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Glacial Deposits, Vol. 48, 2024, Department Of Geography, Geology, And The Environment

Glacial Deposits

Newsletter of the Department of Geography, Geology, and the Environment

Assessment Of Avian Community Structure And Habitat Connectivity In The Fanno Creek Corridor Bird Surveys, Habitat Assessment, And Management Recommendations, Grace Hall

Environmental Science and Management Professional Master's Project Reports

Urbanization can significantly impact habitat quality and connectivity for avian communities, decreasing species richness and diversity. However, in highly fragmented habitats, urban parks and riparian zones can provide important habitat corridors for birds that facilitate movement and access to essential resources. On the west side of greater Portland, Oregon, Fanno Creek may serve as a habitat corridor for birds and other local wildlife.

Fanno Creek is a 25-kilometer tributary of the Tualatin River that runs through the cities of Portland, Beaverton, Tigard, and Durham in northwestern Oregon. The land surrounding the creek includes residential, commercial, and industrial properties as well …

Flowering Rush (Butomus Umbellatus) Id Guide For The Columbia River, Gabriel Campbell, Jacob Rose

Center for Lakes and Reservoirs Publications and Presentations

This is a picture based field guide for how to identify Flowering Rush (Butomus umbellatus) in the Columbia River throughout Oregon and Washington. It includes how to tell this species from commonly co-occurring look-alike species.

An Image Processing Approach For Real-Time Safety Assessment Of Autonomous Drone Delivery, Assem A. Abdelhak, Dan Moss, Alan Hicks, Susan Mckeever

Articles

The aim of producing self-driving drones has driven many researchers to automate various drone driving functions, such as take-off, navigation, and landing. However, despite the emergence of delivery as one of the most important uses of autonomous drones, there is still no automatic way to verify the safety of the delivery stage. One of the primary steps in the delivery operation is to ensure that the dropping zone is a safe area on arrival and during the dropping process. This paper proposes an image-processing-based classification approach for the delivery drone dropping process at a predefined destination. It employs live streaming …

Designing Ris-Assisted Uav 3d Trajectory Using Deep Reinforcement Learning, Linsong Li

Electronic Theses and Dissertations

Unmanned aerial vehicles (UAVs) are increasingly employed as temporary base stations or access points to facilitate data transfer between ground terminals (GTs). However, in urban environments, UAV-GT communication links often face challenges due to obstructions from buildings and other obstacles, resulting in reduced data transfer efficiency. Reconfigurable intelligent surfaces (RIS) provide a promising solution by reflecting signals to enhance communication quality between UAVs and GTs. This thesis addresses the critical challenge of responsive UAV trajectory optimization in RIS-assisted communication networks. A novel approach is proposed, integrating federated learning with reinforcement learning techniques, specifically Double Deep Q-Network (DDQN) and Deep Deterministic …

Effects Of Timber Harvest On Understory Vegetation Succession: A Time Series Study, Reese A. Poindexter, Trevor Weeks, Chad Bishop, Akasha Faist

Undergraduate Theses, Professional Papers, and Capstone Artifacts

Timber harvest, as a necessary and common global practice, can significantly affect the ecosystems being harvested through opening the canopy, disturbing the understory, and resetting successional trajectories. This study examined how timber harvest influenced understory plant functional group dominance, understory species richness, and understory species dominance along a 40-year, or older, harvest timeline across two forest types (mesic and xeric) in Northwestern Montana, U.S.A. In our two forest types, vegetation sampling was completed at 208 sites with 1,040 quadrats across six timber-harvest timelines. Harvest timelines varied from the most recent at 1-5 years post-harvest to over 40 years as the …

The Effect Of Seasonal Ice Cover Duration On Shoreline Erosion In Lake Michigan, Ryan S. Navarre

Dissertations, Master's Theses and Master's Reports

Shoreline erosion in Lake Michigan has been a significant concern for coastal management. Promoting coastal stability and resilience is paramount to protecting these environments, especially amid climate change. While several factors are key in understanding shoreline erosion, seasonal ice cover duration is a prominent yet understudied factor in the Great Lakes region. Here, the relationship between ice cover duration and shoreline erosion rates is assessed across 7 regions of Lake Michigan. An ice cover duration dataset was created for Lake Michigan for 2011 – 2020 and its shorelines were digitized for years with available high-resolution aerial imagery. The statistical relationship …

Hurricane (2021) By John Rocco, Peter Shea

Picture Books

This book pictures the devastation of today's powerful storms. The hurricane wrecks things and drives people from their homes. The boy in the story finds his beloved dock broken up, where he used to swim and fish. The story centers on cooperation and neighborhood resilience: people can get through disasters if they work together.

