Digital Commons Network^™

Highly Sensitive Diffractive Optical Structures For Detection Of Volatile Organic Compounds, Faolan Radford Mcgovern

Doctoral

From aerospace to agriculture, sensors play a fundamental role in many aspects of modern life. Sensors form an integral part of the complex systems and devices required for the continued functioning and development of services and industries across society. The use of sensors is paramount in areas affecting human health, one such area being the monitoring of indoor air quality, in particular the detection of volatile organic compounds (VOCs). Human contact with VOCs has been associated with many health complications, including skin and eye irritation, cardiovascular damage, and cancers. Optical, electrical, gravimetric, and chemical sensors have been developed for VOC …

Surface Modifications Of Titanium Alloys For Biomedical Applications, Justynne Fabian

Doctoral

Hip implant failure remains a critical concern in healthcare, primarily driven by poor bone integration and bacterial infection. These issues contribute to a rising number of revision surgeries, posing significant challenges that must be addressed, particularly in light of an ageing global population. Titanium surface anodisation emerges as a promising solution for biomedical applications, offering a cost-effective, controllable, and efficient process. The anodisation technique results in the formation of titanium dioxide nanotubes (TiO2 NTs) on the metal surface. These nanostructures offer several advantages, including enhanced mechanical properties, and potential for surface modification through the incorporation of antibacterial and osteoinductive properties. …

Machine Learning Applications In Epigenomics And Its Association With Health And Disease, Trevor Doherty

Doctoral

Epigenetic modifications can lead to altered phenotypes without a change in the DNA sequence itself. Disrupted gene expression regulated by epigenetic processes can result in cancers, autoimmune diseases and various other maladies. Machine learning (ML) involves the use of algorithms and models which are trained to learn patterns in data, and has demonstrated remarkable success in solving diverse, complex challenges. Epigenomic studies, such as those that use DNA methylation (DNAm) data, increasingly make use of ML techniques to process extremely high dimensional data obtained from high throughput platforms e.g., DNAm arrays. These datasets suffer from the curse of dimensionality, increased …

An Exploratory Attempt To Incorporate Social Criteria Into Spent Nuclear Fuel Site Screening And Relocation, Julie M. Sorfleet

Cal Poly Humboldt theses and projects

Spent nuclear fuel, also known as nuclear waste, is the byproduct of nuclear power generation. The need for safe and responsible long-term storage and disposal of radioactive fuel presents significant technical and social challenges. These challenges are compounded by several factors, including the emerging nuclear renaissance in the United States, climate and coastal hazards, and the lack of consolidated interim or permanent storage. This research explores perceptions of risk, relocation, and siting spent nuclear fuel, predominantly focusing on Humboldt County, California. I used online surveys, the Analytic Hierarchy Process, and geographic information systems (GIS) analysis to inform how social and …

Snag Failure And Fuel Recovery Following Stand-Replacing Fire In The Klamath Mountains, Joseph R. Nicholas

Cal Poly Humboldt theses and projects

High-severity wildfires can produce extensive patches of standing dead trees (snags), which later contribute to surface fuel loading and present a hazard as they decay and fall. In the Klamath Mountains of northwestern California and southwestern Oregon, recent increases in the occurrence of large stand-replacing wildfires have raised concerns about fuel and vegetation recovery trajectories, the likelihood of future fires, and resulting impacts to local communities. Nevertheless, the post-fire environment may offer opportunities to enhance ecological and community resilience. Estimates of snag failure and fuel loading can support land management planning and risk assessment following wildfire, though such work is …

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 …

Exploring Coastal Spaces Of Tribal Sovereignty And Self-Determination In Ancestral Waters Proposed For Offshore Wind Development, Alyssa Suarez

Cal Poly Humboldt theses and projects

Proposed offshore wind development off California’s North Coast raises novel questions about Tribal sovereignty offshore. This project specifically engages claims, assuming the Yurok Tribe’s framing that offshore wind development poses a coastal hazard. The research followed a co-production framework. The research questions were co-designed with the Yurok Tribe and the research itself governed by a Data Sharing Agreement. The work presents findings from 13 semi-structured interviews with individuals and experts navigating sovereignty in the offshore wind space, including government representatives; lawyers; legal researchers; academics; foundation staff; journalists; and Humboldt Bay community members. Participants identified several key tensions surrounding claims of …

