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2023

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Electrochemical And Colorimetric Nanosensors For Detection Of Heavy Metal Ions: A Review, Sayo Fakayode, Charuksha Walgama, Vivian E. Fernand Narcisse, Cidya Grant Dec 2023

Electrochemical And Colorimetric Nanosensors For Detection Of Heavy Metal Ions: A Review, Sayo Fakayode, Charuksha Walgama, Vivian E. Fernand Narcisse, Cidya Grant

Chemistry, Physics and Astronomy Faculty Scholarship

Human exposure to acute and chronic levels of heavy metal ions are linked with various health issues, including reduced children’s intelligence quotients, developmental challenges, cancers, hypertension, immune system compromises, cytotoxicity, oxidative cellular damage, and neurological disorders, among other health challenges. The potential environmental HMI contaminations, the biomagnification of heavy metal ions along food chains, and the associated risk factors of heavy metal ions on public health safety are a global concern of top priority. Hence, developing lowcost analytical protocols capable of rapid, selective, sensitive, and accurate detection of heavy metal ions in environmental samples and consumable products is of global …

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Mgmt Promoter Methylation Status Prediction Using Mri Scans? An Extensive Experimental Evaluation Of Deep Learning Models, Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi, Ikboljon Sobirov, Mohammad Yaqub Dec 2023

Mgmt Promoter Methylation Status Prediction Using Mri Scans? An Extensive Experimental Evaluation Of Deep Learning Models, Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi, Ikboljon Sobirov, Mohammad Yaqub

Computer Vision Faculty Publications

The number of studies on deep learning for medical diagnosis is expanding, and these systems are often claimed to outperform clinicians. However, only a few systems have shown medical efficacy. From this perspective, we examine a wide range of deep learning algorithms for the assessment of glioblastoma - a common brain tumor in older adults that is lethal. Surgery, chemotherapy, and radiation are the standard treatments for glioblastoma patients. The methylation status of the MGMT promoter, a specific genetic sequence found in the tumor, affects chemotherapy's effectiveness. MGMT promoter methylation improves chemotherapy response and survival in several cancers. MGMT promoter …

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The Effect Of Selected Demographic Factors On The Academic Achievement Of High School Students, Nuwayyir Alenezi Dec 2023

The Effect Of Selected Demographic Factors On The Academic Achievement Of High School Students, Nuwayyir Alenezi

Dissertations (2016-Present)

The purpose of this study was to examine the effect of selected demographic factors on the academic achievement of high school students. More specifically, this study was concerned with the effects of the variables gender, ethnicity, and socioeconomic status on the State of Texas Assessments of Academic Readiness (STAAR) scores in Mathematics, Science, English, and Social Studies. A quantitative causal-comparative or ex post facto research design was used in this study. The population for this study consists of high school students enrolled in a public school in the state of Texas during the 2019-2020 academic school year. The sample population …

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Bingroup2: Statistical Tools For Infection Identification Via Group Testing, Christopher R. Bilder, Brianna D. Hitt, Brad J. Biggerstaff, Joshua M. Tebbs, Christopher S. Mcmahan Dec 2023

Bingroup2: Statistical Tools For Infection Identification Via Group Testing, Christopher R. Bilder, Brianna D. Hitt, Brad J. Biggerstaff, Joshua M. Tebbs, Christopher S. Mcmahan

Department of Statistics: Faculty Publications

Group testing is the process of testing items as an amalgamation, rather than separately, to determine the binary status for each item. Its use was especially important during the COVID-19 pandemic through testing specimens for SARS-CoV-2. The adoption of group testing for this and many other applications is because members of a negative testing group can be declared negative with potentially only one test. This subsequently leads to significant increases in laboratory testing capacity. Whenever a group testing algorithm is put into practice, it is critical for laboratories to understand the algorithm’s operating characteristics, such as the expected number of …

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Spatial Visualization Of High School Geometry Students, Jennifer Crissey Dec 2023