Something, Someday (2023) By Amanda Gorman, Maughn Rollins Gregory

Picture Books

When children think philosophically they inevitably will, and unquestionably should engage in social criticism. In this picture book by the first U.S. National Youth Poet Laureate Amanda Gorman, a Black child in an urban apartment complex surrounded by garbage cleans it up and plants a vegetable and flower garden, enlisting the help of others and overcoming some setbacks. Gorman's text warns children that some adults may say they're too small, or that it’s none of their business, or that what they're trying won’t work, but she reassures them that sometimes it’s OK to ignore those people.

We Are Water Protectors (2020) By Carole Lindstrom, Peter Shea

Picture Books

We Are Water Protectors is a beautiful and partisan book, and the teacher or parent who wants to help children to think better could not find a better place to start, giving the child of whatever age the opportunity to feel the force of this plea, and then to recognize the need to understand the political context within which this issue arises, and the honest differences of opinion about policy that arise in an already disrupted world.

Constacyclic Codes Of Length With Three Prime Factors And Primitive Idempotents, Supakarn Rakphon

Chulalongkorn University Theses and Dissertations (Chula ETD)

Let Fq be a finite field of order q and t be a prime such that q t − 1 = l v1 1 l v2 2 l v3 3 c where l1, l2, l3 are distinct odd primes with gcd(l1l2l3, q(q−1)) = 1 and c is a positive integer with gcd(l1l2l3, c) = 1. In this thesis, we find all irreducible divisors of x l m1 1 l m2 2 l m3 3 −a over Fq and all generator polynomials for constructing a-constacyclic codes of length l m1 1 l m2 2 l m3 3 . In addition, we …

Effective Data Augmentation Techniques For Time Series Classification: An Empirical Evaluation, Pongpanod Sankosik

Chulalongkorn University Theses and Dissertations (Chula ETD)

Time series classification is crucial in fields such as healthcare, finance, and industrial processes, but it faces challenges like temporal data ordering, class im-balance, noise, and limited data. This research explores data augmentation techniques to improve classification performance, focusing on the MiniRocket classifier across 85 UCR datasets. The study identifies conditions under which augmentation techniques, like wDBA, enhance accuracy, though overall performance may vary. A dataset-specific approach is essential for effective augmentation. The research also examines the impact of augmentation on datasets with different characteristics, providing insights into when specific strategies are most benefi-cial. Future work includes optimizing augmentation methods …

Building A Human Digital Twin (Hdtwin) Using Large Language Models For Cognitive Diagnosis: Algorithm Development And Validation, Gina Sprint, Maureen Schmitter-Edgecombe, Diane Cook

Computer Science Faculty Scholarship

Background: Human digital twins have the potential to change the practice of personalizing cognitive health diagnosis because these systems can integrate multiple sources of health information and influence into a unified model. Cognitive health is multifaceted, yet researchers and clinical professionals struggle to align diverse sources of information into a single model. Objective: This study aims to introduce a method called HDTwin, for unifying heterogeneous data using large language models. HDTwin is designed to predict cognitive diagnoses and offer explanations for its inferences. Methods: HDTwin integrates cognitive health data from multiple sources, including demographic, behavioral, ecological momentary assessment, n-back test, …

Social Networks And Large Language Models For Division I Basketball Game Winner Prediction, Gina Sprint

Computer Science Faculty Scholarship

Sporting event outcome prediction is a well-established and actively researched domain, with a particular focus on college basketball’s March Madness tournament. Researchers, fans, and gamblers alike seek accurate game-level predictions using features such as tournament seeds, season performance, and expert opinions. While machine learning algorithms have been harnessed to build prediction models, no perfect model or human-created bracket has emerged. This paper explores a novel approach to basketball game outcome prediction by utilizing the power of social networks and large language models (LLMs). LLMs are trained to understand and generate text, often eliminating the need for a feature engineering step. …

