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Articles 18721 - 18750 of 302466

Full-Text Articles in Physical Sciences and Mathematics

Surface Modification Of Carbon-Based Electrodes For Electrochemical Conversion Processes: Oxygen Reduction Reaction And Bicarbonate Conversion, Udari Shyamika Kodithuwakku Arachchige Jan 2023

Surface Modification Of Carbon-Based Electrodes For Electrochemical Conversion Processes: Oxygen Reduction Reaction And Bicarbonate Conversion, Udari Shyamika Kodithuwakku Arachchige

Theses and Dissertations--Chemistry

Oxygen reduction reaction (ORR) and conversion of bicarbonate into value-added chemicals are two significant electrochemical processes for energy storage and conversion. ORR is an important electrochemical reaction in fuel cells and metal-air batteries that provide power conversion and storage capacity, respectively, for portable electronics, and electric vehicles. However, the performance of catalysts (e.g., platinum-based) is critically limited by slow kinetics, inefficient four-electron pathway, and surface deactivation. This limited performance of platinum-based catalysts, the scarcity of platinum, and vulnerable supply chains for critical minerals require the development of alternative electrocatalysts now more than ever. Carbon-based materials possess several key properties that …

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Spatiotemporal Analysis Of Extreme Precipitation In The Southern Great Plains Hydroclimate Region, P. Flanagan, R. Mahmood Jan 2023

Spatiotemporal Analysis Of Extreme Precipitation In The Southern Great Plains Hydroclimate Region, P. Flanagan, R. Mahmood

School of Natural Resources: Documents and Reviews

No abstract provided.

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Trustworthy Decentralized Last Mile Delivery Framework Using Blockchain, Ala' Alqaisi Jan 2023

Trustworthy Decentralized Last Mile Delivery Framework Using Blockchain, Ala' Alqaisi

Electronic Theses and Dissertations

The fierce competition and rapidly growing eCommerce market are painful headaches for logistics companies. In 2021, Canada Post’s parcel volume peaked at 361 million units with a minimum charge of $10 per each. The Last-Mile Delivery (LMD) is the final leg of the supply chain that ends with the package at the customer’s doorstep. LMD involves moving small shipments to geographically dispersed locations with high expectations on service levels and precise time windows. Therefore, it is the most complex and costly logistics process, accounting for more than 50% of the overall supply chain cost. Innovations like Crowdshipping, such as Uber …

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Practical Secure Aggregation In Federated Learning Using Additive Secret Sharing, Hamid Fazli Khojir Jan 2023

Practical Secure Aggregation In Federated Learning Using Additive Secret Sharing, Hamid Fazli Khojir

Electronic Theses and Dissertations

Federated learning is a machine learning technique where multiple clients with local data collaborate in training a machine learning model. In FedAvg, the main federated learning algorithm, clients train machine learning models locally and share the trained model with the server. While the sensitive data will never be sent to the server, a malicious server can construct the original training data by having access to the clients’ models in each training round. Secure aggregation techniques such as cryptography, trusted execution environment, or differential privacy are used to solve this problem. However, these techniques incur computation and communication overhead or affect …

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Resilience Theory And Coerced Resilience In Agriculture, S. M. Sundstrom, D. G. Angeler, C. R. Allen Jan 2023

Resilience Theory And Coerced Resilience In Agriculture, S. M. Sundstrom, D. G. Angeler, C. R. Allen

School of Natural Resources: Documents and Reviews

No abstract provided.

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Evolution Of The Southwest Drought Learning Network: Collective Response To Exceptional Drought, E. Elias, B. Fuchs, J. Lisonbee, T. Bernadt, V. Martinez, T. Haigh Jan 2023

Evolution Of The Southwest Drought Learning Network: Collective Response To Exceptional Drought, E. Elias, B. Fuchs, J. Lisonbee, T. Bernadt, V. Martinez, T. Haigh

School of Natural Resources: Documents and Reviews

No abstract provided.

