Physical Sciences and Mathematics Commons^™

Self-Attention Enhanced Dual Bigru For Arabic Fake News Detection, Baqer M. Merzah, Jafar Razmara, Jaber Karimpour

Mesopotamian Journal of Computer Science

The rapid proliferation of social media platforms has greatly amplified the dissemination of fake news, representing significant obstacles to public trust and evidence-based decision-making, particularly for the Arabic-speaking population. Meeting the challenge of Arabic fake news detection is a problem compounded by the complex morphological nature of the language, as well as limited resources. This study presents a hybrid deep learning framework that integrates two Bidirectional Gated Recurrent Units (BiGRUs) along with an attention mechanism for efficiently detecting misinformation in Arabic news. The method leverages FastText word embeddings for disambiguating the intricate semantics of the Arabic language. The model is …

Diabetes At A Glance: Assessing Ai Strategies For Early Diabetes Detection And Intervention Via A Mobile App, Ayad Hameed Mousa, Ibrahim Oday Alrubaye, Mayameen S. Kadhim, Ahmed Dheyaa Radhi, Mudatheer M. Al-Slivani, Rusul Mansoor Al-Amri, Liaw Geok Pheng

Mesopotamian Journal of Computer Science

Diabetes is a widespread disease worldwide that does not differentiate between children and adults. It also affects the elderly and pregnant women. However, early detection of the disease facilitates its control to avoid the effects resulting from delayed diagnosis. With the emergence of artificial intelligence represented by machine learning techniques and its use in most sectors, accordingly, the adoption of machine learning techniques to help in disease prediction has become a necessity. This study proposes a machine learning algorithm-based approach for diabetes prediction. This study uses three datasets, two of which are private and the other includes the Pima Indians …

Enhancing Routing Efficiency In Vanets By Leveraging 5g To Mitigate Congestion, Yusor Rafid Bahar Al-Mayouf, Omar Adil Mahdi, Heba Hussain Hadi, Suleman Khan, Mazin Abed Mohammed

Mesopotamian Journal of Computer Science

Transportation networks impact millions of people daily. Their efficiency immediately affects travel time, safety, and environmental sustainability. Unfortunately, various issues hinder the expected performance and efficiency of these networks. Traffic congestion is an up-to-date issue in the urban environment. Fuel consumption is high because travel time has increased, which has a passive environmental impact. Extensive research has been conducted to progress the intelligent transportation systems installed on communication networks and information to treat this congestion. However, there is a significant amount of affront residue in combining real-time data, estimation analytics, and 5G abilities effectively. This paper offers a novel routing …

Roi – Enhancing Detection Of Citrus Disease Based On Yolov10, Raya N. Ismail, Armaneesa Naaman Hasoon, Israa Rafaa Abdulqader, Salwa Khalid Abdulateef

Mesopotamian Journal of Computer Science

One of the most important fruit crops in the world is citrus. However, some citrus diseases spread rapidly, which is why early detection at an accurate stage is important for timely intervention. YOLO-based object detection models, such as the latest YOLOv10, where small lesions are difficult to identify among noisy backgrounds, have recently been developed, yet their accuracy tends to degrade. Therefore, we proposed a citrus disease detection model by integrating the region of interest (ROI) for object segmentation with the YOLOv10 model, thus addressing the issues of low detection accuracy and slow inference time. The proposed model was trained …

A Review Of Image Steganography Based On Metaheuristic Optimization Algorithms, Fatima Abdulhussain Khalil, Ammar Ali Neamah, Hasanen Alyasiri

Mesopotamian Journal of Computer Science

Due to the widespread popularity of digital images on the Internet, image-based steganography has become a widely adopted technique for embedding secret information into everyday visual content. In parallel, steganalysis plays a vital role in digital forensics and information security by seeking to uncover hidden content within these images. Although steganographic techniques—particularly those employing adaptive embedding strategies—have made significant progress, many steganalysis approaches still struggle to generalize effectively across different image types and embedding methods. This contrast highlights the need for more intelligent, flexible, and robust analysis frameworks. This review examines steganographic techniques for digital images and the application of …

Colorado River Insights, 2025: Dancing With Deadpool, Colorado River Research Group

Books, Reports, and Studies

No abstract provided.