Exploring Market Segmentation For Autonomous Ferries, Ashari Fitra Rachmannullah, Taih Cherng Lirn, Kuo Chung Shang

Journal of Marine Science and Technology–Taiwan

This study aims to investigate the determinants that underlie psychographic segmentation in the domain of autonomous ferries (AFs) by using the theory of planned behaviour (TPB) as a guiding theoretical construct. The paper focuses on Indonesian individuals who had previously utilised conventional ferry services. TPB was applied as a catalyst to identify possible market segmentation among potential AF passengers. In this study, cluster analysis is used to differentiate passengers by their perception of using AFs. The results identified three market segments through cluster analysis based on passengers’ perceptions of using AFs: Resource-Limited, Resource-Capable, and Value-Optimistic. Among these segments, the Resource-Capable …

Adaptive Prediction Horizon Energy-Saving Collision-Free Mpc Of Ships Based On Ship-Shore Cooperation, Han Xue, Enjie Yang

Journal of Marine Science and Technology–Taiwan

ABSTRACT:In order to perform the close association between ship maneuvering control and energy consumption through the control strategy, this paper designs an adaptive prediction horizon based energy-saving robust nonlinear model predictive control (APHERNMPC) for underactuated ships to deal with the actual control and state constraints during berthing based on ship-shore cooperation. An improved Emperor Penguin Optimizer (EPO) method is proposed for collision avoidance decision. To solve the problems of falling into local optimum and reducing the convergence speed, the traditional EPO is improved based on Sobol sequence in order to enhance the diversity and ergodicity of the population. The multi-ship …

Research And Design A Lifeboat Virtual Reality Simulation System For Maritime Safety Training In Vietnam, Nguyen Dinh Thach, Nguyen Van Hung

Journal of Marine Science and Technology–Taiwan

Ensuring maritime safety and security is crucial for all nations. Training trainees and operational officers in this field aims to enhance their professional skills and ability to manage and resolve incidents at sea. This article outlines the development of a lifeboat simulation system that integrates Virtual Reality (VR) technology in accordance with international maritime regulations. It describes the creation of an algorithm designed to optimize data transmission between simulation systems using the ant colony optimization technique in conjunction with intelligent control algorithms on Unity 3D software for human interaction. In particular, the system combines training with a maritime simulation framework …

Sales Forecasting For Retail Business Using Xgboost Algorithm And Timesfm, Prathana Dankorpho

Chulalongkorn University Theses and Dissertations (Chula ETD)

The retail industry is continuously evolving with the expansion of sales channels and the diversification of product assortments. However, current forecasting methods, relying on simplistic statistical models, frequently encounter difficulties in adjusting to the dynamic environment. This limitation leads to challenges in accurately predicting sales. Consequently, there is a critical need to improve the accuracy and frequency of sales predictions to enable timely decision-making for business strategies. Through a comprehensive analysis of datasets from 2019 to 2023, this study illustrates the advantages of integrating XGBoost and TimesFM to gain deeper insights into sales patterns. Results demonstrate a significant enhancement in …

Analyzing Business Model Components For Solar Pv Adoption In Mexican Organizations, Erick Ruben Rascon Zapien

Chulalongkorn University Theses and Dissertations (Chula ETD)

The decarbonization of the energy sector is essential in the fight against climate change, making it important to analyze how to facilitate this transition towards renewable energy in society. This research focuses on Mexico, a country whose policies and initiatives demonstrate an interest in the deployment of solar energy, but with a scarcity of literature regarding its use in commercial organizations. This study aims to explore the relationship between Business Model Canvas (BMC) components and the adoption of solar photovoltaic (PV) rooftops by 45 private organizations in Mexico. The study focuses on zero generation or customer-owned PV system, where the …

Contrastive Learning, With Application To Forensic Identification Of Source, Cole Ryan Patten

