Digital Commons Network^™

Reflecting On The Atu Assessment Hackathon: Exploring Assessment And Ai Through Collaborative Challenge-Based Learning, Noreen Henry, Nokuvimba Chiyaka, Olya Antropova

Teaching and Learning Together in Higher Education

No abstract provided.

Learning With Champions: Genai Champions Project Ireland, Rebecca Roper

Teaching and Learning Together in Higher Education

No abstract provided.

Faculty Senate Agenda December 1, 2025, Utah State University

Faculty Senate & Faculty Senate Executive Committee

• 3:00 Call to Order
• Approval of Minutes - November 3, 2025
• 3:05 University Business
• 3:20 Faculty Senate Business
• 3:30 Information
• EPC Report - November 6, 2025
• 3:45 Report
• Honors Program Annual Report
• USUSA Annual Report
• Faculty Evaluation Committee
• Academic Freedom and Tenure
• 4:10 Old Business
• 4:15 New Business
• Faculty Forum
• Adjourn: 4:30 pm

An Objective Method To Locate Shear Lines During The Northeast Monsoon Season In The Philippines, Lyndon Mark P. Olaguera, John A. Manalo, Jun Matsumoto, Faye Abigail T. Cruz, Jose Ramon T. Villarin

SOSE Affiliate: Manila Observatory

The shear line is a narrow zone of maximum horizontal wind shear, typically identified as a confluence zone of low-level wind streams. Previous studies showed that this system can trigger heavy to extreme rainfall events in the Philippines during the northeast monsoon season. However, a research gap remains in objectively identifying and locating this system. Thus, this study develops a detection method that may be used for monitoring and forecasting the location of shear lines. Results show that the gradient of meridional winds in the y-direction (∂V925hPa/∂y), the boundary layer moisture flux convergence, and the 925 hPa relative vorticity may …

The Influence Of Muskrats On The Biodiversity Of Wetlands, Emma Thornton

Biology Student Scholarship

Wetlands are one of the most productive ecosystems in the world and are home to various plant and animal species. The relationships between the species living in the wetlands keep the ecosystem functional as well as increasing biodiversity. Increased biodiversity of wetlands creates more resilient plant communities. Muskrats are ecosystem engineers, meaning that they alter their surroundings to change the quality and quantity of the available resources through behaviors related to their eating habits and their burrow construction. Muskrats are herbivores and consume large amounts of vegetation, which creates opportunities for more plant species by creating new ecological niches. In …

Comparative Analysis Of 2d And 3d Gait Metrics From Video Using Deep Learning Techniques, Akhilesh Singh Kushwaha

Electronic Theses and Dissertations 2020 - Present

This thesis presents a comparative evaluation of two deep learning-based methods for extracting 2D and 3D gait metrics from monocular video: a 2D-to-3D lifting approach combining AlphaPose for keypoint detection with MotionBERT for temporal 3D reconstruction, and a direct 3D estimation method using MeTRAbs. Videos of two healthy adults walking across a ProtoKinetics Zeno™ Walkway were captured laterally at 4K/60 fps using an iPhone 16. Ground-truth spatiotemporal gait parameters were obtained from the pressure-sensitive mat, enabling quantitative validation via Mean Absolute Error (MAE) and Pearson correlation. MeTRAbs consistently outperformed the lifting pipeline, achieving MAE below 2% for temporal metrics (e.g., …

Very Low Frequency Electromagnetic (Vlf-Em) Method As A Tool For Fault Investigation: Examples From İzmir, Türkiye, Meri̇ç Azi̇z Berge

Turkish Journal of Earth Sciences

The investigation of faults in active tectonic regions is of great importance in geosciences, and geophysical methods play a key role in their detection. In particular, determining subsurface characteristics related to faults and identifying palaeoseismological trench locations using geophysical methods are topics of significant research interest to researchers. The very low frequency electromagnetic (VLF-EM) method is one of the geophysical techniques employed to investigate such problems. This study presents the results of simulation and field investigations using the VLF-EM method for fault detection. The well-established Fraser and Karous–Hjelt filters, which are widely used and effective for fault detection, were applied …