Orchestrating Digital Technologies With Incumbent Enterprise Systems For Attaining Innovation, Sachithra Lokuge, Darshana D. Sedera, Varun Grover, Suprateek Sarker

Information Systems Faculty Publications and Presentations

In the late 1990s, most organizations adopted enterprise systems (ES) to automate their core business processes. The very same organizations are presented with a new wave of opportunities to innovate with digital technologies—technologies that purport to have diametrically opposed characteristics to ES. This study explores how organizations integrate digital technologies with their incumbent ES for attaining innovation. The study followed a qualitative approach and gathered data from four organizations consisting of six such projects. By applying a unique theoretical foundation, this study derives interesting insights into the orchestration process of ES and digital technologies for attaining innovation.

Crises, Coloniality, And Energy Transformations In Puerto Rico, Laura Kuhl, Marla Perez-Lugo, Carlos Arriaga Serrano, Cecilio Ortiz Garcia, Ryan Ellis, Jennie C. Stephens

Sociology Faculty Publications

Increased attention to inclusive processes is essential to ensure injustices are not perpetuated during energy transitions. Crises, such as the collapse of the electric grid in Puerto Rico after Hurricane Maria, present the promise of opening windows of opportunity for new ideas and voices to inform the future, but they also create opportunities for powerful interests to reinforce existing power dynamics. While coloniality has been recognized as a barrier to sustainable energy transformations, greater integration of the literature on climate coloniality and sustainability transitions is needed. This chapter analyzes visions of the future of the energy system among diverse constituents …

Opinion Mining On Offshore Wind Energy For Environmental Engineering, Isabele Bittencourt, Aparna S. Varde, Pankaj Lal

School of Computing Faculty Scholarship and Creative Works

Renewable energy sources are vital to help mitigate the effects of climate change, and reducing the carbon dioxide emissions of fossil fuels, e.g. the state of New Jersey has a goal of producing 100% clean energy by 2050. However, the plans for offshore wind energy by the shore of the state still brings much controversy between residents due to the wind farms’ impact on wildlife, coastline, and the people’s view from the beaches. In this context, we perform sentiment analysis on social media data to investigate people’s opinions and concerns regarding offshore wind energy. We adapt 3 machine learning models, …

Using Visual Prompts To Analyze Ejection Fraction In Echocardiograms, Kevin Reisch

Graduate Theses, Dissertations, and Problem Reports (ETD)

Left ventricular ejection fraction (LVEF) is a critical biomarker for heart failure, but manual estimation from echocardiograms is time-consuming. Artificial intelligence can be used to accelerate this process, allowing clinicians to focus on other critical tasks. Current methods typically train models from scratch on echocardiogram datasets; however, this approach is limited by the scarcity of large medical imaging datasets, which are expensive and difficult to acquire. We present a transfer learning approach that leverages pretrained models from massive datasets, enabling continuous improvement as foundation models advance. Our method employs visual prompting to generate trainable masks for echocardiogram videos, transforming the …

Streamer Discharge Modeling For Plasma-Assisted Combustion, Stuart Reyes, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

Some of the popular and successful atmospheric pressure fuel/air plasma-assisted combustion methods use repetitive ns pulsed discharges and dielectric-barrier discharges. The transient phase in such discharges is dominated by transport under strong space charge from ionization fronts, which is best characterized by the streamer model. The role of the nonthermal plasma in such discharges is to produce radicals, which accelerates the chemical conversion reaction leading to temperature rise and ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to develop a predictive model. We examine the important characteristics of streamers that influence combustion and develop some …

A New Paradigm For The Supramolecular Structure Of Laterally Offset Diarenes: Polymorphs Ii Of Para-Substituted Acetophenone Azines, Yp.Ph.(Me)C.N.N.C(Me).Ph.Yp (Y = Cl, Br, Ch3), Harmeet Bhoday, Kaidi Yang, Steven P. Kelley, Rainer Glaser