Electronic Theses and Dissertations

Forensic identification of source problems often fall under the category of verification problems, where recent advances in deep learning have been made by contrastive learning methods. Many forensic identification of source problems deal with a scarcity of data, an issue addressed by few-shot learning. In this work, we make specific what makes a neural network a contrastive network. We then consider the use of contrastive neural networks for few-shot learning classification problems and compare them to other statistical and deep learning methods. Our findings indicate similar performance between models trained by contrastive loss and models trained by cross-entropy loss. We …

Various Surfactant Soil Conditioner Effect On Plant Nutrient Concentration, Soil Nutrient Depletion, Soil Volumetric Water Content, Plant Biomass And Yield In Corn, Timothy Veldkamp

Electronic Theses and Dissertations

Soil conditioners help improve soil structure by increasing aeration, water infiltration and water holding capacity leading to nutrient availability and reduced irrigation needs. The goal of this study was to evaluate the impact of multiple soil conditioners (SC1, SC2, SC3, SC4, and SC5) on corn (Zea mays L.) and their ability to reduce irrigation by 30%. This was evaluated in the field in 2022 and 2023 by Aurora, SD using a Randomized Complete Block Design with six replications. Conditioners were applied as broadcast pre-emergence treatments with 70% irrigation. Control treatments of 70% and 100% irrigation, respectively were included. SC1 application …

Whole Genome Crispr-Cas9 Screens Identify Genes Contributing To Viral Entry And Phagocytosis, Md Saddam Hossain

Electronic Theses and Dissertations

CRISPR/Cas9 is a revolutionary technique for genome editing where Cas9 nucleases can be targeted to specific genomic sites by single-guide RNAs (sgRNAs) containing roughly 20-nucleotide sequences that are complementary to the target region. Double strand breaks created by Cas9 are repaired through non-homologous end-joining (NHEJ) in most cells, resulting in insertions and deletions leading to frame shift mutations in coding regions. Thus, the CRISPR-Cas9 system can be exploited for systematic evaluation of gene function relationships by whole genome screening. We also developed a CRISPR whole‐genome screen and counter‐screen strategy based on a pseudoviral platform that allowed identification of genes specific …

Analysis Of Toxic Chemical Agents And Therapeutics For Toxic Inhaled Agents’ Exposure, Khadija Bilkis

Electronic Theses and Dissertations

When inhaled, toxic inhalation agents (TIAs) such as cyanide (CN), ammonia and sulfur compounds (e.g. methanethiol (MeSH)) can be fatal. Many TIAs cause cellular hypoxia, cytotoxic anoxia, apnea, respiratory failure, neurodegenerative disorder, circulatory collapse, seizures, and potential death by blocking mitochondrial cytochrome c oxidase. All TIA’s have the potential to be employed as chemical warfare agents, terrorist weapons, or dangerous occupational gases. Although many TIAs are potential threats, there are minimal FDA-approved treatments for these substances useful in a mass-casualty situation. Recently, cobinamide (Cbi) has come to light as a potential antidote for MeSH poisoning. However, methods for analyzing MeSH …

Optimal Network Analysis Through Vertex Order Coloring Of Intuitionistic Fuzzy Graph Operations, A. Meenakshi, S. Dhanushiya, Hong Qin, Maniyandy Elangovan

Data Science Faculty Publications

Intuitionistic fuzzy graphs IFGs are a powerful tool for modeling uncertainty and complex relationships. They offer versatile frameworks for addressing real-world challenges. In this research, we have introduced intuitionistic fuzzy vertex order coloring IFVOC and analyzed the alpha-strong (alpha str), beta-strong (beta str), and gamma-strong (gamma str) vertices through their degree. We explored important theorems based on the types of strong vertices, broadening the scope of our study. We analyzed multiple IFG products to determine the most optimal network based on some important metrics, including the weight and total number of alpha str vertices, the chromatic number, and the weight …

Heuristic Machine Learning Approaches For Identifying Phishing Threats Across Web And Email Platforms, Ramprasath Jayaprakash, Krishnaraj Natarajan, J. Alfred Daniel, Chandru Vignesh Chinnappan, Jayant Giri, Hong Qin, Saurav Mallik