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani

Turkish Journal of Electrical Engineering and Computer Sciences

Midair hand gesture recognition plays a crucial role in applications such as sign language recognition and human-computer interaction, particularly for supporting individuals with partial or complete hearing loss. However, recognizing gestures in midair remains challenging due to the rapid and complex nature of hand movements. To address this, noninvasive techniques like surface electromyography (sEMG)—which captures muscle activity through sensors placed on the skin—have gained attention. sEMG provides rich time-series data that reflect both spatial and temporal muscle dynamics. In this study, we propose a deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to classify …

Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition, Awais Ahmed

Turkish Journal of Electrical Engineering and Computer Sciences

Spoken digit recognition (SDR), a type of supervised automatic speech recognition, is essential for various human-machine interaction applications, including banking operations, dialing systems, price extraction, and airline reservation systems. However, designing an effective SDR system presents several challenges, such as developing labeled audio data, selecting appropriate feature extraction methods, and creating high-performance models. To overcome these challenges, a novel approach for robust spoken digit recognition using an integrated log spectrogram convolutional neural network (ILS-CNN) has been proposed. The proposed work presents an efficient SDR method by taking advantage of a log spectrogram layer directly within the neural network to enhance …

Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks, Ivan Kots, Alina Isaeva, Mark Denisenko, Alexander Sinyukin, Andrey Kovalev

Turkish Journal of Electrical Engineering and Computer Sciences

Monitoring the condition of engineering objects is one of the urgent tasks of industry, construction, and transport infrastructure. This article describes a system for condition monitoring and diagnostics of rail tracks in real time. Compared with other similar studies, the proposed system has the advantages of compactness, usability, scalability and versatility of application. The proposed monitoring system is based on an Nvidia Jetson Nano embedded computing board and also includes inertial sensor modules, a microphone, a geolocation module, communication modules, an SSD storage device, and a battery. The prototype of the diagnostic module is a portable device that can be …

Modeling And Simulation Of Dynamic Energy Management Systems For Smart Buildings, Onur Özel, Ali̇ Rifat Boynueğri̇, Hayri̇ Yi̇ği̇t, Burak Tekgün

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both …

Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach, Anis Feddaoui, Lotfi Farah, Abdelouahab Benretem, Mohammed Abdeldjalil Djehaf

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a novel power management strategy for wind farms using a grey wolf optimization (GWO)-based PI controller. The method aims to enhance active and reactive power control in systems employing dou bly fed induction generators. Three control strategies are evaluated—namely, a classical frequency-domain PI controller, an Artificial Neural Network (ANN)-based controller, and the proposed GWO-based PI controller—the last of which represents the main contribution. The classical PI and ANN controllers are included strictly for comparative bench marking. MATLAB simulations demonstrate that the GWO-beased PI controller offers superior dynamic performance, particularly in settling time and overshoot reduction. A power …

Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance, Büşra Ceni̇kli̇oğlu, İbrahi̇m Develi̇, Ayşe Eli̇f Canbi̇len

Turkish Journal of Electrical Engineering and Computer Sciences

A modernist technique, reconfigurable intelligent surface (RIS) provides outstanding signal reflection and amplification, making it highly valuable for upcoming communication systems. Besides, a major contributor is index modulation (IM), attaining superior spectral and energy efficiency, and achieving hardware sufficiency. The primary and novel contribution of this work is the derivation of a highly accurate, closed-form approximate expression for the average bit error rate (ABER) of an orthogonal frequency division multiplexing (OFDM)-IM system operating in the complex and challenging environment characterized by joint transmitter/receiver (Tx/Rx) in-phase and quadrature phase imbalance (IQI) and Weibull fading. This essential analytical achievement is facilitated by …

Impact Of Adaptive Filtering-Based Noise Reduction On The Quality Of F-C Images In Masw, Doğukan Durdağ