Chemistry Faculty Research & Creative Works

The crystal structures of polymorphs II of acetophenone azines Y_pPhRCNNCRPhY_p with R = CH₃ and Y = Cl (1M), Br (2M), and CH₃ (8M) are discussed. The azine molecules in polymorphs II are Ci-symmetric with trans-azine moieties and conrotatory phenyl twists. Polymorphs 1M-I and 2M-I contain C2-symmetric enantiomers with pronounced azine twists and disrotatory phenyl twists and allow for strong lateral double T-contacts. The three polymorphs II exemplify the new Paradigm IV for the supramolecular architectures of "laterally offset diarenes" and result in "shiplap/flat" idioteloamphiphile monolayers. Intralayer lateral attraction is provided by edge-to-face arene-arene contacts …

Echopulse: Ecg Controlled Echocardiograms Video Generation, Yiwei Li, Sekeun Kim, Zihao Wu, Hanqi Jiang, Yi Pan, Pengfei Jin, Sifan Song, Yucheng Shi, Xiaowei Yu, Tianze Yang, Tianming Liu, Quanzheng Li, Xiang Li

Computer Science Faculty Research & Creative Works

Echocardiography (ECHO) is essential for cardiac assessments, but its video quality and interpretation heavily rely on manual expertise, leading to inconsistent results from clinical and portable devices. ECHO video generation offers a solution by improving automated monitoring through synthetic data and generating high-quality videos from routine health data. However, existing models often face high computational costs, slow inference, and rely on complex conditional prompts that require experts' annotations. To address these challenges, we propose ECHOPulse, an ECG-conditioned ECHO video generation model. ECHOPulse introduces two key advancements: (1) it accelerates ECHO video generation by leveraging VQ-VAE tokenization and masked visual token …

Openmuse: Integrating Open-Source Models Into Music Creation Workflows, Tyler K. Vergho

Dartmouth College Master’s Theses

This master's thesis introduces OpenMUSE (Open Multimodal Unified Sound Engine), a platform that demonstrates the potential of open-source AI music generation by integrating state-of-the-art deep learning models into a unified system. By unifying ten different open-source models, including MusicGen, AudioLDM2, and custom-trained text-to-symbolic music generation models, OpenMUSE aims to create a user-friendly interface that empowers artists to produce complex, adaptive musical compositions. The system enhances accessibility by providing a simple web interface and natural language controls, while improving controllability through features like melody conditioning and semantic audio editing. Specifically, OpenMUSE offers a digital audio workstation (DAW)-inspired interface that lowers the …

Group And State-Specific Estimation In Animal Movement Models Using A Bayesian Approach, Anita Bhandari Sharma

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This research study investigates statistical approaches for modeling the movement patterns of white-tailed deer in Louisiana using GPS tracking data. We start by classifying the latent behavioral states using a hidden Markov model (HMM) and then integrate those inferred states into a state-dependent step selection framework to evaluate the land cover preferences. Standard HMMs, however, assume the same movement patterns for all animals, overlooking the differences due to characteristics such as sex, age, breeding season, etc.

To address this limitation, we extend the modeling framework to incorporate the group-level structure defined by similar characteristics or conditions to assess whether such …

Geometric Modeling, Reconstruction And Evaluation Of Maize Leaf Morphology In 3d, Zhaocheng Xiang

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Maize is a vital crop for global food security, yet quantitative characterization of its three-dimensional (3D) morphology remains a major challenge due to the geometric complexity of curved leaf structures and occlusions during data collection. This work presents an integrated framework for the digital reconstruction, parametric modeling, and functional analysis of maize leaf morphology and canopy architecture, advancing the precision and interpretability of phenotyping and modeling in smart agriculture.

First, we propose a descriptive and parametric model that represents maize leaves through three fundamental components: midrib, cross-section, and blade contour. Each is described by geometric curves and controlled by biologically …

Conservation And Survey Division 2024 Annual Report, R.M. Joeckel, Michele Waszgis

Conservation and Survey Division: Faculty and Staff Publications

The Conservation and Survey Division of the University of Nebraska - Lincoln is the agency designated by statute to investigate and interpret the geologically related natural resources of the State, to make available to the public the results of these investigations, and to assist in the development and conservation of these resources. It consists of program areas in geology, water, soils and remote sensing-geographic information systems.