Data Science Faculty Publications

Life has become more comfortable in the era of advanced technology in this cutthroat competitive world. However, there are also emerging harmful technologies that pose a threat. Without a doubt, phishing is one of the rising concerns that leads to stealing vital information such as passwords, security codes, and personal data from any target node through communication hijacking techniques. In addition, phishing attacks include delivering false messages that originate from a trusted source. Moreover, a phishing attack aims to get the victim to run malicious programs and reveal confidential data, such as bank credentials, one-time passwords, and user login credentials. …

Interpreting Neural Operators: How Nonlinear Waves Propagate In Non-Reciprocal Solids, Jonathan Colen, Alexis Poncet, Denis Bartolo, Vincenzo Vitelli

Data Science Faculty Publications

We present a data-driven pipeline for model building that combines interpretable machine learning, hydrodynamic theories, and microscopic models. The goal is to uncover the underlying processes governing nonlinear dynamics experiments. We exemplify our method with data from microfluidic experiments where crystals of streaming droplets support the propagation of nonlinear waves absent in passive crystals. By combining physics-inspired neural networks, known as neural operators, with symbolic regression tools, we generate the solution, as well as the mathematical form, of a nonlinear dynamical system that accurately models the experimental data. Finally, we interpret this continuum model from fundamental physics principles. Informed by …

Large Offshore Wind Farms Have Minimal Direct Impacts On Air Quality, Maryam Golbazi, Cristina L. Archer

Data Science Faculty Publications

Wind power has rapidly grown over the past decade because it is clean, renewable, and abundant. However, wind farms can affect local weather and possibly alter the transport, diffusion, and concentration of air pollutants. Given the unprecedented expansion of offshore wind farms planned along the U.S. East Coast by the Bureau of Ocean Energy Management (BOEM), this study aims to investigate if and how those future offshore wind farms might directly affect air pollution along the densely populated East Coast, in particular, the concentrations of ozone (O₃), fine particulate matter (PM_2.5), sulfur dioxide (SO₂), …

Anonymous Attribute-Based Broadcast Encryption With Hidden Multiple Access Structures, Tran Viet Xuan Phuong

School of Cybersecurity Faculty Publications

Due to the high demands of data communication, the broadcasting system streams the data daily. This service not only sends out the message to the correct participant but also respects the security of the identity user. In addition, when delivered, all the information must be protected for the party who employs the broadcasting service. Currently, Attribute-Based Broadcast Encryption (ABBE) is useful to apply for the broadcasting service. (ABBE) is a combination of Attribute-Based Encryption (ABE) and Broadcast Encryption (BE), which allows a broadcaster (or encrypter) to broadcast an encrypted message, including a predefined user set and specified access policy to …

Deep Transfer Learning-Based Bird Species Classification Using Mel Spectrogram Images, Mrinal Kanti Baowaly, Bisnu Chandra Sarkar, Md.Abul Ala Walid, Md. Martuza Ahamad, Bikash Chandra Singh, Eduardo Silva Alvarado, Imran Ashraf, Md. Abdus Samad

School of Cybersecurity Faculty Publications

The classification of bird species is of significant importance in the field of ornithology, as it plays an important role in assessing and monitoring environmental dynamics, including habitat modifications, migratory behaviors, levels of pollution, and disease occurrences. Traditional methods of bird classification, such as visual identification, were time-intensive and required a high level of expertise. However, audio-based bird species classification is a promising approach that can be used to automate bird species identification. This study aims to establish an audio-based bird species classification system for 264 Eastern African bird species employing modified deep transfer learning. In particular, the pre-trained EfficientNet …

A Systemic Mapping Study On Intrusion Response Systems, Adel Rezapour, Mohammad Ghasemigol, Daniel Takabi

School of Cybersecurity Faculty Publications

With the increasing frequency and sophistication of network attacks, network administrators are facing tremendous challenges in making fast and optimum decisions during critical situations. The ability to effectively respond to intrusions requires solving a multi-objective decision-making problem. While several research studies have been conducted to address this issue, the development of a reliable and automated Intrusion Response System (IRS) remains unattainable. This paper provides a Systematic Mapping Study (SMS) for IRS, aiming to investigate the existing studies, their limitations, and future directions in this field. A novel semi-automated research methodology is developed to identify and summarize related works. The innovative …