Turkish Journal of Earth Sciences

This study investigates the effects of adaptive filtering, based on the least mean square algorithm, on the quality of multichannel analysis of surface waves (MASW) data and frequency-phase velocity (f-c) images. Specifically, the adaptive filtering method aims to decrease the noise and improve the determination of fundamental modes in f-c images. Both sample and field seismic data with varying noise levels were evaluated using adaptive filtering, resulting in significant improvements in f-c image quality. The filtered data displayed a wider frequency range of f-c images, and reduced noise compared to the original noisy data. Based on these findings, adaptive filtering …

Meshed Trees: A Framework For Resilient Network Algorithms And Protocols, Peter Willis

Theses

The continued growth of computer networks in both size and complexity presents challenges for the control protocols that are tasked with maintaining optimal data-forwarding paths. These protocols commonly rely on shortest-path algorithms to determine where network data should be propagated and how it should be analyzed for inclusion in forwarding tables. However, problems arise during reconvergence, the process in which devices rediscover optimal paths following a network failure. Because control protocols were built decades ago for the networks of that era, the existing shortest-path algorithms utilized were designed for problems before the advent of modern computer networks. This resulted in …

Nivolumab Plus Ipilimumab Induce Hyper-Progression In Renal Medullary Carcinoma: Results Of A Phase Ii Trial And Preclinical Evidence, Melinda Soeung, Xinmiao Yan, Ciro Zanca, Jing Qian, Menuka Karki, Fei Duan, Hania Khan, Li Zhang, David H Peng, Mariah Williams, Rong He, Ziheng Chen, Luigi Perelli, Jianfeng Chen, Rebecca S Tidwell, Pankaj K Chauhan, Courtney N Le, Truong N A Lam, Nirjar Bhattacharya, Rutvi Shah, I-Lin Ho, Jason P Gay, Caroline C Carrillo, Ningping Feng, Kang Le, Guang Gao, Teresa L Perry, Faika Mseeh, Yongying Jiang, Quanyun A Xu, Niki Marie Zacharias, Rahul A Sheth, Tharakeswara K Bathala, Priya Rao, Najat C Daw, Durga N Tripathi, Cheryl L Walker, Mohammad M Mohammad, Jianhua Zhang, Guangchun Han, Yanshuo Chu, Ruiping Wang, Minghao Dang, Enyu Dai, Fuduan Peng, Yunhe Liu, Akshaya Jadhav, Wenhua Lang, Claudio A Arrechedera, Leticia Campos Clemente, Edwin R Parra, Hsinyi Lu, Cara L Haymaker, Ignacio I Wistuba, Andrew Futreal, Andrea Viale, Michael J Soth, Philip Jones, Joseph R Marszalek, Timothy Heffernan, Giulio F Draetta, Nizar M Tannir, Jianjun Gao, Linghua Wang, Giannicola Genovese, Pavlos Msaouel

Faculty, Staff and Students Publications

Therapeutic options for patients with renal medullary carcinoma (RMC) are limited. Here we report the results of a phase II clinical trial (NCT03274258) of anti-PD1 nivolumab plus anti-CTLA4 ipilimumab in patients with RMC, with objective response rate as primary outcome. Enrollment was halted for futility at a prespecified interim analysis as all 10 treated patients experienced rapid disease progression. 5/10 met radiological criteria for hyperprogression and median progression-free survival (secondary outcome) was 1.38 months (95% confidence interval: 1.28, 1.60). In a post-hoc single-cell RNA sequencing analysis, data from patients with RMC before and after nivolumab plus ipilimumab treatment indicated that …

Quality Improvement Project: Improving Providers’ Self-Efficacy In Facilitating Mat Usage Through Educational Training, Joshua W. Moore