Multi-Grade Classroom Professional Development And Curated Resources, Angie Marshall

Cal Poly Humboldt theses and projects

This project aims to provide educators and administrators with a comprehensive compendium of resources for effectively designing and implementing instruction in multi-grade classrooms. Limited research exists to support teachers who may struggle with the complexities of teaching multiple grade levels within a single classroom setting. Traditionally, educators obtain their teaching credentials, secure employment, and are expected to effectively instruct the students. However, when assigned to a multi-grade classroom, the instructional demands become significantly more intricate and potentially overwhelming.

The objective of this professional development and resource guide is to equip teachers and administrators with a structured resource to enhance the …

Can Dyslexia Diagnosis Induce A Stereotype Threat Effect? A Literature Review And Research Proposal, David H. Harris

Cal Poly Humboldt theses and projects

Dyslexia is a recognized psychiatric diagnosis in the DSM-5, categorized as a specific language disorder. Dyslexia is a hidden disability that affects how individuals process auditory and visual information. Many people have heard of dyslexia but it is largely misunderstood, even by educational professionals, and its general association with learning disability can be the basis for negative stereotyping and discrimination of people with dyslexia. The ‘Stereotype threat effect’ is a term from social psychology research referring to situations where one’s performance on a task is influenced by their identification with a social group that has a well-known stereotype about their …

The Menstrual Cycle, Dual-Hormone Hypothesis, And Competition: Implications For Athletic Performance, Camille Burns

Cal Poly Humboldt theses and projects

Female athletes perceive that the fluctuating hormones of the menstrual cycle affect their performance. However, research on objective performance is inconclusive, partly due to a lack of studies conducted in real-world competitive contexts. Testosterone is often seen to be elevated near ovulation and is related to social competitiveness. Under the dual-hormone hypothesis, testosterone only predicts competitive behavior when cortisol is low. The current study had two goals: (1) to test whether the dual-hormone hypothesis applied to competitive drive and objective athletic performance, and (2) to examine whether competitiveness and the intensity of one’s response to competition varied across the menstrual …

Social Emotional Learning: Through A Culturally Relevant And Spiritual Lens, Albert Roman

Cal Poly Humboldt theses and projects

In today’s diverse educational landscape, the importance of integrating social-emotional learning (SEL) into secondary English language arts classrooms cannot be overstated. This master’s project endeavors to address this need by developing a series of innovative SEL lessons tailored specifically for secondary ELA teachers. Grounded in the principles of culturally relevant and sustaining pedagogy (CRSP) and enriched with insights from spiritual pedagogy (SP), the project aims to cultivate a holistic approach to education that nurtures students’ emotional well-being, cultural identity, and spiritual growth. The project is structured around the five pillars of SEL: self-awareness, self-management, social awareness, relationship skills, and responsible …

Effects Of Teacher Reinforcements On Student Outcomes In Adapted Physical Education: A Meta-Analysis, Yaxeny Moreno

Cal Poly Humboldt theses and projects

The primary goal is to review the influence of reinforcement strategies in Physical Education (PE) and Adapted Physical Education (APE) settings, focusing on students with disabilities with the ages of 3-22. Reinforcement strategies, such as positive reinforcement/feedback, token economies, verbal praise, tangible rewards, and additional strategies are essential for fostering engagement and skill development. Literature has provided evidence and results to highlight the importance of applying evidence-based reinforcement strategies to which support the behavioral, social, and physical development of students in both Physical Education and Adapted P.E. settings. The purpose of this study was to review and analyze existing literature …

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 …

Estimating Mariana Monitor (Varanus Tsukamotoi) Density With Multiple Methods On Islan Dåno’, Guam, And Its Relevance To Guam Rail (Hypotaenidia Owstoni) Conservation, Jack T. Christie

