Physical Sciences and Mathematics Commons^™

New Observations On The Age And Origin Of The Geologist Seamounts, South Hawaiian Seamount Province, Brandon Chester Scott

UNLV Theses, Dissertations, Professional Papers, and Capstones

Investigation into seamounts that stem from intraplate volcanism—that is volcanism occurring far from plate boundaries—presents an opportunity to deconvolve processes associated with mantle compositional heterogeneities and melting dynamics. Upwelling and decompression of thermochemically anomalous mantle plumes is the primary mechanism for significant intraplate volcanism; however, many seamounts dotted across the Pacific Plate do not correlate spatially, temporally, or geochemically with mantle plume volcanism. One region of enigmatic volcanism in the ocean basins that is not clearly attributable to plume-derived magmatism are the Geologist Seamounts and the wider South Hawaiian Seamount Province (∼19°N, 157°W). Here we present merged multibeam (<100 m) and satellite altimetry bathymetric maps of the Geologist Seamounts region, new ^{40 …}

Electronic Note-String Detector, Gavin Garcia-Rossi, Tommy Smail

Electrical Engineering

As the virtual space has become a dominant part of everyone’s day-to-day lives, many normal face-to-face interactions and services have not yet been facilitated by adapting technology. One of these prevailing areas is music lessons. Over Zoom meetings, or other virtual platforms, it is tremendously challenging to teach students. These challenges include recognizing student mistakes audibly and visually, and being able to give confident feedback on the incorrect notes played by learning musicians. Without having to delve into improving the complex systems that would be required to improve audio, video, and connection quality of these connections, we have another solution …

Rapid Reaction Studies On The Chemistry Of Flavin Oxidation In Urocanate Reductase, Niusha Delavari

Masters Theses

Urocanate reductase (UrdA) is a bacterial flavin-dependent enzyme that reduces urocanate to imidazole propionate, enabling bacteria to use urocanate as an alternative respiratory electron acceptor. Elevated serum levels of imidazole propionate are associated with the development of type 2 diabetes and, since UrdA is only present in humans in gut bacteria, this enzyme has emerged as a significant factor linking the health of the gut microbiome and the metabolic disorder insulin resistance. Here we investigated the chemistry of flavin oxidation by urocanate in the isolated FAD domain of UrdA (UrdA’) using anaerobic stopped-flow experiments at 4 °C. This analysis unveiled …

Multi-Layer Evolution Of Acoustic-Gravity Waves And Ionospheric Disturbances Over The United States After The 2022 Hunga Tonga Volcano Eruption, P. A. Inchin, A. Bhatt, S. A. Cummer, S. D. Eckermann, B. J. Harding, J. Ma, J. J. Makela, J B. Snively

Publications

e Hunga-Tonga Hunga-Ha'apai volcano underwent a series of large-magnitude eruptions that generated in the atmosphere. We investigate the spatial and temporal evolutions of fluctuations driven by atmospheric acoustic-gravity waves (AGWs) and, in particular, the Lamb wave modes in high spatial resolution data sets measured over the Continental United States (CONUS), complemented with data over the Americas and the Pacific. Along with >800 barometer sites, tropospheric observations, and Total Electron Content data from >3,000 receivers, we report detections of volcano-induced AGWs in mesopause and ionosphere-thermosphere airglow imagery and Fabry-Perot interferometry. We also report unique AGW signatures in the ionospheric D-region, measured …

The Drying Of Dry Creek: A Paired Catchment Experiement Assessing Non-Perennial Headwater Streams, Elizabeth Crowther

Boise State University Theses and Dissertations

Intermittent streams make up the majority of waterways in the United States and are becoming more common in a changing climate, yet they lack stream gaging and habitat data compared to their perennial counterparts. Headwater streams in the western US can be classified as intermittent through seasonal contraction of flowing streams. Although small, they provide critical habitat for fish species and contribute to larger downstream systems. Predictive models, such as the Probability of Stream Permanence (PROSPER) model, have been created to map dry and intermittent reaches at the regional scale, yet they lack large-scale spring data sets as inputs for …

Seasonality In Terminus Ablation Rates For The Glaciers In Kalaallit Nunaat (Greenland), Aman K. C.