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Modified Tracer Gas Injection For Measuring Stream Gas Exchange Velocity In The Presence Of Significant Temperature Variation, C. R. Jensen, D. P. Genereux, T. E. Gilmore, D. K. Solomon Jan 2023

Modified Tracer Gas Injection For Measuring Stream Gas Exchange Velocity In The Presence Of Significant Temperature Variation, C. R. Jensen, D. P. Genereux, T. E. Gilmore, D. K. Solomon

School of Natural Resources: Documents and Reviews

No abstract provided.

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Climate Change And The Specter Of Statelessness, Mark P. Nevitt Jan 2023

Climate Change And The Specter Of Statelessness, Mark P. Nevitt

Faculty Articles

What happens when climate change extinguishes entire nations? Neither international nor environmental law has provided a satisfactory answer to this weighty question. Climate change-induced flooding, storm surge, and sea level rise threaten the territorial integrity and habitability of several small island developing states, raising the specter of statelessness. We know that climate catastrophe is coming, but we have failed to take the necessary steps to safeguard several developing nations. This Article argues that innovative legal and policy solutions are needed today to prevent nation extinction tomorrow. I focus on two potential international governance solutions: the U.N. Framework Convention on Climate …

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Defining The "Quadruple-A" Player: What Makes A Baseball Player Succeed In The Minor Leagues And Fail In The Major Leagues?, Sam Bogen Jan 2023

Defining The "Quadruple-A" Player: What Makes A Baseball Player Succeed In The Minor Leagues And Fail In The Major Leagues?, Sam Bogen

CMC Senior Theses

The "Quadruple-A" player is defined as one who is too good to play in Triple-A (the league one step down from Major League Baseball) but not good enough to play consistently in Major League Baseball. This thesis paper attempts to explain the phenomenon of the "Quadruple-A" player. Using Triple-A data from 2013-2022 and Major League data from the "Statcast Era" (2015-2022), I build logistic and linear regression models to predict Major League success based on Triple-A performance data as well as Major League Statcast data, discovering that statistics related to how a player hits the ball such as the speed …

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Utilizing Machine Learning In Healthcare In An Ethical Fashion, Nishka Ayyar Jan 2023

Utilizing Machine Learning In Healthcare In An Ethical Fashion, Nishka Ayyar

CMC Senior Theses

This thesis paper explores the ethical considerations surrounding the use of machine learning (ML) solutions in healthcare. The background section discusses the basics of machine learning techniques and algorithms, and the increasing interest in their utilization in the healthcare sector. The paper then reviews and critically analyzes four studies that highlight concerns related to using ML in healthcare, including issues of bias, privacy, accountability, and transparency. Based on the analysis of these studies, the paper presents several recommendations for addressing these concerns. The paper concludes with a discussion on the potential benefits of using machine learning technology in healthcare. Ultimately, …

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A Study On Global Reef Deterioration: Exploring Coral Bleaching, Emily Fernandez Jan 2023

A Study On Global Reef Deterioration: Exploring Coral Bleaching, Emily Fernandez

CMC Senior Theses

This thesis is a study on coral bleaching and coral mortality, studying the relationship between variables such as depth, exposure, distance to shore, and temperature for percent bleaching. All of the analyses were made using two different data sets, that contain information about bleaching events in specific regions, and dates, and provide information factors such as depth, temperature, and exposure. Models were created for different relationships of variables for eco-regions, recent data, and countries. I attempted to find relationships between variables such as depth, temperature, exposure, and distance to shore, and how they affect coral bleaching. Unfortunately, I did not …

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High Sensitivity Of The Tiger Beetle, Cicindela Circumpicta, To Toxicity From Pyrethroids And Neonicotinoids, And Implications For Ecosystem Function And Species Extinctions, S. Svehla, T. Brosius, Leon Higley, T. Hunt Jan 2023

High Sensitivity Of The Tiger Beetle, Cicindela Circumpicta, To Toxicity From Pyrethroids And Neonicotinoids, And Implications For Ecosystem Function And Species Extinctions, S. Svehla, T. Brosius, Leon Higley, T. Hunt

School of Natural Resources: Faculty Publications

No abstract provided.