Cal Poly Humboldt theses and projects

The Mariana monitor (Varanus tsukamotoi), or hilitiai, is a medium-sized varanid lizard found throughout the Mariana islands. On Islan Dåno’, a small islet off the southwest coast of Guam, hilitai coexist with one of the rarest birds in the world, the Guam rail (Hypotaenidia oswtoni), or ko’ko’, which were introduced to the island in 2010. Since 2009, hilitai have been lethally removed from the island to reduce possible predation on ko’ko’. After 15 years of removal efforts, I sought to 1) estimate the abundance and density of hiltai, 2) assess the effect of removal effort and …

Wait... Homework Can Be Fun?! A Pilot Homework System Study, Caroline Brock

Cal Poly Humboldt theses and projects

Homework has been a long-debated topic in schools. Regardless of where people stand on the issue, the evidence shows that quality homework can be an effective tool to help students be successful in school. Beyond academics, homework can also be used as a tool to help students develop important foundational study skills that are critical for future success. But how can school districts get all stakeholders behind a homework system if they do not see the value of homework, or if the homework is a point of individual or familial stress. Through an action research project using mixed methods, parents …

Elementary Teachers' Knowledge Towards Teaching Physical Education, Hannah Lee Mandy

Cal Poly Humboldt theses and projects

This study examined elementary teachers’ preparation in physical education (PE) and its impact on teaching effectiveness for students, including students with disabilities. Twenty-seven teachers completed a survey and three participated in a follow-up focus group where participants were asked to expand on previous questions. Findings revealed limited PE coursework, minimal hands-on experience and low familiarity with the California Physical Education Standards in teacher preparation programs. Additionally, only 74 percent of participants completed a PE course during their teacher preparation program and focus group participants emphasized their preparation programs focused on lesson planning rather than hands on teaching, and the programs …

Large Language Models And Identity: A Reflexive Approach, Nicholas Austin Nielsen

Cal Poly Humboldt theses and projects

This project explicates theories of identity, technology, and capitalism and uses an auto ethnographic approach in order to apply that explication at a personal level. The project responds to AI rhetoric in business and pedagogy and the instability surrounding perspectives on job security, the role of technology in Higher Education, and existential representations of the human. By deconstructing identity, ideology, cultural contexts, and technologic rhetorics, the goal is to further the scholarship surrounding Large Language Model applications in pedagogy and offer a personal, therapeutic approach to feelings of economic and existential discontent and fear experienced by students and educators regarding …

Provenance Of Clastic Sedimentation In Middle Deadfall Lake And Paleoclimate Modelling Of Glacier Fluctuations At Mount Eddy, Eastern Klamath Mountains, California, Usa, Emily Stebbins

Cal Poly Humboldt theses and projects

This study reconstructs the timing, extent, and paleoclimate conditions associated with late Pleistocene glaciation in the Mount Eddy region of the eastern Klamath Mountains, northern California and investigates the provenance of clastic sedimentation in Middle Deadfall Lake, just east of Mt Eddy. Using a multi-pronged approach that combines geomorphic mapping, sediment core analysis, X-ray fluorescence (XRF) geochemistry, tephrochronology, and glacier modeling using PalaeoIce 2.0, this research provides new insights into glacial dynamics and climate variability in a region with limited glacially derived paleoclimate datasets, as well as past volcanic eruption deposits.

Field and GIS-based geomorphic mapping identified three generations …

Data Mining And Machine Learning-Based Healthcare Monitoring In Cloud-Iot, Sarah Amer, Rania Hazim, Wassan Kader

Mesopotamian Journal of CyberSecurity

Healthcare monitoring Cloud-IoT systems use data mining and machine learning methods to analyse patient data in real-time from linked devices. By offering insights for the early diagnosis of anomalies and individualized treatment suggestions, this strategy improves healthcare management. In this research first the Collect and Load the Clevant Heart Disease Dataset for Data Collection Process. Next, preprocess the loaded data using the Synthetic Minority Oversampling Technique (SMOTE), and then the feature extraction process is done using the Principal Component Analysis (PCA) Method. In this case, the characteristic must be extracted by feeding a specific column. The classification procedure is then …