Boise State University Theses and Dissertations

Since the 1990s, the Greenland Ice Sheet (GrIS) has undergone accelerated mass loss, with a substantial portion due to the dynamic effects of terminus retreat. Conventional assessments of dynamic mass loss, however often overlook the critical aspect of terminus change, focusing primarily on inland ice flow. In this thesis, I construct and analyze mass loss due to both temporal variations in ice flow and detachment of ice from the glacier terminus, called terminus ablation, for 55 marine-terminating glaciers in Greenland over a ten-year period from 2013 to 2023. I calculated terminus ablation rates using openly accessible data for terminus positions, …

Uas-Based Quantification Of Dynamic Lahar Channel Morphology At Volcán De Fuego, Guatemala, Jerry Clay Mock

Boise State University Theses and Dissertations

Lahars are responsible for 26% of the deaths associated with volcanic activity reported since 1500 AD, and are extremely destructive to infrastructure (Thouret et al., 2020). Secondary lahars are volcanic mudflows commonly triggered by rainfall. Valuable land and buildings may be covered or destroyed by thick deposits including heavy boulders, mud, and debris. Bridges and roads can be washed out, cutting people off from vital services and potentially placing them in danger from other hazards. Volcán de Fuego in Guatemala actively produces pyroclastic material in small Strombolian eruptions every 15-20 minutes. Fuego occasionally has larger eruptions and has produced over …

An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour

Neutrosophic Systems with Applications

Since the importance of images in our lives and the advancements in computer data gathering methods, anyone can collect a large number of images, but most of them cannot be processed manually. Image processing therefore becomes appealing since various types of data may be represented and processed digitally. Image processing has become the most popular processing method, employed in security camera films, healthcare images, images from remote sensors, and naturalistic image/videos because of fast computers and processors. In order to raise cognitive function and speed up decision-making, image processing is crucial to many information access systems. Since ambiguity now permeates …

Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir

Knowledge Engineering and Data Science

Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for …

Eeg Classification While Listening To Murottal Al-Quran And Classical Music Using Random Forest Method, Heni Sumarti, Fahira Septiani, Agus Sudarmanto, Wahyu Caesarendra, Rizki Edmi Edison

Knowledge Engineering and Data Science

This study is aimed to classify the brain activity of adolescents associated with audio stimuli; murottal Al-Quran and classical music. The raw data were filtered using Independent Component Analisys (ICA) and followed by band-pass filter in Python on the Google Colab Extraction was processed with Power Spectral Density (PSD) and the Random Forest Method in Weka Machine Learning was used for classification. The research results showed the same results between the two types of stimulation, namely the order of brain waves from highest to lowest were delta, alpha, theta and beta. The average brain waves of teenagers when given murottal …

Deep Learning Approaches With Optimum Alpha For Energy Usage Forecasting, Aji Prasetya Wibawa, Agung Bella Putra Utama, Ade Kurnia Ganesh Akbari, Akhmad Fanny Fadhilla, Alfiansyah Putra Pertama Triono, Andien Khansa’A Iffat Paramarta, Faradini Usha Setyaputri, Leonel Hernandez

Knowledge Engineering and Data Science

Energy use is an essential aspect of many human activities, from individual to industrial scale. However, increasing global energy demand and the challenges posed by environmental change make understanding energy use patterns crucial. Accurate predictions of future energy consumption can greatly influence decision-making, supply-demand stability and energy efficiency. Energy use data often exhibits time-series patterns, which creates complexity in forecasting. To address this complexity, this research utilizes Deep Learning (DL), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU) models. The main objective is to improve the accuracy of …

The Effect Of The Number Of Hidden Layers On The Performance Of Deep Q-Network For Traveling Salesman Problem, Benzfica Hanif, Aisyah Larasati, Rudi Nurdiansyah, Trung Le

Knowledge Engineering and Data Science

The Traveling Salesman Problem (TSP) effectively represents the complex distribution issues encountered by couriers, who must carefully plan a route that includes all customer addresses while minimizing the distance traveled. As the magnitude of deliveries and the range of destinations expand, the courier's responsibility becomes progressively challenging. In this particular context, the objective of our research is to expand the existing knowledge and explore the complete capabilities of Deep Q-Network (DQN) models in order to achieve the most efficient route determination. This endeavor can potentially bring about significant changes in the courier and delivery service sector. The foundation of our …

Stacked Lstm-Gru Long-Term Forecasting Model For Indonesian Islamic Banks, Yayat Sujatna, Adhitio Satyo Bayangkari Karno, Widi Hastomo, Nia Yuningsih, Dody Arif, Sri Setya Handayani, Aqwam Rosadi Kardian, Ire Puspa Wardhani, L.M Rasdi Rere