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Precise Zircon U-Pb Dating Of The Mesoproterozoic Gawler Large Igneous Province, South Australia, Elizabeth A. Jagodzinski, Anthony J. Reid, James L. Crowley, Claire E. Wade, Stacey Curtis Jan 2023

Precise Zircon U-Pb Dating Of The Mesoproterozoic Gawler Large Igneous Province, South Australia, Elizabeth A. Jagodzinski, Anthony J. Reid, James L. Crowley, Claire E. Wade, Stacey Curtis

Geosciences Faculty Publications and Presentations

The Mesoproterozoic Gawler Range Volcanics and Benagerie Volcanic Suite of the Gawler Craton and Curnamona Province, South Australia, together with associated intrusive magmatism, define an intracontinental, subaerial large igneous province (LIP) preserving an estimated 110 000 km3 of volcanic rock, which hosts one of the world's largest orebodies, the Fe oxide-Cu-Au-U deposit at Olympic Dam, and numerous other related Cu-Au deposits. New high-precision Chemical Abrasion Isotope Dilution Thermal Ionization Mass Spectrometry (CA-TIMS) U-Pb dates on volcanic zircons allow for regional correlations between stratigraphic units of the GRV and BVS, and an understanding of how magmatic styles, temperatures, composition and …

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Causes, Responses, And Implications Of Anthropogenic Versus Natural Flow Intermittence In River Networks, Kendra E. Kaiser Jan 2023

Causes, Responses, And Implications Of Anthropogenic Versus Natural Flow Intermittence In River Networks, Kendra E. Kaiser

Geosciences Faculty Publications and Presentations

Rivers that do not flow year-round are the predominant type of running waters on Earth. Despite a burgeoning literature on natural flow intermittence (NFI), knowledge about the hydrological causes and ecological effects of human-induced, anthropogenic flow intermittence (AFI) remains limited. NFI and AFI could generate contrasting hydrological and biological responses in rivers because of distinct underlying causes of drying and evolutionary adaptations of their biota. We first review the causes of AFI and show how different anthropogenic drivers alter the timing, frequency and duration of drying, compared with NFI. Second, we evaluate the possible differences in biodiversity responses, ecological functions, …

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Elastic Thermobarometry, Matthew J. Kohn, Mattia L. Mazzucchelli, Matteo Alvaro Jan 2023

Elastic Thermobarometry, Matthew J. Kohn, Mattia L. Mazzucchelli, Matteo Alvaro

Geosciences Faculty Publications and Presentations

Upon exhumation and cooling, contrasting compressibilities and thermal expansivities induce differential strains (volume mismatches) between a host crystal and its inclusions. These strains can be quantified in situ using Raman spectroscopy or X-ray diffraction. Knowing equations of state and elastic properties of minerals, elastic thermobarometry inverts measured strains to calculate the pressure-temperature conditions under which the stress state was uniform in the host and inclusion. These are commonly interpreted to represent the conditions of inclusion entrapment. Modeling and experiments quantify corrections for inclusion shape, proximity to surfaces, and (most importantly) crystal-axis anisotropy, and they permit accurate application of the more …

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New Age Constraints On The Break-Up Of Rodinia And Amalgamation Of Southwestern Gondwana From The Choquequirao Formation In Southwestern Peru, Eben Blake Hodgin, Victor Carlotto, Francis A. Macdonald, Mark D. Schmitz, James L. Crowley Jan 2023

New Age Constraints On The Break-Up Of Rodinia And Amalgamation Of Southwestern Gondwana From The Choquequirao Formation In Southwestern Peru, Eben Blake Hodgin, Victor Carlotto, Francis A. Macdonald, Mark D. Schmitz, James L. Crowley

Geosciences Faculty Publications and Presentations

The Choquequirao Formation is a >3 km-thick amphibolite-grade succession that outcrops in the Central Andes of southern Peru. To constrain its age and tectonostratigraphic setting, detrital zircon and metamorphic zircon, titanite, and rutile U–Pb isotopic analyses were conducted. Mantle-derived c. 640 Ma detrital zircons constrain the maximum age of the lower part of the succession and 550–490 Ma metamorphic zircon domains constrain its minimum age. The absence of early Paleozoic detrital zircons suggests that deposition predated early Paleozoic orogenesis in southwestern Gondwana. The close similarity of detrital zircon age spectra to those from sediments deposited on the Arequipa basement suggests …