Department Of Computer Engineering, University Of Diyala, 32001 Diyala, Iraq., Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel

Mesopotamian Journal of CyberSecurity

Android devices are rapidly being used, which makes it easy for the malware threat to rise to higher levels. This ever-growing problem has prompted the need to enhance detection systems as far as these devices are concerned. Standard techniques of machine learning (ML) are sufficient from the point of view of their speed for searching patterns and behaviors of contemporary malware; however, it is more important to have effectively enhanced methods. The purpose of this paper is to expand the utilization of Android malware identification via artificial neural networks (ANNs) and compare its efficiency with that of other ML methods. …

Exploring The Impact Of Blockchain Revolution On The Healthcare Ecosystem: A Critical Review, Maad M. Mijwil, Mohammad Aljanabi, Mostafa Abotaleb, Ban Salman Shukur, Ban Salman Shukur, Indu Bala, Kamal Kant Hiran, Ruchi Doshi, Klodian Dhoska

Mesopotamian Journal of CyberSecurity

Blockchain technology is a type of distributed ledger that provides secure and efficient storage, management, and transmission of data over a decentralized network. With its ability to ensure transparency and immutability, blockchain is increasingly adopted across various sectors ranging from finance, healthcare, and logistics to education. In healthcare, blockchain technology is attracting attention because of its potential to fundamentally transform health ecosystems. The healthcare sector has significantly benefited from blockchain technology by enhancing data security and interoperability and reducing medical errors. In this context, a set of studies highlighted the importance of blockchain in the field of healthcare, enhancing trust …

Antdroidnet Cybersecurity Model: A Hybrid Integration Of Ant Colony Optimization And Deep Neural Networks For Android Malware Detection, Riyadh Rahef Nuiaa Al Ogaili, Osamah Adil Raheem, Mohamed H Ghaleb Abdkhaleq, Zaid Abdi Alkareem Alyasseri, Zaid Abdi Alkareem Alyasseri, Ali Hakem Alsaeedi, Yousif Raad Muhsen, Selvakumar Manickam

Mesopotamian Journal of CyberSecurity

Malware detection is a vital problem, and efficient methods that can efficiently detect malware are needed. The increasing use of mobile computers makes malware detection a vital part of security in an era where smartphones have come to play a key role in many of our daily lives. Earlier approaches, however, suffer from high false positive rates; they are not scalable for larger databases, or they are not amenable to adapt well to novel zero-day malware. For these reasons, the demand for more sensitive and flexible detection models is high. In this study, we develop a hybrid mobile malware detection …

Enhancing Crime Detection In Video Surveillance Via A Lightweight Blockchain And Homomorphic Encryption-Based Computer Vision System, Tanya Abdulsattar Jaber

Mesopotamian Journal of CyberSecurity

Blockchain technology consists of distributed ledgers or database systems, regarded as immutable, secure, and innovative, characterized by unsupervised internal maintenance with a special security protocol used to prevent inference from malicious or third parties. The widespread use of this technology has led to deep research into the problems posed by this technology, which can be summarized in terms of computational cost and latency time. The crime detection process in video surveillance has made great progress with the use of technologies such as the Internet of Things and blockchain technologies. However, to reach high levels of security in the physical crime …

Improved Blockchain Technique Based On Modified Slim Algorithm For Cyber Security, Sarah Mohammed Shareef, Rehab Flaih Hassan

Mesopotamian Journal of CyberSecurity

The number of cybersecurity incidents is increasing, and the cost of a security breach has a catastrophic financial effect. The existing real estate information systems require more robust and resilient cybersecurity solutions to secure hardware, software, and databases. Cybersecurity often relies on user behavior. Phishing attacks and social engineering can bypass blockchain security, highlighting the need for robust user education and awareness. Many blockchain networks face challenges in handling a high volume of transactions. Solutions that work well on a small scale may not perform efficiently as the network grows, leading to delays and increased costs. A secure system is …