Knowledge Engineering and Data Science

The development of the Islamic banking industry in Indonesia has become a significant concern in recent years, with rapid growth in the number of banks operating based on Sharia principles. To face emerging challenges and opportunities, a deep understanding of the long-term financial behavior of Islamic banks is becoming increasingly important. This study aims to predict the share price of PT Bank Syariah Indonesia Tbk, over 28 days using the LSTM-GRU stack. The observation stage includes importing the dataset, data separation, model variations, the training process, output, and evaluation. Observations were conducted using 10 model variations from 4 stacks of …

Comparison Of Machine Learning Algorithms For Species Family Classification Using Dna Barcode, Lala Septem Riza, M Ammar Fadhlur Rahman, Yudi Prasetyo, Muhammad Iqbal Zain, Herbert Siregar, Topik Hidayat, Khyrina Airin Fariza Abu Samah, Miftahurrahma Rosyda

Knowledge Engineering and Data Science

Classifying plant species within the Liliaceae and Amaryllidaceae families presents inherent challenges due to the complex genetic diversity and overlapping morphological traits among species. This study explores the difficulties in accurate classification by comparing 11 supervised learning algorithms applied to DNA barcode data, aiming to enhance the precision of species family classification in these taxonomically intricate plant families. The ribulose-1,5-bisphosphate carboxylase-oxygenase large sub-unit (rbcL) gene, selected as a DNA barcode locus for plants, is used to represent species within the Amaryllidaceae and Liliaceae families. The experimental results demonstrate that nearly all tested models achieve accurate species classification into the appropriate …

Dropped Objects Recognition In Offshore Operations Based On Computer Vision And Artificial Intelligence, Xiaochuan Yu

LSU New Orleans Theses and Dissertations

We are more interested in recovering and salvaging containers which may be loaded with either valuable or harmful substances. Therefore, we designed various container models to account for different loading conditions and then exported them to a 3D printer. Six small container models were dropped into the trailer pool at the University of New Orleans (UNO) as planned at angles of 0°, 45°, and 90°.

After collecting all the videos using a high-definition camera set outside the tank, we perform pre-processing tasks on the videos in preparation for model training. The two-phase angle classification method uses a pretrained ResNet50 model …

Motion Simulation And Risk Assessment Of Dropped Objects In Offshore Operations, Hanqi Yu

LSU New Orleans Theses and Dissertations

Subsea pipelines are a cost-effective and reliable way to transport hydrocarbons in offshore oil and gas development. However, dropped objects can pose hazards and cause damage to pipelines. This dissertation briefly introduces the hazards and hidden dangers caused by dropped containers, discusses motion simulation methods for different object shapes, and reviews risk assessment procedures for handling dropped objects in offshore operations. Ongoing research at the University of New Orleans' towing tank on dropped container models is also discussed. Using ANSYS Fluent, we simulate trajectories of container models and calculate relevant hydrodynamic coefficients for different dropped angles. We then apply risk …

Wavelet Compression As An Observational Operator In Data Assimilation Systems For Sea Surface Temperature, Bradley J. Sciacca

LSU New Orleans Theses and Dissertations

The ocean remains severely under-observed, in part due to its sheer size. Containing nearly billion of water with most of the subsurface being invisible because water is extremely difficult to penetrate using electromagnetic radiation, as is typically used by satellite measuring instruments. For this reason, most observations of the ocean have very low spatial-temporal coverage to get a broad capture of the ocean’s features. However, recent “dense but patchy” data have increased the availability of high-resolution – low spatial coverage observations. These novel data sets have motivated research into multi-scale data assimilation methods. Here, we demonstrate a new assimilation approach …

Measuring The Lengths Of Sperm Whales Of The Northern Gulf Of Mexico By Wavelet Analysis Of Their Usual Clicks, George Drouant

LSU New Orleans Theses and Dissertations

Abstract

Acoustic recordings of underwater sounds produced by marine mammals present an attractive alternative to costly and logistically complex ship based visual surveys for collecting population data for various species.

The first reported use of underwater acoustic recordings in the long-term monitoring of sperm whale populations was by Ackleh et al. (Ackleh et al., 2012). The paper describes counting sperm whale clicks at different locations to track population changes over time.