Spatial Visualization Of High School Geometry Students, Jennifer Crissey

Dissertations

Spatial ability has been defined as “the innate ability to visualize that a person has before any formal training has occurred, i.e., a person is born with ability” (Sorby, 1999, p. 21) and is comprised of spatial orientation and spatial skills.Each of these facets are used in everyday life. High school students can enhance their spatial visualization skills through experiences and instruction. The purpose of this study was to test an intervention with the aim of increasing high school geometry students’ spatial visualization skills. The participants in this study were high school geometry students who were randomly placed in either …

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Good Practices And Common Pitfalls In Climate Time Series Changepoint Techniques: A Review, Robert B. Lund, Claudie Beaulieu, Rebecca Killick, Qiqi Lu, Xueheng Shi Dec 2023

Good Practices And Common Pitfalls In Climate Time Series Changepoint Techniques: A Review, Robert B. Lund, Claudie Beaulieu, Rebecca Killick, Qiqi Lu, Xueheng Shi

Department of Statistics: Faculty Publications

Climate changepoint (homogenization) methods abound today, with a myriad of techniques existing in both the climate and statistics literature. Unfortunately, the appropriate changepoint technique to use remains unclear to many. Further complicating issues, changepoint conclusions are not robust to perturbations in assumptions; for example, allowing for a trend or correlation in the series can drastically change changepoint conclusions. This paper is a review of the topic, with an emphasis on illuminating the models and techniques that allow the scientist to make reliable conclusions. Pitfalls to avoid are demonstrated via actual applications. The discourse begins by narrating the salient statistical features …

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Multimodal Image Synthesis And Editing: The Generative Ai Era, Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Lingjie Liu, Adam Kortylewski, Christian Theobalt, Eric Xing Dec 2023

Multimodal Image Synthesis And Editing: The Generative Ai Era, Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Lingjie Liu, Adam Kortylewski, Christian Theobalt, Eric Xing

Machine Learning Faculty Publications

As information exists in various modalities in real world, effective interaction and fusion among multimodal information plays a key role for the creation and perception of multimodal data in computer vision and deep learning research. With superb power in modeling the interaction among multimodal information, multimodal image synthesis and editing has become a hot research topic in recent years. Instead of providing explicit guidance for network training, multimodal guidance offers intuitive and flexible means for image synthesis and editing. On the other hand, this field is also facing several challenges in alignment of multimodal features, synthesis of high-resolution images, faithful …

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Statistical Inference Of Power Hazard Rate Distribution In The Presence Of Competing Risks Model With Application, Hassan M. Aljohani Dec 2023

Statistical Inference Of Power Hazard Rate Distribution In The Presence Of Competing Risks Model With Application, Hassan M. Aljohani

Journal of Statistics Applications & Probability

Over the last decades, several authors have studied competing strategies to analyse the risk. This article investigates the competing risks model when the failure times have power failure rate distribution. The model is formulated considering that causes of failure are independent, and a sample is obtained in complete form. The parameters are studied for the classical maximum likelihood and Baye’s methods. Also, we constructed confidence intervals concerning asymptotic maximum likelihood (ML) confidence intervals and bootstrap confidence intervals. Under the Bayesian approaches, we adopted the Markov chain Monte Carlo (MCMC) method to formulate credible intervals. The performances of estimators are discussed …

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Education In Light Of The Sustainable Development Goals In The Kingdom Of Bahrain, M. Khalifa, R. Alrasheed, Ali M. Aldada Dec 2023

Education In Light Of The Sustainable Development Goals In The Kingdom Of Bahrain, M. Khalifa, R. Alrasheed, Ali M. Aldada

Journal of Statistics Applications & Probability

Quality education is one of the goals of sustainable development - ensuring quality, equitable and inclusive education for all and promoting lifelong learning opportunities for all, the Ministry of Education in the Kingdom of Bahrain has set a set of sub-goals to achieve this goal. Hence, the study aims to investigate the impact of sustainable development goals on education in Bahrain in order to identify the challenges and opportunities available to improve the quality of education, knowledge economy and develop human capital. This paper attempts to answer a major question: What is the impact of sustainable development on education in …

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Quadratic Transmuted Modified Size-Biased Lehmann Type-Ii Distribution, M. Ibrahem, M. M. Nassar, S. S. Radwan, A. Elmasry Dec 2023