Early Holocene Interaction Of Aeolian, Alluvial, And Lacustrine Processes In A Dune-Dammed Valley In The Central Nebraska Sand Hills, Gpsia Mahoney, R. D. Mandel, P.R. Hanson, Sherilyn Fritz

Conservation and Survey Division: Faculty and Staff Publications

No abstract provided.

Stratigraphy And Osl Chronology Of Lunette Deposits Indicates That Nebraska’S Rainwater Basins Formed By Aeolian Deflation Between 39 And 25 Ka, P.R. Hanson, Robert Matthew Joeckel

Conservation and Survey Division: Faculty and Staff Publications

No abstract provided.

Spatial Analysis Of American Chestnut (Castanea Dentata) Distribution And Ecology In Kentucky’S Federal Lands, Jacob Raymond Pease

Murray State Theses and Dissertations

Anthropogenic factors have been the cause of the decline of tree species across the globe. From unsustainable logging and development to disease and improper management, threats to forests have taken their toll. The American chestnut (Castanea dentata) was once an integral basal tree species in Appalachian forests, but chestnut blight drove the species to functional extinction by the mid-1900s. The recent creation of genetically modified chestnuts gives hope for future restoration of the species throughout its historical range. Despite blight resistance, effective restoration will require optimal site selection for finding and planting chestnuts, which will maximize limited resources. …

Strong Neighborhood-Prime Labelings Under Ordinary & Gaussian Integers, Micheal Arnal-Brown

Murray State Theses and Dissertations

This thesis introduces and studies the notion of a strong neighborhood-prime labeling, a strengthening of the neighborhood-prime labeling where the label 1 can be assigned to any vertex in a graph. We prove that several graph families—including paths, cycles (excluding those congruent to 2 modulo 4), caterpillars, helm graphs, closed helm graphs, gear graphs, and graphs with universal vertices—admit such labelings, and also provide results to more general classes of graphs. We extend this new labeling concept to the Gaussian integers using a spiral order- ing on Z[i] and define a Gaussian analogue of strongly neighborhood-primeness. To support this extension, …

New Psychoactive Substances Detected In Wastewater Samples Collected Along The Interstate Highway Rest Areas In Kentucky, Durga Prasad Kodati

Murray State Theses and Dissertations

The rapid emergence and proliferation of new psychoactive substances (NPS) pose significant challenges to public health and law enforcement. The potential for abuse and toxicity of these substances, which are intended to mimic the effects of controlled drugs, has been raising concerns as these compounds are designed to evade being regulated. There are traditional methods of tracking NPS, such as seizures and forensic toxicology, but they are delayed and seldom effective because these substances continue to evolve rapidly. Wastewater-based epidemiology (WBE) has emerged as a promising tool for real-time surveillance of drug consumption. The primary objective of this research was …

Data Injustice In Global Justice, Asaf Lubin, Cherry Tang

Articles by Maurer Faculty

In May 2020, the United Nations Secretary-General unveiled a sweeping “Data Strategy for Action by Everyone, Everywhere,” seeking to unlock the UN’s “full data potential.” The International Criminal Court’s Office of the Prosecutor followed suit, declaring in 2023 its intent to acquire advanced cyber forensic tools so as to hold the “widest range of digital evidence globally.” Across international institutions, data-driven governance has become the norm, with humanitarian agencies and tribunals transforming into “data hubs and information clearinghouses.” This Article critiques the unfettered datafication of global justice by international courts and organizations. These entities have aggressively expanded their data-driven operations …

Assessment Of The Genetic Population Structure And Extent Of Clonality In A Rare Serpentine Endemic, Lathyrus Biflorus T.W. Nelson & J.P. Nelson (Fabaceae), Using Ddrad Sequencing, Ashley Dickinson

Cal Poly Humboldt theses and projects

Lathyrus biflorus, or the two-flowered pea, is a rare herbaceous perennial restricted to a single population in Northern California. The species is considered critically imperiled but remains unprotected under state or federal endangered species acts. Despite its rarity, little is known about its life history, reproductive biology, or genetic diversity. Using genome-wide reduced representation sequencing, this study aimed to address these gaps by investigating the molecular evidence of clonality, the number and diversity of genets (unique genetic individuals which can be made up of one or many clonal units or ramets), and overall genetic health of the population. My …