Analysis of sperm whale clicks offers additional insight into sperm whale populations. The echo location clicks (usual clicks) of sperm whales can be used to give an estimate of …

Virtual Reality In Simulation-Based Emergency Skills Training: A Systematic Review With A Narrative Synthesis, Jonathan R Abbas, Michael M H Chu, Ceyon Jeyarajah, Rachel Isba, Antony Payton, Brendan Mcgrath, Neil Tolley, Iain Bruce

Faculty, Staff and Student Publications

OBJECTIVE: An important role is predicted for virtual reality (VR) in the future of medical education. We performed a systematic review of the literature with a narrative synthesis, to examine the current evidence for VR in simulation-based emergency skills training. We broadly define emergency skills as any clinical skill used in the emergency care of patients across all clinical settings.

METHODS: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines. The data sources accessed during this study included: PubMed, CINAHL, EMBASE, AMED, EMCARE, HMIC, BNI, PsychINFO, Medline, CENTRAL, SCOPUS, Web of Science, BIOSIS …

Fimap A Fast Identity-By-Descent Mapping Test For Biobank-Scale Cohorts, Han Chen, Ardalan Naseri, Degui Zhi

Faculty, Staff and Student Publications

Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants. However, phased haplotype information is often ignored in GWAS or variant set tests for rare variants. Here we leverage the identity-by-descent (IBD) segments inferred from a random projection-based IBD detection algorithm in the mapping of genetic associations with complex traits, to develop a computationally efficient statistical test for IBD mapping in biobank-scale cohorts. …

Single-Cell Dna Methylome And 3d Multi-Omic Atlas Of The Adult Mouse Brain, Hanqing Liu, Qiurui Zeng, Jingtian Zhou, Anna Bartlett, Bang-An Wang, Peter Berube, Wei Tian, Mia Kenworthy, Jordan Altshul, Joseph R Nery, Huaming Chen, Rosa G Castanon, Songpeng Zu, Yang Eric Li, Jacinta Lucero, Julia K Osteen, Antonio Pinto-Duarte, Jasper Lee, Jon Rink, Silvia Cho, Nora Emerson, Michael Nunn, Carolyn O'Connor, Zhanghao Wu, Ion Stoica, Zizhen Yao, Kimberly A Smith, Bosiljka Tasic, Chongyuan Luo, Jesse R Dixon, Hongkui Zeng, Bing Ren, M Margarita Behrens, Joseph R Ecker

Faculty, Staff and Student Publications

Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation–methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 …

Brain-Wide Correspondence Of Neuronal Epigenomics And Distant Projections, Jingtian Zhou, Zhuzhu Zhang, May Wu, Hanqing Liu, Yan Pang, Anna Bartlett, Zihao Peng, Wubin Ding, Angeline Rivkin, Will N Lagos, Elora Williams, Cheng-Ta Lee, Paula Assakura Miyazaki, Andrew Aldridge, Qiurui Zeng, J L Angelo Salinda, Naomi Claffey, Michelle Liem, Conor Fitzpatrick, Lara Boggeman, Zizhen Yao, Kimberly A Smith, Bosiljka Tasic, Jordan Altshul, Mia A Kenworthy, Cynthia Valadon, Joseph R Nery, Rosa G Castanon, Neelakshi S Patne, Minh Vu, Mohammad Rashid, Matthew Jacobs, Tony Ito, Julia Osteen, Nora Emerson, Jasper Lee, Silvia Cho, Jon Rink, Hsiang-Hsuan Huang, António Pinto-Duartec, Bertha Dominguez, Jared B Smith, Carolyn O'Connor, Hongkui Zeng, Shengbo Chen, Kuo-Fen Lee, Eran A Mukamel, Xin Jin, M Margarita Behrens, Joseph R Ecker, Edward M Callaway

Faculty, Staff and Student Publications

Single-cell analyses parse the brain’s billions of neurons into thousands of ‘cell-type’ clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. …

Multivariate Analysis Approach To Factor-Affected Tuberculosis Disease, Zuli Agustina Gultom, Farid Akbar Siregar, Mahardika Abdi Prawira Tanjung, Al-Hamidy Hazidar

Knowledge Engineering and Data Science

Tuberculosis is a disease caused by infection with the mycobacterium tuberculosis complex. Tuberculosis attack organ besides the lung, such as the pleura, lining of the brain, lining of the heart, lymph gland, bones, joint, skin, intestines, kidney, urinary tract, and genital. This disease is found in densely populated settlements with poor sanitation, lack of ventilation and sunlight and lack of rest. Moreover, the factors that will be analyzed in this research are Population Density (X1), Number of HIV/AIDS (X2), number of toddlers who experience nutrition (X3), Number of toddlers who experience BCG immunization (X4), number of toddlers who get exclusive …