Quadratic Transmuted Modified Size-Biased Lehmann Type-Ii Distribution, M. Ibrahem, M. M. Nassar, S. S. Radwan, A. Elmasry

Journal of Statistics Applications & Probability

In this paper, a two-parameter generalization of Modified Size-Biased Lehmann Type-II distribution is obtained, with the purpose of obtaining a more flexible model relative to the behaviour of hazard rate functions. Various statistical properties of this distribution including the density, hazard rate functions, quantile function, mode, moments, incomplete moments, moment generating functions, Lorenz, Bonferroni and Zenga curves, Rényi entropy and distribution of 𝑟# order statistics have been derived. The method of maximum likelihood estimation has been used to estimate the parameters of the Quadratic Transmuted-Modified Size-Biased Lehmann Type-II distribution and its performance is discussed by following a simulation study. Real …

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Understanding And Forecasting Of Credit Defaulters Using R- Programming, V. Bhatt, P. Pathak, S. Rastogi, Venkata M. Bhimavarapu, P. Tapas, S. Kadam Dec 2023

Understanding And Forecasting Of Credit Defaulters Using R- Programming, V. Bhatt, P. Pathak, S. Rastogi, Venkata M. Bhimavarapu, P. Tapas, S. Kadam

Journal of Statistics Applications & Probability

In Technology has provided numerous significant benefits to the financial industry. Financial transactions are now much smoother and faster than they were previously. Creditworthiness is a measure of how likely you are to repay your debt obligations, and it supports lenders decide whether or not to extend new credit to you. The current paper attempts to comprehend credit defaulters and develops a model to aid in understanding the determinants and prediction. A dataset of 376 responses was divided into training and testing data sets in proportions of 70% and 30%, respectively. The authors used traditional Binary Logistic Regression, Deep Learning, …

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A Tiered Approach To Markov Models When Future Events Are Not Independent Of The Past: An Application In Web Analytics, Judah Soobramoney, Retius Chifurira, Knowledge Chinhamu, Temesgen Zewotir Dec 2023

A Tiered Approach To Markov Models When Future Events Are Not Independent Of The Past: An Application In Web Analytics, Judah Soobramoney, Retius Chifurira, Knowledge Chinhamu, Temesgen Zewotir

Journal of Statistics Applications & Probability

The internet has become a digital marketplace that offers goods and services globally. Thereby, compelling enterprises to optimize their websites and online strategies. This paper sought to employ Markov chain models to predict the most likely next webpage viewed. A website comprises several pages (such as “Home”, “About-Us”) and visitors would transition from one page to another by clicking on respective links. The study was conducted on the website of a South African engineering and engineering training company “TEKmation”. The transition probabilities therefore represent the likelihood of moving to a certain webpage, given that the visitor is on a specific …

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Financial Market Index Prediction Using Machine Learning, Abdelgalal O. I. Abaker, Abdalla S. Mahmoud, Abdalla. Ahmed, Ali Rashash R Alzahrani, Adil. O. Y. Mohamed, Azhari A. Elhag Dec 2023

Financial Market Index Prediction Using Machine Learning, Abdelgalal O. I. Abaker, Abdalla S. Mahmoud, Abdalla. Ahmed, Ali Rashash R Alzahrani, Adil. O. Y. Mohamed, Azhari A. Elhag

Journal of Statistics Applications & Probability

The present work aims to tackle the crucial objective of forecasting values for a range of financial market indices in order to maximize income while minimizing potential losses. This study utilizes a comparative analysis approach to examine the performance of artificial neural networks (ANNs) and decision tree models in predicting stock market movements in Saudi Arabia (KSA). The analysis is conducted using a daily database. The predictive models included in this study are constructed using historical stock market data, which encompasses the time period from January 1, 2013, to October 4, 2023. The primary objective of these models is to …

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Comparative Bayesian Analysis Of Garch And Stochastic Volatility Models Using R And Stan, Muhammed Navas T, Mosab I. Tabash, Shazia Farhin, Athar Ali Khan Dec 2023

Comparative Bayesian Analysis Of Garch And Stochastic Volatility Models Using R And Stan, Muhammed Navas T, Mosab I. Tabash, Shazia Farhin, Athar Ali Khan