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Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte Jan 2023

Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte

Browse all Theses and Dissertations

Modern web development has grown increasingly reliant on scripting languages such as PHP. The complexities of an interpreted language means it is very difficult to account for every use case as unusual interactions can cause unintended side effects. Automatically generating test input to detect bugs or fuzzing, has proven to be an effective technique for JavaScript engines. By extending this concept to PHP, existing vulnerabilities that have since gone undetected can be brought to light. While PHP fuzzers exist, they are limited to testing a small quantity of test seeds per second. In this thesis, we propose a solution for …

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Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula Jan 2023

Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula

Browse all Theses and Dissertations

Malware detection is a critical task in ensuring the security of computer systems. Due to a surge in malware and the malware program sophistication, machine learning methods have been developed to perform such a task with great success. To further learn structural semantics, Graph Neural Networks abbreviated as GNNs have emerged as a recent practice for malware detection by modeling the relationships between various components of a program as a graph, which deliver promising detection performance improvement. However, this line of research attends to individual programs while overlooking program interactions; also, these GNNs tend to perform feature aggregation from neighbors …

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Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams Jan 2023

Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams

Browse all Theses and Dissertations

Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …

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Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula Jan 2023

Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula

Browse all Theses and Dissertations

Machine learning techniques utilize training data samples to help understand, predict, classify, and make valuable decisions for different applications such as medicine, email filtering, speech recognition, agriculture, and computer vision, where it is challenging or unfeasible to produce traditional algorithms to accomplish the needed tasks. Unsupervised ML-based approaches have emerged for building groups of data samples known as data clusters for driving necessary decisions about these data samples and helping solve challenges in critical applications. Data clustering is used in multiple fields, including health, finance, social networks, education, and science. Sequential processing of clustering algorithms, like the K-Means, Minibatch K-Means, …

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Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal Jan 2023

Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal

Browse all Theses and Dissertations

Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …

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Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha Jan 2023

Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha

Browse all Theses and Dissertations

Smart cities have emerged to tackle many critical problems that can thwart the overwhelming urbanization process, such as traffic jams, environmental pollution, expensive health care, and increasing energy demand. This Master thesis proposes efficient and high-quality cloud-based machine-learning solutions for efficient and sustainable smart cities environment. Different supervised machine-learning models for air quality predication (AQP) in efficient and sustainable smart cities environment is developed. For that, ML-based techniques are implemented using cloud-based solutions. For example, regression and classification methods are implemented using distributed cloud computing to forecast air execution time and accuracy of the implemented ML solution. These models are …

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Effects Of Phosphorus-Binding Agents On Nutrient Dynamics And A Planktothrix Bloom In A Shallow, Semi-Enclosed Lake Area, Joseph Lee Davidson Jan 2023

Effects Of Phosphorus-Binding Agents On Nutrient Dynamics And A Planktothrix Bloom In A Shallow, Semi-Enclosed Lake Area, Joseph Lee Davidson

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Grand Lake St. Marys is the largest (52 km2) inland lake in Ohio, USA, and receives high nutrient loadings (90th percentile for total nitrogen (N) and phosphorus (P) concentrations in the USA) from a watershed dominated by agricultural row-crops and livestock production. Eutrophication has led to cyanobacterial harmful algal blooms, dominated by non-N2 fixing Planktothrix, that persist year-round, including in winter months. In summer 2020 and 2021, multiple treatments using P-binding agents within a 3.5 ha swimming enclosure were conducted to remove excess dissolved P from the water column. The objective of this study was to examine pre-and-post treatment biogeochemical …

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Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers Jan 2023

Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers

Browse all Theses and Dissertations

Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …

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Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman Jan 2023

Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman

Browse all Theses and Dissertations

Insider threats to information security have become a burden for organizations. Understanding insider activities leads to an effective improvement in identifying insider attacks and limits their threats. This dissertation presents three systems to detect insider threats effectively. The aim is to reduce the false negative rate (FNR), provide better dataset use, and reduce dimensionality and zero padding effects. The systems developed utilize deep learning techniques and are evaluated using the CERT 4.2 dataset. The dataset is analyzed and reformed so that each row represents a variable length sample of user activities. Two data representations are implemented to model extracted features …