Evidence Of Students’ Academic Performance At The Federal College Of Education Asaba Nigeria: Mining Education Data, Arnold Adimabua Ojugo, Christopher Chukwufunaya Odiakaose, Frances Emordi, Rita Erhovwo Ako, Winifred Adigwe, Kizito Eluemonor Anazia, Victor Geteloma

Knowledge Engineering and Data Science

One main objective of higher education is to provide quality education to its students. One way to achieve the highest level of quality in the higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, and prediction about students’ performance. The knowledge is hidden among the educational data set and is extractable through data mining techniques. The present paper is designed to justify the capabilities of data mining …

Recurrent Session Approach To Generative Association Rule Based Recommendation, Tubagus Arief Armanda, Ire Puspa Wardhani, Tubagus M. Akhriza, Tubagus M. Adrie Admira

Knowledge Engineering and Data Science

This article introduces a generative association rule (AR)-based recommendation system (RS) using a recurrent neural network approach implemented when a user searches for an item in a browsing session. It is proposed to overcome the limitations of the traditional AR-based RS which implements query-based sessions that are not adaptive to input series, thus failing to generate recommendations. The dataset used is accurate retail transaction data from online stores in Europe. The contribution of the proposed method is a next-item prediction model using LSTM, but what is trained to develop the model is an associative rule string, not a string of …

Janus: Toward Preventing Counterfeits In Supply Chains Utilizing A Multi-Quorum Blockchain, Vika Crossland, Connor Dellwo, Golam Bashar, Gaby G. Dagher

Computer Science Faculty Publications and Presentations

The modern pharmaceutical supply chain lacks transparency and traceability, resulting in alarming rates of counterfeit products entering the market. These illegitimate products cause harm to end users and wreak havoc on the supply chain itself, costing billions of dollars in profit loss. In this paper, in response to the Drug Supply Chain Security Act (DSCSA), we introduce Janus, a novel pharmaceutical track-and-trace system that utilizes blockchain and cloning-resistant hologram tags to prevent counterfeits from entering the pharmaceutical supply chain. We design a multi-quorum consensus protocol that achieves load balancing across the network. We perform a security analysis to show robustness …

Preventing Inferences Through Data Dependencies On Sensitive Data, Primal Pappachan, Shufan Zhang, Xi He, Sharad Mehrotra

Computer Science Faculty Publications and Presentations

Simply restricting the computation to non-sensitive part of the data may lead to inferences on sensitive data through data dependencies. Inference control from data dependencies has been studied in the prior work. However, existing solutions either detect and deny queries which may lead to leakage – resulting in poor utility, or only protects against exact reconstruction of the sensitive data – resulting in poor security. In this paper, we present a novel security model called full deniability. Under this stronger security model, any information inferred about sensitive data from non-sensitive data is considered as a leakage. We describe algorithms for …

A Deeper Understanding Of The R Process, Mengke Li

All Dissertations

The overarching aim of my PhD research is to deepen our understanding of r-process nu- cleosynthesis. The initial phase of my work involved developing a Machine Learning-based nuclear mass model, specifically tailored to predict nuclear masses crucial for r-process nucleosynthesis. This model was then applied to simulate the r-process, focusing on neutron-rich nuclei significant to nucleosynthesis. The simulations yielded r-process abundance patterns, extending up to thorium and uranium, that align qualitatively with the observed solar system abundance patterns, with the characteristic peaks well positioned. Advancing our study further, we introduced a novel graph-based methodology named GrRproc for calculating r-process abundances. …

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Femtosecond Laser Shock Peening And The Dynamics Of Femtosecond Laser-Induced Shock Waves, Yuxin Li

All Dissertations

Laser shock peening (LSP) is an important material surface strengthening technique that uses laserinduced shock waves to cause severe plastic deformation near material surfaces. It can significantly improve material properties like hardness, strength, fatigue life, and corrosion resistance and is widely used in industrial sectors such as automotive, aerospace, nuclear, and medical areas. The conventional nanosecond laser shock peening (ns-LSP) has demonstrated effectiveness but faces challenges such as complex setup, low throughput, high energy consumption, and inflexibility for complex geometries. Femtosecond laser shock peening (fs-LSP) offers a promising alternative to overcome these issues, thanks to its ultra-high laser intensity and …