Journal of Statistics Applications & Probability

This study uses modelling and model comparison to compare three widely used GARCH models with their stochastic volatility (SV) counterparts in modelling the dynamics of inflation rates using the Bayesian approach. BRICS country consumer price index (CPI) data are used to assess these models. We find that the stochastic volatility models perform better than the GARCH models most of the time. The stochastic volatility in the leverage (SV-L) model is also demonstrated to be the most effective for the BRICS nations that we took into consideration. The article also looks at which model attributes are crucial in simulating inflation rates. …

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Estimation Of Diversification Effects/Benefits Using The Generalised Pareto Distribution - Extreme Value Gumbel Copula Model, O. Jakata, D. Chikobvu Dec 2023

Estimation Of Diversification Effects/Benefits Using The Generalised Pareto Distribution - Extreme Value Gumbel Copula Model, O. Jakata, D. Chikobvu

Journal of Statistics Applications & Probability

The objective of this paper is to estimate the diversification effects/benefits of an investment in a portfolio consisting of the South African Industrial (J520) and the Financial (J580) Indices using the Generalised Pareto Distributions (GPDs) with an extreme value Gumbel copula. The GPD is used as the marginal distribution to both assets to better characterise the extreme risk of returns in both Indices tails. The extreme value Gumbel copula captures the dependence structure (co-movement) of the financial assets in the portfolio. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) goodness of fit tests and the scatterplots indicate that …

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The Extended Log-Logistic Distribution: Properties, Inference, And Applications In Medicine And Geology, Ahmed Z. Afify, Ekramy A. Hussein, Badr Alnssyan, Hisham A. Mahran Dec 2023

The Extended Log-Logistic Distribution: Properties, Inference, And Applications In Medicine And Geology, Ahmed Z. Afify, Ekramy A. Hussein, Badr Alnssyan, Hisham A. Mahran

Journal of Statistics Applications & Probability

In this paper, a new flexible extension of the log-logistic model called the extended odd Weibull log-logistic (EOWLL) distribution is studied. The EOWLL density can be expressed as a mixture of Dagum densities. The EOWLL distribution provides decreasing, increasing, upside-down bathtub, and reversed-J-shaped hazard rates, and right-skewed, symmetrical, and left-skewed densities. Its mathematical properties are derived. The EOWLL parameters are estimated via eight classical methods of estimation. Additionally, extensive simulations are obtained to explore the performance of the proposed methods for small and large samples. Two real-life sets of data from medicine and geology are analyzed, showing the flexibility of …

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The Mediation Of Employee Motivation On The Relationship Between Non-Financial Incentives And Willingness Of Knowledge Sharing In Uae Public Sector, Walid A. M. A. Alrafi, K. C. Low, V. Senasi Dec 2023

The Mediation Of Employee Motivation On The Relationship Between Non-Financial Incentives And Willingness Of Knowledge Sharing In Uae Public Sector, Walid A. M. A. Alrafi, K. C. Low, V. Senasi

Journal of Statistics Applications & Probability

The key aim of the research is to analyze the mediating role of employee motivation in the relationship between non-financial incentives and employees’ willingness to knowledge sharing in the UAE public sector. The study will be particularly conducted on GDRFA, in UAE. Research Methodology: Ensuring the reliability and validity of a certain study is contingent upon designing it with appropriate techniques and methodology [26]. By using rigorous data collection methods and designing investigations that can be universally applied, it is feasible to obtain the most accurate and reliable data from respondents across various groups. The research design encompasses the population, …

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A Study Of The Saudi Stock Market Using Some Statistical Models, Abdelgalal O. I. Abaker, Abdalla S. Mahmoud, Badawi O.Mohammed, Ali R. R. Alzahrani, Adil. O. Y. Mohamed, Azhari A. Elhag Dec 2023

A Study Of The Saudi Stock Market Using Some Statistical Models, Abdelgalal O. I. Abaker, Abdalla S. Mahmoud, Badawi O.Mohammed, Ali R. R. Alzahrani, Adil. O. Y. Mohamed, Azhari A. Elhag