Groundwater Pumping Impacts On Stream Depletion In Humboldt County, Ca: Integrating Analytical Models And Field Data, Andy Hans Heise

Cal Poly Humboldt theses and projects

This study addresses the significant concern of stream depletion from groundwater pumping in Humboldt County, CA. The objective of this study is to develop an analytical model for estimating stream depletion and integrating field data into model parameters.

The methodology involved conducting a field study near three operating wells by a stream, installing stream gages upstream and downstream of the wells, and recording pumping rates and schedules for two of the wells. The third well’s pumping data was synthetically generated, for privacy concerns of the well owner. The StreamDepletR package was used for estimating depletion rates in a stream in …

Home Range, Habitat Use, And Fall Migration Of Lewis’S Woodpeckers In The Eastern Cascade Range, Oregon, Cameron Piper

Cal Poly Humboldt theses and projects

Lewis’s woodpecker (Melanerpes lewis), a burn specialist, is experiencing range-wide population declines despite increasing fire activity in the western U.S. The White River Wildlife Area in Oregon hosts the state's only year-round population, raising questions about their breeding, habitat use, and migration. In summer 2024, we tracked nine woodpeckers using telemetry to estimate home range size and overlap. Full home ranges averaged 428 ha, with 66 ha core areas, and showed evidence of growing after nesting. Home ranges overlapped extensively (Full: 91 ± 13%; Core: 63 ± 29%), though individuals had distinct areas of intense use. Males had …

An Economic And Production Analysis Of Seaweed Farms In California And The Pacific Northwest, Brian Donovan

Cal Poly Humboldt theses and projects

Since the early 2010s, the seaweed aquaculture industry has steadily expanded in the United States, with states like Alaska, Maine, Hawaii, and Connecticut leading the way in the development of this emerging sector. However, information gaps remain concerning certain aspects of the domestic seaweed aquaculture industry. The purpose of this study was to examine the status of the seaweed aquaculture industry along the West Coast of the United States; specifically in the states of California, Oregon, and Washington. Seaweed farmers in these states were invited to voluntarily complete surveys asking important production, economic, and commercial questions regarding their operations. Data …

Common Raven Habitat Selection Along The Northern California Coast, Alon Averbuj

Cal Poly Humboldt theses and projects

Nest predation by common ravens (Corvus corax) is considered one of the most significant barriers to the recovery of the population of the federally threatened western snowy plovers (Anarhyncus nivosus nivosus) in Northern California. To increase productivity of snowy plovers, conservation managers in Northern California employ three main techniques; placing symbolic fencing to deter pedestrian entrance to snowy plover nesting areas, invasive vegetation cutback, and deposition of oyster shells to increase snowy plover nest crypsis. However, little is known on how these techniques affect habitat selection of ravens in the area. I modeled habitat selection of …

Autonomous Landscape Exploration Rover Using Imaging Surface Navigation (Alexis), Noah Jones, Dominic Salupo

Williams Honors College, Honors Research Projects

The objective is to develop a small-form-factor rover prototype that can be used to prove out a novel traversal method for use on extraterrestrial surfaces. The novel traversal method being proposed is LIDAR/CV-enhanced navigation, provided by a detachable flight vehicle that can communicate with the rover. On planets with thin atmospheres, cold gas thrusters or similar may be needed, but for the scope of this project more traditional flight/propulsion methods will be used.

Moore Graphs, Trevor Saxton

Williams Honors College, Honors Research Projects

A Moore graph is a simple regular graph, with n vertices, degree d, and diameter k, that satisfies the Moore bound: n = 1 + d (d − 1)k − 1 d − 2 . There are graphs for which the bound is met and in which existence and uniqueness are known. For k = 2 it is known that the Moore bound is achieved for d = 2, 3, 7, with the case of d = 57 conjectured to exist. For k = 3 the bound is achieved for only d = 3 [5]. Due to the construction of …