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A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham Jan 2023

A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham

Browse all Theses and Dissertations

The Industrial Internet of Things (IIoT) refers to a set of smart devices, i.e., actuators, detectors, smart sensors, and autonomous systems connected throughout the Internet to help achieve the purpose of various industrial applications. Unfortunately, IIoT applications are increasingly integrated into insecure physical environments leading to greater exposure to new cyber and physical system attacks. In the current IIoT security realm, effective anomaly detection is crucial for ensuring the integrity and reliability of critical infrastructure. Traditional security solutions may not apply to IIoT due to new dimensions, including extreme energy constraints in IIoT devices. Deep learning (DL) techniques like Convolutional …

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Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson Jan 2023

Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson

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Automated vehicles pose challenges in various research domains, including robotics, machine learning, computer vision, public safety, system certification, and beyond. These vehicles autonomously handle navigation and locomotion, often requiring minimal user interaction, and can operate on land, in water, or in the air. In the context of aircraft, one specific application is Automated Aerial Refueling (AAR). Traditional aerial refueling involves a "tanker" aircraft using a mechanism, such as a rigid boom arm or a flexible hose, to transfer fuel to another aircraft designated as the "receiver". For AAR, the boom arm may be maneuvered automatically, or in certain instances the …

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Direct Parameter Fitting Of Action Potentials In Skeletal Muscle Cells Which Include Longitudinal Segments, Tyme Suda Jan 2023

Direct Parameter Fitting Of Action Potentials In Skeletal Muscle Cells Which Include Longitudinal Segments, Tyme Suda

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Excitation of skeletal muscle cells triggers a large voltage spike known as an action potential (AP), leading to muscle contraction. Modeling of an AP is typically done using the method developed by scientists Hodgkin and Huxley (HH). In the HH method, voltage and time gated Na+ and K+ ionic currents are simulated, along with a positive “Leak” ionic current and capacitive current. Due to the complexity and the computational time required for simulation, direct fitting of HH parameters to experimental APs has rarely been attempted. A previous thesis at Wright State performed direct fitting for the case of a single …

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Image Schema Decompositions Of The Conceptual Dependency Ingest Primitive: A Study Of Paraphrases, Jamie C. Macbeth, Alexis Kilayko, Zoie Zhao, Sophie Song, Winniw X. Zheng Jan 2023

Image Schema Decompositions Of The Conceptual Dependency Ingest Primitive: A Study Of Paraphrases, Jamie C. Macbeth, Alexis Kilayko, Zoie Zhao, Sophie Song, Winniw X. Zheng

Computer Science: Faculty Publications

One of the hallmarks of the Schank-Minsky Conceptual Dependency Trans-Frames meaning representation system is that it attempts to express complex meanings by building large and complex conceptual structures using a relatively small number of primitives. Recently comparisons of image schemas with Conceptual Dependency primitives revealed ways of possibly reducing the number of primitives while maintaining the expressiveness of the set—an important research goal because it increases the flexibility and richness of the primitive-decomposed structures in a way that better approximates human cognition. Inspired by this prior work, we employ a paraphrase generation system to explore the replacement of the Conceptual …

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An Experiment On The Effects Of Using Color To Visualize Requirements Analysis Tasks, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb Jan 2023

An Experiment On The Effects Of Using Color To Visualize Requirements Analysis Tasks, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb

Computer Science: Faculty Publications

Recent approaches have investigated assisting users in making early trade-off decisions when the future evolution of project elements is uncertain. These approaches have demon-strated promise in their analytical capabilities; yet, stakeholders have expressed concerns about the readability of the models and resulting analysis, which builds upon Tropos. Tropos is based on formal semantics enabling automated analysis; however, this creates a problem of interpreting evidence pairs. The aim of our broader research project is to improve the process of model comprehension and decision making by improving how analysts interpret and make decisions. We extend and evaluate a prior approach, called EVO, …

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