Journal of Statistics Applications & Probability

The objective of this paper is to estimate the diversification effects/benefits of an investment in a portfolio consisting of the South African Industrial (J520) and the Financial (J580) Indices using the Generalised Pareto Distributions (GPDs) with an extreme value Gumbel copula. The GPD is used as the marginal distribution to both assets to better characterize the extreme risk of returns in both Indices tails. The extreme value Gumbel copula captures the dependence structure (co-movement) of the financial assets in the portfolio. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) goodness of fit tests and the scatterplots indicate that …

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A Comparative Study On Market Index Prediction: Long Short- Term Memory (Lstm) Vs. Decision Tree Model, Afrah Al-Bossly, Manahill I. A. Anja, Abdelgalal O. I. Abaker, Hago E. M. Ali, Salem Alkhalaf Dec 2023

A Comparative Study On Market Index Prediction: Long Short- Term Memory (Lstm) Vs. Decision Tree Model, Afrah Al-Bossly, Manahill I. A. Anja, Abdelgalal O. I. Abaker, Hago E. M. Ali, Salem Alkhalaf

Journal of Statistics Applications & Probability

The main objective of this article is to develop a linear exponential function risks in Saudi banks (LINEXLF) to estimate the shape parameter, reliability, and hazard rate functions of the Pareto distribution based on Type II Censored Data. By weighting LINEX loss function to produce a modified loss function called weighted linear exponential (WLINEXLF) loss function. We then use WLINEXLF to derive the shape parameter, reliability, and hazard rate functions of the Pareto distribution. Furthermore, to examine the performance of the proposed method WLINEXLF we conduct a Monte Carlo simulation. The comparison is between the proposed method and other methods …

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Analyzing University Administrations Impact On Faculty Digital Self-Learning, Hanadi Alrashdan, Najwa Darawsheh, Saierah Aabed, Miriam Bsoul, Suzan Ganayem, Menas Mhameed Dec 2023

Analyzing University Administrations Impact On Faculty Digital Self-Learning, Hanadi Alrashdan, Najwa Darawsheh, Saierah Aabed, Miriam Bsoul, Suzan Ganayem, Menas Mhameed

Journal of Statistics Applications & Probability

The study aimed to identify the role of the university administration in enhancing the level of faculty members’ practice of digital heutagogy from the faculty members’ point of view, and the descriptive survey method was used. The study sample consisted of (352) faculty members, who were randomly selected from the study population of (2478). Members, and to achieve the objectives of the study, the (electronic) questionnaire was used as a tool for the study. The results showed that the role of the university administration in enhancing the level of faculty members’ practice of digital Hetogeology from the faculty members’ point …

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The Broadwater Formation (Pliocene) Of Nebraska And Southeastern Wyoming, Robert F. Diffendal Jr., James B. Swinehart Dec 2023

The Broadwater Formation (Pliocene) Of Nebraska And Southeastern Wyoming, Robert F. Diffendal Jr., James B. Swinehart

Robert F. Diffendal, Jr., Publications

The Broadwater Formation, initially defined in 1945, is a Pliocene-aged coarse-grained alluvial deposit in Nebraska and southeastern Wyoming. It is characterized by a complex stratigraphic history and debated geologic interpretations. The formation is a rich resource of groundwater for the citizens of Nebraska and the Central Great Plains. We aim to synthesize and redefine the Broadwater Formation, shedding light on its distribution, geological characteristics, and paleoenvironmental significance. While historical hypotheses on Broadwater Formation paleovalley trajectories suggested northwest-southeast trending valleys, later investigations proposed wind-driven erosional patterns to explain the unique topographic features observed. The Broadwater is divided into an unnamed Upper …

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Using Remote Sensing To Determine Riparian Resilience In Beaver Dammed Versus Un-Dammed Corridors Following Whiplash Weather, Sophie Charlotte Valérie Aubry Dec 2023

Using Remote Sensing To Determine Riparian Resilience In Beaver Dammed Versus Un-Dammed Corridors Following Whiplash Weather, Sophie Charlotte Valérie Aubry