Doctor of Nursing Practice Projects

Opioid Use Disorder (OUD) and Alcohol Use Disorder (AUD) are common diseases treated in detox facilities around the world. Medication-assisted treatment (MAT) is the most effective treatment for OUD and AUD. Despite the need for MAT, many providers do not prescribe lifesaving medications due to a lack of knowledge and confidence. The purpose of this quality improvement project at a local detox facility is to answer the question: What effect on providers’ self-efficacy in facilitating MAT usage upon discharge does educational training have? Under the Social Cognitive Theory (SCT), self-efficacy was targeted using the Plan-Do-Study-Act (PDSA) change model. The aim …

Biochronostratigraphy Of The Cenomanian-Paleocene Platform Margin Carbonate Successions In The Geyik Dağı Area, Central Taurides, Türkiye, Kemal Tasli, Hayati̇ Koç, Cemi̇le Solak

Turkish Journal of Earth Sciences

Slope to basin carbonate successions, ranging in age from the Cenomanian to the Paleocene, are exposed in the Geyik Dağı area that is part of the Anamas-Akseki autochthon (Geyik Dağı unit) cropping out in western Central Taurides (southern Türkiye). Biochronostratigraphic and sedimentologic features of the successions have been recently described from 3 stratigraphic sections. They are structurally separated into 2 successions. The lower succession is unconformably overlain by Eocene turbiditic sandstones. The upper succession is in a tectonic sheet between the Eocene sandstones and the Aladağ unit. Stratigraphic bases of the successions are not exposed in the study area. The …

A Comprehensive Analysis Of Türkiye’S Beaches: Spatial Distribution, Morphometry, And Human Impacts, Muhammed Zeynel Öztürk, Berkay Yilmaz, Abdullah Soykan

Turkish Journal of Earth Sciences

The classification and morphometric characteristics of beaches is crucial for understanding coastal dynamics, evaluating natural and anthropogenic pressures, and supporting effective coastal management and conservation strategies. This is particularly important for countries like Türkiye, where extensive and diverse coastlines play a key role in tourism, the economy, and ecological sustainability. This study presents the first comprehensive, nationwide inventory and characterisation of Türkiye’s beaches, encompassing its 8483 km coastline. Using satellite imagery, 6110 beaches were identified and classified according to environmental conditions, with analyses conducted on their morphological characteristics, sea boundaries, and provincial distributions. The results show that rocky coast and …

An Intelligent Vision System For Metal Surface Defect Detection, Sida Zhang

Dissertations (1934 -)

With the continuous growth in the need for artificial intelligence driven manufacturing, automatic detection of metal surface quality has become a key issue in forging production. Traditional manual detection methods are not only inefficient and subjective but also have low accuracy when analyzing workpieces with complex surfaces and diverse colors. To solve this problem, this dissertation proposes two methods for metal surface defect detection and classification. This dissertation begins with the background of forging and summarizes existing literature on industrial vision systems and surface defect detection methods. Basic image processing techniques, machine learning algorithms, and deep learning foundations—including artificial neural …

Towards A Generalized And Optimized Apriori Approach, Artem Abdikov

Master's Theses

Apriori is a machine learning algorithm developed in 1994 by R. Agrawal and R. Srikant for association rule mining purposes. This family of algorithms takes transactional data and analyzes relationships between variables in large datasets. The typical output of such algorithms is a prediction that if users choose item X, it is highly likely that they will also choose item Y. Apriori is known to be a robust algorithm and is used by many large companies in order to analyze user tendencies and even make recommendations. Although Apriori is a powerful algorithm, its original implementation is known to have limitations, …

Impact Of Community Factors On Naloxone Overdose Reduction In Ohio, Theophilus Oduro Frimpong

Walden Dissertations and Doctoral Studies

The opioid crisis in Ohio, driven by fentanyl, persists due to inequitable access to naloxone despite its proven effectiveness. This study examined how socioeconomic status (SES), race/ethnicity, population density, and hospital availability per capita predicted naloxone overdose reversals (dependent variable) in Ohio. Social-ecological theory guided this quantitative historical correlational analysis of Ohio’s Project DAWN index data (N = 5,280). Inclusion criteria included individuals ages 18 to 65 with naloxone-related overdose reversals (dependent), naloxone distribution (moderator), and community factors (independent). Multiple linear regression results showed that SES (p >.50), race/ethnicity (% White, p = .588; % Black, p = .495; % …

Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …

Advances In Artificial Intelligence For Glioblastoma Radiotherapy Planning And Treatment, Reid Master, Nesha Rubin, James Sampson, Kamlesh K Yadav, Shruti Pandita, Aria Sabbagh, Anika Krishnan, Patrick J Silva, Kenneth S Ramos, Vincent Gregoire, Nikos Paragios, Sunil Krishnan, Tej K Pandita

The Brown Foundation: Institute of Molecular Medicine

Glioblastoma is an aggressive central nervous system tumor characterized by diffuse infiltration. Despite substantial advances in oncology, survival outcomes have shown little improvement over the past three decades. Radiotherapy remains a cornerstone of treatment; however, it faces several challenges, including considerable inter-observer variability in clinical target volume delineation, dose constraints associated with adjacent organs at risk, and the persistently poor prognosis of affected patients. Recent advances in artificial intelligence, particularly deep learning, have shown promise in automating radiation therapy mapping to improve consistency, accuracy, and efficiency. This narrative review explores current auto segmentation frameworks, dose mapping, and biologically informed radiotherapy …

Organizational Leaders’ Effective Strategies For Using Employee Training To Mitigate Threats To Cybersecurity Compliance, Oluwaseye Adekunle Fadare

Walden Dissertations and Doctoral Studies

Organizational leaders increasingly face challenges associated with employee noncompliance with cybersecurity controls, which expose business leaders to reputational and financial risks. Addressing this business problem is critical for cybersecurity leaders and business executives who aim to strengthen digital resilience and sustain profitability. The purpose of this qualitative pragmatic inquiry was to explore effective strategies organizational leaders use to enhance employee cybersecurity compliance through training. The project was grounded in the protection motivation theory and total quality management frameworks, which provide insight into the behavioral and continuous improvement dimensions of cybersecurity management. Six cybersecurity leaders from Nigeria participated in semistructured interviews. …

Spartan Daily, November 25, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 39

Exploring The Link Between Emotional States And Coding Task Quality: A Pilot Study, Aquib Reshad, Valentina Nino, Maria Valero, Adriane Randolph, Yang Shi

Faculty Articles

Emotions play a crucial role in shaping cognitive performance, yet their influence on programing remains understudied. This pilot study investigates the relationship between emotional states and coding task quality. Ten participants completed a programing task while their brain activity was recorded using electroencephalography (EEG), with frontal alpha asymmetry (FAI) applied as a neural marker of emotional valence. Emotional self-reports were collected using the Scale of Positive and Negative Experience (SPANE), and coding quality was evaluated through a structured rubric. Preliminary findings indicate a potential association between FAI and coding performance, whereas self-reported affect showed weaker or inconsistent patterns. Given the …

Deep Learning Reveals How Cells Pull, Buckle, And Navigate Fibrous Environments, Abinash Padhi, Arka Daw, Atharva Agashe, Medha Sawhney, Maahi M Talukder, Mehran M H Pour, Mohammad Jafari, Guy M Genin, Farid Alisafaei, Sohan Kale, Anuj Karpatne, Amrinder S Nain

2020-Current year OA Pubs

Cells in tissues navigate fibrous environments fundamentally differently than they do on flat substrates, but the establishment of cell forces in physiological fibrous settings remains poorly understood. Although factors such as the stiffness of the extracellular matrix (ECM) are known to drive behaviors, including cell motility on flat nonfibrous substrates, the interplay between fiber architecture and stiffness in fibrous ECM is not known. Here, we find that in fibrous environments, the directionality of mechanical forces overrides ECM stiffness as the primary regulator of contractility in migrating cells. Using an approach combining phase microscopy with deep learning to map forces in …

Re: Conditional Approval Letter For The Final Butte Mine Waste Repository Geotechnical Investigation Work Plan (Dated November 14, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.