theses and Dissertations

Achieving a high test coverage is crucial for helping to ensure that integrated circuits are working correctly and are non-defective. Although scan-based structural tests are used throughout the industry, high-level functional tests may be needed to detect some defects— especially those that are environmentally sensitive. Unfortunately, the character of functional test makes it difficult to obtain high coverage, and it is even hard to estimate coverage because fault simulation times of large circuits are long. As a result, some method is required for predicting the ability of a functional test that has not been fault simulated to detect defects. In …

Ai Questions; "The Ai Tea", Sally Brown

Artificial Intelligence Exhibit

This section includes a series of questions related to AI and the exhibit content, as well as button designs by WVU students and Art in the Libraries committee members, a list of the exhibition sponsors, and information on the exhibition launch panel.

Artificial Intelligence In Education, Sally Brown, Jill Woods, Mohamed Hefeida, Jennifer Sano-Franchini, Megan Vendemia, Erin Brock Carlson, Megan Leight, Gangqing Hu, Nicole Fuller

Artificial Intelligence Exhibit

This section explores the intersection of AI and education, including an overview of WVU's AI statement and submissions from WVU faculty, classes, students, and staff on AI related projects.

Teaching Learning Newsletter Vol 5 Issue 1, Sastra Deemed To Be University

TLC Newsletter

No abstract provided.

Jme4110: Hydro-Excavator Robot, Diane L. Evans, Nathan Fenton, Grant Cole, Nicholas Sipe

Washington University / UMSL Mechanical Engineering Design Project JME 4110

In an environmental situation wherein, diesel has leaked into soil surrounding high voltage lines in an underground confined space where workers cannot access physically and for safety reasons. To alleviate the situation, the project goal is to create a remotely controlled robot, with umbilical attachments. Due to the nature of the environment containing sensitive and electrically charged equipment, mechanical means of removing the soil are not feasible. For this reason, the robot is to remove contaminated soil by using a powerful water sprayer and vacuum combination. Other options for features of this robot are that it uses tracks for movement, …

Jme 4110: Automatic Umbrella Opener, Sam Nieder, Adam Freeman

Washington University / UMSL Mechanical Engineering Design Project JME 4110

Manually opening and closing a patio umbrella can be time consuming and laborious. While there are remote controlled umbrellas for sale, they are expensive and may not be a reasonable option for most people. Our task was to create a device that can be retrofitted onto any patio umbrella, that allows it to be opened and closed remotely.

Jme 4110: Remotely Actuated Rail Switch, Calysta Yalew, Chibale Anwisye, Ron Almira, Andy Sengsavang

Washington University / UMSL Mechanical Engineering Design Project JME 4110

This project focuses on developing a device that will switch the direction of rail by moving the manual rail switch itself. This design consists of two winches strategically placed on either side of the rail switch. It is then attached to a beam clamped to the manual switch and via a button on a phone, can pull the handle left and right. With this device patrons are able to keep safe and railway operations would be more efficient.

Optimization Of Thermoelectric Energy Harvester To Power Wireless Onboard Bearing Health Sensors During Rail Service, Danna Cecilia Capitanachi Avila

Theses and Dissertations

This work presents the optimization of a thermoelectric energy harvester designed to supply power to a wireless onboard bearing health monitoring device for critical freight rail components. The study demonstrates an enhancement in the circuitry through the integration of an energy management subsystem (E-Peas AEM20940), which features a boost converter with lower self-start voltage. The harvesting system was tested on dynamic bearing test rigs to closely replicate field service conditions. Test plans were conducted using common freight speeds and loads to simulate a representative urban route. The thermoelectric energy harvester was able to operate at temperature differentials as low as …