Master of Science in Environmental Sciences and Management Projects

Beaver complexes slow and store water allowing for riparian growth which in turn fosters biodiversity, retains carbon, and enhances resistance to fires and drought. Given the benefits associated with beaver complexes and the potential they have for climate mitigation, California hopes to reintroduce beavers and restore their habitat throughout the state. However, the impact of high peak flow events on beaver complexes and their adjacent riparian corridors is less understood and requires more documentation at various spatial scales. To better understand the potential beavers may have as climate change mitigators it is important to understand beaver complex resiliency following a …

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Reimagining Large River Management Using The Resist–Accept–Direct (Rad) Framework In The Upper Mississippi River, Nicole K. Ward, Abigail J. Lynch, Erik A. Beever, Joshua Booker, Kristen L. Bouska, Holly Embke, Jeffrey N. Houser, John F. Kocik, Joshua Kocik, David J. Lawrence, Mary Grace Lemon, Doug Limpinsel, Madeline R. Magee, Bryan M. Maitland, Owen Mckenna, Andrew Meier, John M. Morton, Jeffrey D. Muehlbauer, Robert Newman, Devon C. Oliver, Heidi M. Rantala, Greg G. Sass, Aaron Shultz, Laura M. Thompson, Jennifer L. Wilkening Dec 2023

Reimagining Large River Management Using The Resist–Accept–Direct (Rad) Framework In The Upper Mississippi River, Nicole K. Ward, Abigail J. Lynch, Erik A. Beever, Joshua Booker, Kristen L. Bouska, Holly Embke, Jeffrey N. Houser, John F. Kocik, Joshua Kocik, David J. Lawrence, Mary Grace Lemon, Doug Limpinsel, Madeline R. Magee, Bryan M. Maitland, Owen Mckenna, Andrew Meier, John M. Morton, Jeffrey D. Muehlbauer, Robert Newman, Devon C. Oliver, Heidi M. Rantala, Greg G. Sass, Aaron Shultz, Laura M. Thompson, Jennifer L. Wilkening

School of Natural Resources: Faculty Publications

Background: Large-river decision-makers are charged with maintaining diverse ecosystem services through unprecedented social-ecological transformations as climate change and other global stressors intensify. The interconnected, dendritic habitats of rivers, which often demarcate jurisdictional boundaries, generate complex management challenges. Here, we explore how the Resist–Accept–Direct (RAD) framework may enhance large-river management by promoting coordinated and deliberate responses to social-ecological trajectories of change. The RAD framework identifies the full decision space of potential management approaches, wherein managers may resist change to maintain historical conditions, accept change toward different conditions, or direct change to a specified future with novel conditions. In the Upper Mississippi …

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Increasing Racial Diversity In The North American Plant Phenotyping Network Through Conference Participation Support, David Lebauer, Alexander Bucksch, Jennifer Clarke, Jesse Potts, Sonali Roy Dec 2023

Increasing Racial Diversity In The North American Plant Phenotyping Network Through Conference Participation Support, David Lebauer, Alexander Bucksch, Jennifer Clarke, Jesse Potts, Sonali Roy

Agricultural and Environmental Sciences Faculty Research

A key goal of the North American Plant Phenotyping Network (NAPPN) annual conference is to cultivate a new generation of scientists from diverse backgrounds. As part of their effort to diversify the plant phenomics research community, NAPPN acquired funding to cover all attendance costs for participants from historically black colleges and universities (HBCU) for the 2022 annual meeting. Seven award recipients represented the first attendees from HBCUs in the conference's 6-year history. In this commentary, we report on the impact of the conference awards, including lessons learned, and the future of the award.

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Effects Of Arbuscular Mycorrhizal Fungi Inoculation And Cover Crop On Soil Carbon Dynamics And Microbial Communities In A Mediterranean Lemon Orchard., Anna Rodriguez-Paiatsyka Dec 2023

Effects Of Arbuscular Mycorrhizal Fungi Inoculation And Cover Crop On Soil Carbon Dynamics And Microbial Communities In A Mediterranean Lemon Orchard., Anna Rodriguez-Paiatsyka

Master of Science in Environmental Sciences and Management Projects

Plant-associated fungi such as arbuscular mycorrhizal fungi (AMF) have the potential to sequester carbon (C), improve soil aggregation, and promote plant health. Due to multiple benefits of AMF to plant and soil health, AMF has gained much attention leading to a rapidly expanding market in mycorrhizal bio-stimulants intended to improve crop yield, root development, and soil health in horticultural crops, including citrus. However, there is limited information on how to inoculate a mature citrus orchard, and how inoculation of a mature orchard with AMF affects C sequestration. In this study, we planted a cover crop inoculated with AMF in a …

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Soil Burn Severity And Environmental Covariate Effects On Soil Health Two Years Postfire In The Sierra Nevada, Julie A. Lewis Dec 2023

Soil Burn Severity And Environmental Covariate Effects On Soil Health Two Years Postfire In The Sierra Nevada, Julie A. Lewis

Master of Science in Environmental Sciences and Management Projects

Wildfires have been steadily increasing in both size and severity in recent decades. This global trend is most evident in California, especially the North Coast and Sierra Nevada. Although these trends are rising, there is little known about the effects of these wildfires on forest soils. Soil is the 2nd largest C sink on the planet, and the largest terrestrial bank. Without understanding the implication of rising wildfire severities on these soils, we cannot understand how to help protect this resource in the future. Due to the rapid increase in wildfire size and intensity, there is little known about the …

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Development, Validation, And Testing Of A Novel Ergonomic Backpack, Lyndsey Kate Bouve Dec 2023

Development, Validation, And Testing Of A Novel Ergonomic Backpack, Lyndsey Kate Bouve

Theses and Dissertations (ETD)

Backpacks (BP) are one of the most common means for carrying loads but the loading mechanics that result from carrying heavy loads can have implications across the body. It has been suggested that loads in a BP should not excess 10-15% of the user’s body weight (BW) but that is not always feasible. The loads in a BP are transferred to the body via the shoulder strap which induce a shear and compressive force which act externally on the spine and transfer loads through it to the lumbar. Additionally, the weight of the bag induces an external moment that further …

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Every Relu-Based Neural Network Can Be Described By A System Of Takagi-Sugeno Fuzzy Rules: A Theorem, Barnabas Bede, Olga Kosheleva, Vladik Kreinovich Dec 2023

Every Relu-Based Neural Network Can Be Described By A System Of Takagi-Sugeno Fuzzy Rules: A Theorem, Barnabas Bede, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

While modern deep-learning neural networks are very successful, sometimes they make mistakes, and since their results are "black boxes" -- no explanation is provided -- it is difficult to determine which recommendations are erroneous. It is therefore desirable to make the resulting computations explainable, i.e., to describe their results by using commonsense rules. In this paper, we use "fuzzy" techniques -- techniques developed by Lotfi Zadeh to deal with commonsense rules formulated by using imprecise ("fuzzy") words from natural language -- to show that such a rule-based representation is always possible. Our result does not yet provide the desired explainability, …

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Smooth Non-Additive Integrals And Measures And Their Potential Applications, Olga Kosheleva, Vladik Kreinovich Dec 2023

Smooth Non-Additive Integrals And Measures And Their Potential Applications, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we explain why non-additive integrals and measures are needed, how non-additive integrals and measures are related, how to use them in decision making, and how they can help in fundamental physics. These four topics are covered, correspondingly, in Sections 2-5 of this paper.

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Why Sigmoid Transformation Helps Incorporate Logic Into Deep Learning: A Theoretical Explanation, Chitta Baral, Vladik Kreinovich Dec 2023

Why Sigmoid Transformation Helps Incorporate Logic Into Deep Learning: A Theoretical Explanation, Chitta Baral, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional neural networks start from the data, they cannot easily handle prior knowledge -- this is one of the reasons why they often take very long to train. It is desirable to incorporate prior knowledge into deep learning. For the case when this knowledge consists of propositional statements, a successful way to incorporate this knowledge was proposed in a recent paper by van Krieken et al. That paper uses the fact that a neural network does not directly return a truth value, it returns a real value -- in effect, the degree of confidence in the corresponding statement -- from …

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