Robust And Efficient Methods For Key Generation Using Chaotic Maps And A2c Algorithm, Ali A. Mahdi, Mays M. Hoobi

Mesopotamian Journal of CyberSecurity

In the current digital landscape, information security has become a critical necessity given the escalating frequency and sophistication of cyberattacks across global computing networks. Cryptography is the science and practice of securing information by transforming it into a format that is unreadable or inaccessible to unauthorized parties. The strength of the cryptography algorithm lies in the strength of used encryption key. Recently, the nonlinear behavior of chaotic maps has been utilized as a random source to generate robust key stream bits for cryptographic purposes. The aim of this paper is to introduce an efficient and robust system for generating strong …

Secured Multi-Objective Optimisation-Based Protocol For Reliable Data Transmission In Underwater Wireless Sensor Networks, Mostfa Albdair, Zainab Rustum Mohsin, Ahmed Saihood, Aqeel M. Hamad, Aqeel M. Hamad

Mesopotamian Journal of CyberSecurity

Underwater wireless sensor network (UWSN) requirements have increased beyond applications in environmental monitoring and underwater exploration to military surveillance. The complex underwater environment raises many challenges due to high propagation delays, limited bandwidth, high error rates, and dynamic underwater currents. Most traditional clustering algorithms do not consider the multifaceted requirements of UWSNs. In most cases, a single objective is optimised at the cost of other essential factors, such as energy consumption, network robustness, and data transmission reliability. This paper proposes a new UWSN protocol based on the tiger beetle optimisation (TBO) algorithm for multiobjective K-means clustering (TBO-MOK). The protocol comprises …

Smartphone Authentication Based On 3d Touch Sensor And Finger Locations On Touchscreens Via Decision-Making Techniques, Moceheb Lazam Shuwandy, Rawan Adel Fawzi Alsharida, Maytham M. Hammood

Mesopotamian Journal of CyberSecurity

Smartphone authentication systems must balance security and user convenience, which is a persistent challenge in the digital realm. Traditional biometrics, such as fingerprints and facial recognition, face vulnerabilities to spoofing and environmental conditions, limiting reliability. This study introduces a novel approach by integrating three-dimensional (3D) touch sensors with finger location data for authentication. The goal is to develop a system that improves accuracy while minimizing false positives and negatives, leveraging touch pressure and spatial interaction as unique biometric identifiers. Data from 20 participants, including pressure levels, spatial coordinates, and timestamps, were analysed using Random Forest (RF) and Extreme Gradient Boosting …

Enhancing Cybersecurity With Machine Learning: A Hybrid Approach For Anomaly Detection And Threat Prediction, Adil M. Salman, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Hussein Alkattan, Hussein Alkattan

Mesopotamian Journal of CyberSecurity

In today's digital era, cybersecurity has become a principal concern because of the increasing frequency and advancement of cyber threats. This study explores machine learning models for detecting and predicting anomalies in cybersecurity datasets. The research evaluates models such as linear regression, decision tree, RF, gradient boosting, KNN, SVR, LSTM, and neural networks utilizing performance metrics such as accuracy, MAE and MSE. A hybrid model that integrates different learning strategies is additionally proposed to improve the predictive accuracy and strength. The results highlight the superiority of ensemble approaches, especially the hybrid model, in improving peculiarity detection capabilities. The comparative analysis …

Enhancing Traffic Data Security In Smart Cities Using Optimized Quantum-Based Digital Signatures And Privacy-Preserving Techniques, Tuqa Ghani Tregi, Mishall Al-Zubaidie

Mesopotamian Journal of CyberSecurity

Securing big data in power plants is an important and fundamental step in the infrastructure of smart cities. In addition, it becomes a barrier if it is not controlled from the beginning. Security must be a combination of fast and robust properties. This research presents a traffic security system (TSS) in a smart city (SC). It is a novel paradigm meant to improve data security and integrity by means of a multilayered method. Advanced fault analysis, dual-stage pseudonymizing, quantum key distribution via the BB84 protocol, and Falcon signatures (FS) are combined in the proposed system. TSS enhances data security